The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
7
The Relationship of Knowledge Identification and Creation
with Leadership, Culture and Technology
© 2014 IUP. All Rights Reserved.
Mohnish Kumar*
Knowledge Identification and Creation (KIC) is one of the main knowledge management dimensions which is quantified using the questionnaire developed by Maier and Moseley (2003). This paper tries to find out the relationship and impact of leadership, technology and cultural ethos on KIC. Data from 204 individuals was collected from six organizations. Principal component analysis and multiple regression analysis were applied to test the hypotheses. The theoretical and practical implications are also discussed. The organizational cultural ethos and leadership, along with the technology, influence KIC in a significant manner. Expectancy of a leader is considered negatively as pressure. A non-bossy leader with positive OCTAPACE, along with tailor-made IT services, helps in creating and identifying new knowledge. A non-bossy leader is well accepted by the employees of the surveyed organizations for better KIC. The collaboration and experimentation values need to be promoted along with tailor-made performance support system for improved KIC. The positive organizational cultural ethos of OCTAPACE, along with a good IT system, is a boon in this regard.
* Assistant Professor, Bhim Rao Ambedkar College, University of Delhi, Delhi, Indi a. E-mail: [email protected]
Introduction The importance of knowledge and its uninterrupted creation cannot be overemphasized for the human civilization and its development. Ever since the development of human language, it has become easier for humans to transfer new knowledge to future generations. Since human race is better at learning and retaining knowledge, it survived, grew, and developed better than other animals. With the later development of more advanced languages and writing materials, now knowledge could be stored for posterity.
Those civilizations that had a well-developed culture were able to subsume the less developed civilizations due to better and effective weaponry, war traditions and culture. An inspiring hero or leader like Alexander could shape and sharpen the war traditions and weaponry culture, influencing generations to come to learn and inspire. Similarly, modern organizations, the better ones, survive and prosper and the weaker organizations are consumed or wasted in the path of history.
The world has been in the grip of an unrelenting economic crisis for the past several years. This is forcing the organizations around the world to shut down or lay off the human resources.
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The laying off of employees is a double-edged sword. Though it reduces the fixed cost of salary in the cost of production, it is also making the knowledge of such employees unavailable in the future. Knowledge management may not be a panacea for all ills that hamper the knowledge itself, but it may reduce the extreme cost of such losses through identification of created knowledge to be used in future. Newell et al. (2002) suggested knowledge management for competitive advantage which incorporates identifying, extracting and capturing of knowledge. Drucker (1993) predicted the advent of ‘Knowledge Society’ whose basic resource is ‘Knowledge’, and where the ‘Knowledge Worker’ plays an important role in creating new knowledge.
Debowski (2006) defined knowledge management as the process of identification of new knowledge for the long-term performance and success of organization. Liebowitz and Beckman (1998) assembled the following knowledge processes that form a part of knowledge management.
• Developing new knowledge
• Securing new and existing knowledge
• Distributing knowledge
• Combining available knowledge
Newell et al. (2002) suggested that the process perspective on knowledge management emphasizes that knowledge is socially constructed, that is, knowledge is inherently social and embedded in practice. It defines knowledge in dynamic terms, regarding practice of doing or knowing rather than something static or objective—knowledge which a person possesses.
One of the main dimensions of knowledge management process is Knowledge Identification and Creation (KIC) of new knowledge which includes creativity and innovation. Several authors have proposed and identified several variables that influence the creation and identification of newer knowledge.
The process of KIC begins with transformation of data (isolated facts with no meaning) and information (interpreted data with meaning) into a value-added resource through experience and logical inferences. Knowledge thus becomes an actionable resource in the organization. It provides employees with the ability to perform a particular task or identify hidden trends and unusual patterns within data and information for operational and strategic decision making. Identification and creation of knowledge is often accomplished through interviews, observation, brainstorming sessions, focus groups, portfolio analysis, root-cause analysis, and other similar techniques that generate new ideas and knowledge. These are very often led by experts in the particular domain (Maier and Moseley, 2003).
Kumar (2012) identified organizational culture as a kind of soft force-field that influences the behavior of employees in the organization. It is a kind of boundary wall that gives direction to employees to think, feel, and act as expected by the organization. This is the glue that holds the organization together and presents the organization as a unitary whole to the world.
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Organizational culture describes the collective perceptions, beliefs, and values of employees in the workplace. Individuals learn about the organizational culture from the first day in a new workplace (Debowski, 2006). Organizational cultures strongly influence productivity (Kopelman et al., 1990).
Culture can also be viewed as the accumulated shared learning of a given group, covering behavioral, emotional, and cognitive elements of the group members’ total psychological functioning. For shared learning to occur, there must be a history of shared experience, which in turn implies some stability of membership in the group. Given such a stability and a shared history, the human need for parsimony, consistency, and meaning will cause the various shared elements to form into patterns that eventually can be called culture (Schein, 1992).
Several authors have defined leadership in different ways, ascribing different attributes and functions. Koontz and O’Donnell (1964) defined leadership simply as influence, the art or process of influencing people so that they will strive willingly toward the achievement of group goals. Koontz and O’Donnell (1964) also argued that leadership is the ability of a manager to induce subordinates (followers) to work with confidence and zeal. Roberts and Hunt (1991) also defined a leader as a person whose behavior has a determining effect on the behavior of other group members. Leadership is the interaction among members of a group in which leaders are agents of change. The leader is a person whose acts, more than anyone else’s, affect the motivation and competencies of the group.
Bedeian and Glueck (1983) defined leadership as a term used to describe a category of behavior. According to this view, leadership is a dynamic process in which an individual behaves in a certain manner, thereby influencing others to follow. Thus, leadership is the art of influencing individual or group activities towards achievement of enterprise goals (p. 495). This approach is more appropriate for this research study and has been taken into consideration.
Several earlier studies argued about the interrelationship of cultural ethos, technology and leadership with KIC. Pareek (2006) suggested that some organizations promote creativity and excellence, while other organizations may make people obedient, dependent and conformist. Organizational learning, development, and planned change cannot be understood without considering culture as a primary source of resistance to change and learning—the challenge lies in conceptualizing a culture of innovation in which learning, adaptation, innovation, and perpetual change are the stable elements (Schein, 1992).
It is not only the structural conditions (Starbuck, 1992), but also the cultural conditions that are important for KIC. It is the cultural conditions within a knowledge-intensive firm that primarily promote responsible autonomy (Friedman, 1977) and a workforce that can be trusted to work in the interests of the firm, that is, working autonomously but working very hard and to the best of their abilities (Newell et al., 2002).
Improvements in productivity and quality flow from corporate cultures that systematically recognize and reward individuals, symbolically and materially, for identifying their sense of purpose with the values that are designed into the organization (Willmott, 1993).
