Index numbers for monitoring transit service quality

The measurement of transit service quality is very important for guaranteeing a transport supply characterized by satisfactory service levels for the passengers. Even more important is the monitoring of the levels of service quality over time, which can be very useful to determine if the goals established by the transport planners are being met or exceeded. The status and evolution of transit service quality can be monitored through periodic and regular updating of the opinions expressed by the passengers about the service during the well-known Customer Satisfaction Surveys, allowing the effect of policies to be evaluated and specific interventions to be introduced. In this work, just the issue of monitoring service quality based on users’ opinions is approached, and the index numbers usually applied in the economic and industrial field are proposed for this purpose. Index numbers permit to study the fluctuations or variations of a variable or more variables over time, providing a powerful measurement for making comparisons and predictions of the analyzed concept. The index numbers were calculated on the basis of data collected from Customer Satisfaction Surveys addressed to the passengers of the metropolitan public service of Granada (Spain). The analyzed time period has been established from 2007 to 2013. Interesting results derive from the calculation of the index numbers. Since both perceptions and importance rates are considered in this methodology, the results can inform, not only on the satisfaction tendencies but also on the trend on customers’ priorities, which is actually the expected quality. Therefore, policies could more efficiently be designed to adjust the service to the users’ real needs.     

Passengers’ Perceived Service Quality of City Buses in Taipei: Scale Development and Measurement

Abstract

To understand fully passengers’ perceptions and expectations of the bus service quality in Taipei, business managers and governmental agencies must seek a proper scale that can reflect passengers’ opinions accurately. This study develops and tests a service quality scale designed for a city bus transit system in Taipei. Churchill’s paradigm and a focus group interview were combined into a multistage scale development procedure. Based on the procedure, Taipei city buses were selected as the example, for which a service quality scale was developed. The final scale contains four dimensions and 20 items. These four dimensions are ‘interaction with passengers’, ‘tangible service equipment’, ‘convenience of service’ and ‘operating management support’. Finally, the results of scale development and the managerial applications of the service quality scale for the city transit system are discussed.     

Park-and-ride lot choice model using random utility maximization and random regret minimization

This research aims to understand the park-and-ride (PNR) lot choice behaviour of users i.e., why PNR user choose one PNR lot versus another. Multinomial logit models are developed, the first based on the random utility maximization (RUM) concept where users are assumed to choose alternatives that have maximum utility, and the second based on the random regret minimization (RRM) concept where users are assumed to make decisions such that they minimize the regret in comparison to other foregone alternatives. A PNR trip is completed in two networks, the auto network and the transit network. The travel time of users for both the auto network and the transit network are used to create variables in the model. For the auto network, travel time is obtained using information from the strategic transport network using EMME/4 software, whereas travel time for the transit network is calculated using Google’s general transit feed specification data using a backward time-dependent shortest path algorithm. The involvement of two different networks in a PNR trip causes a trade-off relation within the PNR lot choice mechanism, and it is anticipated that an RRM model that captures this compromise effect may outperform typical RUM models. We use two forms of RRM models; the classical RRM and µRRM. Our results not only confirm a decade-old understanding that the RRM model may be an alternative concept to model transport choices, but also strengthen this understanding by exploring differences between two models in terms of model fit and out-of-sample predictive abilities. Further, our work is one of the few that estimates an RRM model on revealed preference data.

     

