Decision Sciences Theses and Dissertations

Permanent URI for this collection

https://hdl.handle.net/1794/12484

Browse

Browsing Decision Sciences Theses and Dissertations by Title

Now showing 1 - 5 of 5
  • Thumbnail Image
    ItemOpen Access
    CONSUMPTION PREFERENCES, TIME AND UNCERTAINTY: IMPACTS ON RETAIL PRICING TACTICS
    (University of Oregon, 2017-09-06) Jalili, Monire; Pangburn, Michael
    My dissertation is a collection of three essays with analytical models at the interface of marketing and operations with a focus on pricing. The common theme in this dissertation is studying the effect of the consumer-driven demand on the optimal operational decisions of a single firm. This dissertation includes co-authored material. In my first essay, I study the role of consumers' opposing perceptions of green quality on the optimal product line decisions, i.e., products, prices and quality by analyzing the firm's optimization problem and incorporating an endogenous demand model that emerges from the consumers' preferences while considering the cost implications of introducing a green product. My second essay is on optimal timing of price discounts. Delaying discounts, i.e., giving discounts on future spending based on current spending is a prevalent retail discounting practice. For a market of rational and forward-looking consumers who repeatedly visit and purchase with the firm, we analyze the relative efficacy of delayed credits vs. a natural alternative of immediate discounts. In my third essay, I explore a firm's optimal pricing strategy when it simultaneously rents and sells a product for which consumers have a priori valuation uncertainty.
  • Thumbnail Image
    ItemRestricted
    Essays in Operations and Supply Chain Management
    (University of Oregon, 2012) Xu, Shubin; Xu, Shubin; Bean, James
    This dissertation is based on three essays in operations and supply chain management. In essay 1, we study an operations scheduling problem in a complex manufacturing system, most notably, semiconductor manufacturing. In particular, we study the scheduling problem of minimizing total weighted tardiness on parallel non-identical batch processing machines. We formulate the (primal) problem as a nonlinear integer programming model. Moreover, we prove that the primal problem can be solved exactly by solving a corresponding dual problem with nonlinear relaxation. Since both the primal and the dual problems are NP-hard, we propose to use genetic algorithms, based on random keys and multiple choice encodings, to heuristically solve them. We found that the genetic algorithms consistently outperform a standard mathematical programming package in terms of solutions and computation times. We also found that for small scale problem instances, the multiple choice genetic algorithm outperforms the random keys genetic algorithm, while for medium and large scale problem instances, the random keys genetic algorithm outperforms the multiple choice genetic algorithm. In essay 2, we study a monopolist firm offering successive versions of a durable good (e.g., software) that improves over time. The firm decides the time between successive introductions as well as price. In turn, consumers strategically decide whether to purchase or wait for a later version. We model and analyze three alternative strategies for offering successive product versions: the partial-, continuous-, and no-updates policies. We first consider the firm's profit maximizing policy assuming a homogeneous market and subsequently address consumers with heterogeneous product valuations. Our analytic model's simple structure and results highlight the important tradeoff between price and release timing for products with successive versions. In essay 3, we study the effect of time series structure of customer demand models on the value of information sharing within a supply chain. We contribute to the literature by incorporating a nonlinear demand model based on exponential disturbances, coupled with temporal heteroscedasticity, which captures more complex patterns in the demand process. We examine the conditions under which information sharing is valuable.
  • Thumbnail Image
    ItemOpen Access
    ESSAYS ON SUSTAINABLE SUPPLY CHAIN, GROUP DECISION MAKING AND EXPERT-AUGMENTED FEATURE SELECTION
    (University of Oregon, 2022-10-04) Rabiee, Meysam; Pangburn, Michael
    My dissertation consists of an essay in sustainable supply chain management, an essay in group decision making, and an essay in expert-augmented feature selection. My first essay is an unpublished work co-authored with Prof. Nagesh Murthy and Dr. Hossein Rikhtehgar Berenji. In some supply chains, it is extraordinarily expensive for a buyer to audit all selected suppliers to guarantee compliance with the buyer's code of conduct for social and environmental responsibility. In this work, we provide insight to help such a buyer profit from judicious audits, despite the risk of revenue loss due to non-compliance. My second essay is co-authored with Babak Aslani and Dr. Jafar Rezaei; it has been published. The purpose of this article is to investigate the detection and handling of biased decision-makers in group decision-making processes. To address this issue, we developed three algorithms including extreme, moderate, and soft versions. The third essay is an unpublished work co-authored with Mohsen Mirhashemi, Prof. Michael Pangburn, Prof. Dursun Delen, and Dr. Saeed Piri. In this study, we enrich the conventional feature-selection method by incorporating the opinions of experts on the features, a technique we refer to as expert-augmented feature selection. To reflect the trade-off between explainability and prediction accuracy, we develop two very similar models: one for classification problems, and one for regression problems. Finally, we develop a posterior ensemble approach for quantifying each feature's accuracy-contribution degree. This algorithm's output helps us to discover features that are consistently rated, under-rated, or over-rated by experts.
