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

Abstract

"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. In the second essay, we study the retailer’s adoption of tracking technology and its interaction with his strategic inventory decision. In the absence of strategic inventory, the retailer’s costbenefit analysis of tracking technology adoption is rather straightforward. The benefits from eliminating shrinkage costs are compared with the tagging cost required to adopt tracking technology. However, in the presence of strategic inventory, the retailer’s tracking technology decision becomes more nuanced. It does benefit the retailer by eliminating the retailer’s shrinkage cost, but it simultaneously eliminates the additional wholesale price reduction induced by shrinkage, over and above what is induced by strategic inventory. When the retailer adopts a tracking technology, his total order quantity may decrease, thereby reducing his bargaining power to extract a lower future wholesale price. In addition, it also imposes a tagging cost. This raises an important question for a retailer who carries strategic inventory. Should he adopt tracking technology, which eliminates shrinkage but also eliminates the benefit of wholesale price reduction induced by shrinkage? If yes, what is the impact of such a technology adoption on the supplier’s profit? We formulate a stylized game to capture the strategic inventory decision and technology adoption decision of the retailer. In the third essay, we investigate the role of 3D printing in the design of a supply chain that leverages this technology to sell customized products. 3D printing allows manufacturers to produce and sell customized products that can fit the exact customer specifications (biometric profile). Ensuring fit requires capturing each customer’s dimensions, which can be achieved by delegating the process to retailers. This often involves on-site production of the fitted product, which implies ceding pricing power to the retailer. Alternatively, the manufacturer can involve customers directly, usually via a mobile application. By doing so, the manufacturer retains the pricing power, but subjects herself to issues stemming from data imperfections, and consequently, a potential lack of fit of the product. Hence, the manufacturer faces a challenge: should she delegate data collection and 3D printing cost to the retailer or should she bear the 3D printing cost while engaging with the customer directly to carry out data collection? We resolve the manufacturer’s dilemma by revealing the interactions among the manufacturer, the retailer and the customers using a theoretical model."