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Designing efficient stated choice experiments in the presence of reference alternatives

  • Rose, John M.
  • Bliemer, Michiel C.J.
  • Hensher, David A.
  • Collins, Andrew T.

This paper examines various design strategies that might be employed to construct statistically more efficient stated choice designs in the presence of a reference alternative in a choice set. Using data collected in Sydney in 2004 in the context of trading time and cost attributes associated with alternative tolled and non-tolled routes to drive a car to work, we contrast D-efficient designs (based on a number of ways of pivoting attribute levels around a reference alternative) with the more traditional orthogonal designs and conclude that D-efficiency design strategies produce significantly improved results, in a statistical sense of relative efficiency, than the more traditional orthogonal design. Furthermore, the increased use of computer aided personal survey instruments and internet-based surveys enables researchers to structure the experiments around the very specific experiences of each sampled respondent, adding relevance and comprehendability to the attribute levels being assessed in contrast to other averaging methods to construct reference alternatives.

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Article provided by Elsevier in its journal Transportation Research Part B: Methodological.

Volume (Year): 42 (2008)
Issue (Month): 4 (May)
Pages: 395-406

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Handle: RePEc:eee:transb:v:42:y:2008:i:4:p:395-406
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  1. David A. Hensher, 2004. "Identifying the Influence of Stated Choice Design Dimensionality on Willingness to Pay for Travel Time Savings," Journal of Transport Economics and Policy, London School of Economics and University of Bath, vol. 38(3), pages 425-446, September.
  2. David A. Hensher, 2006. "How do respondents process stated choice experiments? Attribute consideration under varying information load," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(6), pages 861-878.
  3. Amos Tversky & Daniel Kahneman, 1979. "Prospect Theory: An Analysis of Decision under Risk," Levine's Working Paper Archive 7656, David K. Levine.
  4. David Schmeidler, 2000. "Utility in Case-Based Decision Theory," Working Papers 00-06, Ohio State University, Department of Economics.
  5. Kenneth Train, 2003. "Discrete Choice Methods with Simulation," Online economics textbooks, SUNY-Oswego, Department of Economics, number emetr2, March.
  6. Ferrini, Silvia & Scarpa, Riccardo, 2007. "Designs with a priori information for nonmarket valuation with choice experiments: A Monte Carlo study," Journal of Environmental Economics and Management, Elsevier, vol. 53(3), pages 342-363, May.
  7. Chris Starmer, 2000. "Developments in Non-expected Utility Theory: The Hunt for a Descriptive Theory of Choice under Risk," Journal of Economic Literature, American Economic Association, vol. 38(2), pages 332-382, June.
  8. Zsolt Sándor & Michel Wedel, 2002. "Profile Construction in Experimental Choice Designs for Mixed Logit Models," Marketing Science, INFORMS, vol. 21(4), pages 455-475, February.
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