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Evaluating the relationship between socially (dis)advantaged neighbourhoods and customer satisfaction of bus service in London, U.K

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  • Grisé, Emily
  • El-Geneidy, Ahmed

Abstract

Affordable and efficient urban public transport is important for the development of a sustainable urban environment. Making sure public transport users are satisfied with the service is a goal many public transport agencies are trying to achieve. Customer satisfaction surveys are often used to monitor customer perceptions of service quality and to determine the relative influence of service attributes on a customer's overall assessment of the service. This study presents a new method to spatially evaluate customer satisfaction survey data through examining satisfaction with bus service across neighbourhoods of varying levels of socio-economic status (SES). Using customer satisfaction survey data collected by Transport for London between 2010 and 2015, multi-level regression modeling is used to estimate the relationship between overall satisfaction and social deprivation of the area in which bus routes were operating. The results indicate lower levels of satisfaction along routes serving low SES neighbourhoods, which appears to be attributed to (1) low satisfaction with service characteristics related to an individual's experience and quality of the bus and (2) conditions of the bus stop and shelter. Findings from this paper shows the importance of including cleanliness and bus internal quality as one of the performance indicators when contracting bus services, to ensure that all customers receive the same quality of service in the region regardless of their SES.

Suggested Citation

  • Grisé, Emily & El-Geneidy, Ahmed, 2017. "Evaluating the relationship between socially (dis)advantaged neighbourhoods and customer satisfaction of bus service in London, U.K," Journal of Transport Geography, Elsevier, vol. 58(C), pages 166-175.
    • Handle: RePEc:eee:jotrge:v:58:y:2017:i:c:p:166-175
    DOI: 10.1016/j.jtrangeo.2016.11.016
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    References listed on IDEAS

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    Cited by:

    1. Eboli, Laura & Forciniti, Carmen & Mazzulla, Gabriella, 2018. "Spatial variation of the perceived transit service quality at rail stations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 67-83.
    2. Li, Xiangrong & Zhu, Shaoying & Yüksel, Serhat & Dinçer, Hasan & Ubay, Gözde Gülseven, 2020. "Kano-based mapping of innovation strategies for renewable energy alternatives using hybrid interval type-2 fuzzy decision-making approach," Energy, Elsevier, vol. 211(C).
    3. Mokonyama, Mathetha & Venter, Christo, 2018. "How worthwhile is it to maximise customer satisfaction in public transport service contracts with a large captive user base? The case of South Africa," Research in Transportation Economics, Elsevier, vol. 69(C), pages 180-186.
    4. Nick Chaloux & Genevieve Boisjoly & Emily Grise & Ahmed El-Geneidy & David Levinson, 2019. "Chaloux, Nick, Boisjoly, Genevieve, Grise, Emily, El-Geneidy, Ahmed, and Levinson, D. (2019) I only get some satisfaction: Introducing satisfaction into measures of accessibility," Working Papers 2019-07, University of Minnesota: Nexus Research Group.
    5. Dubé, Jean & Andrianary, Eugénie & Assad-Déry, François & Poupart, Janie & Simard, Justine, 2018. "Exploring difference in value uplift resulting from new bus rapid transit routes within a medium size metropolitan area," Journal of Transport Geography, Elsevier, vol. 72(C), pages 258-269.
    6. Zhao, Pengjun & Zhang, Yixue, 2019. "The effects of metro fare increase on transport equity: New evidence from Beijing," Transport Policy, Elsevier, vol. 74(C), pages 73-83.
    7. Nick Chaloux & Genevieve Boisjoly & Emily Grise & Ahmed El-Geneidy, & David Levinson, 2018. "I only get some satisfaction: Introducing satisfaction into measures of accessibility," Working Papers 170, University of Minnesota: Nexus Research Group.
    8. Luo, Shuli & He, Sylvia Y. & Grant-Muller, Susan & Song, Linqi, 2023. "Influential factors in customer satisfaction of transit services: Using crowdsourced data to capture the heterogeneity across individuals, space and time," Transport Policy, Elsevier, vol. 131(C), pages 173-183.
    9. Luo, Qingyu & Bing, Xue & Jia, Hongfei & Song, Jinge, 2022. "An incentive subsidy mechanism for bus lines based on service level," Transport Policy, Elsevier, vol. 126(C), pages 1-13.
    10. Luo, Shuli & He, Sylvia Y., 2021. "Understanding gender difference in perceptions toward transit services across space and time: A social media mining approach," Transport Policy, Elsevier, vol. 111(C), pages 63-73.

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