Sequential choice designs to estimate the heterogeneity distribution of willingness-to-pay

Two prominent approaches exist nowadays for estimating the distribution of willingness-to-pay (WTP) based on choice experiments. One is to work in the usual preference space in which the random utility model is expressed in terms of partworths. These partworths or utility coefficients are estimated together with their distribution. The WTP and the corresponding heterogeneity distribution of WTP is derived from these results. The other approach reformulates the utility in terms of WTP (called WTP-space) and estimates the WTP and the heterogeneity distribution of WTP directly. Though often used, working in preference space has severe drawbacks as it often leads to WTP-distributions with long flat tails, infinite moments and therefore many extreme values. By moving to WTP-space, authors have tried to improve the estimation of WTP and its distribution from a modeling perspective. In this paper we will further improve the estimation of individual level WTP and corresponding heterogeneity distribution by designing the choice sets more efficiently. We will generate individual sequential choice designs in WTP space. The use of this sequential approach is motivated by findings of Yu et al. (2011) who show that this approach allows for superior estimation of the utility coefficients and their distribution. The key feature of this approach is that it uses Bayesian methods to generate individually optimized choice sets sequentially based on prior information of each individual which is further updated after each choice made. Based on a simulation study in which we compare the efficiency of this sequential design procedure with several non-sequential choice designs, we can conclude that the sequential approach improves the estimation results substantially.     

Overcoming data limitations for store choice modelling.: Exploiting retail chain choice data by means of aggregate logit models

This paper reports on research aimed at exploiting certain data sources for store choice modelling purposes. Many databases, such as some consumer panels, only record the firm chosen by consumers and not the specific store at which they shop. Four alternative approaches are proposed in order to use this raw information for studying patronage determinants at store level: (a) an ordinary logit model in which chain utility is averaged across stores within; (b) an ordinary logit model in which the choice set is assumed to be composed of the nearest store for each chain; (c) a straightforward application of an aggregate logit model; and (d) the application of an aggregate logit model with choice sets spatially bounded by a distance threshold representing the maximum distance that consumers are willing to travel for shopping. The models are empirically tested in the context of spatial choice behaviour. Goodness of fit indicators reveal that only models (b), (c) and (d) acceptably represent competitive interaction dynamics. As performance of (b) is slightly better than that of (c), it seems that a priori the ‘nearest store assumption’ is a better approach than the modelling of aggregate choice structures. However, when the latter approach is applied with more reliable choice sets, as suggested in model (d), the best performance is achieved. The results thus lead us to think that the aggregate logit model is a promising methodology for solving the problem at issue, but subject to an appropriate definition of the consumers’ choice sets. In fact, such an approach provides a more suitable modelling solution to the extent that the saturation and the intra-firm store heterogeneity become more intense, because these situations presumably imply that consideration sets include several stores from the same chain.     

Generalized Reverse Discrete Choice Models

Marketing practitioners and academics have shown a keen interest in the processes that drive consumers’ choices since the early work of Guadagni and Little (1982). Over the past decade or so, a number of alternative models have been proposed, implemented and analyzed. The common behavioral assumption that underlines these models of discrete choice is random utility maximization (RUM). The RUM assumption, in its simplest form, posits that a consumer with a finite set of brands to choose from chooses the brand that gives her the maximum amount of utility. An alternative approach would be to assume that consumers choose the alternative that offers them the least disutility. Our paper proposes and tests a broad class of generalized extreme value models based on this hypothesis. We model the decision process of the consumer the assumption random disutility minimization (RDM) and derive a new class of discrete choice models based on this assumption. Our findings reveal that there are significant theoretical and econometric differences between the discrete choice models derived from a RUM framework and the RDM framework proposed in this paper. On the theoretical front we find that the class of discrete choice models based on the assumption of disutility minimization is structurally different from the models in the literature. Further, the models in this class are available in closed form and exhibit the same flexibility as the GEV models proposed by McFadden (1978). In fact, the number of parameters are identical to and have the same interpretation as those obtained via RUM based GEV models. In addition to the theoretical differences we also uncover significant empirical insights. With the computing effort and time for both models being roughly the same this new set of models offers marketing academics and researchers a viable new tool with which to investigate discrete choice behavior.JEL Classification: C25, C35, M37, D12     

