Determination and ranking of organizational adherence factors in knowledge-based organizations using the Multi-Objective gray wolf algorithm

Document Type : Research Paper

Authors

1 Department of Public Administration, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran

2 Department of Management, Semnan Branch, Islamic Azad University, Semnan, Iran

3 Department of Management, Kazerun Branch, Islamic Azad University, Kazerun, Iran

10.22075/ijnaa.2023.31135.4571

Abstract

Some of the important and effective issues of HRM and senior managers of knowledge-based organizations are maintaining and improving the commitment level of employees who are the most valuable resources of these organizations. So, this study was conducted to determine and rank organizational commitment factors in knowledge-based organizations using the multi-objective gray wolf optimizer (MOGWO). The study was conducted using a mixed method (qualitative and quantitative) and is applied in terms of objectives and descriptive. The statistical population was selected using exploratory factor analysis (EFA) and included 200 senior managers of knowledge-based companies in Tehran and Alborz provinces, and the sample size was calculated as 132 using Cochran's formula. The best employee commitment (optimal) factors, which were 42 factors, were determined using the MOGWO. Finally, the SWARA method was used to weigh and rank the principal and sub-components from the opinions of 16 experts who were selected by purposive sampling, and it was found that corporate culture is the most important aspect of optimizing employee commitment in knowledge-based organizations. In today's changing and highly competitive environment, organizations must focus more on employee commitment to survive. Besides, knowledge-based organizations should use process re-engineering in human resource processes and working conditions to improve employee commitment levels.

Keywords

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Articles in Press, Corrected Proof
Available Online from 29 December 2023
  • Receive Date: 03 May 2023
  • Revise Date: 01 August 2023
  • Accept Date: 03 August 2023