An Integrated MCDM Approach for Establishing Suppliers' Capability Differences and Selection Based on Sustainable Industry 4.0 Initiatives

ABSTRACT The growing emphasis on sustainability, driven by increased customer awareness and shifting consumer needs, has fundamentally impacted corporate buying methods. Concurrently, the rapid expansion of Industry 4.0 technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) altered production systems by increasing their cognitive ability and adaptability, influencing production operations and strategic supplier selection decisions. Motivated by these imperatives, the current study proposes a comprehensive hybrid framework for evaluating supplier performance and developing supplier skills within an integrated sustainability and Industry 4.0 environment. The proposed framework is made up of four sequential methodological steps. The fuzzy Delphi method (FDM) first identifies and validates critical supplier assessment criteria through structured expert elicitation. Second, a hybrid fuzzy analytic hierarchy process and fuzzy technique for order of preference by similarity to ideal solution (FAHP‐FTOPSIS) framework computes criteria significance weights, with quality, price and delivery performance receiving the most weight; subsequently, it assesses and prioritises supplier performance. Third, multivariate analysis of variance (MANOVA) categorises suppliers into high‐ and low‐performing groups, with employee welfare, price, R&D, agility, delivery performance, green and smart technology and social responsibility being the most significant inter‐group performance distinguishers. Fourth, a sensitivity study with nine weight perturbation scenarios shows strong ranking stability (Spearman's ρ = 0.9273–0.9758; mean ρ = 0.9502), highlighting the framework's robustness and data‐driven nature. The findings establish an empirical foundation for targeted supplier development programs and benchmarking approaches. The framework is empirically validated through a real‐world case study within an Indian electronic retail supply chain.

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Publication Details

Journal
Sustainable Development
Published
2026-09-16
DOI
https://doi.org/10.1002/sd.71694
Primary Topic
Multi-Criteria Decision Making
Type
article
Field-Weighted Citation Impact
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article

An Integrated MCDM Approach for Establishing Suppliers' Capability Differences and Selection Based on Sustainable Industry 4.0 Initiatives

Nidhi Ahuja, Anshu Gupta, P. C. Jha
Sustainable Development
Multi-Criteria Decision Making
article

An Integrated MCDM Approach for Establishing Suppliers' Capability Differences and Selection Based on Sustainable Industry 4.0 Initiatives

Nidhi Ahuja, Anshu Gupta, P. C. Jha
article en

Abstract

ABSTRACT The growing emphasis on sustainability, driven by increased customer awareness and shifting consumer needs, has fundamentally impacted corporate buying methods. Concurrently, the rapid expansion of Industry 4.0 technologies such as the Internet of Things (IoT), blockchain, and artificial intelligence (AI) altered production systems by increasing their cognitive ability and adaptability, influencing production operations and strategic supplier selection decisions. Motivated by these imperatives, the current study proposes a comprehensive hybrid framework for evaluating supplier performance and developing supplier skills within an integrated sustainability and Industry 4.0 environment. The proposed framework is made up of four sequential methodological steps. The fuzzy Delphi method (FDM) first identifies and validates critical supplier assessment criteria through structured expert elicitation. Second, a hybrid fuzzy analytic hierarchy process and fuzzy technique for order of preference by similarity to ideal solution (FAHP‐FTOPSIS) framework computes criteria significance weights, with quality, price and delivery performance receiving the most weight; subsequently, it assesses and prioritises supplier performance. Third, multivariate analysis of variance (MANOVA) categorises suppliers into high‐ and low‐performing groups, with employee welfare, price, R&D, agility, delivery performance, green and smart technology and social responsibility being the most significant inter‐group performance distinguishers. Fourth, a sensitivity study with nine weight perturbation scenarios shows strong ranking stability (Spearman's ρ = 0.9273–0.9758; mean ρ = 0.9502), highlighting the framework's robustness and data‐driven nature. The findings establish an empirical foundation for targeted supplier development programs and benchmarking approaches. The framework is empirically validated through a real‐world case study within an Indian electronic retail supply chain.

Sustainable Development
University of Delhi (IN), Ambedkar University Delhi (IN), IILM Institute for Higher Education (IN)
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Multi-Criteria Decision Making
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