IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v313y2022ics0306261922002410.html
   My bibliography  Save this article

Optimizing urban electric vehicle incentive policy mixes in China: Perspective of residential preference heterogeneity

Author

Listed:
  • Qiu, Y.Q.
  • Tsan Sheng Ng, Adam
  • Zhou, P.

Abstract

The large-scale diffusion of electric vehicles (EVs) helps pave the way towards carbon peak and neutrality goals, while it is affected by the governmental incentive policies at different levels. This paper studies the optimization of demand-side policy mixes from the perspective of residential preference heterogeneity with 18 EV pilot cities in China as the case. A latent class model is used to investigate urban residents’ preferences for demand-side policies and characterization of urban heterogeneities of the preferences. Valid survey data from 1455 respondents were collected from a stated preference experiment, which segmented urban residents into a “policy-sensitive” group (8.25% of the sample), “policy-indifferent” group (27.97%), and “policy-cognitive” group according to their preferences. The 18 pilot cities were grouped into three clusters according to the different compositions of the preference segments. Our analysis shows that it may not be necessary for the municipal governments to provide subsidies for the installations of home chargers currently. Besides, different optimized policy mixes of bus lane access privileges, replacement subsidies, toll discounts, and preferential parking fees for charging were proposed for the three clusters of cities. Our research paradigm applies to cities in other countries that need to optimize EV policy mixes.

