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Modeling spatial and social interdependency effects on commuting mode choice

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  • Giubergia, Daniele
  • Haddad, Angela J.
  • Piras, Francesco
  • Bhat, Chandra R.
  • Meloni, Italo

Abstract

In daily life, individuals are influenced by the behaviors of others. The question of how far-reaching this social influence extends to travel behaviors has received significant attention in recent decades, through the capture of dyadic interaction effects that may exist among individuals. Along these lines, in the current study, we apply a Spatial-Attitudinal Probit Model (SAPM) that assumes an autoregressive lag structure in the utilities underlying individuals’ travel mode choice, specifically focusing on the choice between car and public transportation for commuting trips. Notably, the magnitude of interdependency among decision agents is measured by a global weight matrix, accounting for a dual source of influence: (1) spatial proximity, measured as the Euclidean distance between individuals’ residential locations, and (2) attitudinal similarities, specifically perceptions regarding sustainable mobility and environmental awareness. To our knowledge, this represents the first application of an autoregressive travel mode choice model accounting for both geographical and attitudinal proximity as simultaneous sources of interaction. The dataset for our analysis includes 2,347 observations, corresponding to the one-way commute trips of 2,347 individuals, as reported during a survey conducted between October 2019 and January 2020 in the metropolitan area of Cagliari, Italy. Our results reveal the significant role of social autoregressive parameters and the presence of interdependency effects among individuals’ commute mode choices. The utilization of a social lag structure allows for the separate identification of direct and indirect effects of explanatory variables. Notably, around 40% of the total effect is attributed to the indirect effects arising from individuals’ social interdependencies. This finding holds important implications for evaluating and planning potential future measures aimed at increasing public transit usage.

