Information Processing Pattern and Propensity to Buy: An Investigation of Online Point-of-Purchase Behavior

Abstract

T he information processing literature provides a wealth of laboratory evidence on the effects that the choice task and individual characteristics have on the extent to which consumers engage in alternative-based versus attribute-based information processing. Less attention has been paid to studying how the processing pattern at the point of purchase is associated with a consumer's propensity to buy in shopping settings. To understand this relationship, we formulate a discrete choice model and perform formal model comparisons to distinguish among several possible dependence structures. We consider models involving an existing measure of information processing, PATTERN; a latent variable version of this measure; and several new refinements and generalizations. Analysis of a unique data set of 895 shoppers on a popular electronics website supports the latent variable specification and provides validation for several hypotheses and modeling components. We find a positive relationship between alternative-based processing and purchase, as well as a tendency of shoppers in the lower price category to engage in alternative-based processing. The results also support the case for joint modeling and estimation. These findings can be useful for future work in information processing and suggest that likely buyers can be identified while engaged in information processing prior to purchase commitment, an important first step in targeting decisions.

Exploring the moderating role of construal levels on the impact of process vs outcome attributes on service evaluations

“…Customers’ ability to process information, and to harness cognitive resources can be influenced by the extent of prior experience and familiarity with the given situation or decision-making context (Brooks et al , 2015; Danziger et al , 2012; Nam et al , 2012; Reyt et al , 2016). This effect of expertise could be attributed, in part, to different types of information processing (Mintz et al , 2013), attention paid to information while making comparisons and other decision outcomes. Nam et al (2012) showed that customers with higher product knowledge are more sensitive to identification of the non-alignable differences between the choices.…”

A Model for Inferring Market Preferences from Online Retail Product Information Matrices

“…Other research on the same dataset employed for the current study highlights the differences in methodology and the contribution of this research. Mintz, Currim, and Jeliazkov (2013) use a process framework and categorize the degree to which each shopper uses an overall pattern of "attribute" or "alternative" based information acquisition. Mintz, Currim, and Jeliazkov (2013) relate the "pattern" of information acquisition to whether consumers' buy or don't buy one of the products.…”

“…Mintz, Currim, and Jeliazkov (2013) use a process framework and categorize the degree to which each shopper uses an overall pattern of "attribute" or "alternative" based information acquisition. Mintz, Currim, and Jeliazkov (2013) relate the "pattern" of information acquisition to whether consumers' buy or don't buy one of the products. By comparison, the model primitives in this research are shoppers' preferences and expected level and range of attribute levels, which are revealed in each step of the information acquisition process.…”

“…By comparison, the model primitives in this research are shoppers' preferences and expected level and range of attribute levels, which are revealed in each step of the information acquisition process. While Mintz, Currim, and Jeliazkov (2013) reduce the process to a descriptive scalar measure (e.g. degree of attribute based processing) and does not provide attribute importance weights, this research proposes a cost-benefit/behavioral structure used to infer preferences and market expectations.…”

“…In contrast, the method proposed in this research overcomes the endogeneity bias by jointly modeling information acquisition and product choice. In summary, neither Mintz, Currim, and Jeliazkov (2013) nor Currim, Mintz, and Siddarth (2015) consider the full range of decisions made by shoppers at the point of purchase and consequently do not provide useful measures of attribute importance.…”