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Trip chaining - who wins, who loses?

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  • André De Palma
  • Fay Dunkerley
  • Stef Proost

Abstract

There has been a very large amount of research devoted to the study of activity patterns. The initial studies have been developed in geography (space and time description of human activity, as described by Torsten, Hägerstrand and Peter Hagget) and in economics (starting with the seminal work of Gary Becker). More recently, transportation scholars (see for example the studies of Chandra Bath or of Kay Axhausen) have started to develop sophisticated econometric models to describe the chain of activities during the whole day of individuals. One rationale for this research is the fact that users are increasingly sophisticated and can spend more and more time involved in other activities than the home to work trip. Thus, lengthy trips with many stops can be envisaged (with sometimes one of these stops being at the office). We propose here a new avenue of research covering the following questions: what are the impacts of the chain of activities on the decisions of the firm? The fact that users change their activity patterns does influence the locations of the firms (see for example the emergence of large shopping areas near railway stations or even inside railway stations and airports), as well as their pricing strategies. The questions are: Is the market more or less competitive? Are human activities more or less concentrated as users are more involved in trip chaining?

Suggested Citation

  • André De Palma & Fay Dunkerley & Stef Proost, 2005. "Trip chaining - who wins, who loses?," ERSA conference papers ersa05p496, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa05p496
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    References listed on IDEAS

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    Cited by:

    1. Arthur (Yan) Huang & David Levinson, 2015. "Axis of travel: Modeling non-work destination choice with GPS data," Working Papers 000113, University of Minnesota: Nexus Research Group.
    2. Russo, Antonio, 2013. "Voting on road congestion policy," Regional Science and Urban Economics, Elsevier, vol. 43(5), pages 707-724.
    3. André De Palma & Fay Dunkerley & Stef Proost, 2005. "Asymmetric Duopoly in Space - what policies work?," ERSA conference papers ersa05p494, European Regional Science Association.
    4. Andre De Palma & Fay Dunkerley & Stef Proost, 2010. "Trip Chaining: Who Wins Who Loses?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 19(1), pages 223-258, March.
    5. Huang, Arthur & Levinson, David, 2017. "A model of two-destination choice in trip chains with GPS data," Journal of choice modelling, Elsevier, vol. 24(C), pages 51-62.
    6. Takahashi, Takaaki, 2013. "Agglomeration in a city with choosy consumers under imperfect information," Journal of Urban Economics, Elsevier, vol. 76(C), pages 28-42.

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    More about this item

    JEL classification:

    • D43 - Microeconomics - - Market Structure, Pricing, and Design - - - Oligopoly and Other Forms of Market Imperfection
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • R3 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Real Estate Markets, Spatial Production Analysis, and Firm Location

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