User Report

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Journal of General Management Vol. 26 No.2 Winter 2000

A Reappraisal ofHRM Models in Britain by Pawan s. Budhwar

Human Resource Management is still struggling to find a strategic role.

For a better understanding ofthe subj ect, both management practitioners and scholars need to study human resource management (HRM) in context [1]. The dynamics of both the local/regional and international/ global business context in which the firm operates should be given a serious consideration. Similarly, there is a need to use multiple levels of analysis when studying HRM: the external social, political, cultural, and economic environment; and the industry. Examining HRM out-of-context could be misleading and fail to advance understanding. A key question is how to examine HRM in context? One way is by examining the main models of HRM in different settings. However, there is no existing framework that can enable such an evaluation to take place. An attempt has been made in this paper to provide such a framework and empirically examine it in the British context.

This paper is divided into three parts. Initially, it summarises the main developments in the field of HRM. Then, it highlights the key emphasis of five models of HRM (namely, the 'Matching model'; the 'Harvard model'; the 'Contextual model'; the '5-P model'; and the 'European model' ofHRM). Lastly, we will address the operationalisation of the key issues and emphases of the aforementioned models by examining their applicability in six industries ofthe British manufacturing sector. The evaluation highlights the context specific nature of British HRM.

This introduction looks at the need to identify the core emphasis of the main HRM models that could be used to examine their applicability in different national contexts. Developments in the field of HRM are now well documented in the literature [2, 3]. The debate relating to the nature ofHRM continues today, although the focus of the debate has changed over a period of time. At present, the contribution ofHRM in improving

Pawan S. Budhwar is Lecturer in Organizational Behaviour and HRM at CardiffBusiness School, UK.

Journal of General Management Vol. 26 No.2 Winter 2000

the firm's performance and the overall success of any organization (alongside other factors) is being highlighted in the literature [4, 5].

Alongside these debates, a number of important theoretical developments have taken place in the field of HRM. For example, a number ofmodels ofHRM have been developed over the last 15 years or so. Some of the main models are: the 'Matching model'; the 'Harvard model'; the 'Contextual model'; the '5-P model'; and the 'European model' ofHRM [6, 7]. All these models have been developed in the US and the UK. These models ofHRM are proj ected to be useful for analysis both between and within nations. However, the developers of these models do not provide clear guidelines regarding their operationalisation in different contexts. Moreover, it is interesting to note that, although a large number of scholars refer to these models, very few have tested their practical applicability (exceptions being Benkhoff [8]; Monks [9]; Truss et al. [10]). For the development of relevant management practices there is then a clear need not only to highlight the main emphasis of the HRM models but also to show their operationalisation. Such an analysis will help to examine the applicability of these models in other parts of the world. With the increasing levels ofglobalisation ofbusiness such investigations have become an imperative.

Moreover, although the present literature shows an emphasis on themes such as 'strategic HRM' (SHRM), the majority of researchers persist in examining only the traditional 'hard' and' soft' models ofHRM [11]. For the growth and development of SHRM, there is a strong need to examine the applicability of those models ofHRM which can help to assess the extent to which it has really become strategic in different parts of the world, and the main factors and variables which determine HRM in different settings. This will not only test the applicability of HRM approaches in different regions, but will also help to highlight the context specific nature of HRM practices.

The aims of this paper are twofold. First, to identify the core emphasis offive main models ofHRM which can be used to examine their applicability in different national contexts. Second, to test empirically the applicability of these models of HRM in the British context. Before answering why this investigation is being conducted in the UK, the main models of HRM are briefly analysed.

Models of HRM

Five models ofHRM, which are widely documented in the literature are chosen for analysis. They are: the 'Matching model'; the 'Harvard model'; the 'Contextual model'; the '5-P model'; and the 'European model' ofHRM [12,13, 14]. The reason for the selection and analysis of thesemodelsis two-fold.First, it will help to highlight their main contribution

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to the development of SHRM as a distinct discipline. Second, it will help to identify the main research questions suitable for examining these models in different national settings. The analysis begins with one of the traditional models ofHRM.

The strategic fit of HRM

The main contributors to the 'Matching model' ofHRM come from the Michigan and New York schools. Fombrun et al. 's [15] model highlights the 'resource' aspect ofHRM and emphasises the efficient utilisation of human resources (like otherresources) to meet organizational objectives. The matching model is mainly based on Chandler's [16] argument that an organization's structure is an outcome of its strategy. Fombrun et al. expanded this premise and developed the matching model of strategic RRM, which emphasises a 'tight fit' between organizational strategy, organizational structure and HRM system, where both structure and HRM are dependent on the organization strategy. The main aim of the matching model is therefore to develop an appropriate 'Human Resource System' that will characterise those HRM strategies that contribute to the most efficient implementation ofbusiness strategies. The Schuler group made further developments to the matching model and its core theme of 'strategic fit' in the late 19?Os [17]. The core issues emerging from the matching models are:

1. Do organizations show a 'tight fit' between their HRM and organization strategy where the former is dependent on the latter? Do personnellHR managers believe they should develop HRM systems only for the effective implementation of their organization strategies?

.2. Do organizations consider their HRs as a cost and use them sparingly? Or, do they devote resources to the training of their HRs to make the best use of them?

3. Do HRM strategies vary across different levels of employees?

The soft variant of HRM

Beer et al. [18] articulated the 'Harvard Model' of HRM. It is also denoted as the 'Soft' variant ofHRM [19], mainly because it stresses the 'human' aspect of HRM and is more concerned with the employer- employee relationship. The model highlights the interests of different stakeholders in the organization (such as shareholders, management, employee groups, government, community and unions) and how their interests are related to the objectives of management. It also recognises the influence ofsituational factors (such as the market situation) on HRM policy choices. According to this model, the actual content of HRM is described in relation to four policy areas i.e. human resource flows,

Journal of General Management Vol. 26 No.2 Winter 2000

reward systems, employees' influence and work systems. Each of the four policy areas is characterised by a series of tasks to which managers must attend. The outcomes that these four HR policies need to achieve are commitment, competence, congruence, and cost effectiveness. The model allows for analysis of these outcomes at both organizational and societal levels. As this model acknowledges the role ofsocietal outcomes, it can provide a useful basis for comparative analysis of HRM [20]. The key issues emerging from this model which can be used for examining its applicability in different contexts are:

1. What is the influence ofdifferent stakeholders and situational and contingent variables on HRM policies?

2. To what extent is communication with employees used as a means to maximise commitment?

3. What level of emphasis is given to employee development through involvement, empowerment and devolution?

The contextual model of HRM

Researchers at the Centre for Corporate Strategy and Change at the Warwick Business School developed this model. They examined strategy making in complex organizations and related this to the ability to transform HRM practices [21,22]. Hendry and associates argue that HRM should not be labelled as a single form of activity. Organizations may follow a number of different pathways in order to achieve the same results. This is mainly due to the existence of a number of linkages between the outer environmental context (socio-economic, technological, political-legal and competitive)and inner organizationalcontext (culture, structure, leadership, task-technology and business output). These linkages directly contribute to forming the content of an organization's HRM. The core issues emerging from this model are:

1. What is the influence of economic (competitive conditions, ownership and control, organization size and structure, organizational growth path or stage in the life cycle and the structure of the industry), technological (type of production systems) and socio-political (national education and training set-up) factors on HRM strategies?

2. What are the linkages between organizational contingencies (such as size, nature, positioning ofHR, and HR strategies) and HRM strategies?

Strategic integration of HRM

The existing literature reveals a trend in which HRM is becoming an integral part of business strategy - hence, the emergence of the term SHRM. It is largely concerned with 'integration' and 'adaptation'. The purpose of SHRM is to ensure that [23]:

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Journal of General Management VoL 26 No.2 Winter2000

1. HRM is fully integrated with the strategy and strategic needs of the firm;

2. HR policies are coherent both across policy areas and across hierarchies; and

3. HR practices are adjusted, accepted, and used by line managers and employees as part of their every day work.

Based on such premises, Schuler [24] developed a 5-P model of SHRM that melds five HR activities (philosophies, policies, programs, practices and processes) with strategic needs. This model, to a great extent, explains the significance ofthese five SHRM activities in achieving the organization's strategic needs, and shows the inter-relatedness of activities that are often treated separately in the literature. This is helpful in understanding the complex interaction between organizational strategy and SHRM activities.

The model raises two important issues (also suggested by many other authors in the field) for SHRM comparisons. These are:

1. What is the level of integration of HRM into the business strategy?

2. What is the level ofresponsibility for HRM devolved to line managers?

European model of HRM

Based on the growing importance of HRM and its contribution towards economic success and the drive towards Europeanisation, Brewster [25] proposes a 'European model ofHRM'. His model is based on the premise that European organizations operate with restricted autonomy. They are constrained at both the international (European Union) and national levels by national culture and legislation, at the organization level by patterns of ownership, and at the HRM level by trade union involvement and consultative arrangements [26, p. 3]. Brewster suggests the need to accommodate such constraints when forming a model ofHRM. He also talks about 'outer' (legalistic framework, vocational training programs, social security provisions and the ownership patterns) and 'internal' (such as union influence and employee involvement in decision making) constraints on HRM. Based on such constraints, Brewster's model highlights the influence of factors such as national culture, ownership structures, the role of the state and trade unions on HRM, in different national settings.

The European model shows an interaction between HR strategies, business strategy and HR practice and their interaction with an external environment constituting national culture, power systems, legislation, education, employee representation and the constraints previously mentioned. It places HR strategies in close interaction with the relevant

Journal of General Management Vol. 26 No.2 Winter 2000

organizational strategy and external environment. One important aim of this model is to show factors external to the organization as a part of the HRM model, rather than as a set of external influences upon it.

From the above analyses, it can be seen that there is an element of both the contextual and 5-P models of HRM present in Brewster's European model. Apart from the emphasis on 'strategic HRM', one main issue important for cross-national HRM comparisons emerges from Brewster's model. This is:

• What is the influence of international institutions, national factors (such as culture, legal set up, economic environment and ownership patterns), and national institutions (such as the educational and vocational set-up, labour markets and trade unions) on HRM strategies and HRM practices?

Recently, Budhwar and associates [27, 28,29,30] have proposed a framework for examining cross-national HRM. They have identified three levels of factors and variables that are known to influence HRM policies and practices and which are worth considering for cross-national HRM examinations. These are national factors (such as national culture, national institutions, business sectors and dynamic of the business environment), contingent variables (such as the age, size, nature, ownership, and life cycle stage of the organization, the presence of trade unions and HR strategies, and the interests of different stakeholders) and organizational strategies and policies (related to primary HR functions, internal labour markets, levels ofintegration and devolvement, and nature ofwork). This framework is used to examine the applicability ofthe issues arising from the five HRM models in British organizations. But why conduct this form of investigation, and in the British context?

As mentioned already, there is a scarcity of this type of research. So far, only Truss et al. [31] have examined the applicability of some of the models of HRM in a few UK case companies. Apart from their research, there is scarcely any study that conducts the type ofinvestigation described here. There are, then, two main reasons for conducting this investigation in British companies. First, a UK sample possesses the characteristics suitable to test the operationalisation ofthe main emphases and critical issues ofthe five models ofHRM. Second, the HRM function in the UK is under intense pressure due to competitive conditions, and the restructuring and rightsizing programmes going on in British organizations, as well as the pressure on British firms from EU and other international players to stay competitive and meet the EU regulation regarding the management ofhuman resources. In such dynamic business conditions it is worth examining the HRM function in context. Moreover, since the five models have been developed among Anglo-Saxon nations, it is sensible to test them initially in these countries before recommending their testing in others parts of the world.

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The Research Methodology

Sample and data collection

A mixed methodology, using a questionnaire survey and in-depth interviews, was adopted. During the first phase of the research, a questionnaire survey was conducted between August 1994 and December 1994 in British firms having 200 or more employees in six industries in the manufacturing sector (food processing, plastics, steel, textiles, pharmaceuticals and footwear). The respondents were the top personnel specialist (one each) from each firm. The response rate ofthe questionnaire survey was approximately 19 per cent (93 out of 500 questionnaires). The items for the questionnaire were constructed from existing sources, such as those developed by Cranfield researchers in their study ofcomparative European HRM [32] and other studies (see for example [33, 34]). The questionnaire consisted of 13 sections. These were: HR department structure, role of the HR function in corporate strategy, recruitment and selection, pay and benefits, training and development, performance appraisal, employee relations, HRM strategy, influence ofnational culture, national institutions, competitive pressures and business sector on HRM, organizational details. Public limited companies represented approximately one-third of the sample, with the remainder from the private sector. The industry-wide distribution of respondents is shown in Table 1.

Table 1: Sample Industry Distribution

Indtitry Percentage . Food Processing 17.2 Plastics 17.2 Steel 16.1 Textiles 17.2 Pharmaceuticals 21.5 Footwear 10.8

Analysis of the demographic features of the sample suggests that the sample was representative ofthe total population. Sixty-two per cent of sample organizations were medium-sized and employed 200-499 employees, 14 per cent employed 500-999 employees, 15 per cent 1000- 4999 employees, and 8 per cent employed 5000 or more employees.

In the second phase of the research, 24 in-depth interviews were conducted with personnel specialists representative of those firms which participated in the first phase of the research. The interviews examined six themes, viz. the nature of the personnel function, integration ofHRM into the corporate strategy, devolvement ofHRM to line managers, and the influences of national culture, national institutions and business environment dynamic on HRM.

Journal of General Management Vol. 26 No.2 Winter 2000

Measures

Multiple regression analysis and descriptive statistics are used to analyse questionnaire data. Table 1 in the Appendix shows the main dependent and independent variables used for multiple regression analysis. Table 2 in the Appendix presents the mean scores of respondents regarding the influence of different aspects of national factors (culture, institutions, business environment dynamic and business sector) and HR strategies on HRM policies and practices. The qualitative data is content analysed. In the discussion, survey results are complemented by key messages coming from the qualitative interviews.

Findings of the Study

The matching models suggest a strong dependence ofHRM on organization strategy, i.e, HRM is mainly developed for the effective implementation of organization strategies. The results show that in 34.6 per cent of the organizations under study personnel is involved from the outset in the formation of corporate strategy, and 42 per cent of organizations actively involve HRM during the implementation stage of their organizational strategies. Such a trend of 'active' personnel management is further evident from 55 per cent of sample organizations having personnel representation at board level. Moreover, 81.1 per cent ofthe respondents believe that their HRM has become proactive over the last five years (i.e. more involved in decision making).

Such results reflect the growing strategic and proactive nature of the British personnel function. There is support for such findings in the existing literature [35, 36].

The second reason to examine the matching models in a cross- national context is to assess whether human resources are considered as a cost ('use them sparingly') or as an asset (spend on training to 'make their best use '). The results suggest that British organizations claim to be spending variable though reasonable proportions oftheir annual salaries on human resource development (HRD) related activities (see Table 2).

Table 2: Proportion of Annual Salaries and Wages Currently Spent on Training and Development

Value(%) Percentage of Sample Nil -

0.1- 2.00 41.3 2.01-4.00 7.6 4.01- 6.00 3.3

6.01 or more 1.1 Don't know 46.7

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A similar pattern characterizes the number ofdays training provided to different levels ofemployees (see Table 3). The substantial majority of British firms have increased (rather than maintained or reduced) their training spend across all categories of staff over the last five years (see Table 4). There is evidence that this investment has been directed particularly in the areas of performance appraisal, communication, delegation, motivation and team building.

Table 3: Average Number of Days Training and Development Given to Staff Categories Per Year

Different Cat~ories of Staff Number ofDays Mana}!erial(%) Prof,/Technical(%) Clerical(%) Manual(%)

Nil 1.2 1.1 2.3 1.2 0.1-3.00 24.4 22.8 35.6 24.7 3.01-5.00 20.9 21.7 13.8 11.7

5.01-10.00 7.0 14.7 4.6 11.8 10.1 and above 5.8 4.6 3.5 9.4

Don't know 40.7 40.9 40.2 41.2

These developments in the British HRD scene appear to be consistent with the increased realisation by both business and government that the development of human resources has been neglected for too long [37].

Table 4: Nature of Change in Amount of Money Spent on Training Per Employee

Different Categories of Staff Nature ofChange Mana}!erial("/o) Prof,/Technical("/o) Clerical(%) Manual(%) Increased 59.8 63.0 53.3 60.9 Same 21.7 18.5 28.3 20.7 Decreased 7.6 8.7 7.6 7.6 Don't know 10.9 9.8 10.9 10.9

Another key emphasis of the matching model suggests a variation in HRM strategies across different levels of employees. This is clearly evident from the results as the nature and type of approach to the management of different levels of employees vary significantly (see for example, Tables 3 and 4). This aspect is further highlighted later in this paper. Based on the above evidence, it seems that the British personnel function still plays an implementationist role rather than being actively involved in strategy formulation. On the other hand, there is a strong emphasis on training and development.

Important Situational Determinants

One of the basic assumptions of the Harvard model of HRM is the influence of a number of situational factors (such as work force

Journal of General Management Vol. 26 No.2 Winter 2000

characteristics, unions, labour legislation and business strategy) and different stakeholders (such as unions, government and community) on HRM policies. The impact of a few of the situational factors and stakeholders (proposed by Beer et al. [38D was examined during the multiple regressions, analysis of means scores and the analysis of interview results.

Taking the number of employees as a characteristic of the work force [39, 40], the regression results show that small British organizations (those having less than 499 employees) are likely to recruit their managerial staff by advertising externally. Medium size organizations (those having 500 to 999 employees) are likely to recruittheirclerical staffas apprentices. Large organizations (those having 1000 to 4999 employees) are more likely to use assessment centres to train their human resources. Lastly, very large firms (having over 5000 employees) are less likely to recruit their managerial staff by advertising internally and their manual staff through the use of word of mouth method. These firms are likely, however, to recruit their professional staff with the help of consultants. Moreover, large UK firms are more likely to adopt formal career plans, succession plans and planned job rotation to develop their human resources (for details see Table 1 in Appendix).

Support for these findings can be found in the literature (see for example, [41D. The size ofan organization has a positive relation with the formalism of their HRM policies [42]. Therefore, as the size of the firm becomes large, logically, the degree offormalism ofits personnel function increases and the organization obtains the help ofrecruitment agencies to recruit its professional employees.

The results show a strong impact of labour laws, educational and vocational training set up (highlighting government policy) and unions on British HRM policies (see Table 2 in Appendix). Unions in the UK are now playing a more supportive role [43]. The implementation of labour legislation is also having significant influence on UK HRM policies. Various pressures groups also contribute in this regard (for example, against age discrimination). Over the last decade or so, the education and vocational set-up in the UK has initiated a number of programmes and qualifications such as the national vocational qualifications (NVQs), investors in people (IIP) and' opportunity 2000' . These are now significantly influencing HRM in British organizations [44].

The results also show a number of significant regressions regarding the impact of HR strategies on British HRM. Results in Table 1 in the Appendix show that organizations pursuing a cost reduction strategy are more likely to recruit their clerical and manual staffas apprentices. These organizations are likely to adopt an effective resource allocation HR strategy. Organizations pursuing a talent improvement HR strategy are

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less likely to recruit their manual staff by word of mouth method. However, sample firms pursuing a talent acquisition HR strategy are likely to use consultants to recruit their managerial staff and recruitment agencies for manual staff. These organizations are also likely to adopt assessment centres to train their staff.

Most of the above results seem to be logical. For example, by recruiting employees as apprentices organizations not only pay them less but also train and prepare them for working in the long run in their organizations. Hence, it helps to reduce the costs. Similarly, by recruiting employees externally, organizations increase the opportunity to improve their talent base.

The second key emphasis of the Harvard model of HRM suggests extensive use of communication with employees as a mechanism to maximise commitment [45, p. 63]. Ninety-one per cent of British organizations share information related to both strategy and financial performance with their managerial staff. However, this percentage is significantly lower for other categories of employees (see Table 5).

Table 5: Employees Formally Briefed about Strategy or Financial Performance

Different Categmes of Staff Tvoe ofInformation Managerial(%) Prof/Technical(%) Clerical(%) Manual(%) Strategy - 8.0 8.6 6.4 Financial Performance 6.5 14.8 39.5 38.5 Both 91.3 65.7 42.0 23.6 Neither 2.2 11.6 9.9 31.5

There can be a number of explanations for the difference in the sharing of strategic and financial information with different levels of employees in British organizations. Whilst noting that top personnel specialists are now more and more involved in strategy making, it seems that top management continue to be reluctant to devolve responsibility to line managers for the dissemination offinancial and strategic information. These issues are further examined when discussing the 5-P model.

The above discussion suggests applicability of the Harvard model ofHRM in British organizations. The results showed an impact oflabour laws, education vocational set-up, unions, work force characteristics and HR strategies on HRM policy choices. There are encouraging results on the communication of information with different levels of employees regarding sharing strategic and financial performance and on employee development through their involvement and training.

Contextual Factors

The main issue against which the relevance of the contextual model can be evaluated is the impact on HRM policies and practices of economic

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(characterized by competitive pressures, ownership and life cycle stage), technological (type ofproduction system)and socio-political (characterised by national education and training set-up) factors and organizational contingencies (such as size, age and nature of organization).

The results show a strong influence of competitive pressures on British HRM policies and practices (see Table 2 in Appendix). To achieve a competitive edge in such situations, they are focusing particularly on total customer satisfaction and the restructuring oftheir organizations. As competitive pressures are also forcing British organizations to enter into new business arrangements (such as alliances), so these are having direct influence on HRM policies and practices.

The results also show the impact of increasingly sophisticated informationand communications technology on HRM policies and practices (see Table 2 in the Appendix). Further evidence indicates that the majority of respondents suggest these technologies mainly influence training, appraisal and transfer functions. Why? Because with the change in technology, employees need to be trained to handle it. To see if they have achieved the required competence they are appraised and if required, transferred to suitable positions.

Finally, we summarise the relevance of the contextual model of HRM in terms ofthe impact of organizational contingencies. Contingent variables such as size of the organization, presence of HR strategy and presence of unions were examined above, as were the impacts of ownership and organizational life cycle stage. These variables do not seem significantly to impact HRM in British organizations.

Nevertheless, there is significant evidence overall regarding the applicability of the contextual model ofHRM in British organizations.

Strategic Integration and Devolvement of HRM in Britain

Our discussion now focuses on the relevance of the '5 P' model ofHRM in British organizations. To achieve this, results regarding the integration of HRM into corporate strategy and the devolution of responsibility for HRM to line managers are examined. The detailed results are presented elsewhere [46], but are summarized below.

In brief, the level of integration is measured on the basis of the following four scales:

a) representation of Personnel on the board; b) presence of a written Personnel strategy; c) consultation ofPersonnel (from the outset) in the development

of corporate strategy; and d) translation ofPersonnel/HR strategy into a clear set of work

programmes.

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The level of devolvement is measured on the basis of the following three scales:

a) primary responsibility with line managers for HRM decision making (regarding pay and benefits, recruitment and selection, training and development, industrial relations, health and safety, and workforce expansion and reduction);

b) change in the responsibility of line managers for HRM (regarding pay and benefits, recruitment and selection, training and development, industrial relations, health and safety, and workforce expansion and reduction); and

c) percentage ofline managers trained in performance appraisal, communication, delegation, motivation, team building and foreign language.

High integration is the result of personnel representation at board level, the personnel function being consulted about corporate strategy from the outset, the presence of a written personnel strategy, and the translation of such a strategy into a clear set of work programmes. As mentioned earlier, the personnel function is represented at board level in the majority (55 per cent of organizations). For our sample companies, 87.4 per cent have corporate strategies. Of these, 34.6 per cent consult the personnel function at the outset, 42 per cent involve personnel in early consultation, and only 13.6 per cent involve personnel during the implementation stage. Over a quarter (26.4 per cent) of sample organizations did not have a personnel strategy, 29.9 per cent had an unwritten strategy and 43.7 per cent had a written personnel strategy. A clear majority (57.4 per cent) of organizations felt that their personnel strategy was translated into clear work programmes.

High devolvement is the result of: primary responsibility for pay, recruitment, training, industrial relations, health and safety and expansion/ reduction decisions lying with the line (see Table 6); line responsibility for these six areas on an increasing trend (see Table 7); and, evidence of devolved competency with at least 33 per cent of the workforce being trained in appraisals, communications,delegation, motivation, team building and foreign languages.

Budhwar's [47] analysis shows that when the four measures of integration are summated and divided into a single scale of high and low type, 50.5 per cent of the sample organizations would be categorised as having high integration and 49.5 per cent fall into the low integration category. The average score of the summated integration scale for a1193 organizations is .50. These results show a moderate level of integration being practised in the sample industries. On the other hand, the summated scales demonstrate a low level of devolvement. Sixty-one per cent of the sample practise low levels of devolvement of HRM to line managers.

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Table 6: Primary Responsibility for Major Decisions on Personnel Issues

Personnel Issues Line Line Mgt in IIR Dilpt. inHRDept. Consultation COllSuJtationRelated to: Mgt. wi!il1lB.l)llUt. withLineMat. Pay andBenefits 48.3 14.3 11.0 26.4 Recruitment and Selection 17.2 12.9 34.4 35.5 Training andDevelopment 15.1 18.3 22.5 44.1 Performance Aonraisal 17.5 6.9 30.4 45.2 Industrial Relations 36.3 13.2 25.3 25.2 Health and Safety 18.5 32.6 19.6 29.3 Workforce

19.4 19.4 44.1 17.1Expansion/Reduction WorkSystem/Job Design 7.6 33.7 40.2 18.5 Figures in the above cells represent valid percentage, calculated after excluding the missing values.

Table 7: Change in Responsibility of Line Management for Different Personnel Issues

PellSonnelIssues Increased (%) Same(%) Decreased (%) Pay andBenefits 27.2 65.2 7.6 Recruitment and Selection 43.5 48.9 7.6 Training and Development 69.6 23.9 6.5 Performance Appraisal 60.0 37.8 2.2 Industrial Relations 28.9 63.3 7.8 Healthand Safety 61.5 35.2 3.3 Workforce

38.9 54.4 6.7Expansion/Reduction WorkSystem/Job Design 43.3 53.3 3.3

The results confirm the relevance of the 5-P model of HRM in British organizations. They also help to examine the main emphasis of Brewster's [48] European model of HRM, i.e, the linkages between corporate strategy and HRM strategy.

