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.     

Recommendation and repurchase intention thresholds: A joint heterogeneity response estimation

Recommendation and repurchase intentions are the two most important dimensions of customer loyalty. Latent satisfaction thresholds at the individual level, if obtained, can function as an additional valid and effective criterion for satisfaction ratings in determining customer loyalty. To improve the existing estimation methodology on satisfaction thresholds, this paper proposes a joint heterogeneity response model to simultaneously calibrate the individual-level recommendation and repurchase thresholds through a joint specification over the heterogeneity. It conducts a simulation study to examine the parameter recovery and model validation. This paper further applies the method to two different datasets of satisfaction surveys in the automotive industry, with the first involving owners of vehicles of a single brand, and the second involving owners of vehicles of multiple brands. The results from the two empirical studies show that the proposed model consistently outperforms the two competing models and the extant approach. In addition, the results provide different insights into enhancing customer loyalty by using a new segmentation scheme based on estimated satisfaction thresholds.     

A threshold model for respondent heterogeneity

Continuous models of respondent heterogeneity assume the existence of a response function where variables of interest are continuously related to explanatory variables. In many situations this assumption may not be true. In this paper we propose an approach of modeling respondent heterogeneity that identifies abrupt changes in the distribution of response coefficients around a threshold specification. Our model differs from traditional threshold models by introducing the threshold effect to describe across-unit behavior as opposed to within-unit behavior. We illustrate our proposed Bayesian threshold model for survey data from a large national retail bank that examines the effects of service wait times on customer satisfaction. We find evidence of a threshold effect where long in-process wait times are associated with bank branches characterized by weak associations between service quality drivers and overall perceptions of service quality. Branches with wait times below the threshold are found to have much stronger associations.     

Market segmentation with choice-based conjoint analysis

Choice-based conjoint analysis has increased in popularity in recent years among marketing practitioners. The typical practice is to estimate choice-based conjoint models at the aggregate level, given insufficient data for individual-level estimation of part-worths. We discuss a method for market segmentation with choice-based conjoint models. This method determines the number of market segments, the size of each market segment, and the values of segment-level conjoint part-worths using commonly collected conjoint choice data. A major advantage of the proposed method is that current (incomplete) data collection approaches for choice-based conjoint analysis can still be used for market segmentation without having to collect additional data. We illustrate the proposed method using commercial conjoint choice data gathered in a new concept test for a major consumer packaged goods company. We also compare the proposed method with ana priori segmentation approach based on individual choice frequencies.     

Marketing analytics using anonymized and fragmented tracking data

With the digitization of the retail industry, there is a growing abundance of event-based tracking data describing consumer behavior (e.g., online clickstreams and offline sensors tracking the movement of shoppers). However, stronger data privacy regulations and the growing privacy consciousness of consumers suggest that much of the data may increasingly only be available to retailers in an anonymized and fragmented form that does not identify individual consumers exactly. In response to the relative paucity of research on marketing analytics in retailing using anonymized and fragmented event-based (AFE) tracking data, this paper makes three interrelated contributions. First, we describe the relevance of AFE data in the future of retailing, contrasting it with other forms of aggregate and individual-level data. Second, we propose a methodology for analyzing AFE data, which allows us to approximately recover individual-level heterogeneity and derive meaningful variables from the raw data. Third, we validate the methodology using representative data collected by deploying sensor-enabled shelves in a field experiment within a store. We find that our approach to analyzing AFE data can help uncover interesting patterns of consumer behavior and could be applied across other online and offline retail settings in practice.     

Towards a brain-to-society systems model of individual choice

Canonical models of rational choice fail to account for many forms of motivated adaptive behaviors, specifically in domains such as food selections. To describe behavior in such emotion- and reward-laden scenarios, researchers have proposed dual-process models that posit competition between a slower, analytic faculty and a fast, impulsive, emotional faculty. In this paper, we examine the assumptions and limitations of these approaches to modeling motivated choice. We argue that models of this form, though intuitively attractive, are biologically implausible. We describe an approach to motivated choice based on sequential sampling process models that can form a solid theoretical bridge between what is known about brain function and environmental influences upon choice. We further suggest that the complex and dynamic relationships between biology, behavior, and environment affecting choice at the individual level must inform aggregate models of consumer choice. Models using agent-based complex systems may further provide a principled way to relate individual and aggregate consumer choices to the aggregate choices made by businesses and social institutions. We coin the term “brain-to-society systems” choice model for this broad integrative approach.     

