Bilgi Paylaşımının Önündeki Çeşitli Engellerin Önceliklendirilmesi: Türkiye’deki Akademisyenler Üzerine Neden-Etki Araştırması

Year 2021, Volume: 11 Issue: 3, 578 - 596, 31.12.2021

Esra Baran Kasapoğlu , Berk Küçükaltan , Abdullah Açık , İlke Sezin Ayaz , Ömür Saatçioğlu

https://doi.org/10.2399/yod.21.805205

Cited By: 1

Abstract

Bu çalışma, Türkiye’deki akademisyenler arasında bilgi paylaşımının önündeki çeşitli engel türlerini belirlemeyi ve engeller ile etki dereceleri arasındaki ilişkileri incelemeyi amaçlamaktadır. Bu doğrultuda, nitel ve nicel yaklaşımlar iki aşamada kullanılmaktadır. İlk aşamada, literatür taraması ile bilgi paylaşım engelleri belirlenmiş ve Türk akademisyenlerin önündeki mevcut engelleri saptamak üzere uzman görüşleri ile belirlenen engeller organizasyonel, bireysel ve teknolojik boyutlar altında kategorilendirilmiştir. İkinci aşamada ise, tanımlanan engeller ve etkileşimleri, Yorumlayıcı Yapısal Modelleme (ISM) ve Karar Verme Deneme ve Değerlendirme Laboratuvarı (DEMATEL) yöntemleriyle ayrıntılı olarak incelenmiştir. Araştırmanın bulguları, örgütsel ve bireysel bilgi paylaşım engellerinin teknolojik engellerden daha etkili olduğunu ortaya koymaktadır. ISM ve DEMATEL bulgularına göre, “kurumsal yapı”, “güç ilişkileri” ve “destekleyici kurum kültürü” Türkiye’deki akademisyenler arasında bilgi paylaşımının itici güçleridir. Bu çalışma, hem akademik bilgi paylaşımını teşvik etmek için gerekli eylemleri gerçekleştirmeyi hem de üniversitelerin performanslarını geliştirmeyi sağlayabilecek hiyerarşik ve nedensel bir ilişki modeli sağlamaktadır. Bulgular, akademisyenlerin bilgi paylaşım engellerinin aşılabilmesi için temel engellerin neler olduğu ve birbiriyle nasıl ilişkili oldukları konusunda yararlı bilgiler sunmaktadır. Dolayısıyla, sunulan bulgular hem akademik camiaya hem de düzenleyici eylemleri gerçekleştirmekten sorumlu politika yapıcılara katkıda bulunma konusunda önemli potansiyeller barındırmaktadır.

Keywords

Akademisyenler, bilgi paylaşım engelleri, bilgi paylaşımı, bilgi yönetimi

Prioritizing Different Types of Barriers to Knowledge Sharing: A Cause-and-Effect Analysis of the Views of Academics in Turkey

Abstract

This study aims to identify different types of barriers to knowledge sharing among academics in Turkey and to investigate the relationships between the barriers and their degree of impact. Accordingly, it implements qualitative and quantitative approaches in two phases. In the first phase, the knowledge sharing barriers are identified through the literature review and categorized under organizational, individual, and technological dimensions via expert opinions so as to determine current barriers for the Turkish academics. In the second phase, the identified barriers and their interactions are more deeply investigated by using the Interpretive Structural Modeling (ISM) and Decision Making Trial and Evaluation Laboratory Method (DEMATEL) methods. The findings of the study reveal that organizational and individual knowledge sharing barriers have a stronger effect than technological barriers. According to ISM and DEMATEL findings, “corporate structure”, “power relations"”, and “supportive corporate culture” are the driving forces for the knowledge sharing among the academics in Turkey. This study provides a hierarchical and causal relation model that may enable both performing the actions needed to promote academic knowledge sharing and advancing university performances. The findings offer useful insights on what the key barriers are and how these interrelate, so that they can be overcome. Thus, the findings hold significant potential to contribute both to the academic field and to the policymakers who are in charge of taking regulatory actions.

