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A Bounded Rationality Model of Information Search and Choice in Preference Measurement

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  • Yang , Cathy
  • Toubia, Olivier

Abstract

It is becoming increasingly easier for researchers and practitioners to collect eye tracking data during online preference measurement tasks. The authors develop a dynamic discrete choice model of information search and choice under bounded rationality, that they calibrate using a combination of eye-tracking and choice data. Their model extends the directed cognition model of Gabaix et al. (2006) by capturing fatigue, proximity effects, and imperfect memory encoding and by estimating individual-level parameters and partworths within a likelihood-based, hierarchical Bayesian framework. The authors show that modeling eye movements as the outcome of forward-looking utility maximization improves out-of-sample predictions, enables researchers and practitioners to use shorter questionnaires, and allows better discrimination between attributes.

Suggested Citation

  • Yang , Cathy & Toubia, Olivier, 2014. "A Bounded Rationality Model of Information Search and Choice in Preference Measurement," HEC Research Papers Series 1072, HEC Paris.
    • Handle: RePEc:ebg:heccah:1072
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    Keywords

    Preference Measurement; Incentive Compatibility; Eye Tracking; Dynamic Discrete Choice Models;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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