A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

Welfare of naive and sophisticated players in school choice

Two main school choice mechanisms have attracted the attention in the literature: Boston and deferred acceptance (DA). The question arises on the ex-ante welfareimplications when the game is played by participants that vary in terms of their strategicsophistication. Abdulkadiroglu, Che and Yasuda (2011) have shown that the chances ofnaive participants getting into a good school are higher under the Boston mechanism thanunder DA, and some naive participants are actually better off. In this note we show thatthese results can be extended to show that, under the veil of ignorance, i.e. students not yetknowing their utility values, all naive students may prefer to adopt the Boston mechanism.

The role of awareness, information gathering and processing in school choice

This paper studies the determinants of school choice, focusing on the role of information. Weconsider how parents' search efforts and their capacity to process information (i.e., tocorrectly assess schools) affect the quality of the schools they choose for their children. Usinga novel dataset, we are able to identify parents' awareness of schools in their neighborhoodand measure their capacity to rank the quality of the school with respect to the officialrankings. We find that parents education and wealth are important factors in determiningtheir level of school awareness and information gathering. Moreover, these search effortshave important consequences in terms of the quality of school choice.

Choice by sequential procedures

We propose a rule of decision-making, the sequential procedure guided byroutes, and show that three influential boundedly rational choice models can be equivalentlyunderstood as special cases of this rule. In addition, the sequential procedure guidedby routes is instrumental in showing that the three models are intimately related. We showthat choice with a status-quo bias is a refinement of rationalizability by game trees, which, inturn, is also a refinement of sequential rationalizability. Thus, we provide a sharp taxonomyof these choice models, and show that they all can be understood as choice by sequentialprocedures.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

Simple models for multi-attribute choice with many alternatives: When it does and does not pay to face tradeoffs with binary attributes

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Choice of partners in multiple two-person prisoner's dilemma games: An experimental study

We examine the effect of unilateral and mutual partner selection in the context of prisoner's dilemmas experimentally. Subjects play simultaneously several finitely repeated two-person prisoner's dilemma games. We find that unilateral choice is the best system. It leads to low defection and fewer singles than with mutual choice. Furthermore, with the unilateral choice setup we are able to show that intendingdefectors are more likely to try to avoid a match than intending cooperators. We compare our results of multiple games with single game PD-experiments and find no difference in aggregate behavior. Hence the multiple game technique is robust and might therefore be an important tool in the future for testing the use of mixed strategies.

Health care provider choice in the case of patient-initiated contacts. An extended version of discrete choice of model demand

This paper analyzes the nature of health care provider choice inthe case of patient-initiated contacts, with special reference toa National Health Service setting, where monetary prices are zeroand general practitioners act as gatekeepers to publicly financedspecialized care. We focus our attention on the factors that mayexplain the continuously increasing use of hospital emergencyvisits as opposed to other provider alternatives. An extendedversion of a discrete choice model of demand for patient-initiatedcontacts is presented, allowing for individual and town residencesize differences in perceived quality (preferences) betweenalternative providers and including travel and waiting time asnon-monetary costs. Results of a nested multinomial logit model ofprovider choice are presented. Individual choice betweenalternatives considers, in a repeated nested structure, self-care,primary care, hospital and clinic emergency services. Welfareimplications and income effects are analyzed by computingcompensating variations, and by simulating the effects of userfees by levels of income. Results indicate that compensatingvariation per visit is higher than the direct marginal cost ofemergency visits, and consequently, emergency visits do not appearas an inefficient alternative even for non-urgent conditions.

Notes on stochastic choice

A general formalism on stochastic choice is presented. Tje Rationalizability and Recoverability (Identification) problems are discussed. For the identification issue parametric examples are analyzed by means of techniques of mathematical tomography (Random transforms).

Setting the rules of the game: The choice of electoral systems in advanced democracies

The origins of electoral systems have received scant attention in the literature. Looking at the history of electoral rules in the advanced world in the last century, this paper shows that the existing wide variation in electoral rules across nations can be traced to the strategic decisions that the current ruling parties, anticipating the coordinating consequences of different electoral regimes, make to maximize their representation according to the following conditions. On the one hand, as long as the electoral arena does not change substantially and the current electoral regime serves the ruling parties well, the latter have no incentives to modify the electoral regime. On the other hand, as soon as the electoral arena changes (due to the entry of new voters or a change in their preferences), the ruling parties will entertain changing the electoral system, depending on two main conditions: the emergence of new parties and the coordinating capacities of the old ruling parties. Accordingly, if the new parties are strong, the old parties shift from plurality/majority rules to proportional representation (PR) only if the latter are locked into a 'non-Duvergerian' equilibrium; i.e. if no old party enjoys a dominant position (the case of most small European states)--conversely, they do not if a Duvergerian equilibrium exists (the case of Great Britain). Similarly, whenever the new entrants are weak, a non-PR system is maintained, regardless of the structure of the old party system (the case of the USA). The paper discusses as well the role of trade and ethnic and religious heterogeneity in the adoption of PR rules.

