品牌品类扩张边界的经济分析:基于选择成本分析范式

基于选择成本分析范式,通过引入品类相似系数这一新概念,构建数理模型,分析品类扩张的内在机制。结果表明,品类数量的增加将有利于品牌需求量的提高,但由于消费者选择成本的存在,品类数量的进一步增加将会降低品牌信用度,造成选择成本的增加,从而抑制需求量的扩大,最终品类数量和品牌需求量将会趋向于均衡状态,存在品牌品类扩张的边界。     

Category management and consumer choice

This paper shows the results of an exploratory analysis of the structure of a complex product category: Wine. In complex categories, a usual strategy of consumers is the partitioning of alternatives into homogeneous subsets and the sequential eliminations of subsets until a product/brand is chosen from among few homogeneous alternatives in the last subset. To identify if there is such a kind of strategy and the product attributes involved is of great interest for the retailer. After a discussion of the different modelling alternatives of the choice process, the authors provide an application of the additive trees (ADDTREE) model to explore the hierarchical structure. The ADDTREE results provide a first overview of the competitive market structure of the wine category: competition becomes more intense as the wine category is partitioned by, first, the type of wine criteria and, second, the designation of origin (DO) criteria.     

Recent Progress on Endogeneity in Choice Modeling

We describe recent progress in several areas related to endogeneity, including: choice set formation and attention to attributes; interactions among decision-makers; respondents' strategic behavior in answering stated preference choices; models of multiple discrete/continuous choice; distributions of willingness-to-pay; and methods for handling traditionally endogenous explanatory variables.     

A Micromodel of New Product Adoption with Heterogeneous and Forward-Looking Consumers: Application to the Digital Camera Category

We develop an empirical model for the adoption process of a new durable product that accounts for consumer heterogeneity as well as consumers forward-looking behavior. Accounting for heterogeneity is important for two reasons. As the mix of consumers with different preferences and price sensitivities could change over time, firms need to update their marketing strategies. Further, it allows for a variety of shapes for the aggregate adoption process over time. As prices for durable and technology products fall over time with firms continually introducing enhanced products, consumers may anticipate these prices and improvements and delay their purchases in the product category. Forward-looking consumers optimize purchase timing by trading off their utilities from buying the product and their expectations on future prices, quality levels, and brand availability. Such forward-looking behavior will result in price dynamics in the marketplace as price changes today influence future purchases. And it results in different shapes of the new product sales pattern over time by influencing the time to take-off. We show how the parameters of our model can be estimated using aggregate data on the sales, prices, and attributes of brands in a product category. We apply our model to market data from the digital camera category. Our data are consistent with the presence of both heterogeneity and forward looking behavior among consumers. At the product category level, we are able to decompose the effects of the entry of Sony into primary demand expansion and switching from other brands. At the brand level, we find that there exist several segments in the market with different preferences for the brands and different price sensitivities leading to differences in adoption timing and brand choice across segments. For a given brand, we show how the changing customer mix over time has implications for that brands pricing strategies. We characterize how price effects vary across brands and over time and how price changes in a given time period influence sales in subsequent periods. Model comparison and validation results are also provided.     

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.     

Dynamic Influences on Individual Choice Behavior

Research examining the process of individual decision making over time isbriefly reviewed. We focus on two major areas of work in choice dynamics:research that has examined how current choices are influenced by the historyof previous choices, and newer work examining how choices may be made toexploit expectations about options available in the future. A central themeof the survey is that if a general understanding of choice dynamics is toemerge, it will come through the development of boundedly-rational models ofdynamic problem solving that lie on the interface between economics andpsychology.     

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     

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.     

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.     

