Are expertise diversity, knowledge management
and centrality success factors for innovative
employees?
A case study into the relation between expertise diversity and centrality with innovativeness and the moderating and positive role of knowledge management
June 2011
Bram Geerlings
1749951
B.Geerlings.1@student.rug.nl
University of Groningen
Master in Business Administration
Strategy and Innovation
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Introduction
A growing number of organizations acknowledge that innovativeness of teams and the individual employees is an important factor to create sustainable competitive advantage over the competition. Employee innovative behavior, developing and implementing new ideas for products and work methods are important assets that enables an organization to succeed in a dynamic business environment (Kanter, 1988). According to Scott and Bruce (1994), the foundation of all innovations are creative ideas, and it is individuals or groups who generate, promote, discuss, modify, and ultimately realize ideas. Ammabile (1988) also stressed the importance of innovativeness. In his research he concludes that innovation has a positive influence on the effectiveness and long-term survival of organizations.
To motivate and enable innovative behavior, more and more organizations consist out of departments or teams with differences in expertise. A team or department is a group within an organization, with a clearly defined membership and shares collective responsibilities for a product or service (Hackman, 1987). A reason for organizing work in departments and teams is the expectation that the creation of departments and teams will enable continues improvement (Wellins et al.,1991).
Research has shown that differences in expertise can cause conflicts to arise, which can be negatively associated with the effectiveness and performance of the individual and the team (Murray, 1989). On the other hand, Rink and Ellemers (2007) argue that departments or teams function most effective when the members of the department or team express their different views on work related issues. Also Jehn Northcraft and Neale (1999) stressed the fact that when the information diversity is increased, the possibility of disagreements increases, causing task related discussions to occur more frequent. Differences in information diversity also increases the number of potential good new ideas in a team (Sheremata, 2000). Therefore, teams and departments are composed in a way that the information and expertise diversity is high.
Because teams are composed in a way that the information and expertise diversity is high, managing knowledge is an important factor in the current business environment. Knowledge Management focuses on facilitating and managing knowledge related activities such as creation, capture, transformation and use (Wigg, 1997). Foss Husted and Michailova (2009) concluded in their research that Knowledge Management has become an important asset for the strategy, building of resources and competitive dynamics.
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who are connected across groups have more contact with people with alternative ways of thinking and behaving, and are thus more innovative. This causes that these people have more options and information to base their opinion on. Also Brass (1984) studied the role of centrality within the organization. He found that employees positioned more central obtain more information and insights, which is positive for the innovativeness of the employee, than employees who are positioned less central. Outcome of this theory is the following research question:
What is the influence of expertise diversity on the innovativeness of the employees, what is the (moderating) role of knowledge management on this relationship and what is the role and influence of knowledge management as well as the role of employee centrality on the employee innovativeness?
Relevant definitions
According to Wijnberg (2004), an innovation comprises something new, which is presented in such a way that the value will be determined by the selectors. Hurt et al. (1977) define innovativeness as the willingness to change. Drucker (1985) emphasize that the trigger for the generation of new ideas are often work-related problems and discontinuities employees are confronted with while performing their task. West and Farr (1989) define innovativeness as the intentional generation, promotion, and realization of new ideas within a work role, group or organization, in order to benefit role performance, the group or the organization. Calantone (2002) defines innovativeness as the degree to which an individual, compared to others in the social system, is relatively early in adopting something new. Based on the previous mentioned definitions, the following definition for innovativeness is used in this research: innovativeness is the capability, intention and willingness of employees to change and improve while experiencing work-related problems and discontinuities while performing their task in order to benefit role performance, the group or the organization.
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competences are different for all the team members, it is dependent on the education, knowledge, skills, information, experience and background (Harrison, 2007). Therefore, for the purposes of this research expertise diversity is defined as the difference in expertise for the different employees depending on education, knowledge, age, information and experience.