Keywords

Academics, knowledge management, knowledge sharing, knowledge sharing barriers

References

• Al-Kurdi, O., El-Haddadeh, R., & Eldabi, T. (2018). Knowledge sharing in higher education institutions: A systematic review. Journal of Enterprise Information Management, 31(2), 226–246.
• Ardichvili, A. (2008). Learning and knowledge sharing in virtual communities of practice: Motivators, barriers, and enablers. Advances in Developing Human Resources, 10(4), 541–554.
• Assefa, T., Garfield, M., & Meshesha, M. (2013). Barriers of knowledge sharing among employees: The case of commercial bank of Ethiopia. Journal of Information & Knowledge Management, 12(2), 1350014.
• Blackman, D., & Kennedy, M. (2009). Knowledge management and effective university governance. Journal of Knowledge Management, 13(6), 547–563.
• Chahal, S. S., & Savita, S. (2014). Knowledge sharing among university teaching staff: A case study. Maharshi Dayanand University Research Journal, 21–32.
• Charband, Y., & Navimipour, N. J. (2018). Knowledge sharing mechanisms in the education: A systematic review of the state of the art literature and recommendations for future research. Kybernetes, 47(7), 1456–1490.
• Chauhan, A., Singh, A., & Jharkharia, S. (2016). An interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL) method approach for the analysis of barriers of waste recycling in India. Journal of the Air & Waste Management Association, 68(2), 100–110.
• Cheng, M. Y., Ho, J. S. Y., & Lau, P. M. (2009). Knowledge sharing in academic institutions: A study of multimedia university Malaysia. Electronic Journal of Knowledge Management, 7(3), 313–324.
• Chong, C. W., Yuen, Y. Y., & Gan, G. C. (2014). Knowledge sharing of academic staff: A comparison between private and public universities in Malaysia. Library Review, 63(3), 203–223.
• Chuang, H. M., Lin, C. K., Chen, D. R., & Chen, Y. S. (2013). Evolving MCDM applications using hybrid expert-based ISM and DEMATEL models: An example of sustainable ecotourism. The Scientific World Journal, 2013, 1–18.
• Dehghani, M. (2019). Knowledge-sharing mechanisms in a socio-technical collaborative project in IT-related faculties: Preliminary findings. Proceedings of the 27th European Conference on Information Systems (ECIS) (pp. 1–12), June 8–14, 2019, Stockholm & Uppsala: Sweden.
• Demirel, Y. (2007). A study over the impact of knowledge and knowledge sharing on company performance. [Article in Turkish] Yönetim Bilimleri Dergisi, 5(2), 91–106.
• Fernie, S., Green, S. D., Weller, S. J., & Newcombe, R. (2003). Knowledge sharing: context, confusion and controversy. International Journal of Project Management, 21, 177–187.
• Fullwood, R., Rowley, J., & Delbridge, R. (2013). Knowledge sharing amongst academics in UK universities. Journal of Knowledge Management, 17(1), 123–136.
• Hautala, J. (2011). International academic knowledge creation and ba. A case study from Finland. Knowledge Managaement Research & Practice, 9(1), 4–16.
• Hew, K. F., & Hara, N. (2007). Empirical study of motivators and barriers of teacher online knowledge sharing. Educational Technology Research and Development, 55(6), 573–595.
• Jain, K. K., Sandhu, M. S., & Sidhu, G. K. (2007). Knowledge sharing among academic staff: A case study of business schools in Klang Valley, Malaysia. Kuala Lumpur: UCSI Centre for Research Excellence.
• Jeenger, P., & Kant, R. (2013). Understanding the knowledge sharing barriers in organisation: a fuzzy AHP approach. Journal of Information & Knowledge Management, 12(1), 1350003.
• Joshi, Y., Parmer, S., & Chandrawat, S. S. (2012). Knowledge sharing in organizations: Modeling the barriers, an interpretive structural modeling approach. International Journal of Engineering and Innovative Technology (IJEIT), 2(3), 207–214.