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Newell et al. (2002) went on to say that the strong organizational cultures are those that are shared across the firm, strengthening the firm through integration and enhanced productivity. The integration perspective on organizational culture considers organizational culture as a malleable variable to be shaped by the leader of a firm.
Nonaka and Takeuchi (1995) argued that organizational culture can be seen as consisting of beliefs and knowledge shared by members of the organization. Studies of organizational culture have been able to shed light on the organization as an epistemological system. In addition, they have underscored the importance of such human factors as values, meanings, commitments, symbols, and beliefs, and paved the way for more elaborate research on the tacit aspect of knowledge. Furthermore, they have recognized that the organization, as a shared meaning system, can learn, change itself, and evolve over time through the social interaction among its members and between itself and the environment.
DeLong (1997) argued that organizational culture is relevant to a firm which creates, shares, and uses knowledge. He also suggested four ways in which organizational culture influences behaviors central to knowledge creation, sharing, and use.
1. Culture—and particularly subcultures—shape our assumptions about what knowledge is, and, hence, what knowledge is worth managing.
2. Culture mediates the relationships between individual and organization-level knowledge.
3. Culture creates the context for social interaction that ultimately determines the value an organization derives from knowledge.
4. Culture shapes the processes by which new organizational knowledge—with its accompanying uncertainties—is captured, legitimated, and distributed.
The relationship between culture and knowledge is well articulated. Nonaka and Takeuchi (1995) suggested that knowledge is well embedded in the culture itself and different cultures function as knowledge repository for respective civilization. Schein (1992) conceptualized the group learning and suggested that learning occurs not only at the behavioral level but also at an abstract level internally because of the human capacity to abstract and to be self-conscious. Once people have a common system of communication and a language, learning can take place at a conceptual level and shared concepts become possible. The deeper level of learning that gets us to the essence of culture must be thought of as concepts or shared basic assumptions. Nystrom (1979) argued that the probability of success may be increased by establishing and maintaining a creative problem-solving environment. Starbuck (1992) argued that it is very easy for creativity and innovation to be stifled even when the structural conditions are generally supportive of knowledge work tasks. Firms are, therefore, cautioned to try and avoid the development of particular norms and practices that might constrain innovative behavior (Newell et al., 2002).
Nonaka and Takeuchi (1995) argued that while the studies of organizational culture have recognized the importance of knowledge, they have not given it its due place. They pointed out that there seem to be three common shortcomings with this line of research.
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• First, most of these studies have not paid enough attention to the potential and creativity of human beings.
• Second, the human being, in most cases, is seen as an information processor, not as an information creator.
• Third, the organization is portrayed as rather passive in its relation to the environment, neglecting its potential to change and create.
However, this research study tries to locate the ability of the group of knowledge workers to create and innovate in the supporting organizational culture and technology in the hands of able leadership. Some of the studies in India suggest deep-rooted influence of organizational culture on knowledge management. Singh and Sharma (2011) argued that for an organization to have a KM System (KMS), the organizational culture is a key and primary factor and went on to suggest that it is not only the overall knowledge management that is influenced by the overall organizational culture, rather specific stages of knowledge management process are influenced by specific elements of organizational culture.
Knowledge Management and Leadership A leader not only influences the knowledge management process indirectly through the organizational culture but also most of the time a leader provides a creative leadership directly for the knowledge management process. A leader influences organizational culture (Schein, 1992) which itself is an epistemological (i.e., philosophy of knowledge) system (Nonaka and Takeuchi, 1995). Apart from that, a leader influences knowledge creation though his creative leadership skills, and creative thinking is the core of leadership competence. Puccio et al. (2007) argued that Kotter’s (1996) five skills bear a striking similarity to qualities associated with creative people. When a leader is creative, the chances are very high that he/ she may promote a creative culture and ethos in the organization. Kouzes and Posner (1995) research on what leaders do to bring about extraordinary results bears a resemblance to known process practices that bring about creative acts leading to knowledge creation. Puccio et al. (2007) went on to suggest that creative people and effective leaders may not be one and the same, though the ideas or products developed by successful creative people may ultimately influence others or may inspire change. They also highlighted the fact that in today’s complex work and social environments, creativity plays a crucial role in helping leaders to be more effective at facilitating change.
The development of ICTs helped in storing and sharing the ideas and knowledge with all the employees in the organization. The technology per se is very influential for knowledge creation. Castells (1996) pointed out that the current technological revolution emphasizes the application of knowledge and information to knowledge generation and information processing/communication devices, in a cumulative feedback loop between innovation and the use of innovation. The relationship between knowledge management and technology is bidirectional. As technology helps in knowledge management process, e.g., ICT forms the uniform thread behind all knowledge management dimensions. Same way, knowledge management is instrumental in the development of new technologies or technological
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revolutions. Newer technologies or technological revolutions come on the heap of older technology.
However, knowledge management is not only the domain of technology or IT firms rather it is being practiced by almost all firms with different levels of intensity under different names. Knowledge can be managed without even much help of technology, as has been done since ancient times; for example, the most traditional and most basic method of storytelling and suggesting the moral of the story to the kids by their grandparents at home since tim e im m em orial; like Manusmriti traditional texts were passed on orally through generations. Technology has become the enabler and prompter in the whole gamut of knowledge management.
Methodology This study mainly deals with the descriptive and diagnostic research of KIC dimension of knowledge management process. There are several variables that influence the knowledge management process to its core and they may have significant predictive value for the KIC. These variables provide some structural and cultural conditions and sometimes play a very active role for KIC to grow and develop in the organization. Several variables, including leadership, organizational cultural ethos, technology and background variables, are taken into consideration for this research.
The primary objective of this study is to find out the relationship and impact of organizational culture, leadership, background variables, and technology on KIC.
Hypotheses H
01 : There is no relationship between organizational cultural ethos and KIC.
H A1
: There is a relationship between organizational cultural ethos and KIC.
H 02
: There is no relationship between leadership and KIC.
H A2
: There is a relationship between leadership and KIC.
H 03
: There is no relationship between technology and KIC.
H A3
: There is a relationship between technology and KIC.
H 04
: There is no difference among the sectors of organizations on KIC.
H A4
: There is difference among the sectors of organizations on KIC.
H 05
: There is no difference in perceptions of male and female regarding KIC.
H A5
: There is a difference in perceptions of male and female regarding KIC.
H 06
: There is no relationship between the background variables of employees and KIC.
H A6
: There is a relationship between the background variables of employees and KIC.
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Research Design This particular study is basically non-experimental research design having exploratory, descriptive and diagnostic elements. The questionnaire-based primary data has been randomly collected keeping in mind the research objectives, the hypotheses to be tested, and experiences of the similar studies for proper analysis, effective conclusion, and generalization. A self-administered questionnaire has been provided to respondents, i.e., to workers and managers spread across various functional groups and managerial levels from different selected organizations. Data regarding different aspects of an employee’s life related to knowledge management were collected using different measures including background information or antecedent variables and demographic characteristics of that particular employee (given in Appendix). Several organizations were contacted for data collection, including Most Admired Knowledge Enterprise (MAKE) top 10 awardees. A few of them were really interested in this kind of study, however only after “Non-Disclosure Agreement” was signed. The “Non-Disclosure Agreement” specifically suggests that details about the company or the organization will not be disclosed anywhere and in any manner.
