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This summary is machine-generated.

Utility maximization, a cornerstone of discrete choice modeling, faces challenges from behavioral economics. However, a random utility framework can often approximate complex behaviors, preserving the method's advantages.

Keywords:
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Area of Science:

  • Behavioral Economics
  • Discrete Choice Modeling
  • Mathematical Psychology

Background:

  • The utility maximization paradigm has dominated discrete choice modeling for over four decades.
  • Its core assumptions are increasingly questioned by behavioral economics, mathematical psychology, and choice modeling research.

Purpose of the Study:

  • To review the fundamental properties of utility maximization.
  • To explore necessary or beneficial departures from this paradigm to incorporate complex behavioral patterns.
  • To assess the applicability of existing frameworks to these richer behaviors.

Main Methods:

  • Literature review of utility maximization properties.
  • Analysis of behavioral traits discussed in economics and psychology.
  • Evaluation of the random utility framework's capacity to model diverse behaviors.

Main Results:

  • Utility maximization's historical dominance is explained by its foundational properties.
  • Many observed behavioral traits can be closely approximated within a random utility framework.
  • Departures from strict utility maximization may not always be necessary.

Conclusions:

  • The random utility framework offers a flexible approach to modeling complex human choices.
  • Analysts can retain the benefits of established discrete choice modeling techniques while accommodating a wider range of behaviors.
  • Further research may refine the random utility model for specific non-utility-maximizing behaviors.