{"title":"Evaluation and Ranking of Iran’s Provinces in Terms of Mining Development Using Multicriteria Decision-Making (MCDM) Techniques","authors":"Hossein Komasi, Amir Karbassi Yazdi, Gizem Ozaydin, Gonzalo Valdés González, Davood Jamini","doi":"10.1155/cplx/4594108","DOIUrl":null,"url":null,"abstract":"<p>Mining development is of prime importance for economic growth, industrialization, and resilience, particularly for countries rich in minerals, such as Iran. Using an excellent multicriteria decision-making (MCDM) method, this study attempted to determine provinces with respect to mining development by assessing other regions or provinces by placing them according to each other and similar indicators of development for each region of Iran through ranking them. The national statistical data identified 15 quantitative indicators with regard to employment, mineral production, infrastructure, and environmental safety. The CRITIC method was used to ensure that the criterion weights were objectively established, and the ranking effect of two leading MCDM techniques, TOPSIS and WASPAS, was computed. Sensitivity tests were used to investigate stability of findings under different weighting and model conditions. These regional discrepancies also showed statistically significant differences with provinces (i.e., Kerman, Yazd, and Razavi Khorasan) having the greatest level of correlation with the combined mineral resources, infrastructure, and institutional support. Provinces such as Ilam, Gilan, and Ardabil were losing ground due to inadequate investment, infrastructure, and skilled manpower. In addition, the consistency in rankings using different approaches contributes to the confidence in the proposed model. Moreover, this research facilitates a better perspective and a more comprehensive representation to reach the development of the mining sector in Iran as well as a more evidence-based overall framework for regional development planning (or sustainable management) and future production management.</p>","PeriodicalId":50653,"journal":{"name":"Complexity","volume":"2026 1","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1155/cplx/4594108","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Complexity","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1155/cplx/4594108","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Mining development is of prime importance for economic growth, industrialization, and resilience, particularly for countries rich in minerals, such as Iran. Using an excellent multicriteria decision-making (MCDM) method, this study attempted to determine provinces with respect to mining development by assessing other regions or provinces by placing them according to each other and similar indicators of development for each region of Iran through ranking them. The national statistical data identified 15 quantitative indicators with regard to employment, mineral production, infrastructure, and environmental safety. The CRITIC method was used to ensure that the criterion weights were objectively established, and the ranking effect of two leading MCDM techniques, TOPSIS and WASPAS, was computed. Sensitivity tests were used to investigate stability of findings under different weighting and model conditions. These regional discrepancies also showed statistically significant differences with provinces (i.e., Kerman, Yazd, and Razavi Khorasan) having the greatest level of correlation with the combined mineral resources, infrastructure, and institutional support. Provinces such as Ilam, Gilan, and Ardabil were losing ground due to inadequate investment, infrastructure, and skilled manpower. In addition, the consistency in rankings using different approaches contributes to the confidence in the proposed model. Moreover, this research facilitates a better perspective and a more comprehensive representation to reach the development of the mining sector in Iran as well as a more evidence-based overall framework for regional development planning (or sustainable management) and future production management.
期刊介绍:
Complexity is a cross-disciplinary journal focusing on the rapidly expanding science of complex adaptive systems. The purpose of the journal is to advance the science of complexity. Articles may deal with such methodological themes as chaos, genetic algorithms, cellular automata, neural networks, and evolutionary game theory. Papers treating applications in any area of natural science or human endeavor are welcome, and especially encouraged are papers integrating conceptual themes and applications that cross traditional disciplinary boundaries. Complexity is not meant to serve as a forum for speculation and vague analogies between words like “chaos,” “self-organization,” and “emergence” that are often used in completely different ways in science and in daily life.