Sample Design All those organizations that claim to practice knowledge management form the universe or population of the knowledge management practitioners. The sample selection for this research is basically simple random sampling. First of all, organizations were selected as per their eligibility to be a part of the universe of the knowledge management. Their name could not be given in this research study because of the non-disclosure agreement that the research scholar has signed.
Measures Used The questionnaire begins with a brief introduction of researcher and the topic of the research that is ‘Knowledge Management’. The respondents are requested to give their frank answers, which are best answers for this research. The questionnaire has been divided into the following heads as given in Appendix.
Background information: It includes questions regarding demographic information.
Organizational cultural ethos, viz., OCTAPACE: For collecting the organizational cultural information, the questionnaire suggested by Pareek (1997) was used. It includes 40 questions related to organizational ethos of OCTAPACE (Openness, Confrontation, Trust, Authenticity, Proaction, Autonomy, Collaboration, and Experimentation).
Technological aspect of an organization: This aspect of questionnaire has 5 generic questions related to technology. These questions are applicable even to the most basic of the organization, which may not belong to IT sector.
Leadership pattern questionnaire: This questionnaire is based on Likert and Likert (1976). The 8-point Likert scale is divided into four easily understandable parameters (Very Little: 1, 2; Some: 3, 4; Considerable: 5 ,6 and Very Often: 7, 8) to help the respondents.
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Knowledge management questionnaire: The Knowledge Management Assessment Tool (KMAT) given by Maier and Moseley (2003) is reproduced in the Appendix. This is a diagnostic survey that helps to determine the effectiveness of the knowledge management practices. It is administered on employees to assess the presence of such practices in their work. The respondents rate their level of agreement with 30 statements on five knowledge management dimensions (six for each of the five dimensions of the knowledge management process): identification and creation, collection and capture, storage and organization, sharing and dissemination, and application and use. Individuals completing the assessment simply read each statement and reflect on how it pertains to their work.
Results and Discussion
Econometric Analysis of Data The raw scores of all the questions of every instrument, viz., OCTAPACE, leadership practices, knowledge management dimensions, and the background information of each respondent have been collected and tabulated. These raw scores of each and every question are further processed and transformed into variables, including components and dimensions using standard key of the respective instruments.
The tool of principal component analysis was applied on the raw score of leadership to find out the principal components of leadership. Kumar (2012) and Singh and Kumar (2013) identified four principal components of leadership using factor analysis through principal component analysis on 26 items of leadership as collected using the above-said instrument. Each of these items of leadership deals with particular leadership practices. The factor analysis points out how these items are perceived and grouped by an individual employee. The grouping of these leadership actions is done with the help of principal component analysis. Vera and Crossan (2004) argued about this kind of ingenuity suggesting that most of the work is prescriptive in nature and says little about leadership styles or specific practices through which leaders contribute to knowledge management and culture. The Kumar (2012) and Singh and Kumar (2013) classification of leadership into four principal components suggests that these four groups of leadership activities are valued in the organization. Or it has been observed that employees see or perceive and classify all the leadership behaviors or practices or activities only into these four groups of activities, viz., Leadership1_1, Leadership1_2, Leadership2_1 and Leadership2_2. All the 26 activities were grouped into these four principal components. Three of them were valued very highly and positively and one with expectancy pressure has been present but perceived negatively. It suggests that “Expectancy pressure of a leader” is really abhorred.
Leadership1_1: Expressive Environment Facilitator This principal component of a leader encompasses several leaders’ practices which could be collectively called as expressive environment facilitating practices of a leader. Here, a leader is friendly, open to new ideas, a good listener, allows others to express feelings and ideas, is a role model, and does not dominate and pressurize his followers.
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Leadership1_2: Non-Bossy Leader ‘Leadership1_2’ has items whose common theme is ‘Non-Bossy Leadership’ actions or behaviors where a leader avoids being dogmatic, pontificating, being impatient, dominating, treating his or her subordinates in a condescending manners.
Bass (1990) reviewed several research studies and found evidence concerning the relationship of dominance to leadership. Bass (1990) supported the theoretical concept of non-bossy leader and summarized several studies, a majority of which found leadership to be more dominant (p. 67). Caldwell (1920) also pointed out the strong preference for non-bossy leader by high- school pupils for discipline and order. Similar is the result that comes out of this research study suggesting that the employees expressed preference for leaders who do not act bossy.
Leadership2_1: Democratic Leader This principal component of leadership has a common theme of ‘Democratic Leader’, where a leader avoids imposing a decision, is patient, accepts more blame, uses ‘we’ more often, is open to criticism, encourages disagreements, is willing to take risks, generous in giving credit and recognition, and avoids favoritism.
Leadership2_2: Expectancy Pressure of a Leader
The items under this principal component have the common theme of “Expectancy pressure of a Leader”, where a leader expects best, self or own group importance, encourages people to be innovative and creative, displays confidence and trust in subordinates regardless of what he or she thinks, and shares information frankly.
Kumar (2012) and Singh and Kumar (2013) further divided these four principal components of leadership into mainly three aspects. Expressive environment facilitator and democratic leadership activities or practices form part of the positive aspect of leadership. Expectancy of a leader creates a pressure for an employee which is treated negatively by the employees. Bossy behavior is considered negatively and leaders who avoid bossy behavior are basically leaders who avoid negative practices of bossism.
The leaders’ enthusiasm, interest, and commitment to new ideas and challenges encourage creativity. The supportive leadership is seen in the willingness to take risks, to provide recognition to success, and to clarify what was needed. The leaders accepted failure without destructive criticism and avoided excessive evaluation. Such leaders did not dwell on the status quo (Bass, 1990).
For the data collection on organizational culture, a questionnaire given by Pareek (1997) was used. Pareek (1997) argued that various terms are being used in the context of organizational culture, e.g., values, ethics, beliefs, ethos, climate, environment, and culture. The culture-related concepts can also be seen as multi-level concepts. The core (first level) is the values, which give a distinct identity to a group. This is the ethos of the group. The Random House Dictionary defines ethos as “the fundamental character or spirit of a culture…. Dominant assumptions of people or period” (Pareek, 1997).
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Ethos can be defined as the underlying spirit or character of an entity or group and is made up of its beliefs, customs, or practices. At the base of ethos are core values. The eight important values relevant to institution building are “Openness, Confrontation, Trust, Authenticity, Proaction, Autonomy, Collaboration, and Experimentation”. The acronym came out to be OCTAPACE (Pareek, 1997).
