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Mixture–amount experiments for measuring consumer preferences of energy-saving adaptation strategies: principles and illustration

In: Smart Transport Networks

Author

Listed:
  • Dujuan Yang
  • Gamze Dane
  • Harry J.P. Timmermans

Abstract

Transport is debated by many, and liberalization processes, transport policy, transport and climate change and increased competition between transport modes are the subject of heated discussion. Smart Transport Networks illustrates that whether concerning road, water, rail or air, knowledge on the structure of transport markets is crucial in order to tackle transport issues. The book therefore explores key factors concerning the structure of transport markets, their environmental impact, and questions why decision makers often fail to tackle transport-related problems.

Suggested Citation

  • Dujuan Yang & Gamze Dane & Harry J.P. Timmermans, 2013. "Mixture–amount experiments for measuring consumer preferences of energy-saving adaptation strategies: principles and illustration," Chapters, in: Thomas Vanoutrive & Ann Verhetsel (ed.), Smart Transport Networks, chapter 10, pages 208-223, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:15483_10
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    References listed on IDEAS

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    1. Damaraju Raghavarao & James B. Wiley, 2009. "Conjoint Measurement with Constraints on Attribute Levels: A Mixture–Amount Model Approach," International Statistical Review, International Statistical Institute, vol. 77(2), pages 167-178, August.
    2. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D. With contributions by-Name:Adamowicz,Wiktor, 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304.
    3. Caussade, Sebastián & Ortúzar, Juan de Dios & Rizzi, Luis I. & Hensher, David A., 2005. "Assessing the influence of design dimensions on stated choice experiment estimates," Transportation Research Part B: Methodological, Elsevier, vol. 39(7), pages 621-640, August.
    4. Harmen Oppewal & Harry Timmermans, 1991. "Context Effects And Decompositional Choice Modeling," Papers in Regional Science, Wiley Blackwell, vol. 70(2), pages 113-131, April.
    5. Arentze, Theo & Hofman, Frank & Timmermans, Harry, 2004. "Predicting multi-faceted activity-travel adjustment strategies in response to possible congestion pricing scenarios using an Internet-based stated adaptation experiment," Transport Policy, Elsevier, vol. 11(1), pages 31-41, January.
    6. Sean Doherty & Eric Miller, 2000. "A computerized household activity scheduling survey," Transportation, Springer, vol. 27(1), pages 75-97, February.
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