RESUMO
COVID-19 has revealed global supply chains' vulnerability and sparked debate about increasing supply chain resilience (SCRES). Previous SCRES research has primarily focused on near-term responses to large-scale disruptions, neglecting long-term resilience approaches. We address this research gap by presenting empirical evidence from a Delphi study. Based on the resource dependence theory, we developed 10 projections for 2025 on promising supply chain adaptations, which were assessed by 94 international supply chain experts from academia and industry. The results reveal that companies prioritize bridging over buffering approaches as long-term responses for increasing SCRES. Promising measures include increasing risk criteria importance in supplier selection, supply chain collaboration, and supply chain mapping. In contrast, experts ascribe less priority to safety stocks and coopetition. Moreover, we present a stakeholder analysis confirming one of the resource dependence theory's central propositions for the future of global supply chains: companies differently affected by externalities will choose different countermeasures.
RESUMO
The COVID-19 pandemic has caused major supply chain disruptions and unveiled the pressing need to improve supply chain resilience (SCRES). Industry 4.0 (I4.0) is a promising lever; however, its future in supply chain risk management (SCRM) is highly uncertain and largely unexplored. This paper aims to evaluate I4.0's potential to improve SCRES in a post-COVID-19 world. Based on current literature and multiple workshops, 13 future projections on potential I4.0 application areas in SCRM were developed. A two-round Delphi study among 64 SCRM experts with digital expertise was conducted to evaluate and discuss the projections regarding their probability of occurrence until 2030, their impact on SCRES, and their desirability. A fuzzy c-means algorithm was applied to cluster the projections based on the expert assessments. The expert evaluations led to three clusters on I4.0 application in SCRM: Four projections on generating data, increasing visibility, and building digital capabilities received considerable approval and are reliable to improve SCRES in 2030. Four projections enabling data sharing and processing were predominantly supported and demonstrated realization potential for 2030. Finally, five projections that require major supply network adaptations were deemed unlikely to improve SCRES in 2030. This paper answers several research calls by presenting empirical evidence on the pathway of I4.0 implementation in SCRM following the COVID-19 pandemic. Moreover, it evaluates a holistic set of technologies and indicates prioritization potentials to achieve SCRES improvements.
RESUMO
Much research has been conducted on the effects of COVID-19 on company and supply chain resilience. However, few contributions have focused on small and medium-sized enterprises. These companies are claimed to be the drivers of economic growth but often lack access to resources and alternatives when interruptions occur, making them a bottleneck for supply chains. Using a multiple case study approach, this paper links resilience theory to the design of the relationships between eight German small and medium-sized enterprises and their suppliers and customers. It analyzes the way in which these companies combine contractual and relational investments across their supply chain flows of product, finance, and information in order to improve resilience. Company representatives were interviewed on three occasions between June 2018 and December 2020, that is, before COVID-19 and during the lockdowns. The results of the case study explain why and how companies of this type have been able to anticipate and manage the crisis. The interviews revealed that those companies that made the largest investments in the relational aspects of their partnerships while safeguarding product and financial flows through contracts performed best. In principle, contractual investments are higher in partnerships with suppliers. However, the precise combination of contractual and relational investments depends on the business model, the business philosophy of the CEO, and the allocation of power within the supply chain. These findings indicate that, when collaborating with small businesses, supply chain partners should focus on building relationships in order to create resilience in the supply chain.
RESUMO
The COVID-19 pandemic is one of the most severe supply chain disruptions in history and has challenged practitioners and scholars to improve the resilience of supply chains. Recent technological progress, especially industry 4.0, indicates promising possibilities to mitigate supply chain risks such as the COVID-19 pandemic. However, the literature lacks a comprehensive analysis of the link between industry 4.0 and supply chain resilience. To close this research gap, we present evidence from a systematic literature review, including 62 papers from high-quality journals. Based on a categorization of industry 4.0 enabler technologies and supply chain resilience antecedents, we introduce a holistic framework depicting the relationship between both areas while exploring the current state-of-the-art. To verify industry 4.0's resilience opportunities in a severe supply chain disruption, we apply our framework to a use case, the COVID-19-affected automotive industry. Overall, our results reveal that big data analytics is particularly suitable for improving supply chain resilience, while other industry 4.0 enabler technologies, including additive manufacturing and cyber-physical systems, still lack proof of effectiveness. Moreover, we demonstrate that visibility and velocity are the resilience antecedents that benefit most from industry 4.0 implementation. We also establish that industry 4.0 holistically supports pre-disruption resilience measures, enabling more effective proactive risk management. Both research and practice can benefit from this study. While scholars may analyze resilience potentials of under-explored enabler technologies, practitioners can use our findings to guide industry 4.0 investment decisions.