Suggested Citation

  • Qiu, Y.Q. & Tsan Sheng Ng, Adam & Zhou, P., 2022. "Optimizing urban electric vehicle incentive policy mixes in China: Perspective of residential preference heterogeneity," Applied Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:appene:v:313:y:2022:i:c:s0306261922002410
    DOI: 10.1016/j.apenergy.2022.118794
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922002410
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.118794?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kanchanaroek, Yingluck & Aslam, Uzma, 2018. "Policy schemes for the transition to sustainable agriculture—Farmer preferences and spatial heterogeneity in northern Thailand," Land Use Policy, Elsevier, vol. 78(C), pages 227-235.
    2. Nian, Victor & Hari, M.P. & Yuan, Jun, 2019. "A new business model for encouraging the adoption of electric vehicles in the absence of policy support," Applied Energy, Elsevier, vol. 235(C), pages 1106-1117.
    3. Yoo, James & Ready, Richard C., 2014. "Preference heterogeneity for renewable energy technology," Energy Economics, Elsevier, vol. 42(C), pages 101-114.
    4. Linder, Stephen H. & Peters, B. Guy, 1990. "Policy formulation and the challenge of conscious design," Evaluation and Program Planning, Elsevier, vol. 13(3), pages 303-311, January.
    5. Richard Carson & Theodore Groves, 2007. "Incentive and informational properties of preference questions," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 37(1), pages 181-210, May.
    6. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    7. Parsons, George R. & Hidrue, Michael K. & Kempton, Willett & Gardner, Meryl P., 2014. "Willingness to pay for vehicle-to-grid (V2G) electric vehicles and their contract terms," Energy Economics, Elsevier, vol. 42(C), pages 313-324.
    8. Page, Benjamin I. & Shapiro, Robert Y., 1983. "Effects of Public Opinion on Policy," American Political Science Review, Cambridge University Press, vol. 77(1), pages 175-190, March.
    9. Kong, Deyang & Xia, Quhong & Xue, Yixi & Zhao, Xin, 2020. "Effects of multi policies on electric vehicle diffusion under subsidy policy abolishment in China: A multi-actor perspective," Applied Energy, Elsevier, vol. 266(C).
    10. Wee, Sherilyn & Coffman, Makena & La Croix, Sumner, 2018. "Do electric vehicle incentives matter? Evidence from the 50 U.S. states," Research Policy, Elsevier, vol. 47(9), pages 1601-1610.
    11. Ou, Shiqi & Hao, Xu & Lin, Zhenhong & Wang, Hewu & Bouchard, Jessey & He, Xin & Przesmitzki, Steven & Wu, Zhixin & Zheng, Jihu & Lv, Renzhi & Qi, Liang & LaClair, Tim J., 2019. "Light-duty plug-in electric vehicles in China: An overview on the market and its comparisons to the United States," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 747-761.
    12. Lee, Yongseung & Kim, Chongman & Shin, Juneseuk, 2016. "A hybrid electric vehicle market penetration model to identify the best policy mix: A consumer ownership cycle approach," Applied Energy, Elsevier, vol. 184(C), pages 438-449.
    13. Charles R. Shipan & Craig Volden, 2008. "The Mechanisms of Policy Diffusion," American Journal of Political Science, John Wiley & Sons, vol. 52(4), pages 840-857, October.
    14. Kwon, Yeongmin & Son, Sanghoon & Jang, Kitae, 2018. "Evaluation of incentive policies for electric vehicles: An experimental study on Jeju Island," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 404-412.
    15. Wang, Shanyong & Wang, Jing & Li, Jun & Wang, Jinpeng & Liang, Liang, 2018. "Policy implications for promoting the adoption of electric vehicles: Do consumer’s knowledge, perceived risk and financial incentive policy matter?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 58-69.
    16. Meckling, Jonas & Nahm, Jonas, 2019. "The politics of technology bans: Industrial policy competition and green goals for the auto industry," Energy Policy, Elsevier, vol. 126(C), pages 470-479.
    17. Han, Liu & Wang, Shanyong & Zhao, Dingtao & Li, Jun, 2017. "The intention to adopt electric vehicles: Driven by functional and non-functional values," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 185-197.
    18. Egmond, C. & Jonkers, R. & Kok, G., 2006. "One size fits all? Policy instruments should fit the segments of target groups," Energy Policy, Elsevier, vol. 34(18), pages 3464-3474, December.
    19. Wang, Ning & Tang, Linhao & Pan, Huizhong, 2017. "Effectiveness of policy incentives on electric vehicle acceptance in China: A discrete choice analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 105(C), pages 210-218.
    20. Qiu, Y.Q. & Zhou, P. & Sun, H.C., 2019. "Assessing the effectiveness of city-level electric vehicle policies in China," Energy Policy, Elsevier, vol. 130(C), pages 22-31.
    21. Louviere,Jordan J. & Hensher,David A. & Swait,Joffre D., 2000. "Stated Choice Methods," Cambridge Books, Cambridge University Press, number 9780521788304, September.
    22. Anders Skonhoft & Bjart Holtsmark, 2014. "The Norwegian support and subsidy of electric cars. Should it be adopted by other countries?," Working Paper Series 15814, Department of Economics, Norwegian University of Science and Technology.
    23. Axsen, Jonn & Bailey, Joseph & Castro, Marisol Andrea, 2015. "Preference and lifestyle heterogeneity among potential plug-in electric vehicle buyers," Energy Economics, Elsevier, vol. 50(C), pages 190-201.
    24. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, September.
    25. Yang, Shu & Cheng, Peng & Li, Jun & Wang, Shanyong, 2019. "Which group should policies target? Effects of incentive policies and product cognitions for electric vehicle adoption among Chinese consumers," Energy Policy, Elsevier, vol. 135(C).
    26. Abotalebi, Elnaz & Scott, Darren M. & Ferguson, Mark R., 2019. "Why is electric vehicle uptake low in Atlantic Canada? A comparison to leading adoption provinces," Journal of Transport Geography, Elsevier, vol. 74(C), pages 289-298.
