Theory-Driven Choice Models

We explore issues in theory-driven choice modeling by focusing on partial-equilibrium models of dynamic structural demand with forward-looking decision-makers, full equilibrium models that integrate the supply side, integration of bounded rationality in dynamic structural models of choice and public policy implications of these models.     

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     

HEV Choice Models as a Search Engine for the Specification of Nested Logit Tree Structures

This paper illustrates how the heteroskedastic extreme value (HEV) model can serve as an effective search engine for identifying appropriate tree structures in hierarchical choice models, particularly the nested logit. This use of the HEV model exploits its ability to estimate unique variances, and hence unique scale parameters, for each alternative in a choice set. The analysis of variance can reveal tree structures that may not be obvious to analysts who tend to base their search strategy on intuitive tree structures. The reliance on behavioural intuition may miss out on the identification of the 'best' tree in an econometric sense. This note illustrates how the HEV model is used to search for the hierarchical domain in which a statistically preferred nested logit model is positioned.     

Extended Framework for Modeling Choice Behavior

We review the case against the standard model of rational behavior and discuss the consequences of various anomalies of preference elicitation. A general theoretical framework that attempts to disentangle the various psychological elements in the decision-making process is presented. We then present a rigorous and general methodology to model the theoretical framework, explicitly incorporating psychological factors and their influences on choices. This theme has long been deemed necessary by behavioral researchers, but is often ignored in demand models. The methodology requires the estimation of an integrated multi-equation model consisting of a discrete choice model and the latent variable model system. We conclude with a research agenda to bring the theoretical framework into fruition.     

Modeling Methods for Discrete Choice Analysis

This paper introduces new forms, sampling and estimation approaches fordiscrete choice models. The new models include behavioral specifications oflatent class choice models, multinomial probit, hybrid logit, andnon-parametric methods. Recent contributions also include new specializedchoice based sample designs that permit greater efficiency in datacollection. Finally, the paper describes recent developments in the use ofsimulation methods for model estimation. These developments are designed toallow the applications of discrete choice models to a wider variety ofdiscrete choice problems.     

Role of Forgetting in Memory-Based Choice Decisions: A Structural Model

We propose a structural model to investigate the impact of forgetting on consumers' brand choice decisions in frequently purchased products. Forgetting results in consumers imperfectly recalling their prior brand evaluations when making a purchase decision in the category. We conceptualize the imperfect recall by positing that consumers recall their prior evaluations with noise. Based on prior research in the behavioral area, we characterize the extent of forgetting as an increasing and concave function of time. Our framework generates analytical results on the impact of forgetting on consumers' brand evaluations and their consequent purchase behavior. We calibrate our model using scanner panel data for liquid detergents. Furthermore, we obtain insights into the consumers' extent of forgetting in the category, extent of learning, predicted price elasticities and implications on state dependence and habit persistence. Our results underscore the importance of modeling consumers' ability to recall only imperfectly.     

选择与选择成本——品牌降低选择成本的机制分析

本文通过对选择爆炸式增长的描述,抽象出一般选择过程模型,并深入分析这一过程中所发生的成本及构成,证明品牌正是通过降低消费者的选择成本提高了选择效率,而企业外部顾客的选择效率决定了处于过剩阶段企业的内部价值的实现和内部效率的高低。本文区分了交易费用与选择成本的差别,进一步深化了对"品牌经济学"分析范式的核心范畴——选择成本的认识。     

A Cross-Validity Comparison of Conjoint Analysis and Choice Models at Different Levels of Aggregation

Several (ratings-based) conjoint analysis and experimental choice (choice-based conjoint) models are compared on their ability to predict both aggregate choice shares among the sample and individual choices in an availability validation task. While there was a weak relationship between validations at the individual and aggregate levels, several models stand out. In general, models capturing individual differences validated well at both the individual and aggregate level. The hierarchical Bayes choice and conjoint models validated particularly well.Among choice models, the hierarchical Bayes choice model had the highest aggregate and individual level-validations. It was followed by the hybrid and seven segment latent segment choice models. Overall, the highest validating ratings-based conjoint model was the hierarchical Bayes model. However, the seven segment latent segment conjoint model produced better aggregate choice share validations than any other conjoint model. These results indicate that validations can be improved either by using benefit segment models and/or merging different types of data to estimate more individualized models.In most cases, rescaling improved the ratings-based, but not the choice-based choice share validations. This suggests that one might adjust for differences between ratings and choice tasks before making choice share predictions.     

