Designing and Implementing Fuzzy Expert Systems to Suggest Knowledge Management Technology Compatible with the Strategy Type

Document Type : Original Research Paper

Authors

1 Associate Professor, IT Management, Faculty of Social science and Economics, University of Alzahra, Tehran, Iran.

2 Assistant Professor, Management, Industrial Engineering and Management Faculty, Ghiaseddin Jamshid Kashani University, Ghazvin, Iran.

10.47176/smok.2018.1129

Abstract

As the time and space for accessing the experts are limited, expert systems are created for making the skills of experts available for solving these constraints. Aimed at improving and promoting organizational performance, knowledge management is now regarded as a quite essential practice. Given this, the present study is aimed at introducing the fuzzy expert system to suggest the most proper instruments for knowledge management. To acquire the relevant knowledge, ten top experts in the field of knowledge management were consulted. The proposed system contains a knowledge basis for Fuzzy rules, inference engine based on Fuzzy logic, field interference, and graphical user inference designed in MATLAB software. The inputs of the system include organizational structure, organization strategy, human resource management strategy, the level of IT maturity, organization size and environmental uncertainty. The outputs contain knowledge management tools, which are recommended for users on the basis of the selection process type. Arash Holding Company containing 500 employees was analyzed for testing the performance of designed expert system. The results were presented separately according to the knowledge management processes. The users of the designed system may cover university students, organizations, researchers willing to develop such systems, or individuals who intend to use the available knowledge in the system.

Keywords

References

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Strategic Management of Organizational Knowledge
Volume 1, Issue 2 - Serial Number 2
September 2018
Pages 11-29

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History

  • Receive Date: 03 November 2018
  • Revise Date: 22 January 2019
  • Accept Date: 16 December 2018

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