• Kalkan, V. D. (2004). Türk üniversitelerinde bilgi yönetimi süreçlerinin geliştirilmesi: Öncelikler ve öneriler. Proceeding of 3rd National Knowledge, Economy & Management Congress (pp. 775–782). November 25–26, 2004, Eskişehir, Turkey.
• Karaoğlan, S., & Şahin, S. (2016). An integrated approach to the purchase problem of businesses with DEMATEL and AHP methods: A DSLR camera example. [Article in Turkish] İşletme Araştırmaları Dergisi, 8(2), 359–375.
• Kehm. B., & Teichler, U. (2007). Research on internationalisation in higher education. Journal of Studies in International Education, 11(3/4), 260–273.
• Kim, S., & Ju, B. (2008). An analysis of faculty perceptions: Attitudes toward knowledge sharing and collaboration in an academic institution. Library & Information Science Research, 30(4), 282–290.
• King, W. R. (2009). Knowledge management and organizational learning. In W. R. King (Ed.), Knowledge management and organizational learning (pp. 3–13). Boston, MA: Springer.
• Liebowitz, J., & Beckman, T. J. (1998). Knowledge organizations: What every manager should know. New York, NY: CRC Press LLC.
• Lindsey, K. L. (2006). Knowledge sharing barriers. In D. G. Schwartz (Ed.), Encyclopedia of knowledge management (pp. 499–506). Hershey, PA: IGI Global.
• Luthra, S., Garg, D., & Haleem, A. (2015). An analysis of interactions among critical success factors to implement green supply chain management towards sustainability: An Indian perspective. Resources Policy, 46(1), 37–50.
• Mandal, A., & Deshmukh, S. G. (1994). Vendor selection using interpretive structural modelling (ISM). International Journal of Operations and Production Management, 14(6), 52–59.
• Mehregan, M. R., Hashemi, S. H., Karimi, A., & Merikhi, B. (2014). Analysis of interactions among sustainability supplier selection criteria using ISM and fuzzy DEMATEL. International Journal of Applied Decision Sciences, 7(3), 270–294.
• Menteş, A., Akyıldız, H., & Helvacıoğlu, I. (2014). A grey based DEMATEL technique for risk assessment of cargo ships. Proceedings of the 7th International Conference on Model Transformation (ICMT 2014), July 21–22, 2014, York, UK.
• Olaniran, O. J. (2017). Barriers to tacit knowledge sharing in geographically dispersed project teams in oil and gas projects. Project Management Journal, 48(3), 41–57.
• Patil, S. K., & Kant, R. (2014). A hybrid approach based on fuzzy DEMATEL and FMCDM to predict success of knowledge management adoption in supply chain. Applied Soft Computing, 18, 126–135.
• Ramayah, T., Yeap, J. A., & Ignatius, J. (2013). An empirical inquiry on knowledge sharing among academics in higher learning institutions, Minerva, 51(2), 131–154.
• Riege, A. (2005). Three-dozen knowledge-sharing barriers managers must consider. Journal of Knowledge Management, 9(3), 18–35.
• Rosen, B., Furst, S., & Blackburn, R. (2007). Overcoming barriers to knowledge sharing in virtual teams. Organizational Dynamics, 3(36), 259–273.
• Ruggles, R. L. (1997). Tools for knowledge management: An introduction knowledge management tools. New York, NY: Butterworth-Heinemann.
• Saatçioğlu, Ö. Y., & Özmen, Ö. N. T. (2010). Analyzing the barriers encountered in innovation process through interpretive structural modelling: Evidence from Turkey. Yönetim ve Ekonomi, 17(2), 207–225.
• Santosh, S., & Panda, S. (2016). Sharing of knowledge among faculty in a Mega Open University. Open Praxis, 8(3), 247–264.
• Shao, J., Taisch, M., & Ortega-Mier, M. (2016). A grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) analysis on the barriers between environmentally friendly products and consumers: Practitioners’ viewpoints on the European automobile industry. Journal of Cleaner Production, 112, 3185–3194.
