Revenue management (RM) is the science of selling the right product, to the right person, at the right price. A key to the success of RM, which now spans a broad array of industries, is its grounding in mathematical modeling and analytics. This dissertation contributes to the development of new RM tools by: (1) exploring some fundamental tradeoffs underlying any RM problems, and (2) designing efficient algorithms for some RM applications. Another underlying theme of this dissertation is the modeling of customer preferences, a key component of any RM problem. The first chapters of this dissertation focus on the model selection problem: many demand models are available but picking the right model is a challenging task. In particular, we explore the tension between the richness of a model and its tractability. To quantify this tradeoff, we focus on the assortment optimization problem, a very general and core RM problem. To capture customer preferences in this context, we use choice models, a particular type of demand model. In Chapters 1, 2, 3 and 4 we design efficient algorithms for the assortment optimization problem under different choice models. By assessing the strengths and weaknesses of different choice models, we can quantify the cost in tractability one has to pay for better predictive power. This in turn leads to a better understanding of the tradeoffs underlying the model selection problem. In Chapter 5, we focus on a different question underlying any RM problem: choos- ing how to sell a given product. We illustrate this tradeoff by focusing on the problem of selling ad impressions via Internet display advertising platforms. In particular, we study how the presence of risk-averse buyers affects the desire for reservation con- tracts over real time buy via a second-price auction. In order to capture the risk aversion of buyers, we study different utility models.

This thesis aims to identify the motivating factors driving consumers home purchase decisions from the consumer's point of view. Although there is an abundance of past real estate research, dating back as far as the 1920's, the factors shaping consumers home choice have not been fully explored. Past research has tended to assume that homebuyers arrive at a decision following a logical and rational decision making process. These studies have also tended to focus on utilitarian or economic factors shaping home choice. Although past research has unquestionably added to the understanding of home purchase behaviour, the focus on utilitarian and economic factors does not explain decisions that are underpinned by deep-seated motives. The present thesis extends past research by exploring the less tangible, non-economic aspects of home choice in order to provide a fuller story of why and how people consume homes. The primary aim of this study was to investigate the unsolicited motives underlying consumers' home choices, therefore, a qualitative technique known as ZMET was employed. Based on the notion of unconscious thoughts, ZMET uses visual images gathered and/or generated by consumers to elicit and probe the metaphors that represent their thoughts and feelings. For the present study, 14 consumers who had recently placed an offer on a home took part in the ZMET interview. The present methodology extends past property research which has predominantly taken a quantitative approach. The findings of the study provide a rich insight into the motivations behind consumer home choice. Firstly, it reveals that the pre-purchase checklists used by many homebuyers and real estate agents are inaccurate representation of consumer home choice, and explains why this is so. Secondly, it demonstrates the influence of twenty four motives, including three central constructs (space, nature and views) on consumer home choice and highlights the fact that autobiographical memories underpins many of the motives to impact on choice. Thirdly, it provides a model mapping out the interaction between utilitarian and hedonic motives, which evokes a network of feelings, sensations and emotions that shape consumer home choice. In doing so, the research provides theoretical insight into the link between the rational information-processing model and the experiential view of hedonic consumption in home purchases. This study has shown that a specific set of utilitarian and deep-seated hedonic factors interrelate to culminate upon one's home choice. The findings in this study maintain that while utilitarian factors are significant determinants of home choice, in themselves, they do not always tell the whole story. This new knowledge of how and why homebuyers chose what they did is valuable to practitioners in predicting accurate property demands and value. Real estate agents can-sell more effectively by matching a property to a homebuyer's hedonic needs. The information in this study also helps homebuyers understand that their home choice is guided by internal images and deep-seated motives derived from many years of past experience but more importantly, they can decide if these motives justify the price they pay for the property. Finally, the model gives future researchers a new framework to access meanings necessary for understanding homebuyer choice and allows a closer examination of the mechanics of these influences on the housing market and its demands.

Our research proposes a new, multi-attribute, parameterisation of Tversky’s Elimination- By-Aspects (EBA) model. The EBA model conceptualises choice as a covert sequential elimination process with choice probabilities formulated over all consideration sets of the choice set. This specification attempts to capture the effect of context on choice behaviour. However, the EBA model has seen limited usage due to the large number of required parameters given the set of items under study. For a set of items T, it has 2|T| - 3 free parameters, which is infeasible for all but the simplest of contexts. To provide a practical operationalisation, we impose a set of a priori constraints on the parameter space. We define a generic multi-attribute structure to the set of aspects. This restricts the cardinality of the set of unknown scale values while retaining the functional (recursive) form of the model. The EBA hypothesis of a population of lexicographic decision-makers can therefore be tested in more market-realistic contexts, and inferences made over a large universal set of items described by the complete factorial. We call this model the Multi-attribute Elimination-By-Aspects (MEBA) model. The MEBA model reduces the set of unknown free parameters to a maximum of |T|-1. We develop a general algebraic expression for the MEBA choice probabilities as a function of the attributes of the options in the choice set. This enables the derivation of a likelihood function, and consequently maximum likelihood estimation. We also consider the form of optimal MEBA paired comparison designs. Using Monte Carlo simulation and a discrete choice experiment with consumers, we conduct an initial empirical test of the model against the special case of the MNL model (that assumes no context effects) and find the MEBA model to be a better approximation of observed choice behaviour. This is achieved on a common set of parameters, and so it is due solely to the difference in functional form of the two models. We conclude with a discussion on future research directions, in particular the introduction of heterogeneity into the model, and the description of optimal choice experiments for larger choice set sizes.

Thesis (M.S.)--University of Nevada, Reno, 2005. / "December 2005." Includes bibliographical references (leaves 27-31). Online version available on the World Wide Web.

Bibliography : leaves 93-97

Thesis (Ph. D.)--Ohio State University, 2006. / Full text release at OhioLINK's ETD Center delayed at author's request

Thesis (Ph.D.)--The Ohio State University, 1999. / Co-advisers: Marsha A. Dickson, Sharron Lennon. Includes bibliographical references.

The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Title from PDF of title page (University of Missouri--Columbia, viewed on December 18, 2009). Thesis advisor: Dr. Jung Ha-Brookshire. Includes bibliographical references.

Thesis (M.S.)--The University of North Carolina at Greensboro, 2008. / Directed by Kittichai Watchravesringkan; submitted to the Dept. of Consumer, Apparel and Retail Studies. Title from PDF t.p. (viewed Jan. 28, 2010). Includes bibliographical references (p. 108-121).

Thesis (M.S.)--West Virginia University, 2003. / Title from document title page. Document formatted into pages; contains iv, 56 p. : ill. Includes abstract. Includes bibliographical references (p. 31-32).