Abstract
Most of the urban rail transit enterprises in China have high construction and operation costs, while the government imposes price control on their fares, making their revenues unable to cover their costs and thus causing certain losses. In order to ensure the economic sustainability of urban rail transit enterprises, the government then subsidizes their losses. In the context of loss subsidies as the main subsidy mode for urban rail transit, the government regulates whether urban rail transit enterprises waste cost in order to protect social welfare and reduce the financial pressure of subsidies. This paper constructs an evolutionary game model between government regulators and urban rail transit enterprises, establishes replicated dynamic equations to obtain the evolutionary stabilization strategies of the government and urban rail transit enterprises under different situations, and analyzes the effects of various parameters on the cost control behaviors of urban rail transit enterprises under different loss-subsidy modes through numerical simulations. The theoretical study and simulation results show the following: When only the regulatory policy is adopted, the optimal strategy of urban rail transit enterprises may be cost saving or cost wasting under different subsidy models; if only the penalty policy is adopted, the enterprises will choose the cost wasting strategy when the penalty is small, and the enterprises will choose the cost saving strategy when the penalty is large; if only the fixed proportion subsidy model is adopted, no matter how large the proportion k of government subsidies is, the urban the optimal strategy for rail transit enterprises is cost wasting. If only the regressive loss subsidy model is adopted, the different sizes of its various parameter settings will also lead to the enterprises’ choice of cost wasting strategy or cost saving strategy. Therefore, the government should formulate corresponding policies according to different cost control objectives.
Highlights
IntroductionThe 2018 China Urban Rail Transit Annual Statistical Analysis Report released by the
The 2018 China Urban Rail Transit Annual Statistical Analysis Report released by theChina Urban Rail Transit Association shows that China’s urban rail transit is developing rapidly, with its 2018 operating line length increasing by 14.73% compared to 2017
If a fixed amount of the loss subsidy mode is adopted, Ss = Sw, Ss − Sw = 0 > −0.38, the evolutionary stabilization strategy is consistent with Case 3
Summary
The 2018 China Urban Rail Transit Annual Statistical Analysis Report released by the. By the end of 2018, a total of 35 cities in mainland China had opened urban rail transit, with a total operating line length of 5761.4 km, and the cumulative annual passenger volume of urban rail transit was 21.07 billion [1]. (2) The fixed amount subsidy mode, such as Suzhou subsidizing 300 million RMB per year. (3) The full subsidy mode for losses, for example, in Chengdu, after the fare adjustment in 2017, the annual loss was about 100 million RMB, which was fully subsidized by government financing [2]. From the current situation of rail transit subsidy modes and amounts in major cities in China, the Chinese subsidy mode is mainly the loss subsidy, supplemented by special subsidy, and loss subsidies can be divided into many different modes [2,3]. This study will focus on the loss subsidy mode and explore the advantages and disadvantages of different loss subsidy modes in urban rail transit subsidies, so as to provide suggestions for the government to select the appropriate loss subsidy modes and corresponding policy measures
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.