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Online Car-Hailing Market Regulation Strategy in China: From the Perspective of Quadrilateral Evolutionary Games

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Abstract

This paper fully considers the influence of the government, platforms, drivers and passengers on the regulation of online car-hailing market, and constructs an evolutionary game model of four parties. Then, the strategic stability of evolutionary game model is analyzed. Eleven strategies satisfying the stability conditions are obtained. Finally, the simulation verify the results of analysis. The simulation shows that parties’ decisions will be changed by the strength of the initial willingness. When the rewards and punishments increase, the self-restraint ability of the platform and the drivers can be strengthened. And then, by analyzing the managerial cost, this paper finds that reducing cost can accelerate the system to the stable state. Based on this, the paper puts forward relevant policy suggestions to promote the regulation of online car-hailing market.

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References

  • Al Haddad, C., Chaniotakis, E., Straubinger, A., Plötner, K., & Antoniou, C. (2020). Factors affecting the adoption and use of urban air mobility. Transportation Research Part A: Policy and Practice, 132, 696–712.

    Google Scholar 

  • Armstrong, M. (2006). Competition in two-sided markets. The RAND Journal of Economics, 37(3), 668–691.

    Article  Google Scholar 

  • Barykin, S. Y., Kapustina, I. V., Kalinina, O. V., Dubolazov, V. A., Esquivel, C. A. N., Alyarovna, N. E., & Sharapaev, P. (2021). The sharing economy and digital logistics in retail chains: Opportunities and threats. Academy of Strategic Management Journal, 20, 1–14.

    Google Scholar 

  • Brady, M., Mamanduru, V. K., & Tiwari, M. K. (2017). An evolutionary algorithmic approach to determine the nash equilibrium in a duopoly with nonlinearities and constraints. Expert Systems with Applications, 74, 29–40.

    Article  Google Scholar 

  • Brail, S. (2018). From renegade to regulated: The digital platform economy, ride-hailing and the case of Toronto. Canadian Journal of Urban Research, 27(2), 51–63.

    Google Scholar 

  • Chordiya, R., Sabharwal, M., Relly, J. E., & Berman, E. M. (2020). Organizational protection for whistleblowers: A cross-national study. Public Management Review, 22(4), 527–552.

    Article  Google Scholar 

  • Christensen, C. M., McDonald, R., Altman, E. J., & Palmer, J. (2016). Disruptive innovation: Intellectual history and future paths. Harvard Business School Cambridge.

    Google Scholar 

  • Contreras, S. D., & Paz, A. (2018). The effects of ride-hailing companies on the taxicab industry in las Vegas, Nevada. Transportation Research Part A: Policy and Practice, 115, 63–70.

    Google Scholar 

  • Dudley, G., Banister, D., & Schwanen, T. (2017). The rise of uber and regulating the disruptive innovator. The Political Quarterly, 88(3), 492–499.

    Article  Google Scholar 

  • Flores, O., & Rayle, L. (2017). How cities use regulation for innovation: The case of Uber, Lyft and Sidecar in San Francisco. Transportation Research Procedia, 25, 3756–3768.

    Article  Google Scholar 

  • Friedman, D. (1998). On economic applications of evolutionary game theory. Journal of Evolutionary Economics, 8, 15–43.

    Article  Google Scholar 

  • Hawlitschek, F., Teubner, T., & Gimpel, H. (2018). Consumer motives for peer-to-peer sharing. Journal of Cleaner Production, 204, 144–157.

    Article  Google Scholar 

  • Hu, B., Xia, X., Sun, H., & Dong, X. (2019). Understanding the imbalance of the taxi market: From the high-quality customer’s perspective. Physica A: Statistical Mechanics and its Applications, 535, 122297.

    Article  Google Scholar 

  • Huang, Z., Xiong, X., Chen, W., Zhang, Q., Liu, Y., & Chen, Y. (2018). Three bounded proofs for nonlinear multi-input multi-output approximate dynamic programming based on the l yapunov stability theory. Optimal Control Applications and Methods, 39(1), 35–50.

    Article  Google Scholar 

  • Ji, P., Ma, X., & Li, G. (2015). Developing green purchasing relationships for the manufacturing industry: An evolutionary game theory perspective. International Journal of Production Economics, 166, 155–162.

    Article  Google Scholar 

  • Jiang, H., & Wang, H. (2020). China’s regulatory approach to the sharing economy: A perspective on ride-hailing. University of Illinois Journal of Law, Technology & Policy, 85, 24.

    Google Scholar 

  • Jiang, H., & Zhang, X. (2019). An experimental model of regulating the sharing economy in China: The case of online car hailing. Computer Law & Security Review, 35(2), 145–156.

    Article  Google Scholar 

  • Lei, L., & Gao, S. (2018). Evolutionary game analysis of ridesourcing industry between transportation network companies and passengers under new policies of ridesourcing. IEEE Access, 6, 71918–71931.

    Article  Google Scholar 

  • Lei, L.-C., Gao, S., & Zeng, E.-Y. (2020). Regulation strategies of ride-hailing market in China: An evolutionary game theoretic perspective. Electronic Commerce Research, 20(3), 535–563.

