Search

In the face of supply chain disruptions, firms are expected to swiftly recover and resume operations. Traditional strategies focus on restoring operations to pre‐disruption states while largely maintaining the existing supply network structure. Recent cases, however, highlight a different approach: supply chain plasticity, wherein firms undergo significant structural shifts in supply network design as a response to disruptions with the goal to improve performance. Drawing on the foundations of supply chain responsiveness and network theory, we investigate how (and if) firms redesign their supply chains against a backdrop of increased disruptions and the implications supply chain plasticity has on resilience. Rooted in network theory, this study not only theoretically compares, contrasts, and connects prior concepts with supply chain plasticity but also empirically investigates whether firms exhibit a plastic response by modifying their supply chain network structures—specifically focusing on structural holes, centrality, and clustering network dimensions. Furthermore, we hypothesize that network plasticity impacts firm performance in the form of time to recover from a disruption. The findings demonstrate that the existence and significance of network plasticity in shaping firm responses to disruptions are indeed present and can be beneficial. We also provide evidence that supply chain plasticity is an efficacious strategy to enhance resilience and recovery performance amidst heightened disruption frequency. As firms increasingly face dynamic and complex environments, understanding and leveraging network plasticity will be vital for sustaining competitive advantage and achieving long‐term success. [ABSTRACT FROM AUTHOR]

This study investigates how supply chain characteristics influence a rival firm's response to a focal firm's product preannouncements from a competitive dynamics perspective. Indeed, many firms recognize that it is critical to leverage their supply chains to gain a competitive advantage. We propose that common suppliers enhance a rival firm's awareness of the focal firm's credibility, reducing competitive responses. In addition, a rival firm's strong supplier inventory performance will motivate rivals to respond more aggressively, while the rival's supply–chain partnerships enhance its capability to react to the focal firm. Using panel data from S&P 1500 firms between 2007 and 2015, our findings provide support for our hypotheses, illustrating that supply chain characteristics can significantly influence a rival firm's responses to the focal firm's preannouncements. This research contributes to the competitive dynamics and supply chain management literature by highlighting the strategic role of supply chain characteristics in interfirm competition, offering practical insights for managers on leveraging supply chain resources to effectively navigate competitive threats. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of our study is to investigate how a manufacturing plant's internal operations along with its network of connections (upstream and downstream) can have an impact on its recovery time from a disruption. The authors also examine the inverse-U impact of complexity. Finally, the authors test the moderating role that business continuity management plans (BCP) at the plant level have on recovery time. Design/methodology/approach: To test our hypotheses, the authors partnered with Resilinc Corporation, a Silicon Valley-based provider of supply chain risk management solutions to identify focal firms' suppliers, customers and plant-level data including information on parts, manufacturing activities, bill of materials, alternate sites and formal business continuity plans. The authors employed censored data regression technique (Tobit). Findings: Several important findings reveal that the plant's internal operations and network connections impact recovery time. Specifically, the number of parts manufactured at the plant as well as the number of internal plant processes significantly increase disruption recovery time. In addition, the number of supply chains (upstream and downstream) involving the plant as well as the echelon distance of the plant from its original equipment manufacturer significantly increase recovery time. The authors also find that there exists an inverted-U relationship between complexity and recovery time. Finally, the authors find partial support that BCP will have a negative moderating effect between complexity and recovery time. Originality/value: This research highlights gaps in the literature related to supply chain disruption and recovery. There is a need for more accurate methods to measure recovery time, more research on recovery at the supply chain site level and further analysis of the impact of supply chain complexity on recovery time. [ABSTRACT FROM AUTHOR]