According to Wigg (1997) Knowledge Management includes providing Knowledge Management capabilities and a knowledge architecture so that the enterprise’s facilities, procedures, guidelines, standards and practices facilitate and support active Knowledge Management as part of the organization’s practices and culture. Knowledge Management should also promote knowledge creation and innovation. Quintas, Lefrere and Jones (1997) define Knowledge Management as the process of continually managing knowledge of all kinds to meet existing and emerging needs, to identify and exploit existing and acquired knowledge assets and to develop new opportunities. In this research the definition of Knowledge Management by Almashari, Zairi and Alathari (2002) is used. In their empirical study of the impact of Knowledge management on organizational performance knowledge management is defined as follows: Knowledge Management involves a systematic approach to identifying and capturing information and knowledge about a company (the processes, products, services, markets, customers and competitors), and sharing this for the greater goal of organizational well being and performance.
Blau and Alba (1982) defined centrality as the minimum distance between a person and all other persons in the reference group. In this research, the centrality is measured with the Betweenness Centrality. The Betweenness Centrality measures the frequency with which an actor falls between other pairs of actors on the shortest or geodesic paths connecting them.
Expertise diversity and Innovativeness
Innovativeness is the capability, intention and willingness to solve problems and discontinuities while performing the task. Bantel and Jackson (1989) conclude that differences in expertise within a team is positive related with the ability to solve complex problems. Furthermore, Bantel and Jackson (1989) found evidence that heterogeneity in teams and thus departments has a positive effect on innovative and creative decision making. Consequently, they found that organizations with management with backgrounds which are diverse were more innovative than organizations with management with homogeneous backgrounds.
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learning opportunities will occur and employees are more all-round and motivated, which enhances the team and individual performance. This is also confirmed by Earley and Mosakowski (2000) who conclude that teams or departments with heterogeneous skills and resources are more innovative while solving problems than the more homogenous teams or departments. In case of a high expertise diversity, the information diversity will also be high. A high information diversity increases the number of potential good new ideas in a team (Sheremata, 2000). Furthermore, according to McGrath (1984) one of the advantages of working in teams is that teams advance the knowledge and creativity and enhance the dedication and motivation of the team members, and thus enhances the innovativeness.
Based on the theory, the expectation is that differences in expertise of the employees has a positive influence on the innovativeness of the employees. So, a positive relationship is expected between expertise diversity and the innovativeness. Based on this, the following hypothesis is drawn up:
H1: A higher expertise diversity among employees has a positive influence on the innovativeness of these employees.
Knowledge Management and innovativeness
According to Harari (1994) organizations which stimulate and improve the knowledge of their employees are better in coping with the changes and the organization is better in innovation in the field where the organization is active in. According to Argote and Ingram (2000), the process of sharing knowledge among employees may lead to improved absorptive capacity, improved innovation capacity, and other capabilities, and therefore, to sustained competitive advantage. Carneiro (2000) discusses that personal characteristics of the employees responsible for the execution of the Knowledge Management within the organization is an important factor which influences Knowledge Management in the organization. In turn, Knowledge Management has a positive influence on the competiveness and the innovativeness of the organization. Darroch (2005) has empirically tested what the role of Knowledge Management is within firms. The result of the research is that organizations with the capabilities to manage knowledge use resources more efficient and are thus more innovative than companies which lack these capabilities.
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Management plays an important role in innovation. Amongst other things, Plessis (2007) states that due to Knowledge Management an innovative and creative culture is created. Furthermore, due to the availability and accessibility of knowledge and knowledge flow employees can improve their skills and knowledge, which in turn can improve their innovativeness. Based on the previous, the expectation is that Knowledge Management has a positive influence on the innovativeness. Outcome is the following hypotheses:
H2: The systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization (Knowledge Management) has a positive influence on the innovativeness of the employees.
Centrality and innovativeness
Dolfsma and van der Eijk (2011) studied the influence of centrality on the innovativeness of the employee. They found that more central positioned people contribute more to innovation than people who are positioned in a position which is not central. This is also confirmed by Ibarra (1993). He found that centrality in a network is an important predictor of administrative innovation involvement. Also Bell (2005) found that the network is an important source for new information which can be used for innovation and that centrality in the network enhances the innovativeness.
