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Examining inclusive mobility through smartcard data: What shall we make of senior citizens' declining bus patronage in the West Midlands?

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  • Kandt, Jens
  • Leak, Alistair

Abstract

Free access to public transport is viewed as an effective means to enable inclusive mobility, but the recent decline in bus patronage by passengers entitled to free travel in the West Midlands and other UK regions presents a conundrum to transport research and policy. In this research, we analyse travel smartcard transactions recorded over nearly six years for 371,220 concessionary passengers resident in the West Midlands Combined Authority. Using sequence analysis, we identify six groups representing different temporal boarding profiles. We link these profiles to geo-spatial data and characterise them by means of spatial pattern detection and multinomial logit modelling. We find that, first, the decline in patronage occurs in three waves across the study period according to distinct activity patterns; second, formerly frequent (daily) passengers tend to abandon the bus and thus show the largest impact on the overall trend; third, the neighbourhood context of withdrawing passengers indicates social disadvantage, higher instance of ethnic minorities and lower car ownership rates, in other words higher risk of social exclusion. To discuss these in parts paradoxical results, we identify three causal domains - social, health-related and structural - and conclude with implications for policy promoting inclusive and healthy mobility in later life.

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  • Kandt, Jens & Leak, Alistair, 2019. "Examining inclusive mobility through smartcard data: What shall we make of senior citizens' declining bus patronage in the West Midlands?," Journal of Transport Geography, Elsevier, vol. 79(C), pages 1-1.
    • Handle: RePEc:eee:jotrge:v:79:y:2019:i:c:15
    DOI: 10.1016/j.jtrangeo.2019.102474
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    1. Matthias Studer & Gilbert Ritschard, 2016. "What matters in differences between life trajectories: a comparative review of sequence dissimilarity measures," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(2), pages 481-511, February.
    2. van den Berg, Pauline & Arentze, Theo & Timmermans, Harry, 2011. "Estimating social travel demand of senior citizens in the Netherlands," Journal of Transport Geography, Elsevier, vol. 19(2), pages 323-331.
    3. Bivand, Roger & Piras, Gianfranco, 2015. "Comparing Implementations of Estimation Methods for Spatial Econometrics," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 63(i18).
    4. Hadfield, Jarrod D., 2010. "MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 33(i02).
    5. Jie Huang & David Levinson & Jiaoe Wang & Jiangping Zhou & Zi-jia Wang, 2018. "Tracking job and housing dynamics with smartcard data," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(50), pages 12710-12715, December.
    6. Jianqiang Cui & Becky P. Y. Loo & Dong Lin, 2017. "Travel behaviour and mobility needs of older adults in an ageing and car-dependent society," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 21(2), pages 109-128, May.
    7. Cuauhtemoc Anda & Alexander Erath & Pieter Jacobus Fourie, 2017. "Transport modelling in the age of big data," International Journal of Urban Sciences, Taylor & Francis Journals, vol. 21(0), pages 19-42, August.
    8. Carlo Luiu & Miles Tight & Michael Burrow, 2017. "The unmet travel needs of the older population: a review of the literature," Transport Reviews, Taylor & Francis Journals, vol. 37(4), pages 488-506, July.
    9. 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.
    10. Siren, Anu & Haustein, Sonja, 2013. "Baby boomers’ mobility patterns and preferences: What are the implications for future transport?," Transport Policy, Elsevier, vol. 29(C), pages 136-144.
    11. Schwanen, Tim & Lucas, Karen & Akyelken, Nihan & Cisternas Solsona, Diego & Carrasco, Juan-Antonio & Neutens, Tijs, 2015. "Rethinking the links between social exclusion and transport disadvantage through the lens of social capital," Transportation Research Part A: Policy and Practice, Elsevier, vol. 74(C), pages 123-135.
    12. Webb, E. & Laverty, A. & Mindell, J. & Millett, C., 2016. "Free bus travel and physical activity, gait speed, and adiposity in the english longitudinal study of ageingxs," American Journal of Public Health, American Public Health Association, vol. 106(1), pages 136-142.
    13. Lucas, Karen, 2012. "Transport and social exclusion: Where are we now?," Transport Policy, Elsevier, vol. 20(C), pages 105-113.
    14. Judith Green & Alasdair Jones & Helen Roberts, 2014. "More than A to B: the role of free bus travel for the mobility and wellbeing of older citizens in London," LSE Research Online Documents on Economics 64155, London School of Economics and Political Science, LSE Library.
    15. Gabadinho, Alexis & Ritschard, Gilbert & Müller, Nicolas S & Studer, Matthias, 2011. "Analyzing and Visualizing State Sequences in R with TraMineR," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i04).
    16. Sonja Haustein, 2012. "Mobility behavior of the elderly: an attitude-based segmentation approach for a heterogeneous target group," Transportation, Springer, vol. 39(6), pages 1079-1103, November.
    17. Mimi Sheller & John Urry, 2006. "The New Mobilities Paradigm," Environment and Planning A, , vol. 38(2), pages 207-226, February.
    18. Langfelder, Peter & Horvath, Steve, 2012. "Fast R Functions for Robust Correlations and Hierarchical Clustering," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 46(i11).
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    5. Pieroni, Caio & Giannotti, Mariana & Alves, Bianca B. & Arbex, Renato, 2021. "Big data for big issues: Revealing travel patterns of low-income population based on smart card data mining in a global south unequal city," Journal of Transport Geography, Elsevier, vol. 96(C).
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    7. Zijia Wang & Hao Tang & Wenjuan Wang & Yang Xi, 2020. "The Pattern of Non-Roundtrip Travel on Urban Rail and Its Application in Transit Improvement," Sustainability, MDPI, vol. 12(9), pages 1-16, April.
    8. Haarstad, Håvard & Sareen, Siddharth & Kandt, Jens & Coenen, Lars & Cook, Matthew, 2022. "Beyond automobility? Lock-in of past failures in low-carbon urban mobility innovations," Energy Policy, Elsevier, vol. 166(C).
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    10. Ffion Carney, 2021. "Linking Loyalty Card Data to Public Transport Data to Explore Mobility and Social Exclusion in the Older Population," Sustainability, MDPI, vol. 13(11), pages 1-19, May.

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