Successful Knowledge Sharing Among the Staffs of Economics and Business Management Faculties in Higher Institutions Education

Transcription

1 Successful Knowledge Sharing Among the Staffs of Economics and Business Management Faculties in Higher Institutions Education Salina Daud a, Nuradli Ridzwan Shah Mohd Dali b and Hanifah Abdul Hamid c a,c Universiti Tenaga National College of Business Management and Accounting Campus Sultan Haji Ahmad Shah Bandar Muadzam Shah, Pahang, Malaysia Tel: , Fax: a salina@kms.uniten.edu.my and c hanifah@kms.uniten,.edu.my b Kolej Universiti Islam Malaysia Faculty of Economics and Muamalat Bandar Baru Nilai Nilai Negeri Sembilan Tel: mohdddalins@yahoo.com ABSTRACT Knowledge is seen as the most important strategic resource in organization. Knowledge sharing is a mechanism for faculty members to capture, disseminate, transfer and apply useful knowledge. This study is to examine the factors and barriers which contribute to successful knowledge sharing among Higher Institutions Education (HIEs) faculty members in Malaysia. A crosssectional survey is used as a methodology for data collection. The factors of knowledge sharing for this study are nature of knowledge, working culture, staff attitudes, motivation to share and opportunities to share. The study shows that there is a significant relationship between knowledge sharing with all of the factors for private university, but it is insignificant for public university. This is due to certain factors such as university infrastructure, working culture and staff attitude. However for both HIEs, most of the factors are positively correlated. Keywords Knowledge management, knowledge sharing, learning organization 1.0 INTRODUCTION Organizational performance can be improved by providing useful and relevant knowledge to employees (Alavi & Leidner, 2001; Hansen, Nohria, & Tierney, 1999). Knowledge is recognized as the most important resource in organization (Nahapiet & Ghoshal, 1998; Spender & Grant, 1996). It is considered as the primary source of competitive advantage (Stewart, 1997) and critical to the long term sustainability and success of organization (Nonaka & Takeuchi, 1995). According to knowledge-based view of the firm, organizations need to have the ability to integrate tacit knowledge embedded in the minds of individuals in order for them to survive and sustain competitive advantage (Barnett & Hansen, 1996; Grant, 1996; Nonaka, 1994) Leadbeater (2000) framed the value of knowledge into four major ways: extraordinary leverage and increasing returns; an efficient and effective re-creation of knowledge can represent a substantial source of competitive advantage; uncertain value - knowledge investment value is often difficult to estimate in terms of future discounted cash flows, and 1

2 uncertain value sharing - company may not benefit from knowledge investments because knowledge is embedded in people s mind Rodgers (2003) found that knowledge must be reconceptualized and quantified as a basis of information related to organization performance. The acknowledgement of knowledge as the key resource of today s organization affirms the need for processes that facilitate the creation, sharing and leveraging of individual and collective knowledge (Becerra-Fernandez & Sabherwal, 2001). The key to successfully managing knowledge is now being seen as dependent on the connection between individuals within the organization (Brown & Duguid, 1991). Individuals in organization have always created and shared knowledge. Therefore knowledge sharing has been considered to be a normal function in organization. The focus of this study is to examine the knowledge that exists with and within faculty members in the process of knowledge sharing between individuals. The purpose of this article is to examine factors and barriers that contribute to knowledge sharing practices among faculty members in private and public Higher Institutions Education (HIEs) in Malaysia. 2.0 LITERATURE REVIEW There are three basic processes of knowledge management namely, knowledge acquisition, knowledge sharing and knowledge utilization. Knowledge acquisition is the process of development and creation of insights, skills and relationships while knowledge sharing is the act of disseminating and making available knowledge that is already known, and knowledge utilization is where learning is integrated into the organization (Tiwana, 2002). Knowledge sharing can be a medium to encourage knowledge exchange and creation in the organizations in order to recognize their competitive advantages (Liebowitz, 2001). Employees need to understand how to access and work with information and knowledge, share it and create conditions on how to use it. The understanding of information and knowledge will become a source of intellectual capital through its expression in goods and services. In order to maximimize the sharing and communication of knowledge, companies need to consider several organizational dimensions such as information technology, organization structure, organizational culture and reward systems (Liebowitz & Beckman, 1998). Knowledge sharing success does not depend on technology alone but it is also related to behavioral factors (Calantone, Cavusgil, & Zhao, 2002; Kidwell, Mossholder, & Bennett, 1997; Liao, Chang, Cheng, & Kuo, 2004; Walsham, 2002). An innovative culture, a capacity to learn from failure and good information quality are factors for successful knowledge sharing in public service organizations (Taylor & Wright, 2004). A study on knowledge sharing practices was carried out at national car industry Malaysia; the researchers found that immediate supervisors and employees attitude are the main contributors to successful knowledge sharing besides organizational culture and work group support (Heng et al., 2005). The researchers found that all the four factors are positively correlated to knowledge sharing. There are several published literatures on knowledge sharing barriers mainly related to people or technology. Among the barriers in knowledge sharing between departments are the differences in the nature of business, differences in knowledge requirements, lack of cross-department interaction and lack of information technology support (Michailova & Gupta, 2005). Knowledge sharing barriers are categorized into three main domains; individual, organizational and technological. At individual level, barriers are often associated to factors such as lack of communication skills and social networks, differences in national culture, differences in position status, and lack of time and trust. At organizational level, the barriers are related to factors such as lack of infrastructure and resources, the accessibility of formal and informal meeting spaces and the physical environment. At technology level, barriers are correlated to factors such as unwillingness to use application, unrealistic expectations of IS/IT systems, and difficulties in building, integrating and modifying technology-based systems (Riege, 2005). 2

