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Assessing the Factors Impacting Transport Usage of Mobility App Users in the National Capital Territory of Delhi, India

Author

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  • Sanjay Gupta

    (Department of Transport Planning, School of Planning and Architecture, 4, Block-B, Indraprastha Estate, New Delhi 110002, India)

  • Kushagra Sinha

    (Department of Transport Planning, School of Planning and Architecture, 4, Block-B, Indraprastha Estate, New Delhi 110002, India)

Abstract

Smartphone-based mobility apps have created a smartphone-enabled ecosystem of mobility services in developed countries and are slowly picking up pace in the Global South. Against this backdrop, this study used Latent Class Cluster Analysis to empirically investigate the impacts of mobility apps on transport usage patterns in Delhi by classifying users into three latent clusters based on socioeconomic characteristics, smartphone app usage, attitudes, and transport usage. Cluster 1 consisted of users with low app usage, and higher usage of public transport and intermediate public transport; Cluster 2 consisted of multimodal users with high app usage; and Cluster 3 consisted of users with moderate app usage and heavy reliance on private vehicles. Furthermore, the detailed characteristics of each latent class and factors affecting the individual’s probability of being classified into these clusters are discussed. It was found that younger users with higher education, more smartphone experience, medium-to-high household income and lower vehicle ownership had a very high probability of being classified as a multimodal traveler. Furthermore, the attitudes and preferences of users belonging to these clusters towards their choice of transport are discussed, along with a brief policy discussion for encouraging new app-based mobility services such as MaaS.

