Subsidy and public transit performance: A factor analytic approach

The need to measure and evaluate transit system performance has led to the development of numerous performance indicators. However, depending upon the indicator, we oftentimes reach different conclusions regarding transit system performance. The research reported in this paper uses factor analytic methods to generate a set of underlying attributes (factors) that capture the performance of public transit systems in Indiana. Similar to what is reported in the literature, this study finds three attributes that best describe transit system performance: efficiency, effectiveness, and overall performance. Based upon systemsÕ factor scores, the study finds that systems scoring highly on one attribute generally perform well on the remaining attributes. Further, there is an inverse relationship between system performance and subsidies, a finding that supports performance based subsidy allocations.     

The effects of federal transit subsidy policy on investment decisions: The case of San Francisco's Geary Corridor

In the United States, federal funding for public transit often accounts for a large proportion of a local agency's budget, especially for capital investments. For this reason, local governments can be expected to plan a portfolio of projects that maximize federal contributions. This study examines the financial effects of federal transit subsidy policy on local transit investment decisions. Data from a System Planning Study for the Geary Corridor in San Francisco are used as an illustration. It is found that federal transit subsidy policy provides financial incentives for local decision-makers to select capital-intensive investment options that may not be efficient or effective. While federal financial incentives are not the only factor influencing local investment decisions, some reform of the current subsidy policy may be necessary to reduce the incentive for ineffective use of public resources.     

An analysis of public bus transit performance in Indian cities

Maintaining and enhancing public transit service in Indian cities is important, to meet rapidly growing mass mobility needs, and curb personal motor vehicle activity and its impacts at low cost. Indian cities rely predominantly on buses for public transport, and are likely to continue to do so for years. However, the public bus transit service is inadequate, and unaffordable for the urban poor. The paper explores the factors that contribute to and affect efforts to improve this situation, based on an analysis of the financial and operational performance of the public bus transit service in the four metropolitan centres and four secondary cities during the 1990s. Overall, there were persistent losses, owing to increasing input costs and declining productivity. The losses occurred despite rapidly increasing fares, and ridership declined. The situation, and the ability to address it, is worse in the secondary cities than the metropolitan centres. We suggest a disaggregated approach based on the needs and motivations of different groups in relation to public transit, along with improved operating conditions and policies to internalize costs of personal motor vehicle use, to address the challenge of providing financially viable and affordable public bus transit service.     

Mitigation of disruptions in public transit by Bee Colony Optimization

Dispatchers in many public transit companies face the daily problem of assigning available buses to bus routes under conditions of bus shortages. In addition to this, weather conditions, crew absenteeism, traffic accidents, traffic congestion and other factors lead to disturbances of the planned schedule. We propose the Bee Colony Optimization (BCO) algorithm for mitigation of bus schedule disturbances. The developed model takes care of interests of the transit operator and passengers. The model reassigns available buses to bus routes and, if it is allowed, the model simultaneously changes the transportation network topology (it shortens some of the planned bus routes) and reassigns available buses to a new set of bus routes. The model is tested on the network of Rivera (Uruguay). Results obtained show that the proposed algorithm can significantly mitigate disruptions.     

Disruption management in public transit: the bee colony optimization approach

Disruptions in carrying out planned bus schedules occur daily in many public transit companies. Disturbances are often so large that it is necessary to perform re-planning of planned bus and crew activities. Dispatchers in charge of traffic operations must frequently find an answer to the following question in a very short period of time: How should available buses be distributed among bus routes in order to minimize total passengers' waiting time on the network? We propose a model for assigning buses to scheduled routes when there is a shortage of buses. The proposed model is based on the bee colony optimization (BCO) technique. It is a biologically inspired method that explores collective intelligence applied by honey bees during the nectar collecting process. It has been shown that this developed BCO approach can generate high-quality solutions within negligible processing times.     

A causal analysis of car ownership and transit use

The causal structure underlying household mobility is examined in this study using a sample obtained from the Dutch National Mobility Panel survey. The results indicate that car ownership is strongly associated with mode use, but that it has no influence on weekly person trip generation by household members. Characteristics of mode use are examined through a causal analysis of changes in car ownership, number of drivers, number of car trips, and number of transit trips. It is shown that observed changes in mode use cannot be adequately explained by assuming that a change in transit use influences car use. The finding suggests that the increase in car use, which is a consequence of increasing car ownership, may not be suppressed by improving public transit.     

