Assessing Knowledge Management Maturity in a Telecommunication Company

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1 Available online at GlobalIlluminators Full Paper Proceeding ITMAR -2014, Vol. 1, FULL PAPER PROCEEDING Multidisciplinary Studies ISBN: ITMAR-14 Assessing Knowledge Management Maturity in a Telecommunication Company Professor Dr. Norliya Ahmad Kassim 1*, Noreen Natasha Azmee 2 Faculty of Information Management, Universiti Teknologi MARA (UiTM),Malaysia. Abstract The purpose of the study is to investigate the perceptions of knowledge management (KM) maturity of employees in one telecommunication company focusing on KM strategy, leadership behavior, people and network. A research survey method using questionnaire was distributed to 103 employees of the company of which 64 (62.1%) were returned and usable for analysis. From the findings, the KM maturity dimension on KM strategy was ranked as the highest (mean=4.21), followed by leadership behavior (mean=4.12), and people and network (mean=4.09). The result shows no difference regarding KM strategy, leadership behavior, and people and network according to gender and working experience. The study also found that, there are positive, significant and moderate relationships between leadership behavior and people and network, between KM strategy and leadership behavior, and between people and network and KM strategy. The results are important for the organization to provide significant feedback on employee s perception on the maturity level of knowledge management which is useful for organization s future environment The Authors. Published by Global Illuminators. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the Scientific & Review committee of ITMAR Keywords: Knowledge management, Knowledge management maturity, KM strategy, Leadership behavior, People and network Introduction In today s economy, products are no longer the main attention, but the world is now focusing on knowledge. In knowledge-based organizations, knowledge and intellectual capital are the important asset and critical factor to ensure the success and competitiveness of organization, thus making knowledge management a hot topic. The theory of knowledge management (KM) was cultivated in 1960s by Peter Drucker when he coined the term knowledge worker (as cited in Skyrme, 2002). In the business context, the theory of knowledge management (KM) emerges when knowledge is exploiting and utilizing within an organization (Aranda & Fernandez, 2002). Knowledge management is the process of classifying, collecting, and disseminating the knowledge assets to ensure organization s success, competitive and promote innovation (Nonaka & Takeuchi, 1995; Davenport & Prusak, 2000). Most organizations which are actively engaged with knowledge management (KM) have an issue to identify the effectiveness and maturity of knowledge management *All correspondence related to this article should be directed to Professor Dr. Norliya Ahmad Kassim Faculty of Information Management, Universiti Teknologi MARA (UiTM) Malaysia. norliya@salam.uitm.edu.my, drnorliya@yahoo.com 2015 The Authors. Published by Global Illuminators. This is an open access article under the CC BY-NC-ND license ( Peer-review under responsibility of the Scientific & Review committee of ITMAR-2014.

2 (KM) program (O Sullivan, 2010). The process of measuring the value of knowledge management and knowledge itself is quite challenging in the organization (Jumo, 2011). Knowledge management maturity defines the stages of maturity in which an organization can anticipate to pass through in its journey to improve knowledge-oriented practices and processes (O Sullivan, 2010). Upon this, measuring the growth of knowledge management is unavoidably and cannot be taken as simple (Chua & Chaudhry, 2008). Thus, this study aims to investigate the perceptions of employees in one Telecommunication Company regarding the knowledge management maturity in their organization. However, this paper focuses on three dimensions of knowledge management maturity namely, KM strategy, leadership behavior, and people and network. Specifically, the objectives of the study are: 1. To identify the level of KM maturity (KM strategy, leadership behavior, and people and network) among employees. 2. To compare the differences regarding KM maturity (KM strategy, leadership behavior, and people and network) according to gender and years of working experience. 3. To identify the relationships between factors of KM maturity (KM strategy, leadership behavior, and people and network). Knowledge Management Literature Review Srikantaiah (2008) indicates that KM is a systematic process of identifying, capturing, organizing, and disseminating or sharing explicit and tacit knowledge assets that add value within an organization. Rao (2005) defines KM as a systematic discipline and set of approaches to enable information and knowledge to grow, flow, and create value in an organization. This involves people, information, workflows, enabling tools, best practices, alliances, and communities of practice. Maturity Model According to Menayo and Ringach (2006), maturity model can be defined as evolution of an organism from its early beginnings to a final status which is representing the reality and developed with a specific goal. They also add that maturity model brings advantages to measure the current maturity of the process employed, evaluate the current status of the field practices, set an objective for process design endeavors, guide the evolution of organizational change, and allow comparisons. Similarly, Weerdmeester et al. (2003) refer maturity model as a means of simplifying the description of an organization s level of development, and the stages of development that an organization can be expected to pass through as part of its continuos improvement strategy. Marco (2002) emphasizes that maturity models are designed to be easy to understand and use, thus suitable for presentation to the higher-level decision-makers in an organization. Maturity models are used to describe, explain and evaluate growth life cycles. 22