Competing Online: Studying Consumer Choice Drivers for Online Financial Services

ABSTRACT

Given the rapid increase in the consumer use of online services and the increase in competition between firms that compete online, firms are faced with a crucial challenge. Having invested significant resources in transitioning consumers from using offline services to using online services, they now need to understand what drives consumers to choose between competing online services. Our study seeks an exploratory answer to the above challenge. Specifically, we consider, “what role do factors that drive consumers into using online services play in assisting firms better compete in the online space?” This paper explores the above question by quantifying the value that consumers of an online financial service place on having access to in-depth product information, an affordable online service, an easy to use online service, access to offline capabilities, and available marketing promotions. The results reported in this paper are based on a web-based discrete choice experiment in which 2,209 consumers were asked to compare various online financial service offerings, differing from each other in terms of the relative availability of our critical factors. The results demonstrate that consumer preferences (relative utilities) for various factors of an online financial service are different. Our results enable practicing managers to understand the factors that drive consumer choice when faced with competing online services. We believe that these results have both managerial and research implications for design, management and operations strategy formulation for online services.     

Information Spillovers and the Choice of Export Destination: A Multinomial Logit Analysis of Spanish Young SMEs

Does having more firms around exporting to a particular destination improve the chances of exporting to that destination (e.g. through information spillovers)? We answer this question implementing a multinomial logit model of whether a firm exports to a particular country. To identify the source of information spillovers, we construct indicators of geographical concentration of exporters selling to a specific destination: within industry, multinationals and across industries. In our application with data for Spanish new small sized firms, only within-industry agglomeration of exporting domestic firms significantly affects the probability of small sized firms exporting to the same destination. The significance of localisation economies is robust to a barrage of controls including destination specific characteristics, gravitational factors (distance and level of development), firm heterogeneity (size) and regional differences.     

国家粮食安全：现实挑战与路径选择

尽管我国粮食生产实现了“九连增”,但粮食安全并非高枕无忧。由于工业化、城镇化不断发展和人口递增趋势未减,保障粮食安全面临着诸多挑战,粮食安全仍需要引起全社会的高度关注。从我国粮食安全面临的现实挑战入手,本文提出我国实现粮食安全的现实路径：严格保护水土资源,改善生态环境、节约资源;加强农业技术创新,提高粮食单产的技术支撑;增强政策支持,改善种粮的经济效益;粮食生产立足国内,粮食贸易多元自主发展。     

Choice and the Internet: From Clickstream to Research Stream

The authors discuss research progress and future opportunities for modeling consumer choice on the Internet using clickstream data (the electronic records of Internet usage recorded by company web servers and syndicated data services). The authors compare the nature of Internet choice (as captured by clickstream data) with supermarket choice (as captured by UPC scanner panel data), highlighting the differences relevant to choice modelers. Though the application of choice models to clickstream data is relatively new, the authors review existing early work and provide a two-by-two categorization of the applications studied to date (delineating search versus purchase on the one hand and within-site versus across-site choices on the other). The paper offers directions for further research in these areas and discusses additional opportunities afforded by clickstream information, including personalization, data mining, automation, and customer valuation. Notwithstanding the numerous challenges associated with clickstream data research, the authors conclude that the detailed nature of the information tracked about Internet usage and e-commerce transactions presents an enormous opportunity for empirical modelers to enhance the understanding and prediction of choice behavior.     

Brand and Quantity Choice Dynamics Under Price Uncertainty

We develop a model of household demand for frequently purchased consumer goods that are branded, storable and subject to stochastic price fluctuations. Our framework accounts for how inventories and expectations of future prices affect current period purchase decisions. We estimate our model using scanner data for the ketchup category. Our results indicate that price expectations and the nature of the price process have important effects on demand elasticities. Long-run cross price elasticities of demand are more than twice as great as short-run cross price elasticities. Temporary price cuts (or deals) primarily generate purchase acceleration and category expansion, rather than brand switching.     

Learning About Computers: An Analysis of Information Search and Technology Choice

We estimate a dynamic model of how consumers learn about and choose between different brands of personal computers (PCs). To estimate the model, we use a panel data set that contains the search and purchase behavior of a set of consumers who were in the market for a PC. The data includes the information sources visited each period, search durations, as well as measures of price expectations and stated attitudes toward the alternatives during the search process. Our model extends recent work on estimation of Bayesian learning models of consumer choice behavior in environments characterized by uncertainty by estimating a model of active learning—i.e., a model in which consumers make optimal sequential decisions about how much information to gather prior to making a purchase. Also, following the suggestion of Manski (2003), we use our data on price expectations to model consumers’ price expectation process, and, following the suggestion of McFadden (1989a), we incorporate the stated brand quality information into our likelihood function, rather than modeling only revealed preference data.Our analysis sheds light on how consumer forward-looking price expectations and the process of learning about quality influence the consumer choice process. A key finding is that estimates of dynamic price elasticities of demand exceed estimates that ignore the expectations effect by roughly 50%. This occurs because our estimated expectations formation process implies that consumers expect mean reversion in price changes. This enhances the impact of a temporary price cut. Finally, while our work focuses specifically on the PC market, the modeling approach we develop here may be useful for studying a wide range of high-tech, high-involvement durable goods markets where active learning is important.JEL Classification: C15, C33, C35, C42, C51, C52, D83, D84     

