http://hdl.handle.net/1721.1/7728 Thu, 23 May 2013 10:11:13 GMT 2013-05-23T10:11:13Z http://hdl.handle.net/1721.1/78393 Decision systems performance: an experimental investigation of computer-aided management decision making. Marcotte, Albert Andrew Massachusetts Institute of Technology, Alfred P. Sloan School of Management. Thesis. 1974. Ph.D.; MICROFICHE COPY ALSO AVAILABLE IN DEWEY LIBRARY.; Leaves 9, 10 omitted in paging. Vita.; Bibliography: leaves [197-205]. Tue, 01 Jan 1974 00:00:00 GMT http://hdl.handle.net/1721.1/78393 1974-01-01T00:00:00Z http://hdl.handle.net/1721.1/77877 Three essays on product quality and pricing Nistor, Cristina (Cristina Daniela) This dissertation consists of three essays on product quality and pricing. Essay 1: Pricing and Quality Provision in a Channel: A Model of Efficient Relational Contracts The first essay analyzes how quality concerns affect relationships in a channel. A firm concerned about uncontractible quality for a customizable good has to pay higher prices to sustain a relationship with the supplier. If the customizable good has very volatile demand, premium payments on this good cannot be sustained. Instead, the downstream firm pays a premium for a good with more stable demand that is correlated with demand for the customizable good. I use a novel dataset containing sales made by a wholesaler to Asian restaurants in the Southeastern United States to test this prediction empirically. As predicted by the proposed model, if customizable goods have very volatile demand, the high end restaurants do not pay a premium on those goods but instead pay a premium for other goods with more stable demand. Essay 2: Third Party Marketing Approvals The second essay measures the effect of competition in a certifier market. When customers purchase new products, there is often a degree of uncertainty about their quality. A common solution is to rely on a third-party certifier to provide some form of accreditation that signals quality. However, the incentives of a third-party certifier may not be completely benign. Competitive certification markets may lead the certifiers to provide unduly positive evaluations of quality to gain market share or provide unduly negative evaluations in order to gain credibility with end-users. This paper exploits an unusual natural experiment to evaluate the extent to which third-parties can be relied upon to correctly report product quality. It focuses on the FDA's decision to allow third parties to prepare certifications for certain medical devices, and observes how this decision to introduce competition at the reviewer stage has affected the quality of products allowed to go to market. There is evidence that allowing third party certification leads to significantly lower product quality. However, experience with using a third party reviewer in the past diminishes the negative effect of reviewer competition. Essay 3: Layaway and the Quasi-Endowment Effect of Installment Payments The third essay explores the quasi-endowment effect. The paper evaluates how much consumers are willing to prepay for a purchase which will be experienced in the future. In particular, the results indicate that prepaid installment plans allow the consumer to start deriving utility for the purchase from the moment of the first payment. This quasi-endowment effect is felt only for goods that are purchased for own consumption. Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references. Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/1721.1/77877 2012-01-01T00:00:00Z http://hdl.handle.net/1721.1/77828 Resource allocation in stochastic processing networks : performance and scaling Zhong, Yuan, Ph.D. Massachusetts Institute of Technology. Operations Research Center This thesis addresses the design and analysis of resource allocation policies in largescale stochastic systems, motivated by examples such as the Internet, cloud facilities, wireless networks, etc. A canonical framework for modeling many such systems is provided by "stochastic processing networks" (SPN) (Harrison [28, 29]). In this context, the key operational challenge is efficient and timely resource allocation. We consider two important classes of SPNs: switched networks and bandwidth-sharing networks. Switched networks are constrained queueing models that have been used successfully to describe the detailed packet-level dynamics in systems such as input-queued switches and wireless networks. Bandwidth-sharing networks have primarily been used to capture the long-term behavior of the flow-level dynamics in the Internet. In this thesis, we develop novel methods to analyze the performance of existing resource allocation policies, and we design new policies that achieve provably good performance. First, we study performance properties of so-called Maximum-Weight-[alpha] (MW-[alpha]) policies in switched networks, and of a-fair policies in bandwidth-sharing networks, both of which are well-known families of resource allocation policies, parametrized by a positive parameter [alpha] > 0. We study both their transient properties as well as their steady-state behavior. In switched networks, under a MW-a policy with a 2 1, we obtain bounds on the maximum queue size over a given time horizon, by means of a maximal inequality derived from the standard Lyapunov drift