3 Knowledge Management Maturity Gallager and Hazlett (2004) describe knowledge management maturity model (KMMM) as a mechanism that is being established to aid in assessing the current KM capability, thus facilitating effective measurement of the impact of KM upon business performance. They also emphasize that the KMMM is an instrument for self-assessment which allows the organizations to visualize their current and plan the KM progress. However, Kuriakose et al. (2011) viewed knowledge management maturity model (KMMM) as application of structured approach to KM implementation and engineering of KM. Similarly, Weerdmeester et al. (2003) refer maturity model as a means of simplifying the description of an organization s level of development, and the stages of development that an organization can be expected to pass through as part of its continuous improvement strategy. In addition, Schwartz and Tauber (2009) defined maturity model as a reflection of the distinct, repeatable, and identifiable stages that an organization goes through as it evolves from an initial stage to a final stage. Marco (2002) emphasizes that maturity models are designed to be easy to understand and use, thus suitable for presentation to the higher-level decision-makers in an organization. Knowledge Management Strategy Knowledge management strategies have emerged to help organizations understand the nature of knowledge management initiatives and to identify those knowledge management initiatives that are aligned with the organization s objectives. Hansen, Nohria and Tierney (1999) have identified knowledge management strategies. They proposed two types of knowledge management namely, strategies--codification and personalization-- organizations that could be used for effective leveraging of knowledge assets. Schulz and Jobe (2000) identify similar knowledge management strategies of codification (transformation of tacit knowledge into explicit knowledge to facilitate the flow of organizational knowledge) and tacitness (organizational knowledge is kept tacit in order to prevent competitors from obtaining the knowledge). Leadership Behavior Leadership plays a vital role in ensuring KM is performing effectively in the organization. Ricketts (2003) and Rosenbach and Taylor (1993) describe leadership as the ability to move or influence and getting people to work together toward achieving individual or group goals. In addition, Peter Drucker, the guru of the field management describes leadership as not about a list of attributes as no two leaders will exhibit the same list, nor is it about charisma or some king-like quality (Winston-Churchill Leadership, 2007). According to Ehms and Langen (2002), leadership gives significant influence to the implementation of knowledge management in the organization. They also add that leadership is important to support and encourage the employees in taking parts in the KM activities. This is in line with Hasanali (2002) that leaders make themselves as role model will bring great impact in stimulating the employees to participate in the KM activities. 23

