Subsidizing and pricing private toll roads with noncontractible service quality: A relational contract approach

In private toll roads, some elements of the private operator’s performance are noncontractible. As a result, the government cannot motivate the private operator to improve them through a formal contract but through a self-enforcing contract that both parties are unwilling to deviate unilaterally. In this paper, we use noncontractible service quality to capture these performance elements. By employing a relational contract approach, we aim to investigate the optimal subsidy plan to provide incentives for quality improvement. We show that government subsidy is feasible in quality improvement when the discount factor is sufficiently high and marginal cost of public funds is sufficiently small. Under feasible government subsidy, we have demonstrated the optimal subsidy plans in different scenarios. Moreover, some comparative statics are presented. Based on the derived subsidy plans, we further investigate the optimal toll price. We find that the optimal toll price generates zero surplus for the private operator and positive surplus for consumers. We then make two extensions of our model to re-investigate the government’s optimal decisions on subsidy plan and toll price when her decision sequence is changed and when government compensation is present upon termination of the relationship. Some implications for practice have been derived from our model results.     

Using spike model to reduce traffic congestion and improve public transportation in Malaysia

In this study, passengers’ willingness to pay (WTP) for and willingness to accept (WTA) improved public transportation and shift to public transportation in Malaysia were examined. Specifically, this study aimed to determine the factors or transport attributes that affect passenger WTA and WTP to shift to public transportation. The adopted methodology was based on a contingent valuation (CV) survey, which was conducted on a representative sample of a cross section in residents of Kajang, in Malaysia. This CV primary survey elicited the demand of passengers for improved public transportation. The spike model was adopted to avoid estimation errors caused by a large percentage of respondents who were unwilling to pay and accept at all. The estimation results showed that the best reduction rate for both travel time and cost was 45% among other amounts that range from 15% to 75%. The best parking cost increment was US$0.30 and the average WTP is US$0.68.     

Assessing the financial and social costs of public transport in differing operating environments and with endogenous demand

This paper uses a previously developed spreadsheet cost model which simulates public transport modes operated on a 12-km route to analyse the total costs of different passenger demand levels. The previous cost model was a very powerful tool to estimate the social and operator costs for different public transport technologies. However, as the model is strategic, some basic assumptions were made which are relaxed in this paper. First, the speed-flow equation in the original spreadsheet model assumes that speed decreases according to the ratio of the current frequency and the lane capacity which is based on the safety headway without taking into account passenger boardings. However, this may vary in different operating environments. Therefore, the speed-flow equation is improved by moving from a linear equation to a piecewise equation that considers the features of different operating environments. Second, the model assumes that supply is sufficient to meet demand. However, when the level of demand is high for the lower-capacity public transport technologies, passengers may find the incoming vehicle full and therefore, they have to wait more than one service interval. This paper applies queuing theory to investigate the probability of having to wait longer than the expected service headways which will affect the average passenger waiting time. The extra waiting time for each passenger is calculated and applied in the spreadsheet cost model. Third, the original model assumed that demand was externally fixed (exogenous). To evaluate the differences after applying these equations, endogenous demand rather than exogenous demand will be investigated by using the elasticities for passenger waiting time and journey time.     

Evaluating web site service quality in public transport: Evidence from Taiwan High Speed Rail

More and more public transport system passengers plan their trips by using website services. The passengers’ perceived service quality of a website plays a crucial role in recognizing the satisfaction of a transportation service chain. This study aims to investigate the passengers’ perception of electronic service quality (e-SQ) delivery through the Taiwan High Speed Rail’s (THSR) website, by adopting the Rasch measurement model to measure a subjective latent construct: perceived e-SQ. The Rasch model can compare person parameters with item parameters, which are then subjected to a logarithmic transformation along a logit scale to clearly identify which e-SQ measurement items are appreciated by certain passengers. Analytical results show substantial differences between the perceived e-SQ of various personal characteristics such as age, income, and trip types. Empirical results also demonstrate that passengers are most satisfied with the website’s accuracy of information and introduction to the THSR stations’ surrounding area, but are not satisfied with instructions when a transaction fails as well as the carriage layout of the THSR. Our analytical results also identify which service items lead to the perceived e-SQ difference between business trip and leisure trip passengers. The relationship between the two main attribute dimensions – quality of transportation information provided and quality of website services – are also further examined. The empirical results can help a transportation system service operator to better understand how passengers perceive e-SQ and to suggest what should be improved.     

