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Multivariate methodology for discriminating market segments in urban commuting

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  • Steven D. Silver

    (California State University)

Abstract

Efficient planning operations in the management of public transportation can benefit from more definitive understanding of the market structure of user demand. Market segmentation has been shown to be an effective method to guide the design of transit service offerings that can help transit agencies increase ridership and revenue. This study offers an integration of multivariate methodology for market segmentation in urban work commuting within a high technology corridor that has similarity to other such corridors in the US and worldwide. Adaptive choice conjoint analysis is first used to derive the importance weights of a set of attributes in terms of which service offerings for these commuters can be defined. This methodology allows respondents to more realistically indicate their preferences from full profiles of service offerings. A clustering procedure is then used to explore the grouping of individuals into homogeneous subsets of the sample that approximate market segments. Finally, the combinations of traveler demographics that differentiate clusters are examined with methodology of non-linear discriminant analysis. Access to and use of study methodologies by system analysts and designers is elaborated upon in an online appendix.

Suggested Citation

  • Steven D. Silver, 2018. "Multivariate methodology for discriminating market segments in urban commuting," Public Transport, Springer, vol. 10(1), pages 63-89, May.
    • Handle: RePEc:spr:pubtra:v:10:y:2018:i:1:d:10.1007_s12469-017-0169-8
    DOI: 10.1007/s12469-017-0169-8
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