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  • Giubergia, Daniele & Haddad, Angela J. & Piras, Francesco & Bhat, Chandra R. & Meloni, Italo, 2025. "Modeling spatial and social interdependency effects on commuting mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 196(C).
    • Handle: RePEc:eee:transa:v:196:y:2025:i:c:s0965856425001028
    DOI: 10.1016/j.tra.2025.104474
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    as
    1. Jonas De Vos & Patrick A. Singleton & Tommy Gärling, 2022. "From attitude to satisfaction: introducing the travel mode choice cycle," Transport Reviews, Taylor & Francis Journals, vol. 42(2), pages 204-221, March.
    2. Jing Shi & Vivianne H. M. Visschers & Michael Siegrist & Joseph Arvai, 2016. "Knowledge as a driver of public perceptions about climate change reassessed," Nature Climate Change, Nature, vol. 6(8), pages 759-762, August.
    3. Buehler, Ralph, 2011. "Determinants of transport mode choice: a comparison of Germany and the USA," Journal of Transport Geography, Elsevier, vol. 19(4), pages 644-657.
    4. Li, Zheng & Hensher, David A. & Rose, John M., 2010. "Willingness to pay for travel time reliability in passenger transport: A review and some new empirical evidence," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(3), pages 384-403, May.
    5. Cherchi, Elisabetta, 2017. "A stated choice experiment to measure the effect of informational and normative conformity in the preference for electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 88-104.
    6. Soza-Parra, Jaime & Raveau, Sebastián & Muñoz, Juan Carlos & Cats, Oded, 2019. "The underlying effect of public transport reliability on users’ satisfaction," Transportation Research Part A: Policy and Practice, Elsevier, vol. 126(C), pages 83-93.
    7. Kim, Seheon & Rasouli, Soora, 2022. "The influence of latent lifestyle on acceptance of Mobility-as-a-Service (MaaS): A hierarchical latent variable and latent class approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 304-319.
    8. S. Murray & D. Walton & J. Thomas, 2010. "Attitudes towards public transport in New Zealand," Transportation, Springer, vol. 37(6), pages 915-929, November.
    9. Meyer, Andrew, 2015. "Does education increase pro-environmental behavior? Evidence from Europe," Ecological Economics, Elsevier, vol. 116(C), pages 108-121.
    10. William A. Brock & Steven N. Durlauf, 2001. "Discrete Choice with Social Interactions," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 68(2), pages 235-260.
    11. Chandra Bhat, 2015. "A new spatial (social) interaction discrete choice model accommodating for unobserved effects due to endogenous network formation," Transportation, Springer, vol. 42(5), pages 879-914, September.
    12. 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.
    13. Mondal, Aupal & Bhat, Chandra R., 2022. "A spatial rank-ordered probit model with an application to travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 155(C), pages 374-393.
    14. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555, Enero-Abr.
    15. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    16. Walker, Joan L. & Ehlers, Emily & Banerjee, Ipsita & Dugundji, Elenna R., 2011. "Correcting for endogeneity in behavioral choice models with social influence variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 362-374, May.
    17. Kim, Jinhee & Rasouli, Soora & Timmermans, Harry, 2014. "Expanding scope of hybrid choice models allowing for mixture of social influences and latent attitudes: Application to intended purchase of electric cars," Transportation Research Part A: Policy and Practice, Elsevier, vol. 69(C), pages 71-85.
    18. Van Eenoo, Eva & Boussauw, Kobe, 2023. "“That's not feasible without a car”: An exploration of car-dependent practices," Transport Policy, Elsevier, vol. 144(C), pages 1-10.
    19. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    20. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    21. Bhat, Chandra R., 2014. "The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models," Foundations and Trends(R) in Econometrics, now publishers, vol. 7(1), pages 1-117, July.
    22. Vinayak, Pragun & Dias, Felipe F. & Astroza, Sebastian & Bhat, Chandra R. & Pendyala, Ram M. & Garikapati, Venu M., 2018. "Accounting for multi-dimensional dependencies among decision-makers within a generalized model framework: An application to understanding shared mobility service usage levels," Transport Policy, Elsevier, vol. 72(C), pages 129-137.
    23. Muhammad A. Saleem & Hina Ismail & Rao Akmal Ali, 2021. "Actions Speak Louder than Words: Investigating the Interplay between Descriptive and Injunctive Norms to Promote Alternative Fuel Vehicles," Sustainability, MDPI, vol. 13(17), pages 1-17, August.
    24. Steg, Linda, 2005. "Car use: lust and must. Instrumental, symbolic and affective motives for car use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(2-3), pages 147-162.
    25. Dong Zhang & Jan-Dirk Schmöcker & Satoshi Fujii & Xiaoguang Yang, 2016. "Social norms and public transport usage: empirical study from Shanghai," Transportation, Springer, vol. 43(5), pages 869-888, September.
    26. Eesley, Charles & Wang, Yanbo, 2017. "Social influence in career choice: Evidence from a randomized field experiment on entrepreneurial mentorship," Research Policy, Elsevier, vol. 46(3), pages 636-650.
    27. Shires, J.D. & de Jong, G.C., 2009. "An international meta-analysis of values of travel time savings," Evaluation and Program Planning, Elsevier, vol. 32(4), pages 315-325, November.
    28. Piras, Francesco & Sottile, Eleonora & Tuveri, Giovanni & Meloni, Italo, 2022. "Does the joint implementation of hard and soft transportation policies lead to travel behavior change? An experimental analysis," Research in Transportation Economics, Elsevier, vol. 95(C).
    29. Maren Outwater & Greg Spitz & John Lobb & Margaret Campbell & Bhargava Sana & Ram Pendyala & William Woodford, 2011. "Characteristics of premium transit services that affect mode choice," Transportation, Springer, vol. 38(4), pages 605-623, July.
    30. Guiver, J.W., 2007. "Modal talk: Discourse analysis of how people talk about bus and car travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(3), pages 233-248, March.
    31. Wang, Chih-Hao & Akar, Gulsah & Guldmann, Jean-Michel, 2015. "Do your neighbors affect your bicycling choice? A spatial probit model for bicycling to The Ohio State University," Journal of Transport Geography, Elsevier, vol. 42(C), pages 122-130.
    32. Bhat, Chandra R., 1998. "Analysis of travel mode and departure time choice for urban shopping trips," Transportation Research Part B: Methodological, Elsevier, vol. 32(6), pages 361-371, August.
    33. Ashmore, David P. & Pojani, Dorina & Thoreau, Roselle & Christie, Nicola & Tyler, Nicholas A., 2019. "Gauging differences in public transport symbolism across national cultures: implications for policy development and transfer," Journal of Transport Geography, Elsevier, vol. 77(C), pages 26-38.
    34. Piras, Francesco & Sottile, Eleonora & Tuveri, Giovanni & Meloni, Italo, 2021. "Could psychosocial variables help assess pro-cycling policies?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 108-128.
    35. Bhat, Chandra R. & Pinjari, Abdul R. & Dubey, Subodh K. & Hamdi, Amin S., 2016. "On accommodating spatial interactions in a Generalized Heterogeneous Data Model (GHDM) of mixed types of dependent variables," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 240-263.
    36. Bhat, Chandra R. & Mondal, Aupal, 2022. "A New Flexible Generalized Heterogeneous Data Model (GHDM) with an Application to Examine the Effect of High Density Neighborhood Living on Bicycling Frequency," Transportation Research Part B: Methodological, Elsevier, vol. 164(C), pages 244-266.
    37. Joanna Moody & Elizabeth Farr & Marisa Papagelis & David R. Keith, 2021. "The value of car ownership and use in the United States," Nature Sustainability, Nature, vol. 4(9), pages 769-774, September.
    38. Börjesson, Maria & Rubensson, Isak, 2019. "Satisfaction with crowding and other attributes in public transport," Transport Policy, Elsevier, vol. 79(C), pages 213-222.
    39. Wardman, Mark & Chintakayala, V. Phani K. & de Jong, Gerard, 2016. "Values of travel time in Europe: Review and meta-analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 93-111.
    40. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
    41. Chandra R. Bhat & Subodh K. Dubey & Mohammad Jobair Bin Alam & Waleed H. Khushefati, 2015. "A New Spatial Multiple Discrete-Continuous Modeling Approach To Land Use Change Analysis," Journal of Regional Science, Wiley Blackwell, vol. 55(5), pages 801-841, November.
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