Design of a Fuzzy Expert System for Organizational Performance and Innovation Evaluation Based on the Role of Knowledge Management and Intellectual Capital

Abstract

Objective: This study aimed to evaluate organizational performance and innovation based on the role of knowledge management and intellectual capital.

Methodology: This study was conducted using a qualitative approach (interviews with experts). Through expert interviews and grounded theory, research criteria including causal conditions, intervening factors, strategies, and outcomes were derived. The criteria and sub-criteria were then ranked using the fuzzy Analytical Hierarchy Process (AHP) method. Causal factors and strategies were used as inputs to the model, while outcomes were treated as output variables. The expert system in this study had two inputs and one output. For the input sub-criteria, rules were defined based on expert opinions, and fuzzy inference was performed. The outputs of the expert system were the sub-criteria of the outcomes, which included five variables, and the fuzzy section utilized MATLAB software.

Findings: Among the identified factors, causal factors were found to be more important than contextual and intervening factors. Within the causal factors, social factors were of greater significance. In the strategies category, human resources were identified as the most important, and ultimately, organizational outcomes were considered the most significant results.

Conclusion: Overall, it can be stated that evaluating organizational performance and innovation based on the role of knowledge management and intellectual capital is of great importance. The utilization of a fuzzy expert system approach in this context can significantly assist managers and decision-makers in assessing organizational performance and innovation.