Essays on strategic interactions in vertical supply chains: on the role of inventory and technology

Thesis Advisory Committee
Prof. Sachin Jayaswal (Chair Person)
Prof. Ankur Sinha (Member)
Prof. Benny Mantin (Member)

The past two decades have witnessed a shift from centrally managed supply chains to
decentralized supply chains (Netessine, 2004). In decentralized supply chains, interests of
individual members may not be aligned with each other. This dissertation is an attempt
to understand how the interactions among various agents in a decentralized supply chain
are impacted by different supply chain characteristics. Specifically, we explore the role
of inventory and technology on manufacturer-retailer interactions in decentralized supply
chains. This dissertation consists of three essays, which focus on the following supply chain
characteristics: (i) the manufacturer’s cost learning (ii) the retailer’s adoption of tracking
technology, and (iii) mass customization facilitated by using 3D printing.
In the first essay, we study how the manufacturer’s cost learning impacts the retailer’s
inventory decisions in a decentralized supply chain. Cost learning refers to the manufacturer’s
ability to reduce the marginal production cost due to learning from production activities.
We highlight the ubiquity of cost learning across various industries and discuss how
the manufacturer’s cost learning interacts with the retailer’s strategic inventory. Anand,
Anupindi, and Bassok (2008) have demonstrated that retailers have an incentive to carry
inventory strategically as a bargaining chip to induce the upstream manufacturer to drop
future wholesale prices. The manufacturer, anticipating the retailer’s strategic behavior,
responds by increasing the early period wholesale price. However, when the manufacturer
experiences cost learning, whereby the future production cost reduces with the cumulative
production in the early period, she also has some incentive to reduce the early period
wholesale price to induce the retailer to purchase more. Hence, in the presence of cost learning,
the manufacturer faces a dilemma: should she hold inventory, bearing her holding cost, to
progress faster on the learning curve, or should she adjust her wholesale price to encourage
the retailer to carry inventory, who bears his holding cost but also uses it as a bargaining chip to
lower future wholesale prices? We formulate a game-theoretic model to address this dilemma
and characterize the optimal inventory holding pattern in the supply chain.