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Are people willing to pay more for new energy bus fares?

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  • Lin, Boqiang
  • Tan, Ruipeng

Abstract

This paper adopts the contingent valuation method to study people's willingness to pay for the adoption of new energy buses in the four most developed cities of China: Beijing, Shanghai, Guangzhou and Shenzhen. An interval regression model is employed to analyze the influencing factors of people's willingness to pay and estimate the exact amount of extra money people would pay per fare. The results show that approximately eighty percent of the respondents in the four cities would like to pay extra fare to support the adoption of new energy buses and the specific amount is 0.653 RMB/fare among all the respondents. Those with higher household income, who are younger, who think the adoption can significantly improve air quality and who deem that they live in a place with good air quality are willing to pay higher. But public concern about energy security issue in China does not have significant impact on the willingness to pay. It is therefore recommended that setting a higher price for new energy bus fare is reasonable and more knowledge of new energy buses should be conveyed to the public, especially its purpose of improving air quality and alleviating the high pressure of energy security.

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  • Lin, Boqiang & Tan, Ruipeng, 2017. "Are people willing to pay more for new energy bus fares?," Energy, Elsevier, vol. 130(C), pages 365-372.
    • Handle: RePEc:eee:energy:v:130:y:2017:i:c:p:365-372
    DOI: 10.1016/j.energy.2017.04.153
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    Cited by:

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    3. Tan, Ruipeng & Lin, Boqiang, 2019. "Public perception of new energy vehicles: Evidence from willingness to pay for new energy bus fares in China," Energy Policy, Elsevier, vol. 130(C), pages 347-354.
    4. A. Saidi & G. Sacchi & C. Cavallo & G. Cicia & R. Di Monaco & S. Puleo & T. Del Giudice, 2022. "Drivers of fish choice: an exploratory analysis in Mediterranean countries," Agricultural and Food Economics, Springer;Italian Society of Agricultural Economics (SIDEA), vol. 10(1), pages 1-25, December.
    5. Harris, Andrew & Soban, Danielle & Smyth, Beatrice M. & Best, Robert, 2020. "A probabilistic fleet analysis for energy consumption, life cycle cost and greenhouse gas emissions modelling of bus technologies," Applied Energy, Elsevier, vol. 261(C).
    6. Anna Brdulak & Grażyna Chaberek & Jacek Jagodziński, 2020. "Development Forecasts for the Zero-Emission Bus Fleet in Servicing Public Transport in Chosen EU Member Countries," Energies, MDPI, vol. 13(16), pages 1-20, August.
    7. Ji-Hee Son & Jeawon Kim & Wona Lee & Songhee Han, 2022. "Willingness to Pay for the Public Electric Bus in Nepal: A Contingent Valuation Method Approach," Sustainability, MDPI, vol. 14(19), pages 1-14, October.
    8. Salvador del Saz Salazar & Luis Pérez y Pérez, 2021. "Exploring the Differential Effect of Life Satisfaction on Low and High-Cost Pro-Environmental Behaviors," IJERPH, MDPI, vol. 19(1), pages 1-17, December.
    9. Chen, Yufeng & Ni, Liangfu & Liu, Kelong, 2022. "Innovation efficiency and technology heterogeneity within China's new energy vehicle industry: A two-stage NSBM approach embedded in a three-hierarchy meta-frontier framework," Energy Policy, Elsevier, vol. 161(C).
    10. Ling-Ling Pei & Qin Li, 2019. "Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model," Sustainability, MDPI, vol. 11(5), pages 1-15, February.
    11. Fang, Guochang & Lu, Longxi & Tian, Lixin & he, Yu & Yin, Huibo, 2020. "Research on the influence mechanism of carbon trading on new energy—A case study of ESER system for China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

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