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Public Acceptance of Green Mobility Policies: An Agent-Based Model

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Advances in Social Simulation (ESSA 2022)

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Abstract

We present an agent-based model to simulate policy acceptance for push and pull policy measures. Push measures are generally perceived as restrictive and are often directed towards the reduction of private car use, e.g. fuel price increases and inner-city car bans. Pull measures relate to diverse incentives to facilitate climate-friendly travel choices, e.g. attractive offers for public transport such as interregional cost reductions and expansion of the public transport infrastructure. The model is informed by empirical data regarding agents’ travel mode utilities and allows to evaluate agents’ satisfaction and acceptance of diverse policy scenarios. Regional dependencies are tested for the case of Austria. The results show that the political acceptance of push measures increases when they are combined in packages of measures considering the expansion of public transport infrastructure. Furthermore, the general acceptance of green mobility measures is closely linked to the existing infrastructure of the individual districts.

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Notes

  1. 1.

    Original answer categories of study 1 and 2 had to be adjusted to be comparable.

References

  1. Adnan, M., Outay, F., Ahmed, S., Brattich, E., Di Sabatino, S., Janssens, D.: Integrated agent-based microsimulation framework for examining impacts of mobility-oriented policies. Pers. Ubiquit. Comput. 25(1), 205–217 (2021)

    Article  Google Scholar 

  2. Ahanchian, M., Gregg, J.S., Tattini, J., Karlsson, K.B.: Analyzing effects of transport policies on travelers’ rational behaviour for modal shift in Denmark. Case Stud. Transp. Policy 7(4), 849–861 (2019)

    Article  Google Scholar 

  3. Axsen, J., Plötz, P., Wolinetz, M.: Crafting strong, integrated policy mixes for deep CO2 mitigation in road transport. Nat. Clim. Change 10(9), 809–818 (2020)

    Article  ADS  Google Scholar 

  4. Banister, D., Hickman, R.: Transport futures: thinking the unthinkable. Transp. Policy 29, 283–293 (2013). https://doi.org/10.1016/j.tranpol.2012.07.005

    Article  Google Scholar 

  5. Drews, S., van den Bergh, J.C.: What explains public support for climate policies? A review of empirical and experimental studies. Clim. Policy 16(7), 855–876 (2016)

    Article  Google Scholar 

  6. Engler, D., Groh, E.D., Gutsche, G., Ziegler, A.: Acceptance of climate-oriented policy measures under the COVID-19 crisis: an empirical analysis for Germany. Clim. Policy 21(10), 1281–1297 (2021)

    Article  Google Scholar 

  7. Givoni, M.: Addressing transport policy challenges through policy-packaging. Transp. Res. Part A: Policy Prac. 60, 1–8 (2014)

    Google Scholar 

  8. Hajinasab, B., Davidsson, P., Persson, J.A., Holmgren, J.: Towards an agent-based model of passenger transportation. In: International Workshop on Multi-Agent Systems and Agent-Based Simulation, pp. 132–145. Springer (2015)

    Google Scholar 

  9. Heinfellner, H., Ibesich, N., Lichtblau, G., Stranner, G., Svehla-Stix, S., Vogel, J., Wedler, M., Winter, R.: Sachstandsbericht mobilität und mögliche zielpfade zur erreichung der klimaziele 2050 mit dem zwischenziel 2030. UBA. Rep-0667. Im Auftrag des BMVIT (2018)

    Google Scholar 

  10. Helbing, D.: Agent-based modeling. In: Social Self-Organization, pp. 25–70. Springer (2012)

    Google Scholar 

  11. Huang, X., Lin, Y., Zhou, F., Lim, M.K., Chen, S.: Agent-based modelling for market acceptance of electric vehicles: evidence from China. Sustain. Prod. Consum. 28, 206–217 (2021)

    Article  Google Scholar 

  12. Huétink, F.J., van der Vooren, A., Alkemade, F.: Initial infrastructure development strategies for the transition to sustainable mobility. Technol. Forecast. Soc. Change 77(8), 1270–1281 (2010)