A dynamic choice model of hybrid behavior in the attribute-space

This paper presents a dynamic choice model in the attributespace considering rational consumers that discount the future. In lightof the evidence of several state-dependence patterns, the model isfurther extended by considering a utility function that allows for thedifferent types of behavior described in the literature: pure inertia,pure variety seeking and hybrid. The model presents a stationaryconsumption pattern that can be inertial, where the consumer only buysone product, or a variety-seeking one, where the consumer buys severalproducts simultane-ously. Under the inverted-U marginal utilityassumption, the consumer behaves inertial among the existing brands forseveral periods, and eventually, once the stationary levels areapproached, the consumer turns to a variety-seeking behavior. An empiricalanalysis is run using a scanner database for fabric softener andsignificant evidence of hybrid behavior for most attributes is found,which supports the functional form considered in the theory.

Take-the-best and other simple strategies: Why and when they work 'well' in binary choice

The effectiveness of decision rules depends on characteristics of bothrules and environments. A theoretical analysis of environments specifiesthe relative predictive accuracies of the lexicographic rule 'take-the-best'(TTB) and other simple strategies for binary choice. We identify threefactors: how the environment weights variables; characteristics of choicesets; and error. For cases involving from three to five binary cues, TTBis effective across many environments. However, hybrids of equal weights(EW) and TTB models are more effective as environments become morecompensatory. In the presence of error, TTB and similar models do not predictmuch better than a naïve model that exploits dominance. We emphasizepsychological implications and the need for more complete theories of theenvironment that include the role of error.

Cumulative dominance and heuristic performance in binary multi-attribute choice

Several studies have reported high performance of simple decision heuristics multi-attribute decision making. In this paper, we focus on situations where attributes are binary and analyze the performance of Deterministic-Elimination-By-Aspects (DEBA) and similar decision heuristics. We consider non-increasing weights and two probabilistic models for the attribute values: one where attribute values are independent Bernoulli randomvariables; the other one where they are binary random variables with inter-attribute positive correlations. Using these models, we show that good performance of DEBA is explained by the presence of cumulative as opposed to simple dominance. We therefore introduce the concepts of cumulative dominance compliance and fully cumulative dominance compliance and show that DEBA satisfies those properties. We derive a lower bound with which cumulative dominance compliant heuristics will choose a best alternative and show that, even with many attributes, this is not small. We also derive an upper bound for the expected loss of fully cumulative compliance heuristics and show that this is moderateeven when the number of attributes is large. Both bounds are independent of the values ofthe weights.

Revenue management under general discrete choice model of consumer behavior

Customer choice behavior, such as 'buy-up' and 'buy-down', is an importantphe-nomenon in a wide range of industries. Yet there are few models ormethodologies available to exploit this phenomenon within yield managementsystems. We make some progress on filling this void. Specifically, wedevelop a model of yield management in which the buyers' behavior ismodeled explicitly using a multi-nomial logit model of demand. Thecontrol problem is to decide which subset of fare classes to offer ateach point in time. The set of open fare classes then affects the purchaseprobabilities for each class. We formulate a dynamic program todetermine the optimal control policy and show that it reduces to a dynamicnested allocation policy. Thus, the optimal choice-based policy caneasily be implemented in reservation systems that use nested allocationcontrols. We also develop an estimation procedure for our model based onthe expectation-maximization (EM) method that jointly estimates arrivalrates and choice model parameters when no-purchase outcomes areunobservable. Numerical results show that this combined optimization-estimation approach may significantly improve revenue performancerelative to traditional leg-based models that do not account for choicebehavior.

Satisfaction in choice as a function of the number of alternatives: When "goods satiate" but "bads escalate"

Whereas people are typically thought to be better off with more choices, studiesshow that they often prefer to choose from small as opposed to large sets of alternatives.We propose that satisfaction from choice is an inverted U-shaped function of thenumber of alternatives. This proposition is derived theoretically by considering thebenefits and costs of different numbers of alternatives and is supported by fourexperimental studies. We also manipulate the perceptual costs of information processingand demonstrate how this affects the resulting satisfaction function. We furtherindicate that satisfaction when choosing from a given set is diminished if people aremade aware of the existence of other choice sets. The role of individual differences insatisfaction from choice is documented by noting effects due to gender and culture. Weconclude by emphasizing the need to have an explicit rationale for knowing how muchchoice is enough.