The eight dimensions of OCTAPACE were compacted into a single variable of ‘Over- All-Culture’ using the principal component analysis. Similarly, all the five variables or questions of technology were transformed into one composite variable named ‘All-Technology’ using principal component analysis. The major advantage of using principal component analysis is to get one composite variable that represents all the underlying questions. It helps in understanding the overall impact of all those particular variables at the same time on the dependent variable in the regression analysis.
The principal component multiple regression analysis was used to find the relevant predictors and the extent of their predicting ability. Initially, KIC dimension of knowledge management was taken as dependent variable, and four principal components of leadership (Kumar, 2012), eight OCTAPACE ethos, five technology variables and relevant background variables were incorporated for modeling of the data. Again, the principal components of these variables, viz., ‘Over-All-Culture’ for OCTAPACE, ‘All-Technology’ for technology and four principal components of leadership, are taken as independent variables for the KIC dependent variables in the principal component multiple regression analysis for the modeling.
For calculation of gender-wise and sector-wise differences in the attributes, dummy variables were created and multiple regression equations were run to know the gender and sectorial differences in KIC.
Dummy Variables For calculation of gender differences, a dummy variable named ‘dumvar gender’ was calculated which has two values of ‘0’ and ‘1’. ‘0’ stands for male and ‘1’ stands for female, as shown in Table 1.
Frequency Percent Valid Percent
Valid 0 171 83.8 83.8
1 33 16.2 16.2
Total 204 100.0 100.0
Table 1: Dummy Variable for Gender
For calculation of sectorial differences, two dummy variables named ‘dumvar sec 1’ and ‘dumvar sec 2’ were created. The variable named ‘dumvar sec 1’ stands for the IT sector organizations and the variable ‘dumvar sec 2’ stands for infrastructure sector organizations, except power. The base organizations operate in power sector, as shown in Table 2. These dummy variables have been used in the multiple regression equation to find the gender as well as sectorial differences in the perception of employees regarding KIC.
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Table 2: Dummy Variables for Sector-Wise Distribution of Organizations
Dumvar Sec 1 – Dumvar Sec 2 – No. of Remarks IT Sector Infra. Sector Responses
Except Power
Organization A 0 0 100 Base-Power
Organization B 1 0 38 IT Org.
Organization C 1 0 30 IT Org.
Organization D 0 1 25 Infrastructure
Organization E 0 1 8 Infrastructure
Organization F 1 0 3 IT Org.
Total 71 33 204
Table 3: Descriptive Statistics
Mean SD N
KIC 24.21 5.089 204
Leadership1_2 0.0000000 1.00000000 204 Leadership2_2 0.0000000 1.00000000 204 Collaboration 13.72 2.189 204
Experimentation 13.14 2.376 204 Q3.tailor electronic performance supports system 2.96 0.748 204
KIC Regression For the KIC dimension of knowledge management process, five independent variables (Leadership1_2, Leadership2_2, Collaboration, Experimentation, and the third technology item “tailor electronic performance support system”) were identified, as shown in Table 3.
All the correlation coefficients, as shown in Table 4, among all the variables, are highly significant at 1% level, except the correlation coefficient between Leadership2_2 and the third technology item “tailor electronic performance support system”, which is significant at 5% level. All the correlation coefficients among the independent variables are relatively small but the correlation coefficients between dependent variables and independent variable are relatively medium and large, as expected to explain as much variance as possible. Leadershsip2_2 has negative, significant and relatively small correlation coefficients with remaining independent variables but relatively high with dependent variable. Negative correlation coefficients of Leadership2_2 are quite general and interesting phenomenon of this research. The small, negative, and significant (at 5% level) correlation coefficient between Leadership2_2 and the third technology item “tailor electronic performance support system”, suggests that there is an expectancy pressure on a leader to create a more generalized, homogeneous and ready-made technology and not a tailor-made performance support system. The small but significant correlation coefficients among the predictors suggest that our predictors are measuring different things and there is no collinearity.
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Table 4: Correlations
Pearson KIC 1.000 0.430 –0.399 0.541 0.597 0.451
Correlation Leadership1_2 0.430 1.000 –0.487 0.228 0.263 0.259
Leadership2_2 –0.399 –0.487 1.000 –0.228 –0.262 –0.158
Collaboration 0.541 0.228 –0.228 1.000 0.512 0.243
Experimentation 0.597 0.263 –0.262 0.512 1.000 0.288
Q3.tailor electronic performance support system 0.451 0.259 –0.158 0.243 0.288 1.000
Sig. (1-tailed) KIC – 0.000 0.000 0.000 0.000 0.000
Leadership1_2 0.000 – 0.000 0.001 0.000 0.000
Leadership2_2 0.000 0.000 – 0.001 0.000 0 .012
Collaboration 0.000 0.001 0.001 – 0.000 0.000
Experimentation 0.000 0.000 0.000 0.000 – 0.000
Q3.tailor electronic performance support system 0.000 0.000 0.012 0.000 0.000 –
K IC
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Table 5: Variables Entered/Removedb
Model Variables Entered Variables Removed Method 1 Q3.tailor electronic performance support system, Enter
Leadership2_2, Collaboration, Leadership1_2, Experimentationa
Note: a All requested variables entered; b Dependent Variable: KIC.
Table 5 suggests that all the above variables have been incorporated into the model using “enter method” after finding the appropriate variables by forward and backward method of regression.
In Table 6 R is the value of the multiple correlation coefficient, i.e., 0.747 between the predictors and the outcome. The high multiple correlation coefficient of the value +0.747 suggests that there is good overall fit of the regression model. The R2 of the model is 0.558 which suggests that 55.8% of the variance in the KIC is explained by the model based on the sample. The R2 (55.8%) of this model refers to moderately substantive magnitude of relationship. However, the same model has adjusted R2 of 54.7% which tells us that the 54.7% of the variance in KIC would be accounted for if the model had been derived from the population from which the sample was taken. The adjusted R2 indicates that 54.7% of the
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variance in the dependent variable, i.e., KIC, can be predicted from these five predictors, viz., the third technology item “tailor electronic performance support system”, Leadership2_2, Collaboration, Leadership1_2, and Experimentation (Morgan et al., 2011). In this model, the shrinkage is 55.8 – 54.7 = 1.1. It is a mere shrinkage of 1.1 that suggests that if the model were
Table 7: ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 2934.843 5 586.969 50.041 0.000a
Residual 2322.510 198 11.730
Total 5257.353 203
Note: a Predictors: (Constant), Q3.tailor electronic performance support system, Leadership2_2, Collaboration, Leadership1_2, Experimentation; b Dependent Variable: KIC.
Table 6: Model Summaryb
1 0.747a 0.558 0.547 3.425 0.558 50.041 5 198 0.000 1.979
Model R R2 Adjusted
R2
Std. Error of
the Estimate
R2
Change F Change df1 df2
Sig.
