ORIGINAL EMPIRICAL RESEARCH
Customer reactions to downsizing: when and how is satisfaction affected?
Johannes Habel & Martin Klarmann
Received: 18 May 2013 /Accepted: 14 July 2014 /Published online: 19 August 2014 # Academy of Marketing Science 2014
Abstract Organizational downsizing to cut costs frequently creates new, “hidden costs” that neutralize potential increases in productivity. Customer dissatisfaction is such an overlooked downsizing outcome. Using longitudinal data from the American Customer Satisfaction Index (ACSI), Compustat, and a consumer survey this study analyzes satis- faction outcomes of downsizing. It extends research in this domain to B2C markets and explicitly addresses environmen- tal influences on the downsizing–satisfaction link. Results indicate that there is a negative effect of downsizing on customer satisfaction. It is particularly pronounced for com- panies (1) with little organizational slack, (2) with high labor productivity, or (3) in industries with high R&D intensity. Moreover, downsizing has a stronger negative impact on customer satisfaction in product categories with (4) high risk importance and (5) low probability for consumer errors as well as (6) low level of brand consciousness. Furthermore, customer satisfaction mediates the effect of downsizing on financial performance. The results provide an explanation for
why so many downsizing projects fail and what managers can do to prevent adverse effects of downsizing on customer satisfaction and financial performance.
Keywords Customer satisfaction . Organizational downsizing . Firm performance . Panel data analysis
Introduction
In a “Group Strategy Update,” Australian airline Qantas an- nounced on February 26, 2014, plans to cut 5,000 jobs (Qantas 2014). In the same week, the Financial Times report- ed plans that IBM was to reduce its U.S. workforce by 13,000 to 15,000 employees (Waters 2014). Hence, downsizing con- tinues to be one of the most appealing cost-cutting strategies to firms worldwide. Firms typically expect that the layoffs will improve financial performance. For instance, Qantas (2014) explicitly states in their media release that the “long-term goal” of the cost reductions is “the transformation of the Qantas Group for profitable, sustainable growth.”
The importance of downsizing in business practice has motivated many academic studies. In a comprehensive review, Datta et al. (2010) identify four major research streams. Two of them look at environmental and organizational antecedents of downsizing. The other two address its consequences. Of the streams addressing the consequences of downsizing, the first looks at organizational outcomes. Chadwick, Hunter, and Walston (2004, p. 406) summarize: “The general consensus among researchers over the last two decades is that organiza- tional performance is as likely to suffer as it is to improve after downsizing.” The second addresses outcomes at the employee level. Here, Datta et al. (2010, p. 307) conclude that “[d]ownsizing has a significant potential to … disrupt rela- tionship networks, and destroy the trust and loyalty that binds employees and their employers.”
Article note The authors wish to thank Martin Artz, Christian Homburg, Sabine Staritz, participants of the AMA Summer Marketing Educators’ Conference 2012 in Chicago, participants of the second German-French Customer Empowerment workshop 2013 at the Karlsruhe Institute of Technology (KIT), as well as the three anonymous reviewers and Tomas Hult for their valuable insights and comments on earlier drafts of the manuscript.
J. Habel ESMT European School of Management and Technology, Berlin, Germany
M. Klarmann (*) Institute of Information Systems and Marketing (IISM) at the Karlsruhe Institute of Technology (KIT), Zirkel 2, Building 20.21, Room 104, 76131 Karlsruhe, Germany e-mail: [email protected]
J. Habel Ruhr-University Bochum, Bochum, Germany
J. of the Acad. Mark. Sci. (2015) 43:768–789 DOI 10.1007/s11747-014-0400-y
Interestingly, despite Cascio’s (2005, p.45) advice to “think through the potential consequences of restructuring on cus- tomers,” in their review Datta et al. (2010) identify only two papers that examine the effect of downsizing on customers (out of a total of 91). Recently, more research has been conducted in the area. For example, Subramony and Holtom (2012) report that downsizing reduces customer orientation, which translates into a negative effect on customers’ brand perceptions. However, the focus of research lies on the effect of downsizing on customer satisfaction. Table 1 provides an overview.
As shown in Table 1, researchers consistently report nega- tive effects of downsizing on customer satisfaction. That being said, most evidence comes from B2B samples (Lewin 2009; Lewin and Johnston 2008; Lewin et al. 2010; Williams et al. 2011) or samples with a prominent B2B share (Homburg et al. 2012; Wagar 1998). One is from the financial services sector (McElroy et al. 2001).
Hence, previous research in the area is almost exclu- sively based on environments where personal interaction between employees and customers is important. Here, the internal disruption caused by downsizing will be a particular threat to delivering quality. Through processes
like emotional contagion (e.g., Henning-Thurau et al. 2006), negative job satisfaction outcomes may translate into negative customer satisfaction (e.g., Homburg and Stock 2004). However, elsewhere the relationship may be much more complex. While pointing to personal interaction as differentiator, Anderson et al. (1997) find that productivity improvements (which can be achieved through downsizing) are negatively related to customer satisfaction for services, but positively related for manufactured goods. Homburg et al. (2012) find that customer uncertainty following downsizing is much larger if customers interact frequently with their contact employees from the downsizing firm.
We are interested whether the negative effect of downsizing on customer satisfaction generalizes to other contexts. For our sample we draw on American Customer Satisfaction Index (ACSI) data, which is collected for many product categories (e.g., food, appliances, apparel, internet services, cars), where customers interact less with firm employees. We argue that in the industries covered by the ACSI, the effect of downsizing on customer satis- faction is far less intuitive than in B2B environments. In particular, we expect that the degree to which employees
Table 1 Literature on the effect of downsizing on customer satisfaction
Study Context Data Method Findings
Homburg et al. (2012)
B2B/ B2C
Cross-sectional survey data of 109 managers in companies which had undergone downsizing, 2 scenario experiments with students
Regression analyses
Downsizing increases customer uncertainty, which in turn reduces customer satisfaction. The degree of customer uncertainty further depends on how open a company communicates the downsizing vis-à-vis customers, how strong informal ties between customers and customer-contact employees are, and how important products are for customers.
Lewin (2009) B2B Cross-sectional survey data of 560 purchasing professionals evaluating their downsized/non- downsized suppliers
Structural equation models
Purchasing professionals perceive the performance of downsized suppliers as weaker and are less satisfied and loyal.
Lewin et al. (2010)
B2B Cross-sectional survey data of 435 purchasing professionals evaluating their downsized/non- downsized suppliers
Structural equation models
Purchasing professionals perceive the performance of downsized suppliers as weaker and are less satisfied and loyal. The results partly differ for different cultural contexts (United States vs. Europe).
Lewin and Johnston (2008)
B2B Cross-sectional survey data of 560 purchasing professionals evaluating their downsized/non- downsized suppliers
t tests, analyses of variance
Purchasing professionals perceive the performance of downsized suppliers as weaker and are less satisfied and loyal. However, they evaluate the suppliers with medium rates of personnel reduction as better than suppliers with low or high rates of personnel reduction.
McElroy et al. (2001)
B2C Cross-sectional survey data of customers of 31 regional subunits of a financial services company
Correlation analysis
Downsizing is negatively correlated to customer satisfaction.
Wagar (1998) B2B/ B2C
Key informant surveys of 1,907 establishments covering all major sectors of the Canadian economy
Ordered probit estimation
Downsizing reduces employer efficiency, which is calculated as the sum of customer satisfaction, productivity, and product/service quality.
Williams et al. (2011)
B2B Telephone survey data of 534 service customers before and 994 customers after a downsizing event of one specific company
t tests Average customer satisfaction and retention after the downsizing event is significantly lower than customer satisfaction before the downsizing event.
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are a crucial resource to the downsizing firm will affect the downsizing–satisfaction link. For instance, if the firm has enough excess resources (“organizational slack,” Love and Nohria 2005), product quality is less likely to suffer through downsizing and customers might even ben- efit from reduced prices. Hence, customer satisfaction might not be negatively affected by downsizing. To ac- count for effects like this we analyze measures of the downsizing firm’s resources as moderators of the downsizing–satisfaction link.
Moreover, whether customers respond negatively to downsizing will also depend on what they learn of the downsizing (Homburg et al. 2012). Only if they devote a certain amount of time and attention to a product category might they notice quality deficiencies resulting from downsizing. Likewise, for signaling effects (Love and Kraatz 2009) as well as reputational effects of downsizing (Flanagan and O’Shaughnessy 2005; Zyglidopoulos 2005) to affect satisfaction, typically re- quires that customers follow the business press. To account for these effects, we analyze customers’ product category involvement and customers’ purchase criteria as moderators of the downsizing–satisfaction link.
Finally, we are interested whether customer outcomes to downsizing require firms to reconsider downsizing as a man- agement instrument. Therefore, we link customer satisfaction after downsizing to firm performance.
To test our hypotheses, we use data from three sources: (1) As mentioned before, we use ACSI data to measure customer satisfaction. (2) We measure downsizing, firm performance, and the firm’s resource situation using the Computstat data- base. (3) To measure customer product category involvement and customer purchase criteria, we collected survey data from over 1,500 U.S. consumers. As a result we have a longitudinal dataset with data from 1994 to 2007 (before the financial crisis) from over 100 companies, covering more than 150 downsizing events.
Our research makes at least four contributions to the discipline. First, we extend research on customer re- sponses to downsizing from contexts with much em- ployee–customer interaction to less interactive B2C en- vironments. Second, we identify environmental condi- tions related to the downsizing firm’s resources and customer information processing that determine whether downsizing has a negative impact on customer satisfac- tion. Thus, we facilitate predictions regarding potential problems resulting from downsizing. Third, by employing longitudinal data, our study addresses causal- ity issues. Previous findings on satisfaction outcomes to downsizing come almost invariably from cross-sectional designs. Fourth, by linking customer responses to downsizing with financial performance, our study im- proves the understanding of the ambiguous results on
performance implications of downsizing. If customer outcomes depend on contextual factors, this helps un- derstand mixed performance effects of earlier research.
Conceptual framework
Figure 1 depicts our conceptual framework. It is a causal chain leading from downsizing via customer sat- isfaction to financial performance. Twelve contextual factors moderate the link between downsizing and cus- tomer satisfaction.
We define downsizing as major workforce reductions to cut costs and to improve productivity and consequently financial performance (Freeman and Cameron 1993). The typical rationale behind downsizing is to maintain output levels in terms of product and service quality while using less input—that is, labor—thereby cutting costs. However, as companies may find it difficult to maintain quality levels after downsizing, it could affect customer satisfaction, defined as a “cumulative evaluation of a firm’s market offering” (Fornell et al. 1996, p. 8).
A key conceptual idea behind this paper is that the relationship between downsizing and customer satisfac- tion may not always be negative. In environments where customer interaction with firm employees is not com- mon, we expect that two types of contextual factors influence the downsizing–satisfaction link: (1) variables relating to the resources of the firm and (2) variables related to consumer information processing in the buy- ing process. Overall, we expect that downsizing’s nega- tive effect on customer satisfaction will depend on the degree to which the downsized employees are crucial in line with the resource-based view of the firm (Kozlenkova et al. 2014). And in particular, we expect that downsizing’s negative effect on customer satisfac- tion will depend on the degree to which customers can perceive the downsizing and believe it to be important information.
Concerning the downsizing firm’s resources, we con- sider two sets of variables. The first consists of mea- sures of a company’s resource dependency. Prior downsizing research has identified three key factors in this regard: (1) Firms can shield themselves against disruptions of their resources through organizational slack, defined as “resources in excess of those required to produce necessary outputs” (Love and Nohria 2005, p. 1087). (2) Negative downsizing outcomes are more likely if a firm’s labor productivity, defined as the amount of output per unit of labor (Koch and McGrath 1996), is high. (3) Firms are particularly af- fected by negative affect in the workforce if they de- pend on innovation. This is captured by industry R&D
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intensity, defined as average firm expenditures for re- search and development in an industry (Guthrie and Datta 2008).
The second set of resource-related variables concerns the company’s resource history. A key concept of the resource-based view is path dependence (Vergne and Durand 2010). It posits that history is an important factor driving the outcome of firm decisions (Sydow et al. 2009)—or, in other words, “history matters” (Vergne and Durand 2010, p. 741).
Building on the concept of path dependence, we argue that the effect of downsizing on customer satisfaction depends on at least two past events. First, we include prior downsizing, defined as the occurrence of another major workforce reduction that took place before the downsizing. Second, we include prior losses, defined as negative earn- ings before interest and taxes in the year prior to the downsizing.
Concerning consumer information processing, we also consider two sets of variables. The first set consists of different aspects of customers’ product category involvement, as “de- pending on their level of involvement, individual consumers differ in the extent of their decision process and their search for information” (Laurent and Kapferer 1985, p. 41). Drawing on Laurent and Kapferer’s (1985, Kapferer and Laurent 1993) original scale, we distinguish five dimensions of involvement: (1) a customer’s interest in a product category; (2) hedonic
product value, i.e., a customer’s perception that a product category provides pleasure; (3) sign product value, i.e., a customer’s perception that a product expresses his or her self; (4) risk importance, i.e., a customer’s perception that a poor product choice leads to negative consequences; and (5) prob- ability of error, i.e., a customer’s perception that making a poor product choice is likely.
The second set of consumer-related variables comprises customers’ purchase criteria. Whether the disruption of firm resources after downsizing affects customer satisfaction should depend on what drives customer purchase decisions. We propose that two criteria are of particular relevance in this respect: service consciousness, which denotes to what extent customers place value on services vs. goods in a product category, and brand consciousness, which we define as the extent to which customers place value on brands in a product category.
Lastly, customer satisfaction is modeled as driver of company’s financial performance. It is defined as the mone- tary return a company yields on its invested capital.
Hypotheses
As mentioned before, prior research has established that on average, customer satisfaction decreases after downsizing (e.g., Homburg et al. 2012; Lewin et al. 2010). Therefore,
Customer-Related Moderators
Firm-Related Moderators
Customer Satisfaction
Downsizing Financial
Performance
• Organizational Slack H1: + • Labor Productivity H2: - • Industry R&D Intensity H3: -
Resource Dependency
Category Involvement
• Interest H6: - • Pleasure H7: - • Sign H8: + • Risk Importance H9: - • Probability of Error H10: +
Category Purchase Criteria
• Service Consciousness H11: -
• Brand Consciousness H12: +
Resource History
• Prior Downsizing H4: - • Prior Financial Loss H5: +
-a
a Prior research has established an average negative effect (e.g., Homburg et al. 2012; Lewin et al. 2010).
H13: Indirect effect of downsizing on financial
performance via customer satisfaction
Fig. 1 Conceptual framework
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our hypotheses focus on how the contextual factors depicted in Fig. 1 moderate the negative effect of downsizing on customer satisfaction.
Moderator effects pertaining to a firm’s resources
Organizational slack Our first hypothesis is based on the idea that downsizing poses a risk to customer satisfac- tion through the deterioration of customer-related pro- cesses. However, the way these processes are affected may depend on the excess capacity a company has— that is, organizational slack (Love and Nohria 2005). We propose that higher levels of organizational slack lead to less negative (or even positive) effects on pro- cesses and thus customer satisfaction for two reasons. First, slack may act as a buffer (Bourgeois 1981). A firm with little organizational slack may not have re- sources available to cover the process steps of departing employees, which may lead to a reduction in customer satisfaction. However, a “fat” company should be able to cut personnel while maintaining process performance. Hence, the more slack a company has, the less nega- tively downsizing should affect customer satisfaction.
While slack may offer a buffer, it can also be a cost item. High levels of slack may indicate inefficient processes resulting, for example, in delays for customers (Bourgeois 1981). Downsizing may then become the trigger for improv- ing existing business processes (Marks 2003), which may even increase customer satisfaction through superior quality and/or lower prices. Thus, we hypothesize:
H1: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies with little orga- nizational slack.
Labor productivity Our next hypothesis concerns the moder- ating effect of labor productivity. High labor productivity is likely to be associated with high workplace involvement (Guthrie 2001). We argue that two characteristics of high- involvement workplaces aggravate the effect of downsizing on customer satisfaction.
First, employees in high involvement workplaces are likely to perceive their psychological contract with the firm as strong. That is, employees provide high levels of effort, loyalty, and commitment while expecting in- volvement, job security, and fair treatment (e.g., Tsui et al. 1997). Downsizing can be viewed as a fundamen- tal violation of these obligations. As a result, employees may no longer be willing to achieve previous levels of performance, which may in turn reduce customer
satisfaction. In contrast, in companies with lower work- place involvement and thus a weaker psychological contract, downsizing should result in less disastrous effects on the remaining employees.
Second, in high-involvement workplaces employees are typically more involved in and responsible for quality assurance. To this end, firms assign employees the mission of “satisfy[ing] the customer in the best way they can” (Lawler 1992, p. 36). Resulting from this increase in re- sponsibility, the negative effects of downsizing on em- ployees should more easily translate to a deterioration of quality and hence, customer satisfaction. In contrast, in companies with lower workplace involvement, satisfying customers is spread on more shoulders. As a result, com- panies should be able to better buffer their service to customers from internal disruptions after downsizing. Therefore:
H2: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies with high labor productivity.
R&D intensity Several arguments suggest that downsizing inhibits innovation by impairing the different sources of innovation, such as employees, managers, and customers (Tushman and Nadler 1986). First, concerning employee- triggered innovation, it is worth noting that a major bar- rier for innovation is fear: “When people fear for their jobs, their futures, or even for their self-esteem, it is unlikely that they will feel secure enough to do anything but what they have done in the past” (Pfeffer and Sutton 2000, p. 109; see also Hurley and Hult 1998; Tellis 2013). As downsizing triggers fear, uncertainty, and distrust of management among survivors (e.g., Brockner et al. 1994, 2004) it reduces creativity (Amabile and Conti 1999), and it is thus likely to inhibit employee-triggered innovation. Second, concerning manager-triggered innovation, research has shown that the executors of downsizing suffer from the same symptoms as victims and survivors (Gandolfi 2008). Hence, much like employees, managers who play an active role in a downsizing project should forfeit creativity and innovativeness. Additionally, as in practice downsizing pro- jects are often complex and embedded in a larger reorganiza- tion (Cameron et al. 1991), managers should have less time to initiate, manage, or provide input for innovation projects. As a result, manager-triggered innovation during phases of downsizing should decline.
Third, concerning customer-triggered innovation, downsizing has been shown to increase customer uncertainty (Homburg et al. 2012). We argue that the more
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uncertain customers are, the less readily they should share their ideas or insights with a company. As a result, customer-triggered innovation during downsizing phases is likely to decrease.
In sum, there is good reason to believe and even empirical evidence (Dougherty and Bowman 1995) that downsizing disrupts product innovation. However, if employee-triggered, manager-triggered, and customer- triggered innovation decline, a company may lose its ability to meet customers’ future needs, which should lead to decreasing satisfaction. We propose that firms downsizing in industries with high pressure for innova- tion (e.g., hardware and/or software manufacturers such as Apple, Dell, or Microsoft) should be affected by these effects to a larger extent. Thus, we hypothesize:
H3: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies operating in industries with high R&D intensity.
Prior downsizing Customers’ evaluations of products and services strongly depend on the customers’ prior experiences (Oliver 1997). For example, after experiencing a service fail- ure, customers are more receptive to a repeated service failure, which makes service recovery more difficult (e.g., Liao 2007; Maxham and Netemeyer 2002).
This mechanism poses a critical risk to companies’ downsizing practices in use: many companies do not downsize only once, but they complete several rounds of personnel reductions (e.g., Iverson and Pullman 2000; Moore et al. 2004). Hence, if during an earlier round of downsizing product or service quality has deteriorated, customers are likely to be more receptive for any quality problems during later rounds of downsizing. We thus propose:
H4: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies who undergo repeated downsizing.
Prior losses While some companies reduce their workforce proactively to enhance organizational performance, others downsize reactively owing to financial distress (Freeman and Cameron 1993). We expect that customers react differ- ently to these different motivations.
Research shows that customers care about the fairness of corporate activities and are willing to resist doing business with unfair firms (Kahnemann et al. 1986). In this regard, downsizing may act as a strong signal regarding a firm’s “character” (Love and Kraatz 2009). Customers may perceive
downsizing as particularly opportunistic if the company enjoys profits. In contrast, customers may perceive companies that reduce their workforce to counter losses as less unfair and less socially irresponsible. Indeed, the negative effect of downsizing on corporate reputation is smaller if downsizing is a reaction to performance problems of a firm (Love and Kraatz 2009). Therefore:
H5: The negative effect of downsizing on customer satisfac- tion is less pronounced if a company has had financial losses prior to the downsizing.
Moderator effects pertaining to customer information processing
Product category involvement: interest Product categories which score high on the interest dimension provide personal meaning to customers (Laurent and Kapferer 1985). Customers consume these products more consciously and they are thus more likely to notice deteriorations in product or service quality. As stated by Anderson (1994, p. 28) expec- tations and negative disconfirmation are greater when involve- ment is high, as “customers appear more likely to notice ‘things gone right or wrong’” (Anderson 1994, p. 28). Therefore, we propose:
H6: The negative effect of downsizing on customer satisfac- tion is more pronounced in high interest product categories.
Product category involvement: pleasure Product categories which score high on the pleasure dimension of involve- ment provide hedonic value to customers. Mass layoffs are often thought of as especially unpleasant firm ac- tions, causing fear and problems for the concerned employees (Brockner et al. 1994; Greenglass and Burke 2001; Havlovic et al. 1998). Hedonic consump- tion, however, is also motivated by a desire to escape the problems of the everyday world (e.g., Arnold and Reynolds 2012). Therefore, we expect that downsizing will reduce the hedonic appeal of a firm’s products, which will reduce customer satisfaction, especially in high pleasure categories. Thus:
H7: The negative effect of downsizing on customer satisfac- tion is more pronounced in high pleasure product categories.
Product category involvement: sign A high sign value of a product category indicates that customers’ sense of self
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is strongly linked to the products (Kapferer and Laurent 1993; Laurent and Kapferer 1985). Resulting from this nexus, customers should be inclined to maintain positive attitudes toward these products in order to protect their self-esteem (Bradley 1978; Fournier 1998). Hence, if a company in such a product category downsizes, custom- er satisfaction should be less at stake. Empirical evi- dence supports this. For example, Ferraro et al. (2013) find that in light of a critical incident, customers’ atti- tudes toward a brand deteriorate to a lesser extent if their self-concept is linked to the brand. Similarly, Swaminathan et al. (2007) report that when customers’ self-concept is linked to a brand, these customers “tend to discount and counterargue … negative information” (p. 256). Finally, Johar et al. (2010) state that customer identification with a brand “is one of the best forms of insurance against the possibly devastating effects a crisis can have for an organization.” Hence:
H8: The negative effect of downsizing on customer satisfaction is less pronounced in high sign prod- uct categories.
Product category involvement: risk importance We propose that high risk importance within a product category am- plifies the negative effect of downsizing on customer satisfaction. A perception of high risk leads customers to make a more extended product-related search (Dowling and Staelin 1994; Hoyer and MacInnis 2007). In the course of the search, they may be more likely to learn about a downsizing event, with possible adverse effects on corporate image (Love and Kraatz 2009) and thus on customer satisfaction. Furthermore, similar to our reasoning behind H6 and H7, it seems reasonable to assume that customers consume high-risk products more consciously and are thus more likely to notice quality deteriorations. Hence, we propose:
H9: The negative effect of downsizing on customer satisfac- tion is more pronounced in high risk importance product categories.
Product category involvement: probability of error A high probability of error implies that customers find it difficult to evaluate the quality of a product (Kapferer and Laurent 1993; Laurent and Kapferer 1985). This evaluation difficulty poses an opportunity to downsizing companies: if customers cannot easily access the quality of a product, they should be less likely to notice any quality deteriorations (Anderson 1994). Hence, if after a downsizing event a company’s performance
deteriorates, satisfaction should be less affected. We thus propose:
H10: The negative effect of downsizing on customer satis- faction is less pronounced in high probability of error product categories.
Service consciousness If customers are highly conscious of services in a product category, social interaction with frontline employees plays a particularly large role in driving overall customer satisfaction. Two arguments suggest that under these circumstances, downsizing has a more deleterious effect on customer satisfaction.
First, services rely more on their employees to ensure a high-quality delivery to the customer (Anderson et al. 1997). Hence, firms that downsize may no longer have the staff to provide the service effort customers are used to. Indeed, in seeking productivity improvements, service employees have been shown to reduce the time spent with each customer (Olivia and Sterman 2001). Also, downsizing has been shown to reduce customer orientation of service employees (Subramony and Holtom 2012).
Second, if due to a high service consciousness customer satisfaction depends on the social interaction with frontline employees, customer satisfaction should be affected by the emotions of these frontline employees (Henning-Thurau et al. 2006). As downsizing typically negatively affects employee emotions (e.g., Brockner et al. 1986, 1993; DiFonzo and Bordia 1998; Mishra and Spreitzer 1998), customer satisfac- tion should decrease, too. In contrast, if customer satisfaction depends less on social interaction with frontline employees, the negative effect of downsizing on customer satisfaction via employee emotions should be weaker. Thus, we hypothesize:
H11: The negative effect of downsizing on customer satis- faction is more pronounced if customers have a high service consciousness.
Brand consciousness If a product category is characterized by high brand consciousness, customers place particular empha- sis on the brand when purchasing and using products. One of the key reasons for using brands is that it facilitates decision making through lower information costs (e.g., Erdem and Swait 1998). For instance, categorization research (e.g., Cohen and Basu 1987) has found that to save cognitive energy, customers often reapply judgments that they have already stored in memory (e.g., Sujan 1985). To some extent, this can ensure a stability in brand perceptions over time. For example, Brady et al. (2008) find that the better customers’ brand associations, the less negatively customer satisfaction is
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affected by a performance failure. Similarly, Sloot et al. (2005) find that customers are more loyal to such brands in stock-out situations. Hence, we propose:
H12: The negative effect of downsizing on customer satis- faction is less pronounced if customers have a high brand consciousness.
Indirect effect of downsizing on financial performance via customer satisfaction
If customer satisfaction decreases, so may customer loyalty (Lam et al. 2004), repurchase intentions (Mittal and Kamakura 2001), and willingness to pay (Anderson 1996). These behav- ioral effects might translate into decreased revenues (Fornell 1992), higher costs (Reichheld and Sasser 1990), and, thus, lower financial performance (Anderson et al. 2004; Gruca and Rego 2005). Therefore:
H13: Customer satisfaction mediates the link between downsizing and financial performance.
Methodology
Data collection and sample
We assembled a longitudinal dataset to estimate how downsizing affects subsequent customer satisfaction. By using longitudinal instead of cross-sectional data, our study avoids reverse-causality issues. The American Customer Satisfaction Index (ACSI) is an ideal data source for our purposes. It is a customer-based evaluation of the performance of more than 200 firms in over 40 industries and covers about 43 % of the U.S. economy. To develop the index, about 250 telephone interviews are conducted with current customers of each com- pany on a quarterly basis. While customers rate specific goods or services in these interviews, the answers are then mostly aggregated to the company level (Fornell et al. 1996).
As the index scores reach back as far as 1994, they allow for a comprehensive longitudinal analysis. Also, the index exhibits highly reliable measures of customer satisfaction due to consistent surveys, interview execution, sampling, and estimation across firms and time (see Fornell et al. 1996). The population for our study is all companies listed in the ACSI between 1994 and 2007; 1994 is the first year for which ACSI data is available, and 2007 was chosen as the cutoff in order to exclude any exceptional effects of the subprime and debt crisis on firms’ downsizing activities in the following years. As the economic downturn probably started in 2007 (Pol 2012; Vyas 2011; Wu 2011), we provide robustness checks with 2006 as the cutoff year.
We excluded companies that (1) were not incorporated in the United States (e.g., BMW), or (2) provided customer satisfaction data on the brand instead of the firm level (e.g., Chrysler Corporation, for which the ACSI differentiates be- tween Chrysler and Dodge-Plymouth). We then matched these companies with financial data and employment information of Standard and Poor’s Compustat, excluding companies that (3) were not unequivocally listed on Compustat, or (4) did not provide four consecutive years of complete data. This proce- dure resulted in a panel of 110 companies and 710 firm years. Table 2 shows the sample composition. Differences in the sample size and composition compared to other studies (e.g., Ittner et al. 2009; Tuli and Bharadwaj 2009) are due to our more selective inclusion criteria and our requirement of four consecutive years of complete data.
In addition, we collected survey data to measure the customer- related moderators (product category involvement and purchase criteria). In 2013 we surveyed 1,522 U.S. residents between 18 and 65 years of age. Respondents were acquired through an online panel provider. The sample is representative for the U.S. population in terms of gender, income, and region (p>0.10). Representativeness in terms of age (p<0.05) and education (p<0.001) could not be established, which we attribute to the use of an online survey. Table 3 shows the sample composition.
After agreeing to participate, respondents were randomly assigned to one of the 29 product categories in our sample and asked to evaluate these product categories through an online survey. For each product category, we obtained at least 50 responses. To match the survey data to the individual compa- nies in our dataset, we used the Standard Industrial Classification (SIC) code as the primary key.
Measures
Downsizing We operationalize downsizing as a dummy var- iable indicating a reduction in the number of employees of at least 5 % as observed in Compustat. This approach is consis- tent with many other studies: a dichotomous measure of downsizing is easier to interpret than a continuous measure (Ahmadjian and Robinson 2001) and is thus frequently used (e.g., Bruton et al. 1996; Love and Nohria 2005). Also, an extensive literature review shows 5 % to be a predominant cutoff point (e.g., Cascio, Young, and Morris 1997; Guthrie and Datta 2008). Studies argue that with lower cutoffs, inves- tigators might erroneously interpret unintentional attrition as downsizing, whereas with higher cutoffs, they might overlook important downsizing events (Ahmadjian and Robinson 2001; Cascio et al. 1997).
Researchers also use press announcements to identify downsizing (e.g., Love and Nohria 2005; Nixon et al. 2004; Worrell et al. 1991). Press announcements might be the more
J. of the Acad. Mark. Sci. (2015) 43:768–789 775
valid indicator of downsizing, because mere employment changes may be the result of, for example, spin-offs or out- sourcings. Therefore, we searched the ProQuest database re- cords of the Wall Street Journal and several other wire ser- vices for announcements of layoffs for the firms in our sample. We then constructed a second, narrower downsizing dummy that was set to 1 if employment decreased by at least 5 % and a corresponding announcement was available. We identified 105 downsizing events based on this process. However, as our model requires data availability for the downsizing year as well as the 3 years before, we were only able to use 54 downsizing events. We test our hypotheses using both operationalizations of downsizing.
Customer satisfaction We measure customer satisfaction through the change in customer satisfaction as a firm’s ACSI score in the year after downsizing minus the firm’s ACSI score in the year of downsizing. This way, we analyze how downsizing changes satisfaction.
Resource dependency We measure organizational slack as the ratio of selling, general, and administrative (SG&A) expenses to total sales minus the mean industry SG&A level (sales-weighted) in the year before downsizing. This approach is consistent with other studies (e.g., Love and Nohria 2005; Wiseman and Bromiley 1996). Labor productivity is measured as total sales divided by the
Table 2 Sample composition of the companies in our sample A. Industries Percent of firm-years
with prior downsizing (n=153)
Percent of total firm- years (n=710)
Consumer staples 39 44
Consumer discretionary 27 30
Information technology 8 8
Financials 5 5
Energy 10 5
Telecommunication 4 4
Industrials 7 4
Health care 0 1
B. Revenue Percent of firm-years with prior downsizing (n=153)
Percent of total firm- years (n=710)
< $1 billion 3 2
$1–5 billion 24 19
$5–10 billion 19 21
$10–50 billion 48 50
$50–100 billion 6 7
> $100 billion 0 1
C. Employees Percent of firm-years with prior downsizing (n=153)
Percent of total firm- years (n=710)
< 10,000 18 10
10,000–50,000 39 39
50,000–100,000 21 19
100,000–200,000 15 20
> 200,000 8 11
D. Downsizing percentage
Percent of firm-years with downsizing (n=153)
5–10 % 54
10–15 % 19
15–20 % 10
20–50 % 15
50–100 % 2
776 J. of the Acad. Mark. Sci. (2015) 43:768–789
number of employees minus the corresponding industry aver- age in the year before downsizing (Anderson et al. 1997). For industry R&D intensity, we first calculated the average ratio of research and development expenses to total sales for all companies within every three-digit SIC code. We then averaged these ratios over the year before, the year of, and the year after the downsizing event (Guthrie and Datta 2008).
Resource history Prior downsizing is a dummy indicating if in any of the 3 years prior to our focal downsizing event, the company had already downsized at least once. Using a three- year time horizon is consistent with Love and Nohria (2005). Prior financial loss is a dummy indicating if in the year before downsizing, a company had negative EBIT.
Product category involvement We measure the five dimen- sions of product category involvement with items based on Kapferer and Laurent (1993). The exact wording is reported in Table 4. We assessed our measures using a confirmatory factor analysis. Across all product categories, composite reliabilities (CR) and average variance extracted (AVE) exceed recom- mended threshold levels (Bagozzi and Yi 1988) for all in- volvement dimensions (interest: AVE = 0.74; CR = 0.85; pleasure: AVE = 0.84; CR = 0.94, sign: AVE = 0.89; CR =
0.96, risk importance: AVE = 0.76; CR = 0.87, probability of error: AVE =0.77; CR = 0.93). We also find good psycho- metric properties if we analyze the constructs separately for each product category in our data. The only exception is the composite reliability of the interest dimension for cookies and crackers (CR = 0.69), which is slightly smaller than the recommended threshold of 0.7.
Product category purchase criteria We measure these criteria using self-developed scales (items are listed in Table 4). Again, psychometric properties are good (service consciousness: AVE = 0.88; CR = 0.96 and brand consciousness: AVE = 0.71; CR = 0.91) for the overall sample as well in a separate analysis of each product category.
Control variables As we explain in more detail in the next section, we rely on a fixed effects estimator for the model estimation. A key advantage of this method is that omitted variables bias is strongly reduced (Baltagi 2008). In particular, the model structure already accounts for the influence of firm- specific variables that stay constant over the observed time period. Therefore, we control only for firm size in our model by including total assets and employees (Nixon et al. 2004). Table 4 gives an overview of our measures. Table 5 presents descriptive statistics and correlations.
Table 3 Sample composition of the national survey
a According to 2012 data of the U.S. Census Bureau, see http:// www.census.gov b Without population under 18 and over 65 years of age
A. Gender Percent of survey sample Percent of populationa
Male 49 49
Female 51 51
B. Age Percent of survey sample Percent of populationa,b
18 to 29 24 26
30 to 49 43 42
50 to 65 34 31
C. Education Percent of survey sample Percent of populationa
No college 25 43
Some college, but no degree 29 29
College graduate 27 18
Graduate school 19 10
D. Household Income Percent of Survey Sample Percent of Populationa
< $40 K 40 40
$40 K to $80 K 31 29
> $80 K 29 31
E. Region Percent of Survey Sample Percent of Populationa
Northeast 19 19
Midwest 23 23
West 22 22
South 36 36
J. of the Acad. Mark. Sci. (2015) 43:768–789 777
Model specification and estimation
Model specification To test the effect of downsizing on cus- tomer satisfaction, we specify a model which includes all
independent and moderating variables. Furthermore, the mod- el includes interaction terms between downsizing and all moderators:
ChangeinCustomerSatisfactiont;i ¼ β1Downsizingt−1;i þ β2OrganizationalSlackt−2;i þ β3LaborProductivityt−2;i þ β4IndustryR&DIntensityt;i þ β5PriorDownsizingt−2;i þ β6PriorFinancialLosst−2;i þ β7TotalAssetst;i þ β8Employeest;i þ β9Downsizingt−1;i�OrganizationalSlackt−2;i þ β10Downsizingt−1;i�LaborProductivityt−2;i þ β11Downsizingt−1;i�IndustryR&DIntensityt;i þ β12Downsizingt−1;i�PriorDownsizingt−2;i þ β13Downsizingt−1;i�PriorFinancialLosst−2;i þ β14Downsizingt−1;i�Interesti þ β15Downsizingt−1;i�Pleasurei þ β16Downsizingt−1;i�Signi þ β17Downsizingt−1;i�RiskImportancei þ β18Downsizingt−1;i�ProbabilityofErrori þ β19Downsizingt−1;i�ServiceConsciousnessi þ β20Downsizingt−1;i�BrandConsciousnessi þ αi þ εt;i
where β denotes the regression coefficients, t indicates the year, and i the individual company. αi is an individual (company-specific) error. It accounts for the nested structure of our dataset, where years are nested in firms. εt,i stands for an idiosyncratic (residual) error that may vary over both compa- nies and time. For interpretation purposes, we centered all moderators by subtracting the mean of each variable from its original value (Irwin and McClelland 2001).
The model explains customer satisfaction in a certain year (t) through downsizing in the period before (t-1) to rule out confounding effects and thus allow for causal conclusions. The firm-specific moderators that vary over time (i.e., organi- zational slack, labor productivity, prior downsizing, and prior financial loss) were measured prior to the downsizing event. We chose to measure them in the year before the downsizing event because they could be confounded with the downsizing event itself (e.g., downsizing reduces organizational slack). It is worth noting that this model requires us to have complete data for five consecutive years, ranging from customer satis- faction in t via downsizing in t-1 back to prior downsizing in any of the 3 years before the focal downsizing event, i.e., back to t-4 (see description of measurement above).
Estimation method It is important to emphasize again that our dataset contains multiple observations for each firm. Put dif- ferently, our dataset is of a hierarchical structure in which years are nested in companies. This nested structure often leads to violations of the assumptions of ordinary least squares (OLS), in particular if the individual error αi is not identical across all firms, if it is correlated with the regressors, or if the
idiosyncratic error εt,i is serially correlated or is heteroskedastic (e.g., Baltagi 2008; Boulding and Staelin 1995). To check whether these violations apply to our dataset, we conducted a series of standard statistical tests (e.g., Baltagi 2008; Wooldridge 2002). Indeed, Breusch and Pagan’s (1980) Langrange multiplier test indicated that there is a company- specific intercept in our data (p<0.001), and the Breusch- Godfrey test (see Baltagi and Li 1995) indicated serial corre- lation in the error term εt,i (p<0.001). We therefore resorted to two estimation methods that produce consistent results under these conditions. First, we estimated a fixed effects model with robust standard errors using STATA’s xtreg procedure (Cameron and Trivedi 2010, p. 335). Second, we deployed a fixed effects feasible generalized least squares estimator (Wooldridge 2002, p. 247), using the statistical software package R (procedure pggls, for details see Croissant and Millo 2008). These methods treat the issue of serial correlation through different mechanisms, but they are similar in the way they deal with the company-specific intercept through so-called fixed effects. In particular, they discard any company-specific (i.e., fixed) effect by subtracting the average over time from each variable. This is a standard econometric method when dealing with data structured like ours. It has also frequently been used in studies dealing with downsizing (e.g., Love and Kraatz 2009; Love and Nohria 2005) as well as ACSI data (e.g., Anderson and Mansi 2009; Grewal et al. 2010).
It is worth mentioning that fixed-effects procedures cannot estimate effects of time-invariant independent variables
778 J. of the Acad. Mark. Sci. (2015) 43:768–789
(Baltagi 2008; Wooldridge 2002). Therefore, our regres- sion equation depicted above and our results in the next section do not contain main effects for our time-invariant moderators (interest, pleasure, sign, risk importance, probability of error, service consciousness, and brand consciousness).
Moderated effects of downsizing on customer satisfaction
We first present the results for downsizing being measured as an employment decrease of at least 5 % as observed in
Compustat regardless of whether a downsizing announcement was available. Table 6 shows our estimation results.
As described previously, we present models using different cutoff years and estimators. First, we turn to the results obtained through a fixed effects estimator with clustered errors (models 1 and 2). Before interpreting the results for our hypotheses, we note that the main effect of downsizing is significantly negative both for the cut- off 2007 (β1=−0.97, p<0.01) and 2006 (β1=−0.96, p<0.01). Thus, on average, downsizing has a negative effect on customer satisfaction.
Table 4 Measures and data sources for the customer satisfaction model
Measure Operationalization Data sources
Change in customer satisfaction
Year-to-year change of the American Customer Satisfaction Index (ACSI) by the National Quality Research Center
ACSI
Downsizing (broad definition)
Dummy indicating if the number of employees has decreased by at least 5 % Compustat
Downsizing (narrow definition)
Dummy indicating if both press announcement and employee number indicate workforce reduction of at least 5 %
Compustat, business press
Organizational slack Ratio of selling, general and administrative expenses to total sales (relative to industry average)
Compustat
Labor productivity Ratio of total sales to number of employees (relative to industry average) Compustat
Industry R&D intensity Three-year mean of the average ratios of R&D expenditures to total sales for all companies belonging to a three-digit SIC industry
Compustat
Prior downsizing Dummy indicating if the downsizing dummy (see above) is 1 in any of the three prior years
Compustat
Prior financial loss Dummy indicating if earnings before interest and taxes are negative Compustat
Interesta •What [products] I choose is extremely important to me. •I’m really very interested in [products]. •I couldn’t care less about [products]. (R)b
National survey
Pleasurea •I really enjoy buying [products]. •Whenever I buy [products], it’s like giving myself a present. •To me, it is quite a pleasure to buy [products].
National survey
Signa •You can tell a lot about a person from the [products] he or she chooses. •The [products] a person chooses says something about who they are. •The [products] I choose reflects the sort of person I am.
National survey
Risk importancea •It doesn’t matter too much if one makes a mistake buying [products]. (R)b
•It’s very irritating to choose not the right [products]. •I should be annoyed with myself if it turned out I’d made the wrong choice of [products].
National survey
Probability of errora •I always feel rather unsure about what [products] to pick. •When you choose [products], you can never be quite sure it was the right choice or not. •Choosing [products] is rather difficult. •When you choose [products], you can never be quite certain about your choice.
National survey
Service consciousnessa
When it comes to [products], … •… good customer service is very important to me. •… I place very high value on customer service. •… I consider a very good customer service to be crucial.
National survey
Brand consciousnessa
When it comes to [products], … •… the brand is very important to me. •… I care about the brand very much. •… I choose among my preferred brands only. •… there are certain brands which I would not consider for my choice.
National survey
Total assets Total assets in $100,000 Compustat
Employees Number of employees in 1,000 Compustat
(R) Item reverse coded a 7-point Likert scales anchored “fully disagree” to “fully agree” b Item dropped due to low factor loading
J. of the Acad. Mark. Sci. (2015) 43:768–789 779
T ab
le 5
D es cr ip ti v e st at is ti cs
an d co rr el at io n s fo r th e cu st o m er
sa ti sf ac ti o n m o d el
V ar ia b le
V 1
V 2
V 3
V 4
V 5
V 6
V 7
V 8
V 9
V 1 0
V 11
V 1 2
V 1 3
V 1 4
V 15
V 1 6
V 1 7
V 1 8
M ai n v ar ia b le s
V 1 : d o w n si zi n g (b ro ad ) (t -1 )
V 2 : d o w n si zi n g (n ar ro w ) (t -1 )
0 .5 5
V 3 : ch an g e in
cu st o m er
sa ti sf ac ti o n (t )
−0 .0 4
−0 .0 8
R es o u rc e d ep en d en cy
V 4 : o rg an iz at io n al sl ac k (t -2 )
0 .0 2
0. 0 2
0 .0 4
V 5 : la b o r p ro d uc ti v it y (t -2 )
0 .0 2
−0 .0 4
0 .0 1
−0 .3 5
V 6 : in d u st ry
R & D in te n si ty
(t )
0 .0 2
0. 1 0
−0 .0 4
−0 .1 6
0 .0 2
R es o u rc e h is to ry
V 7 : p ri o r d o w n si zi n g (b ro ad ) (t -2 )
0 .2 0
0. 1 3
−0 .0 4
0 .0 3
0 .0 8
−0 .0 4
V 8 : p ri o r d o w n si zi n g (n ar ro w ) (t -2 )
0 .0 9
0. 1 8
−0 .0 2
0 .0 0
0 .0 1
0 .0 6
0 .5 2
V 9 : p ri o r fi n an ci al lo ss
(t -2 )
0 .2 3
0. 2 6
−0 .0 0
0 .1 2
0 .0 3
0 .1 0
0 .1 7
0 .3 1
C at eg o ry
in v o lv em
en t
V 1 0 : in te re st
−0 .0 4
−0 .0 5
0 .0 4
0 .1 1
−0 .0 3
−0 .0 5
−0 .1 2
−0 .0 7
−0 .0 6
V 11 : p le as u re
−0 .0 7
−0 .0 7
0 .0 5
0 .0 9
−0 .0 4
−0 .0 4
−0 .1 7
−0 .0 8
0 .0 0
0 .7 5
V 1 2 : si g n
−0 .0 6
−0 .1 1
0 .0 6
0 .0 9
−0 .0 1
−0 .1 9
−0 .1 2
−0 .1 2
−0 .1 5
0 .7 8
0 .7 8
V 1 3 : ri sk
im po rt an ce
−0 .0 2
0. 0 6
−0 .0 2
0 .0 2
−0 .0 2
0 .2 8
−0 .0 4
0 .1 3
0 .1 6
0 .4 5
0 .2 5
0 .2 5
V 1 4 : P ro b ab il it y o f E rr o r
−0 .0 0
0. 0 9
−0 .0 5
−0 .1 8
0 .0 3
0 .3 6
0 .0 2
0 .1 9
0 .2 1
−0 .1 1
−0 .1 6
−0 .2 5
0 .6 5
C at eg or y p ur ch as e cr it er ia
V 1 5 : se rv ic e co n sc io u sn es s
−0 .0 4
0. 0 1
−0 .0 3
−0 .0 1
−0 .0 5
−0 .0 4
−0 .1 1
0 .0 4
0 .0 7
0 .3 0
0 .2 7
0 .0 2
0 .3 0
0 .4 4
V 1 6 : b ra n d co n sc io u sn es s
−0 .0 5
−0 .1 1
0 .0 7
0 .1 5
−0 .0 1
0 .2 0
−0 .1 4
−0 .1 7
0 .0 5
0 .5 7
0 .5 6
0 .3 4
0 .3 2
−0 .1 3
0 .1 4
C o n tr o ls
V 1 7 : to ta l as se ts (t )
−0 .0 5
−0 .0 0
0 .0 5
−0 .0 4
0 .0 1
0 .0 1
0 .0 1
0 .0 7
−0 .0 5
−0 .1 0
−0 .3 1
−0 .2 0
0 .0 8
0 .2 8
0 .2 0
−0 .1 7
V 1 8 : em
p lo y ee s (t )
−0 .1 1
−0 .0 9
0 .0 2
−0 .0 9
−0 .0 9
−0 .0 8
−0 .1 3
−0 .0 7
−0 .1 6
0 .1 0
0 .1 0
0 .0 0
−0 .1 8
−0 .0 9
0 .3 5
0 .1 1
0 .2 2
M ea n
– a
– a
−0 .1 8
−0 .0 1
0 .0 0
0 .3 3
– a
– a
– a
4 .7 7
4 .1 6
4 .0 6
4 .1 1
3 .4 1
5 .1 4
4 .5 2
0 .4 3
8 2 .2 5
S ta n d ar d d ev ia ti o n
– a
– a
2 .3 7
0 .0 8
0 .2 2
0 .8 4
– a
– a
– a
0 .6 1
0 .7 0
0 .6 5
0 .4 1
0 .4 0
0 .5 1
0 .3 4
1 .5 8
8 6 .5 6
N o te : p < 0 .0 5 fo r |r |> 0 .0 8 ; p < 0 .0 1 fo r |r |> 0 .1 0 ; p < 0 .0 0 1 fo r |r |> 0 .1 3 (b as ed
on tw o -t ai le d te st s)
a D um
m y v ar ia bl e
780 J. of the Acad. Mark. Sci. (2015) 43:768–789
In H1 we predict that organizational slack positively mod- erates the effect of downsizing on customer satisfaction. The corresponding interaction term is positive and significant both for the cutoff 2007 (β9=6.17, p<0.05) and 2006 (β9=6.55, p<0.05), providing support for H1
Hypothesis 2 posits that labor productivity negatively mod- erates the downsizing–satisfaction link. In support of H2, the interaction between labor productivity and downsizing has a significant negative effect using both the cutoff 2007 (β10= −1.90, p<0.01) and 2006 (β10=−1.83, p<0.01).
H3 suggests that industry R&D intensity negatively mod- erates the downsizing–customer satisfaction chain. This hy- pothesis is strongly supported both for the cutoff 2007 (β11= −0.82, p<0.001) and 2006 (β11=−1.00, p<0.001).
In H4 we propose that downsizing has a more deleterious effect on change in customer satisfaction for firms that under- go repeated downsizing. While, consistent with this proposi- tion, the interaction term between downsizing and prior downsizing is negative, it is insignificant both for the cutoff 2007 and 2006. Hence, H4 is not supported by the data. Similarly, we do not find support for H5: the sign of the interaction coefficient between downsizing and prior financial loss is positive as proposed, but insignificant.
Regarding product category involvement, we do not find support for H6 through H8 as the interaction coefficients are insignificant. Hypotheses 9 and 10 are supported. In line with our propositions, the interaction coefficient between downsizing and risk importance is significantly negative
Table 6 Customer satisfaction model (Broad Downsizing Operationalization)
Dependent variable: change in customer satisfaction (t)
Model 1 Model 2 Model 3 Model 4
Fixed effects with clustered errorsa
Fixed effects with clustered errorsa
Fixed effects GLSb
Fixed effects GLSb
Variable Cutoff year 2007 Cutoff year 2006 Cutoff year 2007 Cutoff year 2006
Downsizing (t-1) −0.97 (0.32)** −0.96 (0.32)** −1.00 (0.17)*** −1.29 (0.24)*** Organizational slack (t-2) 1.10 (1.41)n.s. 0.08 (1.79)n.s. −1.56 (0.59)** 1.25 (1.33)n.s.
Labor productivity (t-2) 1.02 (0.73)n.s. 0.55 (0.92)n.s. −0.64 (0.25)** 0.14 (0.60)n.s.
Industry R&D intensity (t) −0.17 (0.11)n.s. −0.11 (0.13)n.s. −0.30 (0.04)*** −0.14 (0.09)n.s.