A procedure for estimating transit subsidization requirements for developing countries

The paper presents a procedure that has been developed for estimating subsidization requirements for urban transit services in developing countries. The procedure is based on a subsidization policy of reducing transport expenditure burden on the average commuter, by maintaining his transport expenditure-income ratio at a reasonable level. It is designed for both regulated and deregulated transport markets. It requires, as input, historical data (previous year) on fare, productivity, and load factor for the transport service or mode concerned, the transport expenditure-income ratio distribution of the commuters, and the current level of commuter personal transport allowance. It is based on the premise that transport expenditure-income ratio is inversely related to income. The subsidization formula developed in the paper yields a level of subsidy that is commensurate with the level of control a government is able to exercise over transit operations.     

Strategic management of organizational turnarounds in the transit industry

The traditional wisdom that there are increasing returns to scale among bus transit systems has been shaken with recent research findings. The implication from the literature is that unless many transit systems restructure along new organizational lines the financial and service provision difficulties will continue. Very few public transit systems have attempted to strategically manage change and turnaround organizationally.The objectives of this research were to identify the salient factors in organizational turnarounds and to determine whether these factors were evident within transit organizations that have attempted to manage change strategically. The author reviewed the corporate turnaround literature and conducted four case studies of strategic planning/management within the transit industry.All four cases exhibited organizational declines or perceived declines as imminent. They initiated turnarounds through reorganizations and efforts at strategic management. The reorganizations that occurred at all four cases were relatively minor, involving some changes in function. Only minor changes in management occurred and commitment to strategic management varied. Strategic objectives were not quantifiable. All of the cases could have improved their communication below the middle-management levels. The measures of performance in general did not relate a specific strategy and program to a particular turnaround effect. Through management commitment and some minor organizational restructuring two cases achieved some degree of turnaround. Total commitment to strategic management, organizational change, adequate communication, and accurate performance measures are keys to definitive turnarounds.     

Development of multimodal performance measures for transit systems in New York State

The New York State Department of Transportation was required to certify as to the economy and efficiency of transit operators participating in the State's public transportation operating assistance program. This paper describes the efforts undertaken to meet this mandate.Discussed are past efforts to link performance measures to funding programs; reasons for modifying measures which had been used in previous efforts; and some of the problems and issues raised by the use of such criteria. The paper identifies 15 performance measures being used by New York State in its evaluations, the actual ranges encountered in the transit operations being funded through the state program, and tentative acceptable and desirable levels of those measures which the Transportation Department is using in its evaluation. The role these measures play in the state's operating assistance policy decision process is also described.     

Efficiency of urban public transit: A meta analysis

The aim of this paper is twofold. First, to provide a statistical overview of the literature on public transit efficiency performance. Second, to statistically explain the variation in efficiency findings reported in the literature. To this end, first some key concepts of efficiency analysis will be introduced, while next the different frontier methodologies that are used in the literature will be discussed. The empirical part of this paper consists of a statistical summary of the literature as well as meta-regression analyses for different samples of the literature in order to identify key determinants of technical efficiency (TE) of public transit operators. For a broad sample of observations, we found significant and consistent effects of the type of database, region and output measurement method. For the sample of non-parametric studies we found that the type of frontier assumptions also have an impact on the efficiency ratio. Further results show that there is no statistical difference in TE ratios between parametric and non-parametric studies. Finally, we found a positive univariate relationship between the number of inputs in the estimated specification and the efficiency ratio.     

A structured flexible transit system for low demand areas

Public transit structure is traditionally designed to contain fixed bus routes and predetermined bus stations. This paper presents an alternative flexible-route transit system, in which each bus is allowed to travel across a predetermined area to serve passengers, while these bus service areas collectively form a hybrid “grand” structure that resembles hub-and-spoke and grid networks. We analyze the agency and user cost components of this proposed system in idealized square cities and seek the optimum network layout, service area of each bus, and bus headway, to minimize the total system cost. We compare the performance of the proposed transit system with those of comparable systems (e.g., fixed-route transit network and taxi service), and show how each system is advantageous under certain passenger demand levels. It is found out that under low-to-moderate demand levels, the proposed flexible-route system tends to have the lowest system cost.     

