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Measuring supply chain resilience along the automotive value chain — A comparative research on literature and industry

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  • Raaymann, Sophia
  • Spinler, Stefan

Abstract

About three years after the start of the COVID-19 pandemic disrupting global supply chains, companies increasingly focus on creating supply chains that are resilient to the next disruption. While researchers have developed multiple frameworks and quantitative models for assessing risk in supply chains, the question of how to measure supply chain resilience (SCR) with key performance indicators (KPIs) remains unanswered. This research provides answers on how to measure SCR in the automotive industry. Researchers investigated literature’s perspective through text mining on 195 published papers on SCR and compared that to the industry’s perspective. The Analytical Hierarchy Process is applied to text mining results to find the most suitable combination of KPIs. For the industry data, a conjoint method analyzed via an ordinal regression is applied in interviews. The research reveals that the most important KPIs, according to literature, are lead time variation, OTIF (On time in full), and volume flexibility of suppliers. At the same time, the industry also assigns the greatest contribution to OTIF and volume flexibility, and to the stock level of high-risk parts. This study also investigates the different priorities of OEMs, Tier 1 and Tier 2 suppliers when measuring SCR. Perspectives on how to measure resilience vary within the industry as well as between industry and academia. This research reveals the need for a greater exchange between industry and academia as well as a more structural discussion of resilience KPIs and their application within the industry.

Suggested Citation

  • Raaymann, Sophia & Spinler, Stefan, 2024. "Measuring supply chain resilience along the automotive value chain — A comparative research on literature and industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 192(C).
    • Handle: RePEc:eee:transe:v:192:y:2024:i:c:s1366554524003831
    DOI: 10.1016/j.tre.2024.103792
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    1. Sandy Q. Qu & John Dumay, 2011. "The qualitative research interview," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 8(3), pages 238-264, August.
    2. Sandy Q. Qu & John Dumay, 2011. "The qualitative research interview," Qualitative Research in Accounting & Management, Emerald Group Publishing Limited, vol. 8(3), pages 238-264, August.
    3. Zhang, Ying & Snyder, Lawrence V. & Ralphs, Ted K. & Xue, Zhaojie, 2016. "The competitive facility location problem under disruption risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 453-473.
    4. Ramani, Vinay & Ghosh, Debabrata & Sodhi, ManMohan S., 2022. "Understanding systemic disruption from the Covid-19-induced semiconductor shortage for the auto industry," Omega, Elsevier, vol. 113(C).
    5. Can Saglam, Yesim & Yildiz Çankaya, Sibel & Golgeci, Ismail & Sezen, Bulent & Zaim, Selim, 2022. "The role of communication quality, relational commitment, and reciprocity in building supply chain resilience: A social exchange theory perspective," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    6. Dun Li & Bangdong Zhi & Tobias Schoenherr & Xiaojun Wang, 2023. "Developing capabilities for supply chain resilience in a post-COVID world: A machine learning-based thematic analysis," IISE Transactions, Taylor & Francis Journals, vol. 55(12), pages 1256-1276, December.
    7. Hosseini, Seyedmohsen & Ivanov, Dmitry & Dolgui, Alexandre, 2019. "Review of quantitative methods for supply chain resilience analysis," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 285-307.
    8. Suryawanshi, Pravin & Dutta, Pankaj, 2022. "Optimization models for supply chains under risk, uncertainty, and resilience: A state-of-the-art review and future research directions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    9. Anni-Kaisa Kähkönen & Pietro Evangelista & Jukka Hallikas & Mika Immonen & Katrina Lintukangas, 2023. "COVID-19 as a trigger for dynamic capability development and supply chain resilience improvement," International Journal of Production Research, Taylor & Francis Journals, vol. 61(8), pages 2696-2715, April.
    10. Li, Guo & Xue, Jing & Li, Na & Ivanov, Dmitry, 2022. "Blockchain-supported business model design, supply chain resilience, and firm performance," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    11. I. Nyoman Pujawan, 2004. "Assessing supply chain flexibility: a conceptual framework and case study," International Journal of Integrated Supply Management, Inderscience Enterprises Ltd, vol. 1(1), pages 79-97.
    12. Lam, Jasmine Siu Lee & Bai, Xiwen, 2016. "A quality function deployment approach to improve maritime supply chain resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 92(C), pages 16-27.
    13. Aqlan, Faisal & Lam, Sarah S., 2015. "A fuzzy-based integrated framework for supply chain risk assessment," International Journal of Production Economics, Elsevier, vol. 161(C), pages 54-63.
    14. Paul E. Green & Abba M. Krieger & Yoram Wind, 2001. "Thirty Years of Conjoint Analysis: Reflections and Prospects," Interfaces, INFORMS, vol. 31(3_supplem), pages 56-73, June.
    15. David Simchi-Levi & William Schmidt & Yehua Wei & Peter Yun Zhang & Keith Combs & Yao Ge & Oleg Gusikhin & Michael Sanders & Don Zhang, 2015. "Identifying Risks and Mitigating Disruptions in the Automotive Supply Chain," Interfaces, INFORMS, vol. 45(5), pages 375-390, October.
    16. Faraway, Julian J. & Augustin, Nicole H., 2018. "When small data beats big data," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 142-145.
    17. Ali, Mohd Helmi & Chung, Leanne & Kumar, Ajay & Zailani, Suhaiza & Tan, Kim Hua, 2021. "A sustainable Blockchain framework for the halal food supply chain: Lessons from Malaysia," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    18. Thi Huong Tran & Mario Dobrovnik & Sebastian Kummer, 2018. "Supply chain risk assessment: a content analysis-based literature review," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 31(4), pages 562-591.
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