Conclusion

Overall, the results show a mixed picture, i.e. from strong to moderate applicability of the mentioned HRM models in Britain. The study aimed to examine HRM in context, and the findings should be useful for relevant policy makers. In particular, it seems that the sample firms are practising a relatively low level of devolvement in comparison to the integration function. Ifthe HRM function is to become more strategic, then the level of practice of both these concepts has to increase. Such demands are likely to increase in future as more and more firms restructure and become lean in order to respond to competitive and other pressures [49].

The study has two main limitations. First, it is restricted to six industries ofthe UK manufacturing sector. Second, the views of only top

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personnel specialists were examined. In order, therefore, to obtain a more comprehensive picture, research needs to be extended to other business sectors and to the views of other key actors (such as line managers). Future research could also build upon this study by investigating other models ofHRM and their applicability in different national contexts.

Appendix

Table 1: Factors Determining HRM Practices in British Organizations

Independent. lJependentVariables If BiJta . t·valueVarin/J/es Training and development

0.2102 0.2984* 2.3790 Introductory through planned iob rotation lifecycle stage Communication through

0.1629 -0.2663* -2.0720 immediate superior

Turnaround Recruiting managerial staff by 0.3695 -0.3038* -2.6170

lifecycle stage advertising externally Recruiting managerial staff by

0.3695 0.3658** 3.0590 Less than 499 advertising externally employees Recruiting clerical staff from 0.1014 -0.3184* -2.4220

recruitment agencies Between 500- Recruiting clerical staff as

0.3337 0.2891* 2.4600 599 employees apprentices Between 1000- Training and development 4999 through assessment centres 0.2607 0.3547** 2.8530 employees

Recruiting managerial staff by 0.1563 -0.2835* -2.1800

advertising internally Recruiting professionals/technical staff by

0.1039 0.3223* 2.4550 use of search/selection

More than consultants

5000 Recruiting manual staffby

0.3698 -0.4529** -3.9340 employees

word of mouth Training and development through formal career plans

0.1406 0.375** 2.9170

Training and development 0.1685 0.4105** 3.2460

through succession plans Training and development

0.2102 0.3873** 3.0880 though planned job rotation

Public Limited Recruiting managerial staff by 0.3695 0.4436** 3.8050Company advertising externally

Recruiting managerial staff 0.0830 -0.2881* -2.1700

from current employees State-owned Recruiting clerical staff from

0.2842 -0.2583* -2.0650 organization current emnlovees

Recruiting manual staff by 0.3698 -0.3342** -2.9100

word of mouth Organizations incorporated Commnnication through trade

0.7445 -0.216** -3.0370 between 1869- unions or work councils 1899 Organizations incorporated Recruiting manual staff from

0.1557 0.2609* 2.0240 between 1900- current employees 1947

Continued ...

Journal of General Management Vol. 26 No.2 Winter 2000

Table 1 Continued:

Independent lJepen4ent Variables .Jf Beta tvalueVariable Recruitingclericalstaffby 0.2465 -0.3931** -3.2110advertising externally Recruitingmanualstaffby 0.1974 -0.2767* -2.1550advertising externally

Organizations Trainingand development 0.2607 0.4364** 3.3780incorporated throughassessment centres between 1948- Communication through 0.1629 -0.3255* -2.53201980 immediatesuperior

No formal communication 0.3517 0.3265** 2.7370methods Communication through 0.0858 0.2929* 2.2090suggestion box(es) Recruitingclericalstaff from 0.2842 -0.3019* -2.4240current employees

Cost reduction Recruitingclericalstaff as 0.3337 0.4182** 2.9450HRstrategy apprentices Recruiting manualstaff as 0.1330 0.3646** 2.8240apprentices

Talent Recruitingmanualstaff by 0.3698 -0.3655** -3.2440improvement word of mouthHRstrategy Recruiting managerial staffby

0.0777 0.2787* 2.0930use of search/selection Talent consultants acquisition HR Recruitingmanualstaff from 0.0914 0.3024* 2.2880strategy recruitmentagencies

Trainingand development 0.2607 0.2857* 2.2090throughassessment centres Effective Recruitingclericalstaff as

0.3337 0.2882* 2.0300resourceHR apprenticesstrategy Recruitingmanagerial staff by 0.3695 0.3593** 2.9750advertising externally Recruitingmanualstaff by 0.1226 0.3502** 2.6960Unionised advertising internally

firms Communication through 0.3517 -0.255* -2.1820attitude survey Communication throughtrade 0.7445 0.5656** 6.4000unions or work councils

* Significance at .05 level; **Significance at .01 level

-

..

Journal of General Management Vol. 26 No.2 Winter 2000

Table 2: Influence of Different Aspects of National Factors on HRM

Aspectsoff"lational (;ultttre No. of Cases Mean 1 Way in which managers are socialised 84 18.07 2 Common values, norms of behaviour and customs 81 20.28 3 The influence of pressure groups 58 10.47

4 Assumptions that shape the way managers perceive and

84 25.98 think: about the organization

5 The match to the organization's culture and 'the way we

86 35.58 do things around here'

N(ltif.}1Inl T- o '011.6 1 National Labour Laws 82 40.91 2 Trade Unions 61 21.72 3 Professional Bodies 56 15.11 4 Educational and Vocational training set-up 84 27.62 5 International Institutions 54 20.07

A~l1ects QflIusinessEnvironment 1

Increased national/international competition - 72 27.56

Globalisation of corporate business structure Growth of new business arrangements, e.g. business

2 alliances, joint ventures and foreign direct investment 66 19.01 through mergers and acquisitions

3 More sophisticated information/communication

70 19.62 technology or increased reliance on automation

4 Changing composition of the workforce with respect to

48 12.39 gender, age, ethnicity and changing employee values

5 Downsizing of the workforce and business re-

69 23.13 engineering

6 Heightened focus on total management or customer

78 26.92 satisfaction

Aspects qfBusinessSector 1

Common strategies, business logic and goals being 71 22.95

pursued by firms across the sector

2 Regulations and standards (e.g. payments, training,

79 20.35 health and safety) specific to your industrial sector Specific requirement/needs of customers or suppliers

3 that characterise your sector (i.e. supply chain 82 28.96 management)

4 The need for sector-specific knowledge in order to 56 15.35 provide similar goods/services in the sector

5 Informal or formal benchmarking across competitors in

61 16.39the sector (e.g, best practices of market leaders) Cross-sector co-operative arrangements, e.g, common

6 technological innovations followed by all firms in the 37 10.54 sector

7 Common developments in business operations and work

49 14.40 practices dictated by the nature of the business

8 A labour market or skill requirement that tends to be

39 13.10used by your business sector only

Respondentswere asked to allocate a totalof100points to the different aspects ofthe above nationalfactors.

Journal of General Management Vol. 26 No.2 Winter 2000

References

[1] Jackson, S. E. and Schuler, R. S., 'Understanding Human Resource Management in the Context ofOrganizations and their Environment' , Annual Review of Psychology, Vol. 46, 1995, pp. 237-264.

[2] Legge, K., Human Resource Management: Rhetorics and Realities, Chippenham: MacMillan Business, 1995.

[3] Sisson, K. and Storey, J., The Realities of Human Resource Management, Buckingham: Open University Press, 2000.

[4] Guest, D. E., 'Human Resource Management and Performance: A Review and Research Agenda', International Journal ofHuman Resource Management, Vol. 8, No.3, 1997, pp. 263-276.

[5] Schuler. R. S. and Jackson, S. E., Strategic Human Resource Management, London: Blackwell, 1999.

[6] Brewster, C., 'Towards a European Model of Human Resource Management', Journal of International Business Studies, Vol. 26, No.1, 1995, pp. 1-22.

[7] Legge, K., 1995, op. cit. [8] Benkhoff, B., 'A Test ofthe HRM Model: Good For Employers and

Employees', Human Resource Management Journal, Vol. 7, No.4, 1997,pp.44-60.

[9] Monks, K., 'Global or Local? HRM in the Multinational Company: The Irish Experience', The International Journal of Human Resource Management, Vol. 7, No.3, 1996, pp. 721-735.

[10] Truss, C., Gratton, L., Hailey, H., McGovern, P. and Stiles, P., 'Soft and Hard Models ofHuman Resource management: A Reappraisal' , Journal ofManagement Studies, Vol. 34, No.1, 1997, pp. 53-73.

[11] Legge, K., 1995. op. cit. [12] Brewster, C., 1995, op. cit. [13] Legge, K., 1995. op. cit. [14] Poole, M., 'Editorial: Human Resource Management in An

International Perspective', International Journal of Human Resource Management, Vol. 1, No.1, 1990, pp. 1-15.

[15] Fombrun, C. J., Tichy, N. M. and Devanna, M. A., Strategic Human Resource Management, New York: Wiley, 1984.

[16] Chandler, A., Strategy and Structure, Cambridge, MA: MIT Press, 1962.

[17] Schuler, R. S. and Jackson, S. E., 'Organizational Strategy and Organizational Level as Determinants of Human Resource Management Practices', Human Resource Planning, Vol. 10, No.3, 1987, pp. 125-141.

[18] Beer, M., Spector, B., Lawrence, P. R., Quinn Mills, D. and Walton, R. E., Human Resource Management, New York: Free Press, 1984.

[19] Legge, K., 1995. op. cit. [20] Poole, M., 1990. op. cit.

..

[21]

[22].. [23] [24] [25] [26] [27]

[28]

Journal of General Management Vol. 26 No. 2 Winter 2000

Hendry, C and Pettigrew, A.M., 'Patterns of Strategic Change in the Development of Human Resource Management', British Journal ofManagement, Vol. 3, 1992, pp. 137-156. Hendry, C., Pettigrew, A. M. and Sparrow, P. R., 'Changing Patterns of Human Resource Management,' Personnel Management, Vol. 20, No. 11, 1988, pp. 37-47. Schuler, R. S., 'Linking the People with the Strategic Needs of the Business', Organizational Dynamics, Summer, 1992, pp. 18-32. Ibid. Brewster, C., 1995, op. cit. Ibid. Budhwar, P., 'Taking Human Resource Management Research To The Next Millennium: Need For An Integrated Framework', Annual Academy of Management Conference, Chicago, 1999. Budhwar, P. and Debrah, Y., 'Rethinking Comparative and Cross National Human Resource Management Research,' The International Journal of Human Resource Management, 2001 (forthcoming).

[29] Budhwar, P. and Sparrow, P., 'An Integrative Framework For Determining Cross National Human Resource Management Practices', Human Resource Management Review, 2001 (forthcoming) .

[30] Budhwar, P. and Sparrow, P., 'National Factors Determining Indian and British HRM Practices: An Empirical Study', Management International Review, Vol. 38, Special Issue 2, 1998, pp. 105-121.

[31] Truss, C., Gratton, L., Hailey, H., McGovern, P. and Stiles, P., 1997, op. cit.

[32] Brewster, C. and Hegewisch, A., (eds.) Policy and Practice in European Human Resource Management, London and New York: Routledge, 1994.

[33] Baird, L. and Meshoulam, r., 'Managing Two Fits of Strategic Human Resource Management', Academy of Management Review, Vol. 13, No.1, 1988, pp. 116-128.

[34] Jackson, S. E., Schuler, R. S. and Rivero, J. C., 'Organizational Characteristics as Predictors of Personnel Practice', Personnel Psychology, Vol. 42, No.4, 1989, pp. 727-786.

[35] Legge, K., 1995, op. cit. [36] Hendry, C., Human Resource Management: A Strategic

Approach to Employment, Bath: Butterworth-Heinemann, 1998. [37] Townley, B. 'Communicating with Employees' , in Sisson, K. (ed.),

Personnel Management: A Comprehensive Guide to Theory and Practice in Britain, Blackball Business: London, 1996, pp.595- 633.

[38] Beer, M., Spector, B., Lawrence, P. R., Quinn Mills, D. and Walton, R. E., 1984, op. cit.

[39] Jackson, S. E. and Schuler, R. E., 1995, op. cit. [40] Tayeb, M., Organizations and National Culture, London: Sage,

1988.

Journal of General Management Vol. 26 No.2 Winter 2000

[41] Sisson, K. and Storey, J., 2000, op. cit. [42] Brewster, C. and Hegewisch, A., 1994, op. cit. [43] Heery, E., 'Annual Review Article 1996'. British Journal of

Industrial Relations, Vol. 35, 1997, pp. 87-109. [44] Collin, A. and Holden, L., 'The National Framework for Vocational

Education and Training', in. Beardwell, 1. and Holden, L., (eds.), Human Resource Management. London: Pitman Publishing, 1997, pp.345-377.

[45] Truss, C., Gratton, L., Hailey, H., McGovern, P. and Stiles, P., 1997,op. cit.

[46] Budhwar, P., 'Strategic Integration and Devolvement of Human Resource Management in the British Manufacturing Sector' , British Journal of Management, Vol. 11, No.4, 2000, (in Press).

[47] Ibid. [48] Brewster, C., 1995, op. cit. [49] Terry, M. and Purcell, J., 'Return to Slender' , People Management,

23 October, 1997,46-51.

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https://doi.org/10.1177/1536504219865226

California Management Review 2019, Vol. 61(4) 110 –134 © The Regents of the University of California 2019 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/1536504219865226 journals.sagepub.com/home/cmr

Special Issue on AI

Demystifying AI: What Digital transformation leaDers Can teaCh You about realistiC artifiCial intelligenCe Jürgen Kai-Uwe Brock1 and Florian von Wangenheim2

SUMMARY Recent years have seen a reemergence of interest in artificial intelligence (AI) among both managers and academics. Driven by technological advances and public interest, AI is considered by some as an unprecedented revolutionary technology with the potential to transform humanity. But, at this stage, managers are left with little empirical advice on how to prepare and use AI in their firm’s operations. Based on case studies and the results of two global surveys among senior managers across industries, this article shows that AI is typically implemented and used with other advanced digital technologies in firms’ digital transformation projects. The digital transformation projects in which AI is deployed are mostly in support of firms’ existing businesses, thereby demystifying some of the transformative claims made about AI. This article then presents a framework for successfully implementing AI in the context of digital transformation, offering specific guidance in the areas of data, intelligence, being grounded, integrated, teaming, agility, and leadership.

KeYwoRDS: artificial intelligence, polls and surveys, managers, management, management skills

I n 2014, Dr. Julio Mayol wondered, “We have access to a vast quantity of data but it’s hard to extract meaningful information that helps us improve the quality of the care we provide.” Dr. Mayol, Medical Director and Director of Innovation at the Carlos Clinical Hospital in Madrid, Spain, founded in

1787, found the answer after consulting with an external group of technology advi- sors: artificial intelligence (AI). About six months later, the innovation unit of the hospital, under his leadership, embarked on a project to apply AI. Rather than opt- ing for an off-the-shelf generic solution, the team worked closely with a technology

1Fujitsu, Tokyo, Japan 2ETH Zurich, Zurich, Switzerland

865226CMRXXX10.1177/1536504219865226California Management ReviewDemystifying AI: What Digital Transformation Leaders Can Teach You research-article2019

Demystifying AI: What Digital Transformation Leaders Can Teach You 111

provider of AI solutions and co-created an innovative new AI application tailored to their specific needs. After one year, the system was ready for field testing. Six months later, first results showed that the diagnostic and patient’s risks assessment solution can cut the time in half for preliminary assessment of patient records, with a 95% accuracy compared with eight domain experts who were psychiatrists with more than 20 years of experience. An unanticipated positive side effect of this immense increase in efficiency was that the medical staff had much more time for consultations and patient care, thereby increasing customer satisfaction.1

This exemplary case of a successful AI2 application stands in stark contrast to mounting evidence of AI failures,3 gaps between firms’ AI ambition and execu- tion,4 and a general “post-AI-hype sobering.”5 Given the mixed evidence and the paucity of empirical insights related to the successes and failures of AI implementa- tion projects, we embarked on a global research project with the aim of understand- ing managers’ perceptions and evaluations of AI. This research was informed by insights derived from the opening case as well as publicly available case study mate- rial.6 All these cases were excluded from the survey investigation. Between 2016 and 2018, more than 3,000 executives and managers were surveyed globally from across industries with a total of nearly 7,000 projects, including the application of AI and other advanced digital technologies. We do not necessarily assume that manag- ers know best, but they are important information sources about current and future AI potential for various reasons. First, given their involvement and business inter- est, they are the decision makers about future projects. Second, their perceptions and experiences will influence future implementation success.

Based on the above assessment (with high expectations and a few success stories on the one side, but frustrating experiences and stopped projects on the other side), we first establish the current prevalence of AI in business (study 1) and then explore key dimensions of successful AI implementations (study 2). Specifically, study 1 focused on the following research question (RQ1; see Figure 1):

Research Question 1 (RQ1): To what extent has the application of AI diffused in business?

In study 2, we explored AI in business in more detail. Specifically, we were interested in the following three research questions (RQ2-RQ4; see Figure 1):

Research Question 2 (RQ2): What are the anticipated perceived business impacts of AI? More specifically, to what extent are managers expecting impacts in the area of operations, offerings, and customer interactions?7

Research Question 3 (RQ3): Assuming differences concerning the per- ceived business impact of AI, what explains those differences, for example, on a country, industry, firm level, executive (respondent), and skill level?

Research Question 4 (RQ4): Given the opening case of AI success, can we identify leaders, firms that are experienced and successful in

CALIFORNIA MANAGEMENT REVIEW 61(4) 112

implementing AI-related projects?8 What makes them different from lag- gards, firms that have not yet moved beyond the planning phase, in terms of country-, industry-, firm-level factors, executive (respondent) factors, skills, and organizational traits? Furthermore, could these leaders real- ize more positive business impacts in areas such as operational efficiency, organizational agility, revenue growth, competitiveness, and customer experience? And how long does it usually take from the start of an AI project to achieving business impacts? In addition, we investigate whether leaders differ in their perception of AI implementation challenges and key success factors.

Research Structure and Guiding Frameworks

Figure 1 illustrates our research structure and the guiding frameworks we used. Phase 1 of our research, the exploration phase, was informed by ini- tial case study research (e.g., the opening case) and a first digital transformation

Figure 1. Structure and guiding frameworks of the research.

Sources: Framework references (in alphabetical order): John Hagel III and Marc Singer, “Unbundling the Corpo- ration,” Harvard Business Review, 77/2 (March/April 1999): 133-141; E. T. Penrose, The Theory of the Growth of the Firm (London: Wiley, 1959); Lynn W. Phillips, “Assessing Measurement Error in Key Informant Reports: A Methodological Note on Organizational Analysis in Marketing,” Journal of Marketing Research, 18/4 (November 1981): 395-415; Everett M. Rogers, Diffusion of Innovations, 4th ed. (New York, NY: The Free Press, 1995); B. Wernerfeld, “A Resource-based View of the Firm,” Strategic Management Journal, 5/2 (April-June 1984): 171- 180; Robert K. Yin, Case Study Research: Design and Methods, 4th ed. (Los Angeles, CA: Sage, 2009).

Demystifying AI: What Digital Transformation Leaders Can Teach You 113

and AI survey that aimed at understanding the extent of AI diffusion across firms worldwide. Given that AI is a recently adopted technology for most firms, this stage of our research was informed by diffusion of innovation theory in general and organizational innovation adoption implementation research in particular. From this body of past research, plus managerial interviews, we developed our stages of AI implementation model (see Figure 2). Phase 2 of our research, the descriptive phase, aimed at a broad yet deeper understanding of AI in firms’ digi- tal transformation worldwide. As the differential analysis emerged in phase 2 of our research, this phase was guided by three related organizational frameworks: the theory of the growth of the firm, the resource-based view of the firm, and the pragmatic firm conceptualization proposed by Hagel and Singer.9 All three have

Figure 2. Status of AI implementation in firms (study 1).

Source: We derived these five stages from interviews with managers and the organizational stages-of- innovation-adoption-implementation literature (e.g., G. W. Downs Jr., and L. B. Mohr, “Conceptual Issues in the Study of Innovations,” Administrative Science Quarterly, 21/4 (December 1976): 700-714; M. A. Scheirer, “Approaches to the Study of Implementation,” IEEE Transactions on Engineering Management, 30/2 (1983): 76- 82; L. G. Tornatzky and B. H. Klein, “Innovation Characteristics and Innovation Adoption-implementation: A Meta-analysis of Findings,” IEEE Transactions on Engineering Management, 29/1 (1982): 28-45; Everett M. Rogers, Diffusion of Innovations, 4th ed. (New York, NY: The Free Press, 1995). Note: n = 1,614 firms, worldwide, 2016-2017: “Which best describes the progress of your firm’s AI (Artificial Intelligence) implementation?” AI = artificial intelligence; DX = digital transformation.

CALIFORNIA MANAGEMENT REVIEW 61(4) 114

an internal resources focus in common and have guided our assessments in terms of firms’ experience, capabilities, challenges, and success factors. As a multistage, mixed-methods research design, research phase 1 informed research phase 2.

Data Collection

Data for this study were obtained in two waves (see Figure 1). Following a set of digital transformation AI case studies, the first exploratory survey was con- ducted in 2016-2017, addressing the first research question. The survey was con- ducted globally, online, utilizing a database of executives and senior managers provided by an international market research firm. The second survey was con- ducted in 2017-2018, addressing RQs 2 to 4. The second survey used a similar methodology. It was conducted globally, online, and the same market research firm provided samples of executive respondents. Sampling was guided by the following:

• Global coverage: firms from key countries (in terms of economy/GDP) in the Triad.10

• A minimum country quota of n = 50 where possible (with the exception of New Zealand with n = 29 in study 2, this was achieved).

• North American Industry Classification System (NAICS) industry sampling: focus on manufacturing (NAICS code 23, 31, 32, 33), information (NAICS code 51), transportation (NAICS code 48, 49), retail (NAICS code 41, 42, 44, 45), financial services (NAICS code 52), healthcare (NAICS code 62).

• Minimum industry quota: n = 50.

• Focus on medium to large firms in terms of revenue and employees.

• Senior respondents: focus on key informants of firms at C- or VP-level or above.

In order to assess response bias, we followed the logic of Armstrong and Overton11 and found no statistically significant differences at the .05 level in regard to any of the variables that we are reporting below. In terms of common method bias, we applied the marker variable approach and found no significant effects.12 Overall, we are confident that our findings can be generalized to medium to large Triad enterprises in the industries sampled and that our results are not the result of the instrument/sample used in our analysis. Sample details are provided in the endnote.13

AI in Business

To what extent are firms already using AI in their business? In 2016-2017, the time of the first survey, AI applications had already diffused quite broadly, with only 15% of firms not yet having any AI plans and 20% already having delivered results (see Figure 2).

Demystifying AI: What Digital Transformation Leaders Can Teach You 115

Interestingly, the application of AI was typically an integral part of a firm’s digital transformation project. With the exception of isolated experimentation with specific AI techniques such as deep learning, AI was not used in isolation, but as one technological element of several technologies aimed at enhancing a firm’s present and future business.14 It emerged that digital transformation is often the context for AI projects, such as call center transformation using advanced analyt- ics and AI or transforming operations using Internet of things (IoT), advanced analytics, and AI.

The Business Impact of AI

In the second survey, which was executed in 2017-2018, we built on the insights from the first survey and explored the role of AI in firms more deeply. What are the anticipated perceived business impacts of AI? AI can impact the internal operations of a firm, its offerings (in the form of smart products and services15), and how it interacts with its customers. The survey data largely con- firm this (Figure 3). The surveyed executives foresee AI to impact their firms’ offerings. More specifically, they foresee AI to impact the creation of smart ser- vices, to automate operations and manufacturing, to support decision-making and knowledge management, and to automate customer interfaces. Interestingly, the strength of the anticipated impacts does not vary too much (average range: 3.7-3.8 on a 5-point scale). This we interpret as the typical fairly undifferentiated perception by businesses of a new technology prior to wider and deeper diffusion and the emergence of standard business cases and applications.

Despite the largely undifferentiated perception of AI’s business impact— the perception of AI business impacts was also largely similar across countries and industries—some differences emerged. The impact on smart services is more

Figure 3. Anticipated DX/AI impacts on business (study 2).Note: n = 1,218 firms, worldwide, 2017-2018: “In terms of business impact of AI, to what extent will AI make an impact in each of following areas?”

Note: AI = artificial intelligence. *Knowledge management refers to decision-making and knowledge management support.

CALIFORNIA MANAGEMENT REVIEW 61(4) 116

pronounced in financial services and less in healthcare, and the impact on manu- facturing is more pronounced in the manufacturing sector. However, these signifi- cant differences only exhibited effects that are rather small.16

While, on average, AI’s anticipated business impact is seen as moderate to high across all the business impact categories investigated, 3% of the ratings anticipate no impact and 21% anticipate a high impact.17 What explains those differences?

Of the 10+ factors at the country, industry, firm, and executive (respon- dent) level we examined,18 only digital skills have a strong impact. Firms with stronger digital skills anticipate stronger AI-induced business impacts compared with firms with weaker digital skills. This observation is stable across industries and regions (see Figure 4).

These digital skills comprised four, interrelated organizational capabilities:

• Strategic capabilities: digital strategy and digital business development skills.

• Technology capabilities: skills in new digital technologies such as AI or IoT.

• Data capabilities: data science skills.

• Security capabilities: cybersecurity skills.

These results suggest that, just like with other technological innovations in the past, to realize the potential of the new digital technology, AI requires specific organizational capabilities as the firm and the new technology align for best appli- cation and impact.19 AI requires new information technology (IT) skills that are both AI-specific, such as machine learning skills, and generic, such as understand- ing of modern programming languages (e.g., Python), application development techniques (e.g., agile software development), and modern IT architecture skills (e.g., edge computing).20 In addition, data management and analytical skills are required. AI thrives on massive amounts of data requiring the existence of digital data, its management, and its analysis and synthesis. Given that most data are network generated (e.g., websites, sensor data from IoT devices), security skills— generic as well as AI-empowered—become vital to ensure access rights, intrusion detection, and data integrity.21 Last, these skills have to be embedded in a coher- ent and suitable strategic framework to ensure a guided implementation and wider organizational alignment and support.22

We find that firms that have already implemented and delivered business outcomes through three or more digital transformation projects (stage 4; see Figure 2) exhibit particularly strong digital capabilities.23 These firms we label digital transformation leaders (DX leaders for short); this group consists of about 8% of all firms surveyed.