F Change
Durbin- Watson
Change Statistics
Note: a Predictors: (Constant), Q3.tailor electronic performance support system, Leadership2_2, Collaboration, Leadership1_2, Experimentation; b Dependent Variable: KIC.
derived from the population rather than a sample it would account for approximately 1.1% less variance in the outcome. The Durban-Watson value of 1.979 which is near to 2 is quite acceptable.
The ANOVA table (in Table 7) shows that F is 50.041 and is statistically significant. This indicates that these five predictors significantly combine together to predict KIC.
As per Table 8, we have
KIC = 2.443 + 0.803 × Leadership1_2 – 0.729 × Leadership2_2 + 0.583 × Collaboration + 0.690 × Experimentation + 1.589 × the third technology item “tailor electronic performance support system”
Technology and Ethos Till now individual technology and individual ethos items were taken into consideration for prediction of KIC, to have a combined impact of all technology items and all organizational cultural ethos, their principal components were considered for further analysis.
The principal component multiple regression equation was calculated to investigate the best predictors of KIC involving all the technological variables as principal component named ‘All- Technology’, all organizational culture ethos as another principal component named ‘Over-all-
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IF Culture’ along with two principal components of leadership, viz., Leadership1_2 and Leadership2_2 (Table 9). The basic objective behind incorporating the principal components of all cultural ethos and technological variables as another principal component is to predict more about the knowledge management dimensions and knowledge types.
All the correlation coefficients (in Table 10) among all the variables of the above simultaneous regression equation are relatively moderate and small, highly significant at the significance level of 1% and positive, except with Leadership2_2 which has negative correlation coefficients with all the variables (dependent and independent). The relatively small to moderate and highly significant correlation coefficients suggest that the likelihood of multicollinearity is quite less. Table 11 suggests that all the above variables have been incorporated into the model using ‘enter method’.
The multiple correlation coefficient (in Table 12) of these independent variables on KIC is +0.708. The high multiple correlation coefficient suggests that there is good overall fit of the regression model. The R2 of the model is 0.502, which suggests that almost 50% of the variance in the KIC is explained by the model based on the sample. The R2 (50.2%) of this model refers to moderately substantive magnitude of relationship. However, the same model has adjusted R2 of 49.2% which suggests that 49.2% of the variance in KIC would be accounted for if the model had been derived from the population from which the sample was taken. The adjusted R2 indicates that 49.2% of the variance in the dependent variable, i.e., KIC, can be
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
21
Table 9: Descriptive Statistics
Mean SD N
KIC 24.21 5.089 204
Leadership1_2 0.0000000 1.00000000 204
Leadership2_2 0.0000000 1.00000000 204
All-Technology 0.0000000 1.00000000 204
Over-all-Culture 0.0000000 1.00000000 204
Table 10: Correlations
KIC Leadership Leadership All- Over-all- 1_2 2_2 Technology Culture
Pearson Correlation KIC 1.000 0.430 –0.399 0.408 0.652
Leadership1_2 0.430 1.000 –0.487 0.234 0.339
Leadership2_2 –0.399 –0.487 1.000 –0.315 –0.311
All-Technology 0.408 0.234 –0.315 1.000 0.410
Over-all-Culture 0.652 0.339 –0.311 0.410 1.000
Sig. (1-tailed) KIC – 0.000 0.000 0.000 0.000
Leadership1_2 0.000 – 0.000 0.000 0.000
Leadership2_2 0.000 0.000 – 0.000 0.000
All-Technology 0.000 0.000 0.000 – 0.000
Over-all-Culture 0.000 0.000 0.000 0.000 –
N KIC 204 204 204 204 204
Leadership1_2 204 204 204 204 204
Leadership2_2 204 204 204 204 204
All-Technology 204 204 204 204 204
Over-all-Culture 204 204 204 204 204
Table 11: Variables Entered/Removed
Model Variables Entereda Variables Removed Method
1 Over-all-Culture – Enter Leadership2_2 All-Technology Leadership1_2
Note: a All requested variables entered.
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201422
Table 12: Model Summaryb
1 0.708a 0.502 0.492 3.628 0.502 50.103 4 199 0.000 1.865
Model R R2 Adjusted
R2
Std. Error of
the Estimate
R2
Change F
Change df1 df2 Sig.
F Change
Durbin- Watson
Change Statistics
Note: a Predictors: (Constant), Over-all-Culture, Leadership2_2, All-Technology, Leadership1_2; b Dependent Variable: KIC.
predicted from these four predictors comprising principal components, viz., Leadership2_2, Leadership1_2, All-Technology and Over-all-Culture (Morgan et al., 2011). In this model, the shrinkage is 50.2 – 49.2 = 1.0. It is a mere shrinkage of 1.0% that suggests that if the model were derived from the population rather than a sample it would account for approximately 1.0% less variance in the outcome. The Durbin-Watson value of 1.865 which is near to 2 is quite acceptable, suggesting that the assumption of independent errors is tenable.
The ANOVA table (in Table 13) shows that F is 50.103 and is statistically significant even at 1% level of significance. This indicates that these four predictors significantly combine together to predict KIC.
Table 13: ANOVAb
Model Sum of Squares df Mean Square F Sig.
1 Regression 2637.982 4 659.496 50.103 0.000a
Residual 2619.371 199 13.163
Total 5257.353 203
Note: a Predictors: (Constant), Over-all-Culture, Leadership2_2, All-Technology, Leadership1_2; b Dependent Variable: KIC.
Table 14 shows that all the four principal components, viz., two components of leadership, culture and technology, are significantly contributing to the equation for predicting KIC. The resulting model is:
KIC = 24.206 + 0.874 × Leadership1_2 – 0.604 × Leadership2_2 + 0.624 × All-Technology + 2.580 × Over-all-Culture
Again, the dummy variables were introduced in the multiple regression analysis to find out any sectorial difference (Table 15) among the organizations belonging to different sectors and gender differences (Table 16) as follows.
The t-value of ‘dumvar sec 1’ (Table 15) is highly significant even at 1% level. This suggests that the organizations belonging to IT sector are significantly different from the
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
23
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IF power sector organization. They are not only different but are better than the power sector organization in the area of KIC. Similarly, t-value of ‘dumvar sec 2’ is non-significant suggesting that infrastructure sector organizations are not significantly different from power sector organizations in the area of KIC. Similarly, the t-value of ‘dumvar gender’ (Table 16) is non-
significant, suggesting that there is no significant difference among male and female employees’ perception about the KIC in their respective organizations.
