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Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia

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  • Liu, Yan
  • Wang, Siqin
  • Xie, Bin

Abstract

The demand for public transport and commuter behaviour are evidently affected by a series of D-factors relating to the built environment, including density, diversity, design, destination and/or demography. The effect of fare policies, however, in conjunction with built and non-built environment features has not been assessed. Given the 2017 fare policy change introduced in South East Queensland, Australia, this study examines how the policy reform (changes in fares, its structure and incentives) affects public transport ridership. Drawing on two like-for-like periods of transport smart card data before and after the policy reform, we compare the number of card users, journeys, and travel costs under the two fare systems. Through a set of statistical analysis and spatial lag regression, we examine the impact of the fare policy change on ridership, controlled by variations of built and non-built environment features, including population density, land use diversity, demographic features of commuters, distance to the central business district (CBD) and destination accessibility. Our findings show that public transit ridership can be boosted by reducing the fare cost per journey which can then result in overall revenue gain. However, such attraction by fare reduction varies substantially by user groups. Furthermore, the influences of population density, destination accessibility, distance to CBD and demographic features of commuters on ridership are significant (p < 0.01); while the influences of land use diversity and fare change tend to be insignificant compared to the other D-factors. We argue that in order to increase public transport usage policy makers need to consider fare policy reform in conjunction with built environment and demographic factors in order to increase service availability and ensure that services are accessible and affordable to the general public. This study also offers a generic framework that employs big data analytics to assess public policy intervention in the Australian context.