On the effect of operational service attributes on transit satisfaction

Public transport (PT) providers aim to offer services that meet users’ satisfaction, and for this, they can control some operational service attributes such as frequency, speed, crowdedness and reliability. Understanding how these objective attributes affect user satisfaction is essential to improve it cost-effectively, but these associations have not been examined enough in the PT literature. This study aims to unveil how key transit operational variables actually experienced by users affect their satisfaction. We analysed data derived from a multiannual consumer satisfaction survey for the Santiago de Chile Metro system; between January 2013 and June 2016 (n?=?41,993), where approximately 1000 questionnaires were completed each month. We also gained access to a set of operational variables managed by Metro for the same period, including more than 1.4 million records. With this unique dataset, we first developed a structural equation model (SEM) with users’ perceived attributes, finding that safety, ease of boarding, response to critical incidents (CI), the number and type of CI endured, and information, were the variables that mostly affected satisfaction. We also examined heterogeneity in transit satisfaction with SEM-MIMIC models, by characterising the user population through their trip and socioeconomic characteristics, finding a striking result: that as users age they are more satisfied with the system. Next, we assessed whether including operational service attributes, such as crowding levels, frequency, commercial speed and CI, added predictive power to the proposed model. We found that the number of CI, speed, frequency and crowdedness, plus their variability (measured through the coefficient of variation), affected transit satisfaction at significant levels. Including these objective service attributes provided more explanatory power to the SEM-MIMIC transit satisfaction models. Policy recommendations for improving satisfaction, derived from our results, are: to implement an automatic control system for the number of passengers on Metro platforms (as safety and ease of boarding are critical issues for passengers); and to deploy a comprehensive tactical plan to address CI: determine which happen more often, take actions to minimise them and provide better responsive actions.

     

Impact assessment of the Internet of Things on feeder transit performance

ABSTRACT

Efficient planning for demand responsive transit (DRT) can contribute to fulfilling the first/last mile transport needs for users of a major transit line. With the advancement in communication technologies, the internet is expected to assist this growing need of providing first/last mile connectivity. This is proposed to be achieved through a network created by Internet of Things (IoT). This paper evaluates the effect of implementation of IoT on service quality (or disutility) of DRT for two scenarios – with enabled-IoT (e-IoT) and with disabled-IoT (d-IoT). Data from five different DRT-like systems known as Call-n-Ride (CnR) routes operating in Denver, Colorado, are used for evaluation purposes. These CnR routes are Meridian, Interlocken, South Inverness, Broomfield and Louisville. Results show that, in general, all CnR routes would experience more than a 58 percent decrease in disutility if their operations were based on ‘with e-IoT’ operations. Interlocken would record the largest percentage decrease (74 percent) in disutility if its route service switched from the ‘with d-IoT’ to the ‘with e-IoT’ scenario.     

Public transit service operation strategy under indifference thresholds‐based bi‐modal equilibrium

This paper investigates public transit service (fare and frequency) operation strategies in a bi‐modal network with assumption of indifference thresholds‐based travelers' mode choice behavior. Under such behavior, users would switch to a new mode only if its utility is larger than the utility of current mode plus a threshold. The concept of indifference thresholds‐based bi‐modal equilibrium (ITBE) and the properties of the ITBE solution are explicitly proposed. Considering transit operator's different economic objectives (profit‐maximizing, no‐deficit and total system cost‐minimizing), the effect of indifference thresholds on transit fare and frequency schemes is studied. Some numerical experiments are accompanied to verify the theoretical results. Copyright © 2016 John Wiley & Sons, Ltd.     

Learning-based framework for transit assignment modeling under information provision

The modeling of service dynamics has been the focus of recent developments in the field of transit assignment modeling. The emerging focus on dynamic service modeling requires a corresponding shift in transit demand modeling to represent appropriately the dynamic behaviour of passengers and their responses to Intelligent Transportation Systems technologies. This paper presents the theoretical development of a departure time and transit path choice model based on the Markovian Decision Process. This model is the core of the MIcrosimulation Learning-based Approach to TRansit Assignment. Passengers, while traveling, move to different locations in the transit network at different points in time (e.g. at stop, on board), representing a stochastic process. This stochastic process is partly dependent on the transit service performance and partly controlled by the transit rider’s trip choices. This can be analyzed as a Markovian Decision Process, in which actions are rewarded and hence passengers’ optimal policies for maximizing the trip utility can be estimated. The proposed model is classified as a bounded rational model, with a constant utility term and a stochastic choice rule. The model is appropriate for modeling information provision since it distinguishes between individual’s experience with the service performance and information provided about system dynamics.     

Effect of critical incidents on public transport satisfaction and loyalty: an Ordinal Probit SEM-MIMIC approach

Transportation - Supplying public transport systems with high levels of service quality is fundamental for retaining users and attracting new ones. Policies that improve transit service quality...     