Digital Transformation Leader Analysis

What makes these digital transformation (DX) leaders different? In order to find out, we compared them with those firms in our sample that either had

Demystifying AI: What Digital Transformation Leaders Can Teach You 117

no plans yet or were still in the planning phase (implementation stage 0 and 1; see Figure 2). We term these firms “laggards.” Following this classification, we compared 114 DX leaders with 424 laggards. We examined organizational traits

Figure 4. Anticipated business impact of AI and firms’ digital skills (a) across industry (study 2)a and (b) across regions (study 2)a.

Note: AI = artificial intelligence. aAnticipated business impact and digital skills based on separate summated scales, combining the individual impact and skills items.

CALIFORNIA MANAGEMENT REVIEW 61(4) 118

in the area of strategy, leadership, data management, agility, organizational pro- cesses, and innovation, as well as country-, industry-, and firm-level factors.

The DX leaders we identify came from across all countries surveyed and are as prevalent among traditional firms as among digital natives.24 They also did not differ significantly with regard to the reported duration from project start to busi- ness impact.25 The weak industry differences we observe are a reflection of the different extent of digital transformation initiatives in the industries surveyed, with financial services leading and healthcare lagging.26 With regard to traditional organizational measures (such as size in revenue or the number of employees), DX leaders tend to be larger. They report higher revenues and more employees, but these differences are not very pronounced.27 Besides their noted stronger digi- tal capabilities, we identify organizational characteristics where these leaders excelled.

Organizational Characteristics

When compared with laggards, DX leaders differ significantly and strongly28 in seven organizational traits. In order of size of the difference (effect size) between the two groups, these were integrated data management, CEO pri- ority, security strategy, digital processes, digital strategy, agility, and open innova- tion ecosystem.

Integrated data management, the most pronounced difference between lead- ers and laggards, refers to the organizational capability of managing customer and organizational data in a holistic and integrated fashion, avoiding data silos and incompatible data formats. This aspect goes hand in hand with AI’s dependence on data. CEO priority refers to a firm’s leader prioritizing and leading the firm’s digital transformation efforts, which include the application of advanced digital technologies such as AI. An organization-wide security strategy refers to the defini- tion and execution of a cybersecurity strategy across the whole organization. Given the importance of data, a strategic approach to data security—including the management of access rights, intrusion detection, and disaster recovery mecha- nisms—is critical. Digital processes refer to the digitalization of a firm’s core pro- cesses such as sourcing, production, performance reviews, or travel management and expense claims. Digital processes are often the outcome of digital transforma- tion projects. Organization-wide digital strategy refers to the development and exe- cution of a strategic approach to digital transformation, an approach that is contrasted to unplanned or tactical approaches. Organizational agility refers to a firm’s ability to rapidly and flexibly respond to customers’ needs, adapt produc- tion/service delivery to demand fluctuations, and implement decisions in the face of market changes. Agile organizations continuously search for ways to reinvent or redesign their organization and they can do so in a fast and flexible manner as they learn and adapt in the process. Innovation ecosystem refers to the establishment of an open ecosystem for innovation, beyond the boundaries of the firm. Such ecosystems tie into the resources, capabilities, and strength of a firm’s network of business relationships, such as ties with suppliers, alliance partners, and custom- ers (Figure 5).

Demystifying AI: What Digital Transformation Leaders Can Teach You 119

Business Impact

The seven organizational aspects enable the leaders to achieve much greater business impacts compared with laggards. Leaders report significantly stronger actual business impacts in their projects compared with laggards. We find significantly higher levels of impact on transformations of existing business models, improvements in operational efficiency, increase in revenue, strengthen- ing of offerings’ competitiveness, and customer experience enhancements. All of the observed differences are strong (see Figure 6). This moves beyond the mere anticipation of business impact (Figure 3) to managers’ perception of real busi- ness impacts actually achieved.

Challenges

Reflecting the importance of digital skills, the main challenge for all firms is lack of skilled staff and knowledge in digital technologies, which was men- tioned as an implementation challenge by more than half of the firms combined. Lack of organizational agility, internal resistance to change, security risks, lack of leadership and sufficient funding, as well as the challenge of integrating new digital technology with existing technology were stated as challenges by about a quarter of the firms each. Unavailability of suitable technology partners and

Figure 5. Organizational characteristics of DX leaders (study 2).

Note: n = 538 firms (114 leaders, 424 laggards), worldwide, 2017-2018: “To what extent do you agree with the following statements?” (from 1 = strongly agree to 5 = strongly disagree; statements randomly rotated): (1) Digital transformation is the top priority of our CEO; (2) We are executing an organization-wide digital transformation strategy; (3) We have achieved organizational agility; (4) We have established an open ecosys- tem for innovation; (5) We have digital business processes; (6) We are managing customer and organizational data in an integrated manner; (7) We are executing an organization-wide cybersecurity strategy. DX = digital transformation.

CALIFORNIA MANAGEMENT REVIEW 61(4) 120

unstable technology are mentioned as challenges by 19% and 13% of firms, respectively (Figure 7).

Contrary to our expectations, we uncover few differences in terms of chal- lenges perceived by leaders versus laggards. Only organizational agility, security risks, and lack of leadership were challenges that the leaders did perceive as less of a challenge in their AI projects. However, the effect of these differences was fairly small.29 We interpret this rather surprising finding as follows. Although the barri- ers or challenges that firms perceive are similar, the DX leaders have more experi- ence and a stronger resource base to overcome them. This becomes most obvious when looking at the three challenges the DX leaders perceived as significantly less of a challenge and comparing those with challenges that are perceived similar. For example, lack of leadership: DX leaders stated lack of leadership significantly less often as an implementation barrier compared with laggards. Given that DX lead- ers had significantly more CEOs prioritizing digital transformation, perceptions of lack of leadership support should be lower. On the contrary, both DX leaders and laggards perceive lack of skilled staff as a key barrier. This is despite the finding that DX leaders have a stronger digital skills resource base. Taken together, this points to the view that perceived challenges are similar, but that in some cases (e.g., lack of leadership), the DX leaders have already developed to a degree that the challenges are less of an actual implementation success barrier compared with the laggards.

Figure 6. DX/AI business impact (study 2).

Note: n = 538 firms (114 leaders, 424 laggards), worldwide, 2017-2018: “To what extent have you delivered outcomes specified in each of following statements?” (from 1 = not at all to 5 = to a great extent; statements randomly rotated): (1) Increase in revenue; (2) Improvement in customer experience; (3) Strengthening of competitiveness of products or services; (4) Efficiency improvements; (5) Improvement of business agility; (6) Transformation of business models. AI = artificial intelligence.

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Success Factors

In contrast to the implementation challenges, which were similar across the firms surveyed, leaders differed compared with laggards in terms of the importance they attributed to factors contributing to digital transformation out- come success. The following eight success factors turn out to be significantly dif- ferent among the AI leaders: organizational agility, engagement of skilled staff, leadership, support from technology partners, investment, culture, alignment of new digital technologies with existing IT, and learning from failed projects.

The biggest difference between the leaders and the laggards is organiza- tional agility. Leaders attribute much more importance to organizational agility as a factor of project success. Second, leaders have more engaged staff with the required digital skills and leadership support. Support from technology partners, sufficient funding, a supportive culture, alignment of new digital technologies with a firm’s existing technology, and learning from failure were also rated much higher as contributing factors of project success by the leaders as compared with the laggards (Figure 8).

Figure 7. DX/AI implementation challenges (study 2).

Note: n = 3,557 answers by 1,218 firms, worldwide, 2017-2018: “Which of the following statements describes your key challenges? Please select up to three” (categories randomly rotated): (1) Lack of skilled staff**; (2) Lack of knowledge of digital technology**; (3) Lack of organizational agility; (4) Lack of leadership; (5) Fear of change or internal resistance; (6) Unavailability of a right technology partner; (7) Lack of funds; (8) Integrat- ing digital technologies with existing IT; (9) Cybersecurity risks; (10) Adoption of digital technology too early, before it is robust and stable; (11) Others. AI = artificial intelligence; IT = information technology. **Combined in the figure.

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DIGITAL: Guidelines for Successful AI Applications

The present research departed from the tension between AI success sto- ries on one hand and failures and frustrations on the other hand. Based on our research, we now identify seven areas for managerial action and implementa- tion. We use the acronym “D-I-G-I-T-A-L” to describe our implications, where “D” stands for data, “I” for intelligence, “G” for grounded, “I” for integral, “T” for teaming, “A” for agile, and “L” for leadership. We explore these areas below. The more DIGITAL a company is, the higher the likelihood that their digital transformation–embedded AI projects will succeed. For easier comprehension, Figure 9 illustrates the links between the empirical evidence presented and the elements of the DIGITAL implementation framework. Some of the conclusions that we draw from our analyses, obviously, refer to other change projects within the digital transformation of companies as well. With DIGITAL, we also give credit to this notion and remind that implementation of AI, in its present con- dition, is typically linked to digital transformation of corporations in general. For each of the elements of DIGITAL, we provide managers with a few action- inducing discovery questions in order to guide their AI applications. Answering any of those questions with a clear “No” should alert managers to act accord- ingly (see Figure 9).

Figure 8. DX/AI success factors (study 2).

Note: n = 538 firms (114 leaders, 424 laggards), worldwide, 2017-2018: “To what extent have the following factors contributed to the overall outcomes you reported?” (from 1 = not at all to 5 = to a great extent; state- ments randomly rotated): (1) Engagement of skilled staff; (2) Having the right organization and processes; (3) Leadership by management; (4) Development of an enabling culture; (5) Support from technology partners; (6) Investment by the business; (7) Alignment of new digital technologies with existing IT; (8) Learning from failed projects. AI = artificial intelligence; IT = information technology.

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Data

Just like Dr. Mayol alluded to in his opening quote, the fundamental basis for AI success is data. AI requires data, digital data, and in high quality. The AI machine learning technique of deep learning is particularly data hungry. For

Figure 9. Proposed AI implementation success framework, empirical evidence, and action-inducing discovery questions.

Note: AI = artificial intelligence.

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example, Google needed some 10 million images to teach its Google brain sys- tem to identify human faces, human bodies, and cats.30 In a more recent appli- cation, the number of images used increased to 300 million images.31 Without data available for training, AI cannot create value for firms, and without skills to acquire, manage, and analyze the data, valuable and actionable insights cannot be generated. Our research confirms this. Firms with strong data capabilities are expecting to derive more value from AI, and our DX leader analysis showed that integrated data management practices and digital processes, which generate digi- tal data, separate the leaders from the laggards significantly and strongly.

Managers are, therefore, advised to start with a data inventory check before embarking on AI projects. The data inventory check should address questions such as “Do we own or have access to data that are relevant to analytically solve the business problem we are addressing?” “Are the data available in the right digi- tal format?” “Are the data sets sufficiently large to be efficient and effective?” “Are the data sufficiently complete, consistent, accurate, and timely?”

Be Intelligent

Data are the necessary foundation for AI success, but data alone are not sufficient. We identified lack of skilled staff and knowledge in digital technolo- gies as the top AI implementation challenge and engaged skilled staff as one of the key AI implementation success factors. Therefore, managers need to develop digital intelligence in the form of suitable human skills within their organization. This intelligence extends beyond the necessary data-related data science skills to include the strategic-, technological-, and security-related capabilities that we discussed earlier. In fact, AI requires organizations to develop human intel- ligence. How shall managers develop this intelligence, especially considering that AI-specific technical talent is scarce?32

First, it is important to realize that AI success is not just a function of tech- nical skills such as data science capabilities and skills in new digital technologies and cybersecurity. Managerial skills in the form of strategic capabilities are vital. Our results showed that firms with stronger capabilities in the area of digital strat- egies and digital business development skills are expecting to derive more value from AI compared with firms with a weaker skills base. At the heart of these managerial skills is awareness and understanding. This implies awareness of the possibilities and requirements of AI and related new digital technologies and an understanding of how to best leverage this technology in the idiosyncratic context of the firm. Questions such as “How can AI help defend, grow, or transform our business?” or “How can AI improve operational efficiencies?” are indicative. Answering such questions does not require an in-depth how-to technical under- standing of AI, but does require managerial curiosity and interest paired with firm, customer, and industry knowledge.

Second, the required technical AI skills need to be attained. In principle, managers have two options. Develop technical AI skills internally or acquire these skills from outside the firm. Interestingly, we found no difference in how leaders

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approached skills scarcity compared with laggards.33 We recommend a dual- sourcing strategy. Managers should develop existing internal skills and source external talent at the same time in order to build the necessary technical skill base to ensure efficient and effective application of AI technologies.

Finally, digital intelligence has to do with patience. AI is not an instant panacea. Our research unearthed rather lengthy, multiyear processes from project start to impactful execution. Just like the successful case that opened this article, AI projects are usually not deterministic from start to finish, but emerge as the project participants learn, and the system provides feedback. This also distinguishes AI projects from many other IT projects, where the end goal is the successful implementation and use of a system. Especially when embark- ing on an AI project for the first time, managers should allow the AI project team to experiment and provide them with a generous timeline to deliver results and sufficient funding, one of the main barriers we identified. This includes allowing for a “failure culture” as the team learns. DX leaders excelled at learning from failure and it helped them to reap more benefits from their AI projects.

In summary, managers are advised to start with an internal resources check before embarking on AI projects. This check should address questions such as “Do we have a digital strategy in place?” “Do we have the managerial and technical skills required to support successful digital transformation with AI? If not, how do we develop or acquire these skills?” “Are we willing and able to tolerate investing in an emerging rather than deterministic AI digital transformation journey, includ- ing accepting failure?”

Be Grounded

Following the insights derived from more than 7,000 projects world- wide, we conclude that firms are mainly applying the new digital technology to improve their existing business(es) (see Figure 3). The reported business impacts of the DX leaders also suggest a grounded approach with impacts such as improving the existing offering, increasing revenue, or enhancing operational efficiency (see Figure 6). Managers embarking on AI projects should take this insight as suggestive of a rather grounded approach to AI, at least initially. Rather than pursuing high-flying “pie-in-the-sky” projects, firms should “start small” with AI and base the project in their existing core business(es). Our opening case illustrated this: a focused application area and a relatively small project size. The setup allowed for early results, and the project setup was not made overly com- plicated. Again, this also points to the need for using AI for solving concrete busi- ness problems, rather than viewing it as radical innovation and business model disruption from the start—this may happen eventually, but later. AI, just as other technologies, is ultimately not about technology but business opportunities and capabilities. Only when enough experience has been accumulated should firms proceed to more difficult and complex projects involving innovation and new business models. This grounded approach also signifies that adopting AI is like adopting other new technology successfully. Start small, test, learn, and then

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apply more widely. As we noted earlier in this article, this suggests that realizing the potential of AI requires the firm and the new technology to co-align for best application and impact, and it rejects the notion of technological or organiza- tional imperatives.34

Before embarking on AI projects, managers should conduct a reality check in terms of scope and intent of the project(s). This check should address questions such as “Are we experienced enough and resourced properly for the scope of the project?” “Are we following an incremental, current business focused approach with our DX/AI project(s)?” “Do we have a DX/AI projects roadmap?”

Be Integral

Successful firm-wide AI implementations require an integral, holistic approach. Being integral comes in six flavors: strategy, processes, data manage- ment, technology alignment, employee engagement, and culture.

As soon as AI leaves the experimental, feasibility-testing lab environment and is applied to a real business case, managers should first make sure it is embed- ded in and supportive of the firms’ digital strategy. The existence of a digital strat- egy separated the DX leaders from the laggards and signals the importance of viewing AI in a broader context. A firm’s digital strategy, which, in essence, out- lines and documents how a firm wants to achieve its strategic objectives with the help of digital technologies—including but not exclusive to AI—channels its activ- ities and provides for a guiding purpose.

Executing a digital strategy implies the “digitalization” of a firm’s core processes: from procurement processes to internal operations to customer engagement.35 AI cannot augment analog processes. Managers should ask them- selves how digital their firms’ core processes are. Our DX leaders’ analysis showed that digital processes significantly and strongly distinguished them from laggards.

AI requires data. As firms digitize their operations, thereby creating more digital data, the need for an integrated data management approach becomes vital. It is, therefore, not surprising that integrated data management was the number one organizational characteristic differentiating DX leaders from lag- gards, because the mere existence of a lot of data is good but not good enough. Data, even if sufficiently large, complete, consistent, accurate, and timely, are limited if they “live” in isolation and are not connected with other relevant data. Subscribing to the view that firms are essentially consumers, producers, manag- ers, and distributors of information,36 all their data should be connected and integrated to allow for maximum value capture and knowledge generation. To address this challenging task, some innovative firms have recently started to set up so-called data lakes, a centralized repository that allows them to store all their structured and unstructured data and access in a unified way. As firms employ AI for more complex, broader tasks and processes (say, enhancing customer experi- ences), integrated data management becomes more important. Enhancing cus- tomer experiences, for example, requires tapping into data from the firm’s ERP (Enterprise Resource Planning), CRM (Customer Relationship Management),

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CMS (Content Management System), SMM (Social Media Monitoring), and other systems in order to ensure an integral approach to the customer journey.

Integrated data management requires technology alignment. Lack of it was one of the key barriers to AI success and successful alignment one of the key suc- cess factors we identified. Technology alignment specifically refers to the integra- tion of new digital technologies, including AI, with a firm’s existing technologies, and it is all about the question of whether the new and the old can “speak” together and “understand” each other in terms of data. For example, can the firm’s legacy system provide the data required for an AI application in a format that it can compute? Managers should ensure that technology alignment is looked after and instruct experts to ensure seamless integration of the old with the new.

Last, integral implies managers should ensure employee engagement and a supportive culture. Successful AI thrives with engaged skilled staff and an enabling culture, both of which help to overcome internal resistance and lack of skills and knowledge, two of the key barriers we identified. Engagement is particularly important for the employees that will be impacted by AI. As firms seem to be par- ticularly interested in applying AI in the creation of smart services (see Figure 3), for example, engaging and working with the service frontline employees will be instrumental to the success in smart services. Even though our research supports the augmentation view of AI, managers should be aware that frontline employees might fear displacement and should address this fear proactively. Research on how frontline employees’ roles, responsibilities, and actions are likely to change due to AI-automated customer interfaces is in its infancy, but it is safe to assume that managers who address such inherent concerns proactively are more likely to achieve employee engagement.

In conclusion, managers are advised to think about AI as a broad means to support its company-wide digital transformation efforts. To ensure an integral approach, managers should address questions such as “Have our firm’s core busi- ness processes been digitalized?” “Has our firm analyzed what existing/new offer- ings can benefit from DX/AI?” “Has our firm integrated all data into one single data repository?” “Is our firm’s existing IT compatible with the DX/AI technology we plan to adopt?”

Be Teaming

Our opening case illustrated that going for AI alone is unlikely to lead to success. Just as Dr. Mayol and his colleagues collaborated with a technol- ogy adviser and provider, DX leaders stated support by technology partners as a key success factor, and the unavailability of support by a technology partner was stated as an implementation challenge by nearly 20% of firms. Teaming with one or several technology partners—which include technology generalists such as IBM or Fujitsu, software firms such as Microsoft or SAP, or consultancies such as Accenture or Deloitte37—provides firms with two main advantages. First, it provides them with early access to new technology in a field that is still ill- defined and emergent. Second, it allows them to tap into the economies of scope

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and project experiences that both technology firms and technology consultancies have accumulated over the past years as AI projects have mushroomed. For most firms, AI will, for the foreseeable future, not be an off-the-shelf product. Hence, teaming with technology partners to co-create a tailored AI solution is going to be the main approach for now.

The importance of teaming extends beyond the confines of working with technology partners and includes a firm’s business ecosystem,38 which includes suppliers, competitors, customers, and alliance partners from different industries. Having established an open innovation ecosystem was one of the organizational characteristics that set the DX leaders apart from the laggards. Open innovation ecosystems are a means to develop innovative offerings (products and services) beyond the internal capacity and capabilities of the firms. This approach recog- nizes that great talent often resides outside of a firm. Given the discussed AI tech- nical skills scarcity, an open innovation ecosystems approach is particularly fruitful in the case of AI, and the DX leaders demonstrated this. Having established an Open Innovation Ecosystem was one of their defining characteristics. Generally, managers have two options: establishing their own ecosystem39 or joining an existing one.40 Often, as was the case with Dr. Mayol and his colleagues, the route to take is shaped by the nature of the collaboration with the technology partner(s).

Managers are advised to think about AI as an opportunity to partner and develop powerful ecosystems. To understand the teaming options, managers should address questions such as “Does our firm know with whom to partner in support of our DX/AI success?” “Does our firm know with whom competitors partner in their DX/AI projects?” “Did our firm develop or join an ecosystem to enhance its offerings?”

Be Agile

Organizational agility is both a key barrier and a key success factor accord- ing to our empirical analyses. Lack of it was the second most important AI imple- mentation challenge, and great levels of organizational agility was the number one AI success factor. We found agility to also be one of the main business impacts of AI. Agility is, therefore, both a central AI success antecedent as well as an outcome of successful AI implementations, thereby reinforcing its importance as an antecedent. How can managers foster organizational agility? Organizational agility research suggests that a firm’s ability to sense change and to respond read- ily to it by reconfiguring its resources, processes, and strategies is at the core of organizational agility.41 In the context of AI projects, this relates to flexibility in the way the project is approached and managed throughout its life cycle, as AI projects tend to be emergent rather than deterministic, as we noted earlier (cf. Be Intelligent).

Managers are advised to assess their company’s agility in a realistic manner and implement corrective actions if needed. The following questions, guided by the logic of Singh et al.,42 are instructive: “Compared to our competition, how quickly and frequently are we adapting our processes and offerings to stay

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competitive?” “Compared to our competition, how flexible are we to accommo- dating small, medium, and large changes to our processes and offerings?”

Lead

Managers should lead and actively endorse the firm’s AI project(s), just like Dr. Mayol at the Carlos Clinical Hospital in Madrid, and not relegate leader- ship to the project management level. We identified executive leadership as a key success factor and lack of leadership support as a key barrier. The DX leaders we analyzed demonstrated this fact forcefully. One of their defining organiza- tional characteristics was a CEO who prioritized the firm’s digitalization efforts, including AI and other advanced digital technologies.

If data are the foundation for impactful AI, leadership provides the trans- formational energy for firms to be DIGITAL and, as a consequence, successful with AI. Notably, AI has several similarities with other technologies to be implemented in firms, and some of the aspects of our DIGITAL framework would relate to other change management projects as well. However, the broad nature of AI (requiring data, analyses, interdisciplinary teams) makes for some specific requirements, such as data, agility, and the teaming aspect.

Managers are advised to reflect honestly, “Is our executive team and mid- dle management comfortable and supportive of the changes that DX/AI will bring to our firm?” “Is our executive team and middle management actively endorsing and continuously communicating the status and progress of our DX/AI activities to all stakeholders?”

Conclusion and Outlook

AI certainly holds a lot of promise but it is not a panacea. In order to reap its benefits, we developed DIGITAL as a guideline for AI success grounded in the empirical insights of close to 7,000 DX projects that involved new digital technol- ogies such as AI. The basic approach of this article was to learn from today’s DX leader how to become the AI leader of tomorrow. At the same time, in line with the title of this article, we believe we can demystify a few aspects of AI.

The results of this study imply that, in many ways, AI is similar to other technologies companies adopt and implement. It certainly is typically deployed in digital transformation projects, and, as such, shares many similarities with other digital projects. At the same time, the focus on self-learning projects and long-run scaling comes with several interesting findings, such as the focus being integral, teaming, and agile. In contrast to press reports and also some academic papers, our approach to AI is a contemporary and realistic one. Before visions of “AI tak- ing over everything” will become true, “realistic AI” will take place for a long time. It is and will be a competitive advantage to be quick and effective in AI, and our DIGITAL framework and the associated questions to managers should help overcome the barriers, but also some of the illusions, so that “realistic AI” will become real.

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A question that we also addressed in the survey was the future role of humans in AI projects, which we do not report here in detail due to the contro- versial and nonconclusive nature of the responses, and the vastness of the topic. But overall, it is interesting that firms are positive about AI as a technology and the role of humans. First, they expect that AI and humans will work together in the future, rather than working against each other or replacing humans, for at least quite some time. Furthermore, managers assume that we will even see a human premium emerging in the future, in the sense that people will be paying more to get personal, human-to-human services rather than AI technology– mediated services. Interestingly, leaders and laggards are united in this view and showed no significant differences.

Acknowledgments

The authors wish to thank Fujitsu, Corporate Executive Officer and former Chief Marketing Officer Yoshiteru Yamada, and Manager Noriaki Tanaka for support- ing the research project.

Author Biographies

Jürgen Kai-Uwe Brock is the former CMO of Fujitsu Americas, currently work- ing as a senior assignee at Fujitsu’s HQ in Tokyo, Japan (email: brock.Juergen@ fujitsu.com).

Florian von Wangenheim is Professor of Technology Marketing, Department of Management, Technology, and Economics at ETH Zurich (email: fwangenheim@ ethz.ch).

Notes 1. For details regarding this case, see Instituto de Investigation Sanitaria Case Study (IdISSC),

https://www.youtube.com/watch?v=NIDNmwYMjAE. 2. At present, to the best of our knowledge, no commonly agreed definition of artificial intel-

ligence (AI) exists. Definitions range from “every aspect of learning or any other feature of intelligence . . . that a machine can be made to simulate” [John McCarthy, M.L. Minski, N. Rochester, and C.E. Shannon, “A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence,” August 31, 1955, www-formal.stanford.edu/jmc/history/dartmouth. pdf] to “make computers do things at which, at the moment, people are better” [Elaine Rich and Kevin Knight, Artificial Intelligence, 3rd ed. (New York, NY: McGraw-Hill, 2009)] to “AI is whatever hasn’t been done yet” [Douglas Hofstadter, Gödel, Escher, Bach: An Eternal Golden Braid (New York, NY: Basic Books, 1980)] to, more recently, “a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve spe- cific goals and tasks through flexible adaptation” [Andreas Kaplan and Michael Haenlein “Siri, Siri, in My Hand: Who’s the Fairest in the Land? On the Interpretations, Illustrations, and Implications of Artificial Intelligence,” Business Horizons 62/1 (January/February 2019): 15-25]. Given this, we purposely did not provide for an explicit definition of AI in our sur- vey research. However, we provided application examples in the survey as illustrations of AI, such as call center transformation using advanced analytics and AI or transforming opera- tions using Internet of things (IoT), advanced analytics, and AI. Generally, our investigation was guided by the broad and inclusive behavioral definition of AI as originally advanced by Brooks: “Artificial Intelligence . . . is intended to make computers do things, that when done by people, are described as having indicated intelligence” (Rodney Allen Brooks, “Intelligence

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without Reason,” in Proceedings of the 12th International Joint Conference on Artificial Intelligence, ed. M. Ray and J. Reiter (Sydney, Australia: Morgan Kaufmann, 1991), pp. 569-595.

