Advertisement

Demand for Green Refueling Infrastructure

  • Tamara L. SheldonEmail author
  • J. R. DeShazo
  • Richard T. Carson
Article

Abstract

Despite increasing public investment in charging infrastructure for plug-in electric vehicles (PEVs), policymakers know little about drivers’ preferences for publicly-accessible charging stations. Using data from an innovative choice experiment, we estimate demand for PEV charging stations, characterizing willingness to pay for access to types of locations as well as driver tradeoffs between refueling duration and costs. Prospective PEV drivers are willing to pay the actual variable cost of recharging at public charging stations and are willing to pay to cover significant fixed costs at select locations. Not surprisingly, many prospective drivers reveal a positive willingness to accept to wait while refueling, but this varies greatly across latent classes.

Keywords

Choice experiment Transportation policy Clean transportation Electric vehicles 

Notes

References

  1. Achtnicht M, Georg B, Hermeling C (2012) The impact of fuel availability on demand for alternative-fuel vehicles. Transp Res Part D: Transp Environ 17(3):262–269CrossRefGoogle Scholar
  2. Bozdogan H (1987) ICOMP: a new model-selection criterion. In: 1. Conference of the international federation of classification societies, pp 599–608Google Scholar
  3. Brownstone D, Bunch DS, Train K (2000) Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles. Transp Res Part B: Methodol 34(5):315–338CrossRefGoogle Scholar
  4. Bunch DS, Bradley M, Golob TF, Kitamura R, Occhiuzzo GP (1993) Demand for clean-fuel vehicles in California: a discrete-choice stated preference pilot project. Transp Res Part A: Policy Pract 27(3):237–253CrossRefGoogle Scholar
  5. California Department of Transportation (Caltrans) (2013) California household travel survey final survey reportGoogle Scholar
  6. Chen TD, Kockelman KM, Kahn M (2013) The electric vehicle charging station location problem: a parking-based assessment method for Seattle. Transp Res Rec 1254(28–36):2013Google Scholar
  7. DeShazo JR, Song CC, Sinn M, Gariffo T (2015) State of the states’ plug-in electric vehicle policies, UCLA Luskin Center ReportGoogle Scholar
  8. Eisel M, Schmidt J, Kolbe LM (2014) Finding suitable locations for charging stations: implementation of customers’ preferences in an allocation problem. In: IEEE international electric vehicle conference (IEVC), Florence, pp 1–8Google Scholar
  9. Ewing G, Emine S (2000) Assessing consumer preferences for clean-fuel vehicles: a discrete choice experiment. J Public Policy Mark 19(1):106–118CrossRefGoogle Scholar
  10. Franke T, Neumann I, Bühler F, Cocron P, Krems JF (2012) Experiencing range in an electric vehicle: understanding psychological barriers. Appl Psychol: Int Rev 61:368–391CrossRefGoogle Scholar
  11. Golob Thomas F, Bunch David S, David B (1997) A vehicle use forecasting model based on revealed and stated vehicle type choice and utilisation data. J Transp Econ Policy 1997:69–92Google Scholar
  12. Hidrue MK, George RP, Willett K, Meryl PG (2011) Willingness to pay for electric vehicles and their attributes. Res Energy Econ 33(3):686–705CrossRefGoogle Scholar
  13. Ito N, Kenji T, Shunsuke M (2013) Willingness-to-pay for infrastructure investments for alternative fuel vehicles. Transp Res Part D: Transp Environ 18:1–8CrossRefGoogle Scholar
  14. Jia L, Hu Z, Liang W, Tang W, Song Y (2014) A novel approach for urban electric vehicle charging facility planning considering combination of slow and fast charging. In: International conference on power system technology (POWERCON), Chengdu, pp 3354–3360Google Scholar
  15. Kitamura M, Hagiwara Y (2010) Honda ‘lacks confidence’ in electric-car demand. Bloomberg.com. http://www.bloomberg.com/apps/news?pid=newsarchive&sid=a_kxOOLkD.cU. Accessed 5 May 2017
  16. Kurani KS, Thomas T, Daniel S (1996) Testing electric vehicle demand in ‘hybrid households’ using a reflexive survey. Transp ResPart D 1(2):131–150CrossRefGoogle Scholar
  17. Li S, Lang T, Jianwei X, Yiyi Z (2017) The market for electric vehicles: indirect network effects and policy design. J Assoc Environ Res Econ 4(1):89–133Google Scholar
  18. McFadden D (1974) Conditional logit analysis of qualitative choice behaviour. In: Zarembka P (ed) Frontiers in econometrics. Academic Press, New York, pp 105–142Google Scholar
  19. Nylund KL, Tihomir A, Muthén BO (2007) Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Model 14(4):535–569CrossRefGoogle Scholar
  20. Potoglou D, Kanaroglou PS (2007) Household demand and willingness to pay for clean vehicles. Transp Res Part D: Transp Environ 12(4):264–274CrossRefGoogle Scholar
  21. Qian L, Didier S (2011) Heterogeneous consumer preferences for alternative fuel cars in China. Transp Res Part D: Transp Environ 16(8):607–613CrossRefGoogle Scholar
  22. Revelt D, Train K (1999) Customer-specific taste parameters and mixed logit. In: Working Paper. University of California, BerkeleyGoogle Scholar
  23. Scasny M, Zverinova I, Czajkowski M (2015) Individual preference for the alternative fuel vehicles and their attributes in Poland. No 8575, EcoMod2015, EcoMod. https://EconPapers.repec.org/RePEc:ekd:008007:8575. Accessed 5 May 2017
  24. Scarpa R, Rose JM (2008) Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why. Aust J Agric Res Econ 52(3):253–282CrossRefGoogle Scholar
  25. Sheldon TL, DeShazo JR (2017) How does the presence of HOV lanes affect plug-in electric vehicle adoption in California? A generalized propensity score approach. J Environ Econ Manag 85:146–170CrossRefGoogle Scholar
  26. Sheldon TL, DeShazo JR, Carson RT (2017) Electric and plug-in hybrid vehicle demand: lessons for an emerging market. Econ Inq 55(2):695–713CrossRefGoogle Scholar
  27. Sweda T, Klabjan D (2011) An agent-based decision support system for electric vehicle charging infrastructure deployment. In: 7th IEEE vehicle power and propulsion conference, IllinoisGoogle Scholar
  28. Train KE (1998) Recreation demand models with taste differences over people. Land Econ 74(2):230–239CrossRefGoogle Scholar
  29. Williams B, DeShazo JR (2014) Pricing workplace charging: financial viability and fueling costs. In: Transportation Research Board 93rd annual meeting, no. 14-1137Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of EconomicsUniversity of South CarolinaColumbiaUSA
  2. 2.Luskin School of Public AffairsUniversity of CaliforniaLos AngelesUSA
  3. 3.Department of EconomicsUniversity of CaliforniaSan DiegoUSA

Personalised recommendations