Prior downsizing (t-2) −0.09 (0.17)n.s. 0.00 (0.19)n.s. −0.68 (0.08)*** −0.19 (0.11)n.s.
Prior financial loss (t-2) 1.24 (0.89)n.s. 1.88 (0.83)* 0.70 (0.48)n.s. 2.30 (0.60)***
Total assets (t) 0.01 (0.11)n.s. 0.11 (0.07)n.s. 0.07 (0.02)*** 0.19 (0.04)***
Employees (t) 0.00 (0.00)n.s. −0.00 (0.00)n.s. −0.00 (0.00)n.s. −0.00 (0.00)n.s.
Downsizing (t-1) × organizational slack (t-2) H1:+ 6.17 (2.71)* 6.55 (3.02)* −1.96 (1.02)n.s. 6.00 (2.43)* Downsizing (t-1) × labor productivity (t-2) H2:− −1.90 (0.66)** −1.83 (0.61)** −5.39 (0.70)*** −1.98 (0.70)** Downsizing (t-1) × industry R&D intensity (t) H3:− −0.82 (0.18)*** −1.00 (0.19)*** −0.28 (0.09)** −1.29 (0.18)*** Downsizing (t-1) × prior downsizing (t-2) H4:− −0.14 (0.42)n.s. −0.21 (0.44)n.s. −0.28 (0.15)n.s. 0.42 (0.31)n.s.
Downsizing (t-1) × prior financial loss (t-2) H5:+ 1.14 (1.19)n.s. 1.14 (1.08)n.s. 2.80 (0.62)*** 1.59 (0.84)n.s.
Downsizing (t-1) × interest H6:− 0.16 (0.74)n.s. 0.89 (0.92)n.s. 1.77 (0.31)*** 1.59 (0.62)* Downsizing (t-1) × pleasure H7:− -0.41 (0.59)n.s. -0.50 (0.63)n.s. −0.09 (0.32)n.s. −1.26 (0.51)* Downsizing (t-1) × sign H8:+ 0.81 (0.67)n.s. 0.41 (0.73)n.s. 0.51 (0.28)n.s. 0.82 (0.55)n.s.
Downsizing (t-1) × risk importance H9:− −2.48 (0.89)** −2.85 (1.08)** −2.93 (0.32)*** −3.24 (0.75)*** Downsizing (t-1) × probability of error H10:+ 3.92 (1.10)*** 4.51 (1.30)*** 1.94 (0.49)*** 4.44 (0.90)***
Downsizing (t-1) × service consciousness H11:− −0.51 (0.58)n.s. −0.94 (0.71)n.s. −1.73 (0.29)*** −0.91 (0.49)n.s.
Downsizing (t-1) × brand consciousness H12:+ 1.77 (0.84)* 1.78 (0.99)n.s. 1.46 (0.29)*** 1.99 (0.62)**
Year dummiesc Included Included Included Included
Number of firms 110 105 110 105
Number of firm-years 710 637 710 637
Number of downsizing events 153 139 153 139
R2 (within) 0.15 0.17 0.08 0.24
n.s. p>0.05; * p<0.05; ** p<0.01; *** p<0.001 (based on two-tailed tests)
Notes: Unstandardized parameters are shown. Standard errors are in parentheses a Estimated with STATA (version 10.1), procedure xtreg b Estimated with R (version 3.0.2), procedure pggls (version 1.4–0) c Dummy variable for each year was included in the models in order to account for fixed effects on the time level
J. of the Acad. Mark. Sci. (2015) 43:768–789 781
(cutoff 2007: β17=−2.48, p<0.01; cutoff 2006: β17=−2.85, p<0.01), whereas the interaction coefficient between downsizing and probability of error is significantly positive (cutoff 2007: β18=3.92, p<0.001; cutoff 2006: β18=4.51, p<0.001).
Regarding product category purchase criteria, there is no evidence in support of H11. Service consciousness does not have a significant interaction effect with downsizing. Concerning H12, brand consciousness positively moderates the effect of downsizing on change in customer satisfaction for the cutoff 2007 (β20=1.77, p<0.05). When choosing the cutoff 2006, the interaction effect is insignificant. Hence, support for H12 is limited.
Models 3 and 4 are estimated using the fixed effects GLS method as an alternative estimator. Here, in line with models 1 and 2, the moderating effects of labor productivity (H2), industry R&D intensity (H3), risk importance (H9), and prob- ability of error (H10) are supported, whereas the moderating effects of prior downsizing (H4) and sign (H8) are not. The strong consistency across all four models raises our confi- dence in the validity of these findings. Moreover, in line with model 1, the moderating effect of brand consciousness is supported. The interaction effect of organizational slack is significant in model 4 but insignificant in model 3. Hence, seeing that the interaction coefficients of brand consciousness and organizational slack are significant in three out of four models, in summary we find some support for H1 and H12. Lastly, H5, H6, H7, and H11 are partly supported in at least one of models 3 and 4, making our result in their regard somewhat inconclusive.
To gain further insight into the nature of the interaction effects, we plotted them based on model 1 in Table 6. Following Guthrie and Datta (2008), we divided our data into two groups based on whether a firm had downsized in the previous period. In each group, we calculated means and stan- dard deviations of all variables. We then assigned the moderator a value of one standard deviation above and below its mean while constraining all other variables to their means. We then used these values to predict customer satisfaction. Figure 2 shows the plots, which all reveal that downsizing has a negative effect on the change of customer satisfaction. This negative effect is however particularly pronounced for disadvantageous configurations of the moderators, i.e., for low organizational slack, high labor productivity, high industry R&D intensity, high risk importance, low probability of error, and low brand consciousness. The negative effect is alleviated or neutralized for advantageous configurations of the moderators.
Robustness checks for different operationalizations of downsizing
We follow earlier research by considering employee reduc- tions of 5 % or more as downsizing. In this section, we
describe two tests to check whether our results are stable when using other operationalizations. First, we estimated our model a second time with a narrower downsizing dummy. It was set to 1 only if workforce reductions of at least 5 % were accom- panied by a corresponding press announcement. Table 7 shows the results. As changing the operationalization reduces the number of observed downsizing events to 54, we are mainly interested whether hypothesized effects have the same sign across operationalizations. This is the case. Moreover, despite the small sample, three of the hypothesized interaction effects (with R&D intensity, risk importance, and probability error) are statistically significant. Surprisingly, contrary to H6, interest has a significant positive interaction effect for both estimation methods.
Second, we tested the stability of the results when using other values than 5 % as a cutoff-point for downsizing events. We find highly consistent results for cutoff points of 4 to 7 %. Moreover, for a 3 % cutoff point, many effects just barely lose their statistical significance. This might indicate that at a 3 % cutoff point, the effects of downsizing dilute somewhat. Despite that, overall we are confident that our results are stable for cutoff-points ranging from 3 to 7 %. For more extreme cutoff points (e.g., 1, 10, or 15 %) the pattern of results is visibly affected.
Indirect effect of downsizing on financial performance via customer satisfaction
To examine our proposition that customer satisfaction medi- ates the effect of downsizing on financial performance, we conducted a mediation analysis. Therefore, we specified a model with change in financial performance as the dependent variable, operationalized as return on assets (ROA) in t minus ROA in t-1. ROA is calculated as the ratio of earnings before interest, taxes, depreciation and amortization to total assets. This operationalization is widely used in downsizing research (e.g., Bruton et al. 1996; Guthrie and Datta 2008; Love and Nohria 2005). As Cascio, Young, and Morris (1997: 1177) argue: “Any changes in the performance of a firm that result from employment downsizing should show up in the ROA measure.” As independent variables, we included our prior independent variables lagged by one additional period. We further included organizational slack and labor productivity in t as additional control variables.
Table 8 shows the results. Model 1 reports the effect of downsizing on change in financial performance without controlling for change in customer satisfaction. The effect is not statistically significant. In model 2, we added change in customer satisfaction in t-1 as an independent variable. Again, we find no effect of downsizing on fi- nancial performance, whereas—consistent with much ear- lier research (e.g., Anderson et al. 1994; Anderson et al. 2004)—change in customer satisfaction has a positive
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effect (βCS→ROA=0.17, p<0.05). As a robustness check, model 3 shows how the absolute level of customer satis- faction (instead the year-to-year change) affects return on assets. We find a strong positive effect (βCS→ROA=0.57, p<0.001), which substantiates our finding that customer satisfaction is positively linked to financial performance.
The fact that downsizing reduces customer satisfaction and that customer satisfaction drives financial perfor- mance points to a potential indirect effect of downsizing on financial performance via customer satisfaction in line with H13. To test H13, we conducted the Sobel test (Sobel 1982), finding a significant effect (βDS→CS × βCS→ROA=−0.17, p<0.05). Hence, in support of H13 downsizing reduces customer satisfaction, which then re- duces financial performance.
Table 9 analyzes this indirect effect for unfavorable condi- tions of our supported moderators. Following Spiller et al. (2013), we estimated the simple effect of downsizing on satis- faction for different levels of the moderators and then repeated the Sobel test. The negative indirect effect of downsizing on performance via satisfaction becomes stronger for companies with low slack or high labor productivity and in industries with high R&D intensity
as well as in product categories that customers perceive as risky but have a low probability of error.
Discussion
Research implications
Downsizing has been a popular managerial instrument for almost 30 years. However, only recently have researchers started to look at customer outcomes of downsizing. Our re- search contributes to this new research stream in several ways.
Previous research on customer outcomes of downsizing has focused on B2B markets (e.g., Lewin 2009; Lewin and Johnston 2008; Lewin et al. 2010). We extend the field by looking at B2C markets. Here, we also find that downsizing reduces customer satisfaction. We argue that this finding is less intuitive than it maybe sounds. In B2B markets there is typically a strong degree of personal interaction between customers and employees of the downsizing supplier. In con- trast, in most B2C markets, consumers have little to no per- sonal contact with firm employees. As a result, in many product categories consumers seem to be indifferent to
Fig. 2 Interaction plots
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employee working conditions. For instance, despite the highly publicized problems of workers in one of Apple’s supplier firms (e.g., Mishkin 2013), in October 2013 Apple CEO Tim Cook reported that Apple was winning in terms of customer satisfaction (Bradshaw 2013).
In light of this potential consumer indifference to the way products and services are produced, the question becomes: When does downsizing affect satisfaction? Our findings indicate that consumers mostly respond to downsizing if it results in noticeable deteriorations of product performance. Only in firms with resource con- figurations that make them especially vulnerable to losses of human capital (high R&D intensity, high labor productivity, little slack), does downsizing affect
customer outcomes. Moreover, if customers have diffi- culties in evaluating product quality, downsizing does not reduce satisfaction. Similarly, downsizing has little to no effect if customers rely on brands as primary cue in purchasing decisions. Thus, in B2C markets the ef- fect of downsizing on satisfaction is indeed less clear- cut than one would maybe expect.
That said, some of our moderator hypotheses were not supported by the data. For instance, whether services play an important role in a product category does not affect the downsizing-satisfaction link. This is interesting because Anderson et al. (1997) argue that there is a larger trade-off between productivity and customer satisfaction for service companies than for manufacturers. Their argument is based
Table 7 Customer satisfaction model (Narrow Downsizing Operationalization)
Dependent variable: change in customer satisfaction (t)
Model 1 Model 2
Fixed effects with clustered errorsa Fixed effects GLSb
Variable Cutoff year 2007 Cutoff year 2007
Downsizing (t-1) −1.67 (0.32)*** −1.94 (0.40)*** Organizational slack (t-2) 0.60 (1.34)n.s. −0.52 (0.96)n.s.
Labor productivity (t-2) 0.74 (0.59)n.s. −0.09 (0.43)n.s.
Industry R&D intensity (t) 0.00 (0.11)n.s. −0.13 (0.08)n.s.
Prior downsizing (t-2) 0.07 (0.24)n.s. −0.14 (0.13)n.s.
Prior financial loss (t-2) 1.13 (0.74)n.s. 0.94 (0.48)n.s.
Total assets (t) 0.00 (09)n.s. 0.07 (0.03)**
Employees (t) 0.00 (0.00)n.s. −0.00 (0.00)n.s.
Downsizing (t-1) × organizational slack (t-2) H1:+ 6.84 (5.22)n.s. −2.40 (3.89)n.s.
Downsizing (t-1) × labor productivity (t-2) H2:− −2.45 (1.77)n.s. −1.92 (1.55)n.s.
Downsizing (t-1) × industry R&D intensity (t) H3:− −1.17 (0.19)*** −0.58 (0.18)** Downsizing (t-1) × prior downsizing (t-2) H4:− −0.77 (0.93)n.s. 0.54 (0.66)n.s.
Downsizing (t-1) × prior financial loss (t-2) H5:+ −0.40 (0.97)n.s. −0.88 (0.75)n.s.
Downsizing (t-1) × interest H6:− 6.28 (2.93)* 5.99 (2.73)* Downsizing (t-1) × pleasure H7:− −0.71 (0.94)n.s. −1.08 (0.88)n.s.
Downsizing (t-1) × sign H8:+ −2.39 (1.59)n.s. −0.56 (1.66)n.s.
Downsizing (t-1) × risk importance H9:− −2.03 (1.24)n.s. −5.65 (1.54)*** Downsizing (t-1) × probability of error H10:+ 7.77 (2.63)** 10.21 (2.26)***
Downsizing (t-1) × service consciousness H11:− −3.13 (1.62)n.s. −1.50 (1.50)n.s.
Downsizing (t-1) × brand consciousness H12:+ −2.48 (3.11)n.s. −3.21 (2.77)n.s.
Year dummiesc Included Included
Number of firms 110 110
Number of firm-years 710 710
Number of downsizing events 54 54
R2 (within) 0.15 0.20
n.s. p>0.05; * p<0.05; ** p<0.01; *** p<0.001 (based on two-tailed tests)
Unstandardized parameters are shown. Standard errors are in parentheses a Estimated with STATA (version 10.1), procedure xtreg b Estimated with R (version 3.0.2), procedure pggls (version 1.4–0) c Dummy variable for each year was included in the models in order to account for fixed effects on the time level
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on the observation that customization is more important in service firms, which reduces possibilities for increasing productivity. Given the increasing importance of customizing manufactured goods, differences between service firms and manufacturers may have become smaller in this regard.
Likewise, we do not find that downsizing is less harmful to customer satisfaction if firm financial performance was de- clining before the downsizing or if a firm had downsized before. This is noteworthy because past performance explains image effects of downsizing. Love and Kraatz (2009) report that negative effects of downsizing on firm image are less pronounced if the downsizing is a response to performance
problems. The different results points to the importance of distinguishing between image and satisfaction as outcomes of downsizing.
The way our study is designed also extends earlier research methodologically: (1) Previous research on customer outcomes of downsizing used cross-sectional data, which triggers reverse causality issues. It is possible that low customer satisfaction forces firms to cut costs through downsizing. This would also entail a negative correlation between downsizing and satisfac- tion. By linking satisfaction to downsizing the year before, our setup alleviates these concerns. (2) Previous research has relied on single-source data from a customer’s perspective (e.g., Lewin 2009; Lewin and Johnston 2008; Lewin et al. 2010) or
Table 8 Financial performance model
Variable Dependent variable: change in return on assets (t)
Dependent variable: change in return on assets (t)
Dependent variable: return on assets (t)
Model 1 Model 2 Model 3
Change in customer satisfaction (t-1) – 0.17 (0.07)* –
Customer satisfaction (t-1) – – 0.57 (0.14)***
Downsizing (t-2) −0.12 (0.99)n.s. 0.04 (0.99)n.s. 1.07 (0.71)n.s.
Organizational slack (t-3) −2.35 (4.86)n.s. −2.43 (4.96)n.s. −6.26 (5.09)n.s.
Organizational slack (t) −6.47 (5.37)n.s. −6.86 (5.38)n.s. −6.74 (16.77)n.s.
Labor productivity (t-3) −7.61 (1.71)*** −7.73 (1.73)*** −9.00 (4.15)*.
Labor productivity (t) 6.13 (1.33)*** 6.37 (1.35)*** 7.69 (2.41)**.
Industry R&D intensity (t-1) 0.30 (0.90)n.s. 0.33 (0.91)n.s. 0.24 (0.45)n.s.
Prior downsizing (t-3) 0.17 (0.30)n.s. 0.18 (0.30)n.s. 0.50 (0.42)n.s.
Prior financial loss (t-3) −0.46 (1.87)n.s. −0.85 (1.94)n.s. −2.99 (1.68)n.s.
Total assets (t-1) −0.10 (0.09)n.s. −0.12 (0.10)n.s. −0.40 (0.22)n.s.
Employees (t-1) 0.01 (0.00)n.s. 0.01 (0.00)n.s. −0.01 (0.01)n.s.
Downsizing (t-2) × organizational slack (t-3) 11.24 (5.30)* 10.14 (5.30)n.s. 1.50 (7.30)n.s.
Downsizing (t-2) × labor productivity (t-3) 0.34 (1.44)n.s. 0.68 (1.42)n.s. 2.12 (2.15)n.s.
Downsizing (t-2) × industry R&D intensity (t-1) 0.86 (0.60)n.s. 1.05 (0.58)n.s. 2.14 (0.67)**
Downsizing (t-2) × prior downsizing (t-3) −1.42 (0.94)n.s. −1.39 (0.93)n.s. −1.18 (1.00)n.s.
Downsizing (t-2) × prior financial loss (t-3) −2.49 (4.00)n.s. −2.73 (3.94)n.s. −1.95 (1.39)n.s.
Downsizing (t-2) × interest 0.55 (2.93)n.s. 0.36 (2.89)n.s. 1.16 (2.46)n.s.
Downsizing (t-2) × pleasure 1.15 (1.41)n.s. 1.26 (1.40)n.s. −1.89 (1.36)n.s.
Downsizing (t-2) × sign −1.46 (2.57)n.s. −1.50 (2.53)n.s. 0.56 (2.19)n.s.
Downsizing (t-2) × risk importance −0.03 (2.15)n.s. 0.44 (2.09)n.s. −1.45 (1.66)n.s.
Downsizing (t-2) × probability of error 1.64 (2.80)n.s. 0.84 (2.75)n.s. −0.21 (2.19)n.s.
Downsizing (t-2) × service consciousness −0.48 (1.90)n.s. −0.28 (1.85)n.s. −0.76 (1.55)n.s.
Downsizing (t-2) × brand consciousness 0.50 (2.34)n.s. 0.20 (2.30)n.s. −1.74 (1.88)n.s.
Year dummiesa Included Included Included
Number of firms 104 104 104
Number of firm-years 609 609 610
R2 (within) 0.11 0.12 0.23
n.s. p>0.05; *p<0.05; **p<0.01; ***p<0.001 (based on two-tailed tests)
Unstandardized parameters are shown. Standard errors are in parentheses. Estimation method: fixed effects with clustered errors, cutoff year 2007 a Dummy variable for each year was included in the models in order to account for fixed effects on the time level
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a managerial perspective (Homburg et al. 2012). Our research integrates the two perspectives. Hence, with our design com- mon method effects can probably be ruled out as an explanation for the negative downsizing–satisfaction link.
Finally, our study establishes that customer satisfaction following downsizing mediates the downsizing–performance relationship. By identifying this mechanism, it also contrib- utes to research on the “hidden costs” of downsizing, i.e., costs that are often overlooked by managers starting these activities (Buono 2003). Furthermore, our study offers a new explanation why researchers have found it hard to find a consistent effect of downsizing on performance (e.g., Datta et al. 2010). If customer satisfaction mediates the effects of downsizing, interaction effects with context factors can create conflicting evidence with regard to the overall relationship. In fact, we too do not find a significant direct effect of downsizing on financial performance (see model 1 in Table 8). Coupled with our finding of an indirect effect via customer satisfaction, this suggests that multiple (opposing) indirect effects explain the relationship between downsizing and financial performance (e.g., MacKinnon et al. 2000; Rucker et al. 2011; Shrout and Bolger 2002).
It needs to be mentioned that when measuring downsizing, we follow a convention from management research. We con- sider any firm year as a downsizing year in which the number of employees went down by at least 5 %. This comes with limitations. First, the 5 % threshold is somewhat arbitrary. We find that results are mostly robust for other thresholds in a range between 3 and 7 %. For very high threshold values (e.g., 15 %), results differ. Therefore, future research could analyze extreme downsizing events further. Second, large reductions of the number of employees may not always indicate layoffs. Results are qualitatively consistent if only downsizing activi- ties covered in the press are considered. Third, the operationalization of downsizing is very general. Maybe out- comes of downsizing differ depending on the department
affected. Future research could compare downsizing conse- quences between departments.
Managerial implications
Our study has important implications for managers. Managers must be aware that depending on their firm and product category, downsizing has differential effects on customers. Thus, managers should “think outside the firm” while implementing downsizing. Our results indicate that this might be worth the effort. Managers should be especially careful with downsizing if industry R&D intensity and labor produc- tivity are high, while organizational slack is low. Similarly, they should actively consider alternatives to downsizing if customers perceive purchases in the category as risky, cus- tomers find it easy to assess product quality, and customers do not consider the brand an important purchase criterion.
Interestingly, our results suggest that currently managers do not pay much attention to these aspects when engaging in downsizing. A look at our Table 5 reveals that the correlations between the aforementioned variables and downsizing activ- ity are all smaller than 0.10. Hence, it appears as if currently managers mostly ignore the detrimental effects of downsizing on customers. Our study could contribute to increasing the awareness for these issues.
In addition, our study can guide managers interested in reducing detrimental customer outcomes of downsizing. First, customers react more negatively to downsizing in product categories where purchases are perceived as risky. This points to the importance of managing customer per- ceived risk during a downsizing. For instance, marketing managers could consider offering additional guarantees to their customer (e.g., a satisfaction guarantee). They should also implement a communication strategy that transparently addresses potential concerns of the cus- tomers. Second, customers react less negatively to
Table 9 Mediation analysis
βDS→CS βDS→CS × βCS→ROA Sobel test statistic p value (two-tailed)
Main model, i.e. average values for all moderators −0.97 (0.32)** −0.17 −1.98* 0.047 Low organizational slack −1.46 (0.35)*** −0.25 −2.21* 0.027 High labor productivity −1.30 (0.36)*** −0.24 −2.15* 0.032 High industry R&D intensity −1.66 (0.37)*** −0.29 −2.25* 0.025 High risk importance −1.99 (0.49)*** −0.34 −2.19* 0.028 Low probability of error −2.54 (0.58)*** −0.44 −2.24* 0.025 Low brand consciousness −1.57 (0.53)** −0.27 −1.95n.s. 0.051 All of the above −5.76 (1.07)*** −1.00 −2.34* 0.019
n.s. p>0.05; *p<0.05; **p<0.01; ***p<0.001 (based on two-tailed tests)
DS, downsizing; CS, customer satisfaction; ROA, return on assets. Unstandardized parameters are shown. Standard errors are in parentheses. Estimation method: fixed effects with clustered errors, cutoff year 2007. Low/high values for moderators are calculated as one standard deviation below/above the mean value
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downsizing in product categories where brands play an important role. Hence, during downsizing, marketers should put particular emphasis on brand communication at the point of sale and elsewhere.
Limitations
This study does have several limitations. First, it relies on balance sheet data to measure firm-related variables. Hence, downsizing is measured through a proxy, which—as discussed before—is tied to a number of assumptions about the nature of downsizing. We provide evidence that results are relatively stable if other operationalizations are used, but these come with their own disadvantages. Second, the archival nature of the data has also to some extent guided and restricted our choice of firm-level moderators. Survey data could pro- vide additional insights on how to manage downsizing, but data on sensitive issues like downsizing is notoriously difficult to obtain (Homburg et al. 2012) and not available for the time period of interest. Third, in terms of the firms analyzed, this study is subject to the inclusion requirements of the ACSI. It served as the starting point of our data collection efforts. Fourth, product category involvement is measured at one point in time after the focal time-period of the study. Thus, for our results concerning customer-related interactions to hold, it is required to assume that product category involve- ment is to some extent constant over time.
Conclusion
In the B2C markets covered by the American Customer Satisfaction Index, organizational downsizing is on average associated with decreases in customer satisfaction. In turn these customer outcomes of downsizing affect firm perfor- mance. However, the extent of negative customer reactions to downsizing is largely influenced by contextual variables. In particular, the degree to which a firm depends on human resources and the way customers process information in a product category moderate the downsizing-satisfaction link. Hence, in specific firm–product configurations, downsizing may prove detrimental with regard to customer satisfaction. For other firms, downsizing will not entail any negative cus- tomer response.
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J. of the Acad. Mark. Sci. (2015) 43:768–789 789
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- Customer reactions to downsizing: when and how is satisfaction affected?
- Abstract
- Introduction
- Conceptual framework
- Hypotheses
- Moderator effects pertaining to a firm’s resources
- Moderator effects pertaining to customer information processing
- Indirect effect of downsizing on financial performance via customer satisfaction
- Methodology
- Data collection and sample
- Measures
- Model specification and estimation
- Moderated effects of downsizing on customer satisfaction
- Robustness checks for different operationalizations of downsizing
- Indirect effect of downsizing on financial performance via customer satisfaction
- Discussion
- Research implications
- Managerial implications
- Limitations
- Conclusion
- References
Journal of Business Research 76 (2017) 24–33
Contents lists available at ScienceDirect
Journal of Business Research
Cure or curse: Does downsizing increase the likelihood of bankruptcy?
Michelle L. Zorn a,⁎, Patricia M. Norman b, Frank C. Butler c, Manjot S. Bhussar a a Raymond J. Harbert College of Business, Auburn University, 405 W. Magnolia Ave, Auburn, AL 36849, United States b Hankamer School of Business, Baylor University, One Bear Place #98013, Waco, TX 76798-8013, United States c The University of Tennessee Chattanooga, 615 McCallie Ave, Chattanooga, TN 37403, United States
⁎ Corresponding author. E-mail addresses: [email protected] (M.L. Zorn), Pat
(P.M. Norman), [email protected] (F.C. Butler), Msb00
http://dx.doi.org/10.1016/j.jbusres.2017.03.006 0148-2963/© 2017 Elsevier Inc. All rights reserved.
a b s t r a c t
a r t i c l e i n f o
Article history: Received 24 June 2016 Received in revised form 10 March 2017 Accepted 10 March 2017 Available online 14 March 2017
Downsizing is a common organizational practice, yet research on the outcomes of downsizing has produced mixed findings. To contribute to this debate, we use an organizational change perspective to investigate whether the large-scale changes inherent in downsizing set firms on a negative path that is difficult to overcome and ul- timately increases the likelihood of bankruptcy. Additionally,we investigatewhat factors, if any, canmitigate this likelihood. To do so, we build on the resource-based view to suggest that valuable resources can reduce the like- lihood that downsizing will lead to bankruptcy. We find support for our theorizing across a sample of publicly traded firms. Our findings suggest that downsizing firms are significantly more likely to declare bankruptcy than firms that do not engage in downsizing and that intangible resources help to mitigate this likelihood. We do not, however, find support for the role of physical and financial resources in preventing bankruptcy.
© 2017 Elsevier Inc. All rights reserved.
Keywords: Downsizing Bankruptcy Organizational change Resource-based view Intangible resources
1. Introduction
“To stay afloat, companies have cut costs by announcing layoffs and slashing their spending on projects.” (Gensler, 2016).
“GoPro Inc. is cutting 15% of its workforce after attempts to expand beyond its core business of action cameras failed to gain traction.” (Wells, 2016).
Statements such as these are prevalent in the business press and downsizing has become a part of the ongoing life of organizations (Jung, 2015). Irrespective of their current financial positions, firms of all types engage in employee downsizing to reduce their costs, adjust their structures, and create leaner more efficient workplaces (George, 2014; Lewin, Biemans, & Ulaga, 2010). Despite its continued and fre- quent use, research on downsizing continues to yield mixed results. Proponents of downsizing argue that downsizing is an effective strategy with benefits such as performance and sales increases (DeMeuse & Dai, 2013; Love & Nohria, 2005; Yu & Park, 2006). Yet, other studies point to negative consequences for firms and employees, with results demon- strating that firm performance, productivity, and customer satisfaction tend to decline after downsizing (Goesaert, Heinz, & Vanormelingen, 2015; Guthrie & Datta, 2008; Lewin et al., 2010). Further, surviving em- ployees can experience a variety of adverse effects including decreased morale, greater job insecurity, decreased creativity, and increased stress and burnout (Fisher &White, 2000;Niehoff,Moorman, Blakely, & Fuller,
[email protected] [email protected] (M.S. Bhussar).
2001; Probst, 2003; Probst, Stewart, Gruys, & Tierney, 2007; Rusaw, 2004; Shaw, Duffy, Johnson, & Lockhart, 2005).
These mixed findings suggest that important questions about what contributes to the viability of downsizing remain unanswered. To add to this line of inquiry we theorize that, while capable of producing pos- itive returns, downsizing may have unintended consequences that are not fully captured in prior studies. Specifically, we build on the organi- zational change literature to suggest that downsizing disrupts organiza- tions, increasing the likelihood of bankruptcy. Thus, it is essential for managers to understand what might mitigate these negative conse- quences and prevent their firms from declaring bankruptcy. In this study, we investigate whether firms' resources might lessen the likeli- hood of bankruptcy by helping firms overcome the challenges inherent in downsizing. Our study extends prior work by ascertaining whether and which types of resources help in staving off bankruptcy.
The contributions of our study lie at the intersection of the study of bankruptcy and downsizing. While both of these phenomena have been widely studied, there are few studies at the intersection of the two and there is more to be learned in each of these streams. Our liter- ature review generated only two studies that have focused on whether downsizing is associated with subsequent bankruptcy (Powell & Yawson, 2012; Smith, 2010) and a third that briefly mentions an ad- hoc analysis of this relationship (Reynaud, 2013). Each of these studies suggests that downsizing does, indeed, increase the risk of subsequently declaring bankruptcy.We build on these studies, where themost recent year of downsizing examined was 2002, to further investigate this rela- tionship in a sample of US firms in 2010. By comparing our results with these priorworks, we are able to shed light onwhether bankruptcies are
25M.L. Zorn et al. / Journal of Business Research 76 (2017) 24–33
still more likely for firms that downsize in an era when downsizing has become ingrained as an accepted practice.
Second, we take a different approach from prior studies by using the organizational change literature to theorize that the disruptive changes inherent in downsizing increase the likelihood of bankruptcy. Specifi- cally, we suggest that this likelihood increases because downsizing in- terrupts organizational routines, reduces the productivity and increases the stress of remaining employees, and impedes knowledge transfer and organizational learning. By theorizing and empirically demonstrating that downsizing increases the likelihood of bankruptcy we contribute new evidence to the continuing debate surrounding the viability of downsizing.
Third, we submit that the mixed findings in the downsizing litera- turemay be explained, in part, because large-scale changes have the po- tential for positive and negative outcomes and firms must find ways to counteract negative effects. Drawing on the resource-based view, we suggest that a firm's stock of resources may be one mechanism that helps to reduce the negative effects from downsizing, and therefore can help firms avoid bankruptcy. Surprisingly, extant research has just scratched the surface in delineating the role that organizational re- sources can play in downsizing outcomes (Brauer & Laamanen, 2014; Coucke, Pennings, & Sleuwaegen, 2007; Norman, Butler, & Ranft, 2013). For example, Norman et al., 2013 examined the role that re- sources play in subsequent bankruptcy, but did sowith a sample that in- cluded only downsizing firms and thus could not compare downsizing firms to non-downsizing firms. Accordingly, we add to previous find- ings by using a sample of over 4000 firms, both downsizing and non- downsizing, to investigate the differential effects that resources have on bankruptcy andwhether certain resources are particularly important for its prevention.
We also contribute to the bankruptcy literature. In assessing the like- lihood of bankruptcy, both quantitative and qualitative information is useful. Yet, most prior studies have focused on quantitative data in the form of financial ratios and stock-based data because qualitative factors are more difficult to measure in an objective manner (Boratyńska, 2016). Nevertheless, recent studies have started to examinemore close- ly the role that various qualitative factors play in the risk of bankruptcy. For example, recent studies have combined financial and market data with other “soft information,” such as legal actions, timeliness in filing financial reports, employee loyalty, and management quality (Altman, Sabato, & Wilson, 2008; Boratyńska, 2016). Our study adds to this emerging stream of by testing whether another piece of “soft informa- tion,” organizational downsizing, influences the likelihood of bankruptcy.
2. Does downsizing increase the likelihood of bankruptcy?
Downsizing involves workforce reductions undertaken with the goal, and under the economic assumption, that they will improve effi- ciency and performance (Datta, Guthrie, Basuil, & Pandey, 2010). While poor performance can trigger downsizing, even healthy firms downsize because the practice has, consistent with institutional theory, become legitimized as away to enhancefirm value (Jung, 2015) and “… how an organization should be structured to be effective” (McKinley, Zhao, & Rust, 2000, p. 231). Adjustments to workforce composition are increasingly accepted as away to change existing human capital config- urations and reconfigure routines (Brauer & Laamanen, 2014). Thus, at the socio-cognitive level, downsizing has become engrained as an effec- tive schema (McKinley et al., 2000). While managers hope for positive outcomes, research examining performance outcomes of downsizing is equivocal (Datta et al., 2010; Love & Nohria, 2005) and there is some evidence that downsizing increases the risk of bankruptcy (Powell & Yawson, 2012; Smith, 2010). Indeed, some firms experience increased efficiency from downsizing (Yu & Park, 2006), while others struggle with organizational decline (Goesaert et al., 2015; Guthrie & Datta, 2008; Ndofor, Vanevenhoven, & Barker, 2013).
The organizational change literature has shown that large-scale changes can be a source of significant disruption to a firm's processes as employees face challenges to unlearn prior patterns of actions and discover anddevelop new routines (Miller, Pentland, & Choi, 2012). Fur- ther, these changes can introduce a host of emotional changes in re- maining employees. Infrequent changes of large magnitude are especially challenging because they create incoherence or disruptions in organizational memory (Scalzo, 2006), which can lead to conse- quences such as deviations from established policies or procedures (Ramanujam, 2003) and the need to significantly alter routines (Brauer & Laamanen, 2014; Feldman, 2000).
Building on this literature, we theorize that downsizing, like other large-scale changes, disrupts organizational processes throughmultiple mechanisms. First, downsizing damages psychological contracts be- tween a firm and its remaining (surviving) employees (Arshad, 2016). Psychological contract theory suggests that individuals and employers enter into a trust-based informal agreement, whereby employees ex- change their work in return for fair pay and a positive, secure work en- vironment. Downsizing breaches this contract, which can lead to negative employee behaviors including a lack of engagement, reduced loyalty, and fewer organizational citizenship behaviors (De Meuse & Dai, 2013). Survivors often come to view their firms as less than ideal employers and thus turnover is likely to increase (De Meuse & Dai, 2013; Arshad, 2016). In addition, remaining employees may be overworked, leaving them less time for important activities such as de- veloping external networks, which has been linked to value-generating activities like innovation (Rusaw, 2004; Scalzo, 2006). Other well-docu- mented survivor reactions include increased stress (Brockner et al., 1994; Jacobson, 1987), loss of managerial trust (Aryee & Chen, 2004), and increased workloads (Amabile & Conti, 1999). Ultimately, breaches in psychological contracts can reduce productivity and therefore reduce performance (De Meuse & Dai, 2013). Such consequences make bank- ruptcy more likely.
Second, downsizing firms often lose valuable knowledge and human capital. Human capital has been shown to lead to higher performance and is even more critical when it is firm-specific. While firms may try to retain their most valuable employees, unintended human capital losses are likely (Fisher & White, 2000; Schmitt, Borzillo, & Probst, 2011) and remaining employees may be incapable of extending their skills to fill these gaps (Massingham, 2008).
Third, and even more critical from an organizational change per- spective, is the loss of social capital when employees exit. Social capital exists within networks of relationships internal and external to a firm, and is an essential ingredient in the creation of competitive advantage (Nahapiet & Ghoshal, 1998). It is needed to effectively reconfigure rou- tines, which are recurrent patterns of activities that emerge over time (Brauer & Laamanen, 2014), and upgrade capabilities after downsizing (Schenkel & Teigland, 2016). These changes, however, aremore difficult because social capital losses from downsizing damage existing routines, social networks, and organizational memory (Shaw et al., 2005; Schenkel & Teigland, 2016) by increasing the time required to access in- formation and solve non-routine problems (Rusaw, 2004; Scalzo, 2006) and reducing the breadth of potential solutions generated (Moorman & Miner, 1998). Survivors must focus on transferring and acquiring knowledge rather than applying knowledge they already have (Kacmar, Andrews, Van Rooy, Steilberg, & Cerrone, 2006), resulting in lower productivity and decreased efficiency (Holtom & Burch, 2016). Similarly, groups become less effective in how they communicate and interact, reducing their task accomplishments, and adversely impacting firm outcomes (Anderson & Lewis, 2014). These disruptions can in- crease the likelihood that firms will fail (Hannan & Freeman, 1984).
Given that these disruptions can inhibit the effective functioning of firms, we suggest that downsizing sets firms on a negative path that may be difficult to reverse (Datta & Iskandar-Datta, 1995; Hambrick & D'Aveni, 1988). Supporting our theorizing, research has shown that or- ganizational changes increase the likelihood of failure (Amburgey, Kelly,
26 M.L. Zorn et al. / Journal of Business Research 76 (2017) 24–33
& Barnett, 1993; Swift, 2016). Studies have also found that downsizing tends to decrease performance and increase leverage, which increases the likelihood of financial distress (Verwijmeren & Derwall, 2010). Thus, the damage inflicted by downsizing on employees, firm knowl- edge bases, and routines makes it more difficult to effectively rebuild routines, reconfigure resources, and implement other necessary chang- es. Accordingly, we propose:
Hypothesis 1. Firms that downsize are significantly more likely to de- clare bankruptcy than non-downsizing firms.
2.1. Preventing bankruptcy: the role of resources
Because firms strive for positive outcomes after downsizing, under- standing how firms can mitigate possible detrimental outcomes is of great importance. Firms must find ways to replace or work around the loss of human resources and the related disruptions to social capital and organizational routines. Thus, we look to insights from the re- source-based view to investigate how resource factors might enable firms to reduce negative outcomes following downsizing. Prior research on the resource-based view, while vast, has yet to examine the role of resources in preventing the likelihood of bankruptcy following downsizing. For example, Norman et al. (2013) examined the resources of downsizing firms to determine whether they were more likely to go bankrupt, be acquired, or remain a going concern, but did not compare downsizing to non-downsizing firms. Still unresolved is whether cer- tain resources might be more useful for downsizing firms than for other firms. After downsizing, to counteract negative consequences, a firm must leverage its available resources to enact positive changes, such as recreating or adapting social networks and organizational rou- tines (Brauer & Laamanen, 2014; Schenkel & Teigland, 2016). Thus, we extend prior research on the role of resources and downsizing by exam- ining whether a firm's intangible, financial, and physical resources (Chatterjee & Wernerfelt, 1991) can help counteract human capital losses and the accompanying disruptions from downsizing. We visually depict these relationships in Fig. 1.
2.1.1. Intangible resources We suggest that valuable, intangible resources enhance a firm's abil-
ity to negate the pitfalls of downsizing. Intangible resources are those that cannot be easily quantified and include patents, firm reputation, and employee knowledge. In linewith prior literature, we conceptualize intangible assets as those assets which add value above and beyond the book value of a firm's assets (Kaplan & Norton, 2004). For example, rep- utation and brand strength are valued by the market and contribute to competitive advantage, but they are not recorded as assets on a firm's balance sheet. While all types of resources matter, intangibles are par- ticularly important because they often form the basis of routines,
Fig. 1. Theoretical model of
capabilities, and competitive advantage (Barney, 2001), are more diffi- cult to replicate and substitute than other resources (Capron & Hulland, 1999), and help firms to acquire other valuable resources (Zott & Huy, 2007).
Given the flexibility of intangible resources (Sirmon, Hitt, & Ireland, 2007), firms can recombine and redeploy such resources after downsizing. Intangible resources facilitate organizational reconfigurations because their exclusivity provides a cushion allowing firms tomake less hasty, moremeasured decisions. In addition, intangi- ble resources such as brands, intellectual property, and reputation can continue to be leveraged after downsizing (Norman et al., 2013). Intan- gible resources also signal to alliance partners and shareholders that the firm is viable, helping tofill resources gaps by attracting newpartners or investments. Thus, downsizing firms with larger endowments of intan- gible resources should be better positioned to counteract any negative changes and avoid bankruptcy. Thus, we suggest:
Hypothesis 2. Intangible resources are significantly more valuable in preventing the likelihood of bankruptcy for downsizing firms than non-downsizing firms.
2.1.2. Financial resources Financial resources are tangible resources that can be used for a va-
riety of purposes including absolving debt obligations and purchasing more specific resources to help build a competitive advantage (Chatterjee & Wernerfelt, 1991). Excess financial resources are benefi- cial for innovation, learning, and change. These resources allow firms to allocate time and effort towards identifying and pursuing new oppor- tunities aswell as experimentwithways to restructure internal routines so that they are more effective (Iyer & Miller, 2008). In addition, finan- cial resources can help firms attract alliance partners or better leverage other remaining resources. For example, firms can use financial re- sources to fund innovation, introduce new products, launch marketing campaigns, or bolster customer benefits tomitigate possible service hic- cups experienced due to personnel changes during downsizing. GoPro, for example, laid off 7% of its staff in 2015 and subsequently announced plans to enhance software programs that benefit existing customers (Goldman, 2016). Firms can also enhance the knowledge and skills of survivors by funding training and professional development, which helps fill gaps in expertise left by downsizing. Further, financial re- sources can be used to enhance the compensation packages of remain- ing employees, thereby reducing turnover among remaining employees.
The bankruptcy literature has long recognized the importance of li- quidity in preventing bankruptcy (Altman, Iwanicz-Drozdowska, Laitinen, & Suvas, 2014; James, 2016). Not surprisingly, a review of 165 bankruptcy prediction studies found that performance and liquidity measures were the two most used predictors of bankruptcy (Bellovary,
proposed relationships.
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Giacomino, & Akers, 2007). Thus, while financial resources are impor- tant for all firms, we expect downsizing firms with access to greater fi- nancial resources will be able to leverage them to reduce the likelihood of bankruptcy. Accordingly, we predict:
Hypothesis 3. Financial resources are significantly more valuable in preventing the likelihood of bankruptcy for downsizing firms than non-downsizing firms.
2.1.3. Physical resources Physical resources are tangible, fixed assets such as equipment,
plants, or property that can readily be valued and aid firms in accomplishing their operational goals. The resource-based view sug- gests that such resources provide value to the extent that they represent investments that can be exploitedwhen combinedwith other resources or when they confer an advantage that others find difficult to imitate, such as unique retail locations or specialized equipment (Barney, 1991; Eisenhardt & Martin, 2000). Yet, physical resources alone may not be enough to overcome adverse effects from downsizing. For exam- ple, 3D printers, which are physical resources, in the hands of knowl- edgeable employees can enable firms to rapidly and inexpensively test prototypes before settling on a final product design. But as firms down- size and lose valuable human capital, such physical resources alone are unlikely to provide significant value. Similarly, physical resources are unlikely to reduce remaining employee stress or turnover.
While the bankruptcy literature has stressed the importance of fi- nancial assets and examined the role of intangible assets, tangible assets have played a lesser role in bankruptcy prediction. However, both the ability to sell fixed assets and their use for other productive purposes fa- cilitate the ability of firms to successfully reorganize and emerge from bankruptcy (Bauer, 2014; Gilson, Hotchkiss, & Osborn, 2016). Thus, while physical resources are of value to all firms because they facilitate ongoing operations or can be sold or leased to yield additional financial resources, they are unlikely to fill resource gaps left from downsizing. Accordingly:
Hypothesis 4. Physical resources are not significantly more valuable in preventing the likelihood of bankruptcy for downsizing firms than non- downsizing firms.
3. Method
3.1. Data and sample
Our sample consists of all publicly-traded US firms listed in the Compustat database with available financial information for 2010. We selected 2010 to allow examination of bankruptcy outcomes in the five years following the downsizing event (2011–2015). Further, 2010 marked a year of significant positive growth in GDP from 2009, and the five years following have been a period of relative stability, with slight positive growth (World Bank, 2017). After removing firms with inadequate data, we had a maximum useable sample size of 4710 firms. Our sample firms span 83 different industries (3-digit NAICS codes); include service, high-technology, and manufacturing firms; and average $3.7 billion in sales and 10,000 employees. We identified downsizing firms as those that had at least a 3% reduction in total em- ployees from 2009 to 2010 (Goesaert et al., 2015). Roughly 24% of our sample firms downsized in 2010, includingfirms such as Regal Cinemas, Petmed Express, and Ford. In post hoc t-test comparisons, downsizing firms that declared bankruptcy and downsizing firms that did not de- clare bankruptcy did not differ in prior performance, total assets, or total sales. However, these firms did differ significantly in terms of in- dustry and marginally in terms of net income, suggesting that firms that went bankrupt may have operational inefficiencies that were not alleviated by downsizing.
3.2. Variables
3.2.1. Bankruptcy Our dependent variable, indicates whether a firm filed for Chapter
11 bankruptcy. Chapter 11 bankruptcy legally exists so that firms can restructure their balance sheets and avoid liquidation. Bankruptcy is a dummy variable thatwas coded as a 1when a firm declared bankruptcy before the end of 2015 and 0 otherwise (James, 2016; Jones, 2011). Bankruptcies were identified using the UCLA-LoPucki Bankruptcy Re- search Database (BRD), which captures all US publicly-traded compa- nies that have declared bankruptcy since 1979. We further ensured that we captured all bankruptcies using data from the Bloomberg Terminal.
3.2.2. Downsizing Our primary independent variable of interest, downsizing, is mea-
sured with a 0/1 indicator, where 1 indicates that a firm downsized (Powell & Yawson, 2012; Yu & Park, 2006). Following Goesaert et al. (2015), firms were classified as downsizing if they reduced their total number of employees by 3% or more between 2009 and 2010. Given our mean number of employees of roughly 10,000, this suggests a min- imum layoff of approximately 300 employees.
3.2.3. Resources Empirical studies have shown that a significant part of the difference
between a firm's investor valuation and its book value is due to intangi- bles resources not accounted for on a firm's books (Shaikh, 2004). Fol- lowing prior research (Chadwick, Guthrie, & Xing, 2016; Villalonga, 2004), we used Tobin's q as a measure of intangible resources. We used the following simple q ratio in our calculations (Perfect &Wiles, 1994):
q ¼ Market Valueþ Total Debtþ Preferred Stock Liquidition Value Book Value of Assets
where each component was measured at year-end and total debt is the sum of long-term and short-term debt obligations. Financial resources were measured using the current ratio, current assets divided by cur- rent liabilities, which reflects the amount of readily available financial assets at managers' disposal (Iyer & Miller, 2008). Physical resources weremeasured using net value of plant, property, and equipment divid- ed by assets (Adler, Capkun, & Weiss, 2013).
3.2.4. Control variables Wecontrolled for other factors that prior research indicates could in-
fluence either bankruptcy or downsizing. Because poor performance has been associated with both downsizing and bankruptcy, we con- trolled for prior performance using industry-adjusted (3-digit NAICS code) prior year return on assets (ROA). ROA was calculated as net in- come divided by total assets. Similarly, we capture firm profitability using return on equity (ROE). ROE was calculated using net income dived by equity. To control for the concern that downsizing firms may be on a trajectory towards bankruptcy, and thus bias our results towards bankruptcy, we included Altman's Z. Altman's Z has been shown to ac- curately predict the likelihood that firms will declare bankruptcy (Altman et al., 2014) and was calculated using the following formula:
Z‐Score ¼ 1:2Aþ 1:4Bþ 3:3Cþ 0:6Dþ 1:0E
where A is the ratio of working capital to total assets, B is the ratio of retained earnings to total assets, C is the ratio of earnings before interest and taxes to total assets, D is the ratio of the market value of equity to total liabilities, and E is the ratio of sales to total assets (Iyer & Miller, 2008). A higher Z-score indicates that firms are less likely to go bank- rupt in the future. To control for the current debt position of the firm (i.e., leverage), we used a firm's debt to equity ratio, calculated as total liabilities divided by equity. We also controlled for current liquidity
28 M.L. Zorn et al. / Journal of Business Research 76 (2017) 24–33
using the cash ratio.We calculated liquidity using the proportion of cash to current liabilities. To control for firm size, whichmay affect bankrupt- cy declarations (Altman, Sabato, & Wilson, 2010), we included the nat- ural log of employees. Similarly, we controlled for capital expenditures using capital expenditures divided by total assets. In addition to our in- dustry fixed effects and clustered robust standard errors, we also con- trolled for several relevant industry factors. High-tech firms may differ in their human capital usage as well as intangible assets, thus we con- trolled for firms in a high-tech industry by including a dummy indicator, where 1 indicates a firmwas in a high-tech industry as classified by the American Electronics Association. Industries also differ in the extent to which they rely on knowledge workers, who are highly educated and highly skilled (von Nordenflycht, 2011). Because downsizing may have different effects in firms that are heavily reliant on knowledge workers (e.g., managers, engineers, scientists, editors, programmers), we controlled for industry knowledge intensity. This measure is the pro- portion of workers in an industry (2-digit NAICS) in occupational codes below 30-0000 in the 2010 Occupational Employment Statistics survey from the Bureau of Labor Statistics (Coff, 2002).
We also included additional controls that capture the potential rea- son behind the downsizing. First, we controlled for change in market capitalization—market value of equity plus long-term debt—from the close of 2008 to the close of 2009. This measure captures whether firms are downsizing reactively because of a decline in market value (Love & Nohria, 2005). Second, firms often downsize following an ac- quisition (Krishnan, Hitt, & Park, 2007). To control for this likelihood, we included a count of the number of acquisitions in the 5-years prior to the focal year.We also controlled for the amount of human resources slack (HR slack) prior to the downsizing.HR slack is calculated as [(firms employees / firm sales)− (industry employees / industry sales)]. Firms with excess employees may be more likely to downsize or have more success from such a move (Love & Nohria, 2005). To ensure that group- ing relatively small downsizing events with larger downsizing events in our primarymeasure was not driving our results, we also controlled for the percentage reduction in each downsizing firm's workforce. Percent downsized is a continuous measure, with firms that downsized b 3% coded as 0.