Modelling users’ behaviour in inter-urban carsharing program: A stated preference approach

In this paper, the effects of a inter-urban carsharing program on users’ mode choice behaviour were investigated and modelled through specification, calibration and validation of different modelling approaches founded on the behavioural paradigm of the random utility theory. To this end, switching models conditional on the usually chosen transport mode, unconditional switching models and holding models were investigated and compared. The aim was threefold: (i) to analyse the feasibility of a inter-urban carsharing program; (ii) to investigate the main determinants of the choice behaviour; (iii) to compare different approaches (switching vs. holding; conditional vs. unconditional); (iv) to investigate different modelling solutions within the random utility framework (homoscedastic, heteroscedastic and cross-correlated closed-form solutions). The set of models was calibrated on a stated preferences survey carried out on users commuting within the metropolitan area of Salerno, in particular with regard to the home-to-work trips from/to Salerno (the capital city of the Salerno province) to/from the three main municipalities belonging to the metropolitan area of Salerno. All of the involved municipalities significantly interact each other, the average trip length is about 30 km a day and all are served by public transport. The proposed carsharing program was a one-way service, working alongside public transport, with the possibility of sharing the same car among different users, with free parking slots and free access to the existent restricted traffic areas. Results indicated that the inter-urban carsharing service may be a substitute of the car transport mode, but also it could be a complementary alternative to the transit system in those time periods in which the service is not guaranteed or efficient. Estimation results highlighted that the conditional switching approach is the most effective one, whereas travel monetary cost, access time to carsharing parking slots, gender, age, trip frequency, car availability and the type of trip (home-based) were the most significant attributes. Elasticity results showed that access time to the parking slots predominantly influences choice probability for bus and carpool users; change in carsharing travel costs mainly affects carpool users; change in travel costs of the usually chosen transport mode mainly affects car and carpool users.     

Flexing service schedules: Assessing the potential for demand-adaptive hybrid transit via a stated preference approach

This paper assesses the demand for a flexible, demand-adaptive transit service, using the Chicago region as an example. We designed and implemented a stated-preference survey in order to (1) identify potential users of flexible transit, and (2) inform the service design of the flexible transit mode. Multinomial logit, mixed-logit, and panel mixed-logit choice models were estimated using the data obtained from the survey. The survey instrument employed a d_p-efficient design and the Google Maps API to capture precise origins and destinations in order to create realistic choice scenarios. The stated-preference experiments offered respondents a choice between traditional transit, car, and a hypothetical flexible transit mode. Wait time, access time, travel time, service frequency, cost, and number of transfers varied across the choice scenarios. The choice model results indicate mode-specific values of in-vehicle travel time ranging between $16.3 per hour (car) and $21.1 per hour (flexible transit). The estimated value of walking time to transit is $25.9 per hour. The estimated value of waiting time at one’s point of origin for a flexible transit vehicle is $11.3 per hour; this value is significantly lower than the disutility typically associated with waiting at a transit stop/station indicating that the ‘at-home’ pick-up option of flexible transit is a highly desirable feature. The choice model results also indicate that respondents who use active-transport modes or public transit for their current commute trip, or are bikeshare members, were significantly more likely to choose flexible and traditional transit than car commuters in the choice experiments. The implications of these and other relevant model results for the design and delivery of flexible, technology-enabled services are discussed.     

Transit Users’ Route‐Choice Modelling in Transit Assignment: A Review

Abstract

This paper reviews the main studies on transit users’ route choice in the context of transit assignment. The studies are categorized into three groups: static transit assignment, within‐day dynamic transit assignment, and emerging approaches. The motivations and behavioural assumptions of these approaches are re‐examined. The first group includes shortest‐path heuristics in all‐or‐nothing assignment, random utility maximization route‐choice models in stochastic assignment, and user equilibrium based assignment. The second group covers within‐day dynamics in transit users’ route choice, transit network formulations, and dynamic transit assignment. The third group introduces the emerging studies on behavioural complexities, day‐to‐day dynamics, and real‐time dynamics in transit users’ route choice. Future research directions are also discussed.     