The Joint identification of utility and discount functions from stated choice data: An application to durable goods adoption

We present a survey design that generalizes static conjoint experiments to elicit inter-temporal adoption decisions for durable goods. We show that consumers’ utility and discount functions in a dynamic discrete choice model are jointly identified using data generated by this specific design. In contrast, based on revealed preference data, the utility and discount functions are generally not jointly identified even if consumers’ expectations are known. The separation of current-period preferences from discounting is necessary to forecast the diffusion of a durable good under alternative marketing strategies. We illustrate the approach using two surveys eliciting Blu-ray player adoption decisions. Both model-free evidence and the estimates based on a dynamic discrete choice model indicate that consumers make forward-looking adoption decisions. In both surveys the average discount rate is 43 percent, corresponding to a substantially higher degree of impatience than the rate implied by aggregate asset returns. The estimates also reveal a large degree of heterogeneity in the discount rates across consumers, but only little evidence for hyperbolic discounting.     

消费者决策行为的吸引效应及其形成机理探析

吸引效应反映了个体决策行为中的一种非理性行为,是指一特定备择项的加入会令选择集中某一备择项变得更有吸引力,从而被选概率提高的一种现象。本文主要介绍了吸引效应的基本含义及基本策略,探讨了影响吸引效应的主要因素以及吸引效应的形成机理,并对吸引效应的未来研究方向做出了展望。     

Habit Persistence in Time Series Models of Discrete Choice

We provide a framework for modelling habit persistence in choice that integrates vector auto-regressive and moving-average (VARMA) time-series models with random coefficient Multinomial Probit (MNP) models. We provide two classes of models. In the first we assume that the error in the utility function has a general VARMA structure, and in the second we assume that structure for the regression coefficients. We provide an interpretation of these two classes of models. As an illustration, we re-analyse the A.C. Nielsen Company 1986/1987 scanner panel data on ketchup purchases and compare our model with two alternative state dependence models.     

Conjoint models of family decision making

The objective of this research is to develop viable approaches to modeling joint decisions. Using conjoint-analysis-type preference data, three methods are developed to combine individual preferences to approximate joint preferences and predict joint decisions. The first is an equal weighting model, which is a simple average of individual members' part-worth utilities. The second is a relative influence model, which combines individual utility functions using a measure of derived influence. The third is a conflict resolution model, which combines utility functions using a measure of conflict. In addition to these three combination models, individual member models and a joint model based on the joint preferences are available.The application area in which the models are operationalized is family decision making. The decision involves choice of a job by MBA students and spouses at a major private university. The models are first calibrated using preference data on hypothetical jobs from MBAs, spouses, and couples and then evaluated on their ability to predict the actual job chosen.     

The Effect of Attribute Variation on Consumer Choice Consistency

We study the effect of shifts in attribute level differences on consumer choice consistency. Choice consistency is measured as the variance of the random error component in the consumer utility function: the smaller this variance, the higher choice consistency. We hypothesize that due to increased choice difficulty, choice consistency decreases if attribute level differences increase while average utility level differences between alternatives remain the same. In our empirical illustration we focus on the impact of price level shifts on choice consistency in conjoint choice experiments. Our results show that choice consistency decreases as price level differences increase and absolute price levels increase.     

