ENHANCING ORGANIZATIONAL KNOWLEDGE SHARING THROUGH FUZZY LOGIC-DRIVEN DECISION SYSTEMS
DOI:
https://doi.org/10.29121/shodhkosh.v4.i2CDSDAD.2023.6206Keywords:
Fuzzy Logic, Knowledge Sharing, Decision Support Systems, Organizational LearningAbstract [English]
In today organizations, a great number of knowledges is produced and handled. It is highly important to disseminate this knowledge across company employees in order to improve decision-making and innovation. But, the conventional mechanisms of knowledge management suffer difficulties of uncertainty, obscurity and underlying information gaps. Fuzzy logic-based decision systems are used as a means to enhance organizational knowledge-sharing in this research experiment. Fuzzy logic can be used to simplify and enhance reliability of decision-making since they are smoother and reliable decisions using uncertain and imprecise information. This study employs the descriptive statistics and hypothesis testing to prove the affirmation that fuzzy systems have the power to enhance communication, collaboration and learning in organizations.
References
Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136.
Bose, R. (2004). Knowledge management metrics. Industrial Management & Data Systems, 104(6), 457–468.
Choy, K. L., Lee, W. B., & Lo, V. (2002). An intelligent supplier management tool using case-based reasoning techniques. Expert Systems with Applications, 22(3), 213–224.
Mendel, J. M. (2001). Uncertain rule-based fuzzy logic systems: Introduction and new directions. Prentice Hall.
Nonaka, I., & Toyama, R. (2003). The knowledge-creating theory revisited: Knowledge creation as a synthesizing process. Knowledge Management Research & Practice, 1(1), 2–10. DOI: https://doi.org/10.1057/palgrave.kmrp.8500001
O’Donovan, B., & Roode, D. (2002). A critical review of knowledge management: A semiotic perspective. South African Computer Journal, 28(1), 74–81.
Palacios‐Marqués, D., Gil‐Peñalosa, C., & Garrigós‐Simón, F. J. (2016). Fostering knowledge sharing through people involvement. International Journal of Manpower, 37(6), 975–994.
Rahman, H., & Ramos, I. (2013). Challenges in adopting knowledge management systems: An exploratory study of Malaysian organizations. International Journal of Information Systems and Project Management, 1(2), 5–21.
Singh, M. D., & Kant, R. (2008). Knowledge management barriers: An interpretive structural modeling approach. International Journal of Management Science and Engineering Management, 3(2), 141–150. DOI: https://doi.org/10.1080/17509653.2008.10671042
Turban, E., Aronson, J. E., & Liang, T. P. (2007). Decision support systems and intelligent systems (7th ed.). Pearson Education.
Dudnyk, O., & Sokolovska, Z. (2021). Application of fuzzy expert systems in IT project management. In Project Management – New Trends and Applications (pp. ...)..
This study shows how fuzzy expert systems help IT companies manage uncertain business processes, enhancing decision-making and financial results.
Kimseng, T., Javed, A., Jeenanunta, C., & Kohda, Y. (2020). Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms. Journal of Open Innovation: Technology, Market, and Complexity, 6(2), 38.
Lv, Z., & Shen, H. (2021). Artificial intelligence with fuzzy logic system for learning management evaluation in higher educational systems. Journal of Intelligent & Fuzzy Systems, (2), 3501–3511.
Alavi, M., & Leidner, D. E. (2001). Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, 25(1), 107–136. DOI: https://doi.org/10.2307/3250961
Bose, R. (2004). Knowledge management metrics. Industrial Management & Data Systems, 104(6), 457–468. DOI: https://doi.org/10.1108/02635570410543771
Choy, K. L., Lee, W. B., & Lo, V. (2002). An intelligent supplier management tool using case-based reasoning techniques. Expert Systems with Applications, 22(3), 213–224. DOI: https://doi.org/10.1016/S0957-4174(01)00055-0
Dudnyk, O., & Sokolovska, Z. (2021). Application of fuzzy expert systems in IT project management. In Project Management – New Trends and Applications.
Kimseng, T., Javed, A., Jeenanunta, C., & Kohda, Y. (2020). Applications of fuzzy logic to reconfigure human resource management practices for promoting product innovation in formal and non-formal R&D firms. Journal of Open Innovation: Technology, Market, and Complexity, 6(2), 38. DOI: https://doi.org/10.3390/joitmc6020038
Lv, Z., & Shen, H. (2021). Artificial intelligence with fuzzy logic system for learning management evaluation in higher educational systems. Journal of Intelligent & Fuzzy Systems, (2), 3501–3511. DOI: https://doi.org/10.3233/JIFS-189387
Sahibzada, U. F., Latif, K. F., Xu, Y., & Khalid, R. (2020). Catalyzing knowledge management processes towards knowledge worker satisfaction: Fuzzy-set qualitative comparative analysis. Journal of Knowledge Management, 24(10), 2373–2400. DOI: https://doi.org/10.1108/JKM-02-2020-0093
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Swapnil Porwal, Dr. Imad Ansari
This work is licensed under a Creative Commons Attribution 4.0 International License.
With the licence CC-BY, authors retain the copyright, allowing anyone to download, reuse, re-print, modify, distribute, and/or copy their contribution. The work must be properly attributed to its author.
It is not necessary to ask for further permission from the author or journal board.
This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.
