Evaluation Analysis on an Integrated Fare Initiative in Beijing

An effective fare policy and structure will realize a reasonable combination of both public welfare and operational profit. This article presents an evaluation framework for an integrated fare initiative in Beijing. It explores a new set of 10 evaluation indices, which include public acceptance, social equity, convenience, change of subsidy, possibility of modal integration, feasibility of implementation, change of revenue, change of ridership, improvement of operation control, and change of cost. The framework is implemented by combining the method of multiple criteria fuzzy decision with the analytic hierarchy process (AHP). The article examines a survey of Beijing Public Transit System users to assess three integrated fare strategies introduced by the agency. The results from the survey are subsequently used as the input data to the proposed evaluation framework. The implementation of the proposed framework in Beijing has shown that the price level of a one-month pass ticket should be increased, while it is recommended that its price cannot be increased to the level that is close to its operation cost. The case study also shows that the proposed framework is a practical and efficient method for fare evaluation. Journal of Public Transportation, Vol. 8, No. 3, 2005 34 Introduction After entering the new century, many countries, especially developing countries such as China, have been facing more and more serious transportation problems. Transit congestion and declining efficiency of the entire transportation system are the combined results of the rapid increase of car ownership, simultaneous running of motor vehicles and nonmotorized transport tools on the same transportation facilities, imbalanced development of a public transport system and private transport mode, and insufficiency of the urban transportation infrastructure investment. These outcomes have resulted in great losses to the national economy. Giving priority to developing a public transport system with different capacities is becoming a fundamental policy for most cities in China today. Enhancing capacities and improving service quality are key to increasing the number of trips on public transit. Overall success is further ensured through reasonable fare structures and policies and practical fare initiatives. Urban fare policy refers to the institutional arrangement of urban transportation pricing structure and category (Li et al. 2004). Existing urban fare policies are classified into two categories: elementary and accessorial. These categories are often combined in a city. Elementary fare policy includes single, distance-based, one-month pass, one-week pass, and one-day pass tickets; accessorial fare policy includes time-based, ride-number-based, and peak-hour-based tickets. Fare level is one of the key factors affecting public transit ridership. Used as a lever to adjust transit trip demand and supply, fare level can play an important role in the operation of an urban transportation system. An effective fare policy and structure will realize a reasonable combination of both public welfare and operational profit (Lu 2004). In this regard, the fare policy should address both the benefit of a public transport operator, such as an urban rail transit company or a bus company, and the endurance of the rider. Improving pricing methods, establishing a multilevel fare policy system, and implementing integration of pricing of a public transport system represent the trends in fare collection practices. To ensure the success of any new pricing strategy, the ability to evaluate these strategies in an objective and quantitative manner is essential. Unfortunately, few existing theories and practices have attempted to evaluate the implementation effect of an integrated fare initiative from a comprehensive view. In this context, this article proposes a comprehensive evaluation framework to an integrated fare initiative in Beijing. The framework combines multiple criteria fuzzy decisions with the analytic hierarchy process. Evaluation Analysis on an Integrated Fare Initiative in Beijing 35 Review of Fare Policy Evaluation Methodologies The evaluation work of a fare policy is a critical step, which should be included in the entire process of developing a fare system and structure. Specific criteria must be developed before pursuing the evaluation of fare system options and fare strategy options. The selection decision for a fare system usually is based on the results from a fare initiative evaluation. Existing methodologies on the fare initiative evaluation are summarized below. Elasticity Theory Products provided by the transit industry are considered quasi-public products. Fare changes follow econometric rules since demand and market elements exist. The price elasticity of demand measures the responsiveness of quantity demanded to a change in price, when all other factors are held constant. In general, elasticity that can be applied to the transportation field includes point elasticity, arch elasticity, and shrinkage ratio. Transit price sensitivity is measured using the elasticities defined as the percentage change in transit trips resulting from a 1 percent change in fare, holding constant the effects of all other determining variables (Todd 2004). This assessment method represents quantitative assessments of ridership and revenue effects with the fare changes. Curtin (1968) developed a measurement of transit ridership fare elasticity known as the Simpson-Curtin formula. This measurement postulates a fare elasticity of -0.33; that is, a 10 percent increase in fare would result in a 3.3 percent decrease in transit patronage. Since Curtin’s original study, other studies on transit fare elasticity have also been carried out. Major sources and techniques of developing fare elasticities, as summarized by Fleishman et al. (1996), include the following: 1. Time series analysis of the agency’s historical ridership data, which often includes a regression analysis to isolate the effects of fare changes from other factors, such as service changes, employment, or fuel prices; 2. Before and after (“shrinkage”) analysis for a particular fare change; 3. Use of a demand function, often on the basis of the results of stated preference surveys (i.e., asking how people would respond to various fare options and changes, or alternatively asking them to “trade off” fare changes with level-of-service changes); 4. Review of industry experience, particularly for agencies of similar size and with similar characteristics; and Journal of Public Transportation, Vol. 8, No. 3, 2005 36 5. Use of professional judgment in adjusting figures derived from the above sources. Multiple Criteria Fuzzy Decision Theory Selecting a fare system and fare structure is a decision-making process that involves multiple factors. Thus, the evaluation should not only analyze one single index corresponding to a particular factor but also conduct a comprehensive analysis on all indices simultaneously. Fare initiative evaluation is a conflicting analysis process of value judgement from technological, socioeconomic, environmental, and political perspectives. In the design of a fare initiative, it is rather difficult to obtain unique, direct, and concise solutions. Therefore, the fare initiative decision involves multiple factors that should always seek compromised and acceptable alternatives, and which should be evaluated by a suitable method. Multiple criteria comprehensive evaluation provides a flexible approach to dealing with multiplefactor decision-making problems. Fare initiative decision-making involves multiple influencing factors, most of which are difficult to quantify. In other words, the influencing factors are evaluated by qualitative indices. Although such indices cannot be measured quantitatively, their range and influencing tendency can be readily determined. That is to say, we only have fuzzy judgement on them. Therefore, the multiple criteria fuzzy comprehensive evaluation method can be applied in the fare initiative decision making. Li et al. (2004) applied this kind of evaluation method in their study on fare strategies. A mathematical model of a fuzzy comprehensive evaluation can be expressed as follows: When evaluating a subject, suppose that U = {u 1 , u 2 ,..., u m } and V = {v 1 , v 2 ,..., u n } are two finite “reference sets”