The relative impact of corporate reputation on consumer choice: beyond a halo effect

ABSTRACT

Previous work suggests that corporate reputation generates a ‘halo effect’ where products from companies with better reputations are more likely to be chosen. We argue that corporate reputation plays a more expansive role, proposing that consumers will be less price-sensitive to offerings endorsed by companies with good reputations and that it moderates the marginal utility of product features with high clarity. We also propose that an individual’s knowledge of a company increases the likelihood its products will be purchased. Using a choice model incorporating an individual SEM-based reputation measure, we find support for these hypothesised effects in the context of television choices. The results suggest that corporate reputation warrants more attention by marketing managers to increase preferences for their products through these mechanisms.     

PORTFOLIO MANAGEMENT WITH CONSTRAINTS

The traditional portfolio selection problem concerns an agent whose objective is to maximize the expected utility of terminal wealth over some horizon. This basic problem can be modified by adding constraints. In this paper we investigate the portfolio selection problem for an investor who desires to outperform some benchmark index with a certain confidence level. The benchmark is chosen to reflect some particular investment objective and it can be either deterministic or stochastic. The optimal strategy for this class of problems can lead to nonconvex constraints raising issues of existence and uniqueness. We solve this optimal portfolio selection problem and investigate the procedure for both deterministic and stochastic benchmarks.     

Towards a new way to measure power: Applying conjoint analysis to group decisions

This paper presents some preliminary development towards a methodology for measuring power in a group purchase decision. We define power as the capacity of an individual to change the probability of an alternative being chosen by expressing an opinion about that alternative. We present a linear model that relates the group members' preferences to the probability that a given alternative will be chosen. The model parameters reflect specific measures of power and can be estimated by conjoint analysis. We present the results of a pilot field study, conducted on a sample of purchasing managers, which favorably assesses certain psychometric properties of the resulting measures for dyads.     

LINKED RECURSIVE PREFERENCES AND OPTIMALITY

We study a class of optimization problems involving linked recursive preferences in a continuous‐time Brownian setting. Such links can arise when preferences depend directly on the level or volatility of wealth, in principal–agent (optimal compensation) problems with moral hazard, and when the impact of social influences on preferences is modeled via utility (and utility diffusion) externalities. We characterize the necessary first‐order conditions, which are also sufficient under additional conditions ensuring concavity. We also examine applications to optimal consumption and portfolio choice, and applications to Pareto optimal allocations.     

Location choice of academic entrepreneurs: Evidence from the US biotechnology industry

Where knowledge-based firms are located is important because entrepreneurship, firm creation and innovation are typically associated with regional economic development, wealth creation and increased employment. In this paper we examine where academic entrepreneurs locate their firms. We begin by developing a theoretical model that examines the location choice of the academic entrepreneur within the standard utility maximization theory. Academic entrepreneurs are assumed to maximize their utility by allocating their efforts between academic and entrepreneurial pursuits which, in turn, determine their future streams of income and end-period wealth. Optimal allocation turns out to be a function of both personal and external factors that condition the relevant payoffs and such factors can be empirically observed. We then use several candidate explanatory variables to examine those factors that may influence the firm location choice for 187 biopharmaceutical firms started by 275 academic entrepreneurs in the US. From our empirical analysis we find that location-specific factors such as proximity to certain knowledge assets and to the funding venture capital firms, affect the firm location choice of academic entrepreneurs. Nevertheless, entrepreneur-specific characteristics, such as their age, seem to dominate the choice of firm location.     

A model of consumer information search and online network externalities

This article looks at a consumer who faces a choice between two sources of information: conventional and online. The online source is different from the conventional one because consumers care about how many people are using it along with them. Generally, the more users the better (positive network externality), but, on the other hand, the presence of more users implies a reduction of available capacity, about which consumers also care. We assume that consumers maximize their utility, which is modeled as a function of all other consumption, knowledge, and network externalities. Knowledge is conceptualized as a function of the amount of information spent both on the online network and on conventional sources. Since consumer information searches may differ according to demographic differences, this may result in consumers’ differences in their usage of online networks and conventional sources. We include these externalities in our model to better understand consumer choice behavior for the online network. The consumer utility function is estimated by using the model estimation method developed in this article, since the interactions implied by the consumer utility function are more complex than one could hope to estimate econometrically. We use survey data to regress the demand for online information depending on income, education, the number of users, and remaining capacity. We introduce a methodology to simulate how consumers’ representative utilities will behave in different network environments and derive implications for online network suppliers.     

