A Two-Stage Disaggregate Attribute Choice Model

Abstract

A two-stage disaggregate attribute choice model is proposed and empirically implemented. The first stage of the model is attribute processing to screen the number of alternatives down to a lesser number. The second stage is brand (alternative) processing which considers the attributes simultaneously while allowing for tradeoffs among the attributes. This two-stage approach is then applied to the same real world data set as two single stage disaggregate models, logit and Maximum-Likelihood-Hierarchical (MLH) which are state of the art models representing the alternative and attribute processing approaches, respectively. The predictive accuracy of the two-stage approach compares favorably to the single stage models. In addition, it seems to offer diagnostic information that can provide managerial insights not found in the output of the single stage model.choice modeling, hierarchical, brand choice, multistage decisions

Product Complements and Substitutes in the Real World: The Relevance of “Other Products”

“…Here, all competing products deliver requisite benefits, making them suitable for the defining purpose. Gensch (1987) and others have found evidence for buyer decision-making as at least a two-stage process in which the first stage (e.g., consideration)…”

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

“…This idea dates back to early work on information display boards (Bettman and Park 1980, Jacoby et al 1978, Payne 1976, which was subsequently picked up by modelers (Gensch 1987, Gilbride and Allenby 2004, Hauser and Wernerfelt 1990, Liu and Arora 2011. As a result, one might expect that an alternative-based processing rule might be more temporally related to purchase; i.e., alternative-based processing is the strategy that people use after they have developed some initial expertise about the choice set, either by initial attribute-based screening in early phases of the choice or by prior search.…”

Choice modelling with search and sort data from an interactive choice experiment

“…Hauser and Wernerfelt, 1990), or with respect to subsets of its attributes in a non-compensatory manner (e.g. Gensch, 1987). The later approach is plausible in many online choice environments, where search tools readily facilitate the application of heuristics such as EBA.…”