Enhancing marketing with engineering: Optimal product line design for heterogeneous markets

Successful product line design and development often require a balance of technical and market tradeoffs. Quantitative methods for optimizing product attribute levels using preference elicitation (e.g., conjoint) data are useful for many product types. However, products with substantial engineering content involve critical tradeoffs in the ability to achieve those desired attribute levels. Technical tradeoffs in product design must be made with an eye toward market consequences, particularly when heterogeneous market preferences make differentiation and strategic positioning critical to capturing a range of market segments and avoiding cannibalization.We present a unified methodology for product line optimization that coordinates positioning and design models to achieve realizable firm-level optima. The approach overcomes several shortcomings of prior product line optimization models by incorporating a general Bayesian account of consumer preference heterogeneity, managing attributes over a continuous domain to alleviate issues of combinatorial complexity, and avoiding solutions that are impossible to realize. The method is demonstrated for a line of dial-readout scales, using physical models and conjoint-based consumer choice data. The results show that the optimal number of products in the line is not necessarily equal to the number of market segments, that an optimal single product for a heterogeneous market differs from that for a homogeneous one, and that the representational form for consumer heterogeneity has a substantial impact on the design and profitability of the resulting optimal product line — even for the design of a single product. The method is managerially valuable because it yields product line solutions efficiently, accounting for marketing-based preference heterogeneity as well as engineering-based constraints with which product attributes can be realized.     

Duopolistic Price Competition with Captives

We extend the Bertrand duopolistic competition to include captives. These are consumers that have no choice between the suppliers. Usual population of shoppers are modeled performing a sequential search in order to decide where to buy a homogenous good. These two simple departures from the original setup have sharp consequences. First, we find that duopolistic price competition is not robust to inclusion of captives. The equilibrium results starkly differ and the only possible equilibrium now includes duopolists charging monopolistic prices. Second, addition of sequential search introduces multiplicity of pure strategy Nash equilibria. In this setup, we observe perverse optimal response to competitor's price changes. Notably, we find that the firm might want to reduce the price in response to the competitor's price increase, which is at odds with the usual undercutting principle. Third, we investigate the behavior of equilibrium prices depending on the heterogeneity in consumer risk attitudes. We find that the higher consumer heterogeneity with respect to acceptance of risky gambles leads to higher prices in equilibrium.     

Beyond the world of packaged goods: assessing the relevance of integrated marketing communications for retail and consumer service marketing

Product and packaged goods marketers have responded to changing consumer and media environments by adopting integrated approaches to marketing communication. The value and utility of such approaches likely extend to a wide range of marketers, but there have been few published attempts to examine the viability of the integrated marketing communication concept in retail and service marketing. This study addresses this void by using a seven-stage model of integrated marketing communications to examine the media and message delivery practices of national and regional retailers and consumer service marketers. The results of a national mail survey found many of these marketers using such key integrated marketing communication elements as multiple media, databases, individual-level consumer information and behavioural response measures in their media and message delivery practices. Few, however, were using these elements in a strategic or coordinated fashion. Integrated approaches thus appear to have much value in retail and service marketing, particularly as a means for coordinating media and message delivery elements in a fashion that provides a way to link behavioural responses to media vehicles and advertising messages.     

How to generalize from a hierarchical model?

Models of consumer heterogeneity play a pivotal role in marketing and economics, specifically in random coefficient or mixed logit models for aggregate or individual data and in hierarchical Bayesian models of heterogeneity. In applications, the inferential target often pertains to a population beyond the sample of consumers providing the data. For example, optimal prices inferred from the model are expected to be optimal in the population and not just optimal in the observed, finite sample. The population model, random coefficients distribution, or heterogeneity distribution is the natural and correct basis for generalizations from the observed sample to the market. However, in many if not most applications standard heterogeneity models such as the multivariate normal, or its finite mixture generalization lack economic rationality because they support regions of the parameter space that contradict basic economic arguments. For example, such population distributions support positive price coefficients or preferences against fuel-efficiency in cars. Likely as a consequence, it is common practice in applied research to rely on the collection of individual level mean estimates of consumers as a representation of population preferences that often substantially reduce the support for parameters in violation of economic expectations. To overcome the choice between relying on a mis-specified heterogeneity distribution and the collection of individual level means that fail to measure heterogeneity consistently, we develop an approach that facilitates the formulation of more economically faithful heterogeneity distributions based on prior constraints. In the common situation where the heterogeneity distribution comprises both constrained and unconstrained coefficients (e.g., brand and price coefficients), the choice of subjective prior parameters is an unresolved challenge. As a solution to this problem, we propose a marginal-conditional decomposition that avoids the conflict between wanting to be more informative about constrained parameters and only weakly informative about unconstrained parameters. We show how to efficiently sample from the implied posterior and illustrate the merits of our prior as well as the drawbacks of relying on means of individual level preferences for decision-making in two illustrative case studies.