Tradeoffs Between Price and Quality: How a Value Index Affects

The present research examines how the availability of information about the value of a product, expressed as a ratio of the quality received per dollar, influences preference formation. This index, similar to unit price which provides information about how much quantity is received per dollar, presents consumers with information regarding the quality received per dollar. An experiment that compares consumers' preferences inferred from a choice task with their preferences inferred from a conjoint task was conducted. In the choice task consumers selected the most attractive alternative from a set of options, while in the conjoint task the attractiveness of each option was rated. Consumers, presented with an index of quality received per dollar paid (the value index), are more likely to choose a lower priced, higher value option rather than a higher priced, higher quality option compared to consumers presented with only price and quality information. Clearly, how a consumer chooses to “get the best for his or her money” depends on the ease with which information about the choices can be processed.     

Using discrete choice experiments to estimate willingness-to-pay intervals

Willingness-to-pay has always been conceptualized as a point estimate, frequently as the price that makes the consumer indifferent between buying and not buying the product. In contrast, this article estimates willingness-to-pay (WTP) as an interval based on discrete choice experiments and a scale-adjusted latent-class model. The middle value of this interval corresponds to the traditional WTP point estimate and depends on the deterministic utility; the range of the interval depends on price sensitivity and the utility??s error variance (scale). With this conceptualization of WTP, we propose a new measure, the attractiveness index, which serves to identify attractive consumers by combining knowledge about their price sensitivities and error variances. An empirical study demonstrates that the attractiveness index identifies the most attractive consumers, who do not necessarily have the largest WTP point estimates. Furthermore, consumers with comparable preferences can differ in their purchase probability by an average of 16%, as reflected in differences in their WTP intervals, which yields implications for more customized target marketing.     

University choice: which attributes matter when you are paying the full price?

This article presents the results from a longitudinal study of students' choice of university in England. Students were surveyed initially when applying for university (Wave One) and then again when they were about to embark on their chosen course (Wave Two). The results from Wave Two demonstrated a high degree of consistency with the Wave One findings: course and university reputation are far more important and fees are relatively unimportant. However, a key result across both waves was that patterns of utility for students with no parental experience of university were significantly different from students whose parents had attended university. The utility associated with different levels of entry qualifications, of fees and of university and course reputation, differed between social groups. The study suggests that the benefits of going to a highly rated university may be undervalued in families that have no direct experience of higher education. In addition, whilst females are more significantly put off by universities with low entry requirements, the qualitative attitudinal statements included in the follow‐up study seem to indicate that so‐called ‘softer’ factors may also influence their choice.     

净现值指数排序法的问题及解决方法

净现值指数排序法是解决资金预算总额有限情况下独立型方案选优问题的方法之一。但是,由于投资项目的不可分性,净现值指数排序法不能保证所选项目方案的净现值达到最大。因此,依据净现值指数排序法,对净现值指数排序法进行改进。     

Brand Equity, Consumer Learning and Choice

The aim of this paper is to explore the links between brand equity, consumer learning and consumer choice processes in general and considering two recent trends in the market place: store brands and the Internet. We first review the advances that have occurred in brand equity research in marketing in the past decade, with particular emphasis on integrating the separate streams of research emanating from cognitive psychology and information economics. Brand equity has generally been defined as the incremental utility with which a brand endows a product, compared to its non-branded counterpart. We amplify this definition: we propose that brand equity be the incremental effect of the brand on all aspects of the consumer's evaluation and choice process. We propose an agenda of research based on this amplified definition.