Capacity,information and minority games in public transport

Many public transport operators are faced with high peak demands. This leads to crowded vehicles and discomfort for the passengers. The increasing availability of information technologies creates new opportunities for passengers to avoid crowding and for operators to inform passengers and reallocate capacities quicker than before. We define and implement a simple model based on minority games, a class of games that deals with crowding dynamics, adapted to a public transport setting.We propose a model which includes multiple resources and heterogeneous passenger preferences. We have conducted two simulation studies, investigating the dynamics of crowding within a simplified public transport setting. In our first experiment we investigate the effect of the availability of information on crowding. In our second experiment we study dynamic optimization of rolling stock capacities. We find that both the information disclosed and the capacity optimization mechanism have an impact on the number of passengers utilizing resources and their satisfaction. As such, these models enable the development and analysis of new operator policies to deal with crowded situations.     

The concept and impact analysis of a flexible mobility on demand system

This paper introduces an innovative transportation concept called Flexible Mobility on Demand (FMOD), which provides personalized services to passengers. FMOD is a demand responsive system in which a list of travel options is provided in real-time to each passenger request. The system provides passengers with flexibility to choose from a menu that is optimized in an assortment optimization framework. For operators, there is flexibility in terms of vehicle allocation to different service types: taxi, shared-taxi and mini-bus. The allocation of the available fleet to these three services is carried out dynamically so that vehicles can change roles during the day. The FMOD system is built based on a choice model and consumer surplus is taken into account in order to improve passenger satisfaction. Furthermore, profits of the operators are expected to increase since the system adapts to changing demand patterns. In this paper, we introduce the concept of FMOD and present preliminary simulation results. It is shown that the dynamic allocation of the vehicles to different services provides significant benefits over static allocation. Furthermore, it is observed that the trade-off between consumer surplus and operator’s profit is critical. The optimization model is adapted in order to take into account this trade-off by controlling the level of passenger satisfaction. It is shown that with such control mechanisms FMOD provides improved results in terms of both profit and consumer surplus.     

Airport congestion pricing and terminal investment: Effects of terminal congestion,passenger types,and concessions

None of the airport-pricing studies have differentiated the congestion incurred in the terminals from the congestion incurred on the runways. This paper models and connects the two kinds of congestion in one joint model. This is done by adopting a deterministic bottleneck model for the terminal to describe passengers’ behavior, and a simpler static congestion model for the runway. We find that different from the results obtained in the literature, uniform airfare does not yield the first-best outcome when terminal congestion is explicitly taken into account. In particular, business passengers are at first-best charged a higher fare than leisure passengers if and only if their relative schedule-delay cost is higher. We further identify circumstances under which passengers are, given a uniform airport charge scheme, under- or over-charged with respect to the terminal charge. Furthermore, when concession surplus is added to the analysis, the airport may raise (rather than reduce) the airport charge in order to induce more business passengers who in turn will lengthen leisure passengers’ dwell time and hence increase their chance of purchasing concession goods. Finally, the impacts of terminal capacity expansion and time-varying terminal fine toll are discussed.     

A utility-based travel impedance measure for public transit network accessibility

A utility-based travel impedance measure is developed for public transit modes that is capable of capturing the passengers’ behaviour and their subjective perceptions of impedance when travelling in the transit networks. The proposed measure is time-dependent and it estimates the realisation of the travel impedance by the community of passengers for travelling between an origin–destination (OD) pair.The main advantage of the developed measure, as compared to the existing transit impedance measures, relates to its capability in capturing the diversity benefit that the transit systems may offer the society of travellers with different traveling preferences. To clarify the necessity of such capability, we demonstrate the randomness (subjectivity) of travel impedance perceived by transit passengers, through evidence from the observed path choices made in the transit network of the greater Brisbane metropolitan region in Australia.The proposed impedance measure is basically a nested logit “logsum” composition over a generated set of reasonable path options whose systematic utilities are evaluated based on a discrete choice model previously developed and calibrated for the greater Brisbane transit passengers. As a case study, the proposed impedance measure is calculated for all the origin blocks in the Brisbane area, during the morning commutes to the Central Business District (CBD). The results are presented and discussed, and intuitive and important advantages are demonstrated for the proposed measure.     

An economic theory of the public transit firm

This paper presents an economic theory of the public transit firm that considers the public transit firm's operating objectives related to size maximization and cost minimization as well as its operating options and passenger quality-of-service characteristics. The theory indicates that the variables to be used in the performance evaluation of a public transit firm are its operating options and fare. A single measure for transit performance evaluation is the shadow price in maximizing passengers subject to an overall deficit constraint (to be financed by government).     

