Introduction
The present study aims to identify, formulation and develop, weigh, and prioritize the most crucial macro-level performance evaluation indicators for inspecting industrial, mining, and trade organizations in Iran. This will be achieved through a combination of fuzzy multi-criteria decision-making models and the bootstrap statistical method. Furthermore, the study seeks to assess the effectiveness of the research findings by ranking the organizations based on their annual inspection performance and obtaining validation from experts in the Ministry of Industry, Mining, and Trade. Therefore, the objectives and research questions of this study are as follows: To identify and develop the most significant macro-level performance evaluation indicators for inspecting industrial, mining, and trade organizations, employing a fuzzy approach. To rank Iranian industrial, mining, and trade organizations based on the inspection performance of provinces during the first six months of 2022. To evaluate the effectiveness of selected indicators in the ranking process, utilizing an expert-oriented approach.
Research Questions are: What are the primary macro-level inspection indicators that determine the evaluation of performance for industrial, mining, and trade organizations in Iran? How is the performance of industrial, mining, and trade organizations ranked based on the selected macro-level inspection indicators? In what manner do the experts from the Ministry of Industry, Mining, and Trade perceive the effectiveness of the obtained results?)
 Methodology
Considering the nature of the research topic, it is an applied and developmental study, and the research method is a mixed research approach (qualitative-quantitative). To achieve the research objectives, a library research method and purposive sampling based on an expert-oriented approach were utilized, through conducting group brainstorming sessions. Initial indicators were identified and formulated. Then, the most important indicators were extracted using the bootstrap statistical method. The statistical population of this research consisted of 32 provinces, including key stakeholders in the field of supervision and inspection, such as deputy supervisors, heads of inspection departments, and those involved in combating smuggling. The estimated number of individuals in this population was close to 100, and interviews were conducted with 56 participants. To evaluate and rank the performance of inspection, all 32 organizations in the industry, mining, and trade sector in Iran were considered.
Results and Discussion
The results of library research and group sessions with experts led to the identification of 19 initial indicators, which were further consolidated into 8 statistical indicators using the bootstrap method. In order to weight the 8 research indicators, the weight adjustment equation in the entropy method was used, and the topsis method was employed for ranking the provinces. Based on the research results, the eight indicators are the ratio of economic units to existing inspectors, the percentage of inspections of major economic units, the average number of inspected units, the average number of identified non-compliant units by each inspection team, the percentage of identified non-compliant units, the share of each non-compliant unit's violation, the percentage of detected violations excluding the violation of not including the price, and the percentage of major cases out of the total cases. These eight indicators are the most important factors in evaluating the performance of provincial inspections under uncertain conditions. The provinces of Khuzestan, Hormozgan, Kohgiluyeh and Boyer-Ahmad, Hamadan, and Lorestan were ranked first to fifth respectively based on the performance of provincial inspections during the first six months of 2022. Finally, the effectiveness of the indicators and the combined method used for ranking the provinces were tested and verified by experts.
Conclusion
The present study aimed to explore the key performance evaluation indicators of inspection organizations in the industrial, mining, and trade sectors under conditions of uncertainty, using an expert-driven approach and a combination of fuzzy multi-criteria decision-making models. To achieve this, the most important macro-level performance evaluation indicators of inspection organizations in the industrial, mining, and trade sectors were initially identified based on the fuzzy approach from the perspective of experts in the Ministry of Industry, Mining, and Trade. Then, using the selected indicators and a combined approach of entropy and fuzzy TOPSIS, the performance of inspection organizations in the country during the first six months of 2022 was evaluated and ranked. The results of the ranking and the effectiveness of the indicators were measured and confirmed by the experts. Based on the research findings, eight indicators were extracted as the most important macro-level indicators of inspection. The provinces of Khuzestan, Hormozgan, Kohgiluyeh and Boyer-Ahmad, Hamadan, and Lorestan were introduced as the top five provinces in terms of performance. Furthermore, considering the experts' validation results regarding the indicators and the ranking results of the provinces with the selected indicators, the superiority of fuzzy multi-criteria decision-making methods over classical scientific methods in determining and prioritizing factors under conditions of uncertainty was emphasized. Since no independent research has been conducted on evaluating the performance of inspection organizations in the industrial, mining, and trade sectors so far, the statistical indicators of this study will serve as a basis for developing indicators in future research. It is also recommended to utilize fuzzy approaches, especially fuzzy multi-criteria decision-making methods, for statistical analysis, prioritization, and weighting of factors alongside classical scientific methods, as most social and management research is conducted under conditions of uncertainty. This suggestion should be seriously considered by university professors and researchers. In this regard, the role of research institutes and research centers in the country is prominent.