Decision, Operations & Information Technologies
Permanent URI for this communityhttp://hdl.handle.net/1903/2230
Prior to January 4, 2009, this unit was named Decision & Information Technologies.
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Item TWO ESSAYS ON THE ROLE OF INFORMATION TRANSPARENCY IN MARKETPLACE OPERATIONS(2024) Jiang, Jane Yi; Elmaghraby, Wedad J.; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation encompasses two studies on the crucial role of information within marketplace operations. Collaborating with two platforms, we deliver empirical evidence and offer prescriptive insights into how information is conveyed to and perceived by customers, and the consequent impacts on sellers and the marketplace at large.The first study analyzes the introduction of the novel blockchain tracing technology into an online grocery marketplace. Our findings indicate that credible supply chain transparency encourages consumers to more readily buy traced products, especially those that are handling-sensitive or offered in less-trusted markets. Consequently, adopting third-party sellers experienced an average monthly revenue increase of up to 23.4\%. By utilizing structural estimation to understand how consumers assess product attributes and quality, we highlight that consumer responses (and welfare effects) vary in sophistication and size based on their prior experience with the product category. Additionally, we establish that consumers deem blockchain-based. The second study analyzes the unintended transparency issue associated with the pricing structure of bundle discounts and its consequences on product purchases and returns. Our findings reveal that customers tend to overlook complex pricing structures, leading to impulsive buying and increased returns. Enhancing customer attentiveness of pricing can decrease the Retailer's return rates by 20.9\%. Moreover, improving customer attentiveness to pricing benefits retailers by enabling them to create more versatile bundle offers, further optimizing their sales strategy.Item An Operations Management Framework to Improve Geographic Equity in Liver Transplantation(2022) Akshat, Shubham; Raghavan, S.; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In the United States (U.S.), on average three people die every day awaiting a liver transplant for a total of 1,133 lives lost in 2021. While 13,439 patients were added to the waiting list in 2021, only 9,236 patients received liver transplantation. To make matters worse, there is significant geographic disparity across the U.S. in transplant candidate access to deceased donor organs. The U.S. Department of Health and Human Services (HHS) is keen to improve transplant policy to mitigate these disparities. The deceased donor liver allocation policy has been through three major implementations in the last nine years, but yet the issue persists. This dissertation seeks to apply operations management models to (i) understand transplant candidate behavior, and (ii) suggest improvements to transplant policy that mitigate geographic disparity. In the first essay, we focus on reducing disparities in the organ supply to candidate demand (s/d) ratios across transplant centers. We develop a nonlinear integer programming model that allocates organ supply to maximize the minimum s/d ratios across all transplant centers. We focus on circular donation regions that address legal issues raised with earlier organ distribution frameworks. This enables reformulating our model as a set-partitioning problem and our proposal can be viewed as a heterogeneous donor circle policy. Compared to the current Acuity Circles policy that has fixed radius circles around donation locations, the heterogeneous donor circle policy greatly improves both the worst s/d ratio, and the range of s/d ratios. With the fixed radius policy of 500 nautical miles (NM) the s/d ratio ranges from 0.37 to 0.84 at transplant centers, while with the heterogeneous circle policy capped at a maximum radius of 500NM the s/d ratio ranges from 0.55 to 0.60, closely matching the national s/d ratio of 0.5983. Broader sharing of organs is believed to mitigate geographic disparity. Recent policies are moving towards broader sharing in principle. In the second essay, we develop a patient's dynamic choice model to analyze her strategic response to a policy change. First, we study the impact of the Share 35 policy, a variant of broader sharing introduced in 2013, on the behavioral change of patients at the transplant centers (i.e., change in their organ acceptance probability), geographic equity, and efficiency (transplant quality, offer refusals, survival benefit from a transplant, and organ travel distance). We find that sicker patients became more selective in accepting organs (acceptance probability decreased) under the Share 35 policy. Second, we study the current Acuity Circles policy and conclude that it would result in lower efficiency (more offer refusals and a lower transplant benefit) than the previous Share 35 policy. Finally, we show that broader sharing in its current form may not be the best strategy to balance geographic equity and efficiency. The intuition is that by indiscriminately enlarging the pool of supply locations from where patients can receive