3 3.0 METHODOLOGY A cross-sectional survey is used as a method to collect data from Business Management faculty members of HIEs in Malaysia. The respondents are divided into two categories which are private and public university. The methodology of research employed was through survey questionnaires. Statistical data and reports were also obtained from the HEIs as a source of secondary data to complement the findings of the survey. Four factors of knowledge sharing for this study were adapted from Ipe (2003), who proposed a conceptual framework for knowledge sharing in organizations. The factors are nature of knowledge, working culture, motivation to share and opportunities to share. Factor on staff s attitude was adapted from Heng et al. (2005). The focus of this study is on knowledge sharing between Economics and Business Management faculty members in HIEs. A list of variables was given to the respondents and they were asked to indicate their level of agreement based on Likert-scale, with the following representation of level of agreement; 1 indicates strongly agree ; 2 indicates agree ; 3 indicates neutral ; 4 indicates disagree and 5 indicates strongly disagree. 4.0 RESULTS AND DISCUSSION 4.1 Demographic Profiles Table 1: Demographic Profiles Profiles Classification Private University (%) Public University (%) Age >40 Gender Male Female Race Malay Chinese Indian Others Qualification Ph D Master Bachelor Area of Specialization Working Experience (years) Others Business Management HRM Marketing Entrepreneurship Finance Accounting Economics Language Hospitality Islamic Studies Others >

4 Respondents profiles are based on age, gender, ethnic groups, degree of qualification, area of specialization and number of year working as shown in the above Table. Based on Table 1, respondents are categorized into two groups: private and public universities. Private University s respondents consist of 61% female and 39% male, indicating a domination of female in the education line. The trend is similar to public universities in which female respondents are 57% and male are 43% respectively. Looking at the age of the faculty members, most of the respondents from private university are in the range of years of age which consists of 39%. While majority of faculty members in public university (38%) are in the range of years of age. Most of the respondents from both HIEs are Malays (86% for private university and 76% for public university). There are no Chinese and Indian respondents for public university; the balance of 24% is for others (Sudan, Indonesian and Iranian). As for the private university there are Chinese and Indian respondents which consist of 11% and 4% respectively. 4.2 Reliability Test Table 2: Reliability Analysis Factors Number of Items Cronbach s Alpha Nature of knowledge Working culture Staff attitude Motivation to share Opportunities to share Reliability test is an assessment of the degree of consistency between multiple measurements of a variable. Cronbach s alpha is the most widely used measurement tool with a generally agreed lower limit of 0.7. In Table 2 all the alpha coefficients were above the required level of 0.7 as suggested by Nunnally (1978). 4.3 Mean Scores Table 3: Mean Score of Knowledge Sharing Factors Factors Private University Public University Nature of knowledge Working culture Staff attitude Motivation to share Opportunities to share Table 3 shows mean scores for both private and public university. From one-way ANOVA test in the following Table, it shows that there is no significant difference in mean score between both universities. It implies that all the entire factors contribute to knowledge sharing practices. Table 4: One-way ANOVA Factors Sum of df Mean Squares Square F Sig. Nature of knowledge Between Groups Working culture Between Groups Staff attitude Between Groups Motivation to share Between Groups Opportunities to share Between Groups