• Sharma, B. P., & Singh, M. D. (2013a). Modeling individual/group knowledge sharing barriers in Indian engineering industry – an integrated ISM, AHP and similarity coefficient approach. International Journal of Management Science and Engineering Management, 8(3), 179–198.
• Sharma, B. P., & Singh, M. D. (2013b). Modeling the metrics of individual, organisational and technological knowledge sharing barriers: An analytical network process approach. Journal of Information & Knowledge Management, 12(3), 1350018.
• Sharma, B. P., Singh, M. D., & Neha, A. (2012). Knowledge sharing barriers: An approach of interpretive structural modeling. IUP Journal of Knowledge Management, 10(3), 35–52.
• Sohail, M. S., & Daud, S. (2009). Knowledge sharing in higher education institutions: Perspectives from Malaysia. VINE Journal of Information and Knowledge Management Systems, 39(2), 125–142.
• Tahir, L. M., Musah, M. B., Abdullah, A. H., Musta’amal, A. H., & Abdullah, M. H. A. (2016). Technical college teachers sharing their knowledge: Does leadership, institutional factors or barriers predict their practices? Educational Studies, 42(5), 465–492.
• Thani, F. N., & Mirkamali, S. M. (2018). Factors that enable knowledge creation in higher education: A structural model. Data Technologies and Applications, 52(3), 424–444.
• Tian, J., Nakamamon, Y., & Wierzbicki, A. P. (2009). Knowledge management and knowledge creation in academia: A study based on surveys in a Japanese research university. Journal of Knowledge Management, 13(2), 76–92.
• Tseng, S. M. (2017). Investigating the moderating effects of organizational culture and leadership style on IT-adoption and knowledge-sharing intention. Journal of Enterprise Information Management, 30(4), 583–604.
• Uit Beijerse, R. P. (1999). Questions in knowledge management: Defining and conceptualising a phenomenon. Journal of Knowledge Management, 3(2), 94–110.
• Wang, L., Cao, Q., & Zhou, L. (2018). Research on the influencing factors in coal mine production safety based on the combination of DEMATEL and ISM. Safety Science, 103, 51–61.
• Wang, L., Wang, H., & Wang, K. (2010). The investigation analysis on knowledge-sharing barriers and incentives of university scientific research and innovation teams. International Conference on Management and Service Science (pp. 1–4), August 24–26, 2010, Wuhan, China.
• Wang, S., & Noe, R. A. (2010). Knowledge sharing: A review and directions for future research. Human Resource Management Review, 20(2), 115–31.
• Yassin, F., Salim, J., & Sahari, N. (2013). The influence of organizational factors on knowledge sharing using ICT among teachers. Procedia Technology, 11, 272–280.
• Yeşil, S., & Hırlak, B. (2013). An empirical investigation into the influence of knowledge sharing barriers on knowledge sharing and individual innovation behavior. International Journal of Knowledge Management, 9(2), 38–61.
• Yin, S. H., Wang, C. C., Teng, L. Y., & Hsing, Y. M. (2012). Application of DEMATEL, ISM, and ANP for key success factor (KSF) complexity analysis in RD alliance. Scientific Research and Essays, 7(19), 1872–1890.
• Yudatama, U. K. Y., Hidayanto, A. N., & Nazief, B. A. A. (2018). Approach using interpretive structural model (ISM) to determine key sub-factors at factors: Benefits, risk reductions, opportunities and obstacles in awareness IT governance. Journal of Theoretical and Applied Information Technology, 96(16), 5537–5549.
• Zawawi, A. A., Zakaria, Z., Kamarunzaman, N. Z., Noordin, N., Sawal, M. Z. H. M., Junos, N. M., & Najid, N. S. A. (2011). The study of barrier factors in knowledge sharing: A case study in public university. Management Science and Engineering, 5(1), 59–70.