Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework
The purpose of this study is to evaluate Exogenous Risk Factors (ERFs) affecting Key Performance Indicators (KPIs) in automotive supply chains, aiming to enhance resilience against global disruptions. The primary research question focuses on identifying and prioritizing ERFs that pose the greatest t...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-03-01
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| Series: | Journal of Open Innovation: Technology, Market and Complexity |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2199853125000241 |
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| author | Ishansh Gupta Seyed Taha Raeisi Sergio Correa Hendro Wicaksono |
| author_facet | Ishansh Gupta Seyed Taha Raeisi Sergio Correa Hendro Wicaksono |
| author_sort | Ishansh Gupta |
| collection | DOAJ |
| description | The purpose of this study is to evaluate Exogenous Risk Factors (ERFs) affecting Key Performance Indicators (KPIs) in automotive supply chains, aiming to enhance resilience against global disruptions. The primary research question focuses on identifying and prioritizing ERFs that pose the greatest threat to operational performance. A hybrid decision-making framework integrating Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is employed. Validation is ensured through insights from 18 supply chain professionals with diverse roles and a combined 318 years of experience. The study identifies 34 ERFs, including semiconductor shortages, pandemics, and information infrastructure disruptions, and evaluates their impact on KPIs such as missing parts, backlogs, special transports, and wrong deliveries. By extending the traditional PESTLE framework with Transportation and Material dimensions, this study provides actionable strategies to mitigate risks and strengthen supply chain resilience in volatile environments. |
| format | Article |
| id | doaj-art-632423582b724c3cad4591529d9edeb1 |
| institution | Kabale University |
| issn | 2199-8531 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Open Innovation: Technology, Market and Complexity |
| spelling | doaj-art-632423582b724c3cad4591529d9edeb12025-02-11T04:34:45ZengElsevierJournal of Open Innovation: Technology, Market and Complexity2199-85312025-03-01111100489Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE frameworkIshansh Gupta0Seyed Taha Raeisi1Sergio Correa2Hendro Wicaksono3School of Business, Social & Decision Sciences, Constructor University, Campus Ring 1, Bremen 28759, GermanySchool of Business, Social & Decision Sciences, Constructor University, Campus Ring 1, Bremen 28759, GermanyBMW Group, Munich, GermanySchool of Business, Social & Decision Sciences, Constructor University, Campus Ring 1, Bremen 28759, Germany; Corresponding author.The purpose of this study is to evaluate Exogenous Risk Factors (ERFs) affecting Key Performance Indicators (KPIs) in automotive supply chains, aiming to enhance resilience against global disruptions. The primary research question focuses on identifying and prioritizing ERFs that pose the greatest threat to operational performance. A hybrid decision-making framework integrating Fuzzy Analytical Hierarchy Process (FAHP) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) is employed. Validation is ensured through insights from 18 supply chain professionals with diverse roles and a combined 318 years of experience. The study identifies 34 ERFs, including semiconductor shortages, pandemics, and information infrastructure disruptions, and evaluates their impact on KPIs such as missing parts, backlogs, special transports, and wrong deliveries. By extending the traditional PESTLE framework with Transportation and Material dimensions, this study provides actionable strategies to mitigate risks and strengthen supply chain resilience in volatile environments.http://www.sciencedirect.com/science/article/pii/S2199853125000241Supply chain riskFuzzy Analytic Hierarchy Process (FAHP)Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS)Hybrid methodPolitical, Economic, Social, Technological, Environmental, and Legal (PESTLE) |
| spellingShingle | Ishansh Gupta Seyed Taha Raeisi Sergio Correa Hendro Wicaksono Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework Journal of Open Innovation: Technology, Market and Complexity Supply chain risk Fuzzy Analytic Hierarchy Process (FAHP) Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) Hybrid method Political, Economic, Social, Technological, Environmental, and Legal (PESTLE) |
| title | Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework |
| title_full | Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework |
| title_fullStr | Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework |
| title_full_unstemmed | Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework |
| title_short | Evaluating risk factors in automotive supply chains: A hybrid fuzzy AHP-TOPSIS approach with extended PESTLE framework |
| title_sort | evaluating risk factors in automotive supply chains a hybrid fuzzy ahp topsis approach with extended pestle framework |
| topic | Supply chain risk Fuzzy Analytic Hierarchy Process (FAHP) Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) Hybrid method Political, Economic, Social, Technological, Environmental, and Legal (PESTLE) |
| url | http://www.sciencedirect.com/science/article/pii/S2199853125000241 |
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