Viable industrial supplier performance evaluation using fuzzy inference system: a case of the automotive industry

Purpose As the global focus on supply chain management has shifted toward the importance of digitalization, resilience and sustainability to ensure viability, this paradigm merits special consideration in the industrial supplier selection process in a VUCA (Volatile, Uncertain, Complex and Ambiguous) world. Additionally, the increasing geopolitical challenges further complicate the industrial supplier selection process, necessitating robust decision-making frameworks. Thus, this paper aims to present a decision-making system using a fuzzy inference system (FIS) for industrial supplier evaluation and selection, considering a new criterion: viability. Design/methodology/approach Fuzzy set theory, particularly a FIS, is used to address the subjectivity of decision-makers’ preferences. The suggested method’s validity is evaluated using a real automotive case study for industrial supplier selection situations. Findings Seventeen key criteria for viable industrial supplier selection were identified and used to evaluate and select the case study firm’s industrial supplier. The chosen supplier (B) demonstrated superior resilience, sustainability and digitalization capabilities, making it preferable to others. Specifically, supplier (B) exhibited exceptional adaptability to disruptions, a strong commitment to sustainable practices and advanced digital integration that enhances operational efficiency. Practical implications This study provides valuable insights for researchers and professionals by proposing a comprehensive industrial supplier selection system. Integrating diverse criteria is essential for viable performance in supply chains that enhances robustness and adaptability, supporting more strategic decision-making in supplier evaluation amid global and network-related challenges. Originality/value This novel paper introduces a new criterion, i.e. viability, in the industrial supplier selection process in the VUCA environment. In addition, it proposes a decision-making system for viable supplier performance evaluation. Furthermore, it validates the proposed FIS in an automotive case study.

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Publication Details

Journal
Journal of Business and Industrial Marketing
Published
2025-01-23
DOI
https://doi.org/10.1108/jbim-12-2022-0555
Citations
5
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
11.13
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article

Viable industrial supplier performance evaluation using fuzzy inference system: a case of the automotive industry

Abla Chaouni Benabdellah, Anass Cherrafi, Kamar Zekhnini, Surajit Bag et al.
5 citations
Journal of Business and Industrial Marketing
Supply Chain Resilience and Risk Management
11.13
article

Viable industrial supplier performance evaluation using fuzzy inference system: a case of the automotive industry

Abla Chaouni Benabdellah, Anass Cherrafi, Kamar Zekhnini, Surajit Bag, Imane Bouhaddou
article en
5 citations

Abstract

Purpose As the global focus on supply chain management has shifted toward the importance of digitalization, resilience and sustainability to ensure viability, this paradigm merits special consideration in the industrial supplier selection process in a VUCA (Volatile, Uncertain, Complex and Ambiguous) world. Additionally, the increasing geopolitical challenges further complicate the industrial supplier selection process, necessitating robust decision-making frameworks. Thus, this paper aims to present a decision-making system using a fuzzy inference system (FIS) for industrial supplier evaluation and selection, considering a new criterion: viability. Design/methodology/approach Fuzzy set theory, particularly a FIS, is used to address the subjectivity of decision-makers’ preferences. The suggested method’s validity is evaluated using a real automotive case study for industrial supplier selection situations. Findings Seventeen key criteria for viable industrial supplier selection were identified and used to evaluate and select the case study firm’s industrial supplier. The chosen supplier (B) demonstrated superior resilience, sustainability and digitalization capabilities, making it preferable to others. Specifically, supplier (B) exhibited exceptional adaptability to disruptions, a strong commitment to sustainable practices and advanced digital integration that enhances operational efficiency. Practical implications This study provides valuable insights for researchers and professionals by proposing a comprehensive industrial supplier selection system. Integrating diverse criteria is essential for viable performance in supply chains that enhances robustness and adaptability, supporting more strategic decision-making in supplier evaluation amid global and network-related challenges. Originality/value This novel paper introduces a new criterion, i.e. viability, in the industrial supplier selection process in the VUCA environment. In addition, it proposes a decision-making system for viable supplier performance evaluation. Furthermore, it validates the proposed FIS in an automotive case study.

Journal of Business and Industrial MarketingVol. 40(4)
Cadi Ayyad University (MA), International University of Rabat (MA), Excelia Business School (FR), Université Moulay Ismail de Meknes (MA), Laboratoire des technologies innovantes (FR), Université de Picardie Jules Verne (FR)
Industry, innovation and infrastructure
Openalex Percentile: Top 3%
Supply Chain Resilience and Risk Management
11.13
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