A Fuzzy Multi-Criteria Decision Making Methodology for Job Evaluation

Abstract

In this study, the integrated methods Hesitant Fuzzy Analytic Hierarchy Process (HF-AHP), Fuzzy COmplex Proportional Assessment (F-COPRAS), and Fuzzy Technique for Order Performance to Ideal Solution (F-TOPSIS) were used for job evaluation studies in a food company. There has been a decline in employee performance in the company. Unfair wages and unequal workload were identified as the reasons for the failure. Therefore, it has been observed that the staff turnover rate in the company is quite high. The objective is to determine a fair wage policy that will increase employee satisfaction by stratifying with job evaluation analysis between positions. The experts of Human Resources Department determined eight competency evaluation criteria for job evaluation studies in the proposed approach. Based on their judgments on these criteria, the competencies were rated using a linguistic scale and the weighting values were calculated using the HF-AHP method. These values are inputs for the next stage. Employees were ranked using F-COPRAS and F-TOPSIS methods. This study showed that the integrated method can be an effective alternative solution approach for calculating the weighting values and ranking of competencies in job evaluation studies. It has been shown that the use of the strata created as a result of this study is a great facilitator in determining employee pay policies.