Table 1 Descriptive statistics and correlations1.
Variables Mean S.D. 1 2 3 4
1 Bankruptcy 0.01 0.11 2 Prior performance 0.01 11.85 0.00 3 Profitability −0.16 8.55 0.00 −0.01 4 Altman's Z −34.80 1166 0.00 0.24 0.00 5 Leverage 1.44 69.12 0.00 −0.01 −0.26 0.00 6 Liquidity 10.53 228.50 0.00 0.00 0.00 0.00 7 Firm size 1.34 1.37 −0.01 0.04 0.03 0.03 8 Capital Exp. 0.35 4.72 0.02 0.00 0.00 0.00 9 High-tech 0.21 0.41 −0.01 0.00 −0.01 0.01 10 Industry knowledge intensity 25.82 16.24 −0.01 0.00 −0.02 0.00 11 Change in market cap 715.02 4622 −0.01 0.01 0.00 0.01 12 Prior acquisitions 0.66 1.14 −0.02 0.02 0.00 0.02 13 HR slack 0.02 0.37 0.00 −0.01 0.00 −0 14 Pct. downsized 0.04 0.11 0.00 −0.03 −0.02 0.00 15 Downsizing 0.24 0.43 0.02 0.00 −0.02 0.01 16 Intangible 11.70 443.21 0.00 −0.16 0.00 −0 17 Financial 3.30 17.97 −0.01 0.01 0.00 0.06 18 Physical 0.55 0.52 0.04 −0.04 0.00 0.01
Variables 14
14 Pct. downsized 15 Downsizing 0.64 16 Intangible 0.05 17 Financial 0.00 18 Physical 0.01
1 Values N0.03 fall within the 95% confidence interval (p b 0.05).
3.3. Analysis
Our models were estimated using logistic regression. To control for industry differences, we included industry fixed effects (i.e., dummy variables) and clustered robust standard errors. We captured industries using 2-digit NAICS codes. To determine whether multicollinearity was a factor in our models, we assessed correlations and examined variance inflation factors, which all fell well below the commonly accepted cutoff of 10 (Kutner, Nachtsheim, & Neter, 2004).
3.4. Results
Means, standard deviations, and correlations are shown in Table 1. The results of our logistic regression analyses are presented in Table 2. Model 1 includes only control variables, Model 2 includes the main ef- fect for downsizing,Model 3 adds themain effects for the resourcemea- sures, Models 4–6 add individual interactions for each resource type and downsizing, andModel 7 is our fullmodel. Hypothesis 1, which pre- dicted that downsizing firms are significantly more likely to declare bankruptcy than non-downsizing firms, is supported by the coefficient for downsizing in Model 2 (b= 0.72, p = 0.04). Exponentiating the co- efficient reveals that the odds of a downsizing firm declaring bankrupt- cy are twice that of a non-downsizing firm.
Hypothesis 2 predicted that intangible resources would be signifi- cantly more valuable in preventing bankruptcy for downsizing firms than non-downsizing firms. This hypothesis was supported by the neg- ative coefficients for the interaction between downsizing and intangible resources in Model 4 (b=−0.58, p = 0.06) and Model 7 (b =−0.58, p=0.07). These results suggest that intangible resources are indeed ca- pable of reducing the likelihood that downsizing leads to bankruptcy and that intangible assets are more important for downsizing firms than for non-downsizing firms in staving off bankruptcy. As shown in Fig. 2, the amount of intangible resources held by downsizing firms sig- nificantly influences the likelihood of bankruptcy. Downsizing firms with high stocks of intangible resources have a substantially lower like- lihood of bankruptcy than both non-downsizing firms and downsizing firms with low stocks of intangible resources. Our results suggest that
5 6 7 8 9 10 11 12 13
0.00 0.00 −0.03 0.00 0.00 −0.06 0.00 −0.01 0.00 −0.03 0.02 0.00 −0.02 −0.02 0.29 −0.01 0.00 0.24 −0.01 0.01 −0.01 −0.01 −0.01 0.30 −0.02 0.08 0.13 0.12
.01 0.00 0.00 −0.03 0.11 −0.00 −0.00 0.00 −0.01 0.00 0.00 −0.18 0.03 −0.02 0.00 −0.05 −0.07 0.00 0.02 −0.01 −0.08 0.01 −0.01 −0.01 −0.05 −0.05 0.01
.09 0.00 0.00 −0.02 0.01 0.00 0.00 0.00 −0.01 0.03 0.00 0.10 −0.07 0.07 −0.02 −0.03 −0.01 −0.03 0.00 0.02 −0.03 −0.01 0.03 −0.12 −0.16 −0.02 −0.14 0.02
15 16 17
0.02 −0.01 0.00 0.07 −0.02 −0.06
Table 2 Results of logistic regressiona,b.
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Bankruptcy Bankruptcy Bankruptcy Bankruptcy Bankruptcy Bankruptcy Bankruptcy
Prior performance 0.01 0.01 0.13 0.13 0.14 0.13 0.13 (0.01) (0.01) (0.18) (0.18) (0.18) (0.18) (0.18)
Profitability 0.00 0.00 0.00 0.00 0.00 0.00 0.00 (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Altman's Z 0.00 0.00 0.00 −0.00 0.00 0.00 −0.00 (0.00) (0.00) (0.02) (0.02) (0.02) (0.02) (0.02)
Leverage −0.00 −0.00 0.00 0.00 0.00 0.00 0.00 (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Liquidity −0.04 −0.04 −0.01 −0.01 −0.01 −0.01 −0.01 (0.02) (0.02) (0.02) (0.02) (0.02) (0.02) (0.01)
Firm Size 0.01 0.01 0.00 0.01 0.00 0.00 0.01 (0.05) (0.05) (0.05) (0.05) (0.05) (0.05) (0.05)
Capital Expenditures 0.04 0.04 0.04 0.04 0.04 0.04 0.04 (0.04) (0.04) (0.04) (0.04) (0.04) (0.04) (0.04)
High-Tech −0.08 −0.09 −0.05 −0.04 −0.05 −0.05 −0.04 (0.22) (0.21) (0.20) (0.20) (0.20) (0.20) (0.20)
Industry knowledge intensity −0.04⁎⁎⁎ −0.05⁎⁎⁎ −0.03⁎⁎⁎ −0.03⁎⁎⁎ −0.03⁎⁎⁎ −0.03⁎⁎⁎ −0.04⁎⁎⁎
(0.00) (0.00) (0.01) (0.01) (0.01) (0.01) (0.01) Change in market cap −0.00⁎ −0.00† −0.00 −0.00 −0.00 −0.00 −0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Prior acquisitions −0.15 −0.15 −0.14 −0.13 −0.13 −0.14 −0.13
(0.20) (0.19) (0.19) (0.19) (0.19) (0.19) (0.19) HR slack −6.09 −6.20 −4.57 −4.61 −4.20 −4.49 −4.18
(6.10) (6.15) (7.72) (7.94) (7.33) (7.72) (7.83) Pct. downsized −0.30 −2.23† −2.44 −2.58 −2.86† −2.43 −2.98†
(0.97) (1.29) (1.59) (1.66) (1.61) (1.54) (1.68) Downsizing 0.72⁎ 0.63† 1.45⁎ 0.62† 0.81⁎⁎ 1.59⁎⁎
(0.34) (0.35) (0.64) (0.36) (0.28) (0.57) Intangible −0.28 −0.20 −0.28 −0.28 −0.20
(0.24) (0.24) (0.24) (0.24) (0.24) Financial −0.08 −0.07 −0.10 −0.08 −0.10
(0.05) (0.05) (0.07) (0.05) (0.07) Physical 0.12 0.11 0.11 0.19 0.16
(0.15) (0.14) (0.15) (0.12) (0.11) Downsizing X Intan. −0.58† −0.58†
(0.31) (0.32) Downsizing X Fin. 0.07 0.07
(0.07) (0.07) Downsizing X Phys −0.24 −0.21
(0.26) (0.26) N 4710 4710 4641 4641 4641 4641 4641 Pseudo R2 0.07 0.07 0.08 0.08 0.08 0.08 0.08
a Robust standard errors clustered by industry in parentheses. b Pseudo R2 provides an overall model fit in logistic regression and is akin to the traditional R2 metric in OLS. † p b 0.10. ⁎ p b 0.05. ⁎⁎ p b 0.01. ⁎⁎⁎ p b 0.001.
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downsizing firmswith low intangible resources have the greatest likeli- hood of bankruptcy.
Hypothesis 3 predicted thatfinancial resourceswould be significant- ly more valuable in preventing bankruptcy for downsizing firms than
Fig. 2. The interaction between downsizing and intangible resources.
non-downsizing firms. As shown in Table 2, Model 5, this hypothesis was not supported (b = 0.07, s = 0.32). Hypothesis 4 predicted that physical resources would prove of similar value for downsizing and non-downsizing firms. As shown in Table 2, Model 6, we found support for this hypothesis (b = −0.24, p = 0.36).
In sum, these results lend support to our overall theorizing that downsizing can increase the odds of bankruptcy. We also found that in- tangible resources weremore likely to reduce the risk of bankruptcy for downsizing than for non-downsizing firms. However, financial and physical resources were not of greater value for downsizing firms. We discuss the implications of our findings in the Discussion section, but first we turn to the robustness of our results.
3.5. Robustness
We took several steps to ensure the viability of our results. First, we tested models with data from a different time period. We confirm our presented results using a sample of firms with announced downsizings reported in the Wall Street Journal from 1995 to 2000 (e.g., Love & Nohria, 2005; Norman et al., 2013) that were each matched with a
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non-downsizing firm of similar size in the same industry to control for possible self-selection and endogeneity concerns. This matched pair sample helps to address sample-section bias. Given thatfirms self-select by choosing to downsize, we do not know what would have happened had they not engaged in downsizing. Thus, by matching firms that downsizewith firms that exhibit similar pre-downsizing characteristics that did not downsize, we help to alleviate selection bias concerns. Our results from this second sample, fully support our reported results.1
Of particular concern in this line of research are endogeneity con- cerns stemming from either selection bias or from simultaneous causal- ity. In other words, either firms self-select into the sample by downsizing or downsizing firms may have already been on a negative trajectory, making them inherently more likely to declare bankruptcy. We address endogeneity concerns in twoways. As noted above,we con- trol for priorfirmperformance, leverage, prior change inmarket capital- ization, and bankruptcy trajectory using Altman's Z. Altman's Z is a relatively accurate predictor of the likelihood that firms will declare bankruptcy in the future and thus helps to account for firm bankruptcy trajectory prior to the focal event (Altman et al., 2014). To further con- firm our results, we tested our sample with a two-stage instrumental variables technique, a recommended method for reducing endogeneity concerns (Semadeni,Withers, & Certo, 2014). Given our binary outcome variable and binary independent variable, we estimated two-stage bi- variate probit models using the number of previous downsizing events in the five years prior to the downsizing and the natural log of acquisi- tion spending in the year prior to the downsizing event. We selected these instruments based on their significant correlation with the inde- pendent variable andweak or insignificant relationshipwith the depen- dent variable (thus making it unlikely that they are correlated with the error term). Our two-stage bivariate probitmodel confirmed our prima- ry result that downsizing increases the likelihood of bankruptcy. Ulti- mately, these tests are supportive and suggest that endogeneity concerns are not driving our results.
Next, we examined different cutoff values for our dichotomousmea- sure of downsizing (i.e., 5% and 10% downsizing indicators). Results for both 5% and 10% cutoffs supported our primary results, with downsizing significantly increasing the likelihood of bankruptcy.
Our study captures bankruptcy declarations in the five years follow- ing downsizing. We also sought to explore these results for different windows. That is, we investigated whether downsizing was linked to bankruptcy when we examined windows of 1, 2, 3, and 4 years follow- ing 2010.We found a relatively consistent relationship for eachwindow with the only exception being two years following downsizing. Thus, it appears that the relationship between downsizing and bankruptcy is relatively stable when using different post-downsizing estimation pe- riods and supports our notion that downsizing has long-term conse- quences for firms.
We also tested models that included controls for prior downsizing activity. The first was a count of the number of downsizings in the five years prior to our sample period and the second was percentage that the entire firmdownsized in thefive years prior to the focal downsizing. Our results were unchanged when including these controls and they were insignificant in each model. Similarly, we also tested our models using a control for firm age because newer firms have an increased like- lihood of failure (Thornhill & Amit, 2003). Our results were substantive- ly similar.2
4. Discussion
The primary focus of our study was to investigate whether downsizingplacesfirms at a greater risk of bankruptcy and, if so,wheth- er resources could help to mitigate that risk. Given that downsizing has
1 Results for this sample set are available upon request. 2 Because this information is not available for all firms, we did not include firm age in
the presented models.
become a common business practice, it is important to understand the consequences of such a decision. We theorized that downsizing is a large-scale change that is often traumatic for employees and disruptive for firms. While capable of producing positive results, our findings sug- gest that downsizing puts firms on a negative path that makes bank- ruptcy increasingly likely. Even after controlling for numerous other factors including performance, bankruptcy trajectory, and industry fac- tors, downsizing firms were significantly more likely to declare bank- ruptcy than non-downsizing firms. While not always fatal, downsizing does increase the odds that a firm will declare bankruptcy. This finding is in line with work that shows that large-scale organizational changes introduce disruptions that increase the likelihood of bankruptcy (Amburgey et al., 1993; Powell & Yawson, 2012; Swift, 2016) and ex- tends previous findings on the downsizing/bankruptcy relationship to US firms in recent years.
Given the disruptions that are introduced during downsizing, it is critical for managers to understand how to better position their firms to experience positive rather than negative outcomes. Therefore, we sought to provide further insights about what factors might help firms to mitigate detrimental effects and reduce the likelihood of bankruptcy. Drawing on the resource-based view, we examinedwhether a firm's in- tangible, financial, and physical resources could lessen the likelihood of bankruptcy for downsizingfirms.We found support for the positive role that intangible resources play. The interaction between downsizing and intangible resources indicates that intangibles help downsizing firms to stave off bankruptcy. Our finding suggests that a larger base of intangi- ble resources allows a firm to consider a wider range of options when reorganizing following downsizing. We theorize that firms with greater intangible resources can redeploy such resources in unique and, per- haps, creative ways after downsizing that can help to prevent negative outcomes. Indeed, intangible resources, such as employee knowledge, can be leveraged to work around processes that have been interrupted due to employee losses or to replace these processeswithmore efficient ones. Similarly, because these assets can be used in a variety of ways (Sirmon et al., 2007), they may be able to attract alliance partners that can fill resource gaps and thereby soften the blow experienced by downsizing firms. Alternatively, an absence of intangible resources to draw upon limits firms' available options and these options are likely to be less attractive than firms with higher intangibles. Our study sug- gests that intangibles are especially important for firms as they undergo major changes, most notably when those changes require adjustments to existing routines, as is the case for downsizing firms (Brauer & Laamanen, 2014).
Our results show that, unlike intangibles, neither financial nor phys- ical resources significantly changed the likelihood of bankruptcy follow- ing downsizing. The finding for physical assets was as predicted, whereas the finding for financial resources was somewhat surprising. Prior theory has suggested that physical resources alone may not prove especially valuable (Barney, 1991). Our results agree and, at a minimum, suggest that simply having physical resources is not enough to counter large-scale changes following downsizing. In simple terms, we believe that physical assets, such as property or equipment, cannot substitute for valuable human capital losses. That is, holding, or even selling, physical asset does not replace the downsized employees, who fulfill multiple roles as workers, knowledge bearers, and cultural con- tributors within the firm. Because having ample capital is often viewed as a corporate panacea that is always valuable, it was unexpected and interesting to find that financial resources were largely insignificant in our models and did not contribute to the prevention of bankruptcy for downsizing firms. We theorize that this result may be likely for several reasons. First, prior research has shown that downsizing causes disrup- tions to key long-term value creating mechanisms, such as knowledge and routines; it may be that these challenges cannot be overcome by simply havingmore capital. That is, routines andprocess are interrupted and simply throwing more money at this type of problemmay be inef- fective. Second, firms may be unaware of the potential increases in
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employee stress due to downsizing and therefore not use their financial resources in theways that could provemost beneficial to remaining em- ployees. Even with awareness and availability of resources, firm efforts to mitigate the negative impacts that survivors experience may not have the desired effect. Providing bonuses, for example, may not im- prove employee attitudes or decrease stress following downsizing. Fi- nally, this finding may occur because financial resources, unless used to hire new employees, do not provide a direct substitute for the knowl- edge, skills, and abilities of the lost employees. If financial resources were used for the specific purpose of assuaging remaining employee concerns, revamping processes and routines, or even hiring new em- ployees, then financial resources could perhaps reduce these negative effects. However, we speculate that this often may not be the case.
Ultimately, our findings regarding physical and financial resources are supported by resource-based theory, which suggests that more complex, higher-order resources, like intangible assets, are the most valuable and thatmore simplistic resources, such as physical orfinancial resources, alone, do not lead to such advantages.We speculate that per- haps when these resources are combined or bundled with other re- sources in unique ways, they may prove more effective. However, our research suggests that alone these resources, which lack rarity and non-substitutability, are not enough to help downsizing firms prevent bankruptcy.
4.1. Implications for researchers
Our study has several important implications for researchers exam- ining the outcomes of downsizing. Prior research has typically looked at the relationship between downsizing and firm performance, yet perfor- mance measures alone may not capture all of the consequences of downsizing. Furthermore, many performance studies examine 1- to 3- year windows following downsizing and thus may not fully capture its long-term consequences. Our time window spanned 5 years following the downsizing and thus allowed us a longer-term view. Overall, while previous studies have noted that positive results are possible (Love & Nohria, 2005; Yu & Park, 2006), the risk of very negative out- comes may not be fully captured in performance metrics. Losses of human capital, disruptions to routines and memory, and negative ef- fects on remaining employees may create a path dependent process that is difficult for some firms to reverse once underway. Ultimately, a non-financial measure such as bankruptcy helps to capture the poten- tially severe consequences of downsizing.
Next, by examining the role that remaining resources have in lessen- ing the downside of large-scale changes, this study helps to illuminate the role resources play in firms' ability to adapt to organizational chang- es. Prior research on organizational change suggests that “the question of whether change is hazardous should be replaced by the questions of under what conditions change may be hazardous or helpful and whether the direction of change affects its impact on performance and survival” (Haveman, 1992, p. 1). We build on this notion and find sup- port for the idea that intangible resources can help firms to mitigate the potentially significant consequences that accompany large-scale or- ganizational changes.While we find support for some of the key predic- tions of the resource-based view in regards to intangible resources, we also find important boundary conditions in that having more capital or more physical resources alone are of limited value in combatting the negative consequences of change.
Finally, our findings have implications for research examining whether resources have substitution effects (Peteraf & Bergen, 2003). While prior research suggests that resource substitution can occur be- tween competing firms, we build on this by highlighting that within a firm, resources may be able to substitute for one another. When downsizing firms lose human resources, some of the value of these re- sources can be replaced or substituted for using valuable intangible re- sources. If, for example, firms lose employee knowledge when they downsize, they may be able to leverage a valuable brand to attract an
alliance partner with similar skills to those that were lost. Thus, our findings imply that, at times, resources may substitute for one another.
4.2. Implications for practice
A primary implication for practice is that managers must undertake downsizing with a clear understanding of the potential risks and tradeoffs of such actions. Downsizing may involve changes that affect knowledge, routines, and the productivity of remaining employees. It is widely recognized in the literature that these changes are often dis- ruptive and can be difficult to overcome, yet managers frequently en- gage in downsizing. Our findings suggest 1) that managers should carefully consider whether any potential positive returns will outweigh potentially severe consequences and 2) that managers should fully as- sess their resource portfolio prior to downsizing to determine whether their remaining resources can adequately protect the firm from nega- tive consequences. Furthermore, managers must consider that remain- ing resources are not all of equal value. Firms planning to downsize must focus carefully on their intangible resources, rather than financial or physical ones, because these will be critical as firms lose human capital.
Next, our findings have broader implications for managers who choose to downsize as a part of a larger restructuring plan. Organiza- tional restructuring, at times, involves selling off various assets while si- multaneously laying off employees. When firms plan to downsize as part of a larger restructuring, they must ensure that they retain key re- sources that can increase the likelihood that negative outcomes are minimized. Asset sales, particularly when such sales eliminate impor- tant intangible resources, may limit the ability of managers to counter- act the negative effects from employee layoffs. Downsizing while simultaneously spinning off valuable intangible resources may increase the odds that firms will fail.
4.3. Limitations and future research
Our study, like most, suffers from certain limitations. These limita- tions, however, provide avenues for future research. Our study focuses primarily on downsizing. Future research could study the relationships between broader conceptualizations of restructuring and bankruptcy. For example, does restructuring that does not involve downsizing, cre- ate disruptions that increase the risk of bankruptcy? Another potentially interesting avenue is to study whether the value of resources varies in different forms of restructuring. In other words, are resources equally valuable in each formof restructuring?Whilewe did notfind thatfinan- cial resources were particularly valuable for downsizing firms, it may be that firms that engage in portfolio restructurings are more dependent on financial resources to accomplish reorganizing goals.
Future research could also work to determine whether these rela- tionships hold in a recessionary period. The prevalence of bankruptcy tends to increase in recessionary periods (Altman et al., 2014) and in- vestors and creditors are likely to be more frugal, making internally held financial resources more powerful. Additionally, downsizing may garner less negative press during a recession when it may be expected that firms will engage in such activities. As more firms downsize, indi- vidual firms and managers are less likely to suffer reputational damage. This may make it easier for firms to retain and attract employees and other critical resources.
Another limitation is the use of secondary data sources. In this study, we were not able to identify how organizations redeploy resources post-downsizing to stave off bankruptcy. Therefore, researchers may wish to performmore inductive research to examine how organizations successfully redeploy different resources to prevent bankruptcy and other less severe, but still negative, outcomes.
A final limitation was our use of a holistic archival measure of intan- gible resources. While we follow prior research that has used archival measures such as Tobin's q to measure intangible resources, future
32 M.L. Zorn et al. / Journal of Business Research 76 (2017) 24–33
research could collect data on distinct types of intangible resources such as patents or reputation rankings. More refined measures would help create an even finer-grained understanding of how intangible resources help firms avoid bankruptcy.
A final interesting avenue for future research is continued investiga- tion into the role of intangible resources, before and after downsizing. For instance, researchers could undertake a thorough examination of the extent to which changes in intangible assets lead to downsizing de- cisions. Similarly, future research could also use primary data to better delineate the process through which intangible resources aid firms fol- lowing downsizing.
5. Conclusion
This research provides initial insight into the relationship between downsizing and bankruptcy. From an organizational change perspec- tive, downsizing, like other large-scale changes, introduces disruptions that increase the likelihood that firms will experience severe negative consequences. Supporting this, we found that downsizing firms were more likely to declare bankruptcy than their peers that did not down- size.We then drewon the resource-based view to understandwhich re- sources, if any, could reduce this likelihood. We found that intangible resources help to reduce the likelihood of bankruptcy for downsizing firms, but that financial and physical resources do not play a significant role.
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Michelle L. Zorn is in her third year as assistant professor of StrategicManagement at Au- burn University. She has published work on corporate governance and family businesses and her research interests include corporate governance, acquisitions, downsizing, com- petitive dynamics, and family businesses. Prior to joining Auburn, she received her PhD in Strategic Management from Florida State University, her MBA from the University of Southern Mississippi, and her BA in Finance from Virginia Tech.
PatriciaM. Norman is an Associate Professor of Management at Baylor University, where she teaches strategicmanagement. Her research interests include downsizing, innovation, and strategic alliances. Her work has been published in journals such as the Journal of Management, Journal of Business Research, and the Journal of Product Innovation Man- agement. She earned her PhD in Strategic Management from the University of North Car- olina at Chapel Hill. Prior to earning her Ph.D., Patricia served as a contracting/acquisition officer in theU.S. Air Force. She also has a BA in Economics from the University of Pennsyl- vania and an MS in Contracting Management from the Air Force Institute of Technology.
Frank C. Butler is a UC Foundation Associate Professor ofManagement at theUniversity of Tennessee at Chattanooga. His research interests include corporate governance, mergers and acquisitions, and downsizing. His work has been published in outlets such as the Jour- nal of Management, Business Horizons, and Journal of Managerial Issues. Prior to earning his Ph.D. in Strategic Management from Florida State University, Frank worked in the in- formation technology industry in both Germany and the United States. Heworked in a va- riety of roles including quality control, projectmanager, and IT consultant. He received his BBA in Management Information Systems from the University of Georgia.
Manjot S. Bhussar is a third year Doctoral Student in Management at Auburn University. His research interests includemergers and acquisitions, innovation, and downsizing. Prior to starting his Ph.D. in Management at Auburn, Manjot got his MBA from Auburn Univer- sity at Montgomery, and his Bachelors in Engineering from Thapar University, India.
- Cure or curse: Does downsizing increase the likelihood of bankruptcy?
- 1. Introduction
- 2. Does downsizing increase the likelihood of bankruptcy?
- 2.1. Preventing bankruptcy: the role of resources
- 2.1.1. Intangible resources
- 2.1.2. Financial resources
- 2.1.3. Physical resources
- 3. Method
- 3.1. Data and sample
- 3.2. Variables
- 3.2.1. Bankruptcy
- 3.2.2. Downsizing
- 3.2.3. Resources
- 3.2.4. Control variables
- 3.3. Analysis
- 3.4. Results
- 3.5. Robustness
- 4. Discussion
- 4.1. Implications for researchers
- 4.2. Implications for practice
- 4.3. Limitations and future research
- 5. Conclusion
- References
J. Account. Public Policy 36 (2017) 239–257
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J. Account. Public Policy
j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / j a c c p u b p o l
Full length article
Disclosure strategies and investor reactions to downsizing announcements: A legitimacy perspective
http://dx.doi.org/10.1016/j.jaccpubpol.2017.03.003 0278-4254/� 2017 Elsevier Inc. All rights reserved.
⇑ Corresponding author at: Schulich School of Business, York University, 4700 Keele Street, Canada. E-mail addresses: [email protected] (E. Nègre), [email protected] (M.-A. Verdier), [email protected] (C
[email protected] (D.M. Patten).
Emmanuelle Nègre a, Marie-Anne Verdier b, Charles H. Cho c,⇑, Dennis M. Patten d a University of Montpellier, France b University of Toulouse 3 Paul Sabatier, France c Schulich School of Business, York University, Canada d Illinois State University, United States
a r t i c l e i n f o
Article history: Available online 17 April 2017
Keywords: Disclosure strategies Downsizing operations Impression management Legitimacy theory Press releases
a b s t r a c t
In this paper, we focus on a relatively underexplored aspect of sustainability—workforce reductions. We investigate the determinants and consequences of the decisions made by French firms to use press releases in order to announce downsizing operations. We also examine whether the content of press releases has an impact on investor reactions to downsizing announcements. Particularly in the French context, downsizing operations reflect negatively on corporate social responsibility with respect to employees, and we anticipate that French managers will use disclosure strategies to counter a potential legit- imacy threat. Our sample consists of 227 downsizing operations announced between 2007 and 2012 by 119 French listed firms. We find that the disclosure of press releases is driven by both contextual and legitimacy factors. We also find that press releases are associated with more negative reactions to downsizing announcements than when there is no press release, particularly in the case of proactive operations (i.e., implemented by firms with improving performance). A content analysis of press releases indicates that firms, on aver- age, engage in a reactive impression management strategy in their disclosure that consists of attributing downsizing operations to external factors. Moreover, investors penalize the use of proactive arguments, particularly when they are used to justify proactive operations. Overall, our results show that, in the French case, disclosure strategies and their conse- quences on the financial markets relate to a legitimacy perspective.
� 2017 Elsevier Inc. All rights reserved.
1. Introduction
Organizational sustainability includes the economic-financial, environmental, and social aspects of organizations (e.g., Jabbour and Santos, 2008). However, to date, most research in the sustainability domain focuses on the environmental aspect of sustainability as opposed to its social dimension (Sharma and Ruud, 2003). And while recent literature on integrated reporting in sustainability accounting (e.g., Baboukardos and Rimmel, 2016; Melloni et al., forthcoming) does consider dif- ferent CSR dimensions, specific categories are not examined in-depth.
.H. Cho),
240 E. Nègre et al. / J. Account. Public Policy 36 (2017) 239–257
In contrast, in this paper we explore the social issue of workforce reductions. Consistent with Wilkinson (2005), we argue that downsizing operations1 have an adverse impact on sustainability and we note that these operations have been the subject of much controversy. More specifically, several studies note that downsizing operations are perceived by society as a breach of the social contract between organizations and society (e.g., Mäkelä and Näsi, 2010; Van Buren, 2000; Vuontisjärvi, 2013). Accordingly, the issue of workforce reductions falls within the domain of corporate social responsibility (CSR)/sustainability research since the operations have adverse societal consequences, particularly for employees. From an ethical perspective, downsizing operations can also be seen as a questionable business undertaking (Vuontisjärvi, 2013) and are generally imple- mented in order to improve firm efficiency and to maximize value for shareholders. However, for employees and the local com- munity, downsizing operations usually mean significant losses that can be difficult to support (Mäkelä and Näsi, 2010).
Such a breach of the social contract can have severe economic consequences for firms—for instance because of potential strikes or boycotts (e.g., Hunter et al., 2008), which could destroy value for shareholders through lost customers and rev- enues.2 This would be especially true for ‘‘proactive” downsizing operations as they are considered less ethically justifiable (Van Buren, 2000) because they are not justified by apparent financial needs (Love and Kraatz, 2009). Downsizing operations can thus be viewed as negative social events (e.g., Barclay et al., 2005; Flanagan and O’Shaughnessy, 2005; Leana and Feldman, 1988) that create legitimacy threats for organizations. Consequently, companies facing legitimacy threats may use dis- closure strategies to alter perceptions about the legitimacy of the organization (e.g., Beelitz and Merkl-Davies, 2012; Cho, 2009; Cho and Patten, 2007). If this is the case, we would expect to find that, when companies disclose the logic behind downsizing operations, they would be more likely to make them appear more reactive (or less proactive) than they are in reality.
In addition, prior research examines the impact of downsizing announcements on the reaction of financial markets (e.g., Chalos and Chen, 2002; Elayan et al., 1998; Hillier et al., 2007; Lee, 1997) and generally shows a negative investor reaction (e.g., Chen et al., 2001; Elayan et al., 1998; Hillier et al., 2007; Lee, 1997; Lin and Rozeff, 1993; McKnight et al., 2002; Ursel and Armstrong-Stassen, 1995; Worrell et al., 1991). Evidence also suggests that the reason why (proactive or reactive) down- sizing operations occur influences financial market reactions. However, while these prior studies primarily focus on code-law countries and adopt an economic perspective to explain results, we argue that the investigation of downsizing operations in more stakeholder-oriented countries requires consideration of other perspectives such as their potential threat to corporate legitimacy.3
In this study, therefore, we examine the determinants and consequences of the decisions made by French firms to use press releases in order to announce downsizing operations, through a national lens and by adopting a legitimacy perspective. We also examine whether the content of the press releases has an impact on investor reactions to downsizing announce- ments because the analysis of disclosure strategies aligned with such announcements highlights the potentially important role of disclosure in influencing investor response to downsizing announcements. We specifically focus on the French con- text where the need to justify and legitimate downsizing operations through disclosure strategies seems particularly strong. The French legal system protects workers and makes it difficult and costly for firms to dismiss workers (Cascio, 2005), and France is historically known for its strong conflicts between managers (or shareholders) and employees. While cooperation between both parties has been improving to some extent, the country’s protest culture – documented by a high strike rate – is still prevalent and leads to high exposure of downsizing operations in the media.4 Further, and importantly from a legit- imacy perspective, Jung et al. (2015, p. 2064) argue that ‘‘the nature of employment reduction in France is distinct from ‘offen- sive’ layoffs more common in the USA in the last three decades.” They note that in the U.S. firms ‘‘increasingly rely on employee layoffs [. . .] to improve financial performance in the context of increased pressures from shareholder value-driven institutional investors,” while in France, poor performance is the key driver to employment reduction (Jung et al., 2015, p. 2062–2063). Accordingly, proactive operations in France are often viewed as an ‘‘injustice” creating political tensions and generating a need for communication. France is thus a unique setting to examine downsizing operations as these events constitute significant threats to firms. Examining 227 downsizing operations implemented between 2007 and 2012 by 119 French listed companies, we find that the disclosure of press releases to announce downsizing operations is driven by both contextual and legitimacy factors. With respect to the former, we find that press releases are more likely for firms that implement a downsizing for the first time during the period studied, and less likely when downsizing operations are implemented through layoffs rather than voluntary measures (e.g., early retirements, voluntary redundancy plans). With respect to legitimacy-related factors, we
1 We use the term ‘‘downsizing operations” and ‘‘workforce reduction” interchangeably in the paper as we consider them synonymous. As we note in the methods section below, our sample of events includes downsizing operations related to both layoffs and voluntary reduction measures (such as voluntary retirement). We control for differences in these types of reductions in the analysis.
2 An illustration is the 2001 consumer boycott on Danone, a French multinational food and beverage firm. While it was generating high profits, Danone announced a cut of 3000 jobs in Europe, including 1700 in France. This operation was seen as a ‘‘public outrage” (Hunter et al., 2008, p. 338) even by some politicians who ordered hospitals and schools to stop buying Danone products. The Danone logo was modified to include the slogan ‘‘Human beings are not yogurts”. Despite Danone denying the impact of the boycott and strikes on firm performance, a serious decline in the company’s sales and market capitalization has been reported by financial analysts and the media.
3 In the legitimacy perspective, the target audience for disclosure is wider than in the economic perspective and includes several stakeholders (e.g., customers, employees, etc.).
4 For example, on October 5th, 2015, Air France-KLM’s angry employees interrupted a meeting in which managers and employee union representatives were discussing a new large downsizing operation. This operation caused both violent protests and actions against Air France-KLM’s CEO and Human Resources Director and this incident was subject to much international media exposure. French President François Hollande denounced this violence as ‘‘unacceptable and bad for France’s image”. He added that ‘‘social dialogue is important, and when it is interrupted by violence and disputes take on an unacceptable form, it can have consequences for the image and attractiveness [of the country]”.
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find that the probability of the use of press releases increases for firms that belong to socially sensitive industries, and decreases when firms implement downsizing operations during a financial crisis period. We also report a negative association between downsizing announcements via press releases and market reaction. With respect to proactive operations, we find that despite an overall positive (but not significant) market reaction to proactive operations, the reaction is, on average, negative when firms announce such operations through press releases. Finally, content analysis of the 66 press releases issued by sample firms to announce downsizing operations shows that numerous French firms appear to adopt a reactive impression management strat- egy, in that the language of the press releases make the downsizing operations appear more reactive (or less proactive) than they are in reality. This suggests that firms consider legitimacy concerns when adopting disclosure strategies. We also find that the more firms use proactive arguments to justify downsizing operations, the more investors in the French market react neg- atively to such operations. This result contrasts with the one of prior studies conducted in common-law countries that docu- ment a positive market reaction to downsizing announcements if the reasons stated within such announcements are proactive (e.g., Abraham, 2004; Elayan et al., 1998). In addition, the use of proactive arguments in press releases disclosed to announce proactive operations is negatively related to market reaction. Therefore, investors do not penalize the use of impres- sion management. On the contrary, they react negatively to disclosures that could increase a potential legitimacy threat. Overall, our results show that in the French case, disclosure strategies and their consequences on the financial markets relate more to a legitimacy perspective.
Our research extends the empirical literature on both downsizing and sustainability in four different ways. First, most prior research defines proactive and reactive operations according to the reasons stated within downsizing announcements (e.g., Abraham, 2004; Elayan et al., 1998; Lee, 1997; Worrell et al., 1991). However, we provide evidence of impression man- agement strategies in such announcements; that is, firms appear to justify downsizing operations by using reactive argu- ments—they establish a link between the decision to downsize and external events (e.g., bad market or sector conditions) and internal financial difficulties potentially in order to offset any legitimacy threats. Second, we take into account how downsizing operations are brought to the public’s attention (i.e., by the media or directly by the firms through press releases). By issuing press releases, firms keep control of their communication and thus could manipulate a particular mes- sage and make it easier to accept. However, our results suggest that disclosures made via these releases are more likely to damage firm organizational legitimacy. This stands in contrast to Griffin and Sun’s (2013) findings of positive market reac- tions to U.S. company press releases related to carbon emissions. Third, we examine the market reaction to downsizing announcements in a code-law country such as France in which legitimacy considerations are strong and very relevant regarding labor issues (Harris et al., 1994; Mora and Sabater, 2008). In contrast, most prior research has been conducted in common-law countries and finds that when managers mention proactive arguments to justify downsizing operations, investors react positively or less negatively than when reactive arguments are given (e.g., Abraham, 2004; Elayan et al., 1998; Gunderson et al., 1997; Hahn and Reyes, 2004; McKnight et al., 2002). Our results show that, in France the market perceives badly the use of proactive arguments presumably due to concerns with potentially damaged legitimacy. Finally, despite the large number of studies on sustainability issues to date, little attention has been paid to the social dimension of CSR activities and their relation to the concept of sustainability (Kent and Zunker, 2013; Mäkelä and Näsi, 2010). By inves- tigating the disclosure strategies and market reactions to downsizing announcements from a legitimacy perspective, this study helps to address this gap in sustainability-related research.
The remainder of this paper is organized as follows. Section 2 presents the theoretical framework of the study and devel- ops the hypotheses. Section 3 describes the variables and the sample. Sections 4 and 5 present the empirical findings. Sec- tion 6 discusses the main results and concludes.
2. Theoretical framework, literature review and hypotheses development
2.1. Legitimacy and the social contract
As noted by Gray et al. (1995), a large body of social and environmental accounting research is grounded in legitimacy theory. Dowling and Pfeffer (1975, p. 122) define organizational legitimacy as the ‘‘congruence between the social values asso- ciated with or implied by their activities and the norms of acceptable behavior in the larger social system of which they are a part”. The concept of a social contract established between organizations and society is central to legitimacy theory (e.g., Cho, 2009; Deegan, 2002; Deegan and Blomquist, 2006; Hooghiemstra, 2000; Patten, 1992). Shocker and Sethi (1973) argue that all organizations are linked to society by a social contract, and it can be viewed as an ‘‘ethical floor below which firms cannot fall and still be considered socially legitimate” (Van Buren, 2000, p. 210). Therefore, organizational legitimacy and social con- tract compliance go hand in hand (Deegan et al., 2000), and a breach of the contract may lead to a perception by society that the organization is not legitimate.
According to Suchman (1995), prior literature defines organizational legitimacy from two different perspectives. First, from a strategic perspective, legitimacy is considered to be a resource on which an organization is dependent for survival (Dowling and Pfeffer, 1975; Deegan, 2002), and legitimacy can also be influenced or manipulated by organizations to gain societal support. Second, from an institutional perspective, society generates ‘‘cultural pressures that transcend any single organization’s purposive control” (Suchman, 1995, p. 572) and thus managers’ practices are constructed by external institu- tions. Suchman (1995) concludes that both strategic and institutional perspectives need to be considered in order to
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understand the complexity of organizations. Organizational legitimacy is thus the result of both managers’ active strategies and managers’ passive responses to external pressures.
Prior research suggests that firms facing legitimacy threats engage in specific disclosure strategies to alter perceptions about the legitimacy of the organization (e.g., Beelitz and Merkl-Davies, 2012; Cho, 2009; Cho and Patten, 2007). Legitimacy theory has been extensively used in the previous literature to explain firms’ disclosure strategies in non-routine situations (Merkl-Davies and Brennan, 2007) such as (1) corporate scandals (e.g., Breton and Côté, 2006; Elsbach, 1994), (2) environ- mental disasters (e.g., Beelitz and Merkl-Davies, 2012; Cho, 2009; Deegan et al., 2000; Hooghiemstra, 2000; Patten, 1992), and (3) restructuring firms (e.g., Arndt and Bigelow, 2000; Mäkelä and Näsi, 2010; Ogden and Clarke, 2005). Disclosures are regarded as responses to both public pressure and increased media attention (Hooghiemstra, 2000), which are particu- larly strong in the context of downsizing operations (Henderson et al., 2010).
2.2. Downsizing operations
Proactive downsizing operations aim to improve the efficiency and profitability of firms (Freeman and Cameron, 1993; Pouder et al., 2004; Sheaffer et al., 2009) and/or to maintain competitiveness (Lee, 1997), and they are generally imple- mented without apparent financial needs (Love and Kraatz, 2009). In contrast, reactive operations are carried out because of poor or declining firm performance (Lee, 1997; Worrell et al., 1991). Several studies (e.g., Abraham, 2004; Chen et al., 2001; Elayan et al., 1998; Hillier et al., 2007; Lee, 1997; McKnight et al., 2002; Worrell et al., 1991) document that the market reaction is more negative when downsizing operations are reactive compared to when they are proactive, while others report a positive reaction to proactive operations (Abraham, 2004; Elayan et al., 1998; Gunderson et al., 1997; Hahn and Reyes, 2004; McKnight et al., 2002). From an economic perspective, it is argued that proactive operations lead to a positive market reaction because they convey good news to investors about future performance, whereas reactive operations high- light the severity of the financial distress, and thus convey bad news to investors. In order to lessen the impact of bad news, managers can use disclosure strategies when they provide the logic behind reactive operations. According to Lee (1997), management could make downsizing operations appear proactive rather than reactive in their disclosures (i.e., proactive impression management strategy), leading to a more favorable market reaction to downsizing announcements. Lee’s implicit assumption is that investors are the main target audience for disclosure.
We argue that legitimacy considerations should be more prevalent in code-law countries compared to common-law countries due to the strong social differences between these two systems of governance. For example, both Ball et al. (2000) and Simnett et al. (2009) note that code-law countries such as France, Italy, and Spain, are characterized by a stake- holder governance model in which accounting earnings are presumed to be divided among shareholders, governments, man- agers, employees, and other stakeholders. Therefore, when firms announce downsizing operations, employees can perceive the operations as a way for managers to transfer wealth from employees to firms, leading to a breach of the social contract between firms and society. In contrast, labor relations in common-law countries are characterized by ‘‘more flexible hire and fire arrangement” (Munoz-Bullon and Sanchez-Bueno, 2011, p. 2925). Further, France, in particular, relies on a system of code law where the power of unions is stronger than in common law countries (Ball et al., 2000; Garcia Lara et al., 2005; Harris et al., 1994). When the power of unions is high, the issue of the distribution of wealth is more likely to lead to social protests in the form of strikes or boycotts, potentially increasing the costs associated with such operations.
2.2.1. The decision to use press releases: determinants and stock market reaction Beelitz and Merkl-Davies (2012) argue that depending on whether there is congruence or incongruence between manage-
ment’s and organizational audiences’ interpretations of the downsizing, the managerial decision to reduce the workforce is either accepted or rejected. Rejection of the managerial decision could create legitimacy threats for organizations. Therefore, managers have incentives to resolve the conflicting interpretations of the event by using disclosure. In the context of down- sizing operations, one way to preserve organizational legitimacy is to use press releases to announce and justify these oper- ations. However, we assume that the probability of conflicting interpretations of the event is different according to the reason (proactive or reactive) for the operation. The firm’s decision to downsize is more likely to lead to conflicting interpre- tations in the case of proactive operations. Indeed, managers and shareholders may perceive proactive operations positively as they convey a positive signal on future performance. In contrast, particularly in the French context, other stakeholders including employees and the public may perceive these operations negatively as they appear unnecessary regarding the firm’s current performance. Therefore, we assume that for French companies, the probability of disclosing a press release is higher for proactive rather than reactive operations. Further, because the use of press releases could enable firms to resolve the potential conflicting interpretations about the downsizing operations, we expect market reactions to downsizing oper- ations to be less negative when companies proactively announce the workforce reductions via press releases.
We formally state our first two hypotheses as:
H1: The use of press releases by French firms to announce downsizing operations is more likely for proactive than reactive operations.
H2: The market reaction to downsizing operations by French firms will be less negative when press releases are used to announce workforce reductions.
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2.2.2. Content of the press releases and stock market reaction As noted above, prior studies of investor reactions to downsizing operations assume, from an economic perspec-
tive, that proactive operations will be perceived more positively. Based on this, Lee (1997), for example, argues that when managers provide the logic behind the downsizing operations, they have an incentive to use a proactive impression management strategy to make downsizing operations appear more proactive (or less reactive) than they are in reality.
However, in the French context, such an argument may not be valid. In France, downsizing operations are far more likely to be seen as threatening events because they potentially involve a violation of values (Ashforth and Gibbs, 1990). Further, the risk of legitimacy loss is higher in the case of proactive operations because these operations are not justified by apparent financial need (Love and Kraatz, 2009), and thus, they are less ethically justifiable (Van Buren, 2000). Therefore, from a legitimacy perspective, French firms have an incentive to highlight the role of external factors such as demand slump, economic crisis or bad market conditions that are beyond the control of managers (e.g., Brockner, 1990; Stevens and Kristof, 1995) when attempting to justify the downsizing operation. In other words, we expect French firm managers to use a reactive impression management strategy to make downsizing operations appear to be more reactive (or less proactive) in their press releases than they are in reality. Finally, we expect the type of impres- sion management used in the press releases to influence market reactions to the announcements. In contrast to the tra- ditional belief that investors will react more positively to the use of proactive arguments to justify workforce reductions, in the French context, we expect the opposite due to the increased potential for such claims to lead to legitimacy concerns. If investors believe the cost of lost legitimacy outweighs the economic benefit of the downsizing operations, the announcements will lead to reduced market value (Groening and Kanuri, 2013), and we anticipate reactions to be even more negative where proactive arguments are used to justify proactive operations as this reinforces the potential legiti- macy threat.
We formally state these hypotheses as follows:
H3: French firms are more likely to use reactive rather than proactive arguments in press releases announcing downsizing operations.
H4: The market will react negatively to French firms’ use of proactive arguments to justify downsizing operations.
H5: The market reaction will be more negative when proactive arguments are used by French firms to justify proactive oper- ations compared to reactive operations.
3. Research method
3.1. Dependent variables
In this study, we first investigate the determinants of firms’ decisions to issue press releases to announce downsizing operations. Second, we explore the relation between press release disclosure and the stock market reaction to downsizing announcements. We obtained press releases from the Factiva database or from companies’ websites, and in the first equation (Eq. (1)), the dependent variable (DISCPR) equals one when the firm discloses a press release to announce the downsizing and zero otherwise. In the second equation (Eq. (2)), the dependent variable (CARi) is the cumulative abnormal return for firm i over the event period from day 0 until day 2. The event date (t = 0) is the date of the downsizing announcement (by firms themselves through press releases or by the media). We estimate market model parameters using ordinary least squares regression with an estimation period ranging from days �120 to �20 prior to the event date. We consider the CAC All-Tradable index as our proxy for the market portfolio, and we obtain all financial data (stock prices and market index data) from the Datastream database. Appendix A provides additional details on the event study methodology used in this study.
3.2. Independent and control variables
3.2.1. Determinants of the use of press releases To the best of our knowledge, no studies to date focus on the determinants of voluntary disclosure in the social context of
downsizing operations. Therefore, we rely on both CSR disclosure and downsizing literature to identify factors potentially explaining the disclosure decision in this context. We introduce two sets of determinants—contextual and legitimacy factors.
The first contextual factor is the reason for the operation (H1). The empirical literature often defines proactive and reac- tive operations according to the reasons stated within the downsizing announcements (e.g., Capelle-Blancard and Tatu, 2012; McKnight et al., 2002). However, we argue that if managers are using impression management in these announce- ments, the underlying cause of the layoffs may be obscured. Accordingly, we follow Cascio et al. (1997), Love and Kraatz (2009), and Sheaffer et al. (2009) and instead use performance indicators to classify proactive and reactive operations. Sheaffer et al. (2009, p. 260) argue return on assets (ROA) is a ‘‘key financial indicator indicative of firms’ pre-downsizing financial situation” (p. 960). Consistent with Cascio et al. (1997), we compute ROA as earnings before interest, taxes, depre- ciation, and amortization (EBITDA) divided by total assets, and rely on this measure to identify the underlying reason for the
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downsizing operations we explore.5 More precisely, we define operations implemented by firms as proactive (reactive) follow- ing an increase (a decrease) in ROA for the previous year. We use a dummy variable (REASON) coded one for proactive oper- ations and zero otherwise to measure the impacts of the reason for the downsizing on disclosure.
Also related to contextual factors, we introduce a dummy variable (FIRST) taking the value of one for firms implement- ing a downsizing operation for the first time over the period studied and zero otherwise. Lee (1997) argues a first-time downsizing operation usually conveys more new information to stakeholders than subsequent actions, potentially increas- ing the probability of the use of a press release to explain the operation to the public. Further, we include the size of the operation (DOWNSIZE) measured as the percentage of employees laid off as a contextual factor (see, e.g., Nixon et al., 2004; Ursel and Armstrong-Stassen, 1995). Large operations, presumably due to greater visibility, should exhibit a higher probability of disclosure. Finally, we introduce a dummy variable (LAYOFF) that equals one for downsizing operations car- ried out through layoffs and zero for operations implemented through voluntary measures (e.g., early retirements, volun- tary redundancy plans). The unions’ demands and specific actions are likely to be stronger in layoffs than in other types of downsizing operations as layoffs may be perceived as less fair for employees (Greenhalgh et al., 1988), increasing the need for disclosure.
