Efficient choice set designs for estimating availability cross-effects models

Batsell and Polking proposed a discrete choice model which incorporates the availability (presence or absence) of competing brands into the utility of each brand under study. The information on relative impacts of adding or deleting brands is of strategic interest, and models that do not incorporate such effects may be misleading. The designs suggested by Batsell and Polking have 2^m–m–1 choice sets. Even with as few as 10=m brands, this requires over 1000 choice sets. In this paper we provide a catalog of designs for estimating cross effects models in as few as 2m–1 choice sets. This will make cross effects modelling practical in a wide range of academic and commercial settings.     

Modeling preference evolution in discrete choice models: A Bayesian state-space approach

We develop discrete choice models that account for parameter driven preference dynamics. Choice model parameters may change over time because of shifting market conditions or due to changes in attribute levels over time or because of consumer learning. In this paper we show how such preference evolution can be modeled using hierarchial Bayesian state space models of discrete choice. The main feature of our approach is that it allows for the simultaneous incorporation of multiple sources of preference and choice dynamics. We show how the state space approach can include state dependence, unobserved heterogeneity, and more importantly, temporal variability in preferences using a correlated sequence of population distributions. The proposed model is very general and nests commonly used choice models in the literature as special cases. We use Markov chain monte carlo methods for estimating model parameters and apply our methodology to a scanner data set containing household brand choices over an eight-year period. Our analysis indicates that preferences exhibit significant variation over the time-span of the data and that incorporating time-variation in parameters is crucial for appropriate inferences regarding the magnitude and evolution of choice elasticities. We also find that models that ignore time variation in parameters can yield misleading inferences about the impact of causal variables. This paper is based on the first author's doctoral dissertation.     

Incorporating choice dynamics in models of consumer behavior

This paper presents a framework for organizing and discussing factors influencing consumer choice dynamics, how these factors may be incorporated into models of buyer behavior and problems that may arise in estimating such models. The paper identifies research issues and delineates possible approaches. Proceedings of Session on Choice Dynamics at the Banff Symposium on Consumer Decision-Making and Choice Behavior. All authors share equally in content and remaining errors.     

Heterogeneity distributions of willingness-to-pay in choice models

We investigate direct and indirect specification of the distribution of consumer willingness-to-pay (WTP) for changes in product attributes in a choice setting. Typically, choice models identify WTP for an attribute as a ratio of the estimated attribute and price coefficients. Previous research in marketing and economics has discussed the problems with allowing for random coefficients on both attribute and price, especially when the distribution of the price coefficient has mass near zero. These problems can be avoided by combining a parameterization of the likelihood function that directly identifies WTP with a normal prior for WTP. We show that the typical likelihood parameterization in combination with what are regarded as standard heterogeneity distributions for attribute and price coefficients results in poorly behaved posterior WTP distributions, especially in small sample settings. The implied prior for WTP readily allows for substantial mass in the tails of the distribution and extreme individual-level estimates of WTP. We also demonstrate the sensitivity of profit maximizing prices to parameterization and priors for WTP.

Estimation bias in choice models with last choice feedback

The study compares two estimation methods for choice models with last choice feedback, using simulated and real data. The first method ignores the impact of unobserved heterogeneity on observed choices via presample choices, while the second method approximates this impact by a stochastic relationship. In panels with less than 10 choices per panelist, the first method overstates the impact of last choice on current choice and understates the impact of intrinsic preferences (i.e., brand intercepts). The second method performs significantly better than the first method. Under both methods, an increase in the number of heterogeneous coefficients in the model tends to increase the bias in the estimates. The largest bias occurs when lagged choice coefficients are heterogeneous.     

基2DFT的最快速算法

本文提出一种FFT新算法,其计算量不大于现有的各种基2DFT算法.然后,与Winograd小DFT(4,8,16点)结合使用,得出一种计算DFT的最快速算法.     

