Integrated decision support model for performance evaluation of public staff: using AHP and fuzzy TOPSIS

Abstract

Purpose: This study introduces an integrated model for personnel performance evaluation and examines the potential value of Multi-Criteria Decision-Making (MCDM) methods in supporting personnel performance evaluation. Theory and Methods: This study MCDM methods to evaluate personnel performance. The study was carried out in an institution within the public sector, and the performance of a hundred personnel was evaluated under four main criteria and twenty sub-criteria. The study used an integrated decision-making model using Analytical Hierarchy Process (AHP) and fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In the model, AHP was used to calculate criteria weights. Fuzzy TOPSIS was used to rank personnel's performance based on given criteria. In addition, this study conducted a linear regression analysis to compare the findings between the current results and the results obtained from the proposed model. Results: The findings from AHP showed that 'Business Knowledge' is the most critical criterion with a weight of 0.151, whereas 'Keeping the Desk and Space Clean and Tidy' is the least important criterion with an importance weight of 0.006. As a result of the calculations made with fuzzy TOPSIS, the A60 coded personnel had the best performance score with the value of 0.8594 proximity coefficient. The top ten performances were achieved by personnel A60>A43>A96>A50>A57>A3>A95>A70>A91>A35. This study revealed that the findings from the model used, and existing performance measurement had differences. Conclusion: The model used yielded more objective and reliable results than the performance evaluation method applied in the municipality.