Obstfeld ( 2005) examined if fewer structural holes in the in an individual’s network has a positive influence on the employees involvement in innovation. He found that the higher the density in an employee’s network, and thus the absence of structural holes, is positively related to innovativeness. Central positioned employees have obtained legitimacy. According to Kimberly and Evanisko (1981) legitimacy is an important predictor of the innovativeness of an individual. They state that the more innovative employees are likely to have obtained legitimacy and knowledge to be innovative. Following the theory, the expectation is that the Centrality has a positive influence on the innovativeness of the employee. The hypothesis originated from this is:
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Moderator Knowledge Management
Research has shown that differences in expertise can cause conflicts to arise which can be negatively associated with the effectiveness and performance of the individual and the team (Murray, 1989). Through managing knowledge in a proper way, the needed information can be accessed faster and easier and the needed expertise can be better found (Reid, 2003). The better accessibility of information and expertise will prevent conflicts to arise.
According to Roszkiewicz (2007) making accurate decisions means working together with other people to achieve creative solutions. Heterogeneous teams and departments composed with differences in expertise have the ability to make more creative and innovative decisions than teams which are more homogenous (Bantel and Jackson,1989). Because these teams and departments are composed with a high expertise diversity, managing knowledge among the team and department is important and will support and strengthen proper and innovative decision making.
The performance of teams and departments composed with a high expertise diversity is not only dependent on the knowledge of the individual, but also whether the knowledge is shared (Phillips et al, 2004). A way to share this knowledge is through the systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization, Knowledge Management, which will support the positive relation between Expertise Diversity and of the Department (BRON) and the Innovativeness of the employees. Based on the theory, the expectation is that the already positive relation between expertise diversity and the innovativeness is positively influenced and thus reinforced by knowledge management. The following hypothesis is the outcome.
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H2 + Knowledge Management
Expertise Diversity Innovativeness
Centrality H3 + H4 Moderator+ + Conceptual Model
On the basis of the theory and the hypotheses, the following conceptual model is drawn up with the different variables and their mutual relations.
Figure 1: Conceptual model
Data collection
Case Study
This research is based on a single case study. In so doing, especially why and how specific events occur can be measured accurately using primary and secondary data (Yin, 2003). The definition of a case study is an empirical inquiry that investigates a contemporary phenomenon within its real-life context when the boundaries between phenomenon and context are not clearly evident and in which multiple sources of evidence are used (Yin, 2003). The term case study is employed to identify a specific form of inquiry which contrasts with two other influential kinds of social research, namely the experiment and social survey. Gomm (2000) argues that the aim of case study research should be to capture cases in their uniqueness, rather than to use them as a basis for wider generalization. Furthermore, to measure the centrality of the employees at BRON the network analysis is used. The case study is the most suitable study for a network analysis while collecting the needed data for the network analysis is labor intensive and therefore collecting data from multiple cases is not realistic.
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introduction of the personal number and the department BasisRegister OnderwijsNummer (BRON) the information is now digitalized and centralized at one organization. Therefore, the amount of administrative work which previously had to be done by the primary schools is reduced. Through the department BRON), DUO collects individual information of students active on the primary education, based on the personal number. BRON provides other organizations with the information on which the payment for the primary schools is based on. Furthermore, due to the centralization and digitalization of the information at BRON the reliability and safety of the information is improved.
The department BRON is founded in 2009 and is thus a relative new department at the Dienst Uitvoering Onderwijs. Because of the newness of the department, employees experience different types of problems and difficulties while performing their task. BRON is seeking for ways to come up with solutions to these problems and to improve their products and services. Employees are encouraged to come up with new innovative ideas and innovative initiatives by the employees are stimulated. Therefore the department BRON is suitable for a research into what drives and stimulates the innovativeness of the employees at BRON. The management supported the research actively and gave permission to conduct the in-depth-interviews with the 48 employees working at BRON.
The research design employed in this paper is a case study, since the only case that is in-depth investigated is the department BRON. Therefore, the results from the research cannot be utilized for generalization, but can only be used to describe the unique case.
Procedure
Data collection is undertaken by in-depth face-to-face interviews conducted at Dienst Uitvoering Onderwijs, specifically at the department BRON. The selection criteria for the participants is that they work at the department BRON. The interview was divided into three parts. The first part of the interview is the general part. Information was collected about the control variables gender, age and education. Subsequently, in the second part questions about the different variables innovativeness, expertise diversity and knowledge management were asked. In the final part of the interview was asked with which colleagues work related contact, that is contact with colleagues to ask help, advice or information, consists.
