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Discrete Choice Simulation — Stated Preference Policy Modelling

Discrete choice simulation is a behavioural modelling method — grounded in random utility theory formalised by Daniel McFadden in the 1970s and extended to simulation-based estimation by Kenneth Train — that estimates how individuals choose among mutually exclusive alternatives and then uses those estimated preference parameters to forecast how choice shares would shift under hypothetical policy or market scenarios. It is the dominant quantitative tool in transport demand analysis, health economics, environmental valuation, and marketing research.

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Sources

  1. Train, K.E. (2009). Discrete Choice Methods with Simulation (2nd ed.). Cambridge University Press. DOI: 10.1017/CBO9780511753930
  2. Ben-Akiva, M. & Lerman, S.R. (1985). Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press. ISBN: 978-0262022170

Related methods

Referenced by

ScholarGateDiscrete Choice Simulation (Discrete Choice Simulation (Stated Preference / SP Simulation)). Retrieved 2026-06-04 from https://scholargate.app/tr/simulation/discrete-choice-simulation