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Regular Articles

Social networks, social influence and activity-travel behaviour: a review of models and empirical evidence

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Pages 499-523 | Received 06 Feb 2017, Accepted 01 Jul 2017, Published online: 13 Jul 2017

References

  • Akerlof, G. A. (1997). Social distance and social decisions. Econometrica, 65(5), 1005–1027. doi: 10.2307/2171877
  • Arentze, T. A., & Timmermans, H. J. P. (2008). Social networks, social interaction, and activity-travel behavior: A framework for microsimulation. Environment and Planning B: Planning and Design, 35, 1012–1027. doi: 10.1068/b3319t
  • Axhausen, K. W. (2004a). Personal biography, social networks and travel behaviour: Hypotheses and assumptions. Paper presented at the Odyssey meeting, University of Ulster, Belfast.
  • Axhausen, K. W. (2004b). Personal biography, social networks and travel behaviour: Measurement and analysis. Paper presented at the Odyssey meeting, University of Ulster, Belfast.
  • Axhausen, K. W. (2005a, July). Geographies of social networks: The product of personal mobility biographies and generalised costs of contact?. Paper presented at the 37th world congress of the International Institute of Sociology, Stockholm, 2005.
  • Axhausen, K. W. (2005b). Social networks and travel: Some hypotheses. In K. Donaghy, S. Poppelreuter, & G. Rudinger (Eds.), Social dimensions of sustainable transport: Transatlantic perspectives (pp. 90–108). Aldershot: Ashgate.
  • Axhausen, K. W. (2007). Activity spaces, biographies, social networks and their welfare gains and externalities: Some hypotheses and empirical results. Mobilities, 2(1), 15–36. doi: 10.1080/17450100601106203
  • Axhausen, K. W. (2008). Social networks, mobility biographies, and travel: Survey challenges. Environment and Planning B: Planning and Design, 35, 981–996. doi: 10.1068/b3316t
  • Belgiawan, P. F., Schmöcker, J.-D., Abou-Zeid, M., Walker, J., & Fujii, S. (2017). Modelling social norms: Case study of students’ car purchase intentions. Travel Behavior and Society, 7, 12–25. doi: 10.1016/j.tbs.2016.11.003
  • Brock, W. A., & Durlauf, S. N. (2001). Discrete choice with social interactions. Review of Economic Studies, 68, 235–260. doi: 10.1111/1467-937X.00168
  • Brock, W. A., & Durlauf, S. N. (2002). A mutinomial-choice model of neighborhood effects. American Economic Association, 92(2), 298–303.
  • Brock, W. A., & Durlauf, S. N. (2007). Identification of binary choice models with social interactions. Journal of Econometrics, 140, 52–75. doi: 10.1016/j.jeconom.2006.09.002
  • Burt, R. S. (1984). Network items and the general social survey. Social Networks, 6, 293–339. doi: 10.1016/0378-8733(84)90007-8
  • Carrasco, J. A., Hogan, B., Wellman, B., & Miller, E. J. (2008a). Agency in social activity interactions: The role of social networks in time and space. Journal of Economic and Social Geography, 99(5), 562–583.
  • Carrasco, J. A., Hogan, B., Wellman, B., & Miller, E. J. (2008b). Collecting social network data to study social activity-travel behavior: An egocentric approach. Environment and Planning B: Planning and Design, 35, 961–980. doi: 10.1068/b3317t
  • Carrasco, J. A., & Miller, E. J. (2006). Exploring the propensity to perform social activities: A social network approach. Transportation, 33, 463–480. doi: 10.1007/s11116-006-8074-z
  • Carrasco, J. A., & Miller, E. J. (2009). The social dimension in action: A multilevel, personal networks model of social activity frequency between individuals. Transportation Research Part A, 43, 90–104.
