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Geodemographic analysis and the identification of potential business partnerships enabled by transit smart cards


  • Páez, Antonio
  • Trépanier, Martin
  • Morency, Catherine


Smart card automated fare payment systems are being adopted by transit agencies around the world. The data-storage characteristics of smart cards present novel opportunities to enhance transit services. On the one hand, there are fare policies, where smart card holders are given specific rebates on the use of the service based on usage patterns or levels. On the other, there are non-fare policies, for instance if holders receive advantages, such as rebates and offers, from commercial partners. The purpose of this paper is to present a geodemographic framework to identify potential commercial partnerships that could exploit the characteristics of smart cards. The framework is demonstrated using data from Montreal, Canada. Household survey data, specifically trip ends, and business data points are jointly used to determine the exposure of various types of establishments to users of the Montreal Metro network. Spatial analysis of business establishments in the neighborhood of metro stations helps to identify potential commercial partners. The results illustrate the potential of geodemographic analysis to generate intelligence of commercial interest.

Suggested Citation

  • Páez, Antonio & Trépanier, Martin & Morency, Catherine, 2011. "Geodemographic analysis and the identification of potential business partnerships enabled by transit smart cards," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(7), pages 640-652, August.
  • Handle: RePEc:eee:transa:v:45:y:2011:i:7:p:640-652

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    References listed on IDEAS

    1. Morency, Catherine & Trépanier, Martin & Agard, Bruno, 2007. "Measuring transit use variability with smart-card data," Transport Policy, Elsevier, vol. 14(3), pages 193-203, May.
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    Cited by:

    1. Páez, Antonio & Trépanier, Martin & Morency, Catherine, 2012. "Modeling isoexposure to transit users for market potential analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(10), pages 1517-1527.
    2. Bernal, Margarita & Welch, Eric W. & Sriraj, P.S., 2016. "The effect of slow zones on ridership: An analysis of the Chicago Transit Authority “El” Blue Line," Transportation Research Part A: Policy and Practice, Elsevier, vol. 87(C), pages 11-21.


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