Consideration set influences on consumer decision-making and choice: Issues,models, and suggestions

This paper affords a stylized view of individual consumer choice decision-making appropriate to the study of many marketing decisions. It summarizes issues relating to consideration set effects on consumer judgment and choice. It discusses whether consideration sets really exist and, if so, the factors that affect their composition, structure, and role in decision-making. It examines some new developments in the measurement and modeling of consideration set effects on decision-making. The paper concludes with suggestions for needed research. The authors wish to acknowledge the numerous ideas and perspectives contributed by the other members of the Banff Symposium workshop:Mukesh Bhargava (University of Alberta),Bill Black (Louisiana State University),Gary Gaeth (University of Iowa),Hotaka Katahira (University of Tokyo, Japan),Gilles Laurent (Centre HEC-ISA, France),Irwin Levin (University of Iowa),David Midgley (Australian Graduate School of Management),Thomas Novak (Southern Methodist University), andJames Wiley (University of Alberta). This paper has benefited greatly from their contributions.     

Modeling the effects of including/excluding attributes in choice experiments on systematic and random components

This paper examines the impact of attribute presence/absence in choice experiments using covariance heterogeneity models and random coefficient models. Results show that attribute presence/absence impacts both mean utility (systematic components) and choice variability (random components). Biased mean effects can occur by not accounting for choice variability. Further, even if one accounts for choice variability, attribute effects can differ because of attribute presence/absence. Managers who use choice experiments to study product changes or new variants should be cautious about excluding potentially essential attributes. Although including more relevant attributes increases choice variability, it also reduces bias.     

Prospects and problems in modeling group decisions

This paper summarizes some of the major issues related to group decision modeling. We briefly review the existing work on group choice models in marketing and consumer research. We draw some generalizations about which models work well when and use those generalizations to provide guidelines for future research.     

Means matter, but variance matter too: Decomposing response latency influences on variance heterogeneity in stated preference experiments

Response time latencies have been shown to influence consumer’s choice behaviour in choice-based-conjoint studies. The literature has shown that response time latencies affect the mean outputs of parameter estimates derived from models of discrete choice. In this paper, we add further insight into the influences response time latencies have on such models by modelling latent response information associated with the variance of random parameter distributions through parameterisation of variance heterogeneity (or heteroskedasticity). We demonstrate that response time latencies influence not only the means of random parameter distributions, but also the variances, and that failure to account for both may result in incorrect model inferences being drawn.     

Trade,money and employment in intertemporal optimizing models of growth

This paper unites elements of Sidrauski's (1967) monetary model of growth, Ventura's (1997) analysis of the effects of international trade on growth, and some work on the labour market implications of growth by Barro and Sala-i-Martin (1995). It was shown by Ventura that, for a small economy, free international trade leads to an increase of the de facto elasticity of substitution between the domestic factors of production. The first part of the paper analyses how such an increase in the elasticity of substitution influences the steady state and the speed of convergence. From the Sidrauski model we know that money is super-neutral in the long-run but that monetary policy can have real effects along the transition path as long as the intertemporal elasticity of substitution is not equal to one. In the second part of this paper, it is shown how these results also depend on the elasticity of substitution between factors of production. The results give some important insights into possible interactions between monetary and trade policy in the long and short run. The last part of the paper deals with a modified version of the monetary growth model, which includes endogenous labour supply as in Klump (1993) or Barro and Sala-i-Martin (1995). In this context, international trade, by increasing the elasticity of substitution, leads to lower domestic employment in the long run whereas monetary policy may be able to increase employment at least in the short run. Thus, under certain circumstances, trade and monetary policy can be regarded as complementary with respect to their labour market effects.     

Social distancing and store choice in times of a pandemic

Public health officials enforced several measures to contain the COVID-19 pandemic that affected grocery stores, such as limits on store capacities and enforcement of masks and physical distancing among customers. Nevertheless, these measures can provoke queues, which could drive customers away from stores. In this study, we investigate how customers trade off between social distancing measures and increased waiting times during the peak of the COVID-19 pandemic. Our data comes from an online survey applied in New York City in May 2020. This survey included a set of discrete choice experiments framed in virtual stores, as well as a set of psychometric indicators regarding the pandemic. With this data, we estimated a latent class conditional logit model where assignment to classes is correlated with COVID-19 latent variables. We identified three latent classes with preference structures that valued social distancing to varying degrees. In spite of this heterogeneity in preferences, we found that customers were willing to wait longer to access stores with better social distancing measures. This result suggests that stores could increase, rather than decrease, their sales if they enforce public health measures at the expense of longer waiting times.     