Hypotheses Testing The null hypothesis H
01 : There is no relationship
between organizational cultural ethos and KIC is tested using various statistical methods. The positive and highly significant correlation coefficients between organizational cultural ethos of OCTAPACE and KIC suggest that there is a relationship between organizational cultural ethos and KIC. Other than the correlation coefficients, some of the OCTAPACE variables were incorporated as predictors of KIC in the multiple regression analysis. Along with that, the principal component multiple regression analysis was also calculated for KIC as dependent variable and the principal component of all OCTAPACE variables as one of the independent principal component variables named ‘Over-all- Culture’. The presence of this principal component in principal component multiple regression analysis suggests that they do influence the KIC and there is a relationship between them. Thus, the null hypothesis H
01 is rejected
and the alternate hypothesis, H A1
: There is a relationship between organizational cultural ethos and KIC, is accepted.
The null hypothesis H 02
: There is no relationship between leadership and KIC is tested twice using correlation coefficient and principal component multiple regression analysis. All the
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201424
correlation coefficients are highly significant, positive, and moderate in the correlation coefficient matrix involving four principal components of leadership and KIC. In the principal component regression analysis, two of the principal components of leadership are involved as predictors for KIC. The results of these two statistical techniques, when used in the testing of this null hypothesis, suggest that null hypothesis H
02 is
rejected. Thus, the alternate hypothesis H A2
: There is a relationship between leadership and KIC is accepted.
The null hypothesis H 03
: There is no relationship between technology and KIC is tested using principal component multiple regression analysis. For KIC, two different multiple regression equations were calculated: one involving individual items of technology questionnaire and other involving the principal component of technology named “All-Technology”. The individual items of technology, i.e., “We design and tailor our electronic performance support systems to meet our learning needs” got incorporated. Also, the principal c o m p o n e n t o f t e c h n o l o g y ‘A l l -Te c h n o l o g y ’ positively contributed to KIC. Thus, the null h y p o t h e s i s H
03 i s r e j e c t e d a n d t h e a l t e r n a t e
hypothesis H A3
: There is a relationship between technology and KIC is accepted.
The null hypothesis H 04
: There is no difference among the sectors of industry on KIC is tested by introducing and using two dummy variables for three different sectors as independent variables into the respective multiple regression analysis involving KIC as dependent variable. The IT sector organizations are significantly different from power sector organization in KIC. However, infrastructure sector organizations other than power sector are not significantly different from power sector organization regarding KIC. So, it can also be inferred that IT sector organizations are significantly different than the infrastructure sector organizations. So, there is sectorial difference on KIC. Thus, the null hypothesis H
04 is rejected and the
alternate hypothesis H A4
: There is difference among sectors of industry on KIC, is accepted.
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IF
N ot
e: a D
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V ar
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IC .
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
25
The null hypothesis H 05
: There is no difference in perceptions of male and female regarding KIC is tested by introducing and using one dummy variable for the gender of the respondents as independent variable in the respective multiple regression analysis involving KIC as dependent variable. In the multiple regression analysis involving KIC as dependent variable, there is no significant difference between the perceptions of male and female respondents about KIC. Thus, the null hypothesis H
05 is accepted and the respective alternate hypothesis H
A5 is rejected.
The null hypothesis H 06
: There is no relationship between the background variables of employees and the KIC is tested by introducing most of the variables in the multiple regression equations. However, out of so many background variables, none of the variables was able to get into multiple regression equations. Thus we accept the null hypothesis, H
06 and reject the
alternate hypothesis H A6
.
With all the hypotheses tested using statistical techniques, the above conclusions have been reached. On the basis of above statistical results and conclusions, the following empirical and practical implications are arrived at.
Empirical and Practical Implications The simultaneous multiple regression was conducted to investigate the best predictors of KIC. The following five variables, viz., Leadership 1_2 : ‘Non-Bossy Leader’, Leadership2_2: ‘Expectancy pressure of a Leader’, ‘Collaboration’ ethos, ‘Experimentation’ ethos and one technology item named “Q3. We design and tailor our electronic performance support systems to meet our learning needs”, were combined together to predict KIC. All the five variables significantly predict KIC, F (5, 198) = 50.041, p < 0.001. The adjusted R2 (0.547) indicates that 54.7% of the variance in the dependent variable, i.e., KIC, can be explained by the model. According to Cohen (1988), this is a large effect.
Leaving ‘Expectancy Pressure of a Leader’, all the independent variables have positive impact on KIC. Without any expectancy and bossy behavior of a leader, employees generally easily collaborate with one another and work as a team on any problem and experiment on it to solve any problem or knowledge creation. In this whole process of problem solving, the tailor-made performance support system helps positively. The higher level of standardized beta coefficient of the ethos ‘Experimentation’ in the regression equation confirms and supports beyond doubt the argument that experimentation helps in KIC by playing a major
Table 16: Coefficientsa
1 (Constant) 24.029 0.389 61.787 0.000 23.262 24.796
dumvar gender 1.092 0.967 0.079 1.129 0.260 –0.815 2.999
Unstandardized Coefficients
Standardized Coefficients
Note: a Dependent Variable: KIC.
Model
B Std. Error
Beta t Sig.
Lower Bound
Upper Bound
95% Confidence Interval for B
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201426
role. This endeavor of ‘Experimentation’ is also supported by collaboration ethos and tailor- made performance support system.
Similarly, the principal component multiple regression equation was calculated to investigate and find the significant principal components as predictors of KIC. The combination of four variables, viz., Leadership 1_2: ‘Non-Bossy Leader’, Leadership2_2: ‘Expectancy pressure of leader’, ‘All-Technology’ and ‘Over-All-Culture’ predict KIC in a statistically significant manner, F (4, 199) = 50.103, p < 0.001. All the four variables significantly predict KIC. The adjusted R2 (0.492) indicates that 49.2% of the variance in the dependent variable, i.e., KIC, can be explained by the model. This is a large effect. The standardized coefficients of beta for all the independent principal components suggest that ‘Over-All-Culture’ influences the KIC much more and far ahead than other variables like leadership and technology. Positive cultural ethos like OCTAPACE influences KIC more than anything else. Under its influence, the chances are very bright for creativity, invention, and innovation in the organization. Technology and leadership play a significant but secondary role in KIC.
The dummy variables are used to understand the sector-wise/sector-specific difference among the organizations regarding the functioning of this dimension of knowledge management. IT sector organizations are significantly different from the power sector organizations. They are not only different but are better than the power sector organizations in the area of KIC. Similarly, infrastructure sector organizations are not significantly different from power sector organizations in the area of KIC. Similarly, gender-wise difference in respective perceptions about KIC was also calculated. There is no significant difference between perceptions of male and female employees about the KIC in their respective organizations.
Conclusion KIC, as an important dimension of knowledge management, has a very strong relationship with leadership, organizational culture and technology. Of all the four components of leadership, mainly two components of leadership, along with organizational culture and technology, influence the KIC in a significant manner. Under the expectancy-free and non-bossy leadership practices with collaboration and experimentation ethos in the presence of tailor-made electronic performance support system, employees create and identify newer knowledge. Collectively, in the presence of positive OCTAPACE organizational cultural ethos and good IT system, expectancy-free and non-bossy leadership practices help in the organizational objective of KIC. IT sector organizations are more involved in KIC than infrastructure sector organizations. Male and female employees do not see differently about the creation and identification of new knowledge in their respective organizations as they are involved in a similar process.