    27. Makena Coffman & Paul Bernstein & Sherilyn Wee, 2017. "Electric vehicles revisited: a review of factors that affect adoption," Transport Reviews, Taylor & Francis Journals, vol. 37(1), pages 79-93, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Yiran & Zhao, Xiaolei & Lu, Dan & Li, Xiaomin, 2023. "Impact of policy incentives on the adoption of electric vehicle in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    2. Xu, Shuling & Yang, Zihan & Deng, Nana & Wang, Bo, 2024. "Residents' willingness to be compensated for power rationing during peak hours based on choice experiment," Applied Energy, Elsevier, vol. 367(C).
    3. Zhang, Qi & Liu, Jiangfeng & Yang, Kexin & Liu, Boyu & Wang, Ge, 2022. "Market adoption simulation of electric vehicle based on social network model considering nudge policies," Energy, Elsevier, vol. 259(C).
    4. Li, Ze & Guo, Junfei & Gao, Xinyu & Yang, Xiaohu & He, Ya-Ling, 2023. "A multi-strategy improved sparrow search algorithm of large-scale refrigeration system: Optimal loading distribution of chillers," Applied Energy, Elsevier, vol. 349(C).
    5. Zhu, Qingyuan & Xu, Chengzhen & Chen, Qingjuan & Wu, Liangpeng, 2024. "Oil price distortion and its impact on green economic efficiency in China’s transportation: A spatial effect perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Lixu & Wang, Zhiqiang & Xie, Xiaoqing, 2022. "From government to market? A discrete choice analysis of policy instruments for electric vehicle adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 160(C), pages 143-159.
    2. Mekky, Maher F. & Collins, Alan R., 2024. "The Impact of state policies on electric vehicle adoption -A panel data analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    3. Nie, Qingyun & Zhang, Lihui & Li, Songrui, 2022. "How can personal carbon trading be applied in electric vehicle subsidies? A Stackelberg game method in private vehicles," Applied Energy, Elsevier, vol. 313(C).
    4. Yao, Xusheng & Ma, Shoufeng & Bai, Yin & Jia, Ning, 2022. "When are new energy vehicle incentives effective? Empirical evidence from 88 pilot cities in China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 207-224.
    5. Jia, Wenjian & Jiang, Zhiqiu & Wang, Qian & Xu, Bin & Xiao, Mei, 2023. "Preferences for zero-emission vehicle attributes: Comparing early adopters with mainstream consumers in California," Transport Policy, Elsevier, vol. 135(C), pages 21-32.
    6. Peng, Yuan & Bai, Xuemei, 2023. "What EV users say about policy efficacy: Evidence from Shanghai," Transport Policy, Elsevier, vol. 132(C), pages 16-26.
    7. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Hubacek, Klaus, 2022. "Strategies for applying carbon trading to the new energy vehicle market in China: An improved evolutionary game analysis for the bus industry," Energy, Elsevier, vol. 259(C).
    8. Philip, Thara & Whitehead, Jake & Prato, Carlo G., 2023. "Adoption of electric vehicles in a laggard, car-dependent nation: Investigating the potential influence of V2G and broader energy benefits on adoption," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    9. Yang, Shu & Cheng, Peng & Li, Jun & Wang, Shanyong, 2019. "Which group should policies target? Effects of incentive policies and product cognitions for electric vehicle adoption among Chinese consumers," Energy Policy, Elsevier, vol. 135(C).
    10. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    11. Zulfiqar Ali Lashari & Joonho Ko & Seunghyun Jung & Sungtaek Choi, 2022. "Choices of Potential Car Buyers Regarding Alternative Fuel Vehicles in South Korea: A Discrete Choice Modeling Approach," Sustainability, MDPI, vol. 14(9), pages 1-17, April.
    12. Adu-Gyamfi, Gibbson & Asamoah, Ama Nyarkoh & Obuobi, Bright & Nketiah, Emmanuel & Zhang, Ming, 2024. "Electric mobility in an oil-producing developing nation: Empirical assessment of electric vehicle adoption," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    13. Jia, Wenjian & Chen, T. Donna, 2023. "Investigating heterogeneous preferences for plug-in electric vehicles: Policy implications from different choice models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    14. Wang, Xiao-Wu & Cao, Yu-Mei & Zhang, Ning, 2021. "The influences of incentive policy perceptions and consumer social attributes on battery electric vehicle purchase intentions," Energy Policy, Elsevier, vol. 151(C).
    15. Shao, Jing & Jiang, Changmin & Cui, Yinglong & Tang, Yao, 2023. "A game-theoretic model to compare charging infrastructure subsidy and electric vehicle subsidy policies," Transportation Research Part A: Policy and Practice, Elsevier, vol. 176(C).
    16. Kim, Junghun & Seung, Hyunchan & Lee, Jongsu & Ahn, Joongha, 2020. "Asymmetric preference and loss aversion for electric vehicles: The reference-dependent choice model capturing different preference directions," Energy Economics, Elsevier, vol. 86(C).
    17. Jacobus Nel & Roula Inglesi-Lotz, 2022. "Electric Vehicles Market and Policy Conditions: Identifying South African Policy ``Potholes"," Working Papers 202257, University of Pretoria, Department of Economics.
    18. Scheufele, Gabriela & Bennett, Jeffrey W., 2010. "Ordering effects and strategic response in discrete choice experiments," Research Reports 107743, Australian National University, Environmental Economics Research Hub.
    19. Zhang, Tong & Burke, Paul J. & Wang, Qi, 2024. "Effectiveness of electric vehicle subsidies in China: A three-dimensional panel study," Resource and Energy Economics, Elsevier, vol. 76(C).
    20. Manhique, Henrique & Wätzold, Frank, 2023. "Effects of Institutional Setting on Value Estimates of Stated Preference Surveys in Developing Economies: A Discrete Choice Experiment on Conserving Biodiversity in The Cape Floristic Region," MPRA Paper 118750, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:313:y:2022:i:c:s0306261922002410. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.