4 People People are the heart of knowledge management (Kuan, 2005). This is in line with a study by Goh (2006) who emphasizes that people are important element in KM in the process of creating and sharing knowledge. Ehms and Langen (2002) in their article on KM maturity model, propose the element of people or soft factor. In addition, a study by Maponya (2004) argues that employees are important factors in implementing knowledge management because the employees hold a wealth of knowledge and experience that act as resource for the organization. Mohammad Fathian et al. (2008) in their quantitative model of assessing KM, suggested the network as the element to be assessed in the organization. They also describe that network consisted of teamwork and cooperation. Methodology In this study, questionnaires were personally distributed randomly to 103 staff in one telecommunication company in Malaysia. This study adopted questionnaires from previous research of Chan, Chu and Wu (2012). However, out of 103 questionnaires which were distributed to the targeted respondents, only 64 were returned and usable for analysis. Therefore, the response rate is 62.1%. The questionnaire was designed on a 1 (strongly disagree) through 5 (strongly agree) Likert scale. Descriptive and inferential statistics were used in analyzing the data. The data was statistically analysed using the Statistical Package for Social Sciences (SPSS). Profile of Respondents Results In this study female employees had represented the most number of respondents (41 or 71.9%) while 18 or 28.1% were male respondents. A total of 41 (64.1%) of the respondents were Malay, 19 (29.7%) of the respondents were Chinese, and the rest (4 or 6.2%) were Indian. Almost half (48.4% or 31) of the respondents were those whose age were in the range of age group, while the least (9.4% or 6) were those in the range of more than 41 years of age group. 26 (40.6%) of the respondents had 6-10 years of working experience, 19 (29.7%) of the respondents had 5 or less years, followed by 14 (21.9%) of the respondents who had years, and very few (5 or 7.8%) of the respondents had years of working experience. More than half (34 or 53.1%) of the respondents were Bachelor degree holders, 23 (35.9%) of the respondents were Master degree holders while 7 (10.9%) of the respondents were Diploma holders. Reliability Test Reliability tests were executed to test the internal consistency of the respective scale for KM maturity variables which are: KM strategy, leadership behavior, and people and network. The researcher used Cronbach s alpha to evaluate the unidimensionality of a set of scale items. The results show that all dimensions of KM maturity are reliable (cronbach alpha =0.835, 0.712, respectively). Table 1 summarized the scales of all variables which are reliable as all Cronbach s Alpha value exceeds

5 Table 1: Results of Reliability Test Dimensions of KM Maturity No of Statement Cronbach s Alpha KM Strategy Leadership Behavior People and Network Normality Test Normality tests were conducted to determine whether the data were normally distributed. The results in Table 2 show that the observation values with respect to the dimension on KM strategy (p-value=0.004) was not normally distributed. However, the dimensions on leadership behaviour (p-value=0.053), and people and network (p=0.114) showed normal distribution of data. Consequently, all statistical tests of significant differences for the dimensions on KM strategy will use nonparametric techniques while the dimensions on leadership behavior, and people and network will use parametric techniques. Table 2: Normality Test Results Dimensions of KM Maturity Shapiro-Wilk Z statistics p-value KM Strategy * Leadership Behavior People and Network *Significant at 0.05 Perceptions of Knowledge Management Maturity: The following sections will address the first objective of the study which is To identify the perception of level of KM maturity (KM strategy, leadership behavior, and people and network) among employees. Perceptions of Knowledge Management Maturity Focusing on KM Strategy: Table 3 displays the overall mean score of 4.21 which indicates that respondents agree with the statement on KM strategy. The mean scores for all items are between 4.27 to 4.12 and this indicates that they agree with all the statements. Among the five statements, the mean score is highest for the organization has embedded knowledge management (KM) into its business strategy (mean=4.27) followed by most employees believe that sharing knowhow is important to the success of the organization (mean=4.23). The lowest mean score is the statement on the company has communicated a clear KM framework and to its staff to encourage learning and knowledge sharing (mean=4.12) which still indicates that respondents agree that the organization has reached the KM maturity with respect to KM strategy. Overall, it can be concluded that respondents have positive perception that their organization has reached the level of KM maturity with respect to KM strategy. Table 3: Mean Scores of Respondents by Statement: KM Strategy Statements Mean Score Std. Deviation 25