  • Carrasco, J. A., Miller, E. J., & Wellman, B. (2008). How far and with whom do people socialize?: Empirical evidence about distance between social network members. Transportation Research Record: Journal of the Transportation Research Board, 2076, 114–122. doi: 10.3141/2076-13
  • Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591–621. doi: 10.1146/annurev.psych.55.090902.142015
  • Dugundji, E. R., & Gulyás, L. (2008). Sociodynamic discrete choice on networks in space: Impacts of agent heterogeneity on emergent outcomes. Environment and Planning B: Planning and Design, 35, 1028–1054. doi: 10.1068/b33021t
  • Dugundji, E. R., & Gulyás, L. (2013). Sociodynamic discrete choice on networks in space: The role of utility parameters and connectivity in emergent outcomes. Paper presented at the proceedings of the 92th annual meeting of the Transportation Research Board, Washington, DC (CD-ROM).
  • Dugundji, E. R., & Walker, J. (2005). Discrete choice with social and spatial network interdependencies: An empirical example using mixed generalized extreme value models with field and panel effects. Transportation Research Record: Journal of the Transportation Research Board, 1921, 70–78. doi: 10.3141/1921-09
  • Ettema, D., Arentze, T. A., & Timmermans, H. J. P. (2011). Social influences on household location, mobility and activity choice in integrated micro-simulation models. Transportation Research Part A: Policy and Practice, 45, 283–295.
  • Frei, A., & Axhausen, K. W. (2007). Size and structure of social network geographies. Arbeitsberichte Verkehrs­ und Raumplanung, 439, IVT, ETH Zürich, Zürich.
  • Frei, A., & Axhausen, K. W. (2008). Modelling the frequency of contacts in a shrunken world. Arbeitsberichte Verkehrs­ und Raumplanung, 532, IVT, ETH Zürich, Zürich.
  • Goetzke, F. (2008). Network effects in public transit use: Evidence from a spatially autoregressive mode choice model for New York. Urban Studies, 45(2), 407–417. doi: 10.1177/0042098007085970
  • Goetzke, F., & Rave, T. (2011). Bicycle use in Germany: Explaining differences between municipalities with social network effects. Urban Studies, 48(2), 427–437. doi: 10.1177/0042098009360681
  • Goetzke, F., & Weinberger, R. (2012). Separating contextual from endogenous effects in automobile ownership models. Environment and Planning A, 44, 1032–1046. doi: 10.1068/a4490
  • Habib, K., & Carrasco, J. A. (2011). Investigating the role of social network in start time and duration of activities: Trivariate simultaneous econometric model. Transportation Research Record: Journal of the Transportation Research Board, 2230, 1–8. doi: 10.3141/2230-01
  • Habib, K., Carrasco, J. A., & Miller, E. (2008). Social context of activity scheduling: Discrete-continuous model of relationship between “‘with whom”’ and episode start time and duration. Transportation Research Record: Journal of the Transportation Research Board, 2076, 81–87. doi: 10.3141/2076-09
  • Hackney, J., & Marchal, F. (2011). A coupled multi-agent microsimulation of social interactions and transportation behavior. Transportation Research Part A: Policy and Practice, 45, 296–309.
  • Han, Q., Arentze, T. A., Timmermans, H. J. P., Janssens, D., & Wets, G. (2011). The effects of social networks on choice set dynamics: Results of numerical simulations using an agent-based approach. Transportation Research Part A: Policy and Practice, 45, 310–322. doi: 10.1016/j.trb.2010.11.001
  • Kim, J., Rasouli, S., & Timmermans, H. J. P. (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, 69, 71–85.
  • Kim, J., Rasouli, S., & Timmermans, H. J. P. (2016). Investigating heterogeneity in social influence by social distance in car-sharing decisions under uncertainty: A regret-minimizing hybrid choice model framework based on sequential stated adaptation experiments. Paper presented at the proceedings of the 95th annual meeting of the Transportation Research Board, Washington, DC.