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  • Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
  • Handle: RePEc:eee:trapol:v:76:y:2019:i:c:p:78-89
    DOI: 10.1016/j.tranpol.2019.02.004
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    as
    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Wang, Donggen & Chai, Yanwei & Li, Fei, 2011. "Built environment diversities and activity–travel behaviour variations in Beijing, China," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1173-1186.
    3. Marlon Boarnet, 2011. "A Broader Context for Land Use and Travel Behavior, and a Research Agenda," Journal of the American Planning Association, Taylor & Francis Journals, vol. 77(3), pages 197-213.
    4. Patricia L. Mokhtarian & Michael N. Bagley, 2002. "The impact of residential neighborhood type on travel behavior: A structural equations modeling approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 36(2), pages 279-297.
    5. van Wee, Bert, 2011. "Evaluating the impact of land use on travel behaviour: the environment versus accessibility," Journal of Transport Geography, Elsevier, vol. 19(6), pages 1530-1533.
    6. Wang, Zi-jia & Li, Xiao-hong & Chen, Feng, 2015. "Impact evaluation of a mass transit fare change on demand and revenue utilizing smart card data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 213-224.
    7. Tao, Sui & Rohde, David & Corcoran, Jonathan, 2014. "Examining the spatial–temporal dynamics of bus passenger travel behaviour using smart card data and the flow-comap," Journal of Transport Geography, Elsevier, vol. 41(C), pages 21-36.
    8. 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.
    9. Arlie Adkins & Carrie Makarewicz & Michele Scanze & Maia Ingram & Gretchen Luhr, 2017. "Contextualizing Walkability: Do Relationships Between Built Environments and Walking Vary by Socioeconomic Context?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(3), pages 296-314, July.
    10. Reid Ewing & Guang Tian & JP Goates & Ming Zhang & Michael J Greenwald & Alex Joyce & John Kircher & William Greene, 2015. "Varying influences of the built environment on household travel in 15 diverse regions of the United States," Urban Studies, Urban Studies Journal Limited, vol. 52(13), pages 2330-2348, October.
    11. Daniel G Chatman, 2009. "Residential Choice, the Built Environment, and Nonwork Travel: Evidence Using New Data and Methods," Environment and Planning A, , vol. 41(5), pages 1072-1089, May.
    12. Paulley, Neil & Balcombe, Richard & Mackett, Roger & Titheridge, Helena & Preston, John & Wardman, Mark & Shires, Jeremy & White, Peter, 2006. "The demand for public transport: The effects of fares, quality of service, income and car ownership," Transport Policy, Elsevier, vol. 13(4), pages 295-306, July.
    13. Paul van de Coevering & Kees Maat & Bert van Wee, 2015. "Multi-period Research Designs for Identifying Causal Effects of Built Environment Characteristics on Travel Behaviour," Transport Reviews, Taylor & Francis Journals, vol. 35(4), pages 512-532, July.
    14. Wang, Zhaohua & Liu, Wei, 2015. "Determinants of CO2 emissions from household daily travel in Beijing, China: Individual travel characteristic perspectives," Applied Energy, Elsevier, vol. 158(C), pages 292-299.
    15. Ming Li & Guohua Song & Ying Cheng & Lei Yu, 2015. "Identification of Prior Factors Influencing the Mode Choice of Short Distance Travel," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-9, February.
    16. Kamruzzaman, Md. & Baker, Douglas & Washington, Simon & Turrell, Gavin, 2014. "Advance transit oriented development typology: case study in Brisbane, Australia," Journal of Transport Geography, Elsevier, vol. 34(C), pages 54-70.
    17. Michael Manville, 2017. "Travel and the Built Environment: Time for Change," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 29-32, January.
    18. Bhat, Chandra R. & Eluru, Naveen, 2009. "A copula-based approach to accommodate residential self-selection effects in travel behavior modeling," Transportation Research Part B: Methodological, Elsevier, vol. 43(7), pages 749-765, August.
    19. Stephen A. Rhoades, 1993. "The Herfindahl-Hirschman index," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Mar, pages 188-189.
    20. Tang, Siman & Lo, Hong K., 2008. "The impact of public transport policy on the viability and sustainability of mass railway transit - The Hong Kong experience," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(4), pages 563-576, May.
    21. Lu, Xuedong & Pas, Eric I., 1999. "Socio-demographics, activity participation and travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(1), pages 1-18, January.
    22. Holmgren, Johan, 2007. "Meta-analysis of public transport demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(10), pages 1021-1035, December.
    23. Chung, Yi-Shih & Chiou, Yu-Chiun, 2017. "Willingness-to-pay for a bus fare reform: A contingent valuation approach with multiple bound dichotomous choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 289-304.
    24. McMillan, Tracy E., 2007. "The relative influence of urban form on a child's travel mode to school," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(1), pages 69-79, January.
    25. Reid Ewing & Robert Cervero, 2017. "“Does Compact Development Make People Drive Less?” The Answer Is Yes," Journal of the American Planning Association, Taylor & Francis Journals, vol. 83(1), pages 19-25, January.
    26. Zhou, Jiangping, 2012. "Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1013-1029.
    27. Sharaby, Nir & Shiftan, Yoram, 2012. "The impact of fare integration on travel behavior and transit ridership," Transport Policy, Elsevier, vol. 21(C), pages 63-70.
    28. Daniel P. McMillen, 2004. "Geographically Weighted Regression: The Analysis of Spatially Varying Relationships," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 86(2), pages 554-556.
    29. Handy, Susan & Cao, Xinyu & Mokhtarian, Patricia L., 2005. "Correlation or causality between the built environment and travel behavior? Evidence from Northern California," University of California Transportation Center, Working Papers qt5b76c5kg, University of California Transportation Center.
    30. Schwanen, Tim & Mokhtarian, Patricia L., 2005. "What Affects Commute Mode Choice: Neighborhood Physical Structure or Preferences Toward Neighborhoods?," University of California Transportation Center, Working Papers qt4nq9r1c9, University of California Transportation Center.
    31. Erick Guerra & Robert Cervero, 2011. "Cost of a Ride," Journal of the American Planning Association, Taylor & Francis Journals, vol. 77(3), pages 267-290.
    32. Tao, Sui & Corcoran, Jonathan & Hickman, Mark & Stimson, Robert, 2016. "The influence of weather on local geographical patterns of bus usage," Journal of Transport Geography, Elsevier, vol. 54(C), pages 66-80.
    33. Kamargianni, Maria & Dubey, Subodh & Polydoropoulou, Amalia & Bhat, Chandra, 2015. "Investigating the subjective and objective factors influencing teenagers’ school travel mode choice – An integrated choice and latent variable model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 473-488.
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