Implications of the cost of public funds in public transit subsidization and regulation

This paper identifies some implications of the cost of public funds (CF) in public transit subsidization and regulation. Regulation is considered because a monopolistic operator is assumed. A social welfare maximization model is proposed, subject to individual rationality and vehicle capacity constraints. Optimality conditions are provided and a key formula is derived about CF’s role in balancing the need to cover the fixed operation cost through fares on the operator’s side and the effort to maintain the user surplus on the passengers’ side. Major findings from this model’s formulation include: (1) CF determines the extent to which the passengers’ surplus is compromised in order to cover the fixed part of the operating cost, and (2) subsidy is unjustified when CF exceeds the critical shadow price of the financial constraint. Analytical relations are illustrated through numerical examples.     

A methodology to derive the critical demand density for designing and operating feeder transit services

Feeder lines are one of the most often used types of flexible transit services connecting a service area to a major transit network through a transfer point. They often switch operations between a demand responsive and a fixed-route policy. In designing and running such systems, the identification of the condition justifying the operating switch is often hard to properly evaluate. In this paper, we propose an analytical model and solution of the problem to assist decision makers and operators in their choice. By employing continuous approximations, we derive handy but powerful closed-form expressions to estimate the critical demand densities, representing the switching point between the competing operating policies. Based on the results of one-vehicle and two-vehicle operations for various scenarios, in comparison to values generated from simulation, we verify the validity of our analytical modeling approach.     

Design and implementation of efficient transit networks: Procedure, case study and validity test

This paper presents and tests a method to design high-performance transit networks. The method produces conceptual plans for geometric idealizations of a particular city that are later adapted to the real conditions. These conceptual plans are generalizations of the hybrid network concept proposed in Daganzo (2010). The best plan for a specific application is chosen via optimization. The objective function is composed of analytic formulae for a concept’s agency cost and user level of service. These formulae include as parameters key demand-side attributes of the city, assumed to be rectangular, and supply-side attributes of the transit technology. They also include as decision variables the system’s line and stop spacings, the degree to which it focuses passenger trips on the city center, and the service headway. These decision variables are sufficient to define an idealized geometric layout of the system and an operating plan. This layout-operating plan is then used as a design target when developing the real, detailed master plan. Ultimately, the latter is simulated to obtain more accurate cost and level of service estimates.This process has been applied to design a high performance bus (HPB) network for Barcelona (Spain). The idealized solution for Barcelona includes 182 km of one-way infrastructure, uses 250 vehicles and costs 42,489 €/h to build and run. These figures only amount to about one third of the agency resources and cost currently used to provide bus service. A detailed design that resembles this target and conforms to the peculiarities of the city is also presented and simulated. The agency cost and user level of service metrics of the simulated system differ from those of the idealized model by less than 10%. Although the designed and simulated HPB systems provide sub-optimal spatial coverage because Barcelona lacks suitable streets, the level of service is good. Simulations suggest that if the proposed system was implemented side-by-side with the current one, it would capture most of the demand.     

Application of path analysis methodology to transit system maintenance performance

This paper develops a conceptual framework for bus maintenance based on path analysis and applies it to forty-eight bus transit systems. The application determines the total, direct, and indirect effects of the variables identified as having significant causal links with maintenance cost per mile. These variables are identified using the stepwise regression method. The findings are that the wage rate and fleet size increase maintenance cost directly and indirectly. In terms of the standardized regression coefficients, fleet size has been found to be the most important factor affecting maintenance cost per mile, followed by the proportion of articulated buses, the wage rate and local subsidy in that order. The proportion of articulated buses has been found to reduce maintenance cost per mile directly and to increase it indirectly. The indirect path coefficient of the proportion of articulated buses is 0.1794 whereas the direct path coefficient is –0.351. Similarly local subsidy as a proportion of revenue increases maintenance cost per mile directly and reduces it indirectly. The corresponding path coefficients for the direct and indirect effects of local subsidy are 0.2553 and –0.1073. In addition population density and the peak-base ratio are positively and significantly associated with miles between roadcalls. The implications of these findings are briefly examined in this paper. Because the path analysis methodology allows the direct and indirect effects of a causal variable to be determined, it is recommended for policy analysis.     

