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

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.