Complexity in Decision Making – CDM

This research examines how preference and complexity, stemming from choice differentiation, influence decision-making. Gaining insight into the measurement of these abstract qualities is pivotal for guiding product development, market analysis, and predicting industry shifts. Existing models that measure differentiation are often model-specific and lack a behavioral foundation. This study aims to: (1) Categorize existing theoretical models based on measures of differentiation, (2) Contrast these models against empirical ones to identify the implementational gap and its challenge, (3) Propose a unified theoretical framework that generalizes existing theories of measurements of preference and complexity, (4) Provide a behavioral characterization of the theoretical framework that enables empirical application, (5) Provide a numerical algorithm for implementing our novel decision-theoretic framework, and (6) Apply this framework to data to empirically quantify how product differentiation affects choice complexity in various contexts. The project will be conducted from 2024 to 2026 with collaborative researchers. The grant is essential for the successful implementation of the proposed agenda, as it will provide the necessary resources for theoretical collaboration and development, data collection, and empirical analysis. Moreover, the grant is crucial for disseminating research findings and nurturing future researchers in the field by funding research assistant positions. With the support of the grant, the proposed research project will not only contribute valuable knowledge for future studies but also offer practical implications for business planning and market analysis.