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Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models

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  • Wang, Jiangbo
  • Yamamoto, Toshiyuki
  • Liu, Kai

Abstract

This paper proposes customized bus (CB) demand models to investigate dynamic adjustments, spatial dependence, and spatial spillover effects using spatial dynamic panel data techniques and a balanced panel data set collected over two years. The endogeneity introduced by spatial dependence effects is resolved by extending the moment restrictions of the system GMM estimator to a spatial autoregressive dynamic panel. A wide range of variables representing factors related to 1) characteristics of service supply, 2) demographic characteristics, and 3) land use and accessibility were mined and fused to investigate their direct and spillover effects on CB demand. The results reveal the mechanism of spatial dependence such that the increments (or decrement) in demand rather than the amount of demand itself in the neighbourhood contribute to the spatial dependence effects. There is more than 43% matched demand generated in a given area for each-unit increment of demand from its neighbourhood. CB services are more attractive for passengers with long-distance trips, and therefore, increasing the focus on long-distance trips is one potential strategy for increasing ridership. Determined by the role of CB in the transportation system, areas with poor accessibility are found to have larger market niches for CB services.

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  • Wang, Jiangbo & Yamamoto, Toshiyuki & Liu, Kai, 2021. "Spatial dependence and spillover effects in customized bus demand: Empirical evidence using spatial dynamic panel models," Transport Policy, Elsevier, vol. 105(C), pages 166-180.
    • Handle: RePEc:eee:trapol:v:105:y:2021:i:c:p:166-180
    DOI: 10.1016/j.tranpol.2021.03.004
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    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Antonio García-Ferrer & Marcos Bujosa & Aránzazu de Juan & Pilar Poncela, 2006. "Demand Forecast and Elasticities Estimation of Public Transport," Journal of Transport Economics and Policy, University of Bath, vol. 40(1), pages 45-67, January.
    3. Boisjoly, Geneviève & Grisé, Emily & Maguire, Meadhbh & Veillette, Marie-Pier & Deboosere, Robbin & Berrebi, Emma & El-Geneidy, Ahmed, 2018. "Invest in the ride: A 14 year longitudinal analysis of the determinants of public transport ridership in 25 North American cities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 434-445.
    4. Markus Friedrich & Maximilian Hartl & Christoph Magg, 2018. "A modeling approach for matching ridesharing trips within macroscopic travel demand models," Transportation, Springer, vol. 45(6), pages 1639-1653, November.
    5. Cheng Hsiao, 2005. "Why Panel Data?," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 50(02), pages 143-154.
    6. Bresson, Georges & Dargay, Joyce & Madre, Jean-Loup & Pirotte, Alain, 2003. "The main determinants of the demand for public transport: a comparative analysis of England and France using shrinkage estimators," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(7), pages 605-627, August.
    7. Markus Friedrich & Klaus Noekel, 2017. "Modeling intermodal networks with public transport and vehicle sharing systems," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 271-288, September.
    8. Yang, Shuo & Fan, Yingling & Deng, Wei & Cheng, Long, 2019. "Do built environment effects on travel behavior differ between household members? A case study of Nanjing, China," Transport Policy, Elsevier, vol. 81(C), pages 360-370.
    9. David Roodman, 2009. "A Note on the Theme of Too Many Instruments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(1), pages 135-158, February.
    10. David Roodman, 2009. "How to do xtabond2: An introduction to difference and system GMM in Stata," Stata Journal, StataCorp LP, vol. 9(1), pages 86-136, March.
    11. Chakrabarti, Sandip, 2017. "How can public transit get people out of their cars? An analysis of transit mode choice for commute trips in Los Angeles," Transport Policy, Elsevier, vol. 54(C), pages 80-89.
    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. Graham, Daniel J. & Crotte, Amado & Anderson, Richard J., 2009. "A dynamic panel analysis of urban metro demand," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(5), pages 787-794, September.
    14. Liu, Tao & Ceder, Avishai (Avi), 2015. "Analysis of a new public-transport-service concept: Customized bus in China," Transport Policy, Elsevier, vol. 39(C), pages 63-76.
    15. Charles Brown & Robert Moffitt, 1983. "The Effect of Ignoring Heteroscedasticity on Estimates of the Tobit Model," NBER Technical Working Papers 0027, National Bureau of Economic Research, Inc.
    16. Taylor, Brian D. & Fink, Camille N.Y., 2003. "The Factors Influencing Transit Ridership: A Review and Analysis of the Ridership Literature," University of California Transportation Center, Working Papers qt3xk9j8m2, University of California Transportation Center.
    17. Arellano, Manuel & Bover, Olympia, 1995. "Another look at the instrumental variable estimation of error-components models," Journal of Econometrics, Elsevier, vol. 68(1), pages 29-51, July.
    18. FitzRoy, Felix & Smith, Ian, 1998. "Public transport demand in Freiburg: why did patronage double in a decade?," Transport Policy, Elsevier, vol. 5(3), pages 163-173, June.
    19. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    20. J. Paul Elhorst, 2014. "Dynamic Spatial Panels: Models, Methods and Inferences," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 95-119, Springer.
    21. Salima Bouayad-Agha & Lionel Védrine, 2010. "Estimation Strategies for a Spatial Dynamic Panel using GMM. A New Approach to the Convergence Issue of European Regions," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(2), pages 205-227.
    22. Joyce M. Dargay & Mark Hanly, 2002. "The Demand for Local Bus Services in England," Journal of Transport Economics and Policy, University of Bath, vol. 36(1), pages 73-91, January.
    23. Yunfeng Hu & Yueqi Han, 2019. "Identification of Urban Functional Areas Based on POI Data: A Case Study of the Guangzhou Economic and Technological Development Zone," Sustainability, MDPI, vol. 11(5), pages 1-15, March.
    24. Kain, John F. & Liu, Zvi, 1999. "Secrets of success: assessing the large increases in transit ridership achieved by Houston and San Diego transit providers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 33(7-8), pages 601-624.
    25. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 58(2), pages 277-297.
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    2. Chen, Feng & Peng, Haorong & Ding, Wenlong & Ma, Xiaoxiang & Tang, Daizhong & Ye, Yipeng, 2021. "Customized bus passenger boarding and deboarding planning optimization model with the least number of contacts between passengers during COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
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    6. Wang, Jiangbo & Yamamoto, Toshiyuki & Liu, Kai, 2022. "Exploring the subscribing behavior of customized bus passengers: Active users versus inactive users," Journal of choice modelling, Elsevier, vol. 43(C).

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