3. See, for example, Kartik Hosanagar and Apoorv Saxena, “The First Wave of Corporate AI Is Doomed to Fail,” Harvard Business Review Digital Articles, April 18, 2017, https://hbr .org/2017/04/the-first-wave-of-corporate-ai-is-doomed-to-fail; Ben Taylor, “Why Most AI Projects Fail,” Artificial Intelligence, March 1, 2018, https://www.experfy.com/blog/why -most-ai-projects-fail; Matthew Herper, “MD Anderson Benches IBM Watson in Setback for Artificial Intelligence in Medicine,” Forbes, February 19, 2017, https://www.forbes.com/sites /matthewherper/2017/02/19/md-anderson-benches-ibm-watson-in-setback-for-artificial -intelligence-in-medicine/#10c16c083774.

4. See, for example, Sam Ransbotham, David Kiron, Philipp Gerbert, and Martin Reeves, “Reshaping Business with Artificial Intelligence: Closing the Gap between Ambition and Action,” MIT Sloan Management Review, September 6, 2017, https://sloanreview.mit.edu /projects/reshaping-business-with-artificial-intelligence.

5. See, for example, Richard Waters, “Why We Are in Danger of Overestimating AI,” Financial Times, February 4, 2018, https://www.ft.com/content/4367e34e-db72-11e7-9504-59efdb70e12f.

6. Some of these cases are publicly accessible, examples include the following: https:// www.fujitsu.com/global/about/resources/case-studies/cs-2017nov-siemens-gamesa .html; https://www.youtube.com/watch?v=tpkQHlutSzo; https://www.youtube.com/watch ?v=3Lqq6bjoip0.

7. This group of areas of AI business impact follows the logic of John Hagel III and Marc Singer, “Unbundling the Corporation,” Harvard Business Review, 77/2 (March/April 1999): 133-141 (see Figure 1). The authors argued that most companies are essentially three kinds of busi- nesses—a customer relationship business (customer interactions), a product innovation busi- ness (offerings), and an infrastructure business (operations).

8. This research question was guided by the thinking behind the theory of the growth of the firm (Penrose), which attributes a key role to experiential knowledge. Edith T. Penrose, The Theory of the Growth of the Firm (London: Wiley, 1959).

9. Hagel and Singer (1999), op. cit. 10. The term Triad refers to the three key economic regions in the world (originally, the United

States, Europe, and Japan) as originally coined by Ohmae [Kenichi Ohmae, Triad Power: The Coming Shape of Global Competition (New York, NY: Free Press, 1985)], though its modern understanding has broadened [e.g., Alan M. Rugman and Alain Verbeke, “A Perspective on Regional and Global Strategies of Multinational Enterprises,” Journal of International Business Studies, 35/1 (2004): 3-18] to include North America, Asia, and Oceania.

11. J. Scott Armstrong and Terry S. Overton, “Estimating Non-response Bias in Mail Surveys,” Journal of Marketing Research, 14/3 (1977): 396-402. Armstrong and Overton suggest compar- ing early and late respondents for differences along key control variables, assuming that late respondents are more similar to nonrespondents. If no significant differences can be found, one can assume no significant response bias exists. We used the time stamps of the online surveys to gauge possible differences but found none.

12. We derived the marker variable approach from Michael K. Lindell and David J. Whitney, “Accounting for Common Method Variance in Cross-selectional Research Designs,” Journal of Applied Psychology, 86/1 (2001): 114-121. We compared the reported overall business impact of AI (see Figure 4a and 4b) with a theoretically unrelated measure added to the survey. The measure used concerned firms’ United Nations Sustainable Development Goals focus. The two were unrelated (r = –.046; R2 = .003), suggesting common method bias is not a major concern in our study.

13. Sample details of the first survey, conducted in 2016-2017: Total sample size: n = 1,614 (firms). Regions: North Americas (Canada, United States) n = 314; Europe (Finland, France,

Germany, Spain, Sweden, United Kingdom) n = 520; Asia (China, Indonesia, Japan, Singapore, South Korea, Thailand) n = 674; Oceania (Australia) n = 106.

Industry split, North American Industry Classification System (NAICS) code: 23, 31-33, Manufacturing (n = 427); 51, Information (n = 195); 48-49, Transportation (n = 56); 41/42, 44-45, Retail (n = 137); 52, Financial Services (n = 138); 62, Healthcare (n = 100), other (n = 661).

Firm size (employees): <100 full-time employees (FTEs; n = 0); 100-499 (n = 499); 500- 999 (n = 414); 1,000-4,999 (n = 440); 5,000+ (n = 261).

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Firm size (revenue): <1M$ (n = 4); 1-10M$ (n = 182), 10-100M$ (n = 581); 100-1Bn$ (n = 561); 1Bn$+ (n = 263).

Respondent characteristics: Gender: Female (24%), Male (76%). Age: 20s (n = 147), 30s (n = 515), 40s (n = 418), 50s (n = 303), 60s (n = 161). Position: C-suite (n = 1,023), × VP-level (n = 591), Manager (n = 0). Sample details of the second survey, conducted in 2017-2018: Total sample size: n = 1,535 (firms). Regions: North Americas (Canada, United States) n = 137; Europe (Finland, France,

Germany, Spain, Sweden, United Kingdom) n = 502; Asia (China, Indonesia, Japan, Singapore, South Korea, Thailand) n = 473; Oceania (Australia, New Zealand) n = 106.

Industry split, NAICS code: 31-33, Manufacturing (n = 280); 51, Information (n = 93); 48-49, Transportation (n = 83); 41/42, 44-45, Retail (n = 472); 52, Financial Services (n = 158); 62, Healthcare (n = 132), other (n = 0).

Firm size (employees): <100 FTEs (n = 9); 100-499 (n = 309); 500-999 (n = 348); 1,000- 4,999 (n = 357); 5,000+ (n = 195).

Firm size (revenue): <1M$ (n = 9); 1-10M$ (n = 157), 10-100M$ (n = 425); 100-1Bn$ (n = 406); 1Bn$+ (n = 205).

Respondent characteristics: Gender: Female (35%), Male (65%). Age: 20s (n = 173), 30s (n = 474), 40s (n = 332), 50s (n = 171), 60s (n = 68). Position: C-suite (n = 931) × VP-level (n = 262), Manager (n = 25). 14. Other technologies used were, for example, security technologies, mobile technologies,

blockchain, cloud computing, IoT, and big data analytics. The definition for digital transfor- mation used was “Digital transformation refers to the integration of advanced digital tech- nologies (AI, IoT, and cloud-based services) into significant areas of a business with the aim of changing how the business operates and how value is delivered to and created with customers.”

15. For details on smart offerings, see, for example, Michael E. Porter and James E. Heppelmann, “How Smart, Connected Products Are Transforming Companies,” Harvard Business Review, 93/10 (October 2015): 96-114.

16. The effect size for smart services was Cohen’s f = .121, and for manufacturing automation Cohen’s f = .142.

17. The numerical difference in the range of firms is a reflection of missing values. 18. Factors examined include industry sector, country, firm characteristics (revenue, number of

employees, digital/traditional), and respondent characteristics (gender, age, title/position). 19. In the information technology (IT) literature, this co-evolutionary view is referred to as the

emergent imperative. M. Lynne Markus and Daniel Robey, “Information Technology and Organizational Change: Causal Structure in Theory and Research,” Management Science, 34/5 (May 1988): 583-598.

20. We derived this insight from digital transformation projects involving AI of one of the author’s employers, a global provider of IT services, practitioner interviews, and the litera- ture, such as Amir Sharif, “Harnessing Agile Concepts for the Development of Intelligent Systems,” New Generation Computing, 17/4 (December 1999): 369-380; Antonio Gulli, TensorFlow 1.x Deep Learning Cookbook: Over 90 Unique Recipes to Solve Artificial-intelligence Driven Problems with Python (Birmingham, UK: Packt Publishing, 2017); Nicolas Seydoux, Khalil Drira, Nathalie Hernandez, and Thierry Monteil, “Reasoning on the Edge or in the Cloud?” Internet Technology Letters 2/1 (January/February 2018): e51.

21. See, for example, Jian-hua Li, “Cyber Security Meets Artificial Intelligence: A Survey,” Frontiers of Information Technology & Electronic Engineering, 19/12 (December 2018): 1462-1474.

22. See, for example, Francisco J. Mata, William L. Fuerst, and Jay B. Barney, “Information Technology and Sustained Competitive Advantage: A Resource-based Analysis,” MIS Quarterly, 19/4 (December 1995): 487-505; Ferdinand Mahr, Aligning Information Technology, Organization, and Strategy: Effects on Firm Performance (Wiesbaden: Gabler, 2010).

23. Obviously, given the cross-sectional nature of our survey, we cannot claim any causal links here. AI leaders might exhibit stronger digital skills as a result of their digital transformation efforts, and/or their stronger digital skills resulted in more advanced digital transformation efforts compared with the other firms.

Demystifying AI: What Digital Transformation Leaders Can Teach You 133

24. We defined digital natives as firms that were less than 15 years old at the time of the survey and marketing their offerings (products and services) purely online. The survey included a total of n = 648 digital natives.

25. For the majority of firms (61%), it took one or more years before outcomes could be deliv- ered. For 23% of firms, it took two or more years, and for 9%, three or more years.

26. Small effect size for industry, Cramer’s V = .037. 27. Small effect size for revenue, Cramer’s V = .054, and for employees, Cramer’s V = .071. 28. Throughout our DX leader analysis, we report both statistical significance and effect sizes.

Effect sizes are estimates of the strength of an effect in a given population. Especially when sample sizes are large, like in our studies, inferential tests become oversensitive and even the smallest of effects turn out to be statistically significant. In such cases, statistical sig- nificance is actually insignificant and what matters more is the found effect size. Cf. Jürgen Kai-Uwe Brock, “The ‘Power’ of International Business Research,” Journal of International Business Studies, 34/1 (January 2003): 90-99. As we display in Figures 5, 6, and 8, the effects we found are medium to large according to Cohen’s effect size classification. Jacob Cohen, Statistical Power Analysis for the Behavioral Sciences, 2nd ed. (Hillsdale, NJ: Lawrence Erlbaum, 1988). Compared with other studies in the field of international business and organization research (we use the effect size reviews of Ellis (2010) and Paterson et al. (2015) as bench- marks and visualized the average effect sizes they found in Figures 5, 6, and 8), the effects we found were stronger for all but one effect, indicating substantial practical relevance for managers. Paul D. Ellis, The Essential Guide to Effect Sizes: Statistical Power, Meta-Analysis, and the Interpretation of Research Results (Cambridge: Cambridge University Press, 2010); T.A. Paterson, P.D. Harms, P. Steel, and M. Credé, “An Assessment of the Magnitude of Effect Sizes: Evidence From 30 Years of Meta-Analysis in Management,” Journal of Leadership & Organizational Studies, 23/1 (February 2016): 66-81.

29. The found effect sizes were ϕ = .086, ϕ = .093, and ϕ = .077, respectively. 30. Nicola Jones, “Computer Science: The Learning Machines,” Nature, 505/7482 (January 8,

2014): 146-148. 31. Chen Sun, Abhinav Shrivastava, Saurabh Singh, and Abhinav Gupta, “Revisiting

Unreasonable Effectiveness of Data in Deep Learning Era,” arXiv:1707.02968, July 2017. 32. See, for example, David Cyranoski, “China Enters the Battle for AI Talent,” Nature, 553/7688

(January 17, 2018): 260-261. 33. 51% of DX leaders developed skills internally, and 49% sourced skills externally versus 52%

and 48% for laggards; χ2 value = .011, p value = .915 in a 2 × 2 table. 34. As discussed by Markus and Robey, the technological imperative implies that technology

is an exogenous force, which deterministically shapes organizations and people. M. Lynne Markus and Daniel Robey, “Information Technology and Organizational Change: Causal Structure in Theory and Research,” Management Science, 34/5 (May 1988): 583-598. The organizational imperative, in contrast, argues that organizations and people have almost unlimited choice over technological options and control over its consequences. As illustrated in our opening case, successful applications of AI in organizations are neither following the technological imperative nor the organizational imperative, but the emergent imperative, which holds that the uses and consequences of a technology in an organization cannot ex ante be fully determined but emerge from complex social interactions within the firm and its ecosystem.

35. See, for example, Gerrit Berghaus, René Kessler, Viktor Dmitriyev, and Jorge Marx Gómez, “Evaluation of the Digitization Potentials of Non-digital Business Processes,” HMD Praxis der Wirtschaftsinformatik, 55/2 (April 2018): 42c444.

36. See, for example, Kenneth J. Arrow, The Limits of Organization (New York, NY: W.W. Norton, 1974); Arthur L. Stinchcombe, Information and Organizations (Berkeley: University of California Press, 1990).

37. The main technology partners our research identified were, in alphabetical order: Accenture, Amazon, Capgemini, Cisco, Dell, Deloitte, Fujitsu, Google, Hewlett Packard Enterprise (HPE), Hitachi, IBM, Microsoft, NEC, NTT Data, Oracle, PwC, SAP, Salesforce, and TCS (Tata Consultancy Services).

38. The view of a business ecosystem goes back to Moore, who argued that “a company be viewed not as a member of a single industry but as part of a business ecosystem that crosses a variety of industries. In a business ecosystem, companies coevolve capabilities around a new innovation: they work cooperatively and competitively to support new products, satisfy

CALIFORNIA MANAGEMENT REVIEW 61(4) 134

customer needs, and eventually incorporate the next round of innovations.” James F. Moore, “Predators and Prey: A New Ecology of Competition,” Harvard Business Review, 71/3 (May/ June 1993): 75-86.

39. See, for example, Henry Chesbrough, Sohyeong Kim, and Alice Agogino, “Chez Panisse: Building an Open Innovation Ecosystem,” California Management Review, 56/4 (Summer 2014): 144-171; René Rohrbeck, Katharina Hölzle, and Hans Georg Gemünden, “Opening Up for Competitive Advantage—How Deutsche Telekom Creates an Open Innovation Ecosystem,” R&D Management, 39/4 (September 2009): 420-430.

40. For the open innovation dimension of business ecosystems, see Henry W. Chesbrough, Open Innovation: The New Imperative for Creating and Profiting from Technology (Boston, MA: Harvard Business School Press, 2003).

41. See, for example, Carmen M. Felipe, José L. Roldán, and Antonio L. Leal-Rodríguez, “An Explanatory and Predictive Model for Organizational Agility,” Journal of Business Research, 69/10 (October 2016): 4624-4631.

42. Jagdip Singh, Garima Sharma, James Hill, and Andrew Schnackenberg, “Organizational Agility: What It Is, What It Is Not, and Why It Matters,” Academy of Management Proceedings, 2013/1 (2013): 11813-11813.

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Journal of General Management Vol. 26 No.2 Winter 2000

A Reappraisal ofHRM Models in Britain by Pawan s. Budhwar

Human Resource Management is still struggling to find a strategic role.

For a better understanding ofthe subj ect, both management practitioners and scholars need to study human resource management (HRM) in context [1]. The dynamics of both the local/regional and international/ global business context in which the firm operates should be given a serious consideration. Similarly, there is a need to use multiple levels of analysis when studying HRM: the external social, political, cultural, and economic environment; and the industry. Examining HRM out-of-context could be misleading and fail to advance understanding. A key question is how to examine HRM in context? One way is by examining the main models of HRM in different settings. However, there is no existing framework that can enable such an evaluation to take place. An attempt has been made in this paper to provide such a framework and empirically examine it in the British context.

This paper is divided into three parts. Initially, it summarises the main developments in the field of HRM. Then, it highlights the key emphasis of five models of HRM (namely, the 'Matching model'; the 'Harvard model'; the 'Contextual model'; the '5-P model'; and the 'European model' ofHRM). Lastly, we will address the operationalisation of the key issues and emphases of the aforementioned models by examining their applicability in six industries ofthe British manufacturing sector. The evaluation highlights the context specific nature of British HRM.

This introduction looks at the need to identify the core emphasis of the main HRM models that could be used to examine their applicability in different national contexts. Developments in the field of HRM are now well documented in the literature [2, 3]. The debate relating to the nature ofHRM continues today, although the focus of the debate has changed over a period of time. At present, the contribution ofHRM in improving

Pawan S. Budhwar is Lecturer in Organizational Behaviour and HRM at CardiffBusiness School, UK.

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the firm's performance and the overall success of any organization (alongside other factors) is being highlighted in the literature [4, 5].

Alongside these debates, a number of important theoretical developments have taken place in the field of HRM. For example, a number ofmodels ofHRM have been developed over the last 15 years or so. Some of the main models are: the 'Matching model'; the 'Harvard model'; the 'Contextual model'; the '5-P model'; and the 'European model' ofHRM [6, 7]. All these models have been developed in the US and the UK. These models ofHRM are proj ected to be useful for analysis both between and within nations. However, the developers of these models do not provide clear guidelines regarding their operationalisation in different contexts. Moreover, it is interesting to note that, although a large number of scholars refer to these models, very few have tested their practical applicability (exceptions being Benkhoff [8]; Monks [9]; Truss et al. [10]). For the development of relevant management practices there is then a clear need not only to highlight the main emphasis of the HRM models but also to show their operationalisation. Such an analysis will help to examine the applicability of these models in other parts of the world. With the increasing levels ofglobalisation ofbusiness such investigations have become an imperative.

Moreover, although the present literature shows an emphasis on themes such as 'strategic HRM' (SHRM), the majority of researchers persist in examining only the traditional 'hard' and' soft' models ofHRM [11]. For the growth and development of SHRM, there is a strong need to examine the applicability of those models ofHRM which can help to assess the extent to which it has really become strategic in different parts of the world, and the main factors and variables which determine HRM in different settings. This will not only test the applicability of HRM approaches in different regions, but will also help to highlight the context specific nature of HRM practices.

The aims of this paper are twofold. First, to identify the core emphasis offive main models ofHRM which can be used to examine their applicability in different national contexts. Second, to test empirically the applicability of these models of HRM in the British context. Before answering why this investigation is being conducted in the UK, the main models of HRM are briefly analysed.

Models of HRM

Five models ofHRM, which are widely documented in the literature are chosen for analysis. They are: the 'Matching model'; the 'Harvard model'; the 'Contextual model'; the '5-P model'; and the 'European model' ofHRM [12,13, 14]. The reason for the selection and analysis of thesemodelsis two-fold.First, it will help to highlight their main contribution

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to the development of SHRM as a distinct discipline. Second, it will help to identify the main research questions suitable for examining these models in different national settings. The analysis begins with one of the traditional models ofHRM.

The strategic fit of HRM

The main contributors to the 'Matching model' ofHRM come from the Michigan and New York schools. Fombrun et al. 's [15] model highlights the 'resource' aspect ofHRM and emphasises the efficient utilisation of human resources (like otherresources) to meet organizational objectives. The matching model is mainly based on Chandler's [16] argument that an organization's structure is an outcome of its strategy. Fombrun et al. expanded this premise and developed the matching model of strategic RRM, which emphasises a 'tight fit' between organizational strategy, organizational structure and HRM system, where both structure and HRM are dependent on the organization strategy. The main aim of the matching model is therefore to develop an appropriate 'Human Resource System' that will characterise those HRM strategies that contribute to the most efficient implementation ofbusiness strategies. The Schuler group made further developments to the matching model and its core theme of 'strategic fit' in the late 19?Os [17]. The core issues emerging from the matching models are:

1. Do organizations show a 'tight fit' between their HRM and organization strategy where the former is dependent on the latter? Do personnellHR managers believe they should develop HRM systems only for the effective implementation of their organization strategies?

.2. Do organizations consider their HRs as a cost and use them sparingly? Or, do they devote resources to the training of their HRs to make the best use of them?

3. Do HRM strategies vary across different levels of employees?

The soft variant of HRM

Beer et al. [18] articulated the 'Harvard Model' of HRM. It is also denoted as the 'Soft' variant ofHRM [19], mainly because it stresses the 'human' aspect of HRM and is more concerned with the employer- employee relationship. The model highlights the interests of different stakeholders in the organization (such as shareholders, management, employee groups, government, community and unions) and how their interests are related to the objectives of management. It also recognises the influence ofsituational factors (such as the market situation) on HRM policy choices. According to this model, the actual content of HRM is described in relation to four policy areas i.e. human resource flows,

Journal of General Management Vol. 26 No.2 Winter 2000

reward systems, employees' influence and work systems. Each of the four policy areas is characterised by a series of tasks to which managers must attend. The outcomes that these four HR policies need to achieve are commitment, competence, congruence, and cost effectiveness. The model allows for analysis of these outcomes at both organizational and societal levels. As this model acknowledges the role ofsocietal outcomes, it can provide a useful basis for comparative analysis of HRM [20]. The key issues emerging from this model which can be used for examining its applicability in different contexts are:

1. What is the influence ofdifferent stakeholders and situational and contingent variables on HRM policies?

2. To what extent is communication with employees used as a means to maximise commitment?

3. What level of emphasis is given to employee development through involvement, empowerment and devolution?

The contextual model of HRM

Researchers at the Centre for Corporate Strategy and Change at the Warwick Business School developed this model. They examined strategy making in complex organizations and related this to the ability to transform HRM practices [21,22]. Hendry and associates argue that HRM should not be labelled as a single form of activity. Organizations may follow a number of different pathways in order to achieve the same results. This is mainly due to the existence of a number of linkages between the outer environmental context (socio-economic, technological, political-legal and competitive)and inner organizationalcontext (culture, structure, leadership, task-technology and business output). These linkages directly contribute to forming the content of an organization's HRM. The core issues emerging from this model are:

1. What is the influence of economic (competitive conditions, ownership and control, organization size and structure, organizational growth path or stage in the life cycle and the structure of the industry), technological (type of production systems) and socio-political (national education and training set-up) factors on HRM strategies?

2. What are the linkages between organizational contingencies (such as size, nature, positioning ofHR, and HR strategies) and HRM strategies?

Strategic integration of HRM

The existing literature reveals a trend in which HRM is becoming an integral part of business strategy - hence, the emergence of the term SHRM. It is largely concerned with 'integration' and 'adaptation'. The purpose of SHRM is to ensure that [23]:

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1. HRM is fully integrated with the strategy and strategic needs of the firm;

2. HR policies are coherent both across policy areas and across hierarchies; and

3. HR practices are adjusted, accepted, and used by line managers and employees as part of their every day work.

Based on such premises, Schuler [24] developed a 5-P model of SHRM that melds five HR activities (philosophies, policies, programs, practices and processes) with strategic needs. This model, to a great extent, explains the significance ofthese five SHRM activities in achieving the organization's strategic needs, and shows the inter-relatedness of activities that are often treated separately in the literature. This is helpful in understanding the complex interaction between organizational strategy and SHRM activities.

The model raises two important issues (also suggested by many other authors in the field) for SHRM comparisons. These are:

1. What is the level of integration of HRM into the business strategy?

2. What is the level ofresponsibility for HRM devolved to line managers?

European model of HRM

Based on the growing importance of HRM and its contribution towards economic success and the drive towards Europeanisation, Brewster [25] proposes a 'European model ofHRM'. His model is based on the premise that European organizations operate with restricted autonomy. They are constrained at both the international (European Union) and national levels by national culture and legislation, at the organization level by patterns of ownership, and at the HRM level by trade union involvement and consultative arrangements [26, p. 3]. Brewster suggests the need to accommodate such constraints when forming a model ofHRM. He also talks about 'outer' (legalistic framework, vocational training programs, social security provisions and the ownership patterns) and 'internal' (such as union influence and employee involvement in decision making) constraints on HRM. Based on such constraints, Brewster's model highlights the influence of factors such as national culture, ownership structures, the role of the state and trade unions on HRM, in different national settings.

The European model shows an interaction between HR strategies, business strategy and HR practice and their interaction with an external environment constituting national culture, power systems, legislation, education, employee representation and the constraints previously mentioned. It places HR strategies in close interaction with the relevant

Journal of General Management Vol. 26 No.2 Winter 2000

organizational strategy and external environment. One important aim of this model is to show factors external to the organization as a part of the HRM model, rather than as a set of external influences upon it.

From the above analyses, it can be seen that there is an element of both the contextual and 5-P models of HRM present in Brewster's European model. Apart from the emphasis on 'strategic HRM', one main issue important for cross-national HRM comparisons emerges from Brewster's model. This is:

• What is the influence of international institutions, national factors (such as culture, legal set up, economic environment and ownership patterns), and national institutions (such as the educational and vocational set-up, labour markets and trade unions) on HRM strategies and HRM practices?

Recently, Budhwar and associates [27, 28,29,30] have proposed a framework for examining cross-national HRM. They have identified three levels of factors and variables that are known to influence HRM policies and practices and which are worth considering for cross-national HRM examinations. These are national factors (such as national culture, national institutions, business sectors and dynamic of the business environment), contingent variables (such as the age, size, nature, ownership, and life cycle stage of the organization, the presence of trade unions and HR strategies, and the interests of different stakeholders) and organizational strategies and policies (related to primary HR functions, internal labour markets, levels ofintegration and devolvement, and nature ofwork). This framework is used to examine the applicability ofthe issues arising from the five HRM models in British organizations. But why conduct this form of investigation, and in the British context?

