| Summary |
Cheng-Hong Shie, 2006.01
Graduate Institute of Transportation Science, Tamkang University
Currently, Taiwan Railway (TR) has the advantages of shorter travel time and more energy efficient in comparison with other highway transportation modes.
However, these advantages will soon be taken by Taiwan High Speed Rail (THSR).
As one of the major competitors in the transportation market of Taiwan western corridor, TR has to set up new operation strategies in competing with THSR. To enhance the competitiveness of TR, the strategies may include: 1) providing more commuting train services for commuters and transfer passengers at the major THSR stations; and 2) resetting the optimal pricing and scheduling strategies for long-distance train services to cope with the new hallenges bought by THSR.
The deregulation of freeway bus services issued by Ministry of Transportation and Communications (MOTC) in 1995 has produced many new competitors in the market. Nowadays there are only a few survivors in the highly competitive market.
Meanwhile, Taiwan High-Speed Railway, a new competitor that offers fast, reliable, and frequent services, is scheduled to operate at the end of 2005, which will cause great impact on the transportation market of Taiwan’s western corridor. As a result, cooperative strategies among freeway buses will affect the market shares and profits of these companies in the near future.
In this study, we apply non-cooperative game and cooperative game approach to analyze the interaction between the High-speed railway ﹑Taiwan Railway and freeway buses and employ cooperative game to resolve the cooperative strategies among freeway bus companies. Through the construction of the payoff functions and the solutions of market equilibrium, we find the optimal pricing strategies for freeway buses under various cooperative scenarios.
The content of the study includes: 1) modeling the profit functions for modes of transportation﹑Taiwan Railway and freeway bus companies; 2) solving optimal modes of transportation fares under market equilibrium; 3) solving optimal bus in the pool of fares under market equilibrium; 4) applying software MATHEMATICA to solve the Shapley values and Nucleolus, which provide the guidance of profit-sharing in the cooperative game; 5) solving the market equilibrium under various game scenarios; and 6) analyzing the changes of consumer surplus and payoffs before and after the operations of THSR. |
