P RICING OF T RANSIT

first-class fare. The other is that the same commodity is sold at different prices to different consumers. For example, the seller attempts to sell the juices in sightseeing place, the price is higher than are sold in the supermarket. The same commodities are sold at the different prices because the sightseeing places are far away the urban agglomeration.

mileage. The value of fare (F) is the transport distance (D) multiplied by the rate per unit mileage (R). Taiwan Railway Administration (TRA) and long-distance bus firms generally use the distance rate standard system. Tapering rate system is the more distance the buses move, the lower pricing the passengers pay. Tapering rate system can be applied to sectional fare. This method of making fares related to move distance is obtained by dividing transport lines into sections. According to each sectional fare, the fares then increase with the number of sections traveled.

The group rate system is also called the zonal rate system, and this system divides several groups in order to make an identical price in each group. Each group owns a fixed fare. The passengers move around each group, the rate is an identical fare. If passengers cross another group, the transport fare will be calculated between two groups. I use two methods to calculate transport fare between two groups in the following. One is the way of fixed rate fare in a divided group. When the passengers cross another group, the fare will be calculated between two or more than three groups. There are two formulae of fare in the following. The first formula is , F represents total fare, n represents the passengers pass through the number of divided groups, C represents the fare of each divided group.

The second formula is , i represents the extra fare. The other is the way of flexible rate fare in a divided group. The fixed origin-destination point of passengers are become one group. And then many groups can be graduated. Most short-distance bus firms use this method to calculate the fare.

The flat rate system is also called the signal rate system. The passengers just pay a signal fare wherever they travel any destination. I observe most passengers travel on a signal vehicle or throughout the transit network and a numerous times of travels per day;

therefore, transit bus firms use the flat rate system for collecting revenues. Furthermore, the fare collections are used to supervise the payment in urban transit network stations as it is simple and easy.

2.4.2 Subsidy

Transit subsidy policies often play a significant role in matters of transport operation of overall transportation. In the past, Pucher (1983) used the case study from six metropolitan areas through transit subsidies. As a result of subsidies, it brings out the benefits for the poor and low-income households. Wachs (1989) indicated that Federal Transit Subsidy Program in the United States intended to support only capital costs with respect to purchase of land and equipment and the building of new facilities; furthermore,

Hess and Lombardi (2005) said that transit officials and politicians make ineffective and even irresponsible decisions about transit investment. Afterward, public transit has depended on subsidies so that eked out their operating cost and sustained transport operation.

Small and Verhoef (2007) set a concrete model that includes scale economies and underpriced automobile travel in order to argue transit subsidies. As a result of transit subsidies, they offer two responses. First, subsidy behavior would easily accrue to the distorted decision of the transit operators. Subsidy programs should be designed to minimize lower incentive so that transit operations might provide an alternative method to reduce the extent of dependence. Second, the low price-elasticity of transit uses ameliorates the impact of the first argument for subsidies.

Cheng (1998) established the assessment model of public transportation service with respect to each routing; furthermore, she decided the decision variables that include fare rate and routing operation miles. According to the government’s subsidy program of Mass Transit Development and Promotion, Chen and Lee (2003) established the Translog cost functions to analyze the economic characteristics and productivity changes of the subsidized routes of transit buses.

Feng and Lin (1998) established the allocation mechanism and model of transit subsidy that were based on central and local government; furthermore, they disturbed routing types into service and general routing in order to act a loss subsidy or a performance subsidy. In addition, according to Regulation on Subsidization for Riding Mass Transportation, the formulation is showed in the following.

2.4.3 Fare and Subsidy of Fu-kang bus

In this section, I discuss the fare and subsidy rate of Fu-kang bus and medical bus transport. I example for Taipei Municipality and interpret how to calculate the fare and subsidy. People with disabilities are favor 33.3% discount rate of one way trip base on total vehicle distance. People with disabilities are favor a 66.7% discount rate of one way trip based on regulated taxi rate when the riders use the car-pool. I interpret the fare structure that includes distance rate system in the 2.4.1 section. The fare structure of Fu-kang bus belongs to distance rate system; furthermore, the regulated subsidy rate is given.

