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The Applicability of Bayesian Belief Networks for Measuring User Preferences: Some Numerical Simulations

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  • Maciej A Orzechowski
  • Theo A Arentze
  • Aloys W J Borgers
  • Harry J P Timmermans

Abstract

Bayesian belief networks offer an alternative to conventional estimation methods in estimating user preference or utility functions. Because parameter estimates are updated sequentially, this approach seems very promising in user-centred design and data collection systems. The application of such networks however poses several questions, related to speed of learning, sample heterogeneity and discretionalisation of the parameter space. This paper reports the results of a series of numerical simulations which were conducted to gain more insights into these operational decisions.

Suggested Citation

  • Maciej A Orzechowski & Theo A Arentze & Aloys W J Borgers & Harry J P Timmermans, 2008. "The Applicability of Bayesian Belief Networks for Measuring User Preferences: Some Numerical Simulations," Environment and Planning B, , vol. 35(3), pages 521-534, June.
    • Handle: RePEc:sae:envirb:v:35:y:2008:i:3:p:521-534
    DOI: 10.1068/b32054
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    References listed on IDEAS

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    1. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, November.
    2. Donggen Wang & Si-Ming Li, 2004. "Housing Preferences in a Transitional Housing System: The Case of Beijing, China," Environment and Planning A, , vol. 36(1), pages 69-87, January.
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