On the basis of this study, the following recommendations may be incorporated by organizations in their policy.
• All the organizational ethos of OCTAPACE, viz., openness, confrontation, trust, authenticity, proaction, autonomy, collaboration, and experimentation, are positive
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
27
ethos. The top management needs to work on them and promote it throughout the organization. Leaders need to be trained to promote it as leadership and organizational culture and ethos have bidirectional relationship. These organizational ethos variables have very significant impact on KIC and all OCTAPACE variables need to be promoted throughout the organization.
• Leaders should avoid bossy behaviors in their practices. The avoidance of bossy behaviors can improve the organizational culture and thus influence the KIC in a positive way directly as well as indirectly through organizational culture and ethos.
• Leaders should avoid expecting too much from the employees; rather a leader should sit together with the employees and jointly set the targets or goals as well as check points. It not only reduces the expectancy pressure of a leader but also promotes democratic values in the organization. This is nothing but practicing of Management By Objective (MBO) in the organization. This influences the KIC directly and indirectly through improving OCTAPACE organizational ethos and culture.
• All the technological variables are important and they provide basic technological infrastructure for the knowledge management process to flourish in the organization. However, a few of them influence more than others. Tailor- made electronic performance support system specific to the organizational needs and full access to data, information, and knowledge as per the job requirements influence KIC in the organization and help develop it as a ‘Knowledge Organization’. Organizations need to work on that aspect of technology than buying a generalized-off-the-shelf technology from the market.
Limitations: Most of the limitations about this study were concerned with the sampling and survey-based method of data collection and its generalization.
• Most of the time, the general items or questions are put into the standardized questionnaire so that they may be applicable in most of the cases but may not be accurately appropriate for the designated respondents’ choices.
• It may be hard for participants to recall information or tell the truth about a controversial question.
• People sometimes give socially desirable or undesirable responses to the questions instead of frank answers. Thus, it hampers the generalization of the results of the research study.
• The comparison between two respondents may not be exact as one person’s rating may be different from another.
• Out of so many organizations, only six organizations were chosen for data collection and research. Hence, the recommendations may not be generalized.
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201428
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Appendix
Questionnaire
Sir/Madam,
Please rate your own organization on the accompanying answer sheet based on the respective scales and dimensions followed in your organization. This survey is designed to register your opinion regarding the respective organization and its external relationships. In completing the questionnaire, it is important that you answer each question as thoughtfully and frankly as possible. The answers will be summarized in statistical form so that individuals cannot be identified. To ensure complete confidentiality, please do not write your name anywhere on this questionnaire.
There is no right or wrong answer; your frank answers are the best answers.
Background Information
1. Name (not required/optional):
2. Name of the company:
3. Age (in years): (tick mark)
Below 25 25-35 35-45 45-55 55-65
4. Sex (M/F):
5. Functional department:
6. Designation:
7. Managerial level:
Top Middle Lower
8. Experience in the current firm:
9. Total experience:
10. Marital status: Married/Unmarried/Any other
Education
11. Professional:
MBA CA ICWA CS Any Other
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
31
12. Last Academic:
Appendix (Cont.)
Below Graduation Graduation Postgraduation M.Phil. Ph.D.
Organizational Cultural Ethos
Respond to the following items in the blanks provided:
This instrument will help to look at some of the values and beliefs of your organization. Given below are statements that indicate some organizational values. Read each statement, and if these are values shared by you in the organization, give your response. After reading the statement, respond in the blanks provided. Please be frank. Use the following key for your responses:
Write 4 if it is highly valued.
Write 3 if it is given a fairly high value.
Write 2 if it is given a rather low value.
Write 1 if it is given a very low value.
1. Free interaction among employees, each respecting others’ feelings, competence and sense of judgment. ______________________
2. Facing and not shying away from problems. __________________
3. Offering moral support and help to employees and colleagues in a crisis. _____________
4. Congruity between feelings and expressed behavior (minimum gap between what people say and do). ____________________
5. Preventive action on most matters. _____________
6. Taking independent action relating to their jobs. ___________________
7. Teamwork and team spirit. ____________________
8. Trying out innovative ways of solving problems. ______________________
9. Genuine sharing of information, feelings and thoughts in meetings. ____________
10. Going deeper rather than doing surface-level analysis of interpersonal problems. _______
11. Interpersonal contact and support among people. _______________
12. Tactfulness, smartness and even a little manipulation to get things done. ____________
13. Seniors encouraging their subordinates to think about their development and take action in that direction. __________________
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201432
14. Close supervision of, and directing employees on, action. _______________
15. Accepting and appreciating help offered by others. ________________
16. Encouraging employees to take a fresh look at how things are done. ___________
17. Free discussion and communication between seniors and subordinates. __________
18. Facing challenges inherent in the work situation. ________________
19. Confiding in seniors without fear that they will misuse the trust. ____________
20. Owing up to mistakes. _____________
21. Considering both positive and negative aspects before taking action. _____________
22. Obeying and checking with seniors rather than acting on your own. _____________
23. Performing immediate tasks rather than being concerned about large organizational goals. __________
24. Making genuine attempts to change behavior on the basis of feedback. ____________
Use the following key for the remainder of your responses:
Write 4 if it is a very widely shared belief.
Write 3 if it is fairly widely shared.
Write 2 if only some persons in the organization share this belief.
Write 1 if only a few or none have this belief.
25. Effective managers put a lid on their feelings. _______________
26. Pass the buck tactfully when there is a problem. _______________
27. Trust begets trust. ________________
28. Telling a polite lie is preferable to telling the unpleasant truth. _____________
29. Prevention is better than cure. ______________
30. Freedom to employees breeds indiscipline. ______________
31. Usually, emphasis on team work dilutes individual accountability. _____________
32. Thinking out and doing new things tones up the organization’s vitality. __________
33. Free and frank communication between various levels helps in solving problems. ________
34. Surfacing problems is not enough; we should find the solution. _________________
35. When the chips are down, you have to fend for yourself (people cannot rely on others in times of crisis). _____________________
Appendix (Cont.)
