AuthorDivey, Shailesh J.
Other ContributorsHekimoglu, M. Hakan; Ravichandran, T.; Clark, Brian J.; Pazour, Jennifer A.;
AbstractIn the last few decades, a number of organizations have been affected by unforeseen supply-chain vulnerabilities and disruptions. A common theme at the heart of these crises is the lack of robust processes to identify and successfully manage risks exacerbated by the increasing globalization and complexity of supply chains. Risk management, therefore, plays a vital role in effectively operating supply chains in the presence of a variety of uncertainties. My dissertation studies the problem of supply chain risk management from two perspectives: analytical and network science. First (Chapter 2), I focus on the operational aspect to handling supply chain risks, which is appropriately responding to risk by investing in AI-based event-monitoring capabilities. In particular, I investigate a risk-averse firm’s investment decision in event-monitoring technologies, and the impact of risk on disruption mitigation strategies. My ideas around the impact of investing in event-monitoring to mitigate the impact of disruption and the benefits of optimal strategies were developed based on stylized mathematical models. The models help identify the optimal strategies, i.e., the best course of action.
Second (Chapter 3), I address how firm risk affects its centrality within a manufacturing supply chain network. Firms do not exist in isolation, and their decisions determine their influence within the network. Firms’ operational decisions about their connections are self-preserving in order to position themselves for optimal business and information flow as well as social capital. A risk-induced shock to a firm can generate ripple effects in the supply chain, and the decision making of the firm and its connections indicates how risk will affect their importance within the network.;
DescriptionAugust 2022; School of Management
DepartmentLally School of Management;
PublisherRensselaer Polytechnic Institute, Troy, NY
RelationshipsRensselaer Theses and Dissertations Online Collection;
AccessRestricted to current Rensselaer faculty, staff and students in accordance with the
Rensselaer Standard license. Access inquiries may be directed to the Rensselaer Libraries.;