Respondents
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requirements set to the collection of network data, which requires a response rate above 95% (Aalbers and Dolfsma, 2008). The questionnaire was completed by 25 female respondents and 21 male. The age of the respondents ranged from 19 till 53 with an average of 34 year old and a standard deviation of 7,7.
Instruments
Internal consistency
Firstly, the internal consistency will be measured. The internal consistency is the degree to which the different items, expertise diversity, innovativeness, centrality and knowledge management, measure the same construct of the items in the questions. This will be measured with the Cronbachs α. If the Cronbachs α is above 0,6 the connection is reliable. With these reliable outcomes, the correlation analysis is performed.
Innovativeness is measured with a combination of questions from researches of Anderson and West (1996) and Siegel and Kaemmerer (1978). These researches measured group processes and the climate for innovation (TCI) and organizational change and the support for creativity and innovative climate. For this research are relevant questions selected from these researches and relevant questions for the specific situation at BRON are added. All questions are measured with a five-point Likert Scale, with a range from entirely disagree, indicated with a 1, until entirely agree, indicated with a 5. The Cronbach α for innovativeness is 0.72. Based on this, conclusion is that the questions measure the same construct.
Expertise diversity is researched with a combination of questions from researches of Rink and Ellemers (2007) and Bunderson and Sutcliffe (2002). In this researches is measured what the influence is of differences within the team on shared organizational identity and the influence of functional diversity on the process and performance. For this research are relevant questions selected from these researches, relevant questions for the specific situation at BRON are added. All questions are measured with a five-point Likert Scale, with a range from entirely disagree, indicated with a 1, until entirely agree, indicated with a 5. The Cronbach α for expertise diversity is 0.63. Based on this, conclusion is that the questions measure the same construct.
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with a five-point Likert Scale, with a range from entirely disagree, indicated with a 1, until entirely agree, indicated with a 5. The Cronbach α for knowledge management is 0.68. Based on this, conclusion is that the questions measure the same construct.
The examination of centrality is based on the research of Mehra et.al. (2001). The roster method is used to identify the number of ties. Respondents were asked to look at an alphabetical list of employees of the department BRON and place checks next to the names of employees they considered work partners. Work partners are defined as colleagues to whom information, help and advice is exchanged concerning work related issues. These outcome of this matrix are put into the network program UCINET to calculate the InDegree score with the Freeman approach.
In figure 2 the network of the different relationships at BRON are visual displayed. The total number of Ties is 1096, with an average of 23 InDegree ties and a range with a minimum of 11 and a maximum of 39 InDegree ties for the employees.
Figure 2: Workrelations network BRON
Data analysis
Correlation analysis
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(expertise diversity, innovativeness, centrality and Knowledge Management). The reason to do a correlation analysis is that for a correlation analysis, no specific demands are set to the number of respondents. This is in line with the research, which is executed under a relative small population (Case Study). Furthermore, it is usual to conduct a correlation analysis in an analysis with variables measured on interval level (van den Brink en Koele, 2002). Outcome of the correlation analysis is if there is a linear connection between two measurements of two variables. If this is the case, there is a correlation. The correlation coefficient will be between the -1 and the +1, whereby 0 indicates there is no linear connection, -1 a perfect negative connection and +1 a perfect positive connection.
The correlation process is conducted as following. Firstly, the mutual correlations between the variables are tested with the averages and standard deviations through the Pearson correlation coefficient. Per variable, the scale average is calculated and the independent variables are standardized. This standardization is done through z-transformations, so that the outcome is a standard unit and the outcomes can be better compared.
Hierarchic Multiple regression analysis
The next step in the analysis is an Hierarchic Multiple regression analysis, with which a cause-consequence relationship is identified (Aiken & West, 1991) between the variables (expertise diversity, innovativeness, knowledge management and centrality).
This Hierarchic Multiple regression analysis consists out of three steps (Aiken & West, 1991). In the first phase the control variable are put in. The second phase is conducted with the standardized variables of expertise diversity and centrality to measure the effects of these variables on innovativeness. In the final phase the product of the standardized variables and the moderator variable is put in.