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
33
36. People generally are what they appear to be. _______________
37. A stitch in time saves nine. __________________
38. A good way to motivate employees is to give them autonomy to plan their work. ________
39. Employees’ involvement in developing an organization’s mission and goals contributes to productivity. __________________
40. In today’s competitive situation, consolidation and stability are more important than experimentation. __________________
Technological Aspect
Decide to what extent it actually applies to your organization. Use the following scale:
4 – Applies to a great extent
3 – Applies to a moderate extent
2 – Applies to a little extent
1 – Does not apply
1. Learning is facilitated by effective and efficient computer -based information system. ____________________
2. People have ready access to the information network (local area networks, Internet, online, etc.) _________________
3. We design and tailor our electronic performance support systems to meet our learning needs. ___________________
4. People have full access to the data they need to do their job effectively. __________
5. We can adapt software systems to collect, code, store, create and transfer information in ways best suited to meet our needs. ______________________
Leadership Pattern
The following questionnaire is designed to describe the behavior of the leader in any group engaged in problem solving. Please indicate your answer to each question by encircling the choice that best describes your views on that question. Be frank in your assessment and answering.
To what extent do you feel that your leader:
1. Is friendly and easy to talk to. 1 2 3 4 5 6 7 8
2. Listens well to you and others whether 1 2 3 4 5 6 7 8 she or he agrees or disagrees.
Appendix (Cont.)
Very Little Some Considerable Very Often
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201434
Appendix (Cont.)
3. States your point of view as well or better 1 2 3 4 5 6 7 8 than you can, even though she or he disagrees.
4. Encourages you and others to express 1 2 3 4 5 6 7 8 your ideas fully and frankly.
5. Encourages you and others to express 1 2 3 4 5 6 7 8 your feelings frankly.
6. Displays confidence and trust in you and 1 2 3 4 5 6 7 8 others whether or not she or he agrees.
7. Shares information frankly. 1 2 3 4 5 6 7 8
8. Expects each member to do her or his 1 2 3 4 5 6 7 8 very best.
9. Expects a high-quality job from herself 1 2 3 4 5 6 7 8 or himself.
10. Thinks what she or he and the group 1 2 3 4 5 6 7 8 are doing is important.
11. Encourages innovative and creative 1 2 3 4 5 6 7 8 ideas.
To what extent do you feel that your leader:
12. Is willing to take risks. 1 2 3 4 5 6 7 8
13. Is not defensive when criticized. 1 2 3 4 5 6 7 8
14. Avoids treating you and others in a 1 2 3 4 5 6 7 8 condescending manner.
15. Avoids being impatient with the 1 2 3 4 5 6 7 8 progress being made by the group.
16. Avoids dominating the discussion. 1 2 3 4 5 6 7 8
To what extent do you feel that your leader:
17. Avoids pontificating. 1 2 3 4 5 6 7 8
18. Avoids stating her or his vies 1 2 3 4 5 6 7 8 dogmatically.
Very Little Some Considerable Very Often
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
35
19. Encourages group to work through 1 2 3 4 5 6 7 8 disagreements, not suppress them.
20. Uses “we” and “our” rather than 1 2 3 4 5 6 7 8 “I” or “my”.
21. Shows no favorites; treats all 1 2 3 4 5 6 7 8 members equally.
22. Gives credit and recognition 1 2 3 4 5 6 7 8 generously.
23. Accepts more blame than may be 1 2 3 4 5 6 7 8 warranted for any failure or mistake.
24. Avoids imposing a decision 1 2 3 4 5 6 7 8 upon the group.
25. Waits until members of the 1 2 3 4 5 6 7 8 group have stated their positions before stating hers or his.
26. Presents own contribution 1 2 3 4 5 6 7 8 tentatively or as questions.
Knowledge Management Evaluation Tool
Please review each of the following statements and encircle the response that best represents your opinion about your organization using the following scale: 6 = Strongly agree; 5 = Agree; 4 = Mildly agree; 3 = Mildly disagree; 2 = Disagree; 1 = Strongly disagree
Items Response
1. The generation of new ideas and knowledge is highly valued. 1 2 3 4 5 6
2. Job analyses are frequently performed to determine job duties 1 2 3 4 5 6 and requirements.
3. An electronic knowledge base exists to store new ideas, 1 2 3 4 5 6 knowledge, solutions, and best practices.
4. Documents are proactively shared with employees. 1 2 3 4 5 6
5. The collective experience of employees is an integral part of 1 2 3 4 5 6 decision making.
Appendix (Cont.) Very Little Some Considerable Very Often
The IUP Journal of Knowledge Management, Vol. XII, No. 2, 201436
Items Response
6. Suggestions and multiple viewpoints are often sought for 1 2 3 4 5 6 decision making and organization development.
7. The development of job documentation is encouraged. 1 2 3 4 5 6
8. Information from amny sources is stored in an integrated 1 2 3 4 5 6 manner and cross-referenced, facilitating better communication and decision making.
9. No policies or technical security issues prevent the sharing of 1 2 3 4 5 6 information and knowledge.
10. Job responsibilities are carried out and decisions are made 1 2 3 4 5 6 based on all the necessary information and knowledge.
11. Experience is highly valued. 1 2 3 4 5 6 12. Documents can be posted on an organizational intranet 1 2 3 4 5 6
portal or saved on a network server.
13. The information and knowledge you receive is accurate and 1 2 3 4 5 6 up-to-date.
14. An organizational intranet portal exists where information 1 2 3 4 5 6 and knowledge relevant to job requirements may be retrieved.
15. New ideas and knowledge are frequently applied. 1 2 3 4 5 6
16. Brainstorming and other similar techniques are often used 1 2 3 4 5 6 to generate and record new ideas and knowledge.
17. New ideas and knowledge are recorded for future use. 1 2 3 4 5 6
18. It is common practice to store work documents on an 1 2 3 4 5 6 organizational server rather than on personal computers.
19. Electronic and/or non-electronic collaborations, teamwork 1 2 3 4 5 6 and cooperation are a part of doing business.
20. Recorded knowledge and best practices are used for 1 2 3 4 5 6 training, staff development and organizational development.
21. Tips and tools, job aids and case studies of best practices are 1 2 3 4 5 6 available for performance objective.
22. On-the-job time is available to gather information and 1 2 3 4 5 6 knowledge from others.
23. Information is stored and organized in a way that makes it 1 2 3 4 5 6 intuitively easy and quick to locate.
Appendix (Cont.)
The Relationship of Knowledge Identification and Creation with Leadership, Culture and Technology
37
Reference # 29J-2014-04-01-01
Appendix (Cont.)
Items Response
24. Collaborative meetings to gather information and share 1 2 3 4 5 6 knowledge are productive.
25. Advanced technologies such as data warehousing, mining 1 2 3 4 5 6 and modeling are used to leverage data and information for strategic and operational decision making.
26. There is a directory of experts for each major knowledge 1 2 3 4 5 6 domain.
27. Concept mapping, sometimes called “mind mapping”, is a 1 2 3 4 5 6 common technique used to gather new information and knowledge.
28. Documents stored on an organizational server or intranet 1 2 3 4 5 6 contain timely and useful knowledge for our job responsibilities.
29. Incentives are in place that motivate staff to share knowledge. 1 2 3 4 5 6
30. Expert systems and knowledge bases are used to aid in 1 2 3 4 5 6 decision making.
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