6 1. The organization has embedded knowledge management (KM) into its business strategy. 2. Most employees believe that sharing know-how is important to the success of the organization. 3. The organization has implemented a set of KM tools to enable learning before, during and after The organization has clearly identified intellectual assets The company has communicated a clear KM framework and to its staff to encourage learning and knowledge sharing Overall mean for KM strategy Perceptions of Knowledge Management Maturity Focusing on Leadership Behavior: Table 4 shows the overall mean score of 4.12 which indicates that respondents agree with the statement on leadership behavior. The mean scores for all items are between 4.27 to 3.98 and this indicates that they agree with all the statements. Among the five statements, the mean score is highest for managers set themselves as good examples of frequently conducting KM activities (mean=4.27) followed by the organization nurtures the right attitudes among the employees to facilitate sharing and using others know-how (mean=4.16). Although the statement on organization leaders recognize the link between KM and performance (mean=3.98) is the lowest, it still indicates that respondents agree that the organization has reached the KM maturity with respect to leadership behavior. Overall, it can be concluded that respondents have positive perception that their organization has reached the level of KM maturity with respect to leadership behavior. Table 4: Mean Scores of Respondents by Statement: Leadership Behavior Statements Mean Score Std. Deviation 1. Managers set themselves as good examples of frequently conducting KM activities. 2. The organization nurtures the right attitudes among the employees to facilitate sharing and using others know-how. 3. The organization advocates the practice of knowledge sharing and KM activities are encouraged and rewarded. 4. Managers offer the time and support to its staff on learning and knowledge sharing Organization leaders recognize the link between KM and performance. Overall mean for leadership behavior Perceptions of Knowledge Management Maturity Focusing on People and Network: Table 5 depicts the overall mean score of 4.09 which indicates that respondents agree with the statement on people and network. The mean scores for all items are between 4.17 to 3.97 and this indicates that they agree with all the statements. Among the five statements, the 26

7 mean score is highest for networks meet regularly, and they are organized around business needs (mean=4.17) followed by employees seem to be rewarded for performing networks activities that result in knowledge sharing (mean=4.12). Although the statement on networks on a needs basis helps employees know each other (mean=3.97) is the lowest, it still indicates that respondents agree that the organization has the KM maturity with respect to people and networks. Overall, it can be concluded that respondents have positive perception that their organization has reached the level of KM maturity with respect to people and networks. Table 5: Mean Scores of Respondents by Statement: People and Network Statements Mean Score Std. Deviation 1. Networks meet regularly, and they are organized around business needs. 2. Employees seem to be rewarded for performing networks activities that result in knowledge sharing. 3. Networks have clear governance documents, which clearly defined purpose, roles and responsibilities. 4. The company has put in place technology to support networks, and they are well utilized Networks on a needs basis helps employees know each other Overall mean for people and networks Differences of Knowledge Management Maturity according to Gender and Years of Working Experience: The following sections will address the second objective of the study which is To compare the differences regarding KM maturity (KM strategy, leadership behavior, and people and network) according to gender and years of working experience. Differences on KM Strategy between Gender To determine whether there is a significant difference in gender on KM strategy, the Mann- Whitney U Test, a non-parametric was carried out to measure the differences of variables between two independent groups. This is because the distribution of data is not normal. Results of the statistical test are presented in Table 6. The p-value for KM strategy is not significant at 5% level (p=0.167>0.05). It is concluded that male and respondents do not differ in their perception on KM strategy. Table 6: Mann-Whitney U Test on KM strategy between Male and Female Gender Sample size Mean Score Mean Rank p-value Male Female Differences on Leadership Behavior and People and Network between Gender: 27

8 To compare the perceptions between male and female on leadership behavior and people and network in knowledge management maturity, the independent samples t-test is used as the distribution of data of both dimensions are normal. The results are summarized in Table 7. In the case of leadership behavior, the p-value is which is more than This is not significant at 5% level or >0.05. Therefore, it can be concluded that male and female respondents do not differ in their perception on leadership behavior. With regards to the perception on people and networks, the p-value is which is more than This is not significant at 5% level or >0.05. Therefore, it can be concluded that male and female respondents do not differ in their opinion regarding people and network. Table 7: The Independent Samples t-test Result of the Leadership Behavior and People and Network Gender Mean Score p-value Leadership behavior Male Female Male People and Network Female Differences on KM Strategy among Respondents of Different Years of Working Experience: Non-parametric statistical test called Kruskal-Wallis test was used in this analysis because the data were not normally distributed. Table 8 represents the summary of Kruskal-Wallis Test among respondents with different years of working experience. In the case of KM strategy, the p-value of is not significant at 5% level (pvalue=0.922>0.05). Therefore, it can be concluded that, the perception on KM strategy among respondents is the same regardless of how many years of working experience the respondents belong. Table 8: Kruskal-Wallis Test on KM Strategy among Respondents with Different Years of Working Experience Years of Working Experience Sample size Mean Rank Chi-square p-value 5 or less years years years Difference on Leadership Behavior and People and Network among Respondents with Different Years of Working Experience Table 9 illustrates the ANOVA test result on leadership behavior among respondents with different years of working experiences. 28