Results
Correlations
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the result. It is possible there is a joint cause or a general trend. Therefore, this significant relation does not mean there is a cause-consequence relationship, it is a statistic relation.
Table 1: Correlations
N=46 **p <.01
Furthermore, there is a positive relation between innovativeness and expertise diversity (r = .04, p<.81). Conclusion can be that a higher expertise diversity has a positive influence on the innovativeness of the employees. However, the significance is p<.81 which means that the result is not significant and thus not completely reliable. There is a chance of 81% that the found correlation is based on coincidence. Also this relation does not mean there is a cause-consequence relationship, it is a statistic relation.
Between the centrality and the innovativeness of the employee a negative relation is found which was not expected. (r = -.15, p<.33). However also this result is not significant (p<.33) which means that there is a chance of 33% that the found correlation is based on coincidence. Also this relation does not mean there is a cause-consequence relationship, it is a statistic relation. Finally, between the centrality of the employee and the systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization (knowledge management) a negative relation is found (r = -.06, p<.69). Also this result is not significant (p<.33) which means that there is a chance of 69% that the found correlation is based on coincidence and thus also this relation does not mean there is a cause-consequence relationship, it is a statistic relation.
Testing Hypotheses
In the table on the next page, (table 2), are the results of the Hierarchic Multiple regression analysis which is conducted to research the relations between expertise diversity, knowledge management, centrality and innovativeness. In the table are the used B-values and, between the brackets, the significance for the predictors of the innovativeness. The significant
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contribution of expertise diversity, knowledge management, centrality and the interaction with the prediction of the innovativeness of the employees is explained with the B-values. This B-value provides information about innovativeness and the used predictors (expertise diversity, knowledge management and centrality). It is a display to which degree the predictors influence the outcome of the innovativeness of the employees. A positive B-value means if the value of the predictors (expertise diversity, knowledge management and centrality) increases with 1, the value of the innovativeness of the employees increases with the value of the B-value. A negative B-value means that if the value of the predictors increases with 1, the value of the innovativeness of the employees decreases with the value of the B-value.
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Expertise diversity has a positive influence on the innovativeness of the employees of BRON (B = .043, significance = .773). This means when the value of expertise diversity increases with 1, the value of the innovativeness increases with .043. However, this is not a significant contribution to the prediction of the innovativeness of the employees of BRON (p>.05), thus this statement is not reliable thus the hypothesis (H1) that a higher expertise diversity among the employees of BRON has a positive influence on the innovativeness of the employees working at BRON is not confirmed.
Furthermore, outcome of the data is that there is a positive relationship between knowledge management and the innovativeness (B = .464, significance = .003). This means when the value of knowledge management increases with 1, the value of the innovativeness increases with .464. This statement is reliable considering this relation is significant (p<.05). The hypothesis (H2) that the systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization (Knowledge Management) has a positive influence on the innovativeness of the employee working at BRON is confirmed.
The data show a negative relation between the centrality and the innovativeness of the employees (B = -.132, significance = .369). This means when the value of centrality increases with 1, the value of the innovativeness decreases with .132. However, also this not a significant contribution to the prediction of the innovativeness of the employees of BRON (p>.05), thus this statement is not reliable. The hypothesis (H3) that the centrality of an employee at BRON has a positive influence on the innovativeness of the employee of BRON is not confirmed.
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Discussion
Findings
The aim of this research was to investigate the possible relations between innovativeness, expertise diversity, knowledge management and employee centrality at BRON. Specifically is studied what the influence is of expertise diversity on the innovativeness of the employees and what the (moderating) role of knowledge management is on this relationship. Furthermore is researched what the role of knowledge management is on the innovativeness of the employees as well as the role of employee centrality on the employee innovativeness.
In this research was expected that differences in expertise among the employees has a positive effect on the innovativeness of the employees. According to Bantel and Jackson (1989) heterogeneity in teams and thus departments has a positive effect on innovative and creative decision making of the employees working in this department. Also Earley and Mosakowski (2000) conclude that teams or departments with heterogeneous skills and resources are more innovative while solving problems than the more homogenous teams or departments. In contradiction with the literature, expertise diversity among the employees did not correlate significant with innovativeness. This means that the expertise diversity does not have a positive influence on the innovativeness of the employees at BRON.