Determinants of retail bank choice in Nigeria: a focus on gender-based choice decisions

As the Nigerian retail banks customers become more sophisticated, it is now very important that retail banks determine the factors that are important and relevant to the customers’ retail bank choice decisions. By using a survey of retail bank customers, this study evaluates the relative importance attached to retail banks’ choice criteria used by male and female customers in Nigeria. The results show that there are some differences in choice factors used by male and female customers in selecting a retail bank for patronage. The recommendation is that bank managers should take both female and male market segments into consideration when making retail bank strategic planning in order to become competitive. The findings can assist retail bank managers in refining their marketing strategies as a means of overcoming the intense competition that exists in the Nigerian banking system.     

The effects of memory set accessibility and relevance on the use of memory information during product choice

The Accessibility-Relevance framework provides a useful perspective to consider the retrieval and use of memory information during product decision making (Alba, Lynch, and Hutchinson, 1990; Lynch, Marmorstein, and Weigold, 1989). However, it considers accessibility on an individual brand basis, while actual product choice often includes information across multiple alternatives. Thus, memory set accessibility (MSA), the relative accessibility across memory brands, is introduced as a potentially important but unexplored issue within the Accessibility-Relevance research stream. This study 1) provides an explanation for how MSA may produce results which significantly expand the current Accessibility-Relevance conceptualization and 2) considers the effects of MSA and relevance on both brand processing and choice.     

Advances in random utility models report of the workshop on advances in random utility models duke invitational symposium on choice modeling behavior

In recent years, major advances have taken place in three areas of random utility modeling: (1) semiparametric estimation, (2) computational methods for multinomial probit models, and (3) computational methods for Bayesian estimation. This paper summarizes these developments and discusses their implications for practice.     

Consumer power and choice deferral: The role of anticipated regret

This paper examines the influence of social power on consumers' propensity to defer choice. Based on the notion that elevated power reduces regret anticipation—the fear of making a wrong choice—it is proposed that power influences the extent of choice deferral by reducing consumers' susceptibility to anticipated regret. Because of the regret-based mechanism, power can increase or decrease consumers' propensity to defer choice, depending upon the situational factors that are associated with anticipated regret, such as salience of regret, outcome reversibility (e.g., return policy), and locus-of-regret (postponing vs. choosing now). Using different manipulations of power, seven studies provide consistent support for the proposed effects and show that situational factors and marketing strategies can induce, turn off, or even reverse the effect of power on deferral. Theoretical contributions and managerial implications are discussed.     

Multi-stage purchase decision models: Accommodating response heterogeneity, common demand shocks, and endogeneity using disaggregate data

The most comprehensive models of purchase behavior for frequently purchased supermarket items explain households' purchase incidence decisions (whether to buy), brand choice decisions (what to buy), and purchase quantity decisions (how much to buy). In this study, we develop a three-stage purchase incidence/brand choice/purchase quantity model for household-level data in which all three stages are specified with (i) random coefficient distributions for model covariates and (ii) random effect distributions to account for unobserved factors affecting demand (known as common demand shocks), while also (iii) controlling for the effects of endogeneity on prices. Compared to current state-of-the-art models for multi-stage purchase decisions, the results show improvements in fit and forecasting accuracy when purchase behaviors are modeled with all of these components in combination. Perhaps more importantly, when common demand shocks are ignored, substantial differences in parameter estimates and diagnostic information about consumer behavior are likely (median differences in parameter estimates are 10% and 20% in two product categories), which impact managerial deliberations about price and promotion policies. Further, failure to account for common demand shocks affects the mean and variance of random coefficient distributions in unpredictable directions, which could produce results that encourage managers to pursue inappropriate and costly micro-level product marketing strategies.     

Sustainable consumption and plastic packaging: Relationships among product involvement,perceived marketplace influence and choice behavior

This study examines the relationships among human value connotations (instrumental and terminal), product involvement, perceived marketplace influence, and choice behavior in the context of sustainable consumption. Data was collected from 612 urban Indian residents who regularly consume sustainable products, e.g., non-plastic packaging bags. The study operationalizes the partial least square structural equation modeling method in consort with the covariance-based structural equation modeling. The research demonstrates the direct impact of instrumental and terminal values on product involvement and the direct influence of product involvement on perceived marketplace influence towards plastic packaging-related choice behavior. It is pertinent to focus on both instrumental and terminal connotations of human values to augment product involvement for plastic packaging. Limited studies have examined the possible relationships between two distinct yet interconnected connotations of human values on product involvement and perceived marketplace influence in the context of sustainable consumption related to plastic packaging.