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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.

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).

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.

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.

The purpose of this paper is to review the state of the art in extended enterprise (EE) thinking.

The approach used the 2004 book, The Extended Enterprise, as the jumping-off point to review the literature and better define the EE. What was once projected as depicting the future state of supply chain management is now shaping the way in which organizations interact with their customers and suppliers. New issues in this arena include considerations of risk, knowledge sharing, and supply chain performance. The authors review these new developments, describe how they might affect the collaborative supply chain, and posit future trends.

The major theme from this research is that EE thinking is emerging among global companies as a primary way in which firms now compete. The term “Collaborative supply chains” appears, in some circles, to replace the term “EE.” Yet the principles and tenets delineated in the term “EE” are captured in “collaborative supply chains.” The authors find that the EE concept is distinct from other supply chains or subcontracting relationships in that firms are linked as learning organizations. Also, the authors have noted barriers to collaboration such as an unwillingness to share information, lack of trust, perceptions of lack of mutuality and symmetry, and mistrust about the fairness of benefits, costs, and risk sharing.

The limitations of this research could be a function of the papers reviewed since this review was not intended to be exhaustive but merely illustrative of the extant research. Nonetheless, the conclusions from the focus on risk, knowledge sharing, and performance hold strong implications for more collaborative relations among supply chain partners.

Given the importance of supply chain partnerships, this research adds perspective for those firms that are reluctant to engage in such collaborative partnerships. This review contributes to extended enterprise thinking and is therefore insightful for both academics and practitioners.