Author's School

Olin Business School

Author's Department

Supply Chain, Operations, and Technology

Language

English (en)

Date of Award

Spring 5-15-2022

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Chair and Committee

Panos Kouvelis

Committee Members

Lingxiu Dong, Jake Feldman, Danko Turcic, Kaitlin Daniels,

Abstract

The dynamic program is a principal method for analyzing stochastic optimization problems. This dissertation studies three operations management problems that arise in the dynamic environment. The principal motivation behind these comes from the applicability in three areas: the agricultural supply chain, the container shipping industry, and supply chain financing. In the first chapter, we consider the hog production industry, where the hog raising farm should decide the selling strategy among several selling options. The farm also faces the uncertain yield of different weights of hogs and spot price volatility from other interactive markets. In the second chapter, we formulate a blockchain-based cargo reservation system, where a token is designed to be used as a booking deposit to compensate the contractual party if the other side fails to honor the booking, i.e., the overbooking from the service provider and customer no-show. In the third chapter, we study advance payment as a financing instrument in a multitier supply chain to mitigate the supply disruption risk and compare the traditional system (with limited visibility) with the blockchain-enabled system (with perfect visibility). The main goal of this chapter is to shed light on how blockchain adoption impacts agents' operational and financial decisions and profit levels in a multitier supply chain.

We apply the genre of dynamic models to formulate all three problems, but we address them by different methodologies because of the difference in the contexts. The first two problems possess structural properties adequate to find the optimal structural policy for a dynamic program, whereas the last problem can be applied to game theory. In the hog production chapter, we find that the optimal selling strategy for the hog farm is non-monotone. The counter-intuitive situation, namely, the farm does not fulfill the long-term contract but sells to the open market to speculate the high spot price, happens when the open market is good enough. We also propose a newsvendor-like heuristic policy that improves the profit of the hog farm by over 25%. We find the service provider has different acceptance strategies for the maritime container shipping problem with and without overbooking. He always prefers reliable customers without overbooking but prefers unreliable customers with overbooking in some circumstances. In the deep-tier supplier chain finance, take a game-theoretic approach to compare how blockchain-enabled deep-tier financing schemes affect a financially constrained supply chain's optimal risk-mitigation and financial strategies. We find that although improved visibility via blockchain adoption can help the manufacturer make informed supply chain financing decisions, whether it can benefit all supply chain members depends on the financing schemes in use. Blockchain-enabled delegate financing increases risk-mitigation investments and benefits all three tiers of the supply chain only when tier-2 is severely capital-constrained with the working capital below a threshold. Because delegate financing endows the intermediary tier-1 supplier leverage over the manufacturer, the inefficiency inhibits an all-win outcome when the tier-2 is not severely capital-constrained. Blockchain-enabled cross-tier direct financing exhibits a compelling performance as it always leads to win-win-win outcomes (and thus ubiquitously implementable) regardless of the supplier's working capital profile.

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