condition. As a corollary, we establish the full state space collapse property when [alpha] > 1. In the steady-state regime, for any [alpha] >/= 0, we obtain explicit exponential tail bounds on the queue sizes, by relying on a norm-like Lyapunov function, different from the standard Lyapunov function used in the literature. Methods and results are largely parallel for bandwidth-sharing networks. Under an a-fair policy with [alpha] >/= 1, we obtain bounds on the maximum number of flows in the network over a given time horizon, and hence establish the full state space collapse property when [alpha] >/= 1. In the steady-state regime, using again a norm-like Lyapunov function, we obtain explicit exponential tail bounds on the number of flows, for any a > 0. As a corollary, we establish the validity of the diffusion approximation developed by Kang et al. [32], in steady state, for the case [alpha] = 1. Second, we consider the design of resource allocation policies in switched networks. At a high level, the central performance questions of interest are: what is the optimal scaling behavior of policies in large-scale systems, and how can we achieve it? More specifically, in the context of general switched networks, we provide a new class of online policies, inspired by the classical insensitivity theory for product-form queueing networks, which admits explicit performance bounds. These policies achieve optimal queue-size scaling, in the conventional heavy-traffic regime, for a class of switched networks, thus settling a conjecture (documented in [51]) on queue-size scaling in input-queued switches. In the particular context of input-queued switches, we consider the scaling behavior of queue sizes, as a function of the port number n and the load factor [rho]. In particular, we consider the special case of uniform arrival rates, and we focus on the regime where [rho] = 1 - 1/f(n), with f(n) >/= n. We provide a new class of policies under which the long-run average total queue size scales as O(n1.5 -f(n) log f(n)). As a corollary, when f(n) = n, the long-run average total queue size scales as O(n2.5 log n). This is a substantial improvement upon prior works [44], [52], [48], [39], where the same quantity scales as O(n3 ) (ignoring logarithmic dependence on n). Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 189-193). Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/1721.1/77828 2012-01-01T00:00:00Z http://hdl.handle.net/1721.1/77827 Provably near-optimal algorithms for multi-stage stochastic optimization models in operations management Shi, Cong, Ph.D. Massachusetts Institute of Technology Many if not most of the core problems studied in operations management fall into the category of multi-stage stochastic optimization models, whereby one considers multiple, often correlated decisions to optimize a particular objective function under uncertainty on the system evolution over the future horizon. Unfortunately, computing the optimal policies is usually computationally intractable due to curse of dimensionality. This thesis is focused on providing provably near-optimal and tractable policies for some of these challenging models arising in the context of inventory control, capacity planning and revenue management; specifically, on the design of approximation algorithms that admit worst-case performance guarantees. In the first chapter, we develop new algorithmic approaches to compute provably near-optimal policies for multi-period stochastic lot-sizing inventory models with positive lead times, general demand distributions and dynamic forecast updates. The proposed policies have worst-case performance guarantees of 3 and typically perform very close to optimal in extensive computational experiments. We also describe a 6-approximation algorithm for the counterpart model under uniform capacity constraints. In the second chapter, we study a class of revenue management problems in systems with reusable resources and advanced reservations. A simple control policy called the class selection policy (CSP) is proposed based on solving a knapsack-type linear program (LP). We show that the CSP and its variants perform provably near-optimal in the Halfin- Whitt regime. The analysis is based on modeling the problem as loss network systems with advanced reservations. In particular, asymptotic upper bounds on the blocking probabilities are derived. In the third chapter, we examine the problem of capacity planning in joint ventures to meet stochastic demand in a newsvendor-type setting. When resources are heterogeneous, there exists a unique revenue-sharing contract such that the corresponding Nash Bargaining Solution, the Strong Nash Equilibrium, and the system optimal solution coincide. The optimal scheme rewards every participant proportionally to her marginal cost. When resources are homogeneous, there does not exist a revenue-sharing scheme which induces the system optimum. Nonetheless, we propose provably good revenue-sharing contracts which suggests that the reward should be inversely proportional to the marginal cost of each participant. Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2012.; Cataloged from PDF version of thesis.; Includes bibliographical references (p. 157-165). Sun, 01 Jan 2012 00:00:00 GMT http://hdl.handle.net/1721.1/77827 2012-01-01T00:00:00Z