On the other hand, TCGDH uses another fare formula to calculate the fare and discount for medical transport service. I refer to fare and subsidy formula by the Appendix A. Taipei City Government, Department of Social Welfare authorizes Public Transportation Office or welfare organization through this table. The fare and subsidy rate structure is similar to the group rate system. For instance, the subsidy cap of type A per one trip is 95 NT dollars. If it is over the subsidy cap, the passengers need to pay an extra fare by shuttle bus meter.

2.4.4 Political Consideration

Transit service, in the past, is a government-owned business; furthermore, it is regulated by the government. Nowadays, it combines with governmental administration, public and private transport operations’ business. The predominance of allotting subsidies within democratic political system is the government; furthermore, it desires to reap more political popularity. Therefore, the determination of transport service is easily trend to political consideration.

Borck and Wrede (2005) and Borck (2007) interpreted the capture theory as a general explanation of political consideration. For instance, Stigler (1971) was first advanced that the politicians fit in with the riders’ or customers’ interests through legislation in order to win the votes or value money; furthermore, the participants endeavor for their requests through voting in order to reap more subsidies. Peltzman (1976) imitated the consumer choice theory to establish his regulatory process model for underlying political power relationship.

Winston (2000) provided empirical evidence based on urban transport US and UK to interpret actual government failures even though the government subsidy to transit authorities. Corneo (1997) researched the character of taxpayers’ incentives for establishing a positive theory of pricing under monopoly. Most public prices are democratically chosen by plurality voting. He creates the behavior that ‘median-voter pricing’ is named. He showed that marginal-cost pricing reaps the income of the median voter equals the average income. As a result of research, demand for public transit is less elastic in relation to income than are tax payments. Because the income distribution is deflective to the right, the average people desire less transit than the median people. Borck and Wrede (2005) suggest that the median voter is inclining to support subsidize transit in order to diminish demand for town centre housing diminish central city land rents.

2.4.5 Transportation Problems and Game Theory

I first reviewed transportation problems with respect to game theory from (Wardrop, 1952), it was called the ‘Wardropian equilibrium’ of route choice, which is resemble in the Nash equilibrium of an N-player game (Nash, 1950). After that, the two aspects of transportation problems with respect to game theory are researched. The first aspect is optimal traffic control or investment problems. Buttler (1978) formulated the optimal investments of an existing road link over time; furthermore, he considered three state variables of the road and solved with the Pontryagin maximum principle. Friesz and Fernandez (1979) formulated a simple dynamic model to decide optimal maintenance policies for transport facilities; moreover, they solved this model with the Pontryagin maximum principle. Fisk (1984) proposed two game theory model, Nash equilibrium and Stackelberg games for solution algorithms to solve problems in transporation systems modelling. Wie (1995) formulated the dynamic mixed behaviour traffic network equilibrium problem as a non-cooperative N-person, non-zero sum differential game. In addition, two types of players are named as user-equilibrium (UE) players and Cournot-Nash (CN) players are considered in a simple network. Garcia, Reume and Smith (2000) adjusted a unique procedure to compute system-optimal routings in a dynamic traffic network. Bell (2000) formulated the performance reliability of a transport network from a two-player, non-cooperative game. The network users quest a path to minimize its expected trip cost; furthmore, they choose ‘evil entiry’link performace scenarios to maximize the expected trip cost. Bell and Cassir (2002) applied the game theory to solve rist-averse user-equilibrium traffic assignment. Zhane, Peeta, and Friesz (2005) formulated a initial network flow equilibrium model of dynamic multi-player infrastucture networks;

furthmore, they presented in the form of a differential game. Three coupled network layers are called car, urban freight and data are established as Cournot-Nash dynamic agents. The second aspect is road-pricing problems with respect to determing optimal tolls in transport networks. Levinson (1988) examined the question of tax or toll between tollbooths and frontier under jurisdictions; furthermore, he establsihed the potential for a prisoner’s dilema consideration. Levinson (2003) formulated game theory model and queuing analysis to develop micro formulations of congestion. Joksimovic, Bliemer, and Bovy (2004) considered route choice and the elastic demand problem and concentrated on different game formulae of the optial toll problem.