Determining optimal frequency and vehicle capacity for public transit routes: A generalized newsvendor model

The level of service on public transit routes is very much affected by the frequency and vehicle capacity. The combined values of these variables contribute to the costs associated with route operations as well as the costs associated with passenger comfort, such as waiting and overcrowding. The new approach to the problem that we introduce combines both passenger and operator costs within a generalized newsvendor model. From the passenger perspective, waiting and overcrowding costs are used; from the operator’s perspective, the costs are related to vehicle size, empty seats, and lost sales. Maximal passenger average waiting time as well as maximal vehicle capacity are considered as constraints that are imposed by the regulator to assure a minimal public transit service level or in order to comply with other regulatory considerations. The advantages of the newsvendor model are that (a) costs are treated as shortages (overcrowding) and surpluses (empty seats); (b) the model presents simultaneous optimal results for both frequency and vehicle size; (c) an efficient and fast algorithm is developed; and (d) the model assumes stochastic demand, and is not restricted to a specific distribution. We demonstrate the usefulness of the model through a case study and sensitivity analysis.     

Evaluation of an existing bus network using a transit network optimisation model: a case study of the Hiroshima City Bus network

This study evaluates an existing bus network from the perspectives of passengers, operators, and overall system efficiency using the output of a previously developed transportation network optimisation model. This model is formulated as a bi-level optimisation problem with a transit assignment model as the lower problem. The upper problem is also formulated as bi-level optimisation problem to minimise costs for both passengers and operators, making it possible to evaluate the effects of reducing operator cost against passenger cost. A case study based on demand data for Hiroshima City confirms that the current bus network is close to the Pareto front, if the total costs to both passengers and operators are adopted as objective functions. However, the sensitivity analysis with regard to the OD pattern fluctuation indicates that passenger and operator costs in the current network are not always close to the Pareto front. Finally, the results suggests that, regardless of OD pattern fluctuation, reducing operator costs will increase passenger cost and increase inequity in service levels among passengers.     

Traffic dynamics in a bi-modal transportation network with information provision and adaptive transit services

This paper has two major components. The first one is the day-to-day evolution of travelers’ mode and route choices in a bi-modal transportation system where traffic information (predicted travel cost) is available to travelers. The second one is a public transit operator adjusting or adapting its service over time (from period to period) based on observed system conditions. Particularly, we consider that on each day both travelers’ past travel experiences and the predicted travel cost (based on information provision) can affect travelers’ perceptions of different modes and routes, and thus affect their mode choice and/or route choice accordingly. This evolution process from day to day is formulated by a discrete dynamical model. The properties of such a dynamical model are then analyzed, including the existence, uniqueness and stability of the fixed point. Most importantly, we show that the predicted travel cost based on information provision may help stabilize the dynamical system even if it is not fully accurate. Given the day-to-day traffic evolution, we then model an adaptive transit operator who can adjust frequency and fare for public transit from period to period (each period contains a certain number of days). The adaptive frequency and fare in one period are determined from the realized transit demands and transit profits of the previous periods, which is to achieve a (locally) maximum transit profit. The day-to-day and period-to-period models and their properties are also illustrated by numerical experiments.     

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.     

Analyzing the gap between the QOS demanded by PT users and QOS supplied by service operators

This research evaluated the effectiveness of tendered bus public transportation (PT) in improving the attractiveness of that service in order to promote sustainable mobility. This was accomplished by characterizing the gap between the quality of service (QOS) supplied by contract regimes and that which is demanded by passengers. Analysis of a customer satisfaction survey aimed at bus users provided insight into their ranking of 14 QOS parameters while 13 active service contracts were analyzed for their impact on QOS. In-depth interviews with relevant experts completed the complex narrative that is Israel’s policy of privatization in PT. Both qualitative and quantitative analyses helped identify those QOS parameters most in demand by passengers and impacted by contracts. The results show that the gap is minimal, high demand parameters receive increased priority in contracts. In addition this research documented an evolution in the method contracts employed to provide QOS. Late model contracts define an increasingly higher minimum QOS; but also strongly limit the operator’s ability to make service changes. This is a trend which should improve QOS in Israel but reduce the incentive for operator enacted QOS initiatives. Despite its obvious success to date, it might be time to change again the contract regime for the provision of competitive bus services in Israel.     