Furthermore was expected that the presence of a systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization has a positive influence on the innovativeness of the employees. This is based on researches of Harrari (1994) and Plessis (2007). Harrari (1994) states that organizations which stimulate and improve the knowledge of their employees are better in coping with the changes and the organization is better in innovation in the field where the organization is active in. Plessis (2007) found that due to knowledge management an innovative and creative culture is created and due to the availability and accessibility of knowledge and knowledge flow employees can improve their skills and knowledge, which in turn can improve their innovativeness. The literature is supported, knowledge management correlated significant with innovativeness. Thus, the presence of a systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization has a positive influence on the innovativeness of the employees at BRON.
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people contribute more to innovation than people who are positioned in a position which is not central. The research shows a negative but not significant influence of the centrality on the employee innovativeness.
Finally, the expectation was that the positive influence of expertise diversity on the innovativeness of the employees is reinforced by knowledge management. The performance of teams and departments composed with a high expertise diversity is not only dependent on the knowledge of the individual, but also whether the knowledge is shared (Phillips et al, 2004). A way to share this knowledge is through the systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization (knowledge management). The research did not find support for this statement, thus the relationship between expertise diversity and the innovativeness is not positively influenced by the knowledge management activities by the organization.
Conclusion and reflection
The main question of this research was if expertise diversity, knowledge management and centrality success are factors for innovative employees. From the results conclusion is that one of the four researched relations, the relation between knowledge management and innovativeness, had a significant result. About this relation a reliable statement is done that the systematic approach to identify and capture knowledge and sharing this for the greater goal of the organization (Knowledge Management) has a positive influence on the innovativeness of the employees. The other researched relations were not significant and the found relations were trends instead of significant results.
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A strength of the research is representative character of the respondents related to the measured variables. BRON is a relative new department. Because of the newness of the department, employees experience different types of problems and difficulties while performing their task. BRON is seeking for ways to come up with solutions to these problems and to improve their products and services. Employees are encouraged to come up with new innovative ideas and innovative initiatives by the employees are stimulated.
Acknowledgements
I greatly thank W. Dolfsma for his support and useful suggestions during the thesis period. Furthermore I thank R. Wiekel, B.Tonnis M. Wesselman and R. Galliaard of DUO for giving me the opportunity to conduct my research at DUO and their support. Also many thanks go out to the employees of BRON who participated in this research.
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Apendix I: Hierarchic Multiple regression analysis innovativeness, expertise diversity, knowledge management and centrality.
Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 ,092a ,008 -,062 ,42824 ,008 ,118 3 42 ,949 2 ,492b ,242 ,126 ,38851 ,234 4,010 3 39 ,014 3 ,494c ,244 ,105 ,39300 ,002 ,113 1 38 ,739
a. Predictors: (Constant), Education, Age, Gender
b. Predictors: (Constant), Education, Age, Gender, Zscore(KMgem), Zscore(Centrality), Zscore(EDgem)
24/24 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 4,012 ,435 9,228 ,000 Gender -,044 ,145 -,054 -,306 ,761 Age -,003 ,009 -,049 -,296 ,768 Education ,058 ,108 ,088 ,535 ,595 2 (Constant) 3,872 ,399 9,708 ,000 Gender -,084 ,133 -,102 -,635 ,529 Age ,001 ,008 ,014 ,095 ,925 Education ,100 ,103 ,152 ,968 ,339 Zscore(EDgem) ,018 ,061 ,043 ,291 ,773 Zscore(KMgem) ,193 ,060 ,464 3,232 ,003 Zscore(Centrality) -,055 ,060 -,132 -,908 ,369 3 (Constant) 3,859 ,405 9,523 ,000 Gender -,085 ,134 -,103 -,634 ,530 Age ,001 ,009 ,028 ,176 ,861 Education ,095 ,105 ,144 ,897 ,375 Zscore(EDgem) ,009 ,067 ,021 ,131 ,897 Zscore(KMgem) ,194 ,060 ,466 3,207 ,003 Zscore(Centrality) -,051 ,062 -,122 -,814 ,421 Interactie_EDKM ,027 ,080 ,054 ,336 ,739