    Article  Google Scholar 

  13. Köhler, J., Whitmarsh, L., Nykvist, B., Schilperoord, M., Bergman, N., Haxeltine, A.: A transitions model for sustainable mobility. Ecol. Econ. 68(12), 2985–2995 (2009)

    Article  Google Scholar 

  14. Maggi, E., Vallino, E.: Understanding urban mobility and the impact of public policies: the role of the agent-based models. Res. Transp. Econ. 55, 50–59 (2016)

    Article  Google Scholar 

  15. Maggi, E., Vallino, E.: Price-based and motivation-based policies for sustainable urban commuting: an agent-based model. Research in Transportation Business & Management 39, 100,588 (2021)

    Google Scholar 

  16. Mehdizadeh, M., Nordfjaern, T., Klöckner, C.: A systematic review of the agent-based modelling/simulation paradigm in mobility transition. Simul Paradigm Mobil Trans (2022)

    Google Scholar 

  17. Mueller, M.G., De Haan, P.: How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars-Part I: Model structure, simulation of bounded rationality, and model validation. Energy Policy 37(3), 1072–1082 (2009)

    Article  Google Scholar 

  18. Müller, M., Reutter, P.O.: Course change: navigating urban passenger transport toward sustainability through modal shift. Int. J. Sustain. Transp. 1–25 (2021)

    Google Scholar 

  19. Ormerod, P., Rosewell, B.: Validation and verification of agent-based models in the social sciences. In: International Workshop on Epistemological Aspects of Computer Simulation in the Social Sciences, pp. 130–140. Springer (2006)

    Google Scholar 

  20. Pörtner, H.O., Roberts, D.C., Adams, H., Adler, C., Aldunce, P., Ali, E., Begum, R.A., Betts, R., Kerr, R.B., Biesbroek, R., et al.: Climate change 2022: impacts, adaptation and vulnerability. In: IPCC Sixth Assessment Report (2022)

    Google Scholar 

  21. Silvia, C., Krause, R.M.: Assessing the impact of policy interventions on the adoption of plug-in electric vehicles: an agent-based model. Energy Policy 96, 105–118 (2016)

    Article  Google Scholar 

  22. Sopha, B.M., Klöckner, C.A., Febrianti, D.: Using agent-based modeling to explore policy options supporting adoption of natural gas vehicles in Indonesia. J. Environ. Psychol. 52, 149–165 (2017)

    Article  Google Scholar 

  23. Thaller, A., Posch, A., Dugan, A., Steininger, K.: How to design policy packages for sustainable transport: balancing disruptiveness and implement ability. Transp. Res. Part D: Transp. Environ. 91, 102–714 (2021)

    Google Scholar 

  24. Tsoi, K.H., Loo, B.P., Banister, D.: “Mind the (policy-implementation) gap”: transport decarbonisation policies and performances of leading global economies (1990–2018). Global Environ. Change 68, 102–250 (2021)

    Google Scholar 

  25. Unruh, G.C.: Escaping carbon lock-in. Energy Policy 317–325 (2002)

    Google Scholar 

  26. Wicki, M., Huber, R.A., Bernauer, T.: Can policy-packaging increase public support for costly policies? Insights from a choice experiment on policies against vehicle emissions. J. Public Policy 40(4), 599–625 (2020)

    Article  Google Scholar 

  27. Wolf, I., Schröder, T., Neumann, J., de Haan, G.: Changing minds about electric cars: an empirically grounded agent-based modeling approach. Technol. Forecasting Soc. Change 94, 269–285 (2015)

    Article  Google Scholar 

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Correspondence to Marie Lisa Kogler .

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Kogler, M.L., Thaller, A., Reisinger, D. (2023). Public Acceptance of Green Mobility Policies: An Agent-Based Model. In: Squazzoni, F. (eds) Advances in Social Simulation. ESSA 2022. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-031-34920-1_41

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