Forecasting ridership for a metropolitan transit authority

The recent volatility in gasoline prices and the economic downturn have made the management of public transportation systems particularly challenging. Accurate forecasts of ridership are necessary for the planning and operation of transit services. In this paper, monthly ridership of the Metropolitan Tulsa Transit Authority is analyzed to identify the relevant factors that influence transit use. Alternative forecasting models are also developed and evaluated based on these factors—using regression analysis (with autoregressive error correction), neural networks, and ARIMA models—to predict transit ridership. It is found that a simple combination of these forecasting methodologies yields greater forecast accuracy than the individual models separately. Finally, a scenario analysis is conducted to assess the impact of transit policies on long-term ridership.     

A comparison of two methodologies for selecting transit performance indicators

Two contrasting methodologies have appeared in the literature for selecting indicators to evaluate the performance of public transit firms. One methodology specifies the criteria that the selected performance indicators must satisfy. The other methodology requires the specification of operating objectives by the transit firm for the purpose of then selecting performance indicators. This paper compares the two methodologies and discusses the attributes of one methodology versus those of the other methodology. Also, a major difference in the premises of the two methodologies is demonstrated.     

A multiple criteria approach for the evaluation of the rail transit networks in Istanbul

The deficiencies in the Istanbul transportation system have led the local authorities to plan several alternative transportation projects. In this paper three alternative rail transit network proposals are evaluated by using Analytic Hierarchy Process (AHP), a multiple criteria decision support system. The AHP facilitates decision-making by organizing perceptions, experiences, knowledge and judgments, the forces that influence the decision, into a hierarchical framework with a goal, scenarios, criteria and alternatives of choice. Based on this analysis, the decision makers have developed a new alternative as a combination of the most closely competing two alternative rail transit networks. This combination rail transit network is currently under construction.     

Timetable optimization models and methods for minimizing passenger waiting time at public transit terminals

This paper focuses on developing mathematical optimization models for the train timetabling problem with respect to dynamic travel demand and capacity constraints. The train scheduling models presented in this paper aim to minimize passenger waiting times at public transit terminals. Linear and non-linear formulations of the problem are presented. The non-linear formulation is then improved through introducing service frequency variables. Heuristic rules are suggested and embedded in the improved non-linear formulation to reduce the computational time effort needed to find the upper bound. The effectiveness of the proposed train timetabling models is illustrated through the application to an underground urban rail line in the city of Tehran. The results demonstrate the effectiveness of the proposed demand-oriented train timetabling models, in terms of decreasing passenger waiting times. Compared to the baseline and regular timetables, total waiting time is reduced by 6.36% and 10.55% respectively, through the proposed mathematical optimization models.     

Empirical analysis of transportation investment and economic development at state, county and municipality levels

Numerous studies have found positive correlation between transportation infrastructure investment and economic development. Basically these studies use a conventional production function model augmented by a public capital input, mainly highways, rail and other transportation facilities. While the range of the measured economic growth effects varies widely among studies, the positive elasticity between transportation investment and economic development is now commonly accepted. Still a major puzzling issue is that the magnitude of the measured effect seems to decline significantly as the econometric model is further refined, mainly with regard to space and time lags. That is, the use of national or state data produces elasticity results, which are much larger than when using county or municipality data. Similarly, when we introduce into the econometric model a lag between the times when the transportation investments are made and when the economic benefits transpire, the measured elasticities decline with the size of the lag. Thus, the main objective of this paper is to investigate these issues analytically and empirically and provide a plausible explanation. We do so by using alternative econometric models, applying them to a database, which is composed of longitudinal state, county and municipality observations from 1990 to 2000. The key result is that transportation investments produce strong spillover effects relative to space and time. Unless these factors are properly accounted for many reported empirical results are likely to be overly biased, with important policy implications.