As mentioned already, there is a scarcity of this type of research. So far, only Truss et al. [31] have examined the applicability of some of the models of HRM in a few UK case companies. Apart from their research, there is scarcely any study that conducts the type ofinvestigation described here. There are, then, two main reasons for conducting this investigation in British companies. First, a UK sample possesses the characteristics suitable to test the operationalisation ofthe main emphases and critical issues ofthe five models ofHRM. Second, the HRM function in the UK is under intense pressure due to competitive conditions, and the restructuring and rightsizing programmes going on in British organizations, as well as the pressure on British firms from EU and other international players to stay competitive and meet the EU regulation regarding the management ofhuman resources. In such dynamic business conditions it is worth examining the HRM function in context. Moreover, since the five models have been developed among Anglo-Saxon nations, it is sensible to test them initially in these countries before recommending their testing in others parts of the world.

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The Research Methodology

Sample and data collection

A mixed methodology, using a questionnaire survey and in-depth interviews, was adopted. During the first phase of the research, a questionnaire survey was conducted between August 1994 and December 1994 in British firms having 200 or more employees in six industries in the manufacturing sector (food processing, plastics, steel, textiles, pharmaceuticals and footwear). The respondents were the top personnel specialist (one each) from each firm. The response rate ofthe questionnaire survey was approximately 19 per cent (93 out of 500 questionnaires). The items for the questionnaire were constructed from existing sources, such as those developed by Cranfield researchers in their study ofcomparative European HRM [32] and other studies (see for example [33, 34]). The questionnaire consisted of 13 sections. These were: HR department structure, role of the HR function in corporate strategy, recruitment and selection, pay and benefits, training and development, performance appraisal, employee relations, HRM strategy, influence ofnational culture, national institutions, competitive pressures and business sector on HRM, organizational details. Public limited companies represented approximately one-third of the sample, with the remainder from the private sector. The industry-wide distribution of respondents is shown in Table 1.

Table 1: Sample Industry Distribution

Indtitry Percentage . Food Processing 17.2 Plastics 17.2 Steel 16.1 Textiles 17.2 Pharmaceuticals 21.5 Footwear 10.8

Analysis of the demographic features of the sample suggests that the sample was representative ofthe total population. Sixty-two per cent of sample organizations were medium-sized and employed 200-499 employees, 14 per cent employed 500-999 employees, 15 per cent 1000- 4999 employees, and 8 per cent employed 5000 or more employees.

In the second phase of the research, 24 in-depth interviews were conducted with personnel specialists representative of those firms which participated in the first phase of the research. The interviews examined six themes, viz. the nature of the personnel function, integration ofHRM into the corporate strategy, devolvement ofHRM to line managers, and the influences of national culture, national institutions and business environment dynamic on HRM.

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Measures

Multiple regression analysis and descriptive statistics are used to analyse questionnaire data. Table 1 in the Appendix shows the main dependent and independent variables used for multiple regression analysis. Table 2 in the Appendix presents the mean scores of respondents regarding the influence of different aspects of national factors (culture, institutions, business environment dynamic and business sector) and HR strategies on HRM policies and practices. The qualitative data is content analysed. In the discussion, survey results are complemented by key messages coming from the qualitative interviews.

Findings of the Study

The matching models suggest a strong dependence ofHRM on organization strategy, i.e, HRM is mainly developed for the effective implementation of organization strategies. The results show that in 34.6 per cent of the organizations under study personnel is involved from the outset in the formation of corporate strategy, and 42 per cent of organizations actively involve HRM during the implementation stage of their organizational strategies. Such a trend of 'active' personnel management is further evident from 55 per cent of sample organizations having personnel representation at board level. Moreover, 81.1 per cent ofthe respondents believe that their HRM has become proactive over the last five years (i.e. more involved in decision making).

Such results reflect the growing strategic and proactive nature of the British personnel function. There is support for such findings in the existing literature [35, 36].

The second reason to examine the matching models in a cross- national context is to assess whether human resources are considered as a cost ('use them sparingly') or as an asset (spend on training to 'make their best use '). The results suggest that British organizations claim to be spending variable though reasonable proportions oftheir annual salaries on human resource development (HRD) related activities (see Table 2).

Table 2: Proportion of Annual Salaries and Wages Currently Spent on Training and Development

Value(%) Percentage of Sample Nil -

0.1- 2.00 41.3 2.01-4.00 7.6 4.01- 6.00 3.3

6.01 or more 1.1 Don't know 46.7

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A similar pattern characterizes the number ofdays training provided to different levels ofemployees (see Table 3). The substantial majority of British firms have increased (rather than maintained or reduced) their training spend across all categories of staff over the last five years (see Table 4). There is evidence that this investment has been directed particularly in the areas of performance appraisal, communication, delegation, motivation and team building.

Table 3: Average Number of Days Training and Development Given to Staff Categories Per Year

Different Cat~ories of Staff Number ofDays Mana}!erial(%) Prof,/Technical(%) Clerical(%) Manual(%)

Nil 1.2 1.1 2.3 1.2 0.1-3.00 24.4 22.8 35.6 24.7 3.01-5.00 20.9 21.7 13.8 11.7

5.01-10.00 7.0 14.7 4.6 11.8 10.1 and above 5.8 4.6 3.5 9.4

Don't know 40.7 40.9 40.2 41.2

These developments in the British HRD scene appear to be consistent with the increased realisation by both business and government that the development of human resources has been neglected for too long [37].

Table 4: Nature of Change in Amount of Money Spent on Training Per Employee

Different Categories of Staff Nature ofChange Mana}!erial("/o) Prof,/Technical("/o) Clerical(%) Manual(%) Increased 59.8 63.0 53.3 60.9 Same 21.7 18.5 28.3 20.7 Decreased 7.6 8.7 7.6 7.6 Don't know 10.9 9.8 10.9 10.9

Another key emphasis of the matching model suggests a variation in HRM strategies across different levels of employees. This is clearly evident from the results as the nature and type of approach to the management of different levels of employees vary significantly (see for example, Tables 3 and 4). This aspect is further highlighted later in this paper. Based on the above evidence, it seems that the British personnel function still plays an implementationist role rather than being actively involved in strategy formulation. On the other hand, there is a strong emphasis on training and development.

Important Situational Determinants

One of the basic assumptions of the Harvard model of HRM is the influence of a number of situational factors (such as work force

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characteristics, unions, labour legislation and business strategy) and different stakeholders (such as unions, government and community) on HRM policies. The impact of a few of the situational factors and stakeholders (proposed by Beer et al. [38D was examined during the multiple regressions, analysis of means scores and the analysis of interview results.

Taking the number of employees as a characteristic of the work force [39, 40], the regression results show that small British organizations (those having less than 499 employees) are likely to recruit their managerial staff by advertising externally. Medium size organizations (those having 500 to 999 employees) are likely to recruittheirclerical staffas apprentices. Large organizations (those having 1000 to 4999 employees) are more likely to use assessment centres to train their human resources. Lastly, very large firms (having over 5000 employees) are less likely to recruit their managerial staff by advertising internally and their manual staff through the use of word of mouth method. These firms are likely, however, to recruit their professional staff with the help of consultants. Moreover, large UK firms are more likely to adopt formal career plans, succession plans and planned job rotation to develop their human resources (for details see Table 1 in Appendix).

Support for these findings can be found in the literature (see for example, [41D. The size ofan organization has a positive relation with the formalism of their HRM policies [42]. Therefore, as the size of the firm becomes large, logically, the degree offormalism ofits personnel function increases and the organization obtains the help ofrecruitment agencies to recruit its professional employees.

The results show a strong impact of labour laws, educational and vocational training set up (highlighting government policy) and unions on British HRM policies (see Table 2 in Appendix). Unions in the UK are now playing a more supportive role [43]. The implementation of labour legislation is also having significant influence on UK HRM policies. Various pressures groups also contribute in this regard (for example, against age discrimination). Over the last decade or so, the education and vocational set-up in the UK has initiated a number of programmes and qualifications such as the national vocational qualifications (NVQs), investors in people (IIP) and' opportunity 2000' . These are now significantly influencing HRM in British organizations [44].

The results also show a number of significant regressions regarding the impact of HR strategies on British HRM. Results in Table 1 in the Appendix show that organizations pursuing a cost reduction strategy are more likely to recruit their clerical and manual staffas apprentices. These organizations are likely to adopt an effective resource allocation HR strategy. Organizations pursuing a talent improvement HR strategy are

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less likely to recruit their manual staff by word of mouth method. However, sample firms pursuing a talent acquisition HR strategy are likely to use consultants to recruit their managerial staff and recruitment agencies for manual staff. These organizations are also likely to adopt assessment centres to train their staff.

Most of the above results seem to be logical. For example, by recruiting employees as apprentices organizations not only pay them less but also train and prepare them for working in the long run in their organizations. Hence, it helps to reduce the costs. Similarly, by recruiting employees externally, organizations increase the opportunity to improve their talent base.

The second key emphasis of the Harvard model of HRM suggests extensive use of communication with employees as a mechanism to maximise commitment [45, p. 63]. Ninety-one per cent of British organizations share information related to both strategy and financial performance with their managerial staff. However, this percentage is significantly lower for other categories of employees (see Table 5).

Table 5: Employees Formally Briefed about Strategy or Financial Performance

Different Categmes of Staff Tvoe ofInformation Managerial(%) Prof/Technical(%) Clerical(%) Manual(%) Strategy - 8.0 8.6 6.4 Financial Performance 6.5 14.8 39.5 38.5 Both 91.3 65.7 42.0 23.6 Neither 2.2 11.6 9.9 31.5

There can be a number of explanations for the difference in the sharing of strategic and financial information with different levels of employees in British organizations. Whilst noting that top personnel specialists are now more and more involved in strategy making, it seems that top management continue to be reluctant to devolve responsibility to line managers for the dissemination offinancial and strategic information. These issues are further examined when discussing the 5-P model.

The above discussion suggests applicability of the Harvard model ofHRM in British organizations. The results showed an impact oflabour laws, education vocational set-up, unions, work force characteristics and HR strategies on HRM policy choices. There are encouraging results on the communication of information with different levels of employees regarding sharing strategic and financial performance and on employee development through their involvement and training.

Contextual Factors

The main issue against which the relevance of the contextual model can be evaluated is the impact on HRM policies and practices of economic

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(characterized by competitive pressures, ownership and life cycle stage), technological (type ofproduction system)and socio-political (characterised by national education and training set-up) factors and organizational contingencies (such as size, age and nature of organization).

The results show a strong influence of competitive pressures on British HRM policies and practices (see Table 2 in Appendix). To achieve a competitive edge in such situations, they are focusing particularly on total customer satisfaction and the restructuring oftheir organizations. As competitive pressures are also forcing British organizations to enter into new business arrangements (such as alliances), so these are having direct influence on HRM policies and practices.

The results also show the impact of increasingly sophisticated informationand communications technology on HRM policies and practices (see Table 2 in the Appendix). Further evidence indicates that the majority of respondents suggest these technologies mainly influence training, appraisal and transfer functions. Why? Because with the change in technology, employees need to be trained to handle it. To see if they have achieved the required competence they are appraised and if required, transferred to suitable positions.

Finally, we summarise the relevance of the contextual model of HRM in terms ofthe impact of organizational contingencies. Contingent variables such as size of the organization, presence of HR strategy and presence of unions were examined above, as were the impacts of ownership and organizational life cycle stage. These variables do not seem significantly to impact HRM in British organizations.

Nevertheless, there is significant evidence overall regarding the applicability of the contextual model ofHRM in British organizations.

Strategic Integration and Devolvement of HRM in Britain

Our discussion now focuses on the relevance of the '5 P' model ofHRM in British organizations. To achieve this, results regarding the integration of HRM into corporate strategy and the devolution of responsibility for HRM to line managers are examined. The detailed results are presented elsewhere [46], but are summarized below.

In brief, the level of integration is measured on the basis of the following four scales:

a) representation of Personnel on the board; b) presence of a written Personnel strategy; c) consultation ofPersonnel (from the outset) in the development

of corporate strategy; and d) translation ofPersonnel/HR strategy into a clear set of work

programmes.

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Journal of General Management Vol. 26 No. 2 Winter 2000

The level of devolvement is measured on the basis of the following three scales:

a) primary responsibility with line managers for HRM decision making (regarding pay and benefits, recruitment and selection, training and development, industrial relations, health and safety, and workforce expansion and reduction);

b) change in the responsibility of line managers for HRM (regarding pay and benefits, recruitment and selection, training and development, industrial relations, health and safety, and workforce expansion and reduction); and

c) percentage ofline managers trained in performance appraisal, communication, delegation, motivation, team building and foreign language.

High integration is the result of personnel representation at board level, the personnel function being consulted about corporate strategy from the outset, the presence of a written personnel strategy, and the translation of such a strategy into a clear set of work programmes. As mentioned earlier, the personnel function is represented at board level in the majority (55 per cent of organizations). For our sample companies, 87.4 per cent have corporate strategies. Of these, 34.6 per cent consult the personnel function at the outset, 42 per cent involve personnel in early consultation, and only 13.6 per cent involve personnel during the implementation stage. Over a quarter (26.4 per cent) of sample organizations did not have a personnel strategy, 29.9 per cent had an unwritten strategy and 43.7 per cent had a written personnel strategy. A clear majority (57.4 per cent) of organizations felt that their personnel strategy was translated into clear work programmes.

High devolvement is the result of: primary responsibility for pay, recruitment, training, industrial relations, health and safety and expansion/ reduction decisions lying with the line (see Table 6); line responsibility for these six areas on an increasing trend (see Table 7); and, evidence of devolved competency with at least 33 per cent of the workforce being trained in appraisals, communications,delegation, motivation, team building and foreign languages.

Budhwar's [47] analysis shows that when the four measures of integration are summated and divided into a single scale of high and low type, 50.5 per cent of the sample organizations would be categorised as having high integration and 49.5 per cent fall into the low integration category. The average score of the summated integration scale for a1193 organizations is .50. These results show a moderate level of integration being practised in the sample industries. On the other hand, the summated scales demonstrate a low level of devolvement. Sixty-one per cent of the sample practise low levels of devolvement of HRM to line managers.

Journal of General Management Vol. 26 No.2 Winter 2000

Table 6: Primary Responsibility for Major Decisions on Personnel Issues

Personnel Issues Line Line Mgt in IIR Dilpt. inHRDept. Consultation COllSuJtationRelated to: Mgt. wi!il1lB.l)llUt. withLineMat. Pay andBenefits 48.3 14.3 11.0 26.4 Recruitment and Selection 17.2 12.9 34.4 35.5 Training andDevelopment 15.1 18.3 22.5 44.1 Performance Aonraisal 17.5 6.9 30.4 45.2 Industrial Relations 36.3 13.2 25.3 25.2 Health and Safety 18.5 32.6 19.6 29.3 Workforce

19.4 19.4 44.1 17.1Expansion/Reduction WorkSystem/Job Design 7.6 33.7 40.2 18.5 Figures in the above cells represent valid percentage, calculated after excluding the missing values.

Table 7: Change in Responsibility of Line Management for Different Personnel Issues

PellSonnelIssues Increased (%) Same(%) Decreased (%) Pay andBenefits 27.2 65.2 7.6 Recruitment and Selection 43.5 48.9 7.6 Training and Development 69.6 23.9 6.5 Performance Appraisal 60.0 37.8 2.2 Industrial Relations 28.9 63.3 7.8 Healthand Safety 61.5 35.2 3.3 Workforce

38.9 54.4 6.7Expansion/Reduction WorkSystem/Job Design 43.3 53.3 3.3

The results confirm the relevance of the 5-P model of HRM in British organizations. They also help to examine the main emphasis of Brewster's [48] European model of HRM, i.e, the linkages between corporate strategy and HRM strategy.

Conclusion

Overall, the results show a mixed picture, i.e. from strong to moderate applicability of the mentioned HRM models in Britain. The study aimed to examine HRM in context, and the findings should be useful for relevant policy makers. In particular, it seems that the sample firms are practising a relatively low level of devolvement in comparison to the integration function. Ifthe HRM function is to become more strategic, then the level of practice of both these concepts has to increase. Such demands are likely to increase in future as more and more firms restructure and become lean in order to respond to competitive and other pressures [49].

The study has two main limitations. First, it is restricted to six industries ofthe UK manufacturing sector. Second, the views of only top

..

Journal of General Management Vol. 26 No. 2 Winter 2000

personnel specialists were examined. In order, therefore, to obtain a more comprehensive picture, research needs to be extended to other business sectors and to the views of other key actors (such as line managers). Future research could also build upon this study by investigating other models ofHRM and their applicability in different national contexts.

Appendix

Table 1: Factors Determining HRM Practices in British Organizations

Independent. lJependentVariables If BiJta . t·valueVarin/J/es Training and development

0.2102 0.2984* 2.3790 Introductory through planned iob rotation lifecycle stage Communication through

0.1629 -0.2663* -2.0720 immediate superior

Turnaround Recruiting managerial staff by 0.3695 -0.3038* -2.6170

lifecycle stage advertising externally Recruiting managerial staff by

0.3695 0.3658** 3.0590 Less than 499 advertising externally employees Recruiting clerical staff from 0.1014 -0.3184* -2.4220

recruitment agencies Between 500- Recruiting clerical staff as

0.3337 0.2891* 2.4600 599 employees apprentices Between 1000- Training and development 4999 through assessment centres 0.2607 0.3547** 2.8530 employees

Recruiting managerial staff by 0.1563 -0.2835* -2.1800

advertising internally Recruiting professionals/technical staff by

0.1039 0.3223* 2.4550 use of search/selection

More than consultants

5000 Recruiting manual staffby

0.3698 -0.4529** -3.9340 employees

word of mouth Training and development through formal career plans

0.1406 0.375** 2.9170

Training and development 0.1685 0.4105** 3.2460

through succession plans Training and development

0.2102 0.3873** 3.0880 though planned job rotation

Public Limited Recruiting managerial staff by 0.3695 0.4436** 3.8050Company advertising externally

Recruiting managerial staff 0.0830 -0.2881* -2.1700

from current employees State-owned Recruiting clerical staff from

0.2842 -0.2583* -2.0650 organization current emnlovees

Recruiting manual staff by 0.3698 -0.3342** -2.9100

word of mouth Organizations incorporated Commnnication through trade

0.7445 -0.216** -3.0370 between 1869- unions or work councils 1899 Organizations incorporated Recruiting manual staff from

0.1557 0.2609* 2.0240 between 1900- current employees 1947

Continued ...

Journal of General Management Vol. 26 No.2 Winter 2000

Table 1 Continued:

Independent lJepen4ent Variables .Jf Beta tvalueVariable Recruitingclericalstaffby 0.2465 -0.3931** -3.2110advertising externally Recruitingmanualstaffby 0.1974 -0.2767* -2.1550advertising externally

Organizations Trainingand development 0.2607 0.4364** 3.3780incorporated throughassessment centres between 1948- Communication through 0.1629 -0.3255* -2.53201980 immediatesuperior

No formal communication 0.3517 0.3265** 2.7370methods Communication through 0.0858 0.2929* 2.2090suggestion box(es) Recruitingclericalstaff from 0.2842 -0.3019* -2.4240current employees

Cost reduction Recruitingclericalstaff as 0.3337 0.4182** 2.9450HRstrategy apprentices Recruiting manualstaff as 0.1330 0.3646** 2.8240apprentices

Talent Recruitingmanualstaff by 0.3698 -0.3655** -3.2440improvement word of mouthHRstrategy Recruiting managerial staffby

0.0777 0.2787* 2.0930use of search/selection Talent consultants acquisition HR Recruitingmanualstaff from 0.0914 0.3024* 2.2880strategy recruitmentagencies

Trainingand development 0.2607 0.2857* 2.2090throughassessment centres Effective Recruitingclericalstaff as

0.3337 0.2882* 2.0300resourceHR apprenticesstrategy Recruitingmanagerial staff by 0.3695 0.3593** 2.9750advertising externally Recruitingmanualstaff by 0.1226 0.3502** 2.6960Unionised advertising internally

firms Communication through 0.3517 -0.255* -2.1820attitude survey Communication throughtrade 0.7445 0.5656** 6.4000unions or work councils

* Significance at .05 level; **Significance at .01 level

-

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Journal of General Management Vol. 26 No.2 Winter 2000

Table 2: Influence of Different Aspects of National Factors on HRM

Aspectsoff"lational (;ultttre No. of Cases Mean 1 Way in which managers are socialised 84 18.07 2 Common values, norms of behaviour and customs 81 20.28 3 The influence of pressure groups 58 10.47

4 Assumptions that shape the way managers perceive and

84 25.98 think: about the organization

5 The match to the organization's culture and 'the way we

86 35.58 do things around here'

N(ltif.}1Inl T- o '011.6 1 National Labour Laws 82 40.91 2 Trade Unions 61 21.72 3 Professional Bodies 56 15.11 4 Educational and Vocational training set-up 84 27.62 5 International Institutions 54 20.07

A~l1ects QflIusinessEnvironment 1

Increased national/international competition - 72 27.56

Globalisation of corporate business structure Growth of new business arrangements, e.g. business

2 alliances, joint ventures and foreign direct investment 66 19.01 through mergers and acquisitions

3 More sophisticated information/communication

70 19.62 technology or increased reliance on automation

4 Changing composition of the workforce with respect to

48 12.39 gender, age, ethnicity and changing employee values

5 Downsizing of the workforce and business re-

69 23.13 engineering

6 Heightened focus on total management or customer

78 26.92 satisfaction

Aspects qfBusinessSector 1

Common strategies, business logic and goals being 71 22.95

pursued by firms across the sector

2 Regulations and standards (e.g. payments, training,

79 20.35 health and safety) specific to your industrial sector Specific requirement/needs of customers or suppliers

3 that characterise your sector (i.e. supply chain 82 28.96 management)

4 The need for sector-specific knowledge in order to 56 15.35 provide similar goods/services in the sector

5 Informal or formal benchmarking across competitors in

61 16.39the sector (e.g, best practices of market leaders) Cross-sector co-operative arrangements, e.g, common

6 technological innovations followed by all firms in the 37 10.54 sector

7 Common developments in business operations and work

49 14.40 practices dictated by the nature of the business

8 A labour market or skill requirement that tends to be

39 13.10used by your business sector only

Respondentswere asked to allocate a totalof100points to the different aspects ofthe above nationalfactors.

Journal of General Management Vol. 26 No.2 Winter 2000

References

[1] Jackson, S. E. and Schuler, R. S., 'Understanding Human Resource Management in the Context ofOrganizations and their Environment' , Annual Review of Psychology, Vol. 46, 1995, pp. 237-264.

[2] Legge, K., Human Resource Management: Rhetorics and Realities, Chippenham: MacMillan Business, 1995.

[3] Sisson, K. and Storey, J., The Realities of Human Resource Management, Buckingham: Open University Press, 2000.

[4] Guest, D. E., 'Human Resource Management and Performance: A Review and Research Agenda', International Journal ofHuman Resource Management, Vol. 8, No.3, 1997, pp. 263-276.

[5] Schuler. R. S. and Jackson, S. E., Strategic Human Resource Management, London: Blackwell, 1999.

[6] Brewster, C., 'Towards a European Model of Human Resource Management', Journal of International Business Studies, Vol. 26, No.1, 1995, pp. 1-22.

[7] Legge, K., 1995, op. cit. [8] Benkhoff, B., 'A Test ofthe HRM Model: Good For Employers and

Employees', Human Resource Management Journal, Vol. 7, No.4, 1997,pp.44-60.

[9] Monks, K., 'Global or Local? HRM in the Multinational Company: The Irish Experience', The International Journal of Human Resource Management, Vol. 7, No.3, 1996, pp. 721-735.

[10] Truss, C., Gratton, L., Hailey, H., McGovern, P. and Stiles, P., 'Soft and Hard Models ofHuman Resource management: A Reappraisal' , Journal ofManagement Studies, Vol. 34, No.1, 1997, pp. 53-73.

[11] Legge, K., 1995. op. cit. [12] Brewster, C., 1995, op. cit. [13] Legge, K., 1995. op. cit. [14] Poole, M., 'Editorial: Human Resource Management in An

International Perspective', International Journal of Human Resource Management, Vol. 1, No.1, 1990, pp. 1-15.

[15] Fombrun, C. J., Tichy, N. M. and Devanna, M. A., Strategic Human Resource Management, New York: Wiley, 1984.

[16] Chandler, A., Strategy and Structure, Cambridge, MA: MIT Press, 1962.

[17] Schuler, R. S. and Jackson, S. E., 'Organizational Strategy and Organizational Level as Determinants of Human Resource Management Practices', Human Resource Planning, Vol. 10, No.3, 1987, pp. 125-141.

[18] Beer, M., Spector, B., Lawrence, P. R., Quinn Mills, D. and Walton, R. E., Human Resource Management, New York: Free Press, 1984.

[19] Legge, K., 1995. op. cit. [20] Poole, M., 1990. op. cit.

..

[21]

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Hendry, C and Pettigrew, A.M., 'Patterns of Strategic Change in the Development of Human Resource Management', British Journal ofManagement, Vol. 3, 1992, pp. 137-156. Hendry, C., Pettigrew, A. M. and Sparrow, P. R., 'Changing Patterns of Human Resource Management,' Personnel Management, Vol. 20, No. 11, 1988, pp. 37-47. Schuler, R. S., 'Linking the People with the Strategic Needs of the Business', Organizational Dynamics, Summer, 1992, pp. 18-32. Ibid. Brewster, C., 1995, op. cit. Ibid. Budhwar, P., 'Taking Human Resource Management Research To The Next Millennium: Need For An Integrated Framework', Annual Academy of Management Conference, Chicago, 1999. Budhwar, P. and Debrah, Y., 'Rethinking Comparative and Cross National Human Resource Management Research,' The International Journal of Human Resource Management, 2001 (forthcoming).

[29] Budhwar, P. and Sparrow, P., 'An Integrative Framework For Determining Cross National Human Resource Management Practices', Human Resource Management Review, 2001 (forthcoming) .

[30] Budhwar, P. and Sparrow, P., 'National Factors Determining Indian and British HRM Practices: An Empirical Study', Management International Review, Vol. 38, Special Issue 2, 1998, pp. 105-121.

[31] Truss, C., Gratton, L., Hailey, H., McGovern, P. and Stiles, P., 1997, op. cit.

[32] Brewster, C. and Hegewisch, A., (eds.) Policy and Practice in European Human Resource Management, London and New York: Routledge, 1994.