贸易措施的效果分析与政策取向——以关税、配额与补贴为例

关税、配额与补贴是一个国家用来保护国内市场、帮助国内厂商抵御国外对手竞争的常用措施。由于保护机制不同 ,关税、配额与补贴对不同利益主体的利益再分配会产生不同的影响 :关税措施有利于生产者和政府 ,不利于消费者 ;配额措施有利于生产者 ,不利于消费者 ,政府利益不受影响 ;补贴措施有利于生产者和消费者 ,不利于政府。一个国家可以根据其要保护的利益主体不同采取相应的保护措施     

Decision Strategy and Structure in Households: A “Groups” Perspective

From a practical perspective, (arguably) most consumer decisions are not made in isolation of the households in which consumers are inserted, yet we commonly treat them econometrically as if they were. The purpose of this workshop was to take some initial steps in defining needed research in household decision making that structurally accounts for goal sharing, utility interdependence, taste heterogeneity, choice set formation, power structures, group size and composition, and so forth. We also considered conditions under which aggregation of tastes, utility and choices might occur and make sense from both behavioral and modeling perspectives.     

Quick and easy choice sets: Constructing optimal and nearly optimal stated choice experiments

In this paper we compare a number of common strategies for constructing discrete choice experiments. Two of the strategies, including one based on theoretical constructions for optimal discrete choice experiments, produce designs that are better than those that come about from random grouping and from using the L^MA construction. A simple account of this theoretical construction is given.     

国际收支双顺差下的经济政策选择与调整

我国在加入世贸组织以后,外汇储备规模增长迅速,形成了严重的外部经济失衡。本文在指出我国国际收支双顺差的发展趋势、形成原因、利弊影响及研究方法的基础上,重点分析了缓解“双顺差”的经济政策,提出了我国未来时期外汇储备控制的思路、规模和政策选择。     

New Brands Versus Brand Extensions, Attitudes Versus Choice: Experimental Evidence for Theory and Practice

The current study compares better-fitting and worse-fitting new brand names and brand extensions on brand attitudes and choice shares across situations that differ in terms of the amount of product information available and consumer knowledge of the target product category (which had limited effects), 35[emsp4 ]mm cameras (choice-set competitors Nikon and Minolta). While brand extensions and better-fitting brands generally enjoyed more positive brand attitudes and larger choice shares, effects were moderated by product information. When information was limited to brand name and price, the better-fitting brand extension (Sony) commanded more share than did the better-fitting new brand (Optix) which in turn commanded more share than did either the worse-fitting extension (Nike) or the worse-fitting new brand (Topix). But when information on product features was added, target brands were chosen similarly across brand names where the better-fitting new brand Optix garnered slightly (non-significantly; 5%) more share than the better-fitting extension Sony. This weak preference was reversed, however, in the attitude data where Sony was rated significantly higher in liking than Optix. Two focal conclusions emerge. First, new brands can perform as well as or better than brand extensions when consumers process product information. In this study, brand-extension advantages were confined to situations of limited information processing and better fit. Second, since branding effects differed across attitudes and choice, researchers hoping to duplicate in the laboratory the types of branding effects likely to occur in the marketplace may want to expand their traditional focus on attitudes to include choice.     

集聚效应与农业外商直接投资的区位选择——基于1999-2009年中国省际面板数据分析

传统观点认为,农业因其产业链和分工较为简单等原因,相对来说并不易于形成空间集聚,因而,农业FDI的区位选择不存在集聚效应的影响。然而,本文通过统计分析和计量分析发现,农业FDI在中国的区位分布具有明显的空间集聚的特征,这种空间集聚产生的外部性利益,吸引了新进的农业FDI继续定位于这些地区。而且,随着时间的推移,由于因果循环的作用,农业FDI存量越大的地区,吸引的农业外资就会越多;而缺乏足够农业FDI存量的地区,就更加难以吸引农业外资的流入。集聚效应使得农业FDI地区分布的差距逐步扩大。