A model of the vicious cycle of a bus line

It has been frequently noted that in a non-regulated environment the development of public transport service is self-adjusting: Faced with decreasing demand, operators will tend to reduce service to cut costs, resulting in a decrease in the level-of-service, which then triggers a further drop in demand. The opposite may also occur: high demand will induce the operator to increase supply, e.g. through an increase in frequency, which results in a higher level-of-service and a subsequent increase in passenger numbers, triggering another round of service improvements. This paper adds to the literature by presenting an analytic model for analyzing these phenomena that we call vicious and virtuous cycles. Based on field data regarding passengers’ variation in willingness-to-wait for a public transport service, we investigate the dynamics of the line service and show how the emergence of a vicious or virtuous cycle depends on the total number of potential passengers, the share of captive riders, and bus capacity. The paper ends with a discussion of the implications of the findings for the planning of public transport services.     

Crowding in public transport systems: Effects on users,operation and implications for the estimation of demand

The effects of high passenger density at bus stops, at rail stations, inside buses and trains are diverse. This paper examines the multiple dimensions of passenger crowding related to public transport demand, supply and operations, including effects on operating speed, waiting time, travel time reliability, passengers’ wellbeing, valuation of waiting and in-vehicle time savings, route and bus choice, and optimal levels of frequency, vehicle size and fare. Secondly, crowding externalities are estimated for rail and bus services in Sydney, in order to show the impact of crowding on the estimated value of in-vehicle time savings and demand prediction. Using Multinomial Logit (MNL) and Error Components (EC) models, we show that alternative assumptions concerning the threshold load factor that triggers a crowding externality effect do have an influence on the value of travel time (VTTS) for low occupancy levels (all passengers sitting); however, for high occupancy levels, alternative crowding models estimate similar VTTS. Importantly, if demand for a public transport service is estimated without explicit consideration of crowding as a source of disutility for passengers, demand will be overestimated if the service is designed to have a number of standees beyond a threshold, as analytically shown using a MNL choice model. More research is needed to explore if these findings hold with more complex choice models and in other contexts.     

Assessing the cost of transfer inconvenience in public transport systems: A case study of the London Underground

Few studies have adequately assessed the cost of transfers² in public transport systems, or provided useful guidance on transfer improvements, such as where to invest (which facility), how to invest (which aspect), and how much to invest (quantitative justification of the investment). This paper proposes a new method based on path choice,³ taking into account both the operator’s service supply and the customers’ subjective perceptions to assess transfer cost and to identify ways to reduce it. This method evaluates different transfer components (e.g., transfer walking, waiting, and penalty) with distinct policy solutions and differentiates between transfer stations and movements.The method is applied to one of the largest and most complex public transport systems in the world, the London Underground (LUL), with a focus on 17 major transfer stations and 303 transfer movements. This study confirms that transfers pose a significant cost to LUL, and that cost is distributed unevenly across stations and across platforms at a station. Transfer stations are perceived very differently by passengers in terms of their overall cost and composition. The case study suggests that a better understanding of transfer behavior and improvements to the transfer experience could significantly benefit public transport systems.     

User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).     

Analyzing year-to-year changes in public transport passenger behaviour using smart card data

In recent years, there has been increased interest in using completely anonymized data from smart card collection systems to better understand the behavioural habits of public transport passengers. Such an understanding can benefit urban transport planners as well as urban modelling by providing simulation models with realistic mobility patterns of transit networks. In particular, the study of temporal activities has elicited substantial interest. In this regard, a number of methods have been developed in the literature for this type of analysis, most using clustering approaches. This paper presents a two-level generative model that applies the Gaussian mixture model to regroup passengers based on their temporal habits in their public transportation usage. The strength of the proposed methodology is that it can model a continuous representation of time instead of having to employ discrete time bins. For each cluster, the approach provides typical temporal patterns that enable easy interpretation. The experiments are performed on five years of data collected by the Société de transport de l’Outaouais. The results demonstrate the efficiency of the proposed approach in identifying a reduced set of passenger clusters linked to their fare types. A five-year longitudinal analysis also shows the relative stability of public transport usage.     

Operational objective functions in designing public transport routes

This work proposes a framework for the construction of the operational objective functions of the public transport network design problem. This framework takes into account the passengers, operator and community interests. The methodology presented combines the philosophy of the mathematical programming approaches with decision‐making techniques, so as to allow the user to select from a number of alternatives. The nature of the overall formulation is nonlinear and mixed integer programming.