  • Kowald, M., & Axhausen, K. W. (2012). Focusing on connected personal leisure networks: Selected results from a snowball sample. Environment and Planning A, 44, 1085–1100. doi: 10.1068/a43458
  • Kowald, M., Van den Berg, P., Frei, A., Carrasco, J., Arentze, T. A., Axhausen, K., … Wellman, B. (2013). Distance patterns of personal networks in four countries: A comparative study. Journal of Transport Geography, 31, 236–248. doi: 10.1016/j.jtrangeo.2013.06.006
  • Kuwano, M., Tsukai, M., & Matsubara, T. (2012). Analysis on promoting factors of electric vehicles with social conformity. Paper presented at the 13th international conference on Travel Behaviour Research, Toronto, Canada, 15–20, July 2012.
  • Larsen, J., Urry, J., & Axhausen, K. W. (2006). Mobilities, networks and geographies. Aldershot: Ashgate.
  • Leenders, R. T. A. J. (2002). Modeling social influence through network autocorrelation: Constructing the weight matrix. Social Networks, 24, 21–47. doi: 10.1016/S0378-8733(01)00049-1
  • Lin, T., & Wang, D. (2014). Social networks and joint/solo activity-travel behavior. Transportation Research Part A, 68, 18–31.
  • Maness, M., & Cirillo, C. (2016). An indirect latent informational conformity social influence choice model: Formulation and case study. Transportation Research Part B: Methodological, 93, 75–101. doi: 10.1016/j.trb.2016.07.008
  • Manski, C. F. (1993). Identification of endogenous social effects: The reflection problem. The Review of Economic Studies, 60(3), 531–542. doi: 10.2307/2298123
  • McCallister, L., & Fischer, C. (1978). A procedure for surveying personal networks. Sociological Methods and Research, 7, 131–148. doi: 10.1177/004912417800700202
  • Mok, D., Wellman, B., & Carrasco, J. (2010). Does distance matter in the age of the Internet. Urban Studies, 47(13), 2747–2783. doi: 10.1177/0042098010377363
  • Moore, J., Carrasco, J. A., & Tudela, A. (2013). Exploring the links between personal networks, time use, and the spatial distribution of social contacts. Transportation, 40, 773–788. doi: 10.1007/s11116-013-9467-4
  • Ohnmacht, T. (2009). Social-activity travel behaviour: Do the “strong-tie relationships” exist in the same community? The case of Switzerland. Environment and Planning A, 41(12), 3003–3022. doi: 10.1068/a41396
  • Ohnmacht, T., & Axhausen, K. W. (2005). Entwicklung des Forschungsdesign und der Erhebungsinstrumente für das Projekt Mobilitätsbiographien, Mobilitätswerkzeuge und soziale Netze, Arbeitsberichte Verkehrs- und Raumplanung, 298, IVT, ETH Zürich, Zürich.
  • Okushima, M. (2015). Simulating social influences on sustainable mobility shifts for heterogeneous agents. Transportation, 42, 827–855. doi: 10.1007/s11116-015-9649-3
  • Páez, A., & Scott, D. M. (2007). Social influence on travel behavior: A simulation example of the decision to telecommute. Environment and Planning A, 39, 647–665. doi: 10.1068/a37424
  • Páez, A., Scott, D. M., & Volz, E. (2008). A discrete-choice approach to modeling social influence on individual decision making. Environment and Planning B: Planning and Design, 35, 1055–1069. doi: 10.1068/b3320t
  • Pike, S. (2014). Travel mode choice and social and spatial reference groups: Comparison of two formulations. Transportation Research Record: Journal of the Transportation Research Board, 2412, 75–81. doi: 10.3141/2412-09
  • Pike, S. (2015). Endogeneity in social influence and transportation mode choice using ego-networks. Paper presented at the proceedings of the 94th annual meeting of the Transportation Research Board, Washington, DC.