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。     

产品类别视角企业微博互动内容策略的差异性研究

本文基于产品的实用性和享乐性分类视角,按照内容将企业微博互动策略分为社会性和任务导向型两种类型,并以此为依据对企业微博互动策略进行内容分析,探究不同产品类别的企业微博互动策略效果。研究表明,实用性产品和享乐性产品在企业微博互动内容策略及效果上存在差异,以此为企业有效开展微博营销提供理论依据与实践参考。     

A Note on Quality Choice,Monopoly, and Network Externality

Introducing network externalities into a model of vertically differentiated products, Lambertini and Orsini (2001, 2003) analyze the implications of a monopolist’s quality choice for social optimum. Moreover, they examine how the network externality affects quality, quantity, price, and social surplus. In this note, by looking at the nature of cost functions and the degree of network externalities, we reconsider their results, at least some of which depend upon the specificity of the cost functions.      

Choice Based on Goals

This article introduces a goal-based view of consumer choice in which (1) choice is influenced by three classes of goals (consumption goals, criterion goals, and process goals), (2) goals are cognitively represented, and (3) the impact of a goal on choice depends on its activation. For each class of goals, we discuss how goal activation is influenced by direct (subconscious) goal priming, by spreading activation from choice options, from other goals, and from the context, and by goal (non-)achievement. Opportunities for modeling goal-based choice, the integration of emotions in a theory of goal-based choice, and relationships with dual-process theories of decision making are discussed. An expanded version of this paper is available from the first author.     

A New Look at Constructed Choice Processes

Normative models of choice assert axiomatically that preferences are consistent, coherent, and determined only by relevant alternatives. In contrast to this classical economic perspective, behavioral models derived from research in psychology and consumer behavior assert that preferences are not guided by an internal, stable utility function but are constructed during the choice process. The current paper is based on a session on constructed choice processes (CCP) at the 2004 Choice Symposium that focused on how the standard CCP model can be enriched by bringing theories and tools from modern research in social cognition to bear on choice phenomenon. The richer conceptual framework presented by new, currently unpublished empirical work provides a novel perspective on choice construction by integrating the roles of subjective construal, experiential information, attribution, goals, and satisfaction in understanding preference construction processes in choice.     

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.     

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.     

发展甘肃特色农产品的战略选择

甘肃省是农业大省,有特色农业资源,但农业资源"优"而无"势"、特色产品"特"而不"强"的状况较为普遍。针对特色农产品发展过程存在的诸多问题,笔者认为,"强化特色、延伸优势、创新市场"是新形势下发展甘肃特色农产品的战略选择。     

An Analysis of Assortment Choice in Grocery Retailing

Consumers in grocery retailing commonly buy bundles of products to accommodate current and future consumption. When all products in a particular bundle share common attributes (and are selected from the same product category), the consumer is said to assemble an assortment. This research examines the impact of assortment variety on the assortment choice process. In particular, we test the prediction that consumers demand less variety for higher quality items. To investigate this relationship, we employ a flexible choice model, suitable for the analysis of assortment choice. The model, based upon the assumption that the utility of purchase of one item in an assortment depends upon the set of items already selected, allows for a general utility structure across the assortment items. We apply the model to household assortment choice histories from the yogurt product category. Substantively, we show that yogurt choice is affected by brand quality perceptions (quality-tier competition). Moreover, we show that reaction to reductions in variety (number of yogurt flavors) is mediated by brand quality perceptions. Taken together, these empirical facts paint a picture of a consumer who is willing to trade-off variety against product quality in assortment choice.     

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     

Effects of product-specific word-of-mouth communication on product category involvement

Drawing primarily from categorization theory, this paper presents justification for the effects of word-of-mouth (WOM) communication on product category involvement. Results of an empirical test of this relationship are presented showing an enduring effect of positive WOM communication on product category involvement; this effect was not found for negative WOM. These results suggest that positive WOM about one firm's brand may help competitors by increasing involvement, thus generating more sales (not necessarily of one's own brand) in an entire product category. Our findings, coupled with categorization theory, provide support for a series of propositions presented concerning the effects of changes in product category involvement on nondiscussed brand attitudes and purchase intentions.