Consideration-set heuristics
Consumers often choose products by first forming a consideration set and then choosing from among considered products. When there are many products to screen (or many features to evaluate), it is rational for consumers to use consider-then-choose decision processes and to do so with heuristic decisi...
Main Authors: | , |
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Other Authors: | |
Format: | Article |
Language: | en_US |
Published: |
Elsevier
2017
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Online Access: | http://hdl.handle.net/1721.1/111102 https://orcid.org/0000-0001-8510-8640 |
Summary: | Consumers often choose products by first forming a consideration set and then choosing from among considered products. When there are many products to screen (or many features to evaluate), it is rational for consumers to use consider-then-choose decision processes and to do so with heuristic decision rules. Managerial decisions (product development, marketing communications, etc.) depend upon the ability to identify and react to consumers' heuristic consideration-set rules. We provide managerial examples and review the state-of-the-art in the theory and measurement of consumers' heuristic consideration-set rules. Advances in greedoid methods, Bayesian inference, machine-learning, incentive alignment, measurement formats, and unstructured direct elicitation make it feasible and cost-effective to understand, quantify, and simulate “what-if” scenarios for a variety of heuristics. These methods now apply to a broad set of managerial problems including applications in complex product categories with large numbers of product features and feature-levels. |
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