Bus routing strategies in a transit market: A case study of Hong Kong

Conventionally, the objective of transit routing is often set either to minimize the total operational cost, subject to a given level of service quality, or to maximize the service quality at a given acceptable cost. In a deregulated, commercial‐based environment however, such as bus and railway operations in cities of the UK and Hong Kong where several private firms compete in route‐based or area‐based market, routing becomes one of the means for higher returns rather than just for cost saving. In such a case, how do the transit providers set up their routes for profit‐maximization? Will the routing based on the provider's objective meet the user's objective? How do government regulations and policies affect the choice of transit provider's routing strategy? To answer these questions, we first examine the relationship between the objectives of users and transit providers, set up criteria for transit routing quality, and then investigate the possible routing configurations/patterns for a hypothetical case. These criteria include (1) the load factor of transit, (2) the level of route directness, (3) the level of route overlapping, and (4) the total number of routes and (5) the average of route length. These measures are finally applied to a real case in Hong Kong to examine the route changes of Kowloon Motor Bus from 1975 to 1995. The result of the empirical case reveais how key measures such as load factor are controlled by the bus operator and affected by government policies and how the bus routing pattern was adjusted to meet users' need. Facing the dilemma as evident in Hong Kong between the route directness and the efficiency of road use, we suggest that a rational multi‐modal routing structure be put in place if an institutional solution is introduced so that bus and other transit modes can form a sharing program or an alliance.     

A network equilibrium approach for modelling activity-travel pattern scheduling problems in multi-modal transit networks with uncertainty

An understanding of the interaction between individuals’ activities and travel choice behaviour plays an important role in long-term transit service planning. In this paper, an activity-based network equilibrium model for scheduling daily activity-travel patterns (DATPs) in multi-modal transit networks under uncertainty is presented. In the proposed model, the DATP choice problem is transformed into a static traffic assignment problem by constructing a new super-network platform. With the use of the new super-network platform, individuals’ activity and travel choices such as time and space coordination, activity location, activity sequence and duration, and route/mode choices, can be simultaneously considered. In order to capture the stochastic characteristics of different activities, activity utilities are assumed in this study to be time-dependent and stochastic in relation to the activity types. A concept of DATP budget utility is proposed for modelling the uncertainty of activity utility. An efficient solution algorithm without prior enumeration of DATPs is developed for solving the DATP scheduling problem in multi-modal transit networks. Numerical examples are used to illustrate the application of the proposed model and the solution algorithm.     

Evaluating bicycle-transit users’ perceptions of intermodal inconvenience

Bicycles and transit systems are considered to be the pinnacle of green transportation. The combined use of the two could provide a competitive alternative for an integrated, green, and seamless service, yet relatively few studies have investigated the multimodal integration problems of the entire service chain from the perspective of users. Users’ perceived inconvenience during travel can be regarded as a latent construct that describes an unobservable and immeasurable characteristic. Nevertheless, the traditional Likert method in an ordinal scale causes a misleading statistical inference. The Rasch model eliminates such bias generated by an ordinal scale through a logistic linear transformation, and it compares person parameters with item parameters, which are then subjected to a logarithmic transformation along a logit scale to clearly identify which service items’ inconvenience cannot be easily overcome by certain users. This empirical study demonstrates that perceived inconveniences differ based on the users’ sex, riding frequency, trip purpose, and environmental awareness. The differential item functioning analysis that was adopted in this study can identify the critical factors leading to the differences in perceived inconvenience. Our empirical results suggest that a male cyclist who is a commuter with a high monthly riding frequency and who is environmentally conscious has a better ability than their counterpart to overcome perceived inconveniences during travel using a bicycle-transit service. To effectively mitigate users’ perceived inconvenience, the Rasch analytical results suggest that the improvement of the intra-transit system factors in the short term and the improvement of external environmental factors in the long term will be successful. The information herein proves useful for transportation planners and policy makers when considering the special travel needs of certain groups to create a user-friendly bicycle-transit travel environment that promotes its usage.     

Assessing Service Quality,Switching Costs and Customer Loyalty in Home‐Delivery Services in Taiwan

Abstract

This study empirically investigated service quality, switching costs and customer loyalty from home‐delivery services' customers' perceptive. With regard to service quality attributes, findings indicated that customers were most satisfied with ‘range of delivery’, followed by ‘seldom loses parcels’, ‘invoice accuracy’, ‘prompt and reliable collection’ and ‘delivery by due time’. They were least satisfied with competitiveness of price. A structural equation modelling (SEM) approach was employed to analyse the impact of service quality and switching costs on customer loyalty from customers' perspective. Results revealed that service quality positively influenced switching costs and customer loyalty, and switching costs had a positive effect on customer loyalty. Investigation of the moderating effect of switching costs on the relationship between service quality and customer loyalty indicated that it was significantly important. Theoretical and practical implications of the findings for firms providing home‐delivery services are discussed.     

