On March 2011 a destructive 9.0-magnitude earthquake and tsunami along with nuclear explosions struck northeastern Japan; killing thousands of people, halting industry and crippling infrastructure. A large manufacturing company operating outside of Japan received the news in the middle of the night. Within a few hours of the tsunami hitting Japan, this manufacturer’s logistics team ran global materials management reports to communicate the precise status of the products originating from Japan to their entire global network of facilities. With this quick and far reaching communication the manufacturer was able to launch a successful contingency plan. Alternative suppliers, already existing as part of their global network, were evaluated and used to mitigate Japan’s disruptive impact. The resiliency of this manufacturer’s trusted network of supply chain trading partners allowed for minimum disruptions, saving countless money and maintaining continuity for its end-to-end supply chain. This manufacturer was part of a cloud-based supply chain that provided the catalyst to quickly shift its resources to allay the impact of no longer being able to receive product from Japan. Today's supply chains are global and complex networks of enterprises that aim to deliver products in the right quantity, in the right place, and at the right time in an increasingly volatile and unpredictable environment. To cope with internal and external supply chain instability and disruptions, supply chains need to be resilient to survive. A supply chain's ability to collaboratively share information with its supply chain partners is one of the most important factors that enhance a supply chain’s resilience. Cloud based supply chain management (SCM) creates a platform that enables collaborative information sharing that helps to identify, monitor and reduce supply chain risks, vulnerabilities and disruptions. However, supply chain academics and practitioners are at its infancy in understanding the capabilities of cloud based supply chains and its impact on resiliency. The goal of this dissertation is to explore how cloud based SCM make supply chains more resilient to disruptions. To achieve this goal the present research addresses the following fundamental research question: What is the impact of cloud based supply chain management (SCM) on supply chain resilience? To address this research question, this dissertation is comprised of three separate but interrelated essays. The first essay uses the systematically literature review (SLR) method to provide clear definitions of supporting constructs of supply chain resiliency (SCRES), classify the capabilities of SCRES, and identify existing research gaps and future SCRES research ideas. The second essay applies resource-based view (RBV) and dynamic capabilities as the theoretical lens to investigate the role of cloud based SCM in establishing SCRES. The second essay develops a theory-driven, conceptual model to illustrate and explain the relationships among cloud based SCM, SCRES, and the supply chain capabilities identified in the first essay. The third essay uses systems dynamics theory to develop two novel casual loop diagrams (CLD) and its equivalent systems dynamics (SD) models to quantitatively analyze the impact of cloud based information sharing on supply chain performance. A hospital supply chain is used as an illustrative example to show the positive impact on performance. Lead-time, inventory spend, and customer service levels are the comparative performance metrics used in this essay and are consistent with the findings of essays 1 and 2. One CLD and its equivalent SD model represent a traditional on-premise hospital supply chain information sharing platform and the other represent a cloud based hospital information sharing platform. The SD models simulate and compare the performance of the traditional and cloud based hospital supply chain platforms.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc804986 |
| Date | 08 1900 |
| Creators | Kochan, Cigdem Gonul |
| Contributors | Nowicki, David R., Randall, Wesley Spencer, Sauser, Brian, Kulkarni, Shailesh |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | x, 161 pages : illustrations (chiefly color), Text |
| Rights | Public, Kochan, Cigdem Gonul, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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