Evaluation of Barriers to Knowledge Sharing Affecting Employees’ Innovative Behavior with an Emphasis on Ethics and Social Responsibility Using a Group Best–Worst Method (BWM)

Abstract

Organizations need creative and innovative employees to improve performance and achieve sustainable competitive advantage. One of the key factors in shaping innovative behavior is knowledge sharing among employees. In this regard, work ethics and social responsibility are two factors that can positively influence the knowledge-sharing process. However, there are various barriers in the path of knowledge sharing, the intensity and nature of which differ across organizations depending on their cultural and structural characteristics. Therefore, identifying and evaluating these barriers is essential for every organization. In this study, in order to identify and prioritize the barriers to knowledge sharing affecting employees’ innovative behavior with an emphasis on ethics and social responsibility, the Best–Worst Method (BWM) was employed as one of the modern and powerful multi-attribute decision-making (MADM) techniques. To this end, by reviewing the related literature and holding expert panel sessions, 24 barriers to knowledge sharing were identified in a thermal power plant, considering the two mentioned factors. Then, using the proposed group BWM algorithm, the identified barriers were evaluated, weighted, and prioritized.The results indicated that strategic, technological, individual, and cultural barriers, respectively, were the most significant obstacles to knowledge sharing in the studied power plant. Moreover 22.93% and 33.68% of the total weight of the identified barriers were related to ethics and social responsibility factors, respectively. The findings highlight the prominent role of these two factors in improving organizational knowledge sharing. Accordingly, organizations seeking business success should focus on ethics and social responsibility to identify, assess, and eliminate the main barriers to knowledge sharing. Furthermore, the proposed algorithm can serve as a reliable, efficient, and valid method for solving MADM problems.