Importance of user perception in evaluating level of service for bus transit for a developing country like India: a review

Assessment of service quality in bus transit planning has received due attention in recent years from the viewpoint of optimal service allocation. The concept of level of service (LOS) has emerged as an effective tool to measure quality of services. Service-quality assessment provides operators with knowledge on users' satisfaction with existing services and their expected LOSs. The importance of user perception towards assessment of LOS has been acknowledged by researchers. While LOS standards for public transportation have been established by the Transportation Research Board in the USA, researchers have questioned the applicability of these standards in the context of different geographic regions. Since the service delivery environment differs between developed and developing nations, the user perception of service quality varies between these economic regions. Substantial research has been carried out in the context of both developed and developing nations, to identify the bus transit service parameters that affect users' perceived service quality; however, little research exists that establishes LOS thresholds for bus transit, based on user perception. This paper reviews the concept of LOS, describes the importance of user perception in assessment of service quality and identifies the need to establish LOS thresholds for bus transit from user perception for developing countries.     

Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation

A transit service quality study based on cluster analysis was performed to extract detailed customer profiles sharing similar appraisals concerning the service. This approach made it possible to detect specific requirements and needs regarding the quality of service and to personalize the marketing strategy. Data from various customer satisfaction surveys conducted by the Transport Consortium of Granada (Spain) were analyzed to distinguish these groups; a decision tree methodology was used to identify the most important service quality attributes influencing passengers’ overall evaluations. Cluster analysis identified four groups of passengers. Comparisons using decision trees among the overall sample of all users and the different groups of passengers identified by cluster analysis led to the discovery of differences in the key attributes encompassed by perceived quality.     

Emissions of demand responsive services as an alternative to conventional transit systems

The environmental performance of public transport plays a key role in improving air quality in urban areas. An important way of improving existing transit services is to use innovative propulsive systems; however, this needs considerable financial resources that are not always available. Here we assess how the organizational form of the transit system may impact the environment relying on a new methodology that permits comparisons in terms of distance traveled between a traditional fixed-route and a demand responsive transit service. We apply an emission model to find the least polluting transit system under a broad range of scenarios with different road networks, service quality levels and demand densities. Results indicate that demand responsive transit services minimize emissions for high quality service level and low demand density scenarios. Furthermore, the possibility of employing smaller vans with lower emission factors guarantees additional substantial benefits in terms of atmospheric pollution for demand responsive transit services, thereby giving them a competitive advantage in virtually every case.     

Transit user perceptions of driverless buses

This paper reports the results of a stated preference survey of regular transit users’ willingness to ride and concerns about driverless buses in the Philadelphia region. As automated technologies advance, driverless buses may offer significant efficiency, safety, and operational improvements over traditional bus services. However, unfamiliarity with automated vehicle technology may challenge its acceptance among the general public and slow the adoption of new technologies. Using a mixed logit modeling framework, this research examines which types of transit users are most willing to ride in driverless buses and whether having a transit employee on board to monitor the vehicle operations and/or provide customer service matters. Of the 891 surveyed members of University of Pennsylvania’s transit pass benefit program, two-thirds express a willingness to ride in a driverless bus when a transit employee is on board to monitor vehicle operations and provide customer service. By contrast, only 13% would agree to ride a bus without an employee on board. Males and those in younger age groups (18–34) are more willing to ride in driverless buses than females and those in older age groups. Findings suggest that, so long as a transit employee is onboard, many transit passengers will willingly board early generation automated buses. An abrupt shift to buses without employees on board, by contrast, will likely alienate many transit users.

     

The Downs–Thomson Paradox with responsive transit service

Downs (1962) and Thomson (1977) suggested that highway capacity expansion may produce counterproductive effects on the two-mode (auto and transit) transport system (Downs–Thomson Paradox). This paper investigates the occurrence of this paradox when transit authority can have different economic objectives (profit-maximizing