     

The Energy Paradox Revisited: Analyzing the Role of Individual Differences and Framing Effects in Information Perception

In the ongoing debate about the “energy paradox”, a recent stream of literature highlights the importance of behavioural anomalies such as bounded rationality and self-control problems. However, the role of individual-level factors in explaining the energy paradox is still not fully understood. Combining literature on behavioural anomalies and consumer heterogeneity, the current paper analyses how individual differences influence the perception of energy-related information and susceptibility to choice-framing effects. A choice-based conjoint experiment about energy-saving home improvements was conducted with 363 homeowners in Switzerland. Results show that numeracy and energy literacy have no influence on how much attention individuals pay to energy cost savings. However, impulsivity and risk aversion are found to significantly impact homeowners’ weighting of future energy cost savings. Further, it is found that impulsive homeowners are significantly more susceptible to energy cost-framing effects. A key implication for consumer policy is that general educational programs targeted at enhancing citizens’ knowledge and cognitive abilities are unlikely to increase energy conservation investments. The findings further suggest that consumer policies and business models aimed at reducing impulsiveness and influencing risk perception might foster the uptake of energy-saving measures in the residential housing sector.     

Is consumer psychology research ready for today’s attention economy?

ABSTRACT

Attention has become an area of major interest in marketing research as a dependent or moderating variable. In this article, we argue for respondent attention as a pivotal part of any consumer psychology research protocol and highlight the risks of not incorporating realistic attention components into research design. We propose four areas where this approach can help the external validity of consumer psychology research. Our recommendations include accounting for variability in the baseline attention levels; smart use of distractions; allowing for variability in attention over the task and avoiding attention leading/assumptive questions.     

Investigating the unobserved heterogeneity in consumers’ sensitivity to the price of gasoline

We empirically examined how gasoline prices impact consumers’ shopping behaviors. Using individual panel data on gasoline transactions, we found that gasoline prices generally have a statistically and economically significant impact. However, our disaggregate analysis indicated that, across consumers, considerable heterogeneity was present in the underlying sensitivity to the price of gasoline and in the income effect, resulting from fluctuating gasoline prices. More interestingly, the significant effect of gasoline prices was largely driven by the consumers with large purchase volume, and consumers with the highest level of gasoline consumption remained almost perfectly insensitive to the price of gasoline. Such heterogeneity is also present in the effect of gasoline prices on grocery expenditures, and notably, consumers with the largest purchase volume were not associated with statistically significant changes in grocery expenditures. Theoretical background suggests that the financial constraints of consumers and primary vehicle use may explain about the differences in responses to gasoline prices. Results based on individual-level data allowed for a comprehensive understanding of how and how much gasoline prices affect consumer behaviors and showed that inelastic gasoline demand and the considerable income effect due to gasoline prices may not best describe the effect of gasoline prices.     

The 21st Century Approach to the Teaching of the International Accounting Course

Various approaches to the teaching of the International Accounting Course currently exist. These conventional approaches to course presentation are critically analyzed, followed by the introduction of a new approach to International Accounting education. The proposed approach utilizes a comprehensive classification of the multifarious topics constituting International Accounting, which enables a logical, sequential, and progressive presentation of the International Accounting Course material.     

A Low-Effort Recommendation System with High Accuracy

In recent studies on recommendation systems, the choice-based conjoint analysis has been suggested as a method for measuring consumer preferences. This approach achieves high recommendation accuracy and does not suffer from the start-up problem because it is also applicable for recommendations for new consumers or of new products. However, this method requires massive consumer input, which causes consumer reluctance. In a simulation study, we demonstrate the high accuracy, but also the high user’s effort for using a utility-based recommendation system using a choice-based conjoint analysis with hierarchical Bayes estimation. In order to reduce the conflict between consumer effort and recommendation accuracy, we develop a novel approach that only shows Pareto-efficient alternatives and ranks them according to the number of dominated attributes. We demonstrate that, in terms of the decision accuracy of the recommended products, the ranked Pareto-front approach performs better than a recommendation system that employs choice-based conjoint analysis. Furthermore, the consumer’s effort is kept low and comparable to that of simple systems that require little consumer input.     