[33] Baird, L. and Meshoulam, r., 'Managing Two Fits of Strategic Human Resource Management', Academy of Management Review, Vol. 13, No.1, 1988, pp. 116-128.

[34] Jackson, S. E., Schuler, R. S. and Rivero, J. C., 'Organizational Characteristics as Predictors of Personnel Practice', Personnel Psychology, Vol. 42, No.4, 1989, pp. 727-786.

[35] Legge, K., 1995, op. cit. [36] Hendry, C., Human Resource Management: A Strategic

Approach to Employment, Bath: Butterworth-Heinemann, 1998. [37] Townley, B. 'Communicating with Employees' , in Sisson, K. (ed.),

Personnel Management: A Comprehensive Guide to Theory and Practice in Britain, Blackball Business: London, 1996, pp.595- 633.

[38] Beer, M., Spector, B., Lawrence, P. R., Quinn Mills, D. and Walton, R. E., 1984, op. cit.

[39] Jackson, S. E. and Schuler, R. E., 1995, op. cit. [40] Tayeb, M., Organizations and National Culture, London: Sage,

1988.

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[41] Sisson, K. and Storey, J., 2000, op. cit. [42] Brewster, C. and Hegewisch, A., 1994, op. cit. [43] Heery, E., 'Annual Review Article 1996'. British Journal of

Industrial Relations, Vol. 35, 1997, pp. 87-109. [44] Collin, A. and Holden, L., 'The National Framework for Vocational

Education and Training', in. Beardwell, 1. and Holden, L., (eds.), Human Resource Management. London: Pitman Publishing, 1997, pp.345-377.

[45] Truss, C., Gratton, L., Hailey, H., McGovern, P. and Stiles, P., 1997,op. cit.

[46] Budhwar, P., 'Strategic Integration and Devolvement of Human Resource Management in the British Manufacturing Sector' , British Journal of Management, Vol. 11, No.4, 2000, (in Press).

[47] Ibid. [48] Brewster, C., 1995, op. cit. [49] Terry, M. and Purcell, J., 'Return to Slender' , People Management,

23 October, 1997,46-51.

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Article

Does Leadership Style Make a Difference? Linking HRM, Job Satisfaction, and Organizational Performance

Brenda Vermeeren1, Ben Kuipers1, and Bram Steijn1

Abstract With the rise of New Public Management, public organizations are confronted with a growing need to demonstrate efficiency and cost-effectiveness. In this study, we examine the relationship between public organizational performance and human resource management (HRM). Specifically, we focus on job satisfaction as a possible mediating variable between organizational performance and HRM, and on the influence of a supervisor’s leadership style on the implementation of Human Resource (HR) practices. Drawing on a secondary analysis of data from a national survey incorporating the views of 6,253 employees of Dutch municipalities, we tested our hypotheses using structural equation modeling. The findings indicate that (a) job satisfaction acts as a mediating variable in the relationship between HRM and organizational performance and (b) a stimulating leadership style has a positive effect on the amount of HR practices used, whereas (c) a correcting leadership style has no effect on the amount of HR practices used.

Keywords HRM, leadership style, job satisfaction, organizational performance, public sector, Dutch municipalities

Introduction

During the last three decades, public sector performance has become an increasingly important issue. With the rise of New Public Management, targets, performance, and

1Erasmus University Rotterdam, The Netherlands

Corresponding Author: Brenda Vermeeren, Erasmus University Rotterdam, Room M7-13, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. Email: [email protected]

510853ROP34210.1177/0734371X13510853Review of Public Personnel AdministrationVermeeren et al. research-article2013

Vermeeren et al. 175

a more business-oriented management approach have come to play central roles within the public sector (Boyne, Meier, O’Toole, & Walker, 2006; Osborne & Gaebler, 1992; Pollitt & Bouckaert, 2004). Several innovations in the field promised to increase the quality of public service while reducing its costs. However, research into human resource management’s (HRM) contributions to these developments in the public sec- tor has been scarce (Boyne, Poole, & Jenkins, 1999; Gould-Williams, 2003). This neglect persists despite the fact that employees (those who deliver public services) are crucial to achieving superior public performance. High-quality services require highly qualified and motivated personnel (Batt, 2002).

Based on numerous studies in the private sector, we can conclude that human resource (HR) practices and organizational performance are at least weakly related (Boselie, Dietz, & Boon, 2005; Guest, 2011; Paauwe, 2009). However, research com- paring HRM in the public and private sectors suggests that the HR policies and prac- tices in these sectors differ in many important areas (Boyne et al., 1999). In particular, public organizations are more likely than private organizations to engage in activities associated with the role of model employer. Such activities imply commitment to staff training, trade union, and workforce participation in decision making, promotion of equal opportunities, and a concern for the welfare of employees to meet their personal and family needs. Given these empirical findings, we cannot simply assume that the relationship between HRM and performance will be the same in the public sector.

In private sector–based research on HRM and performance, the assumption is that an underlying causal link that runs through employee outcomes (in the form of employee attitudes and behavior) connects HR practices with organizational perfor- mance (Boselie et al., 2005; Guest, 2002; Paauwe & Richardson, 1997). In other words, HR practices are implemented to influence employees, with the ultimate aim to positively influence the organization’s performance. Job satisfaction is conceptualized as one of the key indicators of employee outcomes in HRM and performance research (Guest, 2002; Purcell & Hutchinson, 2007). Previous research has demonstrated a positive relationship between HRM and job satisfaction (e.g., Guest, 2002; Steijn, 2004) and between job satisfaction and performance (e.g., Hackman & Oldham, 1975; Judge, Thoresen, Bono, & Patton, 2001; Taris & Schreurs, 2009). These findings sup- port the idea that job satisfaction acts as a mediating variable in the relationship between HRM and performance. At this time, only a few studies have examined that mediating relationship (e.g., Ahmad & Schroeder, 2003; Gelade & Ivery, 2003), but more research is needed to understand how HRM and organizational performance are related. Such research is even more important in the context of the public sector, as previous research showed differences in job satisfaction between public and private sector employees (DeSantis & Durst, 1996).

In general, in the HRM literature is stated that the HR practices perceived or expe- rienced by employees will be those enacted by their supervisors (Bowen & Ostroff, 2004; Paauwe, 2009; Purcell & Hutchinson, 2007; Wright, Gardner, Moynihan, & Allen, 2005). To influence employee outcomes positively, supervisors require well- designed HR practices for use in their management activities. Den Hartog, Boselie, and Paauwe (2004) stressed the important role that supervisors play in implementing

176 Review of Public Personnel Administration 34(2)

an intended HRM policy, as differences in implementation at this level may be attrib- utable to supervisors’ different leadership styles. Such differences in implementation and communication may lead to variation in employees’ HR perceptions. However, scholars have uncovered little empirical evidence that bears on the role of supervisors’ leadership styles in HRM implementation. Focusing on leadership style can provide additional insight into how supervisors influence the implementation of HR practices.

This study adds to prior research in three ways. First, we focus specifically on the relationship between HRM and organizational performance in the public sector. Second, we test whether job satisfaction acts within a public context as a mediator between HRM and organizational performance. Third, we focus on the influence of a supervisor’s leadership style on the implementation of HR practices. Thus, our main research question is as follows:

Research Question: To what extent is the relationship between HRM and the per- formance of public organizations mediated by job satisfaction and what is the influ- ence of a supervisor’s leadership style on the implementation of HR practices?

After a theoretical exploration of the literature on HRM, job satisfaction, organiza- tional performance, and leadership, we will formulate several hypotheses and test them using survey data from 6,253 employees of Dutch municipalities. We perform these tests using structural equation modeling (SEM). We will then discuss our find- ings. Finally, we conclude by describing suggestions for future research and implica- tions for theory and practice.

Literature Review

The increased focus on performance in the public sector has encouraged a large amount of research (Boyne et al., 2006; Halachmi & Bouckaert, 1996). In particular, the impact of management on performance in public organizations has been frequently studied (Meier, O’Toole, Boyne, & Walker, 2007; Nicholson-Crotty & O’Toole, 2004). The O’Toole and Meier (1999) model of management is well known and has often been used to test the impact managers may have on the performance of public organi- zations. In one of their articles, O’Toole and Meier (2008) focused on the internal side of management and, in particular, on the contribution of “the human side” of public organizations to organizational performance in public education. Their results indicate that the power of HRM in attracting and developing an organization’s human capital is important to organizational performance. Gould-Williams (2003), in turn, examined the relationship between HRM and performance in local government in the United Kingdom. He found, the more HR practices are used within an organization, the greater the impact on organizational performance. In both articles, the authors stated that more research is needed to explore the relationship between HRM and organiza- tional performance in the public sector.

Vermeeren et al. 177

As the existing literature has paid little attention to the relationship between HRM and performance in a public context, we must turn to the general HRM literature to get more insight. However, that literature contains a very diverse array of theoretical per- spectives, definitions, measurements, methodologies, and research fields (Boselie et al., 2005). Nevertheless, following Paauwe (2009), we can conclude that there is at least a weak relationship between HR practices and organizational performance. Yet, despite the fact that several studies indicate a link between HRM and performance, significant challenges to a full understanding of this relationship still exist (Boselie et al., 2005; Bowen & Ostroff, 2004; Guest, 2011; Paauwe, 2009).

In this study, we adopt a micro approach to HRM. This approach reflects a more operational view of HRM by focusing specifically on the effect of multiple HR prac- tices on individuals (Wright & Boswell, 2002). By using this micro approach, we attempt to acquire more insight into the impact of multiple HR practices on individuals (measured through job satisfaction) and, subsequently, on organizational performance. By focusing on job satisfaction as a mediating factor, our aim is to generate a better understanding of what takes place between HRM and performance. Furthermore, scholars frequently identify the leadership style of supervisors (who are increasingly charged with implementing HR practices) as a variable essential to a better under- standing of the relationship between HRM and performance (Bowen & Ostroff, 2004; Paauwe, 2009; Purcell & Hutchinson, 2007; Wright et al., 2005). In this respect, Purcell and Hutchinson (2007) used the term “people management” to mark the dis- tinction between a supervisor’s leadership style and the application of HR practices. This distinction is based on the assumption that supervisors require well-designed HR practices to use in their people management activities and that their leadership style will influence the way they enact these practices.

The Mediating Role of Job Satisfaction

Guest stated in 1999 that, given the growing interest in research on the relationship between HRM and performance, a focus on workers’ viewpoints has become increas- ingly important. An analysis of 104 articles by Boselie et al. (2005) confirms Guest’s impression that the linking mechanisms between HRM and performance have largely been disregarded. To understand how HR practices influence employees and improve worker performance in ways that are beneficial to the organization, research is required that concentrates on employee perceptions of HR practices and establishes relation- ships between their job satisfaction and organizational performance, to take one exam- ple (Purcell & Hutchinson, 2007). One model that takes this focus is the Paauwe and Richardson (1997) model on HRM, HRM outcomes and organizational performance. In this model, the first element consists of HR practices such as recruitment, rewards, and employee participation. This element influences the so-called HRM outcomes, such as job satisfaction and motivation. Both of these elements affect the third ele- ment, organizational performance, which involves performance indicators related to the effectiveness, quality, and efficiency of the organization.

178 Review of Public Personnel Administration 34(2)

A variety of studies have examined separate parts of this model. Focusing specifi- cally on the public sector, a number of studies have explored the relationship between HRM (Element 1) and HRM outcomes (Element 2; for example, Gould-Williams, 2004; Steijn, 2004) and between HRM outcomes (Element 2) and organizational per- formance (Element 3; for example, Kim, 2005; Ostroff, 1992). The model by Paauwe and Richardson (1997) adds to this research through its explicit focus on the mediating effect of HRM outcomes on the relationship between HRM and organizational perfor- mance. Moreover, the Paauwe and Richardson model adds to existing public sector research by promoting an explicit concentration on the concept of HRM itself. This concentration marks an important difference with the aforementioned management model by O’Toole and Meier (2008). Therefore, we use the Paauwe and Richardson model as the starting point for our research. However, while that model offers an exhaustive range of options to consider for each element, we limit ourselves to job satisfaction as the only included HRM outcome.

The introduction of job satisfaction enables us to refine the relationship between HRM and organizational performance. To a large extent, positive employee outcomes depend on employees’ perceptions of how much the organization cares about their well-being and values their contributions (Gould-Williams, 2007; Vermeeren, Kuipers, & Steijn, 2011). In this respect, the degree of job satisfaction will depend on the fulfill- ment of employee’s needs and values (Hackman & Oldham, 1975). To increase orga- nizational performance, it is likely important that the organization must not only meet the needs of customers, but also meet those of employees (Schneider & Bowen, 1993). This assertion is based on the assumption that if organizations care for their employ- ees, these employees will care for the organization (and their customers). In other words, this argument is based on the assumption that a happy worker is a productive worker (Taris & Schreurs, 2009). In this respect, the degree to which HR practices are introduced can be conceptualized as a marker of the extent to which an organization values and cares for employees. As noted above, previous research has demonstrated a positive relationship between HRM and job satisfaction (e.g., Guest, 2002; Steijn, 2004) and between job satisfaction and performance (Hackman & Oldham, 1975; Judge et al., 2001; Taris & Schreurs, 2009).1 These findings support the idea that job satisfaction acts as a mediating variable in the relationship between HRM and perfor- mance. However, this relationship is mostly studied in separate parts and seldom examined within one design. We will therefore study the relationships among HRM, job satisfaction, and organizational performance in one model. Following this plan, our first hypothesis is as follows:

Hypothesis 1: Job satisfaction acts as a mediating variable in the relationship between HRM and organizational performance.

The Role of Leadership Style

For many years, HRM and leadership were separate research areas. Gradually, interest in combining these two areas has grown. The connection between these areas is based

Vermeeren et al. 179

on the proposition that employees are likely to be influenced by the HR practices they experience and their supervisor’s leadership style (Purcell & Hutchinson, 2007). Supervisors need HR practices to support their management activities, and the way supervisors enact these practices is influenced by their leadership style. However, pre- vious research on the relationship between HRM and performance paid little attention to supervisors’ leadership styles. One of the few studies that did attend to leadership style demonstrated that leadership and employee satisfaction with HR practices have a strong and independent impact on such employee attitudes as job satisfaction and commitment (Purcell & Hutchinson, 2007).

However, this demonstration does not allow us to say much about the influence of different leadership styles on the use of HR practices within an organization. It is appropriate to assume a relationship exists between different leadership styles and HRM, because the choice of which HR practices to use appears to be linked to leader- ship style. For example, Zhu, Chew, and Spangler (2005) have shown that transforma- tional leaders influence organizational outcomes by their use of “human-capital-enhancing HRM.” Human-capital-enhancing HRM is defined as an approach to managing people that achieves competitive advantage through the strategic development of a highly committed and capable workforce (Zhu et al., 2005). Their assumption is that transfor- mational leaders possess a clear vision of what the organization will be, and what it will do, in the future. HRM plays a critical role in the communication process between leaders and employees, because without such HRM activities as staffing and training the leader’s vision will not be transmitted effectively.

Today, scholars in the field of leadership research use many and varied conceptual- izations of leadership. Despite differences among these conceptualizations, we can detect a certain commonality. This commonality is not of jargon, but of the ideas that underpin the language used. Many conceptualizations are based on a distinction between an internally and intrinsically directed, people-oriented, and stimulating lead- ership style versus an externally and extrinsically directed, task-oriented and correct- ing leadership style (Howell & Avolio, 1993). For example, this distinction underpins the differentiation made between transformational versus transactional leadership (Bass & Avolio, 1994) and participative versus authoritive leadership (Likert, 1961). With respect to the relationship between leadership style and HRM, Guest (1987) has argued that a more correcting leadership style could be linked to hard HRM and that a more stimulating leadership style could be linked to soft HRM. In his research, he refers to the classic distinction in McGregor (1960) between theory X and theory Y. The “hard” version of HRM is widely acknowledged to place little emphasis on work- ers’ concerns. In contrast, “soft” HRM would be more likely to pay attention to work- ers’ outcomes (Guest, 1987).

We will also use McGregor’s distinction between theory X and theory Y. This dis- tinction, despite frequent criticism (Bobic & Davis, 2003), still remains useful for distinguishing between the different leadership styles a supervisor can adopt. Theory X assumes that employees are not self-motivated and will avoid work if possible. Employees, therefore, must be closely supervised and corrected when necessary. Employees are seen as factors in the production process. Theory Y, in contrast, assumes

180 Review of Public Personnel Administration 34(2)

that employees are ambitious and self-motivated and can play a crucial role within the organization. Supervisors must ensure that their employees are properly stimulated by paying attention to their values and needs. It is in this context that Guest (1999) stated that if more HR practices are used, the impact on workers will be larger. Based on the idea that an HRM system should be designed to meet employees’ needs for skills and motivation and provide them with the opportunity to profile themselves to improve their performance (Appelbaum, Bailey, Berg, & Kalleberg, 2000), we would expect that a stimulating leadership style (theory Y) would be accompanied by the use of a greater number of HR practices tailored to invest in employees and meet their needs than would be the case for a correcting leadership style (theory X), in which employ- ees are seen as factors in the production process. This leads us to our second hypoth- esis, which consists of two separate parts:

Hypothesis 2a: A stimulating leadership style has a positive effect on the amount of HR practices used within an organization.

Hypothesis 2b: A correcting leadership style has a negative effect on the amount of HR practices used within an organization.

Figure 1 shows the overall theoretical model representing the hypotheses thus developed above. In the following sections, we present the methodology for testing this model and our empirical results.

Research Methods

A quantitative study was carried out to address our research question. This section describes the data and the measurement procedure, including the results of a confirma- tory factor analysis using AMOS version 16.

Stimulating Leadership

HRM Job

Satisfaction1

Organizational Performance1

Correcting Leadership

2B

2A 1

Figure 1. Conceptual model.

Vermeeren et al. 181

Data

To test our hypotheses about the direct and indirect relationships between the variables we apply a quantitative research design. For our analysis, we used data from a Dutch national survey on well-being among municipal employees. In 2005, a public sector organization representing municipalities approached 29,626 employees of Dutch municipalities in all functional areas (e.g., administrative, sociocultural, legal and information and communication technology functions), asking them to fill out a ques- tionnaire about employee well-being via Internet or mail. Of these employees, 7,918 respondents participated in the research. The respondents with missing data for the analyzed variables were removed from the sample, which resulted in a file with 6,253 respondents. The data for the resulting sample are as follows: 58% are male, the pre- dominant age is 45 to 54 years (37.5%), and the predominant educational level is secondary (vocational) education (43.1%). When compared with general population data (A+O fonds Gemeenten, 2005), the sample’s deviation from the general popula- tion is small (2%-6%). Despite the response rate of 26.7%, the respondents are gener- ally representative of the population with respect to gender, age, and educational level. The respondents also worked in different municipalities spread across the Netherlands and in organizations of various sizes.

Measures

HRM. HRM and performance research exhibits little consistency in the selection of HR practices by which to measure HRM. Boselie et al. (2005) analyzed 104 important HRM and performance studies and identified as many as 26 different HR practices that are used in different studies. No single agreed, or fixed, list of HR practices or systems of practices exists by which to measure HRM (Guest, 2011; Paauwe, 2009). Nevertheless, a certain consensus regarding the measurement of HRM has emerged in the scientific literature on HRM and performance during the past decade. More than half of the articles published after 2000 made use of Ability, Motivation, and Oppor- tunity (AMO) theory (Paauwe, 2009). AMO theory proposes that an HRM system should be designed to meet employees’ needs for skills and motivation and, after meeting those needs, provide them with opportunities to use their abilities in various roles (Appelbaum et al., 2000). The underlying idea is that employees will perform well if they have the requisite abilities, when they are motivated and when they obtain the opportunity to profile themselves (Appelbaum et al., 2000).

In our study, an existing data set is used for secondary data analysis. Although this data set can be employed to search for the presence of HR practices within organiza- tions, it was not developed for this specific purpose. The survey only measures 10 different HR practices used to a limited extent, and it is not able to measure all the aspects of HRM proposed by AMO theory. In particular, the survey does not allow us to determine whether an HR system provides employees with opportunities to use their abilities in various job roles. Despite this limitation, we use this list of practices as an indicator of the extent to which HR practices were used in public organizations.

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Researchers often advocate the study of an HRM system instead of individual HR practices (Wright & Boswell, 2002). Organizations rarely use HR practices in isolation; they more typically use them in combination. This system approach adheres to the prin- ciple “the whole is more than the sum of its parts” and examines a bundle of HR prac- tices. In this study, we have followed the system approach. In the survey, employees were asked about the use of 10 different HR practices within their organization (job evaluation conversations, assessment interviews, personal development plans, training plans, career plans, competency management, population aging HRM policy, mobility management, job rotation, and individual coaching). This particular list has been used in previous research (Steijn, 2004). In accordance with Guest’s suggestion, we counted how many of these practices were present in the organization according to its employ- ees. Cronbach’s alpha is widely used to demonstrate consistency among a set of items and, based on the score, it might be argued that a bundle of HR practices can be observed (Guest, Conway, & Dewe, 2004). The Cronbach’s alpha of the HR bundle is .70. This is within the range for acceptable internal consistency. The assumption is that the use of more HR practices suggests the existence of a better developed HRM policy within an organization. In making this assumption, we can only say something about the surplus value of HRM in general terms. However, we do not know whether some individual practices have stronger effects than others, how each of the individual practices affects performance and whether complementarities or synergistic interdependent relation- ships among such practices can further enhance organizational performance (Delaney & Huselid, 1996; Guest et al., 2004; Sels et al., 2006).

Job satisfaction. Job satisfaction is measured using one item: “All things considered, how satisfied are you with your job?” The answers were given using a 5-point Likert- type scale ranging from very dissatisfied (1) to very satisfied (5). Although there is some disagreement regarding how to measure job satisfaction, previous research shows that job satisfaction can reliably be measured using only one item (Nagy, 2002; Wanous, Reichers, & Hudy, 1997).

Organizational performance. To measure organizational performance, perceptions of performance and objective performance indicators can be studied (Delaney & Huselid, 1996; Kim, 2005). In this article, the focus is on employee perceptions of organiza- tional performance because objective performance data are not available in the data- base. When objective performance data are not available, subjective (perceptual) performance measures may be a reasonable alternative (Delaney & Huselid, 1996; Kim, 2005). There is evidence of a strong correlation between perceptual and objec- tive measures at the organizational level, although there is always some doubt regard- ing perceptual measures of performance (Kim, 2005). In this study, we used one item to measure performance, “the perception that the organization is doing good work,” utilizing a 5-point Likert-type scale, ranging from totally disagree (1) to totally agree (5). The use of only one indicator is clearly an important limitation, but at least we are able to characterize how employees assess their organization’s performance.

Vermeeren et al. 183

Leadership style. To measure the influence of leadership style, we used two latent vari- ables that correspond to the distinction between stimulating and correcting leadership (cf. Bass & Avolio, 1994; Likert, 1961; McGregor, 1960). The specific items can be found in the appendix. All answers were given on a 5-point Likert-type scale ranging from totally disagree (1) to totally agree (5).

Descriptive and reliability statistics were computed for the individual items and the two scales (see Table 1). To show the strength of the associations between the items, Table 1 displays the correlations matrix. The correlations are all significant at the 1% level.

To test whether the distinction between the two leadership styles is supported by the data, we performed confirmatory factor analysis using AMOS version 16. Unlike exploratory factor analysis, in which only the number of factors and observed vari- ables are specified, confirmatory factor analysis permits specification and testing of a more complete measurement model (Byrne, 2001). The simultaneous estimation of the measurement models allows us to examine the relationships between the items and their latent constructs as well as the relationships among the constructs themselves. Furthermore, one also receives information on whether the items load only on their target variable, or whether they load on the other dimension as well (unidimensionality of factors). Based on the results of the confirmatory factor analysis, the measurement model was modified where necessary. The modifications made to enhance the model included the introduction of error correlations.2 Reasons for error correlation include respondents’ inability to answer questions, a lack of effort on the part of the respon- dents to provide the correct answers or other psychological factors, or inadequately worded questions on the survey questionnaire (Byrne, 2001).

For evaluating the convergent validity of the measurement model, Anderson and Gerbing (1988) suggested examining the construct loading and determining whether each estimator’s coefficient is significant. For this model, the regression weights range from .69 to .89 and all are significant (see Table 1). These coefficients may be inter- preted as indicators of the validity of the observed variables, that is, how well they measure the latent dimension or factor. For this model, convergent validity has been achieved. With regard to discriminant validity, we note that the items related to the same construct are always more closely correlated with one another than with the items for the other construct. In addition, Bagozzi and Philips (1982) suggested that discriminant validity in SEM is achieved if the unconstrained model has a signifi- cantly lower chi-square value than the constrained model. In this study, the chi-square value for the unconstrained model (CMIN 1711.061/df 62) appears to be significantly lower than that for the constrained model (CMIN 2722.621/df 63). Thus, for this model, discriminant validity has been achieved. Finally, the R2 in Table 1 is a measure of reliability, which indicates how consistently the observed variable measures the latent dimension. The explained variance corresponding to the observed variables indicates that the respective factor explains an adequate portion of the variance (between 47% and 78%; Perry, 1996).

The overall fit of the measurement model was tested using absolute and relative fit indices, which indicated a good fit. In general, a chi-square test is used to assess the

184

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Vermeeren et al. 185

sample data in relation to the implied population data. However, there are concerns about using the chi-square test because its probability is sensitive to sample size (Jöreskog, 1993). In larger samples (as in this research), the chi-square test almost always leads to the rejection of the model because the difference between the sample covariances and implied population covariances will lead to a higher chi-square value if the sample size increases.3 As a result, a number of alternative fit measures have been developed (Hu & Bentler, 1999), including the goodness-of-fit index (GFI), the adjusted goodness-of-fit index (AGFI), the normed fit index (NFI), and the compara- tive fit index (CFI). The values for this model were .959 (GFI), .940 (AGFI), .972 (NFI), and .973 (CFI). In the social sciences, a cutoff value of .95 is the prescribed norm (Hu & Bentler, 1999). Based on these fit indices, one can conclude that the model is a good fit. In addition, the root mean square error of approximation (RMSEA) value of .065 indicates that the model is a reasonable fit (Byrne, 2001).