5 4.4 Regression The model assumes knowledge sharing variable as dependent variables and independent variables comprising of nature of knowledge, working culture, staff attitude, motivation to share knowledge and opportunities to share knowledge. Nature of knowledge is divided into implicit and explicit knowledge, and value of knowledge. Table 5: Model Summary Private University Model R R Square Adjusted R Sig. F Square Change Table 5 shows the model summary for private university sample. The regression model suggests that there is positive relationship between dependent and independent variables with R= The estimated R-square= which means that 42% variation in knowledge sharing is explained by all independent variables. Table 6: Model Summary Public University Model R R Square Adjusted R Sig. F Square Change As for the public university, the analysis (Table 6) shows that there is no significant relationship between knowledge sharing and independent variables. This is due to certain factors such as university infrastructure, working culture and staff attitude. 4.4 Correlation Table 7: Correlations Private University Factors Nature of knowledge Working culture Staff attitude Motivation to share Opportunities to share Nature of knowledge 1.642(**) Working culture.642(**) 1.505(**).430(*).478(*) Staff attitude (**) Motivation to share (*) (*) Opportunities to share (*) (*) 1 * Correlation is significant at the 5 level (2-tailed) ** Correlation is significant at the 1 level (2-tailed) Looking at the correlations for private university, nature of knowledge and staff attitude is only correlated to working culture. As for working culture it is obvious that it is positively correlated with the rest of the variables and significant at 95% and 99% percent confidence level. Motivation to share is only correlated with working culture and opportunities to share. Opportunities to share knowledge are positively correlated with working culture and motivation to share. All the variables are correlated at either p=5 or p= 1. From the analysis, it shows that working culture is the main factors that influence faculty members to share knowledge between each other. Table 8: Correlations Public University Factors Nature of knowledge Working culture Staff attitude Motivation to share Opportunities to share Nature of knowledge 1.703(**).583(**).841(**).712(**) Working culture.703(**) 1.716(**).691(**).301 Staff attitude.583(**).716(**) 1.633(**).518(*) Motivation to share.841(**).691(**).633(**) 1.720(**) Opportunities to share.712(**) (*).720(**) 1 ** Correlation is significant at the 1 level (2-tailed) * Correlation is significant at the 5 level (2-tailed) Table 8 shows a significant correlation among the entire factors in public university except for working culture and opportunities to share. Nature of knowledge is highly correlated to motivation to share knowledge, with correlation coefficient (r) = at 10% significant level. Whereas staff attitude and motivation to share is the least correlated coefficient with r = at 5% significant level. 5

6 4.5 Barriers to Knowledge Sharing Reige (2005) addressed that knowledge sharing barriers are categorized into three main domains; individual, organizational and technological. Based on his theory, we found out that the private university has three barriers that falls into two categories. The first category is individual, such as the time constraint faced by the lecturers perhaps due to teaching hour overload. The other barriers are lack of useful databases for the faculty and lack of proper infrastructure which fall under the domain of organization barriers. Lack of useful database is due to many of the online databases that are non-related to business faculty. On the other hand lack of proper infrastructure occurs due to online information like library database available only within campus area. As for the public university, their barriers of knowledge sharing also fall into two major domains: individual and organizational. Individual barriers consist of faculty members having time constraints, faculty members negative attitudes towards knowledge sharing; where some of the staff keep their ego high because they posses more knowledge than others. Other barriers which fall in the individual category are lack of cooperation among faculty members. Differences in national culture also create barriers to knowledge sharing, where some of the respondents suggested an open discussion should being practiced among faculty members. An overloaded work given to faculty members is also a barrier which might cause lack of communication among them which will creates miscommunication. The organizational barriers for the public university consist of lack of infrastructure and discouraging organization environment. Lack of infrastructure can be seen from inadequate IT network and limited database for knowledge sharing. There is also discouraging working environment where public university is practicing a mechanistic systems where there are many bureaucracies in doing work. Indirectly, it will discourage knowledge sharing in the organization. 5.0 CONCLUSION From the results and discussion, it shows that working culture plays an important role in enhancing knowledge sharing among faculty members. The results support the findings by Connelly and Kelloway (2003) who found that management s support for knowledge sharing and a positive social interaction culture are significant predictors for a positive knowledge sharing culture. It shows that knowledge sharing factors do not depend on technology alone (Calantone, Cavusgil, & Zhao, 2002; Kidwell, Mossholder, & Bennett, 1997; Liao, Chang, Cheng, & Kuo, 2004; Walsham, 2002). Basically, both of the faculty members in private and public university could enhance their knowledge sharing practices if the infrastructure is upgraded. Private university for instance, may consider upgrading its online database for the business faculty members by subscribing to more business database. The infrastructure can also be upgraded by giving opportunities for the faculty members to get access to the online database outside of the campus. As for the public university, it may consider to change their systems from mechanistic to organic approach, in order to encourage knowledge sharing. The present database may be upgraded to more relevant and varieties business faculty database. Both universities shall encourage their faculty members to share knowledge by organizing an open discussions, forums, seminars or colloquiums among them. As a conclusion, the study shows that successes of knowledge sharing are based on three main factors; motivation, encouragement and stimulation of individual employees to capture, disseminate, transfer and apply useful knowledge. Secondly, an organization infrastructure which facilitates knowledge flows, processes and resources. It will provide a continual learning culture, clear communication of organization goals and strategy that link knowledge sharing practices that will benefit all employees and leaders. Lastly, technology is a mechanism to provide knowledge sharing platform so that knowledge both from diverse internal or external sources could be accessed by everybody in need of it. 6