offers, they tend to become more selective, resulting in more offer rejections and less efficiency. We illustrate that the heterogeneous donor circles policy that equalizes the s/d ratios across geographies is better than Acuity Circles in achieving geographic equity at the lowest trade-off on efficiency metrics. The previous two essays demonstrate the benefit of equalizing the s/d ratios across geographies. In December 2018 the Organ Procurement and Transplantation Network (OPTN) Board of Directors approved the continuous distribution framework as the desired policy goal for all the organ allocation systems. In this framework, the waiting list candidates will be prioritized based on several factors, each contributing some points towards the total score of a candidate. The factors in consideration are medical severity, expected post-transplant outcome, the efficient management of organ placement, and equity. However, the respective weights for each of these potential factors are not yet decided. In the third essay, we consider two factors, medical severity and the efficient management of organ placement (captured using the distance between the donor hospital and transplant center), and we design an allocation policy that maximizes the geographic equity. We develop a mathematical model to calculate the s/d ratio of deceased-donor organs at a transplant center in a continuous scoring framework of organ allocation policy. We then formulate a set-partitioning optimization problem and test our proposals using simulation. Our experiments suggest that reducing inherent differences in s/d ratios at the transplant centers result in saving lives and reduced geographic disparity.Item Evolution and Current Practices of Ride Services(2021) Noh, Daehoon; Tunca, Tunay I; Business and Management: Decision & Information Technologies; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In the past decade we have seen a rapid transformation in the ride service market with the advent of decentralized Ride Hailing (RH) services (e.g., Uber, Lyft), who gained significant market share at the expense of traditional Vertically Integrated (VI) taxi companies.However, it is not clear what the endgame of this competition between these two models will be. What is more, the current development of driverless car technology, which leads to another form of Vertically Integrated service model, is posing further questions on how the industry will shape in the future. In the first chapter, we analyze this question by game-theoretically modeling entry and competition between decentralized Ride Hailing and Vertically Integrated ride services. First, by comparing monopoly models, we find that due to the advantage of centralization, the VI model is more efficient in increasing firm profits, reducing delays and increasing social welfare compared to the RH model. However, in competition, the RH firm predominantly reverses this disadvantage, and gains the upper hand in the market with lower delays, higher market share, and higher profits due to its flexibility in setting its supply compared to the VI firm, which projects the success of the ride-hailing firms compared to the traditional taxi model. Furthermore, the entry of the RH firm into the market always improves social welfare, while the entry of an inefficient VI firm may reduce industry service levels and surprisingly decrease social despite introducing competition. Our results suggest that entry of a costly self-driving car technology may in fact hurt the industry as a whole and social welfare in a market that is served predominantly by a ride-hailing company, and this technology should be approached carefully by the industry and the regulators. In the second chapter, we examine the effect of offering ride distance information to the drivers in the ride-hailing two-sided market.This is of our interest because currently, the drivers cannot observe the riders' destination. However the leading companies in the ride-hailing business such as Uber and Lyft are experimenting the effect of offering this information to the drivers, but the effect is yet uncertain. It may introduce efficiency, or it may aggravate the cherry picking behavior which will be detrimental to the firm. We develop a game theoretical model of (i) a ride-hailing firm where the drivers do not observe the riders' ride distance (the unobservable case), and (ii) where they can observe (the observable case). We compare the two cases to determine when it would benefit the ride-hailing firm to offer this information to the drivers. We also compare consumer surplus and social welfare to see if the firm's decision may be in conflict with the social planner's. Our main finding is that when consumers are patient, the drivers' cherry picking behavior introduces efficiency to the operations of the observable case, making it optimal for the firm to offer observability to the drivers. However as consumers become impatient, this cherry picking behavior becomes burdensome for the observable case, and thus the firm's optimal decision is to not give observability. Furthermore, under certain parameter regions, the firm's decisions are in conflict with the social planner's objective, thus the government may need to devise a policy to maximize social welfare.