Finally, a traditional measure of scale reliability is Cronbach’s alpha, which mea- sures internal consistency among items on a scale. The Cronbach’s alpha for the stimu- lating leadership scale is .95 and for the correcting leadership scale is .78. Based on these results, one may conclude that the reliability coefficients provide independent corroboration for the results obtained from the use of confirmatory factor analysis. The results show that the distinction between the two leadership styles is supported by the data.

Control variables. Of course, several other variables can affect HRM, job satisfaction, and organizational performance. Therefore, Guest (1999) emphasized that several controls must be in place to take account of individual and organizational factors. Fol- lowing Guest, our control variables are divided into two groups. In the first group, we controlled for individual characteristics (gender, age, and educational level). These controls are based on the assumption that different groups within organizations may be managed differently with the result that their perceptions will be different. Then, we controlled for one important organizational characteristic: organizational size. This control is based on the assumption that large organizations pursuing improved perfor- mance have more resources with which to provide their employees a large HRM policy.

We coded gender as a dummy variable (1 = female). The category of age was sub- divided into five categories (1 = 15-24 years; 2 = 25-34 years; 3 = 35-44 years; 4 = 45-54 years; and 5 = 55 years and older). Educational level was also subdivided into five categories (1 = primary education; 2 = lower vocational education; 3 = higher general secondary education, preparatory academic education; 4 = higher vocational education, candidate exam; and 5 = scientific education). Finally, the category of orga- nizational size was subdivided into seven categories (1 = fewer than 100 employees; 2 = 101-500 employees; 3 = 501-1,000 employees; 4 = 1,001-5,000 employees; 5 = 5,001-10,000 employees; 6 = 10,001-20,000 employees; 7 = more than 20,000 employees). Because we used secondary data analysis, we were restricted to these categories in measuring the control variables.

186 Review of Public Personnel Administration 34(2)

Results

The hypothesized relationships among the variables were analyzed using SEM. This statistical methodology allows us to test the full conceptual model in a simultaneous analysis. In addition, SEM enables us to analyze simultaneously the direct and indirect relationships among the dependent and independent variables. Finally, SEM also enables us to compare different models (Byrne, 2001). We built our SEM model using AMOS version 16. To examine whether the data were normally distributed, the index of multivariate kurtosis was considered. Bentler (2005) has suggested that, in practice, values above 5.00 are indicative of nonnormality. Our data have a score of 4.94, which indicates that it is normally distributed.

In Table 2, the means, standard deviations, and correlations of the study variables are presented.The results show that, of the 10 HR practices, employees observed, on average, the use of 4 HR practices within their organizations. The most frequently observed HR practice was job evaluation conversations, and the least frequently observed practice was job rotation. Employees were generally satisfied with their jobs. The average score for this variable on a 5-point scale was 3.78. Moreover, employees perceive the organization to be doing good work, with the average score on a 5-point scale being 3.48. Finally, the average score for the stimulating leadership style was 3.46 on a 5-point scale; the average score for the correcting leadership style was 3.47.

To test the proposed relationships, a causal structure was posited that resulted in a structural equation model. First, we tested the hypothesis that job satisfaction acts as a mediating variable in the relationship between HRM and organizational performance. A distinction can be made between fully mediated and partially mediated models (Wood, Goodman, Beckman, & Cook, 2008). Therefore, in SEM, two different mod- els must be created. In the first model, the direct relationship between HRM and orga- nizational performance was fixed at zero. In the second model, the direct relationship and indirect relationship between HRM and organizational performance were esti- mated. By using the chi-square difference test and other global-fit measures, one can test the models against each other. In Table 3, the fit indices are presented. The chi- square difference test implies that the relationship between HRM and organizational

Table 2. Means, Standard Deviations, and Correlations (N = 6,253).

M SD 1 2 3 4 5 6 7 8 9

(1) Gender .42 .493 — (2) Age 3.57 .958 −.223** — (3) Educational level 3.18 1.169 .071** −.116** — (4) Organizational size 2.76 1.269 −.009 .007 .159** — (5) HRM 3.73 2.04 .004 .045** .093** ,175** — (6) Job satisfaction 3.78 .933 .037** −.014 .008 −.016 .150** — (7) Organizational performance 3.48 .956 −.011 .005 .040** .043** .206** .319** — (8) Stimulating leadership 3.46 .914 .008 −.002 −.008 .000 .251** .416** .443** — (9) Correcting leadership 3.47 .854 −.007 .014 −.045** .016 .188** .240** .325** .649** —

Note. HRM = human resource management. **p < .01.

Vermeeren et al. 187

performance is partially mediated by job satisfaction. Furthermore, the partially medi- ated model shows a better model fit than the fully mediated model.In Figure 2, the partially mediated model is shown. Only the statistically significant relationships are described (with a significance level of .01). The numerical scores on all lines indicate standardized regression coefficients (β), and the scores in brackets are the explained variances.

Second, we analyzed the effect of leadership style on HRM. We assumed that the amount of HR practices perceived by employees would be influenced by their supervi- sors’ leadership styles. We distinguished between stimulating and correcting leader- ship to test our hypotheses that (a) a stimulating leadership style has a positive effect on the amount of HR practices used within an organization and (b) a correcting leader- ship style has a negative effect on the amount of HR practices used within an organiza- tion. The overall model fit was tested using several fit indices. The model fit values were .999 (GFI), .997 (AGFI), .996 (NFI), and .998 (CFI), implying that the model was a very good fit. In addition, the RMSEA, with a value of .015, also indicated that the model is a good fit.The model in Figure 3 is the result. Only the statistically signifi- cant relationships are shown (with a significance level of .01). The numerical scores on all lines indicate standardized regression coefficients (β), and the scores in brackets are the explained variances. The results show that a stimulating leadership style has a significantly positive effect on the implementation of HR practices, supporting Hypothesis 2a, whereas a correcting leadership style appears to have no effect on the amount of HR practices used, rejecting Hypothesis 2b.

Table 3. Fit Indices for the Fully and Partially Mediated Models.

Model χ2 df GFI AGFI NFI CFI RMSEA

Fully mediated model 189.389 7 .990 .970 .874 .877 .065 Partially mediated model 8.670 6 .999 .998 .994 .998 .008

Note. GFI = goodness-of-fit index; AGFI = adjusted goodness-of-fit index; NFI = normed fit index; CFI = comparative fit index; RMSEA = root mean square error of approximation.

Age

Organizational Size

Educational Level

Job Satisfaction (.024)

HRM (.038)

Organizational Performance

(.127)

.053

.074

.163

.158 .294

-.044 .020

.162

-.118

.158

Figure 2. Result of structural equation modeling.

188 Review of Public Personnel Administration 34(2)

When we compare the model in Figure 2 with the model in Figure 3, we see that the first model shows a statistically significant and positive relation between HRM and organizational performance. However, the model in Figure 3 shows that this relation becomes weaker when the variables related to leadership style are included. Therefore, we also examined whether supervisors’ leadership style influences the relationship between HRM and performance (moderating effect). However, these effects do not appear to be significant. These results imply that leadership style has its own, indepen- dent, effect.

Finally, model validity was achieved through cross-model validation. Camilleri (2006) suggested attaining cross-validation in three phases. In the first phase, data are divided into two data sets. One data set consists of a random selection of 20% of the data collected from respondents; the second data set consists of a random selection of 80% of the data collected. In the second phase, SEM by means of a path analysis that calculates the structural fit index (measured by R2) is conducted for both the data sets. The third phase consists of examining the differences between the calculated structural fit indices obtained for each data set. The extent of model validity is determined by the similarity in the variance accounted for by each data set. The results of the cross-model validation are presented in Table 4. Given the fact that the differences in the explained variances are small, the cross-model validation provided satisfactory results.

Age

Organizational Size

Educational Level

Job Satisfaction (.177)

HRM (.102)

Organizational Performance

(.229)

.054

.076

.163

.050 .161

-.025 .029

.086

-.116

.159

Stimulating Leadership

Correcting Leadership

.252 .439

-.054

.310

.069.649

-.045

Figure 3. Result of structural equation modeling.

Table 4. Results of Cross-Model Validation Showing R2 for the Three Samples.

Predicted variable Full sample 20% sample 80% sample Difference in R2 for 20%-80% sample

HRM .102 .109 .100 .009 Job satisfaction .177 .197 .173 .024 Organizational performance .229 .240 .231 .009

Note. HRM = human resource management.

Vermeeren et al. 189

Discussion

Looking at the main independent and dependent variables, we expected that a supervi- sors’ leadership style has an influence on the implementation of HR practices. Our research provides empirical evidence that a supervisor’s leadership style, and specifi- cally a stimulating leadership style, is important to the HRM–performance relation- ship within an organization. When we compare Figure 2 with Figure 3, we see that adding “leadership” importantly increases explained variance. As such, the results of this study emphasize the important role of supervisors in the HRM and performance model, as was previously suggested by Wright et al. (2005) and Paauwe (2009), among others. When we look at the results in greater detail, we find evidence of the positive relationship between a supervisor’s leadership style and the HR practices conducted within the organization, as previously shown by Purcell and Hutchinson (2007) and Zhu et al. (2005). More specifically, a stimulating leadership style is demonstrated to have an important effect on the implementation of HR practices. In contrast, a correct- ing leadership style appears to have no effect on the amount of HR practices used. Thus, our hypothesis that a stimulating leadership style has a positive effect on the amount of HR practices used within an organization is confirmed, whereas our hypoth- esis that a correcting leadership style has a negative effect on the amount of HR prac- tices used within an organization must be rejected. Nevertheless, the results are in line with the research discussed by Guest (1987), which argued that a stimulating leader- ship style (theory Y) could be linked to soft HRM (HRM focusing on the development, motivation, and commitment of employees). Furthermore, it would be interesting in future research to test Guest’s (1987) idea that theory X (with a correcting role for the supervisor) is linked to hard HRM (a focus on rewards and determinations of whether employees do what the organization requires). To study this relationship, data must include such elements of HRM as performance-related pay. An additional interesting result is that a stimulating leadership style appears to be very important to employees’ degree of satisfaction, while the correcting leadership style has a negative influence on job satisfaction. Finally, a stimulating leadership style and a correcting leadership style have a positive effect on organizational performance, although the effect of the stimu- lating leadership style is much larger.

Our research also provides empirical evidence for the mediating relationship between HRM and organizational performance. The results indicate a direct effect and an indirect effect of HR practices on organizational performance, as is already assumed in the Paauwe and Richardson (1997) model. Our analysis shows that when employees perceive a more elaborate use of HR practices, organizations do achieve a better score for their performance. Moreover, when more HR practices are used, employees expe- rience greater satisfaction, which positively influences organizational performance. This study adds to previous research by confirming the hypothesis that job satisfaction acts as a mediating variable in the relationship between HRM and organizational per- formance. This important finding provides more insight into employees’ reactions to HRM and its effect on organization performance. These reactions have been largely disregarded in previous research (Boselie et al., 2005).

190 Review of Public Personnel Administration 34(2)

Looking at the results in greater detail, we see that older employees and employees with higher education levels perceive a greater use of HR practices. This suggests that different groups within organizations (e.g., younger and older employees) are man- aged differently. In addition, organizational size has a relatively large effect on HRM, as can be concluded from its high beta weight. In line with Guest’s (1999) assumption, this finding indicates that the HRM policy of organizations is influenced by such con- textual variables as the size of the organization.

Finally, our study supports the idea that a focus on HRM as a method of increasing organizational performance is also relevant in the public sector. Based on this study, conclusions regarding the relationship between HR practices and organizational per- formance in private organizations (cf. Paauwe, 2009) also appear applicable to public sector organizations. In line with the results of previous research (e.g., Gould-Williams, 2003; Kim, 2005; O’Toole & Meier, 2008), public organizations appear to be more successful if they value their employees and if they utilize a more extended set of HR practices. In addition, this study illustrates the important role supervisors play in this relationship in the public sector.

Conclusion

In the introduction, we stated that public sector performance has become an increas- ingly important issue over the past three decades. Several innovations in the field have promised to increase the quality of public service while reducing its costs. However, research into the contributions of HRM to these developments has been scarce. Our main research question, therefore, was “To what extent is the relationship between HRM and the performance of public organizations mediated by job satisfaction, and what is the influence of a supervisor’s leadership style on the implementation of HR practices?” Based on the data and arguments presented in this study, one can conclude that a positive relationship exists between HRM and organizational performance in the public sector. Specifically, by studying the relationships among HRM, job satisfaction, and organizational performance in a single model, this research showed that job satis- faction partly mediates the relationship between HRM and organizational perfor- mance. Moreover, this study showed that the choice to use HR practices is influenced by a supervisor’s leadership style.

Despite these findings, the limits of this article suggest lines of further research. This study used a cross-sectional data set restricted to Dutch municipalities. Its find- ings, therefore, have limitations with respect to internal and external validity. A longi- tudinal data set would increase internal validity, as such data enable researchers to make stronger causal claims. HRM–performance research is dominated by cross- sectional research, which generates considerable discussion of questions regarding “what came first?” (Guest, 2011). Are public organizations more successful if they value their employees, or do public organizations value their employees if they are more successful? Or are both propositions true? A similar problem can be observed with respect to the relationship between job satisfaction and performance (Judge et al., 2001; Taris & Schreurs, 2009). For this reason, a longitudinal research design would

Vermeeren et al. 191

be preferable in further research. With respect to external validity, we have examined the HRM and performance relationship in the public sector by focusing on Dutch municipalities. More research is needed to determine whether the HRM–performance relationship holds for different kinds of public sector organizations and different coun- tries. Finally, the selection of the data source (survey) may have influenced some of the results. The use of only one survey instrument may create distortions in the data, in particular regarding common method bias (Podsakoff & Organ, 1986). This is spe- cifically a question with respect to the connection between job satisfaction and organi- zational performance. The strong relationship between these two variables may be attributable to the fact that employees were asked to rate their job satisfaction and their perceptions of organizational performance. This potential problem highlights the importance of replicating our research, ideally by using objective performance indicators.

This study not only generates recommendations to further enhance HRM and per- formance research in the public sector. Based on its observations, this study also pro- vides possible starting points for improving the performance of public organizations through their employees. To increase organizational performance, it appears important that organizations invest in employees’ needs by implementing HR practices. Moreover, this study suggests that the stimulating leadership style is very important to employee satisfaction, while the correcting leadership style negatively influences job satisfaction. This suggestion further implies that when a public sector organization wishes to acquire an involved and motivated staff, its supervisors must assume a stim- ulating role. Based on our findings, attention to a supervisor’s leadership style appears to be a prerequisite for successfully implementing HRM within an organization. More specifically, this study indicates that there is an important role for supervisors to play in implementing HRM, developing a satisfied workforce, and enhancing organiza- tional performance.

Appendix

Correcting Leadership

•• X1: My supervisor keeps an eye on my work to check if I do my work well. •• X2: My supervisor tells me when I do not do my work well. •• X3: My supervisor controls whether work is finished on time.

Stimulating Leadership

•• Y1: My supervisor is aware of employees’ welfare. •• Y2: I get enough support from my supervisor. •• Y3: My supervisor allows people to cooperate well. •• Y4: My supervisor lets me know if she or he is satisfied with my work. •• Y5: My supervisor consults his staff about issues that are important to them. •• Y6: My supervisor provides support as needed. •• Y7: My supervisor creates a work climate in which I can develop new ideas

about my work.

192 Review of Public Personnel Administration 34(2)

•• Y8: My supervisor is accessible. •• Y9: My supervisor lets us participate in conversations that are relevant to me

and my colleagues. •• Y10: My supervisor protects me from high work pressure.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

1. Although there is some disagreement about the precise relationship between job satisfac- tion and performance, the literature generally assumes that greater job satisfaction is asso- ciated with better individual and organizational performance (Judge, Thoresen, Bono, & Patton, 2001; Taris & Schreurs, 2009).

2. Error correlation between X1 and X2 is .137 and between Y10 and Y11 is .326. 3. Chi-square value = N × difference between sample covariances and implied population

covariances.

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Author Biographies

Brenda Vermeeren is a PhD student at the Department of Public Administration at Erasmus University Rotterdam. Her research is focused on the relationship between human resource management (HRM) and Performance of Public Organizations.

Ben Kuipers is an assistant professor at the Department of Public Administration at Erasmus University Rotterdam and director and consultant at Performability. His research and consulting work focus on strategic human resource management, change management, and team perfor- mance in private and public organizations.

Bram Steijn is a full professor of HRM in the public sector at the Department of Public Administration at Erasmus University Rotterdam. His current research is focused on public service motivation, job satisfaction, and HRM and performance in the public sector.

Advances in Developing Human Resources

14(4) 566 –585 © 2012 SAGE Publications

Reprints and permission: sagepub.com/journalsPermissions.nav

DOI: 10.1177/1523422312455610 http://adhr.sagepub.com

455610ADHR14410.1177/1523422312455610Adva nces in Developing Human ResourcesKim and McLean

1Texas A&M University, College Station, TX, USA 2McLean Global Consulting, Inc., USA

Corresponding Author: Sehoon Kim, Educational Administration and Human Resource Development, Texas A&M University, 4226 TAMU College Station, TX 77843, USA Email: [email protected]

Global Talent Management: Necessity, Challenges, and the Roles of HRD

Sehoon Kim1 and Gary N. McLean2

Abstract

The Problem. Despite increasing attention in business, talent management in global contexts has not been explored adequately in HRD. Most studies related to global talent management explain only part of it and do not provide an integrative understanding of what is going on globally in talent management in an HRD perspective. The Solution. This article proposed an integrative conceptual framework for global talent management that involves the necessity, challenges, and roles of HRD. Considering cross-cultural viewpoints and multinational enterprise issues in HRD, the study analyzed why talent management is necessary and the challenges of developing talent. Finally, proposals were made for developing global talent and roles for HRD researchers and practitioners. The Stakeholders. The results of this study will provide insights or guides for researchers interested in talent management/development and HR practitioners involved in a multinational enterprise.

Keywords

talent management, globalization, talent development, high potential, HRD challenges, HRD roles

Kim and McLean 567

Since The War for Talent (Michaels, Handfield-Jones, & Axelrod, 2001), business practitioners have enthusiastically embraced talent management (TM; Iles, Preece, & Chuai, 2010; Lewis & Heckman, 2006). Despite the recent shrinking employment caused by the economic recession, interest in talent in business has extensively increased with the unprecedented global competition (Athey, 2008; Scullion, Collings, & Caligiuri, 2010) because such talent is regarded as generating great ben- efits and value for the organization (Tarique & Schuler, 2010). The business para- digm has shifted from marketing and finance to “talentship” (Boudreau & Ramstad, 2005, p. 21).

As the world economy continues to globalize, organizations continue to increase their international profits and intensify their overseas investments (Guthridge & Komm, 2008). As this occurs, the importance of global talent in organizations has also been increasing. Managing and developing necessary global talent are regarded as among a company’s priorities for sustainable growth (Collings, McDonnell, & Scullion, 2009; Guthridge & Komm, 2008). According to an Ernst & Young survey that included more than 150 global executives among Fortune 1000 companies, 65% of respondents answered that how to deal with global TM would highly impact their organization (Leisy & Pyron, 2009). For this reason, many organizations are making great efforts to acquire, develop, and retain talent worldwide (Boudreau & Ramstad, 2005; Lewis & Heckman, 2006).

In spite of the recent enthusiastic attention to this theme in business, academic activities on managing global talent have not yet fully recognized its importance (Burbach & Royle, 2010). The concept and features of TM have not been clearly and sufficiently explored (Collings et al., 2009; Lewis & Heckman, 2006), and many stud- ies still debate its identity, definition, and scope (Collings & Mellahi, 2009; Farndale, Scullion, & Sparrow, 2010; Iles et al., 2010; Lewis & Heckman, 2006; McLean, 2010; Tarique & Schuler, 2010). Although there is a view in which TM may be a business fad or “old wine in new bottles” (Iles et al., 2010, p. 126), how to deal with talent is critical for organizations to develop in a sustainable way, no matter what we call TM (McLean, 2010). Most studies on TM were found in human resource management (HRM), although development, as focused in HRD, is one of the key elements in the TM pro- cess, and its importance is being increasingly emphasized (Collings & Mellahi, 2009; Tarique & Schuler, 2010). When it comes to a global context, only a few studies on global TM were found. However, these studies, which focused on concepts or cases, explained only part of the global TM approaches and did not provide an integrative understanding of what is going on globally in TM in an HRD perspective.

The purpose of this article is to identify the necessity and challenges of TM in a global context and suggest roles for HRD. First, studies on TM not only in HRD but also in related disciplines were investigated. Then, consideration was given to cross- cultural and multinational enterprise (MNE) issues in HRD, specifically exploring why TM is necessary and the challenges of managing and developing talent in a global setting. Finally, proposals were made for developing global talent and roles for both HRD researchers and practitioners. In this study, we supported the perception of

568 Advances in Developing Human Resources 14(4)

McLean (2010) and Collings and Mellahi (2009) that TM is not a very new concept but should be reemphasized by HR professionals to identify key positions and develop a talent pool, a critical step for successful TM. In addition, findings in this study focused on global TM, which is different from TM in a domestic context.

The results of this study will contribute to further academic and practical studies on global talent by providing guidelines for strategic approaches to managing and devel- oping talent in a global environment.

Talent Management As TM is a relatively new topic in HR, first introduced as a unified concept in the 1990s, there is still ambiguity and a lack of agreement in terms of its definition, nature, and features (Collings & Mellahi, 2009; Garrow & Hirsh, 2008; Iles et al., 2010; Lewis & Heckman, 2006). However, recently, several studies on TM have helped define its attributes, scope, and aspects in both empirical and conceptual ways.

There are three perspectives on TM prevalent in organizations (Lewis & Heckman, 2006). The first looks at TM as typical HR roles and activities. In this perspective, HR provides the same approaches to talent, however that gets defined, through recruiting, development, and retention as is done with employees not defined as talent. The second view emphasizes how to secure and develop internal talent by building talent pools. This is generally related to organizational staffing and career planning. In the third perspective, talent in the organization is identified not for certain jobs or through specific succession plans but through recognizing outstanding individual performance. In this view, organizations evaluate employees according to their performance and try to retain the talent of the A grades and eject the C and D grades. In addition to these three perspectives, there are talent pipeline approaches, such as succession planning and leadership development, that are regarded as TM (Iles et al., 2010).

By borrowing the concept from a supply chain perspective, Cappelli (2008) pro- posed four principles for operating TM more effectively. The four principles are hiring or developing talent according to the business strategy as an investment; reflecting the uncertain future; improving the cost-efficiency of employee development; and balanc- ing individual and the organizational interests in development investment.

Integrating recent definitions and perceptions on TM, Collings and Mellahi (2009) proposed a definition for TM emphasizing its strategic aspects:

Activities and processes that involve the systematic identification of key posi- tions which differentially contribute to the organization’s sustainable competi- tive advantage, the development of a talent pool of high potential and high performing incumbents to fill these roles, and the development of a differenti- ated human resource architecture to facilitate filling these positions with com- petent incumbents and to ensure their continued commitment to the organization. (p. 304)

Kim and McLean 569

In the same vein, Collings and Mellahi (2009) also developed a theoretical model of strategic TM. In their model, the firm’s performance results from a dif- ferentiated HR architecture. To develop and utilize internal talent, an organization should recognize which positions are critically related to its performance. Once a talent pool of high potentials and high performers is formed by developing or recruiting talent, the pivotal positions should be filled from the pool. These organi- zational efforts in HR architecture are intended to enable talent to retain work moti- vation, organizational commitment, and extra-role behavior, which results in sustainable performance in the organization. Organizations that deal with human resources in more than one country, however, need different strategies and action plans for talent from domestic organizations. That is, global TM should involve an integrated strategy of TM activities at a global level in order for the business suc- cess of global organizations that goes beyond general HR assignments (Collings et al., 2009). Thus, global TM is defined as an organization’s efforts to acquire, develop, and retain talent to meet organizational strategies on a global scale, given not only the differences between organizations but also their global and cultural contexts (Scullion et al., 2010; Tarique & Schuler, 2010). Based on the interna- tional human resource management context, Tarique and Schuler identified chal- lenges that influence global TM activities, dividing the challenges into “exogenous” and “endogenous” drivers (p. 126). External challenges include globalization, workforce demographic changes, and shortages of talent, and internal ones incor- porate regional specification, retaining talent, and competencies.

HRD in a Global Context The more globalization, the more studies and practices in international HRD are needed (Wang & McLean, 2007). To support organizational work successfully in this broad and complicated business environment, HRD professionals need a global per- spective and understand differences in cultures among countries (McLean, 2006). However, the majority of the studies on cross-cultural training have looked at culture not as the context but as the content of the training and focused on how to prepare expatriates (Osman-Gani & Zidan, 2001).

Global HRD can promote the global success of the organization because the perti- nent development of human capital produces an invaluable organizational resource (Marquardt, Berger, & Loan, 2004). When organizations become globalized, roles and activities of HRD will also be influenced by different cultures, ways of doing business, physical locations, environments, and languages. If HRD relies on the same approaches in a global situation as used in a domestic setting, this may result in inappropriate behaviors and decisions by employees. This can then lead to lower performance or even business failure. Therefore, HRD professionals should know how to deal with different cultures and utilize global HRD interventions needed for organizations involved in international or global activities (Marquardt et al., 2004; McLean, 2006). These global interventions include virtual or cross-cultural team building, cultural

570 Advances in Developing Human Resources 14(4)

self-awareness, cross-cultural training, sharing stories, joint ventures, global job assignments, and blending of diverse cultures (McLean, 2006).

DeSimone, Werner, and Harris (2002) listed the four major elements included in most cross-cultural training programs: (a) raising the awareness of cultural differ- ences, (b) focusing on ways attitudes are shaped, (c) providing factual information about each culture, and (d) building skills in the areas of language, nonverbal com- munication, cultural stress management, and adjustment adaptation skills (p. 639). Cross-cultural training needs to develop knowledge, skills, and attitudes for interac- tions with people from different cultures (Osman-Gani & Zidan, 2001).

Method To conduct a comprehensive review of literature, we identified keywords and related terms for a database search: talent management, talent development, global talent management, global talent development, global human resources, international human resources, and cultural training. The search was conducted at the end of 2010. The identified literature was screened by types of publication (scholarly article, research report, and book) and published time (only after 1990), with an initial abstract review. Relevant literature (n = 82) was identified through Google Scholar and several academic databases, such as Academic Search Complete, Business Source Complete, Eric, Human Resource Abstracts, and ABI/INFORM Global, and by refer- ences found in the resulting articles.