  • Pike, S., & Lubell, M. (2016). Geography and social networks in transportation mode choice. Journal of Transport Geography, 57, 184–193. doi: 10.1016/j.jtrangeo.2016.10.009
  • Rasouli, S., & Timmermans, H. J. P. (2013). Incorporating mechanisms of social adoption in design and analysis of stated-choice experiments. Transportation Research Record: Journal of the Transportation Research Board, 2344, 10–19. doi: 10.3141/2344-02
  • Rasouli, S., & Timmermans, H. J. P. (2014). Activity-based models of travel demand: Promises, progress and prospects. International Journal of Urban Sciences, 18, 31–60. doi: 10.1080/12265934.2013.835118
  • Rasouli, S., & Timmermans, H. J. P. (2016). Influence of social networks on latent choice of electric cars: A mixed logit specification using experimental design data. Networks and Spatial Economics, 16, 99–130. doi: 10.1007/s11067-013-9194-6
  • Rezende, P. H. R., Sadri, A. M., & Ukkusuri, S. V. (2016). Social network influence on mode choice and carpooling during special events: The case of Purdue game day. Paper presented at the proceedings of the 95th annual meeting of the Transportation Research Board, Washington, DC.
  • Schlich, R., Schőnfelder, S., Hanson, S., & Axhausen, K. W. (2004). Structures of leisure travel: Temporal and spatial variability. Transport Reviews, 24(2), 219–237. doi: 10.1080/0144164032000138742
  • Sharmeen, F., Arentze, T. A., & Timmermans, H. J. P. (2014). Dynamics of face-to-face social interaction frequency: Role of accessibility, urbanization, changes in geographical distance and path dependence. Journal of Transport Geography, 34, 211–220. doi: 10.1016/j.jtrangeo.2013.12.011
  • Sharmeen, F., & Timmermans, H. J. P. (2014). Walking down the habitual lane: Analyzing path dependence effects of mode choice for social trips. Journal of Transport Geography, 39, 222–227. doi: 10.1016/j.jtrangeo.2014.07.012
  • Silvis, J., Niemeier, D., & D’Souza, R. (2006). Social networks and travel behavior: Report from an integrated travel diary. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto.
  • Tan, T., Chua, V., & Axhausen, K. W. (2015). Ego networks and social geographies in Singapore, presentation at Frontiers in Transportation - Workshop, Windsor.
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2010). Location-type choice for face-to-face social activities and its effect on travel behavior. Environment and Planning B: Planning and Design, 37, 1057–1075. doi: 10.1068/b36019
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2012a). A latent class accelerated hazard model of social activity duration. Transportation Research Part A, 46, 12–21.
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2012b). A multilevel path analysis of contact frequency between social network members. Journal of Geographical Systems, 14, 125–141. doi: 10.1007/s10109-010-0138-0
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2012c). Involvement in clubs or voluntary associations, social networks and activity generation: A path analysis. Transportation, 39, 843–856. doi: 10.1007/s11116-012-9403-z
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2013). A path analysis of social networks, telecommunication and social activity-travel patterns. Transportation Research Part C: Emerging Technologies, 26, 256–268. doi: 10.1016/j.trc.2012.10.002
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2015). A multilevel analysis of factors influencing local social interaction. Transportation, 42, 807–826. doi: 10.1007/s11116-015-9648-4
  • Van den Berg, P., Kemperman, A., & Timmermans, H. J. P. (2014). Social interaction location choice: A latent class modeling approach. Annals of the Association of American Geographers, 104, 959–972. doi: 10.1080/00045608.2014.924726
  • Van den Berg, P., Arentze, T. A., & Timmermans, H. J. P. (2009). Size and composition of ego-centered social networks and their effect on geographic distance and contact frequency. Transportation Research Record: Journal of the Transportation research Board, 2135, 1–9. doi: 10.3141/2135-01
  • Van der Poel, M. G. M. (1993). Delineating personal support networks. Social Networks, 15, 49–70. doi: 10.1016/0378-8733(93)90021-C
  • Walker, J., Ehlers, E., Banerjee, I., & Dugundji, E. R. (2011). Correcting for endogeneity in behavioral choice models with social influence variables. Transportation Research Part A: Policy and Practice, 45, 362–374.
  • Xiao, Y., & Lo, H. K. (2016). Day-to-day departure time modeling under social network influence. Transportation Research Part B: Methodological, 92, 54–72. doi: 10.1016/j.trb.2016.05.006