The use of press releases to announce downsizing operations can also result from legitimacy-related factors. Related to these, we first include a dummy variable (SENSIND) that serves as a proxy for socially sensitive industries such as oil and gas, basic materials, aerospace and defense, utilities, and health. Sensitive industries are industries associated with social externalities such as alcohol and tobacco, guns and defense, natural resources, and health (Brammer and Millington, 2005; Hong and Kostovetsky, 2012) or industries that caused numerous social issues in the past. Legitimacy theory suggests sensitive industries are more likely to face legitimacy issues as they are closely monitored by non-governmental organiza- tions, environmental lobby groups (Deegan and Gordon, 1996) and politicians (e.g., Cowen et al., 1987), and accordingly we expect companies within these industries to use disclosure to address these exposures. We next introduce a mimicry factor (MIMETPR) that identifies the number of press releases announcing downsizing operations issued by firms within the same industry for the previous year. Lee (1997) notes that firms within a given industry may feel pressure to mimetically follow the trend of layoffs implemented by competing firms. Further, we include a variable related to labor pressures (LABOR) given that they can increase the need for legitimation and thus the probability of disclosure. Aligned with Depoers (2000) and Missonier-Piera (2004), we use the ratio of labor charges on net sales.6 Finally, we expect the need for legitimation of the downsizing is reduced in times of financial crisis, which could decrease the probability of disclosure. We study the downsizing announcements over the period 2007–2012 and this timeframe includes the financial crisis of 2008–2009, which was charac- terized by negative Gross Domestic Product (GDP) growth rates. In order to take into account the differing economic context, we use a dummy variable (CRISIS) that equals one for downsizing announcements in 2008 and 2009 and zero otherwise.
We control for ownership structure by including a variable related to the percentage of shares held by foreign investors (FORINV). Several studies (e.g., Cormier and Magnan, 2003; Hannifa and Cooke, 2005) show that social and environmental disclosures are positively related to foreign investors. Next, we include a variable (FRSALES) that measures the percentage of net sales realized in France as an increase in this percentage should reinforce negative consequences for firms of potential boycotts. Finally, we control for the firm’s size (FIRMSIZE) as measured by the logarithm of the total assets, and the book-to-market ratio (BM).
3.2.2. Stock market reaction to the use of press releases The test variable related to H2, DISCPR, equals one when the firm issues a press release to announce the downsizing and
zero otherwise (Eq. (2)). We also take into account other factors identified in the prior literature as determinants of market reaction to downsizing announcements (REASON, FIRST, DOWNSIZE, LAYOFF, CRISIS, MIMET). First, prior literature shows that the market reacts more negatively to reactive than proactive operations (e.g., Abraham, 2004; Chen et al., 2001; Elayan et al., 1998; Hillier et al., 2007; Lee, 1997; McKnight et al., 2002; Worrell et al., 1991) because such operations convey a negative signal on performance. Second, previous studies document that the market reacts more negatively to the first downsizing than to subsequent downsizing operations (e.g., Capelle-Blancard and Tatu, 2012; Ursel and Armstrong-Stassen, 1995). Third, the market reaction is more negative in large operations (i.e., when a large percentage of total employees is affected by the downsizing operation) than in small operations (Elayan et al., 1998; Hillier et al., 2007; Lee, 1997; Nixon et al., 2004; Pouder et al., 2004; Ursel and Armstrong-Stassen, 1995; Worrell et al., 1991). Next, McKnight et al. (2002) find that the market reacts more negatively to layoffs than to downsizing operations carried out through voluntary measures. Indeed, layoffs could reflect a strong need to cut costs and be perceived as ‘‘emergency mea- sures” (McKnight et al., 2002, p. 89). Further, Capelle-Blancard and Tatu (2012) find that the market reaction to downsizing announcements is less negative in times of financial crisis than in non-crisis periods, potentially because these operations are less surprising in crisis periods. We add a variable (MIMET) that represents the number of downsizing operations
5 Love and Kraatz (2009) and Sheaffer et al. (2009) also use ROA measures to capture changes in firm profitability. In non-tabulated sensitivity tests, we alternatively identified the underlying reason for the downsizing operations using what Love and Nohria (2005) refer to as the return on market-valued assets. Calculated as EBIT divided by the market value of equity, Love and Nohria argue this metric captures performance relative to current and future performance expectations. Results using this alternative measure for classification of operations are qualitatively unchanged from those we report in the paper.
6 We recognize that the level of unionization can be a good indicator of the labor force power. However, this data is not available for French firms.
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announced by firms within the same industry for the previous year. We expect the market reaction to be less negative when downsizing operation announcements are common within the given industry (Lee, 1997).
We control for sensitive industries as investors should react more negatively to downsizing operations announced by firms in such industries due to the strong risk of legitimacy damage. Next, the percentage of shares held by foreign investors can be considered as a proxy for the market discipline imposed by active investors who constantly demand that firms imple- ment efficient operations to improve their performance (Nishitani and Kokubu, 2012). These investors should thus perceive downsizing operations more positively than local investors. We also take into account firm size because it affects company visibility and public scrutiny (Aerts and Cormier, 2009) which could in turn impact the market reaction. Finally, we include the book-to-market ratio to control for the impact of the firm’s growth prospects on the market reaction.
We analyze newspaper articles and press releases available on the Factiva database to identify the characteristics of downsizing operations (e.g., LAYOFF, DOWNSIZE). We use the Infinancials7 database to obtain data for ROA, total assets, indus- try, and book-to-market ratio. The other variables are collected manually from annual reports for the year before the announcement.
3.3. Models
The explanatory model used to identify the determinants of the disclosure of a press release to announce a downsizing is stated as:
7 See 8 We
Log½PrðDISCPR ¼ 1Þ=ð1 � PrðDISCPR ¼ 1Þ� ¼ b0 þ b1 REASON þ b2 FIRST þ b3 DOWNSIZE þ b4 LAYOFF þ b5 SENSIND þ b6 MIMETPR þ b7 LABOR þ b8 CRISIS þ b9 FORINV þ b10 FRSALES þ b11 FIRMSIZE þ b12 BM þ ei ð1Þ
With DISCPR = disclosure of a press release; REASON = proactive/reactive operations; FIRST = first downsizing imple- mented by the firm over the period studied; DOWNSIZE = size of the downsizing; LAYOFF = downsizing operations imple- mented through layoffs; SENSIND = sensitive industries; MIMETPR = number of press releases disclosed by firms of the same industry to announce downsizing operations; LABOR = labor pressures; CRISIS = economic crisis/expansion periods; FORINV = foreign investors; FRSALES = net sales realized in France; FIRMSIZE = firm size; BM = book-to-market ratio; b0 = intercept; b1. . .12 = regression coefficients; ei = residual term.
In addition, we estimate the following model to analyze the relation between press release disclosure and the stock mar- ket reaction to downsizing announcements:8
CARi ¼ b0 þ b1 DISCPR þ b2 REASON þ b3 FIRST þ b4 DOWNSIZE þ b5 LAYOFF þ b6 SENSIND þ b7 MIMET þ b8 CRISIS þ b9 FORINV þ b9 FIRMSIZE þ b10 BM þ ei ð2Þ
With CARi = cumulative abnormal return for firm i over the event period from day 0 until day 2; DISCPR = disclosure of a press release; REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWNSIZE = size of the downsizing; LAYOFF = downsizing operations implemented through layoffs; SENSIND = sensitive industries; MIMET = number of downsizing operations announced by firms within the same industry; CRISIS = economic crisis/expansion periods; FORINV = foreign investors; FIRMSIZE = firm size; BM = book-to-market ratio; b0 = intercept; b1. . .10 = regression coefficients; ei = residual term.
Table 1 summarizes the independent and control variables.
3.4. Sample selection and descriptive statistics
We initially considered all the downsizing operations announced by French listed firms during the period from 2007 to 2012. Using the Factiva database, we identified all newspaper articles related to French listed firms containing the words layoff, job cut, downsizing, or redundancy plan. We used both singular and plural forms of the words. Our search revealed a total of 318 downsizing operations. We then excluded from our sample (1) financial and insurance firms (8 firms), (2) all observations with missing values for any of the variables used in the empirical analysis (5 firms) and (3) outlier values (2 firms). Finally, we required, for each firm, that the first downsizing in the period studied be preceded by 120 days in which no downsizing operations were announced. This criterion resulted in the exclusion of an additional 76 downsizing opera- tions. Our final sample thus consists of 227 downsizing operations implemented by 119 French listed firms during the period from 2007 to 2012. Table 2 presents the sample selection procedure.
Table 3 presents descriptive statistics. As identified in the table, 30% of the downsizing operations are announced by firms through press releases, while 70% are announced by the media. Moreover, in our sample, the majority of downsizing oper- ations was reactive (60%), implemented through layoffs (55.1%), and was not the first such event implemented by firms over the period studied (55%). Further, 25% of the downsizing operations were announced by firms that belong to a sensitive
http://www.infinancials.com/ for addition information. conduct Hausman tests to check for any endogeneity issues and they indicate none. As such, we conduct OLS regressions.
Table 1 Definition of the independent and control variables.
Variables Definitions Eq. (1)
Eq. (2)
Disclosure of a press release (DISCPR)a
1 if the firm discloses a press release to announce the downsizing; 0 otherwise X
Reason for the downsizing (REASON)
1 if the downsizing is proactive (i.e., implemented by a firm with an increase in the ROA for the previous year); 0 otherwise
X X
First announcement (FIRST) 1 if the firm implements a downsizing for the first time during the period studied; 0 otherwise X X Size of the downsizing
(DOWNSIZE) % of employees laid off X X
Type of downsizing (LAYOFF) 1 if the downsizing is implemented through layoffs; 0 otherwise X X Sensitive industries (SENSIND) 1 if the firm belongs to a sensitive industry (oil and gas, basic materials, health care, utilities); 0
otherwise X X
Mimicry (MIMETPR) Number of press releases announcing downsizing operations issued by firms within the same industry for the previous year
X
Mimicry (MIMET) Number of downsizing operations announced by firms within the same industry for the previous year
X
Labor pressures (LABOR) Labor charges / net sales X Crisis period (CRISIS) 1 for downsizing announcements in 2008 and 2009 (i.e., years with negative GDP growth rates); 0
otherwise X X
Foreign investors (FORINV) % of shares held by foreign investors X X French net sales (FRSALES) % of net sales realized in France X Firm size (FIRMSIZE) Logarithm of the total assets X X Book-to-Market (BM) Book value of firms / market value of firms X X
a The variable DISCPR is an independent variable in Eq. (2) but a dependent variable in Eq. (1).
Table 2 Sample selection procedure.
Number of downsizing operations
All the downsizing operations implemented by French listed firms during the period from 2007 to 2012 318
- financial and insurance firms - missing values - outlier values - operations in the estimation period
- 8 - 5 - 2 - 76
Final sample 227
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industry. The percentage of employees laid off announced is, on average, 3.39%, and 50% of the downsizing operations occurred during times of financial crisis. Labor charges represent more than one third of the total net sales (35%). Foreign investors held on average 13% of the firm’s shares and the average percentage of firms’ net sales realized in France is 48%. Finally, the average book-to-market is 68.54%.
4. Results
4.1. Determinants of the use of press releases to announce downsizing operations
We first compare the reason for the operation between disclosing and non-disclosing companies and Table 4 identifies the frequency distributions and the result of the Pearson’s Chi-Squared test (with asymptotic significance between brackets). The results reveal no significant difference in the use of press releases across proactive and reactive downsizing operations. This is not in line with our first hypothesis (H1).
We next investigate the determinants of firms’ decisions to use press releases to announce downsizing operations using binary logistic regressions. Because two of our intended explanatory variables are highly correlated (see Appendix B),9 we estimate models separately including FIRST and FIRMSIZE. The results of our estimations are reported in Table 5. As identified in the table, the models, based on Chi-Squared test statistics, are statistically valid, and the explanatory power (indicated by
9 The correlation matrix reveals that there is one correlation coefficient higher than 0.4. We run two different regression models to ensure that correlated independent variables (FIRST and FIRMSIZE) are regressed in separate models. We define (i) two specifications of Eq. (1), named models 1 and 2; (ii) two specifications of Eq. (2), named models 3 and 4.
Table 3 Descriptive statistics.
Variables Frequency Mean (Standard deviation)
DISCPR Press release 30.0% No press release 70.0%
REASON Proactive operations 40.0% Reactive operations 60.0%
FIRST First downsizing 45.0% Multiple downsizing operations 55.0%
DOWNSIZE % of employees laid off announced 0.0339 (0.071)
LAYOFF Layoffs 55.1% Voluntary measures 44.9%
SENSIND Sensitive industries 25.0% Other industries 75.0%
MIMETPR Number of press releases announcing downsizing operations issued by firms within the same industry for the previous year
2.2100 (2.406)
MIMET Number of downsizing operations announced by firms of the same industry in the previous year 10.2400 (8.743)
LABOR Labor charges / net sales 0.3546 (1.215)
CRISIS Downsizing operations in crisis periods 50.0% Downsizing operations in expansion periods 50.0%
FORINV % of shares held by foreign investors 0.1320 (0.185)
FIRMSIZE Logarithm of the total assets 15.1400 (2.415)
FRSALES % of net sales realized in France 0.4818 (0.298)
BM Book-to-market ratio 0.6854 (0.611)
Table 4 Difference in reason for the operation between disclosing and non-disclosing firms.
DISCPR = 1 DISCPR = 0
REASON Proactive 29.67% 70.33% Reactive 29.41% 70.59%
Pearson Chi-Squared: 0.002 (0.541)
DISCPR = disclosure of a press release; REASON = proactive/reactive operations.
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Nagelkerke-R2) for the two models is 21.50% and 31.40%, respectively. Model 1 correctly classifies 75.4% of the observations while Model 2 correctly classifies 77.7% of the cases. Each of these is higher than the 70.2% classification rate for a naïve model (i.e., all firms decide not to disclose a press release).
Contrary to H1, the variable REASON is not statistically significant. One potential explanation is that disclosure related to reactive operations can address potential concerns from investors about the firms’ financial situation. Results also reveal that the disclosure of a press release is more likely for firms that implement a downsizing for the first time during the period studied (model 1: p < 0.01). The probability of the disclosure of press releases decreases when downsizing operations are implemented through layoffs rather than voluntary measures (model 1: p < 0.05; model 2: p < 0.01). Disclosure is a means for firms to protect their legitimacy by showing that they do their best to prevent negative consequences of downsizing oper- ations for employees. Conversely, the probability of disclosing a press release is higher for firms that belong to socially sen- sitive industries than for firms in other industries (model 1: p < 0.1; model 2: p < 0.05). This result is in accordance with the previous literature suggesting that firms in sensitive industries are more likely to face legitimacy issues than firms in other industries because their activities are likely to have impact upon society, which result in more voluntary disclosures (e.g., Patten, 1992; Adams et al., 1998). In contrast, the probability of disclosure decreases when the operation is announced in a crisis compared to an expansion period (models 1 and 2: p < 0.01). One potential reason for this latter finding is that firms’ financial difficulties increase in crisis periods and thus the need for legitimation is lower than in economic expansion periods.
Table 5 Determinants of the disclosure of press releases to announce downsizing operations.
Variables Model 1 Model 2
Coefficients Wald (p-value) Coefficients Wald (p-value)
REASON 0.123 0.128 (0.720) �0.007 0.000 (0.984) FIRST 1.132 9.429 (0.002)***
DOWNSIZE 2.161 0.733 (0.392) �1.217 0.200 (0.655) LAYOFF �0.682 3.840 (0.050)** �1.249 9.686 (0.002)***
SENSIND 0.634 2.996 (0.083)* 0.814 4.442 (0.035)**
MIMETPR 0.024 0.115 (0.734) �0.055 0.489 (0.484) LABOR 0.540 0.654 (0.419) 0.183 0.340 (0.560) CRISIS �0.921 6.723 (0.010)*** �1.092 8.460 (0.004)*** FORINV 2.273 6.886 (0.009)*** 2.983 9.595 (0.002)***
FRSALES 0.334 0.302 (0.583) �0.455 0.456 (0.499) FIRMSIZE �0.517 23.831(0.000)*** BM �0.325 1.139 (0.286) �0.224 0.515 (0.473) Intercept �1.438 8.103 (0.004)*** 7.815 17.176 (0.000)*** Nagelkerke R2 0.215 0.314 Chi-Squared (p-value) 36.509 55.535
(0.000) (0.000) Classification rate (overall%) 75.4% 77.7%
REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWNSIZE = size of the downsizing; LAYOFF = downsizing operations made through layoffs; SENSIND = sensitive industries; MIMETPR = number of press releases disclosed by firms of the same industry to announce downsizing operations; LABOR = labor charges/turnover; CRISIS = economic crisis/expansion periods; FORINV = foreign investors; FRSALES = net sales realized in France; FIRMSIZE = firm size; BM = book-to-market ratio. *** Indicate significance at the 1% levels, respectively. ** Indicate significance at the 5% levels, respectively. * Indicate significance at the 10% levels, respectively.
248 E. Nègre et al. / J. Account. Public Policy 36 (2017) 239–257
Results also indicate that the variables DOWNSIZE, MIMETPR, LABOR are not statistically significant. These findings sug- gest that the probability of disclosing a press release to announce a downsizing is not explained by the will of the firm to mimic the disclosure practices of other firms. Similarly, the visibility of the operation proxied by its size does not influence the firm’s decision to disclose a press release to announce a downsizing, as well as labor pressures.
With regards to control variables, we find a positive relation between foreign investors and the probability of issuing a press release (models 1 and 2: p < 0.01). We also find that the disclosure of a press release is negatively related to firm size (model 2: p < 0.01). One possible explanation for this result is the high correlation between the variables FIRST and FIRMSIZE, which means that the probability of implementing a downsizing for the first time during the period studied is higher for small firms than for large firms (and the use of press releases is due to the first-time nature of the event). Alternatively, because information asymmetry is generally greater for small firms than for large firms, small firms receive less media atten- tion and analyst coverage than large firms (Lang and Lundholm, 2000). Accordingly, they may be more likely to use discre- tionary disclosure to influence stakeholder perceptions.
In order to provide an economic interpretation of the results, we compute marginal effects (untabulated results) deter- mined as the means of the independent variables. We find that all the statistically significant variables are also economically significant. A first downsizing implementation increases the probability of disclosure by 22.65% (p < 0.01), and membership in a socially sensitive industry increases the probability of disclosure by 13.28% (p < 0.1). In contrast, downsizing operations implemented through layoffs decrease the probability of disclosure of 13.56% (p < 0.1) and events occurring during a crisis period decrease the probability of disclosure by 18.02% (p < 0.01). Finally, with respect to foreign investors and firm size, at the mean level, an increase of one standard deviation respectively increases the probability of disclosure by 44.79% (p < 0.01) and decreases the probability of disclosure by 6.9% (p < 0.01).
4.2. Effect of the use of press releases on the stock market reaction
In the second stage of our analysis we focus on the market reaction to the downsizing announcements, and overall, we find a negative, but not significant, average market reaction of �0.15% over the three-day event window. In contrast to our expectations, univariate analysis, presented in Panel A of Table 6, indicates that the average market reaction is lower when firms issue press releases to announce downsizing operations than when there is no press release. Indeed, for firms issuing a press release, the market reaction is negative (�0.89%) and statistically significant (p < 0.01), whereas the market reaction is positive (0.16%), but not significant, when there is no press release. One possible explanation for this result is that the dis- closure of press releases to announce downsizing operations increases the visibility of such operations. Given that downsiz- ing operations are generally perceived negatively by the market (e.g., Worrell et al., 1991; Lin and Rozeff, 1993; Ursel and
Table 6 Factors influencing the market reaction to downsizing announcements.
N Mean t-student Median Z Wilcoxon
Standard deviation t-statistic (p- value)
Wilcoxon statistic (p-value)
Panel A: Univariate comparisons of event-period returns DISCPR Press release 67 �0.0089 �0.0031 0.0253 �2.970 �3.270
�2.890*** �2.930*** No press release 160 0.0016 0.0013 0.0239 (0.003)*** (0.001)***
0.834 1.378
REASON Proactive operations 91 0.0020 0.0014 0.02437 1.779
(0.077)* 1.833 (0.067)*
0.792 1.124 Reactive operations 136 �0.0039 �0.0011 0.02475
�1.838* �1.555
Panel B: Multivariate analyses of event-period returns Variables Model 3 Model 4 Model 5
Coef. t (p-value) Coef. t (p-value) Coef. t (p-value)
DISCPR �0.144 �2.082 (0.039)** �0.199 �2.674 (0.008)***
REASON 0.113 1.712 (0.088)* 0.115 1.722 (0.086)* 0.131 1.644 (0.102) FIRST �0.190 �2.657 (0.008)*** �0.191 �2.660 (0.008)*** DOWNSIZE �0.023 �0.340 (0.734) �0.076 �1.033 (0.303) �0.021 �0.313 (0.755) LAYOFF �0.022 �0.323 (0.747) �0.084 �1.134 (0.258) �0.022 �0.325 (0.745) SENSIND 0.050 0.755 (0.451) 0.059 0.873 (0.383) 0.052 0.789 (0.431) MIMET 0.123 1.809 (0.072)* 0.130 1.864 (0.064)* 0.128 1.848 (0.066)*
CRISIS 0.036 0.523 (0.602) �0.025 �0.357 (0.721) 0.034 0.496 (0.621) FORINV 0.092 1.379 (0.169) 0.120 1.748 (0.082)* 0.091 1.364 (0.174) FIRMSIZE �0.053 �0.600 (0.549) BM 0.070 1.022 (0.308) 0.077 1.110 (0.268) 0.066 0.960 (0.338) Proactive*DISCPR �0.126 �1.660 (0.098)* Reactive*DISCPR �0.102 �1.405 (0.162) Intercept �0.005 �1.109 (0.269) 0.003 0.165 (0.869) �0.005 �1.166 (0.245)
N 225 225 225 Adjusted R2 (Fisher) 0.082 (2.996)*** 0.053 (2.257)** 0.049 (2.056)**
Durbin-Watson 1.854 1.851 1.857
DISCPR = disclosure of a press release; REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWNSIZE = size of the downsizing; LAYOFF = downsizing operations made through layoffs; SENSIND = sensitive industries; MIMET = number of down- sizing operations announced by firms within the same industry; CRISIS = economic crisis/expansion periods; FORINV = foreign investors; FIRMSIZE = firm size; BM = book-to-market ratio; Proactive*DISCPR = proactive operations announced by press releases; Reactive*DISCPR reactive operations announced by press releases. *** Indicate significance at the 1% levels, respectively. ** Indicate significance at the 5% levels, respectively. * Indicate significance at the 10% levels, respectively.
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Armstrong-Stassen, 1995; Lee, 1997; Elayan et al., 1998), the negative market reaction to these operations should be higher in the case of high visibility. The univariate analyses also reveal that the market reaction to proactive operations is positive (0.20%) but not significant, whereas the market reaction to reactive operations is negative (�0.39%) and statistically signif- icant (p < 0.1).
Results of the regression analysis focusing on explaining differences in the market reactions, presented in Panel B of Table 6, confirm the univariate analyses in that the press release variable (DISCPR) is negative and statistically significant (model 3: p < 0.05; model 4: p < 0.01) when controlling for other potential determinants of the market reaction to such oper- ations. This is contrary to H2. Results also indicate that the market reaction to downsizing announcements is positively asso- ciated with proactive operations (models 3 and 4), although the REASON variable is significant at only p < 0.1. Further, when cases where the downsizing related to merger and acquisition (six observations) are removed, this relation is no longer sig- nificant at conventional levels.10 Thus, in the French context it is not clear whether, as in prior investigations in other settings (e.g., Abraham, 2004) investors positively value proactive downsizing operations. Second, our results confirm that investors have a more negative reaction to a firm’s first downsizing than to subsequent downsizing operations (model 3: p < 0.01). This is in line with Lee (1997) and Capelle-Blancard and Tatu (2012) who posit that in the case of multiple downsizing operations,
10 Other results reported in the paper do not change with the removal of the merger and acquisition-related downsizing observations.
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the first downsizing contains more information, and thus, should have a greater impact on the market reaction. Consistent with Lee (1997), we obtain a positive relation between the market reaction and the number of downsizing operations announced by firms within the same industry (models 3 and 4: p < 0.1). Finally, our results show that the market reaction is positively correlated to the percentage of shares held by foreign investors (model 4: p < 0.1). All the remaining factors are not significant (DOWNSIZE, LAYOFF, SENSIND, CRISIS, FIRMSIZE and BM).
To better understand why investors react negatively to downsizing operations announced by press releases, we allow for impacts to differ across press releases disclosed to announce proactive vs. reactive operations (Proactive⁄DISCPR; Reac- tive⁄DISCPR). The results (model 5) reveal that the market reaction is more negative in the case of press releases disclosed to announce proactive operations (p < 0.1). More precisely, the disclosure of a press release leads to a reversal in the market reaction related to proactive operations. When firms disclose press releases to announce proactive operations, investors per- ceive these operations negatively, whereas they perceive proactive operations positively when there is no press release. This result suggests that investors perceive positively proactive operations but not the disclosure made by firms to announce such operations.
5. Content of press releases and consequences on the market reaction
In the final stage of our investigation, we conduct additional analyses examining the content of the press releases announcing downsizing operations and how the content relates to market reactions. The purpose of the content analysis is threefold. First, we provide evidence on the content of the press releases issued to announce downsizing operations, and then, we investigate whether the content contributes to the more negative market reaction to downsizing announce- ments disclosed through press releases. Finally, we examine whether the content of the press releases leads to a reversal in the market reaction related to proactive operations. The subsample consists of the 66 downsizing operations announced by press releases by 54 French listed firms.
5.1. Methodology
Although manual content analysis of the press releases is labor-intensive (Beattie et al., 2004), the relatively small size of the subsample allowed us to conduct an in-depth analysis of disclosures. Length of press releases varies from a minimum of 89 to a maximum of 2986 words, with an average of 679 words per press release.
Similar to Files et al. (2009), we observe varying degrees of prominence of the disclosure related to downsizing operations within press releases. Among the 66 press releases, 38 (58%) are entirely dedicated to downsizing operations, whereas 28 (42%) include additional subjects. In this latter case, the company describes the downsizing operations in the body of the press release, but the headline refers to other subjects. We take into account the prominence of the disclosure related to downsizing operations by using a variable (PROMWORD) that measures the total number of words related to the downsizing operation divided by the total number of words included in the press release. On average, 63.11% of the total number of words included in the press release is dedicated to the downsizing operation.
We next identify the reasons stated for downsizing operations. We rely on schemes used in prior studies (e.g., Capelle-Blancard and Tatu, 2012; Elayan et al., 1998; Lee, 1997) to distinguish proactive and reactive arguments and we pro- vide examples of these in Table 7. We use statements as the unit of analysis because they are more reliable than other units of analysis such as words or sentences. According to Milne and Adler (1999), individual words have no meaning to provide a sound basis for coding disclosures without a sentence or sentences for context. Given the possibility of multiple themes within the same sentence, we do not use sentences as the unit of analysis. Press releases were separately assessed by two independent coders.11 The Kappa index is 0.8 and indicates sufficient reliability (e.g., Fogarty and Rogers, 2005), and all coding differences between the two coders were resolved through discussions.
The content of press releases (PRCONT) is defined in terms of proactive and reactive arguments. Following Henry (2008), we calculate this variable as the count of proactive statements minus the count of reactive statements, divided by the sum of proactive and reactive statement counts. Therefore, a positive (negative) score indicates a higher number of proactive (reac- tive) arguments than reactive (proactive) arguments. The first specification of Eq. (2) (model 3) becomes Eq. (3):12
11 A c 12 Bec
(LAYOF
CARi ¼ b0 þ b1 PROMWORD þ b2 PRCONT þ b3 REASON þ b4 FIRST þ b5 DOWNSIZE þ b6 SENSIND þ b7 MIMET þ b8 FORINV þ b9 BM þ ei ð3Þ
With CARi = cumulative abnormal return for firm i over the event period from day 0 until day 2; PROMWORD = number of words related to the downsizing operation, divided by the total number of words in the press release; PRCONT = count of proactive statements minus count of reactive statements, divided by the sum of proactive and reactive statement counts;
opy of the coding instructions is available from the authors on request. ause of the small sample size for this analysis, we reduce the number of independent variables. Compared to model 3, we exclude one contextual factor F) and one legitimacy-related factor (CRISIS) because of the lack of significance of these variables in the previous analyses.
Table 7 Examples of proactive and reactive arguments.
Proactive arguments Reactive arguments
� Performance increase � Cost reduction � Improvement of customer satisfaction � Development of new products � Implementation of new technologies
� Financial distress � Bad market conditions � Bad sector conditions � Changes in regulatory requirements
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REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWN- SIZE = size of the downsizing; SENSIND = sensitive industries; MIMET = number of downsizing operations announced by firms within the same industry; FORINV = foreign investors; BM = book-to-market ratio; b0 = intercept; b1. . .9 = regression coefficients; ei = residual term.
5.2. Results
As highlighted in Table 8 and in support of H3, we find no significant difference between proactive and reactive opera- tions in terms of arguments used to justify downsizing operations. Both proactive and reactive operations are mainly justi- fied using reactive arguments (see negative scores). The finding that proactive operations are being justified using reactive arguments is consistent with legitimacy theory. French firms appear to engage in impression management, presumably in an effort to make proactive operations appear more acceptable for employees, unions and the public.
Next, we examine whether the content of press releases issued to announce downsizing operations influences market reactions. Table 9 reports results for two specifications of Eq. (3): models 6 and 7. Results show that the content of press releases (PRCONT) is significantly related to differences in market reactions (model 6: p < 0.05). More precisely, we find a negative relation between the market reaction and the content of press releases. Supporting H4, we find the use of more proactive arguments to justify downsizing operations is significantly associated with more negative investor reactions. In contrast, the prominence of the downsizing operation in the press release is not significantly associated with the market reaction.
Finally, to test H5, we distinguish in model 7 the content of press releases disclosed to announce proactive vs. reactive operations (Proactive⁄PRCONT; Reactive⁄PRCONT). In support of H5, we find that the more firms use proactive arguments to justify proactive operations in the press release, the more the market reacts negatively (p < 0.05). This result is also in line with the legitimacy perspective, in that investors appear to perceive negatively the use of proactive arguments to justify proactive operations, potentially because it increases the risk of additional legitimacy costs being imposed on the firms.
5.3. Sensitivity tests
5.3.1. Endogeneity concerns We first check that results are not driven by selection bias introduced when we focus on disclosing firms. To address this
endogeneity concern, we employ the Heckman (1979) selection model. We use a two-stage regression with the two speci- fications of Eq. (1) (models 1 and 2) to estimate the likelihood of disclosing a press release that announces the downsizing, and then compute an inverse Mills ratio using the parameters of this model. The inverse Mills ratio, when included in the two specifications of Eq. (3) (models 6 and 7), is not statistically significant at conventional levels, suggesting our results are not driven by endogeneity bias.
5.3.2. Controlling for the overall tone of the press releases Next, we examine whether content results are influenced by the overall tone (TONE) of press releases issued by firms to
announce downsizing operations. Consistent with Henry (2008), we measure the variable TONE by the number of positive statements minus the number of negative statements, divided by the total number of statements. Non-tabulated univariate analyses show that the market reaction is not associated with the tone of the press release (p > 0.941). The results of mul- tivariate analyses, reported in Table 10, confirm that the variable TONE does not influence the market reaction, suggesting that our primary results are not driven by confounding information disclosed in press releases.
5.3.3. Further analysis of relations during crisis period As noted above, our test period overlaps with the financial crisis of 2008 and 2009, and our results show that while sam-
ple companies were less likely to use a press release to announce their downsizing operations during those years, market reactions did not differ significantly across the crisis period. In our last set of sensitivity tests, we explore whether the impact
Table 8 Univariate comparisons of the content of press releases between proactive and reactive operations.
N Mean t-student Median Z Wilcoxon Standard deviation t-statistic (p-value) Wilcoxon statistic (p-value)
Proactive operations 27 �0.2947 �0.3333 0.6151 �0.590 �0.560 �2.490** �2.406**
Reactive operations 40 �0.2045 �0.3333� 0.6125 0.557) (0.575) �2.112** 1.831*
Proactive (reactive) operations are implemented by firms with an increase (a decrease) in the ROA for the previous year. PRCONT = count of proactive statements minus count of reactive statements, divided by the sum of proactive and reactive statement counts.
** Indicate significance at the 5% levels, respectively. * Indicate significance at the 10% levels, respectively.
Table 9 Content analysis and multivariate analysis of event-period returns [�120; �20].
Variables Model 6 Model 7
Coef. t (p-value) Coef. t (p-value)
PROMWORD 0.082 0.654 (0.516) 0.035 0.279 (0.781) PRCONT �0.271 �2.059 (0.044)** REASON 0.057 0.472 (0.638) �0.028 �0.215 (0.831) FIRST �0.203 �1.450 (0.153) �0.177 �1.275 (0.208) DOWNSIZE �0.140 �1.120 (0.267) �0.115 �0.922 (0.360) SENSIND 0.163 1.277 (0.207) 0.199 1.557 (0.125) MIMET 0.135 1.085 (0.282) 0.151 1.230 (0.224) FORINV 0.168 1.364 (0.178) 0.145 1.188 (0.240) BM 0.199 1.626 (0.110) 0.200 1.658 (0.103) Proactive*PRCONT �0.336 �2.562 (0.013)** Reactive*PRCONT �0.080 �0.606 (0.547) Intercept �0.021 �2.375 (0.021)** �0.020 �2.251 (0.028)**
N 66 66 Adjusted R2 (Fisher) 0.117 (1.958)* 0.140 (2.055)**
Durbin-Watson 2.391 2.311
PROMWORD = number of words related to the downsizing operation, divided by the total number of words in the press release; PRCONT = count of proactive statements minus count of reactive statements, divided by the sum of proactive and reactive statement counts; REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWNSIZE = size of the downsizing; SENSIND = sensitive industries; MIMET = number of downsizing operations announced by firms within the same industry; FORINV = foreign investors; BM = book-to-market ratio; Proactive*PRCONT = content of press releases disclosed to announce proactive operations; Reactive*PRCONT = content of press releases disclosed to announce reactive operations. ***Indicate significance at the 1% levels respectively.
** Indicate significance at the 5% levels respectively. * Indicate significance at the 10% levels respectively.
252 E. Nègre et al. / J. Account. Public Policy 36 (2017) 239–257
of our independent variables differed during the financial crisis relative to periods of more normal economic operations. To examine this issue, we construct interaction terms using CRISIS and all combinations of the other independent variables used in the prior analyses. Our results (non-tabulated) indicated only one of the crisis period interaction terms was statistically significant at conventional levels. The CRISIS⁄PRCONT variable was negatively signed statistically significant (p < 0.05) in the analysis of differences in market reaction across press release content (original model 6). This finding indicates that investors reacted more negatively to the use of proactive arguments in the press releases during the financial crisis than during other sample years, supporting the position that investors see the use of that tactic as increasing legitimacy threats even more dur- ing periods of financial downturn.
6. Discussion and conclusions
In this study we investigate the determinants and consequences of French firms’ decisions to use press releases to announce downsizing operations. We also examine the content of press releases and its influence on investor reactions to downsizing announcements. The French context is a unique setting to study downsizing operations as it is characterized by extensive legal protections for workers, a strong protest culture, and a high strike rate. From a legitimacy point of view,
Table 10 Content analysis and market reaction after controlling for the tone of the press release.
Variables Model 6 bis Model 7 bis
Coef. t (p-value) Coef. t (p-value)
TONE 0.168 1.208 (0.232) 0.145 1.040 (0.303) PROMWORD 0.093 0.742 (0.461) 0.048 0.380 (0.705) PRCONT �0.362 �2.395 (0.020)** REASON 0.057 0.474 (0.637) �0.021 �0.163 (0.871) FIRST �0.221 �1.579 (0.120) �0.195 �1.394 (0.169) DOWNSIZE �0.143 �1.151 (0.255) �0.119 �0.961 (0.341) SENSIND 0.170 1.336 (0.187) 0.202 1.582 (0.119) MIMET 0.126 1.016 (0.314) 0.143 1.155 (0.253) FORINV 0.166 1.356 (0.181) 0.146 1.192 (0.238) BM 0.179 1.453 (0.152) 0.183 1.500 (0.139) Proactive*PRCONT �0.377 �2.755 (0.008)*** Reactive*PRCONT �0.153 �1.021 (0.312) Intercept �0.023 �2.587 (0.012)** �0.022 �2.427 (0.019)**
N 66 66 Adjusted R2 (Fisher) 0.124 (1.923)* 0.141 (1.969)**
Durbin-Watson 2.396 2.322
TONE = number of positive statements minus the number of negative statements, divided by the total number of statements; PROMWORD = number of words related to the downsizing operation, divided by the total number of words in the press release; PRCONT = count of proactive statements minus count of reactive statements, divided by the sum of proactive and reactive statement counts; REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWNSIZE = size of the downsizing; SENSIND = sensitive industries; MIMET = number of downsizing operations announced by firms within the same industry; FORINV = foreign investors; BM = book-to-market ratio; Proactive*PRCONT = content of press releases disclosed to announce proactive operations; Reactive*PRCONT = content of press releases disclosed to announce reactive operations. *** Indicate significance at the 1% levels respectively. ** Indicate significance at the 5% levels respectively. * Indicate significance at the 10% levels respectively.
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these operations thus constitute highly threatening events for firms, particularly when they are proactive. We find that French firms are more likely to issue press releases when they implement a downsizing for the first time during the period studied and when they belong to sensitive industries. In contrast, the probability of disclosure decreases for downsizing operations implemented through layoffs and during crisis periods. Overall, these results show that the French company use of press releases to announce workforce reductions is driven by both contextual and legitimacy factors. Next, we find that the average market reaction to downsizing operations announced by press releases is significantly more negative than the average market reaction to announcements where there is no press release (i.e., downsizing operations are announced by the media). We also provide evidence that the market reaction is more negative where the press releases announce proactive as opposed to reactive operations.
In order to better understand why the market reacts negatively when firms issue press releases, we examine the content of the press releases in terms of proactive and reactive arguments. First, we find that French firms, on average, adopt a reac- tive impression management strategy in their press releases as they mainly use reactive arguments to justify these opera- tions, even when the downsizing operations are proactive. This evidence suggests that firms may be using impression management to maintain organizational legitimacy. As noted by Love and Kraatz (2009), proactive operations are less well received by employees, unions and the public because they are implemented without apparent financial need. The need for legitimation is thus stronger in proactive than in reactive operations, and our results suggest firms use reactive arguments in these cases to potentially reduce their legitimacy threats. We further show that investors react more negatively to the use of proactive arguments for proactive operations indicating that French investors interpret the use of reactive arguments in such cases as reducing the exposure to the potential legitimacy costs of proactive downsizing operations. Overall, we show that in the French case, the disclosure strategies and their consequences on the financial markets relate to a legitimacy perspective. Both proactive and reactive operations are mainly justified by reactive arguments and the market reacts negatively to the use of proactive arguments presumably because they fail to reduce the risk of legitimacy damage.
Like all studies, this examination is subject to certain limitations. First, we focus on the study of disclosure at the time of the announcement of downsizing operations. However, it could also be interesting to examine the subsequent disclosures made by firms, for instance during the downsizing process. This should lead us to consider disclosure as a dynamic and mutual influence process. Indeed, it is likely that a firm’s disclosure interacts with both the unions’ disclosure and the media. Second, our investigation is limited to an analysis of archival data. Interviews with managers, heads of investor relations, or heads of financial communication could potentially reveal additional insight into companies’ use of press release disclosure at the time of downsizing operations. Of course, too, we examine only the French context in this study. Examining the extent
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to which companies in other countries sensitive to employee issues use disclosure related to workforce reductions would prove valuable. Overall, by providing evidence of disclosure strategies and their impact on market reactions, this study con- tributes to the literature on CSR/sustainability and encourages future research on accounting choices in social contexts.
Acknowledgments
The authors wish to thank Editors Lawrence Gordon and Martin Loeb, Salvador Carmona, one anonymous reviewer, two anonymous participants (A and B) of the JAPP Conference, Isabelle Martinez, Niamh Brennan, Amy Hageman (discussant at the 2016 Conference of the American Accounting Association’s Public Interest Section Mid-Year Meeting) and the partici- pants of the 36th French Accounting Association Annual Meeting, the 3rd French Conference on Social and Environmental Accounting Research, the 38th European Accounting Association Annual Congress, the 2016 Conference of the American Accounting Association’s Public Interest Section Mid-Year Meeting for their valuable comments and suggestions provided on earlier versions of this paper. We also thank the ‘‘Labex Entreprendre” (Responsible Management and Entrepreneurship Chair), Montpellier Research in Management and the ESSEC Research Centre (CERESSEC) for financial support.
Appendix A. Event study methodology
The abnormal return for firm i on day t is equal to the difference between the observed return and the expected return for firm i on day t. Expected return is defined as that expected if the event did not take place.
ARit ¼ Rit � EðRitÞ
With ARit = abnormal return for firm i on day t; Rit = observed return for firm i on day t; E(Rit) = expected return for firm i on day t.
The observed return is:
Rit ¼ log½ðPit þ DitÞ=Pit � 1�
With Rit = return on the share price of firm i on day t; Pit = share price of firm i on day t; Dit = dividend paid on firm i’s shares on day t; Pit � 1 = share price of firm i on day t � 1.
For the estimation of the expected return, two benchmark models are used: the index model (1) and the market model (2). The expected return for firm i on day t is:
EðRitÞ¼ Rmt ðA:1Þ
or
EðRitÞ¼ ai þ biRmt ðA:2Þ
With E(Rit) = expected return for firm i on day t; Rmt = return on the CAC All-Tradable index on day t. In Eq. (A.2), the parameters ai and bi are OLS values that are calculated using an estimation period running from trading
days �180 to �20 prior to the event period (t = 0 is the event date). Average abnormal returns for each relative day are calculated by:
AARt ¼ð1=NÞ XN
i¼1 ARit
With ARit = abnormal return for firm i on day t. The cumulative average abnormal return over the event period from k days until l days is given by the equation below:
CAARk;l ¼ Xl
t¼k AARt
With AARt = Average Abnormal Return on day t.
Appendix B. Correlation matrix
DISCPR REASON FIRST DOWNSIZE LAYOFF SENSIND MIMETPR MIMET LABOR CRISIS FORINV FRSALES FIRMSIZE BM
DISCPR 0.003 0.173⁄⁄⁄ 0.147⁄⁄ �0.017 0.138⁄⁄ �0.033 �0.091 0.135⁄⁄ �0.148⁄⁄ 0.172⁄⁄⁄ 0.082 �0.292⁄⁄⁄ �0.136⁄⁄ REASON 0.003 0.02 0 �0.02 0.003 �0.110⁄ �0.092 0.081 0.185⁄⁄⁄ 0.097 �0.09 �0.018 0 FIRST 0.173⁄⁄⁄ 0.02 0.249⁄⁄⁄ 0.228⁄⁄⁄ �0.033 �0.098 �0.084 0.106 0.226⁄⁄⁄ �0.073 0.247⁄⁄⁄ �0.478 �0.028 DOWNSIZE 0.165⁄⁄ �0.043 0.231⁄⁄⁄ 0.130⁄ �0.045 0.011 �0.008 0.296⁄⁄⁄ 0.033 0.006 0.344⁄⁄⁄ �0.449⁄⁄⁄ 0.092 LAYOFF �0.017 �0.02 0.228⁄⁄⁄ 0.109 0.013 �0.046 �0.037 0.103 �0.067 0.038 0.214⁄⁄⁄ �0.389⁄⁄⁄ �0.012 SENSIND 0.138⁄⁄ 0.003 �0.033 �0.160⁄⁄ 0.013 �0.043 �0.128⁄ 0.001 �0.094 0.104 �0.104 0.091 �0.052 MIMETPR 0.001 �0.184⁄⁄⁄ �0.153⁄⁄ �0.003 �0.049 0.037 0.863⁄⁄⁄ �0.075 0.088 0.03 �0.092 �0.1 0.236⁄⁄⁄ MIMET �0.121⁄ �0.112⁄ �0.111⁄ �0.025 �0.06 �0.139⁄⁄ 0.742⁄⁄⁄ �0.08 0.027 �0.018 0.005 �0.05 0.293⁄⁄⁄ LABOR 0.111⁄ �0.109 0.164⁄⁄ 0.260⁄⁄⁄ 0.216⁄⁄⁄ 0.017 0.041 �0.037 �0.082 0.031 0.186⁄⁄⁄ �0.176⁄⁄⁄ �0.053 CRISIS �0.148⁄⁄ 0.185⁄⁄⁄ 0.226⁄⁄⁄ 0.094 �0.067 �0.094 �0.02 0.124⁄ �0.041 �0.042 �0.044 �0.164⁄⁄ 0.044 FORINV 0.123⁄ 0.026 �0.116⁄ �0.036 0.01 0.114⁄ 0.014 �0.082 �0.127⁄ �0.077 �0.147⁄⁄ 0.101 �0.133⁄⁄ FRSALES 0.046 �0.083 0.233⁄⁄⁄ 0.253⁄⁄⁄ 0.203⁄⁄⁄ �0.125⁄ �0.107 0.068 0.205⁄⁄⁄ �0.02 �0.214⁄⁄⁄ �0.435⁄⁄⁄ 0.104 FIRMSIZE �0.290⁄⁄⁄ �0.028 �0.501⁄⁄⁄ �0.425⁄⁄⁄ �0.383⁄⁄⁄ 0.093 �0.108 �0.083 �0.434⁄⁄⁄ �0.188⁄⁄⁄ 0.175⁄⁄⁄ �0.335⁄⁄⁄ 0.005 BM �0.137⁄⁄ 0.035 �0.049 0.025 �0.008 �0.024 0.181⁄⁄⁄ 0.246⁄⁄⁄ �0.008 0.079 �0.152⁄⁄ 0.052 0.047
Pearson (Spearman) correlation coefficients are presented below (above) the diagonal. The coefficients in bold are all higher than 0.5. DISCPR = disclosure of a press release; REASON = proactive/reactive operations; FIRST = first downsizing implemented by the firm over the period studied; DOWNSIZE = size of the downsizing; LAYOFF = downsizing operations implemented through layoffs; SENSIND = sensitive industries; MIMETPR = number of press releases disclosed by firms of the same industry to announce downsizing operations; MIMET = number of downsizing operations announced by firms of the same industry; LABOR = labor pressures; CRISIS = economic crisis/expansion periods; FORINV = foreign investors; FRSALES = net sales realized in France; FIRMSIZE = firm size; BM = book-to-market ratio.
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256 E. Nègre et al. / J. Account. Public Policy 36 (2017) 239–257
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- Disclosure strategies and investor reactions to downsizing announcements: A legitimacy perspective
- 1 Introduction
- 2 Theoretical framework, literature review and hypotheses development
- 2.1 Legitimacy and the social contract
- 2.2 Downsizing operations
- 2.2.1 The decision to use press releases: determinants and stock market reaction
- 2.2.2 Content of the press releases and stock market reaction
- 3 Research method
- 3.1 Dependent variables
- 3.2 Independent and control variables
- 3.2.1 Determinants of the use of press releases
- 3.2.2 Stock market reaction to the use of press releases
- 3.3 Models
- 3.4 Sample selection and descriptive statistics
- 4 Results
- 4.1 Determinants of the use of press releases to announce downsizing operations
- 4.2 Effect of the use of press releases on the stock market reaction
- 5 Content of press releases and consequences on the market reaction
- 5.1 Methodology
- 5.2 Results
- 5.3 Sensitivity tests
- 5.3.1 Endogeneity concerns
- 5.3.2 Controlling for the overall tone of the press releases
- 5.3.3 Further analysis of relations during crisis period
- 6 Discussion and conclusions
- Acknowledgments
- Appendix A Event study methodology
- Appendix B Correlation matrix
- References
ORIGINAL EMPIRICAL RESEARCH
Customer reactions to downsizing: when and how is satisfaction affected?
Johannes Habel & Martin Klarmann
Received: 18 May 2013 /Accepted: 14 July 2014 /Published online: 19 August 2014 # Academy of Marketing Science 2014
Abstract Organizational downsizing to cut costs frequently creates new, “hidden costs” that neutralize potential increases in productivity. Customer dissatisfaction is such an overlooked downsizing outcome. Using longitudinal data from the American Customer Satisfaction Index (ACSI), Compustat, and a consumer survey this study analyzes satis- faction outcomes of downsizing. It extends research in this domain to B2C markets and explicitly addresses environmen- tal influences on the downsizing–satisfaction link. Results indicate that there is a negative effect of downsizing on customer satisfaction. It is particularly pronounced for com- panies (1) with little organizational slack, (2) with high labor productivity, or (3) in industries with high R&D intensity. Moreover, downsizing has a stronger negative impact on customer satisfaction in product categories with (4) high risk importance and (5) low probability for consumer errors as well as (6) low level of brand consciousness. Furthermore, customer satisfaction mediates the effect of downsizing on financial performance. The results provide an explanation for
why so many downsizing projects fail and what managers can do to prevent adverse effects of downsizing on customer satisfaction and financial performance.
Keywords Customer satisfaction . Organizational downsizing . Firm performance . Panel data analysis
Introduction
In a “Group Strategy Update,” Australian airline Qantas an- nounced on February 26, 2014, plans to cut 5,000 jobs (Qantas 2014). In the same week, the Financial Times report- ed plans that IBM was to reduce its U.S. workforce by 13,000 to 15,000 employees (Waters 2014). Hence, downsizing con- tinues to be one of the most appealing cost-cutting strategies to firms worldwide. Firms typically expect that the layoffs will improve financial performance. For instance, Qantas (2014) explicitly states in their media release that the “long-term goal” of the cost reductions is “the transformation of the Qantas Group for profitable, sustainable growth.”
The importance of downsizing in business practice has motivated many academic studies. In a comprehensive review, Datta et al. (2010) identify four major research streams. Two of them look at environmental and organizational antecedents of downsizing. The other two address its consequences. Of the streams addressing the consequences of downsizing, the first looks at organizational outcomes. Chadwick, Hunter, and Walston (2004, p. 406) summarize: “The general consensus among researchers over the last two decades is that organiza- tional performance is as likely to suffer as it is to improve after downsizing.” The second addresses outcomes at the employee level. Here, Datta et al. (2010, p. 307) conclude that “[d]ownsizing has a significant potential to … disrupt rela- tionship networks, and destroy the trust and loyalty that binds employees and their employers.”
Article note The authors wish to thankMartin Artz, Christian Homburg, Sabine Staritz, participants of the AMA Summer Marketing Educators’ Conference 2012 in Chicago, participants of the second German-French Customer Empowerment workshop 2013 at the Karlsruhe Institute of Technology (KIT), as well as the three anonymous reviewers and Tomas Hult for their valuable insights and comments on earlier drafts of the manuscript.