  • Thumbnail Image
    ItemOpen Access
    How Can Buyers Engage Suppliers to Be More Socially and Environmentally Responsible?
    (University of Oregon, 2019-09-18) Rikhtehgar Berenji, Hossein; Murthy, Nagesh
    A major concern for buyers in a given tier of the supply chain continues to be the challenge of balancing the economic benefits of outsourcing with the loss in their ability to control and influence sustainability performance of their suppliers. The overarching question in this dissertation is how buyers can engage suppliers to improve social and environmental performance of the supply chain. A combination of analytical and empirical models are developed and analyzed to offer a buyer guidance at strategic (i.e., managing trust in buyer-supplier relationships) and tactical (i.e., designing suitable contracting mechanisms) levels on how to make suppliers more socially and environmentally responsible. In the first essay, we consider a buyer who enjoys the pricing power and also has the ability to commit to contract terms. We investigate how such a buyer's commitment to contract terms affects the sustainability and financial performance of the supply chain. The second essay focuses on understanding the impact of supplier competition on the buyer's ability to influence suppliers' compliance when suppliers have more parity in contracting power. Unlike the first essay, wherein the buyer stipulates both price and quantity, this essay considers situations wherein the supplier offers a wholesale price and the buyer is limited to only offering the quantity in a wholesale contract. In the third essay, we propose a framework to investigate the role of specific nature of trust (i.e., calculative and relational trust) between buyers and suppliers in influencing the impact of their supplier relationship management strategies on suppliers' sustainability performance. This dissertation includes previously unpublished co-authored material.
  • Thumbnail Image
    ItemOpen Access
    Patient-Centric Innovation in Service Modalities for End-Stage Renal Disease
    (University of Oregon, 2021-11-23) Jabbari, Mona; Murthy, Nagesh
    The purpose of this study is to examine the feasibility of introducing innovative dialysis delivery methods. In the first essay, advised by Prof. Nagesh Murthy and Dr. Eren Cil, we study a new and non-traditional dialysis service modality, called a mobile dialysis clinic, that can reduce the travel burden for ESRD patients, resulting in a reduction in hospitalization costs undertaken by Medicare.To this end, we develop a framework to consider the strategic interaction between Medicare and a dialysis service provider and examine the potential benefit to Medicare for considering a “shared-savings payment policy.” Specifically, our proposed incentive payment structure features “reward rate” as the percentage of hospitalization cost savings that the provider receives as a bonus payment for offering coverage using a mobile dialysis clinic. We first establish that the provider undertakes the additional costs of a new modality only when the reward rate offered by Medicare exceeds a critical level. We, then, show that once offering the new modality becomes viable, the provider serves more patients with the new modality and consequently decreases the hospitalization costs for Medicare as the reward rate increases. Despite the favorable effects of the new modality on the total hospitalization costs, Medicare faces a trade-off between lowering the hospitalization cost and the sharing cost savings with the provider. Hence, we find that Medicare does not always optimally offer enough compensation to the provider to justify offering the new service modality. However, we also identify certain conditions under which Medicare, interestingly, finds it optimal to increase the reward rate to incentivize the provider to offer a mobile clinic even when this increased reward rate results in a drastic improvement in provider’s profit with only a marginal reduction in Medicare’s cost. We discuss the prospect of offering assisted home dialysis in the second essay to overcome the barriers to home dialysis. The second essay is advised by Prof. Nagesh Murthy and Dr. Eren Cil. Assisted home dialysis can be provided in-home or via telemedicine by a nurse. We develop a mathematical model to examine the implications of an optimal integration of new modalities, i.e., satellite clinics and nurse assisted home-dialysis into the existing dialysis network on the provider's profit and Medicare's costs. We analyze these implications under a variety of scenarios that reflect geographic dispersion of patients from the existing main clinic, patient preferences, and hospitalization cost attributed to recurring distance traveled. Our findings can help policymakers for Medicare design new policies that motivate providers to introduce new and innovative ways of offering dialysis to patients.