Essays in Operations Management

This dissertation consists of three main chapters focusing on operational problems in supply chain contracting, online food-ordering services, and agricultural open burning in developing countries. In Chapter 2, we analyze a contract in which a supplier, who is exposed to disruption risk, offers a supply-flexibility contract comprising of a wholesale price and a minimum-delivery fraction ("flexibility" fraction) to a buyer facing random demand. The supplier is allowed to deviate below the order quantity by at most the flexibility fraction. The supplier's regular production is subject to random disruption but she has access to a reliable expedited supply source at a higher marginal cost. We derive the supplier-led optimal contract and show that supply-chain effciency improves relative to the price-only contract. More interestingly, even though the buyer lets the supplier decide how the two share supply risk, profits of both the players increase by the introduction of flexibility into the contract. Further, supply-flexibility may be even more valuable for the buyer compared to the supplier. Interestingly, the flexibility fraction is not monotone in supplier reliability and a more reliable supplier may even prefer to transfer more risk to the buyer. The robustness of these findings is established on two extensions: one where we study a buyer-led contract (i.e., the buyer chooses the flexibility fraction) and the other where the expedited supply option is available to both the supplier and the buyer. In Chapter 3, We study the problem of managing queues in online food-ordering services where customers, who place orders online and pick up at the store, are offered a common quote time, i.e., the promised pick-up time minus the time the order is placed. The objective is to minimize the long-run average expected earliness and tardiness cost incurred by the customers. We introduce the family of static threshold policies for managing such queues. A static threshold policy is one that starts serving the first customer in the queue as soon as the server is free and the time remaining until the promised pick-up time of that customer falls below a fixed threshold. In important technical contributions for establishing the attractiveness of the optimal static threshold policy, we develop three sets of lower bounds on the optimal cost. The first set of lower bounds exploits structural properties of two special static threshold policies, while the second set utilizes the idea of a clairvoyant optimal policy by considering a decision maker who has either full or partial knowledge of the outcomes of future uncertainties. To obtain our third set of lower bounds, we develop bounds on the optimal earliness and tardiness costs by establishing lower and upper bounds on the steady-state waiting time under an optimal policy. The optimal static threshold policy is asymptotically optimal in several cases, including the heavy traffic and the light traffic regimes. We also develop a dynamic threshold policy in which the threshold depends on the queue length. Finally, through a comprehensive numerical study, we demonstrate the excellent performance of both the static and the dynamic threshold policies. In Chapter 4, we study how the government can use information-disclosure policies to minimize agricultural open burning in developing countries. Agricultural open burning, i.e., the practice of burning crop residue in harvested fields to prepare land for sowing a new crop, is well-recognized as a significant contributor to CO2 and black carbon emissions, and longterm climate change. Low-soil-tillage practices using a specific agricultural machine called Happy Seeder, which can sow the new seed without removing the previous crop residue, have emerged as the most effective and profitable alternative to open burning. However, given the limited number of Happy Seeders that the government can supply, and the fact that farmers incur a significant yield loss if they delay sowing the new crop, farmers are often unwilling to wait to be processed by the Happy Seeder and, instead, decide to burn their farms. A Happy Seeder is assigned to process a group of farms in an arbitrary order. The government knows, but does not necessarily disclose, the schedule for the Happy Seeder at the start of the sowing season. Farmers are impatient, in the sense that they incur a disutility per unit of time associated with waiting for the Happy Seeder. If the Happy Seeder processes a farm, then the farmer gains a positive utility. At the beginning of each period, each farmer decides whether to burn her farm or to wait, given the information provided by the government about the Happy Seeder's schedule. We propose a class of information-disclosure policies, which we refer to as threshold policies, that provide no information to the farmers about the schedule until a pre-specified period and then reveal the entire schedule. By obtaining the unique symmetric Markov perfect equilibrium under any threshold policy, we show that the use of an optimal threshold policy can significantly lower the number of farms burnt compared to that under the full-information and no-information disclosure policies.