J. Habel ESMT European School of Management and Technology, Berlin, Germany
M. Klarmann (*) Institute of Information Systems and Marketing (IISM) at the Karlsruhe Institute of Technology (KIT), Zirkel 2, Building 20.21, Room 104, 76131 Karlsruhe, Germany e-mail: [email protected]
J. Habel Ruhr-University Bochum, Bochum, Germany
J. of the Acad. Mark. Sci. (2015) 43:768–789 DOI 10.1007/s11747-014-0400-y
Interestingly, despite Cascio’s (2005, p.45) advice to “think through the potential consequences of restructuring on cus- tomers,” in their review Datta et al. (2010) identify only two papers that examine the effect of downsizing on customers (out of a total of 91). Recently, more research has been conducted in the area. For example, Subramony and Holtom (2012) report that downsizing reduces customer orientation, which translates into a negative effect on customers’ brand perceptions. However, the focus of research lies on the effect of downsizing on customer satisfaction. Table 1 provides an overview.
As shown in Table 1, researchers consistently report nega- tive effects of downsizing on customer satisfaction. That being said, most evidence comes from B2B samples (Lewin 2009; Lewin and Johnston 2008; Lewin et al. 2010; Williams et al. 2011) or samples with a prominent B2B share (Homburg et al. 2012; Wagar 1998). One is from the financial services sector (McElroy et al. 2001).
Hence, previous research in the area is almost exclu- sively based on environments where personal interaction between employees and customers is important. Here, the internal disruption caused by downsizing will be a particular threat to delivering quality. Through processes
like emotional contagion (e.g., Henning-Thurau et al. 2006), negative job satisfaction outcomes may translate into negative customer satisfaction (e.g., Homburg and Stock 2004). However, elsewhere the relationship may be much more complex. While pointing to personal interaction as differentiator, Anderson et al. (1997) find that productivity improvements (which can be achieved through downsizing) are negatively related to customer satisfaction for services, but positively related for manufactured goods. Homburg et al. (2012) find that customer uncertainty following downsizing is much larger if customers interact frequently with their contact employees from the downsizing firm.
We are interested whether the negative effect of downsizing on customer satisfaction generalizes to other contexts. For our sample we draw on American Customer Satisfaction Index (ACSI) data, which is collected for many product categories (e.g., food, appliances, apparel, internet services, cars), where customers interact less with firm employees. We argue that in the industries covered by the ACSI, the effect of downsizing on customer satis- faction is far less intuitive than in B2B environments. In particular, we expect that the degree to which employees
Table 1 Literature on the effect of downsizing on customer satisfaction
Study Context Data Method Findings
Homburg et al. (2012)
B2B/ B2C
Cross-sectional survey data of 109 managers in companies which had undergone downsizing, 2 scenario experiments with students
Regression analyses
Downsizing increases customer uncertainty, which in turn reduces customer satisfaction. The degree of customer uncertainty further depends on how open a company communicates the downsizing vis-à-vis customers, how strong informal ties between customers and customer-contact employees are, and how important products are for customers.
Lewin (2009) B2B Cross-sectional survey data of 560 purchasing professionals evaluating their downsized/non- downsized suppliers
Structural equation models
Purchasing professionals perceive the performance of downsized suppliers as weaker and are less satisfied and loyal.
Lewin et al. (2010)
B2B Cross-sectional survey data of 435 purchasing professionals evaluating their downsized/non- downsized suppliers
Structural equation models
Purchasing professionals perceive the performance of downsized suppliers as weaker and are less satisfied and loyal. The results partly differ for different cultural contexts (United States vs. Europe).
Lewin and Johnston (2008)
B2B Cross-sectional survey data of 560 purchasing professionals evaluating their downsized/non- downsized suppliers
t tests, analyses of variance
Purchasing professionals perceive the performance of downsized suppliers as weaker and are less satisfied and loyal. However, they evaluate the suppliers with medium rates of personnel reduction as better than suppliers with low or high rates of personnel reduction.
McElroy et al. (2001)
B2C Cross-sectional survey data of customers of 31 regional subunits of a financial services company
Correlation analysis
Downsizing is negatively correlated to customer satisfaction.
Wagar (1998) B2B/ B2C
Key informant surveys of 1,907 establishments covering all major sectors of the Canadian economy
Ordered probit estimation
Downsizing reduces employer efficiency, which is calculated as the sum of customer satisfaction, productivity, and product/service quality.
Williams et al. (2011)
B2B Telephone survey data of 534 service customers before and 994 customers after a downsizing event of one specific company
t tests Average customer satisfaction and retention after the downsizing event is significantly lower than customer satisfaction before the downsizing event.
J. of the Acad. Mark. Sci. (2015) 43:768–789 769
are a crucial resource to the downsizing firm will affect the downsizing–satisfaction link. For instance, if the firm has enough excess resources (“organizational slack,” Love and Nohria 2005), product quality is less likely to suffer through downsizing and customers might even ben- efit from reduced prices. Hence, customer satisfaction might not be negatively affected by downsizing. To ac- count for effects like this we analyze measures of the downsizing firm’s resources as moderators of the downsizing–satisfaction link.
Moreover, whether customers respond negatively to downsizing will also depend on what they learn of the downsizing (Homburg et al. 2012). Only if they devote a certain amount of time and attention to a product category might they notice quality deficiencies resulting from downsizing. Likewise, for signaling effects (Love and Kraatz 2009) as well as reputational effects of downsizing (Flanagan and O’Shaughnessy 2005; Zyglidopoulos 2005) to affect satisfaction, typically re- quires that customers follow the business press. To account for these effects, we analyze customers’ product category involvement and customers’ purchase criteria as moderators of the downsizing–satisfaction link.
Finally, we are interested whether customer outcomes to downsizing require firms to reconsider downsizing as a man- agement instrument. Therefore, we link customer satisfaction after downsizing to firm performance.
To test our hypotheses, we use data from three sources: (1) As mentioned before, we use ACSI data to measure customer satisfaction. (2) We measure downsizing, firm performance, and the firm’s resource situation using the Computstat data- base. (3) To measure customer product category involvement and customer purchase criteria, we collected survey data from over 1,500 U.S. consumers. As a result we have a longitudinal dataset with data from 1994 to 2007 (before the financial crisis) from over 100 companies, covering more than 150 downsizing events.
Our research makes at least four contributions to the discipline. First, we extend research on customer re- sponses to downsizing from contexts with much em- ployee–customer interaction to less interactive B2C en- vironments. Second, we identify environmental condi- tions related to the downsizing firm’s resources and customer information processing that determine whether downsizing has a negative impact on customer satisfac- tion. Thus, we facilitate predictions regarding potential problems resulting from downsizing. Third, by employing longitudinal data, our study addresses causal- ity issues. Previous findings on satisfaction outcomes to downsizing come almost invariably from cross-sectional designs. Fourth, by linking customer responses to downsizing with financial performance, our study im- proves the understanding of the ambiguous results on
performance implications of downsizing. If customer outcomes depend on contextual factors, this helps un- derstand mixed performance effects of earlier research.
Conceptual framework
Figure 1 depicts our conceptual framework. It is a causal chain leading from downsizing via customer sat- isfaction to financial performance. Twelve contextual factors moderate the link between downsizing and cus- tomer satisfaction.
We define downsizing as major workforce reductions to cut costs and to improve productivity and consequently financial performance (Freeman and Cameron 1993). The typical rationale behind downsizing is to maintain output levels in terms of product and service quality while using less input—that is, labor—thereby cutting costs. However, as companies may find it difficult to maintain quality levels after downsizing, it could affect customer satisfaction, defined as a “cumulative evaluation of a firm’s market offering” (Fornell et al. 1996, p. 8).
A key conceptual idea behind this paper is that the relationship between downsizing and customer satisfac- tion may not always be negative. In environments where customer interaction with firm employees is not com- mon, we expect that two types of contextual factors influence the downsizing–satisfaction link: (1) variables relating to the resources of the firm and (2) variables related to consumer information processing in the buy- ing process. Overall, we expect that downsizing’s nega- tive effect on customer satisfaction will depend on the degree to which the downsized employees are crucial in line with the resource-based view of the firm (Kozlenkova et al. 2014). And in particular, we expect that downsizing’s negative effect on customer satisfac- tion will depend on the degree to which customers can perceive the downsizing and believe it to be important information.
Concerning the downsizing firm’s resources, we con- sider two sets of variables. The first consists of mea- sures of a company’s resource dependency. Prior downsizing research has identified three key factors in this regard: (1) Firms can shield themselves against disruptions of their resources through organizational slack, defined as “resources in excess of those required to produce necessary outputs” (Love and Nohria 2005, p. 1087). (2) Negative downsizing outcomes are more likely if a firm’s labor productivity, defined as the amount of output per unit of labor (Koch and McGrath 1996), is high. (3) Firms are particularly af- fected by negative affect in the workforce if they de- pend on innovation. This is captured by industry R&D
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intensity, defined as average firm expenditures for re- search and development in an industry (Guthrie and Datta 2008).
The second set of resource-related variables concerns the company’s resource history. A key concept of the resource-based view is path dependence (Vergne and Durand 2010). It posits that history is an important factor driving the outcome of firm decisions (Sydow et al. 2009)—or, in other words, “history matters” (Vergne and Durand 2010, p. 741).
Building on the concept of path dependence, we argue that the effect of downsizing on customer satisfaction depends on at least two past events. First, we include prior downsizing, defined as the occurrence of another major workforce reduction that took place before the downsizing. Second, we include prior losses, defined as negative earn- ings before interest and taxes in the year prior to the downsizing.
Concerning consumer information processing, we also consider two sets of variables. The first set consists of different aspects of customers’ product category involvement, as “de- pending on their level of involvement, individual consumers differ in the extent of their decision process and their search for information” (Laurent and Kapferer 1985, p. 41). Drawing on Laurent and Kapferer’s (1985, Kapferer and Laurent 1993) original scale, we distinguish five dimensions of involvement: (1) a customer’s interest in a product category; (2) hedonic
product value, i.e., a customer’s perception that a product category provides pleasure; (3) sign product value, i.e., a customer’s perception that a product expresses his or her self; (4) risk importance, i.e., a customer’s perception that a poor product choice leads to negative consequences; and (5) prob- ability of error, i.e., a customer’s perception that making a poor product choice is likely.
The second set of consumer-related variables comprises customers’ purchase criteria. Whether the disruption of firm resources after downsizing affects customer satisfaction should depend on what drives customer purchase decisions. We propose that two criteria are of particular relevance in this respect: service consciousness, which denotes to what extent customers place value on services vs. goods in a product category, and brand consciousness, which we define as the extent to which customers place value on brands in a product category.
Lastly, customer satisfaction is modeled as driver of company’s financial performance. It is defined as the mone- tary return a company yields on its invested capital.
Hypotheses
As mentioned before, prior research has established that on average, customer satisfaction decreases after downsizing (e.g., Homburg et al. 2012; Lewin et al. 2010). Therefore,
Customer-Related Moderators
Firm-Related Moderators
Customer Satisfaction
Downsizing Financial
Performance
• Organizational Slack H1: + • Labor Productivity H2: - • Industry R&D Intensity H3: -
Resource Dependency
Category Involvement
• Interest H6: - • Pleasure H7: - • Sign H8: + • Risk Importance H9: - • Probability of Error H10: +
Category Purchase Criteria
• Service Consciousness H11: -
• Brand Consciousness H12: +
Resource History
• Prior Downsizing H4: - • Prior Financial Loss H5: +
-a
a Prior research has established an average negative effect (e.g., Homburg et al. 2012; Lewin et al. 2010).
H13: Indirect effect of downsizing on financial
performance via customer satisfaction
Fig. 1 Conceptual framework
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our hypotheses focus on how the contextual factors depicted in Fig. 1 moderate the negative effect of downsizing on customer satisfaction.
Moderator effects pertaining to a firm’s resources
Organizational slack Our first hypothesis is based on the idea that downsizing poses a risk to customer satisfac- tion through the deterioration of customer-related pro- cesses. However, the way these processes are affected may depend on the excess capacity a company has— that is, organizational slack (Love and Nohria 2005). We propose that higher levels of organizational slack lead to less negative (or even positive) effects on pro- cesses and thus customer satisfaction for two reasons. First, slack may act as a buffer (Bourgeois 1981). A firm with little organizational slack may not have re- sources available to cover the process steps of departing employees, which may lead to a reduction in customer satisfaction. However, a “fat” company should be able to cut personnel while maintaining process performance. Hence, the more slack a company has, the less nega- tively downsizing should affect customer satisfaction.
While slack may offer a buffer, it can also be a cost item. High levels of slack may indicate inefficient processes resulting, for example, in delays for customers (Bourgeois 1981). Downsizing may then become the trigger for improv- ing existing business processes (Marks 2003), which may even increase customer satisfaction through superior quality and/or lower prices. Thus, we hypothesize:
H1: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies with little orga- nizational slack.
Labor productivity Our next hypothesis concerns the moder- ating effect of labor productivity. High labor productivity is likely to be associated with high workplace involvement (Guthrie 2001). We argue that two characteristics of high- involvement workplaces aggravate the effect of downsizing on customer satisfaction.
First, employees in high involvement workplaces are likely to perceive their psychological contract with the firm as strong. That is, employees provide high levels of effort, loyalty, and commitment while expecting in- volvement, job security, and fair treatment (e.g., Tsui et al. 1997). Downsizing can be viewed as a fundamen- tal violation of these obligations. As a result, employees may no longer be willing to achieve previous levels of performance, which may in turn reduce customer
satisfaction. In contrast, in companies with lower work- place involvement and thus a weaker psychological contract, downsizing should result in less disastrous effects on the remaining employees.
Second, in high-involvement workplaces employees are typically more involved in and responsible for quality assurance. To this end, firms assign employees the mission of “satisfy[ing] the customer in the best way they can” (Lawler 1992, p. 36). Resulting from this increase in re- sponsibility, the negative effects of downsizing on em- ployees should more easily translate to a deterioration of quality and hence, customer satisfaction. In contrast, in companies with lower workplace involvement, satisfying customers is spread on more shoulders. As a result, com- panies should be able to better buffer their service to customers from internal disruptions after downsizing. Therefore:
H2: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies with high labor productivity.
R&D intensity Several arguments suggest that downsizing inhibits innovation by impairing the different sources of innovation, such as employees, managers, and customers (Tushman and Nadler 1986). First, concerning employee- triggered innovation, it is worth noting that a major bar- rier for innovation is fear: “When people fear for their jobs, their futures, or even for their self-esteem, it is unlikely that they will feel secure enough to do anything but what they have done in the past” (Pfeffer and Sutton 2000, p. 109; see also Hurley and Hult 1998; Tellis 2013). As downsizing triggers fear, uncertainty, and distrust of management among survivors (e.g., Brockner et al. 1994, 2004) it reduces creativity (Amabile and Conti 1999), and it is thus likely to inhibit employee-triggered innovation. Second, concerning manager-triggered innovation, research has shown that the executors of downsizing suffer from the same symptoms as victims and survivors (Gandolfi 2008). Hence, much like employees, managers who play an active role in a downsizing project should forfeit creativity and innovativeness. Additionally, as in practice downsizing pro- jects are often complex and embedded in a larger reorganiza- tion (Cameron et al. 1991), managers should have less time to initiate, manage, or provide input for innovation projects. As a result, manager-triggered innovation during phases of downsizing should decline.
Third, concerning customer-triggered innovation, downsizing has been shown to increase customer uncertainty (Homburg et al. 2012). We argue that the more
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uncertain customers are, the less readily they should share their ideas or insights with a company. As a result, customer-triggered innovation during downsizing phases is likely to decrease.
In sum, there is good reason to believe and even empirical evidence (Dougherty and Bowman 1995) that downsizing disrupts product innovation. However, if employee-triggered, manager-triggered, and customer- triggered innovation decline, a company may lose its ability to meet customers’ future needs, which should lead to decreasing satisfaction. We propose that firms downsizing in industries with high pressure for innova- tion (e.g., hardware and/or software manufacturers such as Apple, Dell, or Microsoft) should be affected by these effects to a larger extent. Thus, we hypothesize:
H3: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies operating in industries with high R&D intensity.
Prior downsizing Customers’ evaluations of products and services strongly depend on the customers’ prior experiences (Oliver 1997). For example, after experiencing a service fail- ure, customers are more receptive to a repeated service failure, which makes service recovery more difficult (e.g., Liao 2007; Maxham and Netemeyer 2002).
This mechanism poses a critical risk to companies’ downsizing practices in use: many companies do not downsize only once, but they complete several rounds of personnel reductions (e.g., Iverson and Pullman 2000; Moore et al. 2004). Hence, if during an earlier round of downsizing product or service quality has deteriorated, customers are likely to be more receptive for any quality problems during later rounds of downsizing. We thus propose:
H4: The negative effect of downsizing on customer satisfac- tion is more pronounced in companies who undergo repeated downsizing.
Prior losses While some companies reduce their workforce proactively to enhance organizational performance, others downsize reactively owing to financial distress (Freeman and Cameron 1993). We expect that customers react differ- ently to these different motivations.
Research shows that customers care about the fairness of corporate activities and are willing to resist doing business with unfair firms (Kahnemann et al. 1986). In this regard, downsizing may act as a strong signal regarding a firm’s “character” (Love and Kraatz 2009). Customers may perceive
downsizing as particularly opportunistic if the company enjoys profits. In contrast, customers may perceive companies that reduce their workforce to counter losses as less unfair and less socially irresponsible. Indeed, the negative effect of downsizing on corporate reputation is smaller if downsizing is a reaction to performance problems of a firm (Love and Kraatz 2009). Therefore:
H5: The negative effect of downsizing on customer satisfac- tion is less pronounced if a company has had financial losses prior to the downsizing.
Moderator effects pertaining to customer information processing
Product category involvement: interest Product categories which score high on the interest dimension provide personal meaning to customers (Laurent and Kapferer 1985). Customers consume these products more consciously and they are thus more likely to notice deteriorations in product or service quality. As stated by Anderson (1994, p. 28) expec- tations and negative disconfirmation are greater when involve- ment is high, as “customers appear more likely to notice ‘things gone right or wrong’” (Anderson 1994, p. 28). Therefore, we propose:
H6: The negative effect of downsizing on customer satisfac- tion is more pronounced in high interest product categories.
Product category involvement: pleasure Product categories which score high on the pleasure dimension of involve- ment provide hedonic value to customers. Mass layoffs are often thought of as especially unpleasant firm ac- tions, causing fear and problems for the concerned employees (Brockner et al. 1994; Greenglass and Burke 2001; Havlovic et al. 1998). Hedonic consump- tion, however, is also motivated by a desire to escape the problems of the everyday world (e.g., Arnold and Reynolds 2012). Therefore, we expect that downsizing will reduce the hedonic appeal of a firm’s products, which will reduce customer satisfaction, especially in high pleasure categories. Thus:
H7: The negative effect of downsizing on customer satisfac- tion is more pronounced in high pleasure product categories.
Product category involvement: sign A high sign value of a product category indicates that customers’ sense of self
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is strongly linked to the products (Kapferer and Laurent 1993; Laurent and Kapferer 1985). Resulting from this nexus, customers should be inclined to maintain positive attitudes toward these products in order to protect their self-esteem (Bradley 1978; Fournier 1998). Hence, if a company in such a product category downsizes, custom- er satisfaction should be less at stake. Empirical evi- dence supports this. For example, Ferraro et al. (2013) find that in light of a critical incident, customers’ atti- tudes toward a brand deteriorate to a lesser extent if their self-concept is linked to the brand. Similarly, Swaminathan et al. (2007) report that when customers’ self-concept is linked to a brand, these customers “tend to discount and counterargue … negative information” (p. 256). Finally, Johar et al. (2010) state that customer identification with a brand “is one of the best forms of insurance against the possibly devastating effects a crisis can have for an organization.” Hence:
H8: The negative effect of downsizing on customer satisfaction is less pronounced in high sign prod- uct categories.
Product category involvement: risk importance We propose that high risk importance within a product category am- plifies the negative effect of downsizing on customer satisfaction. A perception of high risk leads customers to make a more extended product-related search (Dowling and Staelin 1994; Hoyer and MacInnis 2007). In the course of the search, they may be more likely to learn about a downsizing event, with possible adverse effects on corporate image (Love and Kraatz 2009) and thus on customer satisfaction. Furthermore, similar to our reasoning behind H6 and H7, it seems reasonable to assume that customers consume high-risk products more consciously and are thus more likely to notice quality deteriorations. Hence, we propose:
H9: The negative effect of downsizing on customer satisfac- tion is more pronounced in high risk importance product categories.
Product category involvement: probability of error A high probability of error implies that customers find it difficult to evaluate the quality of a product (Kapferer and Laurent 1993; Laurent and Kapferer 1985). This evaluation difficulty poses an opportunity to downsizing companies: if customers cannot easily access the quality of a product, they should be less likely to notice any quality deteriorations (Anderson 1994). Hence, if after a downsizing event a company’s performance
deteriorates, satisfaction should be less affected. We thus propose:
H10: The negative effect of downsizing on customer satis- faction is less pronounced in high probability of error product categories.
Service consciousness If customers are highly conscious of services in a product category, social interaction with frontline employees plays a particularly large role in driving overall customer satisfaction. Two arguments suggest that under these circumstances, downsizing has a more deleterious effect on customer satisfaction.
First, services rely more on their employees to ensure a high-quality delivery to the customer (Anderson et al. 1997). Hence, firms that downsize may no longer have the staff to provide the service effort customers are used to. Indeed, in seeking productivity improvements, service employees have been shown to reduce the time spent with each customer (Olivia and Sterman 2001). Also, downsizing has been shown to reduce customer orientation of service employees (Subramony and Holtom 2012).
Second, if due to a high service consciousness customer satisfaction depends on the social interaction with frontline employees, customer satisfaction should be affected by the emotions of these frontline employees (Henning-Thurau et al. 2006). As downsizing typically negatively affects employee emotions (e.g., Brockner et al. 1986, 1993; DiFonzo and Bordia 1998; Mishra and Spreitzer 1998), customer satisfac- tion should decrease, too. In contrast, if customer satisfaction depends less on social interaction with frontline employees, the negative effect of downsizing on customer satisfaction via employee emotions should be weaker. Thus, we hypothesize:
H11: The negative effect of downsizing on customer satis- faction is more pronounced if customers have a high service consciousness.
Brand consciousness If a product category is characterized by high brand consciousness, customers place particular empha- sis on the brand when purchasing and using products. One of the key reasons for using brands is that it facilitates decision making through lower information costs (e.g., Erdem and Swait 1998). For instance, categorization research (e.g., Cohen and Basu 1987) has found that to save cognitive energy, customers often reapply judgments that they have already stored in memory (e.g., Sujan 1985). To some extent, this can ensure a stability in brand perceptions over time. For example, Brady et al. (2008) find that the better customers’ brand associations, the less negatively customer satisfaction is
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affected by a performance failure. Similarly, Sloot et al. (2005) find that customers are more loyal to such brands in stock-out situations. Hence, we propose:
H12: The negative effect of downsizing on customer satis- faction is less pronounced if customers have a high brand consciousness.
Indirect effect of downsizing on financial performance via customer satisfaction
If customer satisfaction decreases, so may customer loyalty (Lam et al. 2004), repurchase intentions (Mittal and Kamakura 2001), and willingness to pay (Anderson 1996). These behav- ioral effects might translate into decreased revenues (Fornell 1992), higher costs (Reichheld and Sasser 1990), and, thus, lower financial performance (Anderson et al. 2004; Gruca and Rego 2005). Therefore:
H13: Customer satisfaction mediates the link between downsizing and financial performance.
Methodology
Data collection and sample
We assembled a longitudinal dataset to estimate how downsizing affects subsequent customer satisfaction. By using longitudinal instead of cross-sectional data, our study avoids reverse-causality issues. The American Customer Satisfaction Index (ACSI) is an ideal data source for our purposes. It is a customer-based evaluation of the performance of more than 200 firms in over 40 industries and covers about 43 % of the U.S. economy. To develop the index, about 250 telephone interviews are conducted with current customers of each com- pany on a quarterly basis. While customers rate specific goods or services in these interviews, the answers are then mostly aggregated to the company level (Fornell et al. 1996).
As the index scores reach back as far as 1994, they allow for a comprehensive longitudinal analysis. Also, the index exhibits highly reliable measures of customer satisfaction due to consistent surveys, interview execution, sampling, and estimation across firms and time (see Fornell et al. 1996). The population for our study is all companies listed in the ACSI between 1994 and 2007; 1994 is the first year for which ACSI data is available, and 2007 was chosen as the cutoff in order to exclude any exceptional effects of the subprime and debt crisis on firms’ downsizing activities in the following years. As the economic downturn probably started in 2007 (Pol 2012; Vyas 2011; Wu 2011), we provide robustness checks with 2006 as the cutoff year.
We excluded companies that (1) were not incorporated in the United States (e.g., BMW), or (2) provided customer satisfaction data on the brand instead of the firm level (e.g., Chrysler Corporation, for which the ACSI differentiates be- tween Chrysler and Dodge-Plymouth).We thenmatched these companies with financial data and employment information of Standard and Poor’s Compustat, excluding companies that (3) were not unequivocally listed on Compustat, or (4) did not provide four consecutive years of complete data. This proce- dure resulted in a panel of 110 companies and 710 firm years. Table 2 shows the sample composition. Differences in the sample size and composition compared to other studies (e.g., Ittner et al. 2009; Tuli and Bharadwaj 2009) are due to our more selective inclusion criteria and our requirement of four consecutive years of complete data.
In addition,we collected survey data tomeasure the customer- related moderators (product category involvement and purchase criteria). In 2013 we surveyed 1,522 U.S. residents between 18 and 65 years of age. Respondents were acquired through an online panel provider. The sample is representative for the U.S. population in terms of gender, income, and region (p>0.10). Representativeness in terms of age (p<0.05) and education (p<0.001) could not be established, which we attribute to the use of an online survey. Table 3 shows the sample composition.
After agreeing to participate, respondents were randomly assigned to one of the 29 product categories in our sample and asked to evaluate these product categories through an online survey. For each product category, we obtained at least 50 responses. To match the survey data to the individual compa- nies in our dataset, we used the Standard Industrial Classification (SIC) code as the primary key.
Measures
Downsizing We operationalize downsizing as a dummy var- iable indicating a reduction in the number of employees of at least 5 % as observed in Compustat. This approach is consis- tent with many other studies: a dichotomous measure of downsizing is easier to interpret than a continuous measure (Ahmadjian and Robinson 2001) and is thus frequently used (e.g., Bruton et al. 1996; Love and Nohria 2005). Also, an extensive literature review shows 5 % to be a predominant cutoff point (e.g., Cascio, Young, and Morris 1997; Guthrie and Datta 2008). Studies argue that with lower cutoffs, inves- tigators might erroneously interpret unintentional attrition as downsizing, whereas with higher cutoffs, they might overlook important downsizing events (Ahmadjian and Robinson 2001; Cascio et al. 1997).
Researchers also use press announcements to identify downsizing (e.g., Love and Nohria 2005; Nixon et al. 2004; Worrell et al. 1991). Press announcements might be the more
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valid indicator of downsizing, because mere employment changes may be the result of, for example, spin-offs or out- sourcings. Therefore, we searched the ProQuest database re- cords of the Wall Street Journal and several other wire ser- vices for announcements of layoffs for the firms in our sample. We then constructed a second, narrower downsizing dummy that was set to 1 if employment decreased by at least 5 % and a corresponding announcement was available. We identified 105 downsizing events based on this process. However, as our model requires data availability for the downsizing year as well as the 3 years before, we were only able to use 54 downsizing events. We test our hypotheses using both operationalizations of downsizing.
Customer satisfaction We measure customer satisfaction through the change in customer satisfaction as a firm’s ACSI score in the year after downsizingminus the firm’s ACSI score in the year of downsizing. This way, we analyze how downsizing changes satisfaction.
Resource dependency We measure organizational slack as the ratio of selling, general, and administrative (SG&A) expenses to total sales minus the mean industry SG&A level (sales-weighted) in the year before downsizing. This approach is consistent with other studies (e.g., Love and Nohria 2005; Wiseman and Bromiley 1996). Labor productivity is measured as total sales divided by the
Table 2 Sample composition of the companies in our sample A. Industries Percent of firm-years
with prior downsizing (n=153)
Percent of total firm- years (n=710)
Consumer staples 39 44
Consumer discretionary 27 30
Information technology 8 8
Financials 5 5
Energy 10 5
Telecommunication 4 4
Industrials 7 4
Health care 0 1
B. Revenue Percent of firm-years with prior downsizing (n=153)
Percent of total firm- years (n=710)
< $1 billion 3 2
$1–5 billion 24 19
$5–10 billion 19 21
$10–50 billion 48 50
$50–100 billion 6 7
> $100 billion 0 1
C. Employees Percent of firm-years with prior downsizing (n=153)
Percent of total firm- years (n=710)
< 10,000 18 10
10,000–50,000 39 39
50,000–100,000 21 19
100,000–200,000 15 20
> 200,000 8 11
D. Downsizing percentage
Percent of firm-years with downsizing (n=153)
5–10 % 54
10–15 % 19
15–20 % 10
20–50 % 15
50–100 % 2
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number of employees minus the corresponding industry aver- age in the year before downsizing (Anderson et al. 1997). For industry R&D intensity, we first calculated the average ratio of research and development expenses to total sales for all companies within every three-digit SIC code. We then averaged these ratios over the year before, the year of, and the year after the downsizing event (Guthrie and Datta 2008).
Resource history Prior downsizing is a dummy indicating if in any of the 3 years prior to our focal downsizing event, the company had already downsized at least once. Using a three- year time horizon is consistent with Love and Nohria (2005). Prior financial loss is a dummy indicating if in the year before downsizing, a company had negative EBIT.
Product category involvement We measure the five dimen- sions of product category involvement with items based on Kapferer and Laurent (1993). The exact wording is reported in Table 4.We assessed our measures using a confirmatory factor analysis. Across all product categories, composite reliabilities (CR) and average variance extracted (AVE) exceed recom- mended threshold levels (Bagozzi and Yi 1988) for all in- volvement dimensions (interest: AVE = 0.74; CR = 0.85; pleasure: AVE = 0.84; CR = 0.94, sign: AVE = 0.89; CR =
0.96, risk importance: AVE = 0.76; CR = 0.87, probability of error: AVE =0.77; CR = 0.93). We also find good psycho- metric properties if we analyze the constructs separately for each product category in our data. The only exception is the composite reliability of the interest dimension for cookies and crackers (CR = 0.69), which is slightly smaller than the recommended threshold of 0.7.
Product category purchase criteria We measure these criteria using self-developed scales (items are listed in Table 4). Again, psychometric properties are good (service consciousness: AVE = 0.88; CR = 0.96 and brand consciousness: AVE = 0.71; CR = 0.91) for the overall sample as well in a separate analysis of each product category.
Control variables As we explain in more detail in the next section, we rely on a fixed effects estimator for the model estimation. A key advantage of this method is that omitted variables bias is strongly reduced (Baltagi 2008). In particular, the model structure already accounts for the influence of firm- specific variables that stay constant over the observed time period. Therefore, we control only for firm size in our model by including total assets and employees (Nixon et al. 2004). Table 4 gives an overview of our measures. Table 5 presents descriptive statistics and correlations.
Table 3 Sample composition of the national survey
a According to 2012 data of the U.S. Census Bureau, see http:// www.census.gov bWithout population under 18 and over 65 years of age
A. Gender Percent of survey sample Percent of populationa
Male 49 49
Female 51 51
B. Age Percent of survey sample Percent of populationa,b
18 to 29 24 26
30 to 49 43 42
50 to 65 34 31
C. Education Percent of survey sample Percent of populationa
No college 25 43
Some college, but no degree 29 29
College graduate 27 18
Graduate school 19 10
D. Household Income Percent of Survey Sample Percent of Populationa
< $40 K 40 40
$40 K to $80 K 31 29
> $80 K 29 31
E. Region Percent of Survey Sample Percent of Populationa
Northeast 19 19
Midwest 23 23
West 22 22
South 36 36
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Model specification and estimation
Model specification To test the effect of downsizing on cus- tomer satisfaction, we specify a model which includes all
independent and moderating variables. Furthermore, the mod- el includes interaction terms between downsizing and all moderators:
ChangeinCustomerSatisfactiont;i ¼ β1Downsizingt−1;i þ β2OrganizationalSlackt−2;i þ β3LaborProductivityt−2;i þ β4IndustryR&DIntensityt;i þ β5PriorDownsizingt−2;i þ β6PriorFinancialLosst−2;i þ β7TotalAssetst;i þ β8Employeest;i þ β9Downsizingt−1;i�OrganizationalSlackt−2;i þ β10Downsizingt−1;i�LaborProductivityt−2;i þ β11Downsizingt−1;i�IndustryR&DIntensityt;i þ β12Downsizingt−1;i�PriorDownsizingt−2;i þ β13Downsizingt−1;i�PriorFinancialLosst−2;i þ β14Downsizingt−1;i�Interesti þ β15Downsizingt−1;i�Pleasurei þ β16Downsizingt−1;i�Signi þ β17Downsizingt−1;i�RiskImportancei þ β18Downsizingt−1;i�ProbabilityofErrori þ β19Downsizingt−1;i�ServiceConsciousnessi þ β20Downsizingt−1;i�BrandConsciousnessi þ αi þ εt;i
where β denotes the regression coefficients, t indicates the year, and i the individual company. αi is an individual (company-specific) error. It accounts for the nested structure of our dataset, where years are nested in firms. εt,i stands for an idiosyncratic (residual) error that may vary over both compa- nies and time. For interpretation purposes, we centered all moderators by subtracting the mean of each variable from its original value (Irwin and McClelland 2001).
The model explains customer satisfaction in a certain year (t) through downsizing in the period before (t-1) to rule out confounding effects and thus allow for causal conclusions. The firm-specific moderators that vary over time (i.e., organi- zational slack, labor productivity, prior downsizing, and prior financial loss) were measured prior to the downsizing event. We chose to measure them in the year before the downsizing event because they could be confounded with the downsizing event itself (e.g., downsizing reduces organizational slack). It is worth noting that this model requires us to have complete data for five consecutive years, ranging from customer satis- faction in t via downsizing in t-1 back to prior downsizing in any of the 3 years before the focal downsizing event, i.e., back to t-4 (see description of measurement above).
Estimation method It is important to emphasize again that our dataset contains multiple observations for each firm. Put dif- ferently, our dataset is of a hierarchical structure in which years are nested in companies. This nested structure often leads to violations of the assumptions of ordinary least squares (OLS), in particular if the individual error αi is not identical across all firms, if it is correlated with the regressors, or if the
idiosyncratic error ε t , i is serially correlated or is heteroskedastic (e.g., Baltagi 2008; Boulding and Staelin 1995). To check whether these violations apply to our dataset, we conducted a series of standard statistical tests (e.g., Baltagi 2008; Wooldridge 2002). Indeed, Breusch and Pagan’s (1980) Langrange multiplier test indicated that there is a company- specific intercept in our data (p<0.001), and the Breusch- Godfrey test (see Baltagi and Li 1995) indicated serial corre- lation in the error term εt,i (p<0.001). We therefore resorted to two estimation methods that produce consistent results under these conditions. First, we estimated a fixed effects model with robust standard errors using STATA’s xtreg procedure (Cameron and Trivedi 2010, p. 335). Second, we deployed a fixed effects feasible generalized least squares estimator (Wooldridge 2002, p. 247), using the statistical software package R (procedure pggls, for details see Croissant and Millo 2008). These methods treat the issue of serial correlation through different mechanisms, but they are similar in the way they deal with the company-specific intercept through so-called fixed effects. In particular, they discard any company-specific (i.e., fixed) effect by subtracting the average over time from each variable. This is a standard econometric method when dealing with data structured like ours. It has also frequently been used in studies dealing with downsizing (e.g., Love and Kraatz 2009; Love and Nohria 2005) as well as ACSI data (e.g., Anderson and Mansi 2009; Grewal et al. 2010).
It is worth mentioning that fixed-effects procedures cannot estimate effects of time-invariant independent variables
778 J. of the Acad. Mark. Sci. (2015) 43:768–789
(Baltagi 2008; Wooldridge 2002). Therefore, our regres- sion equation depicted above and our results in the next section do not contain main effects for our time-invariant moderators (interest, pleasure, sign, risk importance, probability of error, service consciousness, and brand consciousness).
Moderated effects of downsizing on customer satisfaction
We first present the results for downsizing being measured as an employment decrease of at least 5 % as observed in
Compustat regardless of whether a downsizing announcement was available. Table 6 shows our estimation results.
As described previously, we present models using different cutoff years and estimators. First, we turn to the results obtained through a fixed effects estimator with clustered errors (models 1 and 2). Before interpreting the results for our hypotheses, we note that the main effect of downsizing is significantly negative both for the cut- off 2007 (β1=−0.97, p<0.01) and 2006 (β1=−0.96, p<0.01). Thus, on average, downsizing has a negative effect on customer satisfaction.
Table 4 Measures and data sources for the customer satisfaction model
Measure Operationalization Data sources
Change in customer satisfaction
Year-to-year change of the American Customer Satisfaction Index (ACSI) by the National Quality Research Center
ACSI
Downsizing (broad definition)
Dummy indicating if the number of employees has decreased by at least 5 % Compustat
Downsizing (narrow definition)
Dummy indicating if both press announcement and employee number indicate workforce reduction of at least 5 %
Compustat, business press
Organizational slack Ratio of selling, general and administrative expenses to total sales (relative to industry average)
Compustat
Labor productivity Ratio of total sales to number of employees (relative to industry average) Compustat
Industry R&D intensity Three-year mean of the average ratios of R&D expenditures to total sales for all companies belonging to a three-digit SIC industry
Compustat
Prior downsizing Dummy indicating if the downsizing dummy (see above) is 1 in any of the three prior years
Compustat
Prior financial loss Dummy indicating if earnings before interest and taxes are negative Compustat
Interesta •What [products] I choose is extremely important to me. •I’m really very interested in [products]. •I couldn’t care less about [products]. (R)b
National survey
Pleasurea •I really enjoy buying [products]. •Whenever I buy [products], it’s like giving myself a present. •To me, it is quite a pleasure to buy [products].
National survey
Signa •You can tell a lot about a person from the [products] he or she chooses. •The [products] a person chooses says something about who they are. •The [products] I choose reflects the sort of person I am.
National survey
Risk importancea •It doesn’t matter too much if one makes a mistake buying [products]. (R)b
•It’s very irritating to choose not the right [products]. •I should be annoyed with myself if it turned out I’d made the wrong choice of [products].
National survey
Probability of errora •I always feel rather unsure about what [products] to pick. •When you choose [products], you can never be quite sure it was the right choice or not. •Choosing [products] is rather difficult. •When you choose [products], you can never be quite certain about your choice.
National survey
Service consciousnessa
When it comes to [products], … •… good customer service is very important to me. •… I place very high value on customer service. •… I consider a very good customer service to be crucial.
National survey
Brand consciousnessa
When it comes to [products], … •… the brand is very important to me. •… I care about the brand very much. •… I choose among my preferred brands only. •… there are certain brands which I would not consider for my choice.
National survey
Total assets Total assets in $100,000 Compustat
Employees Number of employees in 1,000 Compustat
(R) Item reverse coded a 7-point Likert scales anchored “fully disagree” to “fully agree” b Item dropped due to low factor loading
J. of the Acad. Mark. Sci. (2015) 43:768–789 779
T ab
le 5
D es cr ip tiv
e st at is tic s an d co rr el at io ns
fo r th e cu st om
er sa tis fa ct io n m od el
V ar ia bl e
V 1
V 2
V 3
V 4
V 5
V 6
V 7
V 8
V 9
V 10
V 11
V 12
V 13
V 14
V 15
V 16
V 17
V 18
M ai n va ri ab le s
V 1:
do w ns iz in g (b ro ad ) (t -1 )
V 2:
do w ns iz in g (n ar ro w ) (t -1 )
0. 55
V 3:
ch an ge
in cu st om
er sa tis fa ct io n (t )
−0 .0 4
−0 .0 8
R es ou rc e de pe nd en cy
V 4:
or ga ni za tio
na ls la ck
(t -2 )
0. 02
0. 02
0. 04
V 5:
la bo r pr od uc tiv
ity (t -2 )
0. 02
−0 .0 4
0. 01
−0 .3 5
V 6:
in du st ry
R & D in te ns ity
(t )
0. 02
0. 10
−0 .0 4
−0 .1 6
0. 02
R es ou rc e hi st or y
V 7:
pr io r do w ns iz in g (b ro ad ) (t -2 )
0. 20
0. 13
−0 .0 4
0. 03
0. 08
−0 .0 4
V 8:
pr io r do w ns iz in g (n ar ro w ) (t -2 )
0. 09
0. 18
−0 .0 2
0. 00
0. 01
0. 06
0. 52
V 9:
pr io r fi na nc ia ll os s (t -2 )
0. 23
0. 26
−0 .0 0
0. 12
0. 03
0. 10
0. 17
0. 31
C at eg or y in vo lv em
en t
V 10 :i nt er es t
−0 .0 4
−0 .0 5
0. 04
0. 11
−0 .0 3
−0 .0 5
−0 .1 2
−0 .0 7
−0 .0 6
V 11 :p
le as ur e
−0 .0 7
−0 .0 7
0. 05
0. 09
−0 .0 4
−0 .0 4
−0 .1 7
−0 .0 8
0. 00
0. 75
V 12 :s ig n
−0 .0 6
−0 .1 1
0. 06
0. 09
−0 .0 1
−0 .1 9
−0 .1 2
−0 .1 2
−0 .1 5
0. 78
0. 78
V 13 :r is k im
po rt an ce
−0 .0 2
0. 06
−0 .0 2
0. 02
−0 .0 2
0. 28
−0 .0 4
0. 13
0. 16
0. 45
0. 25
0. 25
V 14 :P
ro ba bi lit y of
E rr or
−0 .0 0
0. 09
−0 .0 5
−0 .1 8
0. 03
0. 36
0. 02
0. 19
0. 21
−0 .1 1
−0 .1 6
−0 .2 5
0. 65
C at eg or y pu rc ha se
cr ite ri a
V 15 :s er vi ce
co ns ci ou sn es s
−0 .0 4
0. 01
−0 .0 3
−0 .0 1
−0 .0 5
−0 .0 4
−0 .1 1
0. 04
0. 07
0. 30
0. 27
0. 02
0. 30
0. 44
V 16 :b
ra nd
co ns ci ou sn es s
−0 .0 5
−0 .1 1
0. 07
0. 15
−0 .0 1
0. 20
−0 .1 4
−0 .1 7
0. 05
0. 57
0. 56
0. 34
0. 32
−0 .1 3
0. 14
C on tr ol s
V 17 :t ot al as se ts (t )
−0 .0 5
−0 .0 0
0. 05
−0 .0 4
0. 01
0. 01
0. 01
0. 07
−0 .0 5
−0 .1 0
−0 .3 1
−0 .2 0
0. 08
0. 28
0. 20
−0 .1 7
V 18 :e m pl oy ee s (t )
−0 .1 1
−0 .0 9
0. 02
−0 .0 9
−0 .0 9
−0 .0 8
−0 .1 3
−0 .0 7
−0 .1 6
0. 10
0. 10
0. 00
−0 .1 8
−0 .0 9
0. 35
0. 11
0. 22
M ea n
–a –a
−0 .1 8
−0 .0 1
0. 00
0. 33
–a –a
–a 4. 77
4. 16
4. 06
4. 11
3. 41
5. 14
4. 52
0. 43
82 .2 5
St an da rd
de vi at io n
–a –a
2. 37
0. 08
0. 22
0. 84
–a –a
–a 0. 61
0. 70
0. 65
0. 41
0. 40
0. 51
0. 34
1. 58
86 .5 6
N ot e: p < 0. 05
fo r |r| > 0. 08 ;p
< 0. 01
fo r |r| > 0. 10 ;p
< 0. 00 1 fo r |r| > 0. 13
(b as ed
on tw o- ta ile d te st s)
a D um
m y va ri ab le
780 J. of the Acad. Mark. Sci. (2015) 43:768–789
In H1 we predict that organizational slack positively mod- erates the effect of downsizing on customer satisfaction. The corresponding interaction term is positive and significant both for the cutoff 2007 (β9=6.17, p<0.05) and 2006 (β9=6.55, p<0.05), providing support for H1
Hypothesis 2 posits that labor productivity negatively mod- erates the downsizing–satisfaction link. In support of H2, the interaction between labor productivity and downsizing has a significant negative effect using both the cutoff 2007 (β10= −1.90, p<0.01) and 2006 (β10=−1.83, p<0.01).
H3 suggests that industry R&D intensity negatively mod- erates the downsizing–customer satisfaction chain. This hy- pothesis is strongly supported both for the cutoff 2007 (β11= −0.82, p<0.001) and 2006 (β11=−1.00, p<0.001).
In H4 we propose that downsizing has a more deleterious effect on change in customer satisfaction for firms that under- go repeated downsizing. While, consistent with this proposi- tion, the interaction term between downsizing and prior downsizing is negative, it is insignificant both for the cutoff 2007 and 2006. Hence, H4 is not supported by the data. Similarly, we do not find support for H5: the sign of the interaction coefficient between downsizing and prior financial loss is positive as proposed, but insignificant.
Regarding product category involvement, we do not find support for H6 through H8 as the interaction coefficients are insignificant. Hypotheses 9 and 10 are supported. In line with our propositions, the interaction coefficient between downsizing and risk importance is significantly negative
Table 6 Customer satisfaction model (Broad Downsizing Operationalization)
Dependent variable: change in customer satisfaction (t)
Model 1 Model 2 Model 3 Model 4
Fixed effects with clustered errorsa
Fixed effects with clustered errorsa
Fixed effects GLSb
Fixed effects GLSb
Variable Cutoff year 2007 Cutoff year 2006 Cutoff year 2007 Cutoff year 2006
Downsizing (t-1) −0.97 (0.32)** −0.96 (0.32)** −1.00 (0.17)*** −1.29 (0.24)*** Organizational slack (t-2) 1.10 (1.41)n.s. 0.08 (1.79)n.s. −1.56 (0.59)** 1.25 (1.33)n.s.
Labor productivity (t-2) 1.02 (0.73)n.s. 0.55 (0.92)n.s. −0.64 (0.25)** 0.14 (0.60)n.s.
Industry R&D intensity (t) −0.17 (0.11)n.s. −0.11 (0.13)n.s. −0.30 (0.04)*** −0.14 (0.09)n.s.
Prior downsizing (t-2) −0.09 (0.17)n.s. 0.00 (0.19)n.s. −0.68 (0.08)*** −0.19 (0.11)n.s.
Prior financial loss (t-2) 1.24 (0.89)n.s. 1.88 (0.83)* 0.70 (0.48)n.s. 2.30 (0.60)***
Total assets (t) 0.01 (0.11)n.s. 0.11 (0.07)n.s. 0.07 (0.02)*** 0.19 (0.04)***
Employees (t) 0.00 (0.00)n.s. −0.00 (0.00)n.s. −0.00 (0.00)n.s. −0.00 (0.00)n.s.
Downsizing (t-1) × organizational slack (t-2) H1:+ 6.17 (2.71)* 6.55 (3.02)* −1.96 (1.02)n.s. 6.00 (2.43)* Downsizing (t-1) × labor productivity (t-2) H2:− −1.90 (0.66)** −1.83 (0.61)** −5.39 (0.70)*** −1.98 (0.70)** Downsizing (t-1) × industry R&D intensity (t) H3:− −0.82 (0.18)*** −1.00 (0.19)*** −0.28 (0.09)** −1.29 (0.18)*** Downsizing (t-1) × prior downsizing (t-2) H4:− −0.14 (0.42)n.s. −0.21 (0.44)n.s. −0.28 (0.15)n.s. 0.42 (0.31)n.s.
Downsizing (t-1) × prior financial loss (t-2) H5:+ 1.14 (1.19)n.s. 1.14 (1.08)n.s. 2.80 (0.62)*** 1.59 (0.84)n.s.
Downsizing (t-1) × interest H6:− 0.16 (0.74)n.s. 0.89 (0.92)n.s. 1.77 (0.31)*** 1.59 (0.62)* Downsizing (t-1) × pleasure H7:− -0.41 (0.59)n.s. -0.50 (0.63)n.s. −0.09 (0.32)n.s. −1.26 (0.51)* Downsizing (t-1) × sign H8:+ 0.81 (0.67)n.s. 0.41 (0.73)n.s. 0.51 (0.28)n.s. 0.82 (0.55)n.s.
Downsizing (t-1) × risk importance H9:− −2.48 (0.89)** −2.85 (1.08)** −2.93 (0.32)*** −3.24 (0.75)*** Downsizing (t-1) × probability of error H10:+ 3.92 (1.10)*** 4.51 (1.30)*** 1.94 (0.49)*** 4.44 (0.90)***
Downsizing (t-1) × service consciousness H11:− −0.51 (0.58)n.s. −0.94 (0.71)n.s. −1.73 (0.29)*** −0.91 (0.49)n.s.
Downsizing (t-1) × brand consciousness H12:+ 1.77 (0.84)* 1.78 (0.99)n.s. 1.46 (0.29)*** 1.99 (0.62)**
Year dummiesc Included Included Included Included
Number of firms 110 105 110 105
Number of firm-years 710 637 710 637
Number of downsizing events 153 139 153 139
R2 (within) 0.15 0.17 0.08 0.24
n.s. p>0.05; * p<0.05; ** p<0.01; *** p<0.001 (based on two-tailed tests)
Notes: Unstandardized parameters are shown. Standard errors are in parentheses a Estimated with STATA (version 10.1), procedure xtreg b Estimated with R (version 3.0.2), procedure pggls (version 1.4–0) c Dummy variable for each year was included in the models in order to account for fixed effects on the time level
J. of the Acad. Mark. Sci. (2015) 43:768–789 781
(cutoff 2007: β17=−2.48, p<0.01; cutoff 2006: β17=−2.85, p<0.01), whereas the interaction coefficient between downsizing and probability of error is significantly positive (cutoff 2007: β18=3.92, p<0.001; cutoff 2006: β18=4.51, p<0.001).
