Abstract
Performance evaluation is a comprehensive process for comparing activities compared with predetermined organizational criteria. Based on the results of performance evaluation, organizations can embark on purposeful actions to improve their situation. Obviously, the success of organizations and the economic development of the country depend on the performance of human resources (HR). This paper proposes a novel hybrid evaluation framework for analyzing the performance of public sector organizations. The suggested setting allows for performance evaluation based on a comprehensive approach involving expert knowledge. For this purpose, the research integrates the Balanced Scorecard (BSC) approach and fuzzy multi-criteria decision-making (MCDM) methods. Initially, the employees’ performance factors (criteria) are identified from the literature based on the BSC dimensions. Then, the most relevant of them are finalized through the fuzzy Delphi method (FDM) questionnaires and experts’ opinions. In the second stage, the weights of criteria are determined by adopting the fuzzy best-worst method (FBWM). Moreover, two fuzzy MCDM techniques, namely VIKOR and Grey Relational Analysis (GRA), are used to examine the performance of the eight important public sector organizations of Iran. Finally, a Monte Carlo simulation-based (MCSB) approach and a scenario-based (SCB) approach are applied to compare the effectiveness of fuzzy VIKOR and fuzzy GRA. The results suggest that the critical employees’ performance factors include sharing knowledge with colleagues (0.136), optimal use of facilities (0.123) and participation in solving organizational issues (0.118). Additionally, based on the implemented sensitivity analysis approaches, fuzzy VIKOR generates more reliable results and also has higher robustness than fuzzy GRA.
Afrasiabi, A.; Chalmardi, M. K.; Baležentis, T. 2022. A novel hybrid evaluation framework for public organizations based on employees’ performance factors. Evaluation and program planning: Elsevier B.V. ISSN 0149-7189. 91, April, 102020, p. 1–18; DOI:10.1016/j.evalprogplan.2021.102020;[Social Sciences Citation Index (Web of Science); Scopus; GEOBASE].