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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?

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Bibliographic Info

Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa05p496.

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Date of creation: Aug 2005
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Handle: RePEc:wiw:wiwrsa:ersa05p496

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References

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  1. Bhat, Chandra R. & Frusti, Teresa & Zhao, Huimin & Schönfelder, Stefan & Axhausen, Kay W., 2004. "Intershopping duration: an analysis using multiweek data," Transportation Research Part B: Methodological, Elsevier, vol. 38(1), pages 39-60, January.
  2. André De Palma & Fay Dunkerley & Stef Proost, 2008. "Trip chaining: Who wins who loses?," Working Papers hal-00348451, HAL.
  3. Golob, Thomas F., 2000. "A simultaneous model of household activity participation and trip chain generation," Transportation Research Part B: Methodological, Elsevier, vol. 34(5), pages 355-376, June.
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  8. Bhat, Chandra R., 2008. "The multiple discrete-continuous extreme value (MDCEV) model: Role of utility function parameters, identification considerations, and model extensions," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 274-303, March.
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  10. Anderson,S.P. & de Palma,A., 1995. "Product Diversity in Asymmetric Oligopoly:Is the Quality of Consumer Goods Too Low?," Papers 9521, Paris X - Nanterre, U.F.R. de Sc. Ec. Gest. Maths Infor..
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  15. David Hensher & April Reyes, 2000. "Trip chaining as a barrier to the propensity to use public transport," Transportation, Springer, vol. 27(4), pages 341-361, December.
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Citations

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Cited by:
  1. André De Palma & Fay Dunkerley & Stef Proost, 2008. "Trip chaining: Who wins who loses?," Working Papers hal-00348451, HAL.
  2. Dunkerley Fay & Andre de Palma & Proost Stef, 2005. "Asymmetric Duopoly in Space - what policies work?," Energy, Transport and Environment Working Papers Series ete0509, Katholieke Universiteit Leuven, Centrum voor Economische Studiën, Energy, Transport and Environment.
  3. Russo, Antonio, 2012. "Voting on Road Congestion Policy," TSE Working Papers 12-310, Toulouse School of Economics (TSE), revised Nov 2012.
  4. 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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