Regarding product category purchase criteria, there is no evidence in support of H11. Service consciousness does not have a significant interaction effect with downsizing. Concerning H12, brand consciousness positively moderates the effect of downsizing on change in customer satisfaction for the cutoff 2007 (β20=1.77, p<0.05). When choosing the cutoff 2006, the interaction effect is insignificant. Hence, support for H12 is limited.
Models 3 and 4 are estimated using the fixed effects GLS method as an alternative estimator. Here, in line with models 1 and 2, the moderating effects of labor productivity (H2), industry R&D intensity (H3), risk importance (H9), and prob- ability of error (H10) are supported, whereas the moderating effects of prior downsizing (H4) and sign (H8) are not. The strong consistency across all four models raises our confi- dence in the validity of these findings. Moreover, in line with model 1, the moderating effect of brand consciousness is supported. The interaction effect of organizational slack is significant in model 4 but insignificant in model 3. Hence, seeing that the interaction coefficients of brand consciousness and organizational slack are significant in three out of four models, in summary we find some support for H1 and H12. Lastly, H5, H6, H7, and H11 are partly supported in at least one of models 3 and 4, making our result in their regard somewhat inconclusive.
To gain further insight into the nature of the interaction effects, we plotted them based on model 1 in Table 6. Following Guthrie and Datta (2008), we divided our data into two groups based on whether a firm had downsized in the previous period. In each group, we calculated means and stan- dard deviations of all variables.We then assigned the moderator a value of one standard deviation above and below its mean while constraining all other variables to their means. We then used these values to predict customer satisfaction. Figure 2 shows the plots, which all reveal that downsizing has a negative effect on the change of customer satisfaction. This negative effect is however particularly pronounced for disadvantageous configurations of the moderators, i.e., for low organizational slack, high labor productivity, high industry R&D intensity, high risk importance, low probability of error, and low brand consciousness. The negative effect is alleviated or neutralized for advantageous configurations of the moderators.
Robustness checks for different operationalizations of downsizing
We follow earlier research by considering employee reduc- tions of 5 % or more as downsizing. In this section, we
describe two tests to check whether our results are stable when using other operationalizations. First, we estimated our model a second time with a narrower downsizing dummy. It was set to 1 only if workforce reductions of at least 5 % were accom- panied by a corresponding press announcement. Table 7 shows the results. As changing the operationalization reduces the number of observed downsizing events to 54, we are mainly interested whether hypothesized effects have the same sign across operationalizations. This is the case. Moreover, despite the small sample, three of the hypothesized interaction effects (with R&D intensity, risk importance, and probability error) are statistically significant. Surprisingly, contrary to H6, interest has a significant positive interaction effect for both estimation methods.
Second, we tested the stability of the results when using other values than 5 % as a cutoff-point for downsizing events. We find highly consistent results for cutoff points of 4 to 7 %. Moreover, for a 3 % cutoff point, many effects just barely lose their statistical significance. This might indicate that at a 3 % cutoff point, the effects of downsizing dilute somewhat. Despite that, overall we are confident that our results are stable for cutoff-points ranging from 3 to 7 %. For more extreme cutoff points (e.g., 1, 10, or 15 %) the pattern of results is visibly affected.
Indirect effect of downsizing on financial performance via customer satisfaction
To examine our proposition that customer satisfaction medi- ates the effect of downsizing on financial performance, we conducted a mediation analysis. Therefore, we specified a model with change in financial performance as the dependent variable, operationalized as return on assets (ROA) in t minus ROA in t-1. ROA is calculated as the ratio of earnings before interest, taxes, depreciation and amortization to total assets. This operationalization is widely used in downsizing research (e.g., Bruton et al. 1996; Guthrie and Datta 2008; Love and Nohria 2005). As Cascio, Young, and Morris (1997: 1177) argue: “Any changes in the performance of a firm that result from employment downsizing should show up in the ROA measure.” As independent variables, we included our prior independent variables lagged by one additional period. We further included organizational slack and labor productivity in t as additional control variables.
Table 8 shows the results. Model 1 reports the effect of downsizing on change in financial performance without controlling for change in customer satisfaction. The effect is not statistically significant. In model 2, we added change in customer satisfaction in t-1 as an independent variable. Again, we find no effect of downsizing on fi- nancial performance, whereas—consistent with much ear- lier research (e.g., Anderson et al. 1994; Anderson et al. 2004)—change in customer satisfaction has a positive
782 J. of the Acad. Mark. Sci. (2015) 43:768–789
effect (βCS→ROA=0.17, p<0.05). As a robustness check, model 3 shows how the absolute level of customer satis- faction (instead the year-to-year change) affects return on assets. We find a strong positive effect (βCS→ROA=0.57, p<0.001), which substantiates our finding that customer satisfaction is positively linked to financial performance.
The fact that downsizing reduces customer satisfaction and that customer satisfaction drives financial perfor- mance points to a potential indirect effect of downsizing on financial performance via customer satisfaction in line with H13. To test H13, we conducted the Sobel test (Sobel 1982), finding a significant effect (βDS→CS × βCS→ROA=−0.17, p<0.05). Hence, in support of H13 downsizing reduces customer satisfaction, which then re- duces financial performance.
Table 9 analyzes this indirect effect for unfavorable condi- tions of our supported moderators. Following Spiller et al. (2013), we estimated the simple effect of downsizing on satis- faction for different levels of the moderators and then repeated the Sobel test. The negative indirect effect of downsizing on performance via satisfaction becomes stronger for companies with low slack or high labor productivity and in industries with high R&D intensity
as well as in product categories that customers perceive as risky but have a low probability of error.
Discussion
Research implications
Downsizing has been a popular managerial instrument for almost 30 years. However, only recently have researchers started to look at customer outcomes of downsizing. Our re- search contributes to this new research stream in several ways.
Previous research on customer outcomes of downsizing has focused on B2B markets (e.g., Lewin 2009; Lewin and Johnston 2008; Lewin et al. 2010). We extend the field by looking at B2C markets. Here, we also find that downsizing reduces customer satisfaction. We argue that this finding is less intuitive than it maybe sounds. In B2B markets there is typically a strong degree of personal interaction between customers and employees of the downsizing supplier. In con- trast, in most B2C markets, consumers have little to no per- sonal contact with firm employees. As a result, in many product categories consumers seem to be indifferent to
Fig. 2 Interaction plots
J. of the Acad. Mark. Sci. (2015) 43:768–789 783
employee working conditions. For instance, despite the highly publicized problems of workers in one of Apple’s supplier firms (e.g., Mishkin 2013), in October 2013 Apple CEO Tim Cook reported that Apple was winning in terms of customer satisfaction (Bradshaw 2013).
In light of this potential consumer indifference to the way products and services are produced, the question becomes: When does downsizing affect satisfaction? Our findings indicate that consumers mostly respond to downsizing if it results in noticeable deteriorations of product performance. Only in firms with resource con- figurations that make them especially vulnerable to losses of human capital (high R&D intensity, high labor productivity, little slack), does downsizing affect
customer outcomes. Moreover, if customers have diffi- culties in evaluating product quality, downsizing does not reduce satisfaction. Similarly, downsizing has little to no effect if customers rely on brands as primary cue in purchasing decisions. Thus, in B2C markets the ef- fect of downsizing on satisfaction is indeed less clear- cut than one would maybe expect.
That said, some of our moderator hypotheses were not supported by the data. For instance, whether services play an important role in a product category does not affect the downsizing-satisfaction link. This is interesting because Anderson et al. (1997) argue that there is a larger trade-off between productivity and customer satisfaction for service companies than for manufacturers. Their argument is based
Table 7 Customer satisfaction model (Narrow Downsizing Operationalization)
Dependent variable: change in customer satisfaction (t)
Model 1 Model 2
Fixed effects with clustered errorsa Fixed effects GLSb
Variable Cutoff year 2007 Cutoff year 2007
Downsizing (t-1) −1.67 (0.32)*** −1.94 (0.40)*** Organizational slack (t-2) 0.60 (1.34)n.s. −0.52 (0.96)n.s.
Labor productivity (t-2) 0.74 (0.59)n.s. −0.09 (0.43)n.s.
Industry R&D intensity (t) 0.00 (0.11)n.s. −0.13 (0.08)n.s.
Prior downsizing (t-2) 0.07 (0.24)n.s. −0.14 (0.13)n.s.
Prior financial loss (t-2) 1.13 (0.74)n.s. 0.94 (0.48)n.s.
Total assets (t) 0.00 (09)n.s. 0.07 (0.03)**
Employees (t) 0.00 (0.00)n.s. −0.00 (0.00)n.s.
Downsizing (t-1) × organizational slack (t-2) H1:+ 6.84 (5.22)n.s. −2.40 (3.89)n.s.
Downsizing (t-1) × labor productivity (t-2) H2:− −2.45 (1.77)n.s. −1.92 (1.55)n.s.
Downsizing (t-1) × industry R&D intensity (t) H3:− −1.17 (0.19)*** −0.58 (0.18)** Downsizing (t-1) × prior downsizing (t-2) H4:− −0.77 (0.93)n.s. 0.54 (0.66)n.s.
Downsizing (t-1) × prior financial loss (t-2) H5:+ −0.40 (0.97)n.s. −0.88 (0.75)n.s.
Downsizing (t-1) × interest H6:− 6.28 (2.93)* 5.99 (2.73)* Downsizing (t-1) × pleasure H7:− −0.71 (0.94)n.s. −1.08 (0.88)n.s.
Downsizing (t-1) × sign H8:+ −2.39 (1.59)n.s. −0.56 (1.66)n.s.
Downsizing (t-1) × risk importance H9:− −2.03 (1.24)n.s. −5.65 (1.54)*** Downsizing (t-1) × probability of error H10:+ 7.77 (2.63)** 10.21 (2.26)***
Downsizing (t-1) × service consciousness H11:− −3.13 (1.62)n.s. −1.50 (1.50)n.s.
Downsizing (t-1) × brand consciousness H12:+ −2.48 (3.11)n.s. −3.21 (2.77)n.s.
Year dummiesc Included Included
Number of firms 110 110
Number of firm-years 710 710
Number of downsizing events 54 54
R2 (within) 0.15 0.20
n.s. p>0.05; * p<0.05; ** p<0.01; *** p<0.001 (based on two-tailed tests)
Unstandardized parameters are shown. Standard errors are in parentheses a Estimated with STATA (version 10.1), procedure xtreg b Estimated with R (version 3.0.2), procedure pggls (version 1.4–0) c Dummy variable for each year was included in the models in order to account for fixed effects on the time level
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on the observation that customization is more important in service firms, which reduces possibilities for increasing productivity. Given the increasing importance of customizing manufactured goods, differences between service firms and manufacturers may have become smaller in this regard.
Likewise, we do not find that downsizing is less harmful to customer satisfaction if firm financial performance was de- clining before the downsizing or if a firm had downsized before. This is noteworthy because past performance explains image effects of downsizing. Love and Kraatz (2009) report that negative effects of downsizing on firm image are less pronounced if the downsizing is a response to performance
problems. The different results points to the importance of distinguishing between image and satisfaction as outcomes of downsizing.
The way our study is designed also extends earlier research methodologically: (1) Previous research on customer outcomes of downsizing used cross-sectional data, which triggers reverse causality issues. It is possible that low customer satisfaction forces firms to cut costs through downsizing. This would also entail a negative correlation between downsizing and satisfac- tion. By linking satisfaction to downsizing the year before, our setup alleviates these concerns. (2) Previous research has relied on single-source data from a customer’s perspective (e.g., Lewin 2009; Lewin and Johnston 2008; Lewin et al. 2010) or
Table 8 Financial performance model
Variable Dependent variable: change in return on assets (t)
Dependent variable: change in return on assets (t)
Dependent variable: return on assets (t)
Model 1 Model 2 Model 3
Change in customer satisfaction (t-1) – 0.17 (0.07)* –
Customer satisfaction (t-1) – – 0.57 (0.14)***
Downsizing (t-2) −0.12 (0.99)n.s. 0.04 (0.99)n.s. 1.07 (0.71)n.s.
Organizational slack (t-3) −2.35 (4.86)n.s. −2.43 (4.96)n.s. −6.26 (5.09)n.s.
Organizational slack (t) −6.47 (5.37)n.s. −6.86 (5.38)n.s. −6.74 (16.77)n.s.
Labor productivity (t-3) −7.61 (1.71)*** −7.73 (1.73)*** −9.00 (4.15)*.
Labor productivity (t) 6.13 (1.33)*** 6.37 (1.35)*** 7.69 (2.41)**.
Industry R&D intensity (t-1) 0.30 (0.90)n.s. 0.33 (0.91)n.s. 0.24 (0.45)n.s.
Prior downsizing (t-3) 0.17 (0.30)n.s. 0.18 (0.30)n.s. 0.50 (0.42)n.s.
Prior financial loss (t-3) −0.46 (1.87)n.s. −0.85 (1.94)n.s. −2.99 (1.68)n.s.
Total assets (t-1) −0.10 (0.09)n.s. −0.12 (0.10)n.s. −0.40 (0.22)n.s.
Employees (t-1) 0.01 (0.00)n.s. 0.01 (0.00)n.s. −0.01 (0.01)n.s.
Downsizing (t-2) × organizational slack (t-3) 11.24 (5.30)* 10.14 (5.30)n.s. 1.50 (7.30)n.s.
Downsizing (t-2) × labor productivity (t-3) 0.34 (1.44)n.s. 0.68 (1.42)n.s. 2.12 (2.15)n.s.
Downsizing (t-2) × industry R&D intensity (t-1) 0.86 (0.60)n.s. 1.05 (0.58)n.s. 2.14 (0.67)**
Downsizing (t-2) × prior downsizing (t-3) −1.42 (0.94)n.s. −1.39 (0.93)n.s. −1.18 (1.00)n.s.
Downsizing (t-2) × prior financial loss (t-3) −2.49 (4.00)n.s. −2.73 (3.94)n.s. −1.95 (1.39)n.s.
Downsizing (t-2) × interest 0.55 (2.93)n.s. 0.36 (2.89)n.s. 1.16 (2.46)n.s.
Downsizing (t-2) × pleasure 1.15 (1.41)n.s. 1.26 (1.40)n.s. −1.89 (1.36)n.s.
Downsizing (t-2) × sign −1.46 (2.57)n.s. −1.50 (2.53)n.s. 0.56 (2.19)n.s.
Downsizing (t-2) × risk importance −0.03 (2.15)n.s. 0.44 (2.09)n.s. −1.45 (1.66)n.s.
Downsizing (t-2) × probability of error 1.64 (2.80)n.s. 0.84 (2.75)n.s. −0.21 (2.19)n.s.
Downsizing (t-2) × service consciousness −0.48 (1.90)n.s. −0.28 (1.85)n.s. −0.76 (1.55)n.s.
Downsizing (t-2) × brand consciousness 0.50 (2.34)n.s. 0.20 (2.30)n.s. −1.74 (1.88)n.s.
Year dummiesa Included Included Included
Number of firms 104 104 104
Number of firm-years 609 609 610
R2 (within) 0.11 0.12 0.23
n.s. p>0.05; *p<0.05; **p<0.01; ***p<0.001 (based on two-tailed tests)
Unstandardized parameters are shown. Standard errors are in parentheses. Estimation method: fixed effects with clustered errors, cutoff year 2007 aDummy variable for each year was included in the models in order to account for fixed effects on the time level
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a managerial perspective (Homburg et al. 2012). Our research integrates the two perspectives. Hence, with our design com- monmethod effects can probably be ruled out as an explanation for the negative downsizing–satisfaction link.
Finally, our study establishes that customer satisfaction following downsizing mediates the downsizing–performance relationship. By identifying this mechanism, it also contrib- utes to research on the “hidden costs” of downsizing, i.e., costs that are often overlooked by managers starting these activities (Buono 2003). Furthermore, our study offers a new explanation why researchers have found it hard to find a consistent effect of downsizing on performance (e.g., Datta et al. 2010). If customer satisfaction mediates the effects of downsizing, interaction effects with context factors can create conflicting evidence with regard to the overall relationship. In fact, we too do not find a significant direct effect of downsizing on financial performance (see model 1 in Table 8). Coupled with our finding of an indirect effect via customer satisfaction, this suggests that multiple (opposing) indirect effects explain the relationship between downsizing and financial performance (e.g., MacKinnon et al. 2000; Rucker et al. 2011; Shrout and Bolger 2002).
It needs to be mentioned that when measuring downsizing, we follow a convention from management research. We con- sider any firm year as a downsizing year in which the number of employees went down by at least 5 %. This comes with limitations. First, the 5 % threshold is somewhat arbitrary. We find that results are mostly robust for other thresholds in a range between 3 and 7%. For very high threshold values (e.g., 15 %), results differ. Therefore, future research could analyze extreme downsizing events further. Second, large reductions of the number of employees may not always indicate layoffs. Results are qualitatively consistent if only downsizing activi- ties covered in the press are considered. Third, the operationalization of downsizing is very general. Maybe out- comes of downsizing differ depending on the department
affected. Future research could compare downsizing conse- quences between departments.
Managerial implications
Our study has important implications for managers. Managers must be aware that depending on their firm and product category, downsizing has differential effects on customers. Thus, managers should “think outside the firm” while implementing downsizing. Our results indicate that this might be worth the effort. Managers should be especially careful with downsizing if industry R&D intensity and labor produc- tivity are high, while organizational slack is low. Similarly, they should actively consider alternatives to downsizing if customers perceive purchases in the category as risky, cus- tomers find it easy to assess product quality, and customers do not consider the brand an important purchase criterion.
Interestingly, our results suggest that currently managers do not pay much attention to these aspects when engaging in downsizing. A look at our Table 5 reveals that the correlations between the aforementioned variables and downsizing activ- ity are all smaller than 0.10. Hence, it appears as if currently managers mostly ignore the detrimental effects of downsizing on customers. Our study could contribute to increasing the awareness for these issues.
In addition, our study can guide managers interested in reducing detrimental customer outcomes of downsizing. First, customers react more negatively to downsizing in product categories where purchases are perceived as risky. This points to the importance of managing customer per- ceived risk during a downsizing. For instance, marketing managers could consider offering additional guarantees to their customer (e.g., a satisfaction guarantee). They should also implement a communication strategy that transparently addresses potential concerns of the cus- tomers. Second, customers react less negatively to
Table 9 Mediation analysis
βDS→CS βDS→CS × βCS→ROA Sobel test statistic p value (two-tailed)
Main model, i.e. average values for all moderators −0.97 (0.32)** −0.17 −1.98* 0.047 Low organizational slack −1.46 (0.35)*** −0.25 −2.21* 0.027 High labor productivity −1.30 (0.36)*** −0.24 −2.15* 0.032 High industry R&D intensity −1.66 (0.37)*** −0.29 −2.25* 0.025 High risk importance −1.99 (0.49)*** −0.34 −2.19* 0.028 Low probability of error −2.54 (0.58)*** −0.44 −2.24* 0.025 Low brand consciousness −1.57 (0.53)** −0.27 −1.95n.s. 0.051 All of the above −5.76 (1.07)*** −1.00 −2.34* 0.019
n.s. p>0.05; *p<0.05; **p<0.01; ***p<0.001 (based on two-tailed tests)
DS, downsizing; CS, customer satisfaction; ROA, return on assets. Unstandardized parameters are shown. Standard errors are in parentheses. Estimation method: fixed effects with clustered errors, cutoff year 2007. Low/high values for moderators are calculated as one standard deviation below/above the mean value
786 J. of the Acad. Mark. Sci. (2015) 43:768–789
downsizing in product categories where brands play an important role. Hence, during downsizing, marketers should put particular emphasis on brand communication at the point of sale and elsewhere.
Limitations
This study does have several limitations. First, it relies on balance sheet data to measure firm-related variables. Hence, downsizing is measured through a proxy, which—as discussed before—is tied to a number of assumptions about the nature of downsizing. We provide evidence that results are relatively stable if other operationalizations are used, but these come with their own disadvantages. Second, the archival nature of the data has also to some extent guided and restricted our choice of firm-level moderators. Survey data could pro- vide additional insights on how to manage downsizing, but data on sensitive issues like downsizing is notoriously difficult to obtain (Homburg et al. 2012) and not available for the time period of interest. Third, in terms of the firms analyzed, this study is subject to the inclusion requirements of the ACSI. It served as the starting point of our data collection efforts. Fourth, product category involvement is measured at one point in time after the focal time-period of the study. Thus, for our results concerning customer-related interactions to hold, it is required to assume that product category involve- ment is to some extent constant over time.
Conclusion
In the B2C markets covered by the American Customer Satisfaction Index, organizational downsizing is on average associated with decreases in customer satisfaction. In turn these customer outcomes of downsizing affect firm perfor- mance. However, the extent of negative customer reactions to downsizing is largely influenced by contextual variables. In particular, the degree to which a firm depends on human resources and the way customers process information in a product category moderate the downsizing-satisfaction link. Hence, in specific firm–product configurations, downsizing may prove detrimental with regard to customer satisfaction. For other firms, downsizing will not entail any negative cus- tomer response.
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- Customer reactions to downsizing: when and how is satisfaction affected?
- Abstract
- Introduction
- Conceptual framework
- Hypotheses
- Moderator effects pertaining to a firm’s resources
- Moderator effects pertaining to customer information processing
- Indirect effect of downsizing on financial performance via customer satisfaction
- Methodology
- Data collection and sample
- Measures
- Model specification and estimation
- Moderated effects of downsizing on customer satisfaction
- Robustness checks for different operationalizations of downsizing
- Indirect effect of downsizing on financial performance via customer satisfaction
- Discussion
- Research implications
- Managerial implications
- Limitations
- Conclusion
- References
Contents lists available at ScienceDirect
Scandinavian Journal of Management
journal homepage: www.elsevier.com/locate/scajman
Downsizing and the fragility of corporate reputation: An analysis of the impact of contextual factors
Ann-Christine Schulza,⁎, Sarah Johannb
a University of Applied Sciences for Management and Communication (FHWien der WKW), Waehringer Guertel 97, 1180 Vienna, Austria b Technische Universität Berlin, Department of Business, Straße des 17. Juni 135, 10623 Berlin, Germany
A R T I C L E I N F O
Keywords: Corporate reputation Downsizing Layoff Restructuring Stakeholders
A B S T R A C T
This study extends prior research on the impact of downsizing on corporate reputation by investigating how specific aspects of downsizing measures influence this relationship. Using panel data on the S&P 100 companies for the period 1990–2000, we find that downsizing affects corporate reputation negatively and that the size of the effect depends on the content and the context of the downsizing announcement. More specifically, we find that the motive for downsizing, the time period in which it is announced as well as the extent of previous layoffs significantly influence the reputational penalties that are associated with corporate downsizing. Our results thus elucidate how contextual factors of a downsizing decision can influence the extent of the reputational damage of this measure.
1. Introduction
Since the late 1980s, many US-based firms have adopted downsizing programs and reduced their workforce in order to cut costs and improve their performance (Baumol, Blinder, & Wolff, 2003; Davis & Haltiwanger, 1999). In the US, the Bureau of Labor Statistics counted on average over 1300 mass-layoff events per month in the period 1995–2001, which resulted in millions of job losses (Bureau of Labor Statistics, 2017). Research on corporate downsizing has so far focused predominantly on analyzing the effects of downsizing on a firm’s per- formance and on employees (for an overview, see Datta, Guthrie, Basuil, & Pandey, 2010). Few studies, however, have investigated how downsizing influences other organizational outcomes, such as a firm’s creativity, innovative capability or reputation, although these are cru- cial to a firm’s performance. To our knowledge, only the studies by Flanagan and O’Shaughnessy (2005), Love and Kraatz (2009) and Zyglidopoulos (2003, 2005) have analyzed the impact of downsizing on corporate reputation. The findings of these studies concur that, on average, corporate downsizing has a negative impact on a firm’s ex- ternal reputation. Moreover, they show that the relationship between downsizing and corporate reputation is moderated by firm-specific at- tributes, such as a firm’s age or performance. With these exceptions, however, research has so far neglected the impact of other contextual factors, particularly those that are associated with the downsizing an- nouncement. Datta et al. (2010, p. 339) have lamented the lack of studies on how contextual factors affect the outcomes of downsizing.
Responding to their criticism, we aim to address this gap and analyze how the contextual conditions that are associated with the downsizing announcement − namely, the motive for downsizing, the time period of the decision, and previous layoffs − influence the relationship be- tween downsizing and corporate reputation.
Corporate reputation is one of the most important strategic re- sources for firms (e.g., Fombrun, 1996; Roberts & Dowling, 2002; Weigelt & Camerer, 1988). Defined as “a perceptual representation of a company’s past actions and future prospects that describe the firm’s overall appeal to all its key constituents when compared with other leading rivals” (Fombrun, 1996, p. 72), corporate reputation can be regarded as a general organizational attribute that is based on stake- holders’ perceptions of a firm’s past actions. Reputation constitutes an intangible resource that is hard to replicate. Crucially, it can facilitate access to resources controlled by key stakeholders and in that way in- fluence a firm’s ability to create and sustain a competitive advantage that ultimately results in better firm performance (Barney, 1991; Benjamin & Podolny, 1999; Deephouse, 2000; Fombrun & Shanley, 1990). Indeed, previous research has shown that corporate reputation is positively associated with a firm’s financial success (e.g., Deephouse, 2000; Eberl & Schwaiger, 2005; McGuire, Schneeweis, & Branch, 1990; Raithel & Schwaiger, 2015; Roberts & Dowling, 2002; Rose & Thomsen,2004). For that reason, managers seek to improve and sustain the firm’s good overall reputation through their strategic decisions and actions.
A firm’s reputation is not static but evolves continuously:
https://doi.org/10.1016/j.scaman.2017.11.004 Received 1 July 2016; Received in revised form 9 October 2017; Accepted 17 November 2017
⁎ Corresponding author. E-mail addresses: [email protected] (A.-C. Schulz), [email protected] (S. Johann).
Scandinavian Journal of Management 34 (2018) 40–50
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stakeholders observe the strategic choices its managers make and infer from their outcomes the firm’s ability to create value for them (Basdeo, Smith, Grimm, Rindova, & Derfus, 2006). In that respect, certain stra- tegic actions may improve a firm’s reputation, if they are perceived as appropriate choices in a given context. Such strategic choices may in- volve, for example, the introduction of popular management techniques (e.g., total quality management, quality circles or job enlargement) (Staw & Epstein, 2000) or market actions that signal a firm’s competi- tiveness (Basdeo et al., 2006). Other decisions, however, may severely damage a firm’s reputation. If managers make decisions that are mainly motivated by managerial self-interest or favor the interests of some stakeholders at the expense of others − in short, if a firm acts in ways that are perceived as controversial by some of their stakeholders (Bednar, Love, & Kraatz, 2015), it may incur reputational penalties. Bednar et al. (2015), for example, found that the use of so-called “poison pills,” i.e. measures taken by the board of directors to deter hostile takeovers, has a negative impact on a firm’s reputation. Simi- larly, Williams and Barrett (2000) have shown that legal infringements have a negative impact on corporate reputation.
One prevalent management practice that is likely to impact a firm’s reputation is corporate downsizing. Previous research has shown that downsizing, a cost-cutting measure aimed at improving a firm’s per- formance, tends to affect negatively a company’s stock-market perfor- mance and, thus, shareholder wealth (e.g., Chen, Mehrotra, Sivakumar, & Yu, 2001; Elayan, Swales, Maris, & Scott, 1998; Farber & Hallock, 2009; Hallock, 1998; Hillier, Marshall, McColgan, & Werema, 2007; Lee, 1997; Nixon, Hitt, Lee, & Jeong, 2004). The effect of downsizing on a firm’s operational performance remains unclear. Some studies have found that its effects are positive, while others have shown that its ef- fects are negative (e.g., Brauer & Laamanen, 2014; Cascio, Young, & Morris, 1997; Guthrie & Datta, 2008; Love & Nohria, 2005). In addition, prior research has shown that various internal and external stake- holders view corporate downsizing negatively. Employees, as important internal stakeholders, are likely to view reductions in their firm’s workforce as a serious violation of their moral contract with the firm, as it threatens their job security (Morrison & Robinson, 1997; Turnley & Feldman,1998). As a consequence, layoffs can weaken employee com- mitment and job satisfaction (Armstrong-Stassen, Cameron, & Horsburgh, 1996; Brockner, Grover, Reed, & Dewitt, 1987). There is also evidence that downsizing has an adverse impact on work perfor- mance, which is manifested in reduced organizational creativity and innovative capability (Amabile & Conti, 1999; Bommer & Jalajas, 1999). The effects of downsizing on external stakeholders have also been researched. For example, Homburg, Klarman and Staritz (2012) found that downsizing tends to increase customer uncertainty and, as a result, to affect negatively a firm’s relationship with its customers.
Given the various negative effects that corporate downsizing has on a firm, it is not surprising that previous empirical research on the re- putational effects of downsizing has shown that, in general, its impact on a firm’s overall reputation is negative (Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009; Zyglidopoulos, 2005). However, it remains unclear whether the effects of downsizing on a firm’s reputation are uniformly negative or whether they depend on the specific measures that a firm takes. Past research on stock-market responses to corporate downsizing has shown that how a firm’s shareholders assess downsizing varies according to the extent of the layoffs announced, the official reason for downsizing, whether the layoffs are permanent or temporary and the number of previously announced decisions to downsize (Chalos & Chen, 2002; Chatrath, Ramchander, & Song, 1995; Chen et al., 2001; Elayan et al., 1998; Farber & Hallock, 2009; Hahn & Reyes, 2004; Hallock, 1998; Hillier et al., 2007; Lee, 1997; Lin & Rozeff, 1993; Palmon, Sun, & Tang, 1997; Worrell, Davidson, & Sharma, 1991). This suggests that how other stakeholders perceive and evaluate a company is also likely to depend on the specific aspects of the downsizing an- nouncement. In this study, we will build on the results of previous studies on the impact of downsizing on corporate reputation by
analyzing in depth the attributes that characterize specific instances of downsizing; namely, the motive that has led a company to lay off staff, the time period of the downsizing and how it relates to previous layoffs. To answer this research question, we will analyze data on a sample of firms drawn from the S&P 100 Index for the period 1990–2000, which subsequently became known as the “downsizing decade” (Wagar, 1998, p. 34).
Our study makes an important contribution to management re- search and practice. The findings of our study provide insights into how corporate downsizing affects organizational outcomes. Previous re- search has focused on investigating the direct relationship between downsizing and firm reputation and on how firm-specific attributes moderate this relationship. Our study, however, is the first to examine how the attributes of specific instances of downsizing affect corporate reputation. In this way, our findings also shed more light on the ante- cedents of corporate reputation. Moreover, we contribute to the emerging research on the impact of critical events on a firm’s behavior. Our study examines how a particular type of critical events − namely, layoffs − may influence the media and other stakeholders’ perceptions of downsizing. Furthermore, our study has also important implications for the communication of downsizing.
2. Theoretical background and hypotheses
2.1. The impact of downsizing on corporate reputation
Corporate reputation can be viewed as one of the most important strategic resources a firm has at its disposal (e.g., Fombrun, 1996; Roberts & Dowling, 2002; Weigelt & Camerer, 1988). An established reputation reduces uncertainty, guides the actions of a firm’s stake- holders (Dowling, 1986; Fombrun & Shanley, 1990) and can thus sig- nificantly influence the firm’s performance. A good corporate reputa- tion may reduce customer uncertainty about the quality of a company’s products (Shapiro, 1983). It may also reduce the uncertainty that em- ployees feel about their employer (Cable & Graham, 2000), as well as uncertainty among actors on the capital market about future stock performance and corporate earnings (Beatty & Ritter, 1986). Firms with a good reputation are in a better position to charge premium prices for their products (Milgrom & Roberts, 1986) and are more attractive to skilled employees or investors than firms with a poor reputation (Beatty & Ritter, 1986; Roberts & Dowling,2002). Unsurprisingly, research has found that a firm’s reputation has a positive impact on its financial performance (e.g., Deephouse, 2000; Eberl & Schwaiger, 2005; McGuire et al., 1990; Raithel & Schwaiger, 2015; Roberts & Dowling, 2002; Rose & Thomsen, 2004) and that managers consequently have an interest in building and preserving a good overall corporate reputation and avoiding reputational damage (e.g., Roberts & Dowling, 2002).
Corporate reputation is determined by various factors and is con- structed through the perceptions of external observers on the basis of available information about a firm’s activities (Fombrun & Shanley, 1990). External stakeholders perceive news about a firm’s financial performance, quarterly results, and strategic actions and achievements, or advertising as important signals on whose basis they assess the status of a company and its future prospects. This information is released by the firm in the form of annual or quarterly reports, conference calls, press releases or marketing activities that influence the corporate brand or image of the firm. So-called “information intermediaries,” such as the media and financial analysts, play an important role in the way information is processed and distributed to external stakeholders (e.g., Fogarty & Rogers, 2005; Pollock & Rindova, 2003; Zuckerman, 1999). They collect, process and distribute information through various channels (e.g., newspapers, magazines, blogs, research reports) to the stakeholders of the firm who develop perceptions and internal assess- ments regarding the firm’s actions. Their individual perceptions and assessments are then aggregated to form collective judgments that amount to a firm’s corporate reputation (DiMaggio & Powell, 1983;
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Fombrun & Shanley, 1990). Each strategic decision that managers make is likely to have a direct
impact not only on the firm’s competitive position, but also on its overall reputation. Existing empirical research confirms that strategic decisions and corporate practices can affect a firm’s reputation. Staw and Epstein (2000), for example, showed that firms that adopt popular management techniques are associated with higher reputation. Simi- larly, Basdeo et al. (2006) found that the number of a company’s market actions positively influences its reputation. However, reputation can also be easily damaged. Corruption, bribery, financial fraud and drastic violations of environmental and social standards can create a climate of controversy and distrust among stakeholders and can even harm a firm’s reputation to such an extent that restoring it might prove hard or nearly impossible (Fich & Shivdasani, 2007). Williams and Barrett (2000), for example, have shown that if firms violate health and safety regulations or environmental regulations, their reputation suffers. Moreover, firms may face reputational penalties if their managers do not adhere to commitments they have signaled they would honor (Herbig, Milewicz, & Golden, 1994) or when they introduce manage- ment practices that are not in line with the expectations of stakeholders. For example, Bednar et al. (2015) found that using “poison pills” to avoid hostile takeovers is perceived as a controversial practice that can damage corporate reputation. Similarly, Fombrun and Shanley (1990) showed that in the mid-1980s diversification was negatively associated with corporate reputation because many stakeholders perceived it as a value-destroying strategy. In sum, managers need to be aware of the effects of their decisions on the company’s overall reputation. This applies also to the decision to lay-off employees.
Corporate downsizing, though often intended to improve a firm’s cost structure and competitive position, tends to harm corporate re- putation (Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009; Zyglidopoulos, 2005). Flanagan and O’Shaughnessy (2005) have shown that downsizing announcements and corporate reputation scores are negatively associated. Similarly, Zyglidopoulos (2005) and Love and Kraatz (2009) found that downsizing announcements generally result in a drop in corporate reputation in the year following the announcement. While managers seem to use downsizing as a feasible way of meeting the demands of the product market (Filatotchev, Buck, & Zhukov, 2000; Hallock, 1998; Palmon et al., 1997; Vicente-Lorente & Suárez-Gonzáles, 2007), organizations are negatively affected by downsizing in various respects. The fact that human resources are among a firm’s most im- portant resources explains why this is the case. Employees share spe- cific knowledge, skills and abilities that can produce valuable output that is hard to imitate. If workforce reductions are perceived by the remaining employees as major psychological contract violations re- garding job security (Morrison & Robinson, 1997; Turnley & Feldman, 1998), they might develop a “survivorship syndrome” that can result in negative consequences such as decreased employee commitment and job satisfaction (Armstrong-Stassen et al., 1996; Brockner et al., 1987). Furthermore, layoffs can destroy informal communication networks within the organization and may create a climate of distrust and un- fairness that reduces the ability of firms to share information. Such disruptions may thus damage an organization’s creativity and in- novative capability (Amabile & Conti, 1999; Bommer & Jalajas,1999). Finally, downsizing may not produce the expected performance out- comes. Research has shown that downsizing generally results in nega- tive stock-market returns (e.g., Chen et al., 2001; Elayan et al., 1998; Hallock, 1998; Lee, 1997; Worrell et al., 1991). The effects of down- sizing on operational performance can be either positive or negative. Cascio et al. (1997), for example, found that the change in a company’s operational performance is negative both in the year of staff cuts and in the following year. However, Elayan et al. (1998) and Espahbodi, John, and Vasudevan (2000) found that operational performance effects can also be positive. In sum, research has shown that corporate downsizing has various negative implications for the firm and its stakeholders—i.e., for employees, customers and investors—and creates greater
uncertainty about a firm’s prospects. Consequently, downsizing leads stakeholders to view a firm less favorably.
2.2. The impact of the content and context of downsizing
In this study, we propose that the negative impact of downsizing on external reputation depends on the content and context of the down- sizing announcement. The three factors on which we will be focusing are the motive behind the decision to downsize, the time period in which the downsizing was announced and the extent of prior down- sizing measures.
2.2.1. The motive for downsizing How stakeholders such as employees, customers and investors in-
terpret and perceive corporate decisions may depend on the motives behind layoffs and on the reasons that the firms give for downsizing. Firms that announce the intention to downsize aim to convey the image of strategically appropriate decision-making, instead of hinting at the prospect of negative performance. To that end, they usually provide detailed information on the motives and reasons for planned layoffs during analyst conference calls, press conferences or via business press announcements; e.g., restructuring, a prospective M&A, improving ef- ficiency, or an overall slump in demand. Consequently, the motives and reasons for announced layoffs are typically known to external stake- holders and can be viewed as a form of corporate signaling (Asquith & Mullins, 1986) or impression management (Staw, McKechnie, & Puffer, 1983). Especially in the wake of threats such as the possibility of bankruptcy or in circumstances that could lead a company to send mixed signals and that create uncertainty about the company’s future performance (e.g., layoffs), managers may try to manage the percep- tions of the company’s constituents by providing information that is likely to influence their impression of the firm (e.g., Marcus & Goodman, 1991; Sutton & Callahan,1987).
Research has shown that investors react differently to layoff an- nouncements, depending on the motives provided (Chen et al., 2001; Farber & Hallock, 2009; Hahn & Reyes, 2004; Palmon et al., 1997). For that reason, we propose that the impact of downsizing on firm re- putation will vary, depending on the explanations and reasons that management gives. We will focus on internal, efficiency-driven motives and on external, demand-driven motives, which, as previous studies have shown, impact the performance of both the firm and the re- maining employees differently (Drzensky & Heinz, 2016; Elayan et al., 1998; Palmon et al., 1997).
As a result of significant changes in market forces and governance forces in the late 1980s, during the 1990s managers started to focus more closely on promoting the interests of shareholders and to put greater emphasis on shareholder wealth (Davis & Thompson, 1994; Lazonick & O’Sullivan, 2000). Responding to the increasing pressure to maximize shareholder wealth, managers began to take action to re- structure and downsize the extent of their firm’s activities (Gordon & Pound, 1993; Lazonick & O’Sullivan, 2000; Useem, 1996) in order to improve efficiency. In that context, downsizing can be seen as a way to meet this objective. However, efficiency-driven downsizing is asso- ciated with relatively high uncertainty as to whether the objective of increasing firm performance will be achieved. This is because the po- sitive effects of “leaner” production may be offset by the negative ef- fects of downsizing on the firm’s human resources and its innovation capability. Moreover, many journalists viewed critically the stronger emphasis on shareholder interests at the expense of the interests of other stakeholders such as employees, customers and policy makers (Kennedy, 2000; Koslowski, 2000). In addition, since firm performance is often tied to managers’ compensation, cutting labor costs with the aim to improve firm performance can be seen as a selfish way of serving the managers’ personal interests (Drzensky & Heinz, 2016). In light of these criticisms, we expect that downsizing measures that are internally driven by the need to increase efficiency are viewed very critically by a
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firm’s stakeholders. Furthermore, we propose that downsizing in response to external
factors, such as a decline in demand, has a less negative impact on company reputation and is more likely to be viewed as a necessity by a firm’s stakeholders. Downsizing due to decreasing demand signals that the firm has difficulties in selling output and is forced to lay off em- ployees reluctantly. The information that announcements of downsizing associated with a decline in demand typically convey is that the man- agement believes that the firm is facing a long-term decline in demand (rather than short-term excess capacity); for example, because of par- ticular trends in the economy, the loss of a key customer or because of a decrease in customer satisfaction. Since customers are one of the most important assets of firms (e.g., Schulze, Skiera, & Wiesel, 2012) such changes can result in a material loss of sales and earnings. To com- pensate for such losses, a firm will need to adjust the cost structure, so demand-driven downsizing is likely to be viewed as a necessity. Con- sequently, the decision to lay-off staff would also be viewed as more legitimate than when the motive is to serve mainly the interests of shareholders. For that reason, downsizing that is associated with a decline in demand is likely to have a less negative impact on a firm’s reputation. Taking these points in consideration, we propose that, in general, efficiency-driven downsizing has a more negative impact on a firm’s reputation than downsizing associated with a decline in demand.
Hypothesis 1. The impact of downsizing on corporate reputation will be more negative when the announced motive for downsizing is internal and associated with an increase in efficiency than when it is external and associated with a decline in demand.
2.2.2. Time period of downsizing We argue that certain critical events can influence how stakeholders
perceive a firm’s decision to downsize and that the effect of downsizing on the firm’s reputation depends on the time period of the downsizing announcement in relation to such a critical event. Critical events can be defined as “dramatic happenings that focus sustained public attention and invite the collective definition or redefinition of social problems” (Hoffman & Ocasio, 2001, p. 414). Such events attract attention to specific aspects of a firm’s behavior and may change stakeholders’ views on certain decisions and strategic actions (Chandler, 2014).
With regard to corporate downsizing in the 1990s in the US, we expect that the negative effects of downsizing on company reputation were more pronounced in the second half of the 1990s due to a critical event in 1996; namely, AT&T’s announcement that it would lay off 40,000 employees (New York Times, 1996). The company’s stake- holders viewed negatively the scale of this event and, as a result, the announcement not only hurt significantly the employees’ motivation and commitment to the firm, but also received negative coverage in the press. The New York Times (1996, p. 11), for example, reported in relation to this event “Morale at the company was crippled; Robert E. Allen, then AT&T’s chairman, found his picture on the cover of News- week magazine, in a police-style lineup under the headline ‘Corporate Killers.”' In the aftermath of the event, Clinton’s public administration increasingly criticized mass layoffs and their impact on communities and the broader society (New York Times, 1996). Over the following months and years the media discourse with regard to downsizing grew increasingly negative and the negative rhetoric permeated media re- ports on the downsizing programs announced by other firms, while managers’ rhetoric became more defensive of similar decisions. For all those reasons, this event can be viewed as a “turning point” (New York Times, 1996: D1) in the public debate on corporate downsizing.
Research has shown that the media can influence public knowledge and opinions. In particular, the agenda-setting theory has proposed that the media coverage of certain issues can raise the salience of these is- sues on the public agenda and thus increase public awareness and concern (Ader, 1995; Behr & Iyengar, 1985; McCombs & Shaw, 1972). Critical and visible events in particular can attract significant media
attention (Roche, 2000; Tilcsik & Marquis, 2013), which may influence how the public views a firm and interprets certain management con- cepts or strategies. In view of the marked shift towards negative rhetoric with regard to downsizing since 1996, we propose that during the 1990s downsizing announcements made after 1996 have had a more negative impact on the reputation of the respective firms.
Hypothesis 2. During the 1990s, downsizing announcements made before 1996 had a less negative impact on the respective firms’ corporate reputation than announcements made after 1996.
2.2.3. Extent of prior downsizing How stakeholders perceive downsizing also depends on whether the
decision is unique or whether the firm has downsized extensively in the past. If a firm has downsized significantly in the past, downsizing again is likely to increase uncertainty on the part of stakeholders. When firms lay off employees, they have to cover significant costs, such as sever- ance payments (Worrell et al., 1991). The larger the layoff, the higher the costs associated with a workforce reduction. Extensive previous reductions in a company’s workforce also mean that a large number of workers have already left the company. As a result, extensive down- sizing may represent a serious loss of knowledge. A major loss of human capital is likely to damage a firm’s bundle of resources and thus the capabilities that the firm needs in order to create and sustain a com- petitive advantage (Nixon et al., 2004). In addition, as Brauer and Laamanen (2014) argue, large reductions in the workforce augment the negative effects of the so-called survivor syndrome. As routines become more stretched and more dysfunctional, the impact of downsizing on a firm’s performance becomes increasingly negative. Considering these effects, we propose that firms that have experienced significant down- sizing in the past will encounter greater problems as a result of downsizing again than firms that have never downsized in the past. Moreover, the decision to downsize again will create greater un- certainty about the prospects of the company. Hence, for firms that have downsized extensively in the past we expect that stakeholders will view more critically a firm’s decision to downsize and that the overall impact of downsizing on company reputation is greater:
Hypothesis 3. The impact of downsizing on corporate reputation is more negative if a firm has already downsized extensively in previous years.
3. Method
3.1. Sample
Our sample consists of the Standard & Poor’s 100 firms (S&P 100) in the period 1990–2000. We chose to use the S&P 100 firms because, as leading U.S. stocks, they are highly visible and closely monitored by the media and other external constituents who may have an influence on corporate reputation. We chose the 1990–2000 period because it was a period with a high prevalence of downsizing. We gathered annual data on the reputation of those firms using Fortune’s “America’s Most Admired Companies” (AMAC) survey. The sample of firms represented in Fortune’s AMAC changes from one year to the next, so the data on reputation do not cover our sample of the S&P 100 firms in all years. Moreover, we required that a firm-year observation was included if the company received a Fortune AMAC reputation rating in at least two consecutive years and the record of financial information was complete. Due to incomplete data and M&As among the S&P 100 firms, our final sample comprises 74 firms and 646 firm-years. For these firm-years, we collected downsizing announcements. Data for the control variables were collected from the Compustat and Thomson Reuters 13f data- bases.
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3.2. Dependent variable
Our dependent variable is corporate reputation. We measured cor- porate reputation using the overall score that a firm received for a given year in Fortune’s AMAC ranking. In this annual survey, the largest companies in various industries are evaluated by several thousand ex- pert participants, such as senior executives, outside directors and fi- nancial analysts (Fombrun & Shanley, 1990; Roberts & Dowling, 2002). The respondents are asked to rate the firms of the industry they are familiar with on a number of dimensions, such as quality of manage- ment, innovativeness or quality of products and services. The ratings of these dimensions are then aggregated into an overall raw reputation score. We chose to utilize the AMAC score for several reasons. First, this score is the most widely used measure of corporate reputation in management studies (Dowling, 2016). Second, the AMAC score has been used in all studies on the impact of downsizing on corporate re- putation (see Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009; Zyglidopoulos, 2005). Given that we aim to refine the findings of pre- vious research on the impact of downsizing on corporate reputation, using the same measure of reputation allows comparisons between our findings and those of earlier works. Third, although the AMAC index is based on the responses of industry experts who regularly assess com- panies in their own industry, it is also used routinely as a reputation measure for other stakeholder groups such as customers (Sarstedt, Wilczynski, & Melewar, 2013; Walker, 2010) and has been found to be highly correlated with measures such as employees’ pride in organiza- tional membership and job satisfaction (Helm, 2013). In our sample, the ranking score ranges from 3.32 to 9.02, with a mean of 6.59.
3.3. Explanatory variables
3.3.1. Corporate downsizing To measure corporate downsizing, we analyzed layoff announcements
in the public business press, including the business sections of main- stream newspapers. For that purpose, we searched full text articles and abstracts in the New York Times, Wall Street Journal, Los Angeles Times and Washington Post, as well as in several wire services, for announce- ments during the period from 1989 through to 2000. To identify downsizing, we searched for the following terms: “layoff,” “laid off,” “downsize,” “downsizing,” “downsized,” plus firm name and specific time period (e.g., Hallock, 1998). We limited our search to permanent reductions in personnel and excluded temporary layoffs. We also ex- cluded downsizing announcements that had already been executed or were part of a broader downsizing program, downsizing announce- ments that did not report the number of employees that would be laid off, and announcements of plans to revise the number of employees that
would be laid off due to downsizing. In accordance with similar studies (e.g., Love & Kraatz, 2009), an additional criterion was that the an- nounced downsizing would affect at least 1% of the workforce. Finally, if a firm made two or more separate downsizing announcements in the same year, we aggregated them into a single observation. This proce- dure resulted in 197 firm-years with downsizing announcements in the total sample of 646 firm-years. Of the 74 firms in our sample, 61 firms announced at least one downsizing measure in this period. The down- sizing firm-years were coded as dummy variables that took the value “1” if a firm announced downsizing in the respective year. To in- vestigate the impact of downsizing on firm reputation, we lagged our independent variables by one year.
3.3.2. Motive for downsizing In a downsizing announcement, managers usually state the reason
for their decision. Drawing such information from newspaper articles on the downsizing of specific firms, we coded the publicly announced motives for downsizing as follows: “efficiency-motivated downsizing,” “demand-decline-motivated downsizing,” and “other-motivated down- sizing.” When an announcement indicated that downsizing was moti- vated by the desire to cut costs or boost profitability, that instance was coded as “efficiency-motivated.” When the announcement indicated that the firm would downsize in response to a slump in demand, an industry downturn or an economic downturn, that instance was coded as “demand-decline motivated.” Downsizing announcements due to other reasons, such as reorganization or an M&A were classified as “other-motivated downsizing.” If a firm had issued multiple downsizing announcements within the same year, we used the announcement that contained the greatest number of layoffs. Examples of how we coded various downsizing announcements are presented in Table 1. The coding was carried out independently by two researchers who achieved an inter-rater reliability of over 90% (92.5%). In cases of disagreement, consensus was reached through discussions between the coders. Of the 197 firm-years with downsizing, 86 downsizing announcements were assigned to the category “efficiency-motivated downsizing” and 43 to “demand-decline-motivated downsizing.” To further check the relia- bility of our coding of the motives for downsizing, we additionally asked a group of five students to code selected downsizing announce- ments and compared the results. To facilitate their task, we described orally the three motives for downsizing to the group and provided an example of each case. After this introduction, we asked the students to assign ten randomly picked downsizing announcements to one of the three downsizing categories. The congruence between the classification we had carried out and the classification the students carried out reached nearly 80% (78.0%), which indicates that our coding is robust. We created two dummy variables efficiency-motivated downsizing and
Table 1 Examples of Motives for Downsizinga.
aKeywords used to code the text are highlighted in grey.
