Validation of Green Supplier Ranking Results Using a Model Comparison and Scenario Analysis Approach (MCDM) Based on Rough Sets

Hossein  Poursmaeil; Majid Bagherzadeh Khajeh; Kamaleddin  Rahmani; Alireza  Bafandeh Zendeh; Mohammad  Pasban

Authors

Hossein Poursmaeil Department of Management, Ta.C., Islamic Azad University, Tabriz, Iran Author https://orcid.org/0009-0003-8784-8599
Majid Bagherzadeh Khajeh Department of Management, Ta.C., Islamic Azad University, Tabriz, Iran https://orcid.org/0000-0001-5788-7085
Kamaleddin Rahmani Department of Management, Ta.C., Islamic Azad University, Tabriz, Iran Author https://orcid.org/0009-0002-0749-9206
Alireza Bafandeh Zendeh Department of Management, Ta.C., Islamic Azad University, Tabriz, Iran Author https://orcid.org/0000-0002-7687-6055
Mohammad Pasban Department of Management, Ta.C., Islamic Azad University, Tabriz, Iran Author https://orcid.org/0000-0001-5283-8508

Keywords:

Supplier selection, multi-objective programming, rough sets, confirmatory factor analysis, Iran Khodro

Abstract

Environmental protection and sustainable development, as strategic imperatives, have made green supplier selection a key issue in manufacturing supply chains. Accordingly, the aim of this study was to validate a green supplier selection model based on a multi-objective programming approach and rough sets within the context of the automotive industry (Iran Khodro Company). In terms of purpose, this research was applied-developmental, and in terms of methodology, it was descriptive. The statistical population consisted of Iran Khodro Company and all of its affiliated parts suppliers. Data were collected using a researcher-developed questionnaire as well as documents and records obtained from the company and its suppliers. Based on the Morgan table for sample size determination, 66 respondents were selected to complete the questionnaire, while at the decision-making stage, 18 qualified suppliers were examined. The validity of the measurement instrument was assessed using content validity (through the relevant index/coefficient), and its reliability was evaluated using Cronbach’s alpha. In the validation phase, the quality of the measurement model was first assessed through confirmatory factor analysis. The results indicated that the model fit indices were within acceptable ranges, with the values of CMIN/χ², RMSEA, and RMR being reported. In addition, the factor loadings of all items associated with the extracted components—including information exchange, types of environmental certifications, recycling, sustainable design, and procurement of environmentally friendly raw materials—were greater than 0.5, and the t-statistics for all measurement paths exceeded 1.96 at the 95% confidence level. Therefore, the construct validity of the model was confirmed. Finally, using the integrated multi-objective programming and rough set model, the selected suppliers were ranked and selected in terms of price, quality, service level, and environmental components, and practical recommendations were proposed to facilitate more effective implementation of the model.

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