7 There are two limitations in this study. First, data is collected by using cross-sectional survey method. Second, the study focuses on Economics and Business Management faculty members of HIEs in Malaysia where the results limit generalization for the study. 6.0 REFERENCES Alavi, M., & Leidner, D. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. Management Information Systems Quarterly, 25(1), Barnett, W. P., & Hansen, M. T. (1996). The red queen in organizational evolution. Strategic Management Journal, 17(Summer), Becerra-Fernandez, I., & Sabherwal, R. (2001). Organizational knowledge management: A contingency perspective. Journal of Management Information Systems, 18(1), Brown, J. S., & Duguid, P. (1991). Organizational learning and communities of practice: Toward a unified view of working, learning, and innovation. Organization Science, 2(1), Calantone, R. J., Cavusgil, S. T., & Zhao, Y. (2002). Learning orientation, firm innovation capability, and firm performanmce. Industrial Marketing Management, 31, Connelly, C. E., & Kelloway, E. K. (2003). Predictors of employees' perceptions of knowledge sharing cultures. Leadership and Organization Development Journal, 24(5/6), Grant, R. (1996). Prospering in dynamically competitive environments: Organizational capability as knowledge integration. Organization Science, 7(4), Hansen, M. T., Nohria, N., & Tierney, T. (1999). What's your trategy for managing knowledge? Harvard Business Review, 77(2), Heng, L. H., Mohd Nor, N., Omain, S. Z., Mohd Salleh, N., Jusoh, A., & Md Yatim, S. (2005). Perkongsian pengetahuan di syarikat pengedaran kereta nasional Malaysia. Paper presented at the National Conference of Management of Technology and Technology Entrepreneurship, Johor Bharu, Johor. Ipe, M. (2003). Knowledge sharing in organizations: A conceptual framework. Human Resource Development Review, 2(4), Kidwell, R. E., Mossholder, K. W., & Bennett, N. (1997). Cohesiveness and organizational citizenship behavior: A multilevel analysis using work group and individuals. Journal of Management, 23(6), Leadbeater, C. (2000). New meaures for the new economy. The Institute of Chartered Accountants, London. Liao, S. H., Chang, J. C., Cheng, S. C., & Kuo, C. M. (2004). Employee relationship and knowledge sharing: A case study of a Taiwanese finance and securities firm. Knowledge Management Research and Practice, 2, Liebowitz, J. (2001). Knowledge management and its link to artificial intelligence. Expert systems with applications, 20, 1-6. Liebowitz, J., & Beckman, T. (1998). Knowledge organizations: What every manager should know. CRC Press LLC. Michailova, S., & Gupta, A. (2005). Knowledge sharing in consulting companies: Opportunities and limitations of knowledge codification. Journal of Information & Knowledge Management, 4(3), Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital and the organizational advantage. Academy of Management Review, 23(3),

8 Nonaka, I. (1994). The dynamics theory of organizational knowledge creation. Organization Science, 5(1), Nonaka, I., & Takeuchi, H. (1995). The knowledge creating company: How Japanese companies create the dynamics of innovation.: New York: Oxford University Press. Nunnally, J. C. (1978). Psychometric Theory: New York, McGraw Hill. Riege, A. (2005). Three-dozen knowledge sharing barriers managers must consider. Journal of Knowledge Management, 9(3), Rodgers, W. (2003). Measurement and reporting of knowledge-based assets. Journal of Intellectual Capital, 4(2), Spender, J. C., & Grant, R. M. (1996). Knowledge and the firm: Overview. Strategic Management Journal, 17, 5-9. Stewart, T. A. (1997). Intellectual capital: The new wealth of organization: New York: Doubleday Currency. Taylor, W. A., & Wright, G. H. (2004). Organizational readiness for successful knowledge sharing: Challenges for public sectors managers. Information Resources Management Journal, 17(2), Tiwana, A. (2002). The Knowledge Management Toolkit: Orchestrating IT, Strategy and Knowledge Platforms: Prentice Hall. Walsham, G. (2002). Knowledge management: the benefits and limitations of computer systems. European Management Journal, 19(6),