Hofstede's individual-level indulgence dimension: Scale development and validation

In spite of the important role of culture in consumer behavior, there has been no study of the effects of indulgence vs. restraint, the sixth dimension of Hofstede's cultural framework, at the individual level. This is mainly because there has been no scale to measure indulgence vs. restraint at the individual level. Given that ascribing national-level cultural scores to individuals may cause an ecological fallacy, the four studies of this research conceptualize and develop a valid and reliable measure for individual-level indulgence. In study 1 (n= 290), using PCA, the items were purified to the final six items. The result of an EFA in study 2 (n=230) suggested a unidimensional six-item structure for the scale. This structure was confirmed by a CFA in study 3 (n=257). Study 3 established the reliability, convergent, discriminant, and criterion validities of the scale. In study 4 (n=219), through developing and testing the nomological network, the nomological validity of the scale was supported by showing that the impacts of individual-level indulgence on hedonic attitudes and repurchase intentions are mediated by positive post-purchase emotions and hedonic attitudes, respectively.     

Results May Vary: Overcoming Variability in Consumer Response to Advertising Music

Although listening to music seems effortless, it actually involves many separate psychological mechanisms. This article describes and extends the multimechanism framework proposed by Juslin and colleagues, highlighting how the operation of psychological mechanisms leads to two general types of variability in consumer response to advertising music. First, the risk of between‐consumer variability (individual differences) in musical response is moderate or high for most mechanisms, and it often depends on each individual's particular history of exposure to music (listening biography). Second, within‐consumer variability occurs when different mechanisms have contrasting effects, so that an individual consumer's musical response is often mixed (e.g., guilty pleasures, bittersweet feelings, pleasurable sadness). Both types of variability can negatively impact advertising objectives (message reception, recall, acceptance, brand attitudes, etc.). The article offers preliminary suggestions for how marketers can use a multimechanism approach to successfully incorporate music in commercials and reduce the risk of unanticipated consumer responses. It ends with proposals for further research.     

Consumer choice of retail shopping aids

This research investigates how consumer and product category attributes affect consumer interest in using various shopping aids. Research hypotheses were proposed based on a contingency framework of the relationship between consumer characteristics (i.e., purchase need, product knowledge, and brand preference heterogeneity) and shopping aid solutions (expanded selection, additional product information, personalization, and evaluative information). The findings demonstrated the importance of considering consumer characteristics when retailers design and provide shopping aids for consumers to facilitate purchase completion.     

Value-based pricing in competitive situations with the help of multi-product price response maps

This article introduces multi-product price response maps for various value pricing applications in competitive situations. The maps are based on the direct elicitation of individual willingness to pay (WTP) as a range for competing products; they reveal an individual's or market's choice probability for a focal product, at its own and competing products' prices. Transforming the price response into profit, revenue, or unit sold maps supports optimal pricing decisions. The maps are also useful for optimizing profit differences from the closest competitor and for portfolio pricing. Managers can use a consumer indecisiveness map, gained from the WTP range data, to devise complementary marketing measures at prices where consumer uncertainty is high. The illustration of this approach uses two empirical examples, featuring two or more competing consumer goods, and demonstrates the predictive and external validity of these proposed maps.     

Enforcement of Environmental Law by Individuals and Interest Groups: Reconceptualizing Standing

The paper argues that environmental law can learn from consumer law as far as standing is concerned. Valuable guidance can be given to both individual and collective action. Consumer law rests on a well-founded concept of a double-track procedural system of complementary individual and collective enforcement that has undergone a considerable development over the years. With special reference to the European Court of Justice decision C-321/95 P (Greenpeace International and 18 Others v. Commission) of 2 April 1998, three arguments are put forward. Firstly, environmental law may learn from consumer law by adopting the EC approach to confer direct effect to secondary law. This empowers the individual with respect to environmental as well as participatory ends. Secondly, environmental law may espouse modern approaches with respect to the standing of associations. Thirdly, theories of judicial review need to be rethought, taking into account the new conflicts that emerge from EC integration.