9 In the case of leadership behavior, the p-value of is not significant at 5% level or p- value of 0.666>0.05. It is concluded that, the perception on leadership behavior is the same regardless of how many years of working experience the respondents belong. The p-value of is not significant at 5% level or p-value is 0.780>0.05. It is concluded that, the perception on people and network is the same regardless of how many years of working experience the respondents belong. Table 9: ANOVA Test on Leadership and Behavior and People and Network among respondents with different years of working experiences Variables Sum of squares df Mean F Sig. Square Leadership and Between Groups behaviors Within Groups Total People network and Sum of squares df Mean Square F Sig. Between Groups Within Groups Total Relationship between Factors of KM Maturity (KM strategy, Leadership Behavior and People and Network) The final section addresses the third objective of the study which is To identify the relationships between factors of KM maturity (KM strategy, leadership behavior, and people and network). A Spearman s rho correlation analysis was carried out to determine the relationship between factors of KM maturity (KM strategy, leadership behavior, and people and network). The results as depicted in Table 10 showed that KM strategy was positively and moderately correlated with leadership behavior (p<0.01, r=0.758) followed by leadership behavior with people and networks (p<0.01, r=0.682), and people and network with KM strategy (p<0.01, r=0.631). Thus, the results disclosed significant positive relationships between all variables at the confidence level of 1%. The interpretation of this relationship is that on the average, a respondent who has a moderate level on their perceiveness on KM strategy is fairly likely to have a moderate level on their perceiveness on leadership behavior. A respondent who has a moderate level on their perceiveness on leadership behavior is fairly likely to have a moderate level on their perceiveness on people and network. A respondent who has a moderate level on their perceiveness on people and network is fairly likely to have a moderate level on their perceiveness on KM strategy. 29

10 Table 10: Coefficient of Correlation between Mean Scores of KM Strategy, Leadership Behavior, and People and Network KM Strategy Leadership People and Network Behavior KM Strategy Correlation Coefficient ** 0.631** Sig. (2-tailed) N Leadership Behavior Correlation 0.758** ** Coefficient Sig. (2-tailed) N People and Network Correlation 0.631** 0.682** Coefficient Sig. (2-tailed) N CONCLUSIONS This study has examined the level of KM strategy, leadership behavior, and people and network in an organization. This study had revealed several important profile and practices with regard to KM maturity in organization. The results illustrated that the perceptions of the respondents on factors of KM maturity are quite similar and positively rated by employees. The study has contributed to the understanding of the level of KM strategy, leadership behavior, people and network in a telecommunication company in Malaysia. The contribution of the study can also be seen in terms of providing information regarding KM maturity to the body of knowledge especially for knowledge management in Malaysia. It is not the attempt of the study to develop a process of measuring knowledge management maturity in the organizations in Malaysia, however, the assessment of the study s result can provide ways for successfully measuring knowledge management maturity by considering the KM practitioners in the organization. In addition, the findings of this study contributes to the literature on KM maturity since no previous empirical studies has been done in the Malaysian environment. This study provides and helps the organizations to have a glimpse of knowledge management maturity especially to KM practitioners and thus provides guidance to assess the KM maturity in their organization. Finally, this study also hopes to stimulate future research pertaining technology and knowledge databases in measuring KM maturity in the organizations. REFERENCES Arias Aranda, D., & Molina-Fernández, L. M. (2002). Determinants of innovation through a knowledge-based theory lens. Industrial Management & Data Systems, 102(5), Chan, K. H., Chu, S. K. W., & Wu, W. W. (2012). Exploring the correlation between knowledge management maturity and intellectual capital efficiency in Mainland Chinese listed companies. Journal of Information & Knowledge Management, 11(03), Chua, A. Y. K. & Chaudhry, A. S. (2008). Knowledge management measurement: An agenda for organizations and economies. In Srikantaiah, T. K. & Koenig, M. E. D. 30

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