In spite of the few studies on TM or global TM in HRD, we found a number of relevant literature related to TM in HRM and industrial psychology. The identified studies were analyzed to identify how academic studies and practical activities related to global TM have been conducted and how to maximize developing global talent in the organization.

Why Is Global TM Necessary? Global TM includes organizational activities to acquire, develop, and retain talent for organizational strategies on a global scale, taking account of cultural contexts (Scullion et al., 2010). Despite the recent global economic recession that has resulted in massive downsizing and restructuring in business, the majority of firms still recog- nize TM as one of the top organizational priorities (Tarique & Schuler, 2010). The reasons global TM is necessary can be identified as expansion of a market to the world, deficiency of talent, and competition for talent.

Expansion to the World As companies step into a global environment, they face competition for talent, one of the most valuable assets in the organization (Bartlett & Ghoshal, 1998). A Hewitt survey of more than 500 companies in the United States revealed that 45% of the

Kim and McLean 571

organizations were currently doing or within 3 years would do business in other countries (Gandossy & Kao, 2004). The success of the organization in a global set- ting depends on how the resources are used and how talent is supported to commit to the work and organization (Marquardt et al., 2004). Marquardt et al. (2004) clas- sified organization types according to global status: domestic, international, multina- tional, and global. They found that each stage had different strategies, products, competitors, markets, structures, and cultural sensitivity. Because of these different corporate activities, globalized organizations need talent who can make a profit in a wide scope of environments (Farndale et al., 2010). Moreover, infrastructure around TM in other regions may be different from the headquarters country of the organiza- tion (Leisy & Pyron, 2009; Odell & Spielman, 2009).

According to a McKinsey Global Survey, most global companies expect that emerging global markets will provide not only more production but also talent and innovation and plan to look for talent in local markets (44%) or from developed mar- kets and deploy them to emerging markets (35%; Dye & Stephenson, 2010). To iden- tify, acquire, develop, and retain global talent, global organizations need new types of competencies, recruitment strategies, development approaches, career paths, and reward systems that are different from the domestic environment (Marquardt et al., 2004). Global TM is not merely about managing physical bodies of smart people but also about dealing with human capital and the intangible resources of individual knowledge and skills (Odell & Spielman, 2009).

Deficiency of Talent The U.S. labor force will decline as Baby Boomers retire and the birth rate decline (Athey, 2008). As in the United States, several reports and studies warned that work- ing populations in most developed countries were rapidly decreasing, and this phe- nomenon would spread over the world in a few years (Gandossy & Kao, 2004; Hayutin, 2010; Leisy & Pyron, 2009; Orr & McVerry, 2007; Strack, Baier, & Fahlander, 2008; Tucker, Kao, & Verma, 2005). According to Hayutin, for the past 20 years, the working-age population grew rapidly in Africa, the Middle East, and Asia, but, for the coming 20 years, the increase would slow in most countries. Most devel- oped countries are projected to face a workforce shrinkage, and the European working population will decline by 50 million (Hayutin, 2010).

The shortages of labor will result in a serious deficiency of talent (Strack et al., 2008) that can cause low productivity in organizations (Dye & Stephenson, 2010). This deficiency will affect the state of talent pools in organizations. Relying only on traditional HR activities may be an ineffective way to retain enough talent because of the limited resources in the labor market. For a sustainable talent supply, organizations need to emphasize not only acquiring and retaining high performers but also develop- ing internal employees who have potential and encouraging them to increase their abilities (Athey, 2008; Strack et al., 2008). In addition, the development activities should not be ad hoc or haphazard but strategically planned to align organizational goals and vision (McDonnell, Lamare, Gunnigle, & Lavelle, 2010).

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Competition for Talent

The lack of labor may be one of the major reasons why more intense competition to acquire and retain talent happens (Strack et al., 2008). However, a lack of critical skills that employees have is also regarded as one of the key factors that increase the need for talent globally (Odell & Spielman, 2009; Zheng, 2009) because skill defi- ciency is related to a high rate of turnover (Zheng, 2009). As global competition for talent heats up, organizations that do not prepare ways to acquire, develop, utilize, and retain talent may fall behind in a race for global business. Therefore, organizations need to consider carefully the actions they take for a sustainable talent supply (Bhatnagar. 2008).

Challenges of Developing Global Talent Given the geographic and cultural scope in which global organizations work, we found three primary challenges that may occur while developing global talent: ethno- centric strategy, worries about global mobility, and barriers between headquarters and subsidiaries countries.

Ethnocentric Strategy One of the critical challenges global organizations can encounter when they deal with talent development is ethnocentrism, defined as a belief that other groups are inferior to one’s own (Barger, 2008). Many organizations are not aware that what they have carried out may not be applicable to other regions, cultures, or countries and believe that standardization through an ethnocentric approach is more efficient than consider- ing difference. Indeed, many HR practitioners struggle with a balance between global formalization or standardization and local flexibility or customization (Begley & Boyd, 2003). With global standardization (formalization), organizations may expect efficiency and fairness in HR policies and activities (Begley & Boyd, 2003). However, regional strategies for talent—hiring regional talent and developing them taking into account local contexts—can result in better performance with lower costs than central strategies because each region or country may have a different perception and condi- tion of talent (Tarique & Schuler, 2010).

For instance, Boussebaa and Morgan (2008) discovered that one of the challenges of a multinational company in France, with headquarters in the United Kingdom, was the difference in understanding of talent in headquarters. According to their study, talent has a meaning of someone who has potential among the U.K. companies, whereas talent in France means someone who has already developed and proven their abilities. Failure to take into account the different understanding of concepts of talent brought about a failure of the talent development system projects led by the British company in France.

Moreover, ethnocentric perceptions of global organizations can result in less prep- aration for global assignments of their talent, which is associated with expatriate

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failure (Choi, 2002; Shen & Lang, 2009; Yeaton & Hall, 2008). According to Osman- Gani (2000), U.S. expatriates generally deemed that a 3-day predeparture training is most appropriate, whereas the majority of German, Japanese, and Korean expatriates considered at least a 1-week-long training as a minimum. In fact, 16% to 40% of U.S. expatriates fail their assignment and return prematurely (Wagner & Hollenbeck, 1995), which is an apparent contrast to a 5% to 10% global assignment failure of non- U.S. expatriates (Dowling, Welch, & Schuler, 1999).

Worries About Global Mobility Through the McKinsey Global Survey, Dye and Stephenson (2010) found that 35% of global companies considered deploying talent employed in the host country to other countries. This means a substantial number of people will work for years in an environment where the culture, language, law, business style, and weather may be different from their home country. Although the experience of global assignments can be invaluable for learning and development, many employees assigned to work in another country may be demotivated not only because of the new environment they will face but also because of worries about career disadvantages after repatriation to their home country (Guthridge & Komm, 2008).

Marquardt et al. (2004) reported that 20% of the repatriates left their organization within 1 year after they came back and 50% quit the job within 1 to 3 years. Mismanagement of expatriates can cause tremendous damage to organizations. The reasons why expatriates fear global mobility are that they think they lose promotion opportunities, there may be limited positions for them when they come back, the overseas assignment may be a result of a demotion, few colleagues welcome them back (Allen & Alvarez, 1998), and they hear about negative repatriate experiences from their colleagues (Farndale et al., 2010). In addition to the situations that may happen in the organization, reverse culture shock of the expatriates themselves, as well as their families, can result in maladjustment (Marquardt et al., 2004).

De Cieri, Sheehan, Costa, Fenwick, and Cooper (2009) found that national identity with their country of birth and quality of life in the home country are also factors that can influence global mobility of employees, either in a positive or negative way. A strong sense of national identity is likely to strengthen the desire for repatriation. In terms of quality of life in the home country, they contended that people tend to desire to relocate and stay in another country if the life in the host country is better than in the home country.

Barriers Between Headquarters and Subsidiaries When the goals of the global organization’s headquarters are not in alignment with the subsidiaries, the regional or local strategies and activities may not be in accord with the overall organization’s purposes (Bjorkman, Barner-Rasmussen, & Li, 2004). If the relationship between headquarters and subsidiaries is distant, local branches

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will be interested in developing talent only for their performance, not for the overall success of the organization. In this regard, subsidiary managers may recruit, assess, and develop talent with a standard according to their own strategies and competen- cies rather than that of the headquarters (Mellahi & Collings, 2010). Sometimes the best employee in the organization can be a victim of abandonment when he or she is positioned between the headquarters and subsidiary (Gandossy & Kao, 2004). Furthermore, this defensive behavior can bring about a reduction in effectiveness of global TM strategies (Farndale et al., 2010).

When barriers between headquarters and subsidiaries are strong, a lack of appropri- ate information on talent in the subsidiaries can cause a failure of the global TM sys- tem, which may result in limited opportunities for talent at subsidiaries to work in the upper management team at headquarters (Mellahi & Collings, 2010).

Mellahi and Collings (2010) also found that a reason for a lack of communication between headquarters and subsidiaries is culture. In regions that have a strong power distance culture, such as China, Japan, and South Korea, people tend to regard saving face for someone who is in a higher position as very valuable. Therefore, employees cannot easily report their opinions to headquarters even though mismanagement of talent may happen in the subsidiary.

HRD Roles for Success in Global TM Wooldridge (2006) warned that relying heavily on a particular approach to talent can no longer be beneficial for the organization and can even adversely affect the future of the organization. Too much emphasis on attracting and retaining talent, and ignor- ing or neglecting development or deployment, may cause significant harm to the organization (Athey, 2008; Pfeffer, 2001). For this reason, many global organizations have changed their talent supply strategies from hiring outsiders to developing insid- ers (Boussebaa & Morgan, 2008; Osman-Gani & Chan, 2009), although this does not mean that external transfusion of talent has been ignored. The roles of HRD are critical for global organizations, not only to support talent in order to generate better performance but also to develop employees who have global potential that will lead to a sustainable talent supply for the organization. For successful global TM, we sug- gest roles for HRD in the areas of balancing centralized and decentralized strategies, developing global competencies, creating structured global talent development, and conducting global team building.

Balancing Centralized and Decentralized Strategies Although global organizations may have headquarters that have central power and roles, their global subsidiaries are normally led by managers from diverse areas (Marquardt et al. 2004). That is, on the one hand, globally unified strategies, struc- tures, and corporate cultures are emphasized; on the other hand, locally specified and customized approaches cannot be ignored. Thus, when a global organization makes

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a decision, the uniqueness of each local environment should be taken into account throughout the vision and strategies of the global organization (Harvey, Fisher, McPhail, & Moeller, 2009).

To enhance the organization’s homogeneous culture and strategies, many compa- nies send managers from headquarters to sites around the world to communicate cen- tral values and cultures (Marquardt et al., 2004). HR managers from headquarters can help incorporate and utilize global TM systems at the subsidiaries, taking into account the local context. Beechler and Woodward (2009) mentioned the Coca Cola Company as an example of an effective strategy of bringing local talent to headquarters and developing their leadership ability. After one or one and a half years, they go back to the subsidiaries as a manager and spread the company’s core values and culture to the local firms. The shared global TM system and its strategies will make it possible for global organizations to have a balanced supply, structured deployment, and develop- ment in terms of talent (Mellahi & Collings, 2010).

Using the same values, systems, and even HR resources tends to provide organiza- tional efficiency, such as flexibility for deploying talent, active communication and cooperation between organizations, and cost saving. However, talent developed for the specific market and culture can result in better performance. A decentralized approach that develops and delivers localized or acculturated interventions (Marquardt et al., 2004) can be effective for local organizations and employees. For example, from a study with Japanese MNCs, Arreglel, Beamish, and Hébert (2009) found that the regional-level effects provided positive influences, such as expanded localized knowl- edge, strong social relationships, and transfer of knowledge and practices due to geo- graphic proximity. Talent hired and developed through localized strategies may be more productive at the local businesses than at headquarters or in another region. When local HR practitioners adopt a TM system and interventions created by head- quarters, the success of the system and interventions will depend on how well the system is localized, taking account of the local culture and business context (Boussebaa & Morgan, 2008).

Developing Global Competencies Global competencies are indicators that global organizations utilize to manage global talent (Farndale et al., 2010). The competencies need to be used to align and integrate activities and processes with regard to TM in each subsidiary and region in order to maximize the synergy of organizational functions, as well as performance excellence of talent (Heinen & O’Neill, 2004). The role of HRD here is to identify the competen- cies and provide effective interventions to develop the abilities of global talent.

Marquardt et al. (2004) introduced six global competencies as special abilities for global employees: cultural self-awareness, global perspectives, language, tolerance for ambiguity and differences, cultural flexibility, and strong communication skills. Among these competencies, the need for cognitive abilities is related to a global mind- set. A global mindset, which is the ability to develop individual criteria that can be

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applied to different regions, nations, and cultures and properly utilize those criteria in a different context, is the most critical for the sustainable success of global organiza- tions (Begley & Boyd, 2003). Tarique and Schuler (2010) found three types of required global talent competencies through several related studies. First, general business competencies, which can apply to most companies, are needed for global talent. The second is cross-cultural competencies divided into the competencies we can easily learn, such as knowledge about the culture, and ones that take a long time to obtain, such as characteristics or attitudes common within the culture. The last type is compe- tencies for creating and managing knowledge required for business performance. Global competencies can be utilized not only for training and development but also for global recruitment, assessment, career paths, staffing, and reward and recognition (Marquardt et al., 2004).

Creating Structured Global Talent Development Global organizations need a structured development system to grow their employees’ abilities for business competitiveness (Marquardt et al., 2004). The structured devel- opment system should be connected to business strategies and goals, reflect needs for global talent development strategies, identify action steps, and analyze inner and outer factors and resources.

Global leadership development, succession plans, and expatriate training can be included in a global development system (Odell & Spielman, 2009). Although these interventions are different from each other, the key activities used may be similar. Systematic cross-cultural training and encouraging global assignments may be exem- plary activities.

Global talent who work with people from different cultures and backgrounds need cross-cultural training because the training helps employees not only obtain knowl- edge, skills, and attitudes needed for challenging assignments (Osman-Gani & Zidan, 2001) but also adapt to a culturally different region or country, which is essential for a successful international task (DeSimone et al., 2002). Despite much research on cross-cultural training, McLean (2006) pointed out that many training programs deal- ing with cross-cultures are still “atheoretical” (p. 211) and emphasize mainly what to do or not to do. Relying only on cognitive information and linguistic skills can be less effective for people who are preparing for global tasks (Guthridge & Komm, 2008; McLean, 2006). To make a cross-cultural training program effective, trainees should have learning experiences in terms of acculturation and be encouraged to have a “cul- tural milieu” (Marquardt et al., 2004, p. 44) in the program (Stanek, 2000).

Work experience in a challenging assignment is one of the most effective ways of developing employees (Meyers, Paunonen, Gellatly, Goffin, & Jackson, 1989). This effective approach is also applied to development in a global setting, providing thor- ough support for completing global assignments (McLean, 2004). These assignments can be coordination, computational, or creative tasks so that global talent can develop interpersonal skills, problem-solving abilities, mediating abilities, business insights,

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and specific subject knowledge and techniques (Harvey et al., 2009). Experiences in different cultures and countries also enable global talent to develop cultural awareness and tolerance (Guthridge & Komm, 2008). In spite of its merit, a global assignment is the least extensively used intervention among global organizations because it takes time to produce desirable results, and employers may be afraid of providing continual opportunities that may fail and damage their business (McDonnell et al., 2010). However, HRD needs to create opportunities for challenging global assignments and establish a supportive environment for talent so that they can improve their capacities and commit to their job and organization (Hiltrop, 1999).

These development interventions provided for talent should be strategically con- nected to the global TM system. McDonnell et al. (2010) discovered that a number of global organizations did not allocate learning resources to their talent, although they had formalized global development programs. HRD practitioners should recognize what interventions they have and how they can help talent to develop their organiza- tional performance.

Conducting Global Team Building A global team, a group of employees from different cultures or countries who work together to do a particular job (McLean, 2006), is regarded as an integrated, strategic, and generative approach to managing global talent (Beechler & Woodward, 2009). As telecommunicating technologies are developed, global teams can be organized as not only face to face but also virtual teams in which group members can work in different places at the same time using a web-chat or web-cam (McLean, 2006). Regardless of type, a global team is expected to provide organizations with capa- bilities to respond to global challenges, solving complex global problems quickly (Marquardt et al., 2004).

According to Marquardt et al. (2004), a global team influences global TM in sev- eral positive ways. First, a global team can encourage an atmosphere of managing talent from all over the world. If employees in an organization are culturally and nationally diverse, the employees can help stop or reduce the effects of making a biased decision when recruiting, deploying, promoting, and developing people. Second, organizations have an opportunity to find and develop their high potentials scattered over the world. Through a global team, talent located in a subsidiary can have a chance to show their capability and to be provided with equal support for development from the organization. Third, while dealing with challenging global tasks, talent can enlarge perspectives, increase global capacities, and gain global managerial skills.

However, a global team does not always guarantee successful results. Several studies have pointed out the ineffectiveness of a globally heterogeneous team because of communication problems, behavioral conflicts, and discriminations (Chatman, Polzer, Barsade, & Neale, 1998; Ely & Thomas, 2001; Thomas, 1999). In this regard, Thomas (1999) found that the difference in effectiveness between a culturally

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homogeneous and heterogeneous team is dependent on the nature of the tasks. He contended that homogeneous teams perform better with highly structured or overall assessment tasks, whereas diverse teams show more confidence and proficiency with tasks involving creative solutions and idea generation. In addition to the nature of the tasks, he argued that individual cultural characteristics also influence the result of the effectiveness of diverse teams. That is, the more individuals with collectivistic char- acteristics a team has, the more effective the performance of the team is because a collectivistic person tends to be more receptive and regards group harmony as impor- tant. However, those from a collectivistic culture may be less creative because it is more subject to groupthink.

To enhance the effectiveness of a global team, global organizations need to pro- vide organizational activities, as well as develop their systems and cultures, so that the organizations can be open to diversity without any unhealthy interpersonal con- flict and difficulty (Beechler & Woodward, 2009). Diversity training, coaching, and mentoring programs can help develop both knowledge and attitudes for working with diverse colleagues (McGuire, 2011). Cultural facilitation and mediation by HRD professionals may reduce the incidences of prejudice and misbehavior in the first meeting (McLean, 2006). When individuals are willing to learn about and accept differences, a diverse team can generate a synergic effect and provide better performance (Ely & Thomas, 2001). Interpersonal problems can also be addressed by clarifying team goals, roles and responsibilities, or procedures and processes (Burke, 2011). Efforts for global team building should be a long-term approach in a systemic way so that organizations sustain the interventions and develop their cul- tures (McGuire, 2011).

Conceptual Framework for Global TM On the basis of the findings explored, we created a conceptual framework for the necessity, challenges, and roles of HRD in terms of global TM (Figure 1). First, global TM plays a critical role for global organizations because of the globalized business environment, shortage of talent, and competition for talent. Second, ethnocentric per- spectives in terms of talent development, concerns of talent about global mobility, and gaps between headquarters and subsidiaries can be challenges in developing global talent. Third, for success in global TM, HRD needs to balance strategies between centralized and decentralized, develop global competencies, create a structured devel- opment system, and support global team building.

Discussion Despite the limited literature directly relevant to global TM, we found sufficient information to present the necessity, challenges, and HRD roles through reviewing literature related to HRD, HRM, and industrial psychology and synthesizing their contents. Our findings support our initial research assumption that TM is not a

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concept newly created but is reinterpreted HRM/HRD activities focusing on high potentials or high performers (Collings & Mellahi, 2009; Iles et al., 2010; McLean, 2010). Challenges and HRD practitioners’ roles regarding global TM may not be very different from those of general international HRD. However, we believe how to manage or develop global talent is critical for success in global business and HR scholars and practitioners should keep paying attention to matters of global talent.

What we discovered in this article makes several contributions to HRD. First, we disclose a topic that has not received much attention among HRD professionals but inevitably needs their involvement and interest. What HRD can consider and do for talent development in a global context was also identified. In addition, we provided strategic and systematic approaches to developing global talent for HRD professionals extending beyond relying solely on cross-cultural training, the most frequently occur- ring activity in both the field and academy.

This study has limitations. First, only studies written in English were reviewed because of our language and search limitations. Although it appears that the majority of research on global TM has been conducted in the United States, Europe, and coun- tries using English, such as Australia and Singapore, there may be studies or cases in non–English-speaking countries. Second, focusing only on content related to global talent and global HRD limited viewpoints beyond HRD and HRM, although we agree that TM should not be confined to HR. As global talent is emphasized in global busi- ness, identifying, developing, deploying, and retaining talent are no longer only HR’s job but the responsibility of all management from line manager to top executive (McCauley & Wakefield, 2006; Odell & Spielman, 2009). Third, our research focus is limited to for-profit organizations and do not include nonprofit global organizations. Thus, there may be difficulty in applying our findings to different types of global organizations.

Figure 1. Conceptual framework of the necessity, challenge, and HRD roles for global talent management (TM)

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Recommendations for HRD Researchers

There are four recommendations we suggest for HRD researchers. First, HRD researchers need to pay more attention to global TM. Although the

number of articles on TM have rapidly increased since the concept of TM was intro- duced (Iles et al., 2010), more theoretical and practical studies are necessary for estab- lishing TM as a solid academic area within HRD. How to manage global talent has been one of the hot issues among organizations involved in international business or interested in global human resources. However, academic development of TM is still so minimal that what scholars have accomplished for TM does not meet the field’s needs. This leads many organizations to rely mainly on business consultants who may use tools or models not theoretically grounded. For the academic development of global TM, more cases need to be investigated and, based on those case studies, more empirical studies should be conducted. And then, HRD researchers can perform theory-building studies on global TM and examine those theories.

Second, HRD researchers need to be careful when they prescribe roles for HRD in TM. In an actual business situation, dividing HRD from HRM is likely to be mean- ingless because both have the same goal, contributing to organizational performance and have many overlapping tasks under the same umbrella, HR. Thus, it is hard to say that HRD oversees only training functions in TM or that identifying and deploying talent are only HRM’s functions. Rather, to supply the talent the organization needs, HRD must be involved in all processes of TM. For example, when individuals with high potentials need to be developed as leaders, HRD can draw a career map, identify necessary competencies, provide interventions, and evaluate not only TM activities but also the talent themselves.

Third, TM in nonprofit organizations should also be explored. Most studies on global TM are focused on corporations, not other types of organizations, such as non- governmental organizations. Because these organizations have different purposes, structures, and activities, they may need a different definition of talent and a unique process for managing talent.

Fourth, HRD researchers can broaden their perspective on TM to the national level. Most studies on TM in HR deal with the corporate level. Like the discipline of HRD involving community and nation, however, TM at the national level should also be explored by HRD scholars, recognizing a country as an organization. Therefore, a national policy on acquiring, developing, retaining, and utilizing talent, talent flow in a country, and national brain drain versus gain can be exemplary subjects for further studies on national TM. We expect that these studies will show reasons why phenom- ena that corporations cannot control occur, such as a deficiency of talent or incompe- tent employees, and provide appropriate directions for fundamental remedies.

Recommendations for HRD Practitioners Global TM can be a new term and area among HRD practitioners, especially those involved in a global organization. A great deal of attention is necessary when HRD

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practitioners deal with global TM because efforts for managing talent are likely to fail without consideration of the necessities and possible challenges mentioned ear- lier. We recommend the following for HRD practitioners who are preparing to man- age global talent.

First, the meaning of talent should be defined, taking into account the organiza- tion’s business contexts and strategies. Even though organizations do business glob- ally in the same industry, they may have different types of business operations, such as company-owned, joint venture, and outsourced, and the TM approach should be adapted to the business type (Gandossy & Kao, 2004). Misunderstandings can occur when leaders are seen as equal to talent or leadership development is considered the same as talent development. However, a leader can be talent depending on whether the position is critical for the organization’s profit and sustainable development.

Second, TM is a long-term approach. If HRD practitioners expect immediate effects from global TM, the results may be disappointing. Hasty changes in the management plan and system because of expectations for short-term results can cause not only a waste of time and money but also a loss of trust in HR by the organization. Thus, HRD practitioners may need to be cautious with TM, making sure every step of TM works properly and persuade clients who desire instant outcomes of their investment on TM if necessary.

Third, successful global TM needs fairness in the whole process. Once employees question the criteria for selection of talent, the appropriateness of development oppor- tunities, and the timing of deployment or promotion, complaints about the TM system will arise and cause the organization to suspect its effectiveness. Constant communica- tions and clear statements on the policies and processes will help minimize employees’ confusion or misunderstanding about the organizational approach to TM.

Fourth, HRD practitioners should be aware that the process of TM can result in unexpected problems in cultures different from the host culture. For example, while managing the talent pool, designating talent may cause an unpleasant relationship among colleagues in collectivistic cultures. Because people regard group harmony as most desirable in those cultures, both the selected individuals and their colleagues may feel uncomfortable with a public announcement about the results of the selection. Sometimes, employees in the culture refuse to be identified as a talent because of their relationship with their colleagues.

Fifth, best practices or illustrative case studies can be produced and shared in orga- nizational and interorganizational levels in order to be used as a benchmark, develop more appropriate methods and processes related to TM, and enhance abilities of HRD practitioners. When these techniques are used, however, what is common and different from the applying organization should be taken into account.

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

582 Advances in Developing Human Resources 14(4)

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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Bios

Sehoon Kim is a PhD student in the Department of Educational Administration and Human Resource Development at Texas A&M University. He previously worked in the HR field in Korea. His research interests include work hours, talent management, cross-cultural issues, and brain drain.

Dr. Gary N. McLean (Ed.D., Ph.D. hon.) is president of McLean Global Consulting, Inc., a family business. As an OD practitioner, he works extensively globally. He also teaches regu- larly at universities in Thailand, Mexico, and France. He was formerly a senior professor and executive director of international human resource development programs at Texas A&M University and is professor emeritus at the University of Minnesota. He has served as President of the Academy of Human Resource Development and the International Management Development Association. His research interests are broad, focusing primarily on organization development and national and international HRD.

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