Suggested Citation

  • Sanjay Gupta & Kushagra Sinha, 2022. "Assessing the Factors Impacting Transport Usage of Mobility App Users in the National Capital Territory of Delhi, India," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13768-:d:951627
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    1. Konrad, Kathrin & Wittowsky, Dirk, 2018. "Virtual mobility and travel behavior of young people – Connections of two dimensions of mobility," Research in Transportation Economics, Elsevier, vol. 68(C), pages 11-17.
    2. Hensher, David A., 1998. "The imbalance between car and public transport use in urban Australia: why does it exist?," Transport Policy, Elsevier, vol. 5(4), pages 193-204, October.
    3. Molin, Eric & Mokhtarian, Patricia & Kroesen, Maarten, 2016. "Multimodal travel groups and attitudes: A latent class cluster analysis of Dutch travelers," Transportation Research Part A: Policy and Practice, Elsevier, vol. 83(C), pages 14-29.
    4. Ho, Chinh Q. & Hensher, David A. & Mulley, Corinne & Wong, Yale Z., 2018. "Potential uptake and willingness-to-pay for Mobility as a Service (MaaS): A stated choice study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 302-318.
    5. Kuhnimhof, Tobias & Buehler, Ralph & Wirtz, Matthias & Kalinowska, Dominika, 2012. "Travel trends among young adults in Germany: increasing multimodality and declining car use for men," Journal of Transport Geography, Elsevier, vol. 24(C), pages 443-450.
    6. Bhat, Chandra R. & Sivakumar, Aruna & Axhausen, Kay W., 2003. "An analysis of the impact of information and communication technologies on non-maintenance shopping activities," Transportation Research Part B: Methodological, Elsevier, vol. 37(10), pages 857-881, December.
    7. Efthymiou, Dimitrios & Antoniou, Constantinos & Waddell, Paul, 2013. "Factors affecting the adoption of vehicle sharing systems by young drivers," Transport Policy, Elsevier, vol. 29(C), pages 64-73.
    8. Al-Ayyash, Zahwa & Abou-Zeid, Maya & Kaysi, Isam, 2016. "Modeling the demand for a shared-ride taxi service: An application to an organization-based context," Transport Policy, Elsevier, vol. 48(C), pages 169-182.
    9. Geels, Frank W., 2012. "A socio-technical analysis of low-carbon transitions: introducing the multi-level perspective into transport studies," Journal of Transport Geography, Elsevier, vol. 24(C), pages 471-482.
    10. Lavery, T.A. & Páez, A. & Kanaroglou, P.S., 2013. "Driving out of choices: An investigation of transport modality in a university sample," Transportation Research Part A: Policy and Practice, Elsevier, vol. 57(C), pages 37-46.
    11. Marco Diana & Patricia Mokhtarian, 2009. "Grouping travelers on the basis of their different car and transit levels of use," Transportation, Springer, vol. 36(4), pages 455-467, July.
    12. Yongsung Lee & Giovanni Circella & Patricia L. Mokhtarian & Subhrajit Guhathakurta, 2020. "Are millennials more multimodal? A latent-class cluster analysis with attitudes and preferences among millennial and Generation X commuters in California," Transportation, Springer, vol. 47(5), pages 2505-2528, October.
    13. Van Exel, N.J.A. & Rietveld, P., 2009. "Could you also have made this trip by another mode? An investigation of perceived travel possibilities of car and train travellers on the main travel corridors to the city of Amsterdam, The Netherland," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 374-385, May.
    14. Kaplan, Sigal & Moraes Monteiro, Mayara & Anderson, Marie Karen & Nielsen, Otto Anker & Medeiros Dos Santos, Enilson, 2017. "The role of information systems in non-routine transit use of university students: Evidence from Brazil and Denmark," Transportation Research Part A: Policy and Practice, Elsevier, vol. 95(C), pages 34-48.
    15. Kroesen, Maarten, 2014. "Modeling the behavioral determinants of travel behavior: An application of latent transition analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 56-67.
    16. Shaheen, Susan PhD & Cohen, Adam & Martin, Elliot PhD, 2013. "Public Bikesharing in North America: Early Operator Understanding and Emerging Trends," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1x26m6z7, Institute of Transportation Studies, UC Berkeley.
    17. Kitamura, Ryuichi & Yamamoto, Toshiyuki & Susilo, Yusak O. & Axhausen, Kay W., 2006. "How routine is a routine? An analysis of the day-to-day variability in prism vertex location," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(3), pages 259-279, March.
    18. Heinen, Eva & Chatterjee, Kiron, 2015. "The same mode again? An exploration of mode choice variability in Great Britain using the National Travel Survey," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 266-282.
    19. Khan, Nazmul Arefin & Habib, Muhammad Ahsanul & Jamal, Shaila, 2020. "Effects of smartphone application usage on mobility choices," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 932-947.
    20. Circella, Giovanni & Tiedeman, Kate & Handy, Susan & Alemi, Farzad & Mokhtarian, Patricia, 2016. "What Affects Millennials’ Mobility? Part I: Investigating the Environmental Concerns, Lifestyles, Mobility-Related Attitudes and Adoption of Technology of Young Adults in California," Institute of Transportation Studies, Working Paper Series qt6wm51523, Institute of Transportation Studies, UC Davis.
    21. Robert Schlich & Kay Axhausen, 2003. "Habitual travel behaviour: Evidence from a six-week travel diary," Transportation, Springer, vol. 30(1), pages 13-36, February.
    22. Hirotugu Akaike, 1987. "Factor analysis and AIC," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 317-332, September.
    23. Ryley, Tim J. & A. Stanley, Peter & P. Enoch, Marcus & M. Zanni, Alberto & A. Quddus, Mohammed, 2014. "Investigating the contribution of Demand Responsive Transport to a sustainable local public transport system," Research in Transportation Economics, Elsevier, vol. 48(C), pages 364-372.
    24. Giannopoulos, G. A., 2004. "The application of information and communication technologies in transport," European Journal of Operational Research, Elsevier, vol. 152(2), pages 302-320, January.
    25. Circella, Giovanni & Alemi, Farzad & Tiedeman, Kate & Berliner, Rosaria M & Lee, Yongsung & Fulton, Lew & Mokhtarian, Patricia L & Handy , Susan, 2017. "What Affects Millennials’ Mobility? PART II: The Impact of Residential Location, Individual Preferences and Lifestyles on Young Adults’ Travel Behavior in California," Institute of Transportation Studies, Working Paper Series qt5kc117kj, Institute of Transportation Studies, UC Davis.
    26. Shaheen, Susan PhD & Totte, Hannah & Stocker, Adam, 2018. "Future of Mobility White Paper," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt68g2h1qv, Institute of Transportation Studies, UC Berkeley.
    27. Andrew Harvey & Maria Taylor, 2000. "Activity settings and travel behaviour: A social contact perspective," Transportation, Springer, vol. 27(1), pages 53-73, February.
    28. Alonso-González, María J. & Hoogendoorn-Lanser, Sascha & van Oort, Niels & Cats, Oded & Hoogendoorn, Serge, 2020. "Drivers and barriers in adopting Mobility as a Service (MaaS) – A latent class cluster analysis of attitudes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 378-401.
    29. Vij, Akshay & Carrel, André & Walker, Joan L., 2013. "Incorporating the influence of latent modal preferences on travel mode choice behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 54(C), pages 164-178.
    30. Banister, David, 2008. "The sustainable mobility paradigm," Transport Policy, Elsevier, vol. 15(2), pages 73-80, March.
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