Priyali Rajagopal

Consumer Evaluations of Hybrid Products

This article examines how consumers evaluate hybrid products. Hybrid products possess features of more than one category and hence may be categorized into alternative categories. We combine two different streams of literature--traditional categorization and psycholinguistics--to demonstrate how beliefs about two different categories can be elicited for a hybrid product using a priming approach. We also find that relative category knowledge can moderate the elicitation of multiple category beliefs.

I Imagine, I Experience, I Like: The False Experience Effect

False memories refer to the mistaken belief that an event that did not occur did occur. Much of the research on false memories has focused on the antecedents to and the characteristics of such memories, with little focus on the consequences of false memories. In this research, we show that exposure to an imagery-evoking ad can result in an erroneous belief that an individual has experienced the advertised brand. We also demonstrate that such false experiential beliefs function akin to genuine product experience beliefs with regard to their consequences on product attitude strength, a finding we call the false experience effect. We further demonstrate two moderators of this effect-plausibility of past experience and evaluation timing.

Motivated Reconstruction: The Effect of Brand Commitment on False Memories.

Across 5 studies, we examine the effect of prior brand commitment on the creation of false memories about product experience after reading online product reviews. We find that brand commitment and the valence of reviews to which consumers are exposed, interact to affect the incidence of false memories. Thus, highly committed consumers are more susceptible to the creation of false experience memories on exposure to positive versus negative reviews, whereas low commitment consumers exhibit similar levels of false memories in response to both positive and negative reviews. Further, these differences across brand commitment are attenuated when respondents are primed with an accuracy motivation, suggesting that the biasing effects of commitment are likely because of the motivation to defend the committed brand. Finally, we find that differences in false memories subsequently lead to differences in intentions to spread word-of-mouth (e.g., recommend the product to friends), suggesting that the consequences of false product experience memories can be significant for marketers and consumers. Our findings contribute to the literatures in false memory and marketing by documenting a motivated bias in false memories because of brand commitment.

A New Bayesian Spatial Model for Brand Positioning

Purpose: Joint space multidimensional scaling (MDS) maps are often utilized for positioning analyses and are estimated with survey data of consumer preferences, choices, considerations, intentions, etc. so as to provide a parsimonious spatial depiction of the competitive landscape. However, little attention has been given to the possibility that consumers may show heterogeneity in their information usage (e.g. Bettman et al., 1998) and the possible impact this may have on the corresponding estimated joint space maps. This paper address this important issue and proposes a new Bayesian Multidimensional Unfolding model for the analysis of two or three-way preference data. Our new MDS model explicitly accommodates dimensional selection and preference heterogeneity simultaneously in a unified framework.Design/Methodology/Approach: This manuscript introduces a new Bayesian hierarchical spatial model with accompanying MCMC algorithm for estimation that explicitly places constraints on a set of scale parameters in such a way as to model a consumer to use or not use each latent dimension in forming their preferences, while at the same time permitting consumers to differentially weigh each utilized latent dimension. In this manner, both preference heterogeneity and dimensionality selection heterogeneity are modeled simultaneously.Findings: The superiority of our model over existing spatial models is demonstrated in both the case of simulated data, where the structure of the data are known in advance, as well as in an empirical application/illustration relating to the positioning of digital cameras. In the empirical application/illustration, the policy implications of accounting for the presence of dimensionality selection heterogeneity is shown to be derived from the Bayesian spatial analyses conducted. The results demonstrate that a model that incorporates dimensionality selection heterogeneity outperforms models that cannot recognize that consumers may be selective in the product information that they choose to process. Such results also show that a marketing manager may encounter biased parameter estimates and distorted market structures if s/he ignores such dimensionality selection heterogeneity. The proposed Bayesian spatial model provides information regarding how individual consumers utilize each dimension, and how the relationship with behavioral variables can help marketers understand the underlying reasons for selective dimensional usage. Further, the proposed approach helps a marketing manager to identify major dimension(s) that could maximize the effect of a change of brand positioning, and thus identify potential opportunities/threats that existing multidimensional scaling methods cannot provide.Originality/Value: To date, no existent spatial model utilized for brand positioning can accommodate the various forms of heterogeneity exhibited by real consumers mentioned above. The end result can be very inaccurate and biased portrayals of competitive market structure whose strategy implications may be wrong and non-optimal. Given the role of such spatial models in the classical Segmentation-Targeting-Positioning paradigm which forms the basis of all marketing strategy, the value of such research can be dramatic in many Marketing applications, as illustrated in the manuscript via analyses of both synthetic and actual data.