    Article  Google Scholar 

  • Leung, X. Y., Xue, L., & Wen, H. (2019). Framing the sharing economy: Toward a sustainable ecosystem. Tourism Management, 71, 44–53.

    Article  Google Scholar 

  • Li, L., Bai, Y., Song, Z., Chen, A., & Wu, B. (2018). Public transportation competitiveness analysis based on current passenger loyalty. Transportation Research Part A: Policy and Practice, 113, 213–226.

    Google Scholar 

  • Li, X., Zhang, S., Liu, D., Cheng, T., & Zhang, Z. (2022). Policy evaluation and policy style analysis of ride-hailing in china from the perspective of policy instruments: The introduction of a toe three-dimensional framework. Processes, 10(10), 2035.

    Article  Google Scholar 

  • Miller, S. R. (2016). First principles for regulating the sharing economy. Harvard Journal on Legislation, 53, 147.

    Google Scholar 

  • Nguyen-Phuoc, D. Q., Vo, N. S., Su, D. N., Nguyen, V. H., & Oviedo-Trespalacios, O. (2021). What makes passengers continue using and talking positively about ride-hailing services? the role of the booking app and post-booking service quality. Transportation Research Part A: Policy and Practice, 150, 367–384.

    Google Scholar 

  • Nguyen-Phuoc, Duy Q., Tran, Phuong Thi Kim., Su, Diep Ngoc., Oviedo-Trespalacios, Oscar., & Johnson, L.W. (2021). Nguyen-Phuoc, Duy Q and Tran, Phuong Thi Kim and Su, Diep Ngoc and Oviedo-Trespalacios, Oscar and Johnson, Lester W. Travel behaviour and society 24, 218–230.

  • Ozkan-Canbolat, E., Beraha, A., & Bas, A. (2016). Application of evolutionary game theory to strategic innovation. Procedia-Social and Behavioral Sciences, 235, 685–693.

    Article  Google Scholar 

  • Pu, D., Xie, F., & Yuan, G. (2020). Active supervision strategies of online ride-hailing based on the tripartite evolutionary game model. IEEE Access, 8, 149052–149064.

    Article  Google Scholar 

  • Selten, R., & Selten, R. (1988). A note on evolutionarily stable strategies in asymmetric animal conflicts (pp. 67–75). Berlin: Springer.

    Google Scholar 

  • Sun, Q., He, Y., Wang, Y., Ma, F., et al. (2019). Evolutionary game between government and ride-hailing platform: Evidence from China. Discrete Dynamics in Nature and Society, 2019, 568.

    Article  Google Scholar 

  • Tang, Q. (2020). The regulative path on ‘special car’and other sharing economies. China Legal Science, 4, 286–302.

    Google Scholar 

  • Teubner, T., & Flath, C. M. (2020). Privacy in the sharing economy. Journal of the Association for Information Systems, 20(3), 2.

    Google Scholar 

  • Wang, W., Zhang, Y., Feng, L., Wu, Y. J., & Dong, T. (2020). A system dynamics model for safety supervision of online car-hailing from an evolutionary game theory perspective. IEEE Access, 8, 185045–185058.

    Article  Google Scholar 

  • Weng, Z., & Luo, P. (2021). Supervision of the default risk of online car-hailing platform from an evolutionary game perspective. Sustainability, 13(2), 555.

    Article  Google Scholar 

  • Xiao, Z., Jiang, J., Zhu, Y., Ming, Z., Zhong, S., & Cai, S. (2015). A solution of dynamic vms placement problem for energy consumption optimization based on evolutionary game theory. Journal of Systems and Software, 101, 260–272.

    Article  Google Scholar 

  • Zhan, X., Szeto, W., & Chen, X. M. (2022). The dynamic ride-hailing sharing problem with multiple vehicle types and user classes. Transportation Research Part E: Logistics and Transportation Review, 168, 102891.

    Article  Google Scholar 

  • Zhong, Y., Yang, T., Cao, B., & Cheng, T. (2022). On-demand ride-hailing platforms in competition with the taxi industry: Pricing strategies and government supervision. International Journal of Production Economics, 243, 108301.

    Article  Google Scholar 

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Funding

The present research work has been supported by Social Science Planning Project of Chongqing, China [No. 2019YBGL049] and Transportation Science and Technology Project of Chongqing Transportation Bureau, No. 2022-17. The authors gratefully acknowledge the support of these institutions.

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Author notes

  1. YaPing Hou and ShuHan Gao authors contributed equally to this work.

Authors and Affiliations

  1. School of Traffic and Transportation, Chongqing jiaotong University, Chongqing, 400074, China

    Yong Peng & ShuHan Gao

  2. Center of Highway construction and maintenance, Transportation Bureau in Shizhong District of Neijiang City, Sichuan, 610200, China

    YaPing Hou

Authors
  1. Yong Peng
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  2. YaPing Hou
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Correspondence to Yong Peng.

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Peng, Y., Hou, Y. & Gao, S. Online Car-Hailing Market Regulation Strategy in China: From the Perspective of Quadrilateral Evolutionary Games. Comput Econ (2023). https://doi.org/10.1007/s10614-023-10461-9

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