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demand-decline-motivated downsizing which took the value “1” if a firm announced downsizing with the respective motive in the respective year, and “0” otherwise.
3.3.3. Time period of downsizing To analyze pre- and post-1996 downsizing announcements, we
created two dummy variables. If downsizing was announced between 1990 and 1995, the variable pre-1996 downsizing was set to “1.” If downsizing was announced after 1995, the variable post-1996 down- sizing was set to “1.” We counted 127 downsizing announcements in the pre-1996 period and 70 in the post-1996 period.
3.3.4. Extent of prior downsizing To measure the extent of previous cases of downsizing in a firm, we
calculated the sum of the extent to which it had downsized in the previous two fiscal years. The variable extent of prior downsizing ranges from 0.00 to 0.49, with a mean of 0.04%.
3.4. Control variables
To take into account other factors that may influence corporate reputation, we controlled for certain company characteristics, following prior research (e.g., Basdeo et al., 2006; Bednar et al., 2015; Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009; Musteen, Datta, & Kemmerer, 2010; Philippe & Durand, 2011; Roberts & Dowling, 2002; Staw & Epstein, 2000).
In line with previous research, we controlled for a company’s past reputation by including the lagged dependent variable, i.e., Fortune’s AMAC reputation score in the previous year (Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009; Roberts & Dowling, 2002). We named this variable prior corporate reputation. This score can in- fluence how stakeholders interpret and evaluate a firm’s activities (Love & Kraatz, 2009). Moreover, Roberts and Dowling (2002) found a high persistence of corporate reputation over time.
Following the suggestions of previous studies, we controlled for a firm’s age (Flanagan & O’Shaughnessy, 2005; Musteen et al., 2010; Philippe & Durand, 2011). Firm age is the logged number of years since a firm’s founding year. We obtained information on each company’s founding year from Standard & Poor’s Register of Corporations (Flanagan & O’Shaughnessy, 2005).
Larger firms tend to receive more media attention and are thus more visible than smaller firms (Fombrun & Shanley, 1990). For that reason, we controlled for firm size and measured this variable using the natural log of a firm’s total sales at the end of the preceding fiscal year (Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009).
Prior research has shown that a firm’s AMAC rating is heavily in- fluenced by its previous financial results (e.g., Brown & Perry, 1994). To remove this performance “halo”, we included various performance variables as controls. The first of these is average profitability, which reflects the mean of the return of assets (ROA) ratio over the three preceding years (Love & Kraatz, 2009; Musteen et al., 2010). The second performance measure we used is average sales growth, which reflects the mean of sales growth in the three preceding years (Love & Kraatz, 2009; Musteen et al., 2010). The third measure is profitability change. We measured changes in profitability as the change in the ROA ratio between two consecutive years and included the percentage ROA change between year t-1 and t as well as its lagged measure (i.e., the percentage ROA change between t-2 and t-1) in our models (Love & Kraatz, 2009). The reason for including the lagged measure was that reputational changes may lag behind increases or decreases in perfor- mance. The fourth performance measure is market capitalization change. We included two measures: the percentage change in the market value of the firm between t-1 and t and its lagged measure, i.e., the percentage change in market value between t-2 and t-1 (Love & Kraatz, 2009). Finally, we included Tobin’s Q as a control and measured the variable as the market value of a firm divided by the book value of that firm in year
t (Flanagan & O’Shaughnessy, 2005). We included the debt-to-equity ratio to control for firm risk (Brown
& Perry, 1984; Flanagan & O’Shaughnessy, 2005). Institutional ownership has been found to be positively related to
corporate reputation (Bednar et al., 2015; Fombrun & Shanley, 1990). For that reason, we included the level of institutional ownership by calculating the percentage of total shares owned by institutions such as mutual funds or investment banks in year t (Bednar et al., 2015; Fombrun & Shanley, 1990).
We also controlled for year-specific effects by including the years 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998 and 1999 as time-dummy variables (Philippe & Durand, 2011). The year 2000 is the omitted year.
3.5. Analysis
To test our hypotheses, we used a panel design with the firm-year as the unit of analysis. We estimated the parameters of our model by ap- plying a fixed-effects model, which takes into account firm-specific errors. The fixed-effects model assumes that firm-specific heterogeneity is “fixed” in the intercept term and thus allows firm-specific error terms to be correlated with regressors. We also conducted a Hausman test to evaluate whether our choice was appropriate for our data (Greene, 2003; Gujarati, 2003). The Hausman test was significant (p < 0.01), which confirms that choosing a fixed-effects model over a random-ef- fects model was the right choice.
4. Results
Table 2 presents the means, standard deviations and correlation coefficients for all variables used in our analysis. The results of the firm- fixed-effects regressions of the explanatory and control variables on corporate reputation are presented in Table 3.
The F-statistic indicates that each model is significant (p < 0.01) compared to the control model. The adjusted R-square for each model is high (0.87). Our models thus have a good predictive ability with regard to corporate reputation. Model 1 in Table 3 is the base model of control variables regressed on corporate reputation. The results indicate that prior corporate reputation, average profitability, market capitalization change and institutional ownership are significant and positively asso- ciated with corporate reputation while firm size is significant and ne- gatively associated with corporate reputation. Model 2 in Table 3 tests the direct effect of downsizing on corporate reputation. As shown in Model 2, corporate downsizing is significant and negatively related to corporate reputation (β = -0.15, p < 0.01). If firms downsize, their reputation score decreases on average by 0.15. These findings support prior research in that corporate downsizing is associated with reputa- tional penalties.
In Model 3 in Table 3, we test Hypothesis 1 that the impact of downsizing on corporate reputation will be more negative when the announced motive for downsizing is associated with an increase in ef- ficiency than when it is associated with a decline in demand. To test this hypothesis, we included the motives for downsizing as independent variables in the model. As Model 3 shows, efficiency-motivated down- sizing has a significant and negative impact on firm reputation (β = −0.12; p < 0.01), while demand-decline-motivated downsizing is not significant. These findings provide support for Hypothesis 1, when downsizing is driven by a desire to increase efficiency, its impact on corporate reputation is more negative than when it is driven by a de- cline in demand. In Model 4 we test Hypothesis 2 that during the 1990s announcements of downsizing that were made after 1996 had a more negative impact on corporate reputation than announcements made before 1996. As Model 4 shows, the coefficient of post-1996 downsizing is significantly negative (β = −0.20, p < 0.01) and larger than the coefficient of pre-1996 downsizing (β = −0.12, p < 0.05). Although the difference of the coefficients is not significant, our findings provide
A.-C. Schulz, S. Johann Scandinavian Journal of Management 34 (2018) 40–50
45
partial support for Hypothesis 2. Hypothesis 3 suggests that the impact of downsizing on corporate reputation will be moderated by the extent of past instances of downsizing in the same firm. As shown in Model 5 in Table 3, the interaction of corporate downsizing and the extent of prior downsizing is significant and positive (β = 0.89, p < 0.05), which supports our Hypothesis 3. These findings indicate that down- sizing announcements have a more negative impact on firm reputation if a firm has already downsized extensively during the previous two years.
4.1. Supplementary analyses
To examine the robustness of our findings we conducted additional analyses. First, we analyzed the models for our study sample (S&P 100)Ta
b le
2 D es cr ip ti ve
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d C or re la ti on
sa ,b .
V ar ia bl es
M ea n
s. d .
1 2
3 4
5 6
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9 1 0
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1 3
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6 .5 9
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0 .3 0
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0 .4 0
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0 .3 9
– 6 . P os t- 1 9 9 6 d ow
n si zi n g
0 .1 1
0 .3 1
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− 0 .1 7
– 7 . E xt en
t of
p ri or
d ow
n si zi n g
0 .0 4
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− 0 .2 3
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0 .1 1
0 .1 3
– 8 . P ri or
co rp or at e re p u ta ti on
6 .6 5
0 .9 9
0 .9 1
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– 9 . Fi rm
ag e
7 6 .4 8
4 2 .4 5
0 .1 0
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0 .0 8
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0 .0 9
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si ze
9 .5 8
0 .9 8
0 .2 3
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– 1 1 . A ve
ra ge
p ro fi ta bi li ty
0 .0 5
0 .0 5
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− 0 .1 9
− 0 .1 4
− 0 .0 7
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ra ge
sa le s gr ow
th 0 .0 7
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− 0 .1 4
− 0 .0 6
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– 1 3 . P ro fi ta bi li ty
ch an
ge (t , t- 1 )
− 0 .1 8
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0 .0 8
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ch an
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0 .1 7
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0 .0 7
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0 .0 5
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– 1 7 . T ob
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1 .4 7
1 .3 4
0 .4 7
− 0 .1 8
− 0 .1 4
− 0 .1 1
− 0 .1 8
0 .0 4
− 0 .1 4
0 .4 7
0 .0 1
− 0 .0 3
0 .7 1
0 .1 5
0 .0 8
0 .0 8
0 .1 8
0 .1 6
– 1 8 . Fi rm
ri sk
0 .2 0
0 .1 2
− 0 .1 7
− 0 .0 6
− 0 .0 0
0 .0 6
− 0 .0 8
0 .0 1
− 0 .0 8
− 0 .1 5
0 .1 2
0 .0 5
− 0 .2 6
0 .0 2
− 0 .0 5
− 0 .1 1
− 0 .1 0
− 0 .1 2
− 0 .2 3
– 1 9 . In st it u ti on
al ow
n er sh ip
0 .5 7
0 .1 4
− 0 .2 2
− 0 .1 2
− 0 .1 3
− 0 .1 1
− 0 .1 9
0 .0 7
− 0 .0 1
− 0 .2 6
0 .1 3
− 0 .3 9
− 0 .1 5
− 0 .1 0
− 0 .0 1
0 .0 4
0 .1 0
0 .0 3
− 0 .0 9
− 0 .1 3
a n =
6 4 6 fi rm
-y ea rs .
b C or re la ti on
s la rg er
th an
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ifi ca n t at
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Table 3 Results of fixed-effects regression analysisa.
Variables Model 1 Model 2 Model 3 Model 4 Model 5
Constant 3.82*** 3.92*** 3.87** 3.86** 3.95**
(0.82) (0.81) (0.81) (0.81) (0.81) Prior corporate reputation 0.69** 0.68** 0.69** 0.68** 0.67**
(0.03) (0.03) (0.03) (0.03) (0.04) Firm age −0.01 −0.01 −0.01 −0.01 −0.01
(0.01) (0.01) (0.01) (0.01) (0.01) Firm size −0.15† −0.15† −0.15† −0.16† −0.17†
(0.08) (0.08) (0.08) (0.08) (0.08) Average profitability 1.34* 1.16* 1.14* 1.22* 0.81
(0.60) (0.60) (0.60) (0.60) (0.62) Average sales growth 0.29 0.24 0.24 0.27 0.24
(0.25) (0.24) (0.25) (0.25) (0.24) Profitability change (t, t-1) 0.01 0.00 0.01 0.00 0.00
(0.01) (0.01) (0.01) (0.01) (0.01) Profitability change (t-1, t-
2) −0.00 −0.00 −0.00 −0.00 −0.00
(0.01) (0.01) (0.01) (0.01) (0.01) Market capitalization
change (t, t-1) 0.43** 0.40** 0.40** 0.39** 0.40**
(0.06) (0.06) (0.06) (0.06) (0.06) Market capitalization
change (t-1, t-2) 0.30** 0.27** 0.28** 0.28** 0.28**
(0.05) (0.05) (0.05) (0.05) (0.05) Tobin’s Q 0.04 0.03 0.03 0.03 0.03
(0.03) (0.03) (0.03) (0.03) (0.03) Firm risk −0.16 −0.23 −0.19 −0.23 −0.24
(0.27) (0.27) (0.27) (0.27) (0.27) Institutional ownership 0.44† 0.42† 0.41 0.42† 0.48†
(0.25) (0.25) (0.25) (0.25) (0.25) Corporate downsizing −0.15** −0.21**
(0.04) (0.04) Efficiency-motivated
downsizing −0.12**
(0.04) Demand-decline-motivated
downsizing −0.05
(0.05) Pre-1996 downsizing −0.12*
(0.05) Post-1996 downsizing −0.20**
(0.06) Extent of prior downsizing −0.92**
(0.35) Corporate downsizing x
Extent of prior downsizing
0.89*
(0.41)
F-statistic 36.56** 36.59** 35.28** 35.07** 34.18**
R-square 0.89 0.89 0.89 0.89 0.89 Adjusted R-square 0.87 0.87 0.87 0.87 0.87
a n = 646 firm-years; all regression models also include time dummy variables that are jointly significant (p < 0.01).
† p < 0.10. * p < 0.05. ** p < 0.01. *** p < 0.001.
A.-C. Schulz, S. Johann Scandinavian Journal of Management 34 (2018) 40–50
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to examine the effect of corporate downsizing on firm reputation in a more recent period; namely, 2010–2012. In that period, downsizing events were less frequent than in the period that our original sample covers. In the 2010–2012 period the percentage of firm-years with downsizing is smaller than in the 1990–2000 period, i.e., 12.9% com- pared to 30.4% of firm-years respectively. This disparity is not sur- prising, given that during the 1990s the frequency and scale of mass layoffs in US companies were unprecedented (Morris, Cascio, & Young, 1999; Wagar, 1998) − this, as we explained, is the reason why we chose the 1990–2000 period for our investigation. Our analysis shows that in the more recent period, i.e., 2010–2012, downsizing had a ne- gative and significant effect on firm reputation (β = −0.26; p < 0.01) and that previous layoffs in the same company weakly moderate this relationship (β = 6.17; p < 0.10). Our results indicate that the motive for downsizing had no impact on reputation in this period; however, this can be explained by the lower frequency of downsizing events in the 2010–2012 period. Overall, the additional analysis reveals that our results are on the whole robust even in a period characterized by less downsizing.
In our second robustness test, we aim to test the robustness of our findings for alternate reputation measures and specifically analyze the impact of downsizing on the firm’s reputation as employer. Current and potential employees are important stakeholders of the firm. For ex- ample, Brown and Matsa (2016) show that firms get fewer and lower quality applications if they are under financial distress. We used the 100 Best Companies to Work for in America (BCW) as dependent variable for our 1990–2000 sample. The list is based on a score that is compiled from employee responses to a survey created by the Great Place to Work Institute and the institute’s evaluation of work conditions at the re- spective companies (for a detailed description of the data, see Edmans, 2011). Using this list, we measured the impact of downsizing on the firm’s reputation as employer. On the basis of the information we de- rived from the list, we created two dependent variables: the dummy variable top-25 firm, which takes the value “1” if the firm was listed among the top 25 firms and “0” otherwise, and the dummy variable top- 50 firm, which takes the value “1” if the firm was listed among the top 50 firms and “0” otherwise. Because the BCW only contains limited data about our sample of S&P 100 firms for the period 1990–2000, the sample for this additional analysis was reduced to 178 firm-years for 1993, 1998, 1999, and 2000. Interestingly, the ranking of the firms listed in the BCW is highly correlated with our AMAC reputation score (rho = 0.26, p < 0.01), which supports our choice of the AMAC score as a reputation measure. We investigated the relationship between downsizing and employee reputation using the dichotomous variables top-25 firm and top-50 firm as dependent variables. We ran simple logit models and used the same control variables as in our original models. The results show that downsizing has a negative and significant impact (β = −2.50; p < 0.05) on the predicted probability that the company was ranked among the top 50 firms and a negative and weakly sig- nificant impact (β = −2.30; p < 0.10) on the predicted probability that the company was ranked among the top-25 firms. Thus, firms that downsize are less likely to be rated as top employers. These results are consistent with our findings that downsizing is negatively associated with firm reputation and reveal that the effect of downsizing on firm reputation is robust independently of the stakeholder group that eval- uates the reputation of that firm.
5. Discussion
5.1. Main findings and contributions of this study
This study was motivated by the need to gain deeper insights into how specific aspects of a firm’s decision to downsize influence the ne- gative impact of downsizing on firm reputation. For that purpose, we examined how the motive for downsizing, the time period of the downsizing announcement and previous downsizing measures impact
the relationship between downsizing and firm reputation during the 1990s in the US. Our findings indicate that, on average, downsizing due to a decline in demand does not impact a firm’s reputation, while downsizing intended to increase efficiency has a significantly negative impact on a firm’s reputation. Moreover, we found that the time period of downsizing also influences the reputational effects. Downsizing measures that are announced in periods when the media and internal and external stakeholders are particularly critical of layoffs tend to have a more negative impact on a firm’s reputation. Finally, we found that extensive previous layoffs strengthen the negative effect of downsizing on firm reputation.
The results of our study have various implications for management research and business practice. First, our findings contribute to the literature on the organizational outcomes of downsizing by providing a more detailed understanding of the relationship between downsizing and corporate reputation. Prior research has shown that the negative impact of downsizing on reputation can be cushioned by certain firm characteristics such as firm age or firm performance (Flanagan & O’Shaughnessy, 2005; Love & Kraatz, 2009). Specifically, the reputa- tion of older firms and of firms that performed poorly in the preceding year tends to suffer less when they downsize. Although previous works provide evidence that the firm-specific context plays an important role in the relationship between downsizing and firm reputation, we are the first to find that specific characteristics of the downsizing measure in- fluence this relationship. Our study shows that the motive for down- sizing, the time period of the announcement, and the extent of previous layoffs may either buffer or amplify the reputational effects of down- sizing. Specifically, we have shown that if downsizing is viewed as an externally driven necessity aimed to ensure the firm’s survival, as in the case of a sudden decline in demand, the decision may be evaluated as legitimate and may not affect negatively the firm’s reputation. On the contrary, if managers decide to downsize a firm in order to streamline operations and improve efficiency, regardless of the firm’s actual per- formance, stakeholder groups such as employees may perceive down- sizing primarily as an internally driven, selfish decision that serves only the interests of managers and shareholders. In such cases, downsizing is likely to have a much more negative impact on the firm’s reputation. In sum, our study demonstrates that the motives for downsizing influence decisively its reputational effects. In addition, our results indicate that the time period of the downsizing announcement, particularly in rela- tion to critical events, such as unprecedented layoffs, also influences significantly the extent of these reputational effects. Specifically, we found that if a firm downsizes after a critical event that significantly and negatively influenced the general public view on layoffs, the ne- gative impact of this decision on the firm’s reputation is slightly more pronounced. We furthermore found that the extent of previous layoffs also influences the magnitude of the effect that downsizing has on a firm’s reputation. When firms have already downsized to a large extent in the past, downsizing again leads stakeholders to view much more negatively the prospects of the firm. Hence, we can conclude that sta- keholders are far from forgetting these past decisions. Instead, they add to the reputational penalty of the firm.
Second, our study also contributes to the literature on the de- terminants of corporate reputation (for an overview, see Ali, Lynch, Melewar, & Jin, 2015). Previous studies in this stream have investigated the direct impact of variables such as firm performance, firm size or firm risk (e.g., Fombrun & Shanley, 1990; McGuire et al., 1990), the impact of governance decisions (Bednar et al., 2015) and management decisions such as the adoption of popular management techniques or market actions (Basdeo et al., 2006; Staw & Epstein, 2000). However, there is little research on the impact of corporate restructuring deci- sions on a firm’s reputation. We add to this body of knowledge by in- vestigating one type of corporate restructuring, namely downsizing. By showing how specific aspects of this type of corporate restructuring decision affect a firm’s reputation, we gain a more fine-grained un- derstanding of the underlying factors that influence this relationship.
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Third, our study also contributes to the emerging stream on the relationship between critical events and firm behavior in management research (e.g., Chandler, 2014; Hoffman & Ocasio, 2001). Previous studies have sought to understand how critical events impact the broader institutional context of a firm and how firms respond to such events. Hoffman and Ocasio (2001), for example, investigated differ- ences in the attention that the media and industry experts pay to var- ious types of critical events and Chandler (2014) examined how critical events impact institutional pressure on a firm and, consequently, a firm’s behavior. We contribute to this discussion by investigating how a critical event − in this case, an unprecedented mass layoff − by one firm can change the public debate on mass layoffs and moderate the reputational effects of similar events for other firms.
Fourth, our findings also highlight the evidence of previous research that reputation can be fragile and hard to restore. Once it is eroded, it takes time to rebuild it (Herbig et al., 1994). One consequence of the negative impact that downsizing has on corporate reputation is that it may hinder a firm’s access to important resources and ultimately weaken its performance. This suggests that when managers intend to lay off employees, they need to consider the potential damage to the firm’s reputation in addition to other costs associated with downsizing and need to find ways of mitigating the negative reputational effects and/or try to restore the firm’s reputation. One way of mitigating the negative effect is to proactively influence the perceptions of the firm’s stakeholders through carefully constructed announcements (Elsbach, 1994). For example, if managers need to announce massive layoffs, they may need to consider that certain motives may be viewed as more ac- ceptable than others and thus cause less damage to the firm’s reputa- tion. Generally, how and when to announce layoffs and what in- formation to provide are important considerations. In this context, our study also suggests that it might make sense for firms to improve the communication (e.g., via the services of independent IR firms) in order to reduce the reputational damage of downsizing or even restore the firm’s reputation in the long-run. This suggestion is based on evidence that IR firms can influence significantly the media coverage of news that concerns specific firms (Solomon, 2012), and thus the views of stakeholders whose opinions are shaped by information provided by the media.
Finally, the potential reputational damage that is associated with downsizing might managers also induce to reconsider the necessity of potential layoffs. For example, Harrison and Scorse (2010) show that anti-sweatshop campaigns which were aimed to improve work condi- tions for employees lead to significant wage increases. In order to avoid reputational damage as consequence to these campaigns managers in- creased wages. Similarly, rational managers might consider the re- putational costs associated with downsizing and, in consequence, avoid downsizing, if possible.
5.2. Limitations and future research
This study has certain limitations, which may stimulate further re- search into its topic. One limitation is that we investigated how specific aspects of downsizing influence a firm’s reputation. The set of con- textual conditions on which we focused, however, is not exhaustive. Future studies could investigate how other contextual conditions, such as the type of ownership or third-party actors such as labor unions or the media may affect the relationship between downsizing and re- putation. For example, Friebel and Heinz (2014) have shown that downsizing announcements made by foreign-owned firms attract greater media attention than announcements made by domestic firms and that the tone of media reports is more negative in the first case. Furthermore, in our study, we treat the media as important information intermediaries that decrease information asymmetries between a firm and its stakeholders. However, the media are also active agents that can select and bias information. Therefore, we think that it would be in- teresting for future research to explore how media coverage of firms
undertaking downsizing influences the relationship between down- sizing and firm reputation.
A second limitation of our study is related to the study context. Our Hypothesis 2 is specifically related to the public debate on downsizing in the US. In our analysis, we examine the S&P 100 firms in the 1990s. However, although we would expect similar results for firms in other countries in a different time period, we do not know yet whether and to what extent these findings are generalizable. An analysis of these re- lationships for different countries and time periods may thus be an interesting future research avenue.
Furthermore, future research could explore the perceptions of var- ious stakeholder groups in greater depth and how downsizing is per- ceived by different stakeholders. The reputation data for this study come from managers and directors as well as investment analysts. These are experts of the firm and its industry and are thus important stake- holder groups. However, there are other groups of stakeholders such as customers and suppliers whose perceptions are also influential for a firm’s reputation.
Finally, researchers could also examine how the reputational effects of downsizing develop in the long-term, how much time it takes for a firm’s reputation to recover from the negative effects of downsizing and which potential measures could help to restore corporate reputation.
6. Conclusion
This study extends prior research on the impact of downsizing on external corporate reputation by investigating how specific aspects of downsizing measures influence a firm’s reputation. Our results show that downsizing affects corporate reputation negatively and that the size of the effect depends on the motive for downsizing, the timing of downsizing and the extent of previous layoffs. These findings elucidate how the content and context of downsizing announcements can sig- nificantly influence the extent of the reputational penalties that are associated with corporate downsizing and advances our understanding of the organizational outcomes of downsizing and the moderating role of critical events.
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- Downsizing and the fragility of corporate reputation: An analysis of the impact of contextual factors
- Introduction
- Theoretical background and hypotheses
- The impact of downsizing on corporate reputation
- The impact of the content and context of downsizing
- The motive for downsizing
- Time period of downsizing
- Extent of prior downsizing
- Method
- Sample
- Dependent variable
- Explanatory variables
- Corporate downsizing
- Motive for downsizing
- Time period of downsizing
- Extent of prior downsizing
- Control variables
- Analysis
- Results
- Supplementary analyses
- Discussion
- Main findings and contributions of this study
- Limitations and future research
- Conclusion
- References
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(Bloomberg) -- Bankrupt Japanese Town Takes Drastic Steps to Halt 'Ghost' Status
Bankrupt Mining Town Downsizes to Avoid Becoming a Ghost
A sleepy, former coal-mining town in northern Japan is taking unprecedented measures to combat its biggest challenge: a devastating shrinking of its population. Its success could decide the future for hundreds of other local governments waging the same battle for survival.
Since its peak in the post-war economic boom of the 1960s, the population of Yubari, a little more than an hour's drive east of Sapporo on Japan's northern island of Hokkaido, has declined by more than 90 percent to just 9,000 as older residents died and young people moved away to bigger cities. Ten years ago, it became Japan's first municipality to declare bankruptcy.
To keep from becoming a so-called ghost town—when a city ceases to function due to a precipitous decline in population and is ultimately abandoned—Yubari embarked on a drastic experiment. City officials began merging schools, slashing government jobs and salaries, halting funds for public swimming pools, toilets and parks, curtailing services such as bus routes and snow removal, and downgrading the local hospital to a clinic. The most drastic measure has been the forced relocation of hundreds of residents from public housing on the city's outskirts to blocks of new, low-rise apartments closer to the city center.
"Yubari can potentially lead the example of a real-time compact city," said Yoshio Kurihara, senior researcher at Mitsui Global Strategic Studies Institute in Tokyo, who called Yubari's experiment an "extremely important" model for Japan. "Successful results from the city's trial can be applied on a nationwide scale."
By 2040, about half of Japan's municipalities, or 896 towns and cities, will be on a course to future extinction as their numbers of women of reproductive age drop below levels needed to sustain them, according Japan Policy Council projections. More than 20 percent of residential areas in Japan will become ghost towns by 2050, Japan's land ministry forecasts. And data from the National Institute of Population and Social Security Research show a 16 percent population decline country-wide within 25 years, with 20 percent of municipalities experiencing a drop below 5,000 people. The "compact city" solution is being considered as a model for survival by these areas facing depopulation.
Some small towns and cities in rural prefectures have been experimenting with merging to reduce public administration costs. That has led to a small local government looking after a large area, making it difficult to provide services to remote residents.
Authorities in prefectures such as Aomori and Toyama also have been trying to implement the compact city strategy, but they have faced strong resistance from residents to relocate even after improving transportation and commercial infrastructure to lure people into central areas. That makes the Yubari experiment, largely being carried out with public support, unique.
"Yubari's example can definitely be applied to other municipalities," Kurihara said. "Yubari shows what the future holds and offers hints."
Negative Reaction
Residents had initially reacted negatively to the relocation plan, according to Tsuyoshi Setoguchi, a professor specializing in urban planning at Hokkaido University, who was involved in creating and implementing Yubari's compact city plan. He and his students met with relocated residents over the course of a year to provide details of the plan and convince them of the benefits.
"Their first reaction was, 'We are old and are gone in 10 years so why not leave us alone,' or that to move was too tiresome at that point in their lives," said Setoguchi, noting that a survey of a group of relocated residents he conducted showed they gave an above-average rating to their new environment. "Many expressed the merits of being able to live in an assembled community, which provided a sense of security and helped cut costs such as heating."
Some residents complained about the environment for raising children, with public parks suffering from funding cuts and kids having to leave town for high school. Yet for others, a new home is an upgrade.
Convenient Bathing
Yoneo Watabiki, 76, who spent a third of his life working at the coal mines, said he had no qualms about leaving the public housing, made of wood, where he'd lived with his family for decades.
"I am glad I moved," Watabiki said. "Now I have a bath in my own house and don't have to go to public bathhouses. I can take a shower when I want to."
Another resident, Kiyoshi Yanagihara, 97, who moved to Yubari to work in the mines after completing military service in 1943, said he also enjoys having a more convenient place to bathe, as well as a nearby food cooperative and neighbors who cook for each other.
"The current residence is very comfortable compared with the previous one—like heaven and hell," he said. "I don't feel lonely because the people I've lived with for 20 and 30 years have all relocated together."
More Housing
Since starting the relocation process in 2010, Yubari had moved 275 households, or 5 percent of total, as of 2015. As a result, the cost of maintaining and managing public housing has fallen to about 70 million yen ($680,000) annually from about 100 million yen six years ago. The plan is to construct 33 more low-rise blocks for public housing by 2020, as well as build or renovate low-rent apartment blocks for at least 800 workers who currently commute from the outskirts. By 2019, the city plans a complex to potentially house government offices, a library, a cafe, a childcare center and other facilities.
These days, the outskirts of Yubari are dotted with vacated, decrepit buildings. Faded billboards of old movies such as "Roman Holiday" can be seen downtown near a now-deserted entertainment area where closed cafes and karaoke bars provide a glimpse of the hustle-bustle of days of old. The lively town was a coal capital in Japan, and its population grew to 117,000 in the 1960s. Yubari has been in slow decline over the past 50 years. The last mine closed in 1990.
Most Aged
Its 9,000 people are collectively the country's most aged, with those 65 and older accounting for 48 percent of its residents. Yubari's population is expected to further halve over the next 10 years.
Through cost-cutting measures, Yubari has paid back about a third of its debt accrued through bond issuance, but still has to repay 25 billion yen by March 2027. The city's revenue has dwindled by about two-thirds since 2009.
Yubari Mayor Naomichi Suzuki, 35, said the city is looking to tap revenue from national resources, namely coal-bed methane from the former mines.
"It's important to balance the defensive policy of the compact city plan with an offensive one of lifting revenue," he said in an interview.
Even though the population outlook looks grim, the city's youngest-ever mayor, who took office in 2011, says there are other ways to build a successful community.
"Child care is a top priority, and we are rapidly building low-rent houses for the young, because a favorable environment for them is key to the city's sustainability," he said. "Yubari's population will likely fall by half 10 years from now, but population isn't everything. I want to assess by whether people feel happy remaining here."
—With assistance from Chris Cooper and Katsuyo Kuwako.
Yubari's efforts called "extremely important" model for Japan. Attribution Chris Cooper: contributor Katsuyo Kuwako: contributor Chikako Mogi: author Yuki Hagiwara: author Garfield Clinton Reynolds: editor Yusuke Miyazawa: editor Kazunori Takada: editor Sheridan Prasso: editor
To contact the authors of this story: Chikako Mogi in Tokyo at [email protected] Yuki Hagiwara in Tokyo at [email protected]
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The Essence of Downsizing: A Review of Literature
Prantika Ray & Sunil Maheshwari
Prantika Ray (E- mail: [email protected]) is Doctoral Scholar & Sunil Maheshwari (E-mail: [email protected]) is Professor, Human Resources Management Area, Indian Institute of Management Ahmedabad 380015.
The process of downsizing has often been considered as a one- time activity that is disconnected from the processes and the out- comes associated with the activ- ity. Since the strategies, organi- zational, industrial and environ- mental characteristics play a cru- cial role in determining the suc- cess and/or failure of the downsizing process, a piece-meal approach to the research on downsizing is not enough. This paper thus presents a holistic view of the downsizing process where the dynamics that ensue during the downsizing are eluci- dated in a framework. This pa- per further discusses certain im- plications for practitioners and provides scope for future research for the researchers.
Introduction
The aftermath of the process of downsizing by organizations is a very cru- cial point of concern. Several research- ers have spoken about the possible out- comes in relation to firm’s operational performance such as organizational learning capacity, change in the organi- zational culture (Cascio, 1993), techno- logical advancement (Maheshwari & Kulkarni, 2003), improvement of the organization’s competitive position (Amabile & Conti, 1999), financial and market outcomes such as market valua- tion (Love & Kraatz, 2009; ), short-term market reaction (Love & Kraatz, 2009), signal for potential synergies (Bowman & Singh, 1993; Cascio et al., 1997; Demuse et al., 1994), and willingness for future acquisitions (Krishnan, Hitt & Park, 2007). However, after the organi- zation has been downsized, additional challenges are made in handling the re- maining human capital in the organiza- tion. In this paper, we have concentrated on the outcomes of downsizing based on current and potential employees. It is vi- tal for an organization as an employer to consider various factors to ensure high commitment and low turnover intentions of the present employees and the attrac- tiveness of the organization for the po-
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tential job-seekers. These factors are firm characteristics, industry character- istics, individual characteristics (em- ployee and their supervisors); possible outcomes of various downsizing pro- cesses, and various steps implemented by the organization to combat negative ef- fects of downsizing.
What Is Downsizing?
Downsizing has been defined as “the planned elimination of positions and jobs, which does not include the normal retire- ments or resignations, but the voluntary severance and early retirement pack- ages” (Cascio, 1993). It refers to a de- liberate intention of laying off a certain number of workforce from the organiza- tion. Organizational decision makers pro- vide various reasons behind downsizing, which are the following:
Downsizing is basically considered a mode to remove the redundan- cies in the organization, and it is mostly considered in the terms of headcount reduction.
(a) To reduce costs (Gandolfi & Hansson, 2011; Sahdev, 2003), (b) to improve the speed of decision-making (Cameron, 1994), (c)to improve one’s competitive strategy (Levitt, Wilson, & Gilligan, 2008; Macky, 2004), (d) to enhance communica- t ions within the organization (Cameron, 1994), (e) to maximize shareholder returns (Escalante, 2001), and (f) to improve organiza- tional efficiency (Zyglidopoulos,
2003) and productivity (Cameron, 1994). Downsizing is basically con- sidered a mode to remove the redun- dancies in the organization, and it is mostly considered in the terms of headcount reduction; but it can also be a form of revamping the job de- sign and revisiting and redesigning certain jobs (Cascio, 1993).
Forms of Downsizing
Downsizing can thus be broadly cat- egorized into three types:
Workforce Reduction: Organiza- tions have taken up workforce reductions not only to reduce the salary, training, promotion, and rewards related to the costs in the organizations but also as an attempt to create a ‘lean’ organization. The workforce reduction could be in terms of hiring freezes, layoffs, volun- tary retirement, and golden handshakes (Howard, 1988; Maheshwari & Kulkarni, 2003; Tourish, Paulsen, Hobman & Bordia, 2004). The first form of workforce reduction unlike the other three is the stoppage of the recruitment into the organization, and thus barring the entry of the potential employees and keeping the current employees unaf- fected (Feldman, 1996). The downside of hiring freezes is the signal to the job market about the difficulties in the func- tioning of the company, which will affect the future jobseeker’s attraction to the organization (Feldman, 1996). The effec- tiveness of voluntary retirement and golden handshakes is decided by the tim- ing, the composition of the people asked to leave, and the rationale behind the re-
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duction in workforce. If the employees in the organization are nearing their re- tirement age, their commitment and pro- ductivity probably decrease, the early departure of such employees enhances the proportion of highly motivated and productive employees in the organization (Howard, 1988).
Work Redesign: Organizations take up work redesign to eliminate redundant jobs and units, and the target of the re- design is to define better job roles and refine the work done by the employees. The redesigning of work could be in the form of abolition of functions, merger of units, job redesign, and reduction of work hours (Gandolfi, 2005). Work redesign is based on two parameters of work in the organization—autonomy and workload; the primary aspect is to bring change in the two parameters (Mishra & Spreitzer, 1998). Gandolfi (2005) discussed the depth and breadth of the downsizing strategies; the four levels of downsizing with the objective of work redesign are layer elimination, unit combination, prod- uct removal, and process arrangement. With the merger of organizations, there are instances where similar units or prod- ucts in both the organizations are merged, and thus, these redundancies could either be completely eliminated or redesigned with newer process roles or objectives. Griffin (1991) showed that the work re- design has no immediate short-term ef- fects, but in the long term, it affects em- ployees’ behavioral outcomes as well as the organizational outcomes.
Systemic Strategy: This strategy, un- like the other two, aims at eliminating
workforce or at changing the organiza- tional culture and brings about attitudinal differences in the employees. The strat- egy aims at a bottom-up approach and in- creases the accountability of the entire organization (Cameron, 1994). Cascio (1993) discussed the systemic strategy, which being a long-term strategy leads to the development of a continuous improve- ment in the organization. These strategies can vouch for a better employer brand, as it sends a signal to the potential em- ployees about the organization’s objectives to develop an environment for the employee’s career advancement.
Process Elements & Outcomes
Organizational Commitment and Turnover Intentions: Downsizing is implemented through workforce reduc- tion, and hence, it is often followed by role overload and lack of role clarity. In addition, the survivors or the employees retained in the organization exhibit low levels of organizational commitment and high turnover intentions (Allen, Free- man& Russell , 2001; Waraich & Bharadwaj, 2012). Thus, organizations implementing the downsizing processes through work redesign strategy further intend to develop clearer roles for the employees, reduce the role overload, and enhance role clarity that would lead to higher commitment levels and lower turn- over intentions (Ugboro, 2006). Hence:
Downsizing is implemented through workforce reduction, and hence, it is often followed by role overload and lack of role clarity.
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Proposition 1: Organizations imple- menting the downsizing strategy through utilization of the workforce redesign strat- egy would report higher levels of com- mitment and lower turnover intentions compared to the workforce reduction strategy.
Organizational identification is a step ahead of organizational commitment, where the employees incorporate the organization’s values, norms, etc., into their self-identities, and the self-defini- tion is tied to the collective (Knippenberg & Sleebos, 2006). Organizational com- mitment is found to be strongly related to the perceived organizational support than the organizational identification be- cause the former considers the individual and the organization as two distinct enti- ties. Organizational commitment has been found to be more closely related to turn- over intentions than organizational iden- tification owing to the greater associa- tion of organizational membership in the former (Knippenberg & Sleebos, 2006; Gautam, Dick & Wagner, 2004). Hence:
Proposition 2: Downsizing would be more closely related to organizational com- mitment than organizational identifi- cation.
Trustworthiness of the Leader: Cameron (1994) discussed the impor- tance of visibility, accessibility of the leader, and the frequent interactions to confront the pain and discomfort in the organizational environment. The individu- als who remain in the organization after the downsizing process exhibits work- place behaviors based on the leadership
characteristics in the organization. If in- dividuals perceive the competency of their leader, they consider the manage- ment can improve the competitive stance of the organization (Spreitzer & Mishra, 2002). One major dimension of trustwor- thiness of the leader is the employee’s awareness about the goal of the organi- zation, i.e., the goals that the organiza- tion seeks to achieve and the means by which they would be achieved (Cho & Park, 2011). The second component of trustworthiness is dependent on the amount of autonomy given to the employ- ees (Cho & Park, 2011). However, im- mediately after the organizational downsizing, it may not be feasible to pro- vide autonomy owing to the sparseness of resources and dipped financial perfor- mance. At that point, communication about the various measures taken in the organization, supervisor’s attention to- wards job redesign, and reduction of work overload would increase the trustworthi- ness in the leader.
Proposition 3a: The leader’s accessibil- ity is strongly related to the trustwor- thiness of the leader.
Proposition 3b: The leader’s competency is strongly related to the trustworthi- ness of the leader.
Proposition 3c: The greater the commu- nication about the organization’s goals to the employees, greater is the trust- worthiness of the leader.
Presence of Unions: Appelbaum, Simpson, and Shapiro (1987) discussed in their paper that wrong communication about any downsizing decision in the
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unions might lead to possible disruptive behavior and employee unrest. The time and content of the news as well as the situational factors play a crucial role in determining the delivery of the notifica- tion of the downsizing plan. Hellgren and Sverke (2001) discussed in detail the ef- fect of union part icipation in the downsizing process. The proper commu- nication about the reasons for downsizing, educating the employees about the inter- ventions, and organizational strategies following the downsizing process would increase both the union satisfaction as well as the well-being of the employees.
Wrong communication about any downsizing decision in the unions might lead to possible disruptive behavior and employee unrest.
Managerial Discretion: Elvira and Zatzick (2002) discussed the role of managerial discretion in the case of in- voluntary layoffs. But if we consider the voluntary exits in the form of severance pay and early retirement incentives, the managerial discretion is lost to a greater extent. The reason behind it is that individual’s decision about staying or leaving the organization depends on the individual’s interests and the benefits re- ceived from the organization.
Perceived Justness of the Process: Employees eligible for the voluntary workforce reduction program expect fairness in the process in terms of ad- equacy of the provisions and communi- cation about the downsizing process. Al- though they are not the ones who leave
the organization, the probability of being targeted in the further downsizing pro- cesses makes the employees receptive about the fairness of the measures taken by the organization. The fairness is based on the amount of input an individual has put in the organization and the provisions received in return, in other words, the distributive justice. Those who perceive the process to be fair would show higher levels of commitment and lower turnover intentions. Hence:
Proposition 4a: Survivors who find the provisions taken up in the downsizing process adequate would show higher levels of organizational commitment and lower turnover intentions.
The survivors often feel the loss of control over the situation, and so an en- vironment of uncertainty develops in their workplace (De Vries & Balazs, 1997). In the process of the workforce reduc- tion, if only the workforce is eliminated without any redefinition or elimination in the job, there can be incidences of high stress in the organization. The primary reasons behind it are work overload, role ambiguity, etc. (Brockner, 1992). This could even lead to lower perceived or- ganizational support, lower organizational commitment, higher burnout, and greater intentions to quit (Tombaugh & White, 1990; Ugboro, 2006). Hence:
Proposition 4b: Greater the perceived uncertainty in the workplace, lesser is the perceived organizational sup- port.
Proposition 4c: Survivors perceiving un- certainty in the workplace would ex-
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hibit lower organizational commit- ment.
Proposition 4d: Survivors perceiving un- certainty in the workplace would ex- hibit greater intentions to quit.
Proposition 4e: Survivors perceiving un- certainty in the workplace would ex- hibit higher burnout.
Perceived Degree of Threat: Lazarus and Folkman’s framework elu- cidates the stress in the post-downsizing environment, especially when there is a limitation on the autonomy of the individu- als, increase in workload and an uncer- tainty of further layoffs in the organiza- tion. These factors lead to an increased perception of threat in the minds of the individuals (Brockner, Spreitzer, Mishra, Hochwarter, Pepper & Weinberg, 2004). Hence:
Proposition 5a: Individual’s perceived degree of threat is related to work overload.
Proposition 5b: Individual’s perceived degree of threat is related to the in- creased uncertainty in the environ- ment.
Perceived degree of empowerment: Brockner et al. (2004) explicated in their paper that the perceived control of the post-layoff situation could help the sur- vivors to cope with the perceived threat of well-being that might arise due to the uncertainties in the workplace and job roles. Mishra, Mishra and Spreitzer (2009) developed a matrix on two dimen- sions, namely, the degree of trust in man- agement and the degree of empower-
ment, and concluded that employees high on both the dimensions provided the most constructive responses and also acted as “active advocates” by giving useful in- sights for the development of the organi- zation. An important point highlighted in this paper is that high degree of empow- erment should be coupled with high trust in the management; otherwise, the re- sponses could be detrimental.
High degree of empowerment should be coupled with high trust in the management; otherwise, the responses could be detrimental.
Career Life Cycle Stages- Early- career, Mid-career, and Late-career: The effects of downsizing have been found to be varying on the individuals at different stages of their career life cycle (Feldman, 1996). The mid-career em- ployees, who are in the pursuit of reach- ing the top management roles, are greatly affected by the downsizing process (Feldman, 1996). The relationship be- tween job involvement and organizational commitment is maximum in the early- career stage (apprenticeship) and mini- mum in the late career stage (establish- ment stage) (Jans, 1989). Thus, the em- ployees at different stages of their ca- reer have different preferences. Hence, the assistance provided after the downsizing at various stages of career would be different. A person in the ear- lier stage of the career would seek a job with high job involvement, whereas a person in the latter stage would look at pension benefits (Jans, 1989). However, some extremely competent employees
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are lost in the “open window” or golden handshake program, and so there are organizations that even practice mana- gerial discretion through acceptance of VRS applications, but the firm perfor- mance in India shows not much improve- ment (Maheshwari & Kulkarni, 2003). In this situation, it is vital for an organiza- tion to carefully develop a plan for cat- egorizing the employees whom they defi- nitely want to retain and the ones who can be offered VRS. The most critical factor that needs to be considered be- fore applying managerial discretion is the individual’s willingness to stay in the or- ganization. Despite the competencies that the individual possesses, if an individual prefers voluntary retirement instead of staying in the organization, the idea of retaining the individual may not be fruit- ful.
Proposition 6: The managerial discretion would be significantly related to the exit of an employee from the organi- zation. The relationship is moderated by the voluntariness of the process in such a manner that the managerial discretion is predominant in the case of an involuntary turnover, whereas in the case of voluntary turnover, other factors such as severance package or the presence of unions predominate are also considered.
Organizational Characteristics
Industry Dynamism and Attractive- ness: Downsizing has a negative effect on learning and innovation as well as there is a loss of the social capital that the organization had built over the years
(Amabile & Conti, 1999; Fisher & White, 2000). Harrigan and Dalmia (1991) placed human capital in high-tech organization above any other organiza- tional assets, thus, attributing importance to the knowledge that gives an edge to the innovation-driven industry. This type of industry requires job autonomy and creativity (Amabile & Conti, 1999; Tzafrir & Eitam-Meilik, 2005). Organi- zations having high R&D intensity are extremely dynamic and base their com- petitive advantage on skilled human capi- tal, hence, it is observed that these or- ganizations have greater negative impact on their performance compared to the ones that are low on R&D intensity (Guthrie & Dutta, 2008). These organi- zations have high creativity and thus downsizing would act as an impediment on the creativity owing to increased workload pressures (Amabile & Conti, 1999). Organizations with high capital intensity and growth have been found to exhibit greater negative relationships between the downsizing process and the firm outcomes (Guthrie & Dutta, 2008). Hence:
Organizations with high capital in- tensity and growth have been found to exhibit greater negative rela- tionships between the downsizing process and the firm outcomes
Proposition 10: Workforce reduction downsizing strategy will have a greater negative impact on the cre- ativity of a high-tech organization as compared to a work redesign strat- egy.
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Organization’s Brand Image as an Employer: Perceived organizational sup- port is the individual’s perception of the organization’s support and care-taking characteristics that are aimed towards the individual’s well-being (Eisenberger, Huntington, Hutchinson & Sowa, 1986). It is observed that organizations adopt- ing workforce reduction strategies exhibit less attraction for job-seekers, and this relationship is mediated by the perceived organizational support (Kammeyer- Mueller & Liao, 2006). Rhoades and Eisenberger (2002) enumerated the three antecedents of the perceived organiza- tional support—fairness, supervisor sup- port, and organizational rewards and job conditions. Kammeyer-Mueller and Liao (2006) further discussed that the assis- tance, participation, and communication are the three strategies that organizations undertake to ensure that the impact on the employees is as minimal as possible. Prior communication about workforce reduction to the employees makes them consider the procedures to be transpar- ent and fair and thus induce procedural fairness. Moreover, work redesign is aimed at developing well-defined job roles in the organization. The well-estab- lished roles lead to a reduction in work overload and enhancement of job au- tonomy, thereby increasing the perceived organizational support (Rhoades & Eisenberger, 2002). Thus, with the en- hancement in perceived organizational support, one can expect an increase in job-seeker attraction.
Proposition 7a: Workforce reduction strategies incorporating prior com- munication to the employees would
report high job-seeker attraction, which is mediated by perceived or- ganizational support.
Proposition 7b: Work redesign strategies incorporating reduction of work over- load and enhancement of job au- tonomy would report high job-seeker attraction, which is mediated by per- ceived organizational support.
The impact of the downsizing pro- cess is significantly lower for a highly reputed firm.
Downsizing process is found to have a significant negative effect on a firm’s reputation as has been perceived by the market analysts and the peer firm ex- ecutives (Love & Kraatz, 2009). How- ever, the impact of the downsizing pro- cess is significantly lower for a highly reputed firm. Gatewood et al. (1993) stated that the individual’s perception of a firm’s reputation is strongly related to job seekers’ familiarity with the organi- zation. The familiarity can develop de- pending on an individual’s acquaintance working in the organization, through ad- vertisements or even through news ar- ticles. With the increased perception of organizational support in the downsizing process, the negative relationship be- tween downsizing and firm reputation is reduced. The increase in the assistance provided to retrenched employees and prior communicat ion about the downsizing process possibly induce organization’s trustworthiness in the minds of the potential employees, which is also a mode to enhance reputation (Love & Kraatz, 2009). Therefore,
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Proposition 8a: The downsizing process is negatively related to the job-seeker attraction and this relationship is mediated by firm reputation.
Proposition 8b: The negative relationship between downsizing and firm repu- tation is moderated by the perceived organizational support, such that with an increase in the perceived organi- zational support, the negative rela- tionship between them reduces.
The organizations undertaking the downsizing, especially workforce reduc- tion, send a signal to the potential em- ployees that they can rely less on getting a secured job in the organization (De Vries & Balazs, 1997; Kammeyer- Mueller & Liao, 2006). The individuals who would like to be employed in an or- ganization with high job security would avoid an organization that has downsized. This is because they consider such orga- nizations to be low on stable employment (Kammeyer-Muller & Liao, 2006). How- ever, the systemic downsizing that aims at revamping the organizational culture is seen as a constructive process that leads to the incremental and long-term development of human resources. Hence:
Proposition 9: Organization employing workforce reduction downsizing technique would report lower job- seeker attraction than organizations taking up systemic downsizing tech- niques.
Conclusion
Despite discussions on the effects of the downsizing process on the current
and future employees of the organization, there have been very few research pa- pers encompassing the process elements, the organizational characteristics, indi- vidual characteristics, leadership charac- teristics, and the future and current em- ployee outcomes. This study tries to col- late all the studies that have discussed the various aspects of downsizing and to tie them in one comprehensive theoreti- cal framework. Some of the relationships in the framework have been well-estab- lished but there is future scope of devel- oping empirical studies on the other pro- posed relationships. This study has sev- eral implications for both researchers and practitioners. There are several relation- ships that need to be empirically estab- lished, especially the mediation and mod- eration relationships. So, this study can act as a starting point for future research. Another contribution that the research- ers can further make in this regard is to include the established theories for ob- taining the causalities in the relationships that have been discussed in the study. Furthermore, the studies conducted in the field of downsizing process should be lon- gitudinal. Organizations that adopt downsizing need to take into account various firm characteristics, industry characteristics, and individual character- istics before choosing a downsizing strat- egy. It is evident that the combination of these characteristics would bring about a completely different scenario for each organization; therefore, imitating a downsizing strategy without considering these characteristics could lead to detri- mental outcomes. Thus, the organizations need to look at the downsizing process in a holistic approach and not a piece-
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Fig. 1 Conceptual Framework of the Downsizing Process
meal approach. Incorporation of all the factors, as well as processing of elements and outcomes, would help the organiza- tions to develop a better and fool-proof organizational strategy post-downsizing.
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Bulletin of the Transilvania University of Braşov Series V: Economic Sciences • Vol. 10 (59) No. 1 - 2017 HR strives in a challenging environment. Downsizing. Evidence from the International Public Organizations
area
Cristina DRUMEA 1 Abstract: The present paper presents new and unexpected movements on the international organizations labor market under the pressure of budget cuts. It focuses on the administration field of work, emphasizing on the staff resizing and the associated stress for the personnel under the effects of the automation and ultimately the effects of a new reality. A brief analysis of the staff downsizing processes and effects in large public organizations highlighting the difficulties and the stress, along with productivity changes, is performed. The research is empirical, but lead by factual observations and data on institutional strain prompted by change in large public organizations. It stays mainly onto the HR input as both promoter and dissuader of the process, while wider organizational implications are being conveyed as part of the equation. Key-words: downsizing, organizational change, public organizations 1. Introduction and literature review
The main definition we find while searching for the concept of downsizing is „intentional reduction in the size of a workforce at all staffing levels, to survive a downturn, improve efficiencies, or become a more attractive candidate for acquisition or merger” (Business Dictionary)
This is quite to be expected, we see the concept utilized on our current life, but we can only guess its impact while seeing it from the other side of the barricade, meaning as personnel about to be affected by it. What is further interesting is the carryover of the concept towards another one: rationalization. Seen not only as a need to save on resources when they become scarce, but also as a way to find a rationale on maintaining an unmodified level of service agreements with the stakeholders.
Is it rational to size down the staff under the pressure of budget reduction, automation, or externalization? It certainly is, but then again it depends a lot on the angle on which we judge it. 1 Transilvania University of Braşov, [email protected]
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We find in the literature the concept of „lean management”, which is a modern management myth. When companies are unwell economically or doing „too well” in the sense that they have gained „excess fat”, they are „put on a diet” (Hoßfeld, 2013), meaning that downsizing is the next step to be taken by the management. Is it working the same in the public sector? Obviously not, as stakeholders (member States) are less reactive than the clients or market in general, as it would be the case for a private company. However, when they do react, it is generally on a domino effect logic, which increases the pressure on management to perform in staff reduction while keeping the „business” running and creating at the same time an aura of legitimacy on the whole process (Bărbulescu, 2015).
On the same legitimacy aspect, authors stress on the fact that companies have an interest in presenting a specific image of their practices in staff reduction; an image that makes the practice appear legitimate, i.e. desirable, and proper or socially appropriate (Suchman, 1995). These aspects are of most significance to the public entities in particular, as public perception of management practice and of the way funds are spent set a trend on the future contributions of the member states (Anton, 2009). Moreover, the resistance to downsizing of the staff itself and the repercussions back to the funds originators in terms of poor management of funds create a supplementary pressure on the public organizations to: manage workforce reductions in respect of the costs savings while maintaining the public mandate intact.
Once they mature, international public organizations become subject of contrary types of pressure. On one hand, they turn out to be more complicated because of the increasing complexity of tasks and the increase in the number of stakeholders, including the number of member states represented directly and indirectly (Băcanu, 2014). On the other hand, the public wants them to become more efficient and to operate with lower costs. Both types of pressure push the executive management to adopt corporative management solutions. Even if the immediate results seem to validate these solutions, the mismatch between the organization's public specificity and the private nature of the means of addressing the use of financial resources creates sort of a fear of failing the (public) organization's scope.
The usage of financial efficiency methods in public organizations and their effect on employees remains a subject of study. The outcome created by the wage scale reduction and/or staff downsizing may have both positive and negative aspects on staff. In other words, the employee can improve their performance per se, under the fear of post cuts, but can also counterfeit it by increasing their individual efficiency in reducing the effort along the way. Fewer tasks performed or with less efficiency while the working time gets wasted in the effort of appearing indispensable to an organization that does not see the same value added from its distressed employee.
While difficult times may positively motivate employee to perform better and to voluntarily take an increased amount of pressure, the stress may act differently and although it seems unavoidable, it actually gives the employee a choice whether
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to go through it or not. This inevitability can create the “trap” awareness to which stressed employee submerges and the consequent vicious circle is one step closer to being created. Managers who choose to ignore these facts face not only the risk of decreased HR performance, but also the risk of spoiled organizational culture (Neacşu, 2015).
In order to alleviate the stress, some organizations apply a more sophisticated tool used to make the downsizing be seen as a joint effort of staff in creating new synergies by reducing the size of the organization; by doing that, management hopes to create the vectors of an accepted co-ordination. All agents adhere to an accounting convention that incorporate downsizing in how to plan and staff the number of jobs (Bernier, 2015). The efficiency of such new-aged management tools is very uncertain and remains to be seen, as reality strikes when human nature intervenes in survival mode.
2. Staff downsizing. Ethical dilemmas
Budgetary cuts, followed by staff downsizing and subsequent reduction of activities, services or mandates in the public sector have a peculiar way of happening, quite different of comparable events in the private sector. Why is that? It comes firstly from the extent of the general public attained by these changes. As the downsizing is becoming significant, same comes to the extent of services the remaining staff is able to insure; however, as practice has repeatedly shown, staff reduction in the public sector was never or almost never accompanied by a similar reduction of the service level agreement, which leads to the second concern: to what extent the staff downsizing can be implemented in public sector without affecting the very essence of the services provided. We take a first swift example from the Australian public sector, which has undergone significant changes involving managerialism, privatization, devolution and downsizing. This presented ethical challenges, especially where HR practitioners’ own professional values on one side and organizational requirements of practicality on the other side came into conflict. This delicate balance adds to the complexity of HR challenge and can result into unwelcome solutions where managing downsizing puts the specialists under pressure to comply with unethical directions or expectations; this conducts to the establishment of compromise choices, rather than ideal choices, when confronted with such situations (Shacklock, 2006).
Ethical dilemma: who is to leave first? Who is to leave at all? What are the criteria in cutting down the posts? First step is of course to release the organigram of the vacant positions that are carried over year after year in the public organizations in an unconfessed hope that they are going to continue to grow. This initial move is free of tangible stress for the personnel, although it is the blowing signal for further more concrete changes that will affect real people, not only positions. Second wave
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is still less painful, as the retiring personnel (or early retirees) is not being replaced and no further recruitment is performed on the vacancies, which reduces spending on salaries, but increases workload on the remaining staff. Real problematic work in downsizing begins with the actual cuts that terminate existing contracts and separates personnel from what they thought would be one of the safest workplaces.
The gap between safety expectation combined with (sometimes) deep specialization in (administrative) public sector specific tasks on one side and harsh reality that brings early terminations on the other side seems difficult to fill in, at least from the point of view of the employees. This brings us back to what (objective) criteria are to be used in order to correctly decide who is to be next on the list. Is the performance appraisal a good and reliable tool to base such decisions upon? Theory may approve, but practice definitely contradicts it for all the reasoning stated previously.
3. Budget cuts under stakeholders’ pressure in administration In a discussion about the evolution of public organizations, focusing on their size in terms of number of people they use as staff, one can not avoid the connection with a pair of concepts, naming good public-private good. The ideas associated with this pair of concepts are exposed in public economics theory, but are relatively less familiar even in the academic world.
The consequence is the emergence of a relatively “emotional” approach of the connection public good or service - public organization. Although the general public wants an improvement in the supply of public goods they also seek a decrease of the associated costs. Besides the tendency to transfer such public goods/services’ realisation to the private sector in the hope of achieving the costs reduction, the pressure towards even lower costs and consequently reduction of the public organizations’ size, is growing.
Public desire to reduce the cost and size of public organizations appears as a natural consequence of the continuous improvement of labor productivity. This is influenced both by the increase of staff’s individual performance and the reengineering processes, but mostly by rethinking processes through IT. It works in the same manner not only in the public sector, but in here the staff’s resitence and inertia are considerably higher, plus less easy to obturate due to the size of the organizations themselves.
Both policymakers and the public seek an operational costs’ limitation of all public organizations. As new products and new associated public organizations arise, keeping under control of the whole package requires a reduction in the size of existing organizations, even if the volume of products it generates is growing due to objective increase of demand. Mandates are also extended and broader, meaning that
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new and more sophisticated public services and/or good develop as the society at large evolves. That requires more skilles from the public employees, while still the public demand to lower the costs is maintained and affirmed.
The requirement to reduce the size of public organizations is further enhanced in the case of international organizations in which are represented the member states, in different proportions. Thus the previous requirement gets reflected and also shaped by the policy-makers associated with the predominant states. Even if some of the organizations seem less affected by political factors, such as the WHO (World Health Organization), WMO (World Meteorrological Organization) or, on another note organizations operating with significant funding from private sources, such as FIFA (Fédération Internationale de Football Association), we still see that the actual influence of the political decision-makers of governmnents is crucial.
Given this power relationship, governed by political will, the pressure exerted on public international organizations reflects both public expectations about the growth of labor productivity due to IT and the "opportunity" to influence its public behaviour at the the level of each participating country. A member state will try to use a public organizationto whose financing is participating in a manner that best respond to its expectations.
State will shape its financial contribution for that organization, possibly even its membership, according to the tally between the organization’s "performance" and its own agenda. A recent case exemplifying previous assertion is that of South Africa who withdrew from the International Tribunal or of Israel whic reduced its contribution to the UN because of decisions taken by these bodies that affected them one way or the other.
So overall pressure in favor of downsizing is usually effected by reducing financial contributions and creating preconditions that directly address staff reductions. These main areas are complemented by other actions aimed at the same organizational results. For example, it supports a relocation of segments of the organization's operating in a manner similar to the onesspecific to corporations. Clearly this relocation is made from a big city where the duty station may have been longly located, to a town in an emerging area, which can be claimed as to be better positioned for the organization's operations. 4. Stakeholders’ accountability Budget cuts in organizations is reflected both in downsizing, as well as in developing new salary packages. The latter consist of course in a reduction of the employees’ income. Some of the reductiona and for some of the employees are theoretically compensated by relocations to areas with lower costs of daily life.
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The individual result of all these movements associated to the staff downsizing is a more intensive labor and a productivity increase. Even if there is a additional technological support and updated IT used, maintaining quality standards involves extra effort.
As above mentioned dimensional trend was inspired by the private sector it is expected that other approaches of the same inspirational origin arise. One of these is the so-called outsourcing. This translates, in the case of public organizations in subcontracting activities carried out by its own staff previously. If the free market is associated with a large Western city where find the headquarters of international organizations are located, then, paradoxically, subcontracting may prove costly. Unfortunately the current reality offer a significant number of cases in which extra costs of subcontracting are pitched high. This sustains the general impression that international public organizations spend too much, thus the sensible solution should be the dowsizing.
On the other hand, opinions about individual facts and general impression of the public, with or without the intervention of politicians modeling, are a result of the evolution of public international organizations in the so-called period of globalization. Most factors impacting this evolution generate the increase of the organizations’ complexity. The generic term of growth means that operating parameters get more difficult to manage. This phenomenon accentuates the bureaucracy in organizations - in the usual negative sense – with the known consequences.
The first aspect associated with the of the increase of the representativity of international organizations in question is to increase the number of States which are involved in their work. In some way this means that decision and control mechanisms become more complicated. Even if the decision is linked to a differentiation that reflects the contribution of each state, the associated issues related to a consensual behavior of decision-makers are kept. Therefore operating mechanisms become even more bureaucratic.
Consequently, the need to clarify the modus operandi of the organizations calls for creating a comprehensive and extended set of procedures. And these procedures, as well as those associated with the high-end decision-making process lead to an emphasis of the bureaucracy with all its negative consequences. As time went by, it was outlined that the negative effects at the level of these public international organizations are similar to those in mining and large series production associated with Fordism concepts. Essentially, at the pyramid’s organizational base it is expected that a real decrease in labor productivity arises, along with a decrease of the employee’s responsibility overall.
Starting from this hypoteshis in connection to the individual activity/practice, for which stand the private industrial organizations as well as the international organizations current examples, the actual concern for increased productivity and accountability becomes the main reason for budget cuts. Claiming this worry is all
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the more intense as it blurres the care to promote political interests of the Member States of international organizations.
If the interest in establishing procedures appears to become a permanent and important task, the ranking of the work determinants changes in favor of the quantitative aspects. In the hope of achieving a mission driven behavior, some interest to operate on the basis of objectives and quantitative models appears automatically, while performance standards for the organizational divisions and individuals becomes the necessary metrics in deciding on whose head futures cuts will fall. 5. Conclusions
In such context, the concern for promoting political interests is reflected in shaping state budget allocations for the international organizations. This so-called modelling/shaping is, in fact, often and increasingly often, a reduction in budgetary allocations, but what makes it difficult to be put in place is the fact that it is accompanied by requirements to improve work processes, their effectiveness and overall efficiency. If the first course of action seems vague, the second leads inevitably to recalibration of the organization in terms of staff size, along with operating costs decrease thereof. In absolute terms this may result in a reduction of the staff number, as well as a reduction of the pay level.
In fact, it seems that the reductions’ spectrum determines a positive effect on the organization. On the one hand there is an increase of the staff’s interest to perform. We should not avoid observing that this interest could actually be replaced by a concern to seek and receive a positive assessment from the supervisors and/or higher hierarchy, particularly when individual performance metric system is marked by subjectivity. Consequently, what is to be perceived is not necessarily a real up rise of productivity, but definitely a quest for recognition and appreciation from the significant hierarchical factors.
On the other hand, a reduction in contributions and subsequent apportionments announced by Member States can generate an adaptation of the organization concerned. This adjustment is materialized in finding alternative resources, which is a healthy approach. The effect of increasing the influence of different "sponsors", meaning donors, NGOs, lobby groups etc. remains to be evaluated in the future. At the present time the international organization facing downsizing due to budgetary cuts and subsequent automation processes extends its known operational model, seeking predictable results based on milestones of the past.
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6. References Anton, C.E., 2009. Recruitment of the Future Professionals in the Financial-
Accounting Field. Marketing Studies in the Context of International Accounting Convergence”- INTED 2009 - International Technology, Education and Development Conference. Valencia, Spain.
Bărbulescu, O., 2015. The profile of the lease services consumer in Brașov County. Advances in the area of marketing and business communication. Editura ISEUN.
Băcanu, B., 2014. Anti-Strategic Management. Teorie şi studii de caz. Iași: Polirom. Bernier, S., 2015. Rôles des outils de gestion dans les réductions d'effectifs.
Comptabilité, Contrôle et Audit des invisibles, de l'informel et de l'imprévisible, 36eme Congres de l'AFC, Toulouse, France. Available at: <https://hal.archives-ouvertes.fr/hal-01188238>
Drumea, C., 2016. Synopsis of the HR stress, pressure and subsequent underperformance in Public Organizations. Bulletin of the Transilvania University of Brașov, Vol. 9 (58), Series V, No. 2, pp. 185-192.
Genda, Y., Kuroda, S. and Ohta, S., 2015. Does downsizing take a toll on retained staff? An analysis of increased working hours in the early 2000s in Japan. Journal of the Japanese and International Economies, Vol. 36, June 2015, pp. 1–24.
Hoßfeld, H., 2013. Corporate Dieting. Persuasive Use of Metaphors in Downsizing. Management Revue – Socio-Economic Studies, Vol. 24, Issue 1, pp. 53-70.
Neacşu, N. A., 2015. Implementation of ISO 22000 - a tool to increase business efficiency and customer satisfaction. A Case Study: SC Prodlacta Brasov. Bulletin of the Transilvania University of Braşov, Vol. 8 (57), Series V, No. 2, pp. 105-112.
Shacklock, A.H., 2006. Courage, compromise or capitulation: human resource practioners under ethical duress. International Journal of Human Resources Development and Management (IJHRDM), Vol. 6, No. 2/3/4.
Suchman, M. C., 1995. Managing Legitimacy: Strategic and Institutional Approaches, Academy of Management Journal, Vol. 20, No. 3, pp. 571 - 610.
*** http://www.businessdictionary.com/definition/downsizing.html
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Development of institutional downsizing theory: evidence from the MNC downsizing strategy and HRM practices in Taiwan
Philip C.F. Tsai a
and Yu-Fang Yen b∗
a International Business Administration Department/Graduate School, Wenzao Ursuline College
of Languages, Kaohsiung, Taiwan; b Department of Business Administration, National Quemoy
University, Kinmen, Taiwan
Although downsizing is one of the most essential strategies of a firm, its effectiveness has been controversial. Institutional downsizing theory asserts that institutional factors influence the motivation of firms to adopt organisational downsizing as a common strategy. Institutional factors not only lead the internal motivation for downsizing, but also influence external downsizing actions. To develop institutional downsizing theory further, this study empirically examines whether the theory applies to the responsible downsizing strategy of multinational corporations (MNCs) and human resource management (HRM) practices to enhance intellectual capital. This study investigated 224 firms in Taiwan, including local firms and MNC subsidiaries from different countries, as the sample to examine this research question. The results revealed a high degree of isomorphism in actual downsizing strategy and HRM practices among these firms. However, universal value is a vital institutional force not discussed in the literature. The findings of this study support and extend institutional downsizing theory and imply the downsizing strategies of MNCs and HRM practices. However, the research background of this study is only in Taiwan; this may limit the generalisation capability of the findings to other contexts and cultures.
Keywords: downsizing; institutional downsizing theory; MNCs; HRM practices
Introduction
In rapidly changing environments, firms have consistently introduced numerous types of
strategies to survive, thrive, and gain competitive advantage. Organisational downsizing
has been a popular strategy since the 1980s (Cascio, 2002; Datta, Guthrie, Basuil, &
Pandey, 2010; Fisher & White, 2000; Love & Kraatz, 2009; Tsai & Yen, 2008). Consider-
able research has observed the outcomes of organisational downsizing that are problematic
and do not benefit firm performance, but possibly harm employees and their families
(Datta et al., 2010; Guthrie & Datta, 2008; Mckee-Ryan & Kinicki, 2002). Although
organisational downsizing has become popular practice in global business environments,
it remains a controversial and frequently disputed subject. Numerous researchers have
attempted to explain the economic motivations for organisational downsizing. However,
based on institutional theory, McKinley, Sanchez, and Schick (1995) listed constraining,
cloning, and learning as the three social forces behind applying an organisational down-
sizing strategy. In addition, several studies have claimed that institutional factors are
part of downsizing motivation (Lamertz & Baum, 1998; Budros, 1999). McKinley,
Zhao, and Rust (2000) suggested that through the collective and concrete process of
socio-cognition, managers deem organisational downsizing as a legitimate, effective,
# 2013 Taylor & Francis
∗Corresponding author. Email: [email protected]
Total Quality Management, 2015
Vol. 26, No. 3, 248 – 262, http://dx.doi.org/10.1080/14783363.2013.791118
and unavoidable strategy while neglecting their enterprise traits, managerial contingency,
and resources. This institutional theory of downsizing provides a more complete expla-
nation of downsizing motivation. Tsai, Wu, Wang, & Huang (2006) found that insti-
tutional factors not only influence internal motivation for downsizing but also lead
firms to adopt similar and external actions in downsizing. However, because of the con-
straints of their smaller sample sizes, external downsizing actions are considered unsyste-
matic actions that limit the generalisation capability of institutional downsizing theory.
This work suggests adopting higher level strategies and comprehensive systematic
human resource management (HRM) practices to make institutional downsizing theory
more explanatory and predictable.
To mitigate the negative effect of downsizing, interest in the employee-centred com-
prehensive organisational downsizing strategy has increased rapidly in the past decade
(Appelbaum, Everard, & Hung, 1998; Cascio, 2002; Freeman, 1999). After reviewing
various studies on employee-centred organisational strategy, we determined that this
type of downsizing strategy, referred to as the ‘responsible downsizing strategy, is a com-
prehensive and systematic downsizing strategy that can enhance post-downsizing perform-
ance and reduce harm to employees.’ Tsai and Shih (in press) provided empirical evidence
that verifies our finding. Therefore, this study proposes applying this finding to examine the
influence of institutional factors on this type of systematic downsizing strategy.
The responsible downsizing strategy specifically emphasises reevaluating and redesign-
ing post-downsizing HRM practices to enhance organisational capabilities (Appelbaum et al.,
1998; Cascio, 2002; Freeman, 1999). From the resource-based view (Barney, 1991), a firm’s
competitive organisational capability is based on its intellectual capital. Therefore, firms that
adopt post-downsizing HRM practices for enhancing intellectual capital can strengthen
organisational capabilities and ensure successful downsizing. Therefore, this study suggests
using these crucial HRM practices to test evaluate the effects of institutional factors.
Furthermore, institutional factors influence the global popularity of organisational
downsizing and cause firms to adopt isomorphic downsizing actions (McKinley et al.,
2000; Tsai et al., 2006). This study investigated whether institutional forces cause firms
with various national and cultural backgrounds to adopt similar responsible downsizing
strategies and post-downsizing HRM practices to enhance intellectual capital. The litera-
ture focusing on transnational comparisons of HRM practices (Bjorkman, Fey, & Park,
2007), based on institutionalism, is minimal. In particular, research emphasising the
responsible downsizing strategy and post-downsizing HRM practices for enhancing intel-
lectual capital is lacking.
To develop institutional downsizing theory further, this study adopted a quantitative
research method for examining a large-scale sample. Taiwanese and MNC firms with
various home country cultures (e.g. USA, Japanese, and European Union (EU) multina-
tional corporations (MNCs)) were selected as the samples to verify whether firms adopt
isomorphism in responsible downsizing strategy and post-downsizing HRM practices
for enhancing intellectual capital. Following the quantitative research, three focus group
interviews were conducted to explain the statistical results.
Literature review
Institutional theory of downsizing
Downsizing has been one of the most critical strategies for firms facing managerial chal-
lenges. Particularly in an era of global financial depression, many firms have adopted
organisational downsizing strategies to survive (Wilkinson, 2005). The performance and
Total Quality Management 249
effectiveness of downsizing have been controversial, generally harmed employees and
their families, and even caused social problems (Mckinley et al., 2000; Mckee-Ryan &
Kinicki, 2002; Tsai & Yen, 2008). The reasons for downsizing popularity have been inves-
tigated, including its negative effects. McKinley et al. (1995, 2000) have proposed using
downsizing theory to explain these phenomena.
The influence of institutional motivations on organisational downsizing
Previous literature has indicated multiple driving motivations behind organisational down-
sizing. For decades, considerable research has identified organisational decline as the main
factor (economic factor) for organisational downsizing. Because organisational downsiz-
ing also entails negative effects, the question remains what the rationale for downsizing is.
According to the explanations of institutional downsizing theory proposed by McKinley
et al. (1995, 2000), social institutional forces motivate firms to execute organisational
downsizing strategy. The forces include constraining, cloning, and learning. Managers
consider organisational downsizing as an unavoidable action with legitimacy and
ethical acceptability via the psychological process of socio-cognition.
The influence of institutionalism on external behaviours and practices in organisational downsizing
Using qualitative research on 18 firms in Taiwan, Tsai et al. (2006) verified the contention
that institutional factors induce internal motivations for organisational downsizing. They
further proposed that downsizing motivation is a combination of economic, institutional,
and socio-cognition factors. Most firms forming downsizing motivation prioritise benefits;
however, to maintain a certain social image and to gain expected advantage, external
downsizing behaviours generally follow recognised social norms. Findings from Tsai
et al. (2006) demonstrate that most firms have adopted a mild and gradual strategy to
execute downsizing, which is linked with reengineering and overall system change. The
chosen targets for layoff were primarily performance based and all the firms offered legit-
imate severance conditions and job-seeking consultations. These institutional factors are
meaningful in balancing the harm to downsized employees.
One drawback of the findings of Tsai et al. (2006) is that they were derived from 18
firms in Taiwan. However, generalising a widely acceptable theory needs the support of
empirical evidence from quantitative research with a larger sample size. Those downsizing
practices were also unsystematic actions lacking supportive values; therefore, we suggest
adopting higher level strategies and systematic HRM practices to verify the development
of institutional downsizing theory as more explanatory and predictable.
Responsible downsizing strategy
Numerous studies have focused on types of downsizing strategy; namely the hierarchy of
workforce reduction strategies (Greenhalgh, Lawrence, & Sutton, 1988), three strategies
for organisational change (Cameron, Freeman, & Mishra, 1993), the social institutional
downsizing strategy (McKinley et al., 1995), the alternative strategy (McCune, Beaty,
& Montagno, 1988), and three resource reduction approaches (Dewitt, 1998). Although
there have been many arguments and discussions regarding downsizing strategy, relevant
literature offers contradictory findings about the influence of organisational downsizing
(Cameron, 1994; Cascio, 2002; Rigby, 2002; Tsai & Yen, 2008).
250 P.C.F. Tsai and Y.-F. Yen
Many researchers have proposed long-term and comprehensive employee-centred
downsizing strategies, such as the prescription for successful organisational downsizing
(Cameron, 1994), downsizing driving redesign, the redesign driving downsizing strategy
(Freeman, 1999), and responsible strategies for restructuring (Appelbaum et al., 1998;
Cascio, 2002). Cascio (2002) investigated 6418 firms among the top firms listed on the
S&P 500 Index from 1982 to 2000. Because the strategies have some common traits,
this study constructed a strategy that encompasses these traits, referred to as the respon-
sible organisational downsizing strategy. The four traits are (1) management deeming
employees as long-term assets and a source of innovativeness when designing an organ-
isational downsizing strategy; (2) firms strategically consider long-term payoff prior to
downsizing to choose an appropriate change strategy; (3) employees participate in
opinion-sharing, and the lay-off procedure is justifiable; and (4) firms employing suitable
employee caring practices that correspond to the downsizing strategy, such as a reasonable
amount of compensation, job-leaving consultations, job-seeking services, or career-
change training. Tsai and Shih (in press) empirically proved that the strategy can
improve firm performance when firms use a quantitative method. Therefore, this research
considered the responsible organisational downsizing strategy to be a more strategic and
systematic strategy for examining institutional downsizing theory and for contributing
substantially to its development.
HRM practices for enhancing intellectual capital
An employee-centred organisational downsizing strategy emphasises reexamining and
redesigning HRM practices (Appelbaum et al., 1998; Cameron, 1994; Cascio, 2002;
Freeman, 1999) and addresses organisational downsizing concerns with corporate long-
term profits, and whether future operations after downsizing meet customer requirements
and create customer value more effectively. Currently, firms must provide high-quality
and inexpensive new products and services to create competitive advantage (Chang &
Huang, 2010; Shih, Lin & Lin, 2011). From the perspective of resource-based theory
(Barney, 1991), organisational innovativeness is a key competence for firms to create valu-
able resources. Hamel (2000), and Kaplan and Norton (2004) have denoted four categories
of such resources as intangible assets or intellectual capital: (1) human capital, referring to
valuable employees with strategically key job positions regarding specific knowledge,
skills, and talent (Kaplan & Norton, 2004); (2) structural capital, referring to a firm’s
unique and innovative abilities to combine internal and external resources effectively,
and to modify or create new markets (Teece, Pisano, & Sheun, 1997); (3) social capital,
referring to abilities to acquire profits in existing social networks or social structures
(Snell, Youndt, & Wright, 1996); and (4) organisational capital, referring to a firm’s abil-
ities to incorporate distinct cultures, leadership, employees, strategic objectives, and
employee knowledge sharing (Kaplan & Norton, 2004). Youndt, Subramaniam, and
Snell (2004) suggested that firms concentrate on generating valuable ideas and design
business models based on their culture and daily routines.
Creating and enhancing the above intellectual capital depend on employees. Firms
should therefore possess a set of HRM practices to create and strengthen intellectual
capital post downsizing and to ensure the success of an organisational downsizing strategy.
The set of HRM practices is comprehensively systematic and is relevant in the era of
knowledge economy; therefore, we propose using this set to verify institutional downsiz-
ing theory, which might contribute greatly to its development.
Total Quality Management 251
Individual strategies, practices, and international context
According to basic logic and managerial mentality, firms should consider their external
management environments, internal/external resources, and overall management strategy
to formulate various downsizing strategies to improve corporate performance (Cascio &
Wynn, 2004; Datta et al., 2010). This is particularly true for MNCs with various host
country cultural backgrounds. For example, the USA and European countries are generally
capitalistic; however, European societies are more socialistic. Regarding general manage-
ment practices, Americans are more outcome-oriented, whereas Europeans are more pro-
cedure-oriented. European firms value employee behaviours, whereas US firms generally
value performance; and social institutional constraints are more powerful in European and
Asian firms than in US firms (Hodgetts, Luthans, & Doh, 2006). In some societies strongly
influenced by Confucius, firms generally are benevolent and righteousness oriented
(Graham & Lam, 2003; Tsai et al., 2006). The national cultural framework of Hofstede
(1980) indicates that Europeans and Americans are more individualistic and Asians are
more collectivistic; Asians maintain greater power distance from others than Europeans
and Americans do; and Asians tend to avoid uncertainty more than Europeans and Amer-
icans do. Research in the cross-cultural management field (Swierczek & Hirsch, 1994) has
shown that Asian firms possess distinct basic values, management styles, management
types, and action-orientations more than USA and European countries do. An increasing
concern is that both the responsible downsizing strategy and the intellectual capital
concept were developed in the USA. Relevant literature on this topic is insufficient for
determining whether these concepts meet the needs of other cultures. Therefore, we
propose the following two hypotheses:
H1: Firms exhibiting different national cultural backgrounds will adopt a differentiated responsible downsizing strategy.
H2: Firms exhibiting different national cultural backgrounds will adopt differentiated HRM practices for enhancing intellectual capital.
To examine these hypotheses empirically, we investigated 224 firms in Taiwan,
including local firms and MNCs from various host country cultural backgrounds as the
sample to test the further development of institutional downsizing theory.
Methodology
Sample and data
The samples were collected from three sources in Taiwan: the first source was from a list
of downsizing investigations from the Taiwan Labor Department; the second was one of a
famous national management consultations held in Taiwan, and the third was a list of 370
top foreign corporations in Taiwan, indexed by the China Credit Information Service, Ltd.
in 2009. The research targets were limited to firms’ strategic business units that had experi-
enced downsizing. We requested that the respondents of each firm be HRM executives or
department managers.
To facilitate understanding of the questionnaire, we sent questionnaires to MNC firms
in two languages (Chinese and English) and sent the Chinese questionnaires to local firms
via mail or e-mail. We made contact by telephone or e-mail if we had not received replies
after three weeks.
The data collection yielded 224 effective replies from 236 firms. The sample encom-
passed various business categories, including 98 local firms (43.8%), 35 US MNCs
(15.6%), 48 Japanese MNCs (21.5%), 35 EU MNCs (15.6%), and eight other Asian
252 P.C.F. Tsai and Y.-F. Yen
MNCs (3.6%). Among them, 75% were manufacturing firms, 22.3% were service-provid-
ing firms, 55.3% had annual sales amounting to more than US$166 million; 19.6% had
annual sales amounting between US$166 million and US$30 million; 19.2% had total
employees numbering of over 1000; and 51.3% had total employees numbering
between 100 and 1000. From the aspect of span of downsizing, most of the firms
(39.3%) laid off 5 – 15% of their employees, and 16.9% of the total firms laid off 16 –
50% of their employees.
Reliability and validity tests on measuring tools
Responsible downsizing strategy
The tool for measuring the responsible downsizing strategy was developed according to 19
principles of the responsible restructuring strategy proposed by Cascio (2002), 30 success-
ful downsizing prescriptions by Cameron (1994), and variables addressed in a generalised
organisational downsizing strategy proposed by Freeman (1999). There were originally 18
items. After three factor analyses, items 4, 5, and 11 were deleted and the other items were
merged into four dimensions: (1) the mindset of treating employees as long-term assets;
(2) appropriate strategies for change; (3) employee anticipation and justifiable procedures
in downsizing; and (4) employee caring practices during downsizing. Therefore, we
obtained construct validity of the measuring tools and used Cronbach’s a to examine
the reliability of the four dimensions. The mindset of treating employees as long-term
assets is .762; an appropriate change strategy is .850; employee anticipation and justifiable
procedures in downsizing is .728; and employee caring practices during downsizing is
.757. The overall values of reliability are greater than .7 and the Pearson Correlation Coef-
ficients of the four dimensions reached significant level (,.01).
Post-downsizing HRM practices enhancing intellectual capital
The tool for measuring HRM practices to enhance intellectual capital was developed based
on focused group interviews with top management teams (TMTs) in practical fields. We
invited 16 top executives from various businesses, such as information technology, petro-
chemical, steeling, construction, retailing, chemical material, medical, education, and
logistics and divided them into two focused groups. The focus group members included
presidents, TMT members such as VPs, directors, and senior managers, and heads of func-
tional departments. These interviewees not only possessed years of top management prac-
tical experience but also participated in strategic, HRM, and intellectual capital lectures at
the EMBA Program. Before discussion, we posed the question, ‘In the post-downsizing
period, what HRM practices will your firms adopt to enhance intellectual capital to
build competitive advantage?’ We also reminded group members to pay attention to influ-
ential factors from their specific businesses. The group discussions began by executives
illustrating HRM practices in their firms to enhance intellectual capital, followed by inter-
active discussions. During the discussions, researchers observed and reminded them to
focus on the main topic. After every group reached a concrete primary conclusion, we
mixed the two groups to facilitate discussion and to form a consensus.
After referring to the focused group conclusions, the literature, and existing measuring
scales, such as the intellectual capital scale and the organisational capability audit, we inte-
grated the 18 items in the survey. After three factor analyses, the 18 items were categorised
into four dimensions, namely human capital, procedure capital, internal social capital, and
external social capital. We acquired the construct validities of these four dimensions by
Total Quality Management 253
performing exploratory factor analysis and used Cronbach’s a to determine the measure-
ment reliability. Consequently, human capital is .884, procedure capital is .899, internal
social capital is .873, and external social capital is .876. The overall reliability is above
.7, and the Pearson correlation coefficient of the four dimensions reached a significant
level (,.01).
Data analysis
We used a one-way analysis of variance (ANOVA) to verify potential differences when
firms with varying home country cultures execute an organisational downsizing strategy
(including four dimensions) and apply HRM practices for enhancing intellectual capital
in the post-downsizing period. We also used the Scheffe comparison to conduct post
hoc multiple comparisons to determine whether their differences rank according to size.
Focused group discussions
To apply the statistical results approach to reality, this work conducted three focus group
interviews to verify the statistical results, including HR managers, TMT executives, and
labour union leaders. Each focus group comprised six to eight members. Before the
focus group interviews, quantised summaries were provided to each member. After the
discussions, the conclusions were summarised and member consensus was reached. We
then used the triangulation comparison method (Figure 1) to compare conclusive opinions
from the three focus groups.
Analysis and discussion
Results from quantitative analysis
Comparisons of actions in the responsible downsizing strategy
In addition to combining the detailed actions of responsible organisational downsizing into
four dimensions, this work also analysed parts that cannot be categorised and may have
special meaning. Table 1 shows that the overall degree of the responsible downsizing strat-
egy of MNCs is high (the average is between 4.78 and 4.92) with a mean of 4.915. Among
them, Japanese MNCs have the highest number (5.008). However, the average scores for
the four dimensions are as follows: ‘the mindset of treating employees as long-term assets’
is 5.678, significantly higher than other dimensions (4.992, 4.630, and 5.208). The dimen-
sion ‘employee anticipation and justifiable procedure in layoff’ scored the lowest. In
national background, US MNCs scored higher in the dimension ‘employee anticipation
and justifiable procedure in layoff,’ whereas European MNCs scored lower.
Figure 1. Triangulation analysis on focus groups.
254 P.C.F. Tsai and Y.-F. Yen
Table 1. The comparisons of the responsible organisational downsizing strategies.
Overall responsible downsizing strategy
Treating employees as long-term assets
Changing strategy
Employee participation and justifiable procedure
Employee caring practices
0. Local firms
Average 4.928 a
5.697 a
5.040 b
4.670 b
5.181 c
Samples 98 98 98 98 98 Standard deviation
0.655 0.982 0.946 1.115 1.134
1. American MNCs
Average 4.946 b
5.733 d
5.071 d
4.457 a
5.321 a
Samples 35 35 35 35 35 Standard deviation
0.681 1.044 0.950 1.1764 1.165
2. Japanese MNCs
Average 5.008 d
5.729 b
4.989 a
4.895 d
5.276 b
Samples 48 48 48 48 48 Standard deviation
0.7041 1.057 1.069 1.175 1.048
3. EU MNCs Average 4.780 c
5.457 c
4.900 c
4.328 c
5.257 a
Samples 35 35 35 35 35 Standard deviation
0.746 1.078 1.297 1.246 1.049
4. Other Asian MNCs
Average 4.652 5.875 4.468 4.625 4.437 Samples 8 8 8 8 8 Standard deviation
0.921 1.207 1.739 1.356 1.279
Total Average 4.915 5.678 4.992 4.630 5.208 Samples 224 224 224 224 224 Standard deviation
0.693 1.027 1.064 1.171 1.114
Notes: EU MNCs include: French, British, German, Dutch, and Swiss. Sample from Asian MNCs into account due to its small sample size (sample size: 8). a the 3rd highest rank;
b the 2nd highest rank;
c the 4th highest rank;
d the highest rank.
T o
ta l
Q u
a lity
M a
n a
g e m
e n
t 2
5 5
This research attempted to determine whether the differentiations of varying downsiz-
ing actions of MNCs reach a significant level. The analysis of ANOVA shows the results
have not reached a significant level. The F (P) values for responsible downsizing strategy,
long-term perspectives, changing strategies, participation and justifiable procedures, and
employee caring practices are .537(. 708), .645(. 631), 1.428 (. 226), 1.124 (. 346), and
.654 (. 625). The above result is highly isomorphic; the varying MNCs’ responsible down-
sizing actions differentiate, however, they have not reached a significant level, therefore
H1 was rejected, which also indicates their actions in organisational downsizing strategy
are highly similar.
Comparison of the action not included in the responsible downsizing strategy
Three downsizing actions are not included in the four dimensions: ‘we lay off employees
and sell unprofitable assets (such as selling whole business units or factories)’, ‘we take
quick action to lay off employees’, ‘we designate an organizational downsizing project
to plan and execute downsizing affairs.’ The comparisons are shown in Table 2. The
average scores of these three actions are lower than the previous four dimensions,
meaning that the sampled MNCs generally did not consistently agree on these actions
as responsible downsizing actions. Among them, ‘we lay off employees and sell unprofi-
table assets’ scored 3.83. However, we designated an organisational downsizing project
Table 2. Comparison of the action not included in the responsible downsizing strategy.
We lay off employees and meanwhile sell unprofitable assets
We take quick actions to lay off
employees
We designate an downsizing project team
to plan and execute downsizing affairs
0. Local firms
Average 4.06 a
4.09 b
3.89 c
Samples 98 98 98 Standard deviation
1.673 1.663 1.435
1. American MNCs
Average 3.89 d
4.40 d
4.14 d
Samples 35 35 35 Standard deviation
1.827 1.786 1.648
2. Japanese MNCs
Average 3.87 c
4.73 a
3.71 b
samples 48 48 48 Standard deviation
1.794 1.647 1.458
3. EU MNCs Average 3.03 b
4.23 c
4.49 a
Samples 35 35 35 Standard deviation
1.200 1.516 1.579
4. Other Asian MNCs
Average 3.88 3.75 4.38 samples 8 8 8 Standard deviation
1.126 0.886 1.847
Total Average 3.83 4.29 4.00 Samples 224 224 224 Standard deviation
1.670 1.645 1.521
a the highest rank;
b the 4th highest rank;
c the 3rd highest rank;
d the 2nd highest rank.
256 P.C.F. Tsai and Y.-F. Yen
team to plan and execute downsizing affairs in European MNCs scored the highest.
Clearly, MNCs from various national backgrounds differentiate on these three items.
The ANOVA analysis indicates that the item, ‘we lay off employees and sell unprofi-
table assets’ reached a significant level with F (P) value of 2.574 (. 039); the items, ‘we
take quick actions to lay off employees’; ‘we designate an organizational downsizing
project to plan and execute downsizing affairs’ scored F (P) values of 1.490 (. 206) and
1.686 (. 654). The analytical results of the Scheffe multiple comparison on ‘we lay off
employees and sell unprofitable assets’ scored a p-value of .041, indicating that local
firms are inclined to take this action comparatively with European MNCs.
Comparison of post-downsizing HRM practices enhancing intellectual capital
Table 3 shows that varying MNCs generally adopt HRM practices to enhance intellectual
capital (with an average between 5.03 and 5.29); the average score for all investigated
firms is 5.224; among them, the US MNCs scored the highest with 5.444 and also
scored higher in the other four dimensions, compared with other firms. Local firms and
US MNCs also scored higher than Japanese and European MNCs. This finding differs
from the traditional impression that local firms and Japanese firms should be similar.
Table 3. Comparisons on HRM practices enhancing intellectual capital in the post-downsizing period.
Overall intellectual
capital HRM practices
Human capital
Procedure capital
Internal social capital
External social capital
0 Local firms Average 5.290 a
5.320 a
5.279 a
5.326 a
5.229 a
Samples 98 98 98 98 98 Standard
deviation 0.9229 0.872 1.036 1.059 1.018
1 American MNCs Average 5.444 b
5.388 b
5.382 b
5.407 b
5.628 b
Samples 35 35 35 35 35 Standard
deviation 0.940 1.056 1.029 1.055 0.868
2 Japanese MNCs Average 5.218 c
5.195 c
5.237 c
5.213 c
5.229 c
Samples 48 48 48 48 48 Standard
deviation 0.904 0.998 0.939 0.979 0.998
3 EU MNCs Average 5.030 d
5.040 d
4.988 d
5.050 d
5.050 d
Samples 35 35 35 35 35 Standard
deviation 0.977 1.026 1.019 1.012 1.392
4 Other Asian MNCs Average 4.333 4.125 4.100 3.968 5.250 Samples 8 8 8 8 8 Standard
deviation 1.518 2.067 1.585 1.764 0.896
Total Average 5.224 5.217 5.199 5.223 5.264 Samples 224 224 224 224 224 Standard
deviation 0.969 1.031 1.054 1.089 1.061
a the 2nd highest rank;
b the highest rank;
c the 3rd highest rank;
d the 4th highest rank.
Total Quality Management 257
The analysis of ANOVA shows that the items ‘overall intellectual capital HRM prac-
tices’, ‘human capital’, ‘procedure capital’, and ‘internal social capital’, in local firms are
significantly higher than other Asian MNCs. However, because of the small sample size of
Asian MNCs (eight firms only), the statistical meaning is weak. The differentiation of
other MNCs has not reached a significant level. Therefore, H2 was also rejected, indicating
that their HRM practices for enhancing intellectual capital are highly similar.
These quantitative statistics verify that MNCs adopt highly isomorphic actions in their
organisational downsizing strategies and HRM practices for enhancing intellectual capital.
This result is consistent with institutional theory. Based on neo-institutional theory
(DiMaggio & Powell, 1983), institutionalism allows members to choose good manage-
ment and organisational structural norms for reducing uncertainties and acquiring behav-
ioural legitimacy (McKinley et al., 2000). Business behaviours that comply with social
expectations increase legitimacy, resources, and survival capability, and eventually help
organisations survive and succeed (Carroll & Hannan, 1989; DiMaggio & Powell,
1983; Oliver, 1991, 1997; Scott, 1987). Once managers regard organisational downsizing
as a social convention that they should obey, they will accept isomorphic behaviours as
legitimate (Oliver, 1997). Therefore, this result contributes to further development of insti-
tutional downsizing theory.
Explanation from focused group interview
This study used a qualitative method to explain the quantitative results, and summarised
the findings based on the results from interviewing three focus groups. MNCs employ
Table 4. Reasons why varying MNCs take similar actions during downsizing and post-downsizing time.
Labour union leaders
HR managers
TMT executives
1. The samples are taken from one single country (Taiwan). The MNCs managerial actions usually have to comply with local related laws, governmental requirements, social expectations and values, common practices, and labour relationships, etc. Therefore, the practices might not similar to their home countries
V V V
2. The widespread of massive media and internets make managerial mentality and practices reach certain consistency via learning and imitation
V V V
3. Obeying laws, treating employees well, and managing firms in a responsible way have been a universal value in developed countries. Therefore, makes no big differences among these practices
V V V
4. The popularity of management education (e.g. MBA and EMBA) has made managers to access to similar managerial strategies and recognition on intellectual capital
V V
5. The managers who filled out the questionnaires might concern about social image and deliberately gave lower grades to these two variables
V
6. These MNCs are all firm come from capitalism countries
V
258 P.C.F. Tsai and Y.-F. Yen
similar actions to the responsible downsizing strategy and HRM practices to enhance intel-
lectual capital in the post-downsizing period.
Table 4 illustrates the common consensus from the focused groups, indicating that
focused groups reached agreements on items 1 – 3, but did not reach agreements on
items 4 – 6. Item 1 indicates that MNCs should adjust themselves according to local
laws, social cultures, and labour relationships. Therefore, they might not engage in the
same actions as home country firms do. The rationale for this is that the survival of a
firm depends on complying with the legitimate action of external environments. This
finding also corresponds to propositions of HRM practices in MNCs. Item 2 indicates
that ‘firms tend to take consistent actions via learning or imitating’, matching organis-
ational downsizing theory proposed by McKinley et al. (1995), which emphasises that
organisational downsizing behaviours stem from learning. Item 3 shows that ‘law-
abiding, treating employees well, and just management are universal values in developed
countries, promoting the influence of institutional factors on firms to a universal level.’
This finding is meaningful for developing institutional theory, particularly in the field of
international business management and management practices.
With regard to item 4, ‘the prevalence of management education facilitates managers
to have similar recognition on management,’ reached a consensus. This finding extends the
proposition raised by McKinley et al. (2000) that firms should use social recognition to
adopt the responsible downsizing strategy and HRM practices to enhance intellectual
capital. The reason labour union leaders cannot reach a consensus is that they do not
have management education opportunities. Item 5 indicates that compared with labour
union leaders, managers who completed the questionnaires rated these two variables
higher because they care more about social image. Although this item might create a
flaw in common method bias, it shows the effect of social expectation on managers
who completed the questionnaires.
Conclusions and suggestions
The findings from this research reveal that institutional factors influence MNCs with
varying national backgrounds that conduct the responsible downsizing strategies and
HRM practices that enhance intellectual capital in the post-downsizing period, to eventually
adopt isomorphic actions. This finding is consistent with the institutional downsizing theory
proposed by McKinley et al. (1995, 2000) and the empirical research result from Tsai et al.
(2006). The finding also contributes to generating a further development of institutional
downsizing theory. The results of this research indicate that institutional factors include
laws in local countries, social recognition, and ethical norms upgraded to a cross-national
level. In particular, this research found that treating employees well entails demonstrating
universal values with a soft coercive power that mitigates the harm caused from downsizing
and helps firms redevelop employee capabilities in the post-downsizing period. This univer-
sal value spreads, due to globalisation and the prevalent interactions of management and
practices (learning and imitation). Considering factors when applying the neo-institutional
theory on international business is also necessary (organisational downsizing), namely the
dependent relationships among countries and the recognition of supervisor responsibilities.
Implications of research
The field of international business has not widely discussed the organisational downsizing
institutional theory proposed by McKinley; however, the responsible downsizing strategy
Total Quality Management 259
and HRM practices enhancing intellectual capital in the post-downsizing period should
draw more attention. Universal values should be the critical force in institutionalism, par-
ticularly when applied to international business. Responding to the proposition by
Kostova, Roth, and Dacin (2008), the institutional theory research on multinational
business practices should include both internal and external institutional factors, as well
as other organisational theories, such as the dependence relationships among countries
(resource dependence theory and power theory), and managers’ recognition of their
agency responsibilities (agent theory).
Practical implications
Behavioural legitimacy is critical to business management, particularly for the organis-
ational downsizing strategy, which might harm employees and cause social instability.
International management firms should not only acquire internal legitimacy, but also
legitimacy in foreign social institutions. To comply with the internal institution of host
firms and acquire profits from foreign investments, MNCs should design appropriate strat-
egies and practices based on the interfaces of host firms and local institutional factors. For
example, adopting a responsible institutional downsizing strategy would reduce objections
to and criticism for organisational downsizing in host environments. Using isomorphic
HRM practices to enhance intellectual capital would help demonstrate that cultivating
local employees contributes to maintaining competitiveness with other countries. This
image would be easily accepted by local employees and society, and gradually decrease
the number of negative images of organisational downsizing. Universal values such as
‘treating employees well’ should be emphasised.
Suggestions for future research
The research background in this study is Taiwan, a Chinese society, with the national
characteristics of a medium level of power distance, masculinity, individualism, and
uncertainty avoidance that emphasise benevolence and righteousness. Therefore, different
research targets in another social context might incur varying outcomes. Further research
should investigate cross-cultural comparisons on various backgrounds to design a larger
sample to construct a more comprehensive organisational downsizing institutional
theory. According to Kostova et al. (2008), we should not only apply institutional
theory to examine MNC actions (isomorphic actions) but also adopt other perspectives.
Actions that are less isomorphic imply an inability to explain some aspects of neo-insti-
tutional theory.
Acknowledgements
This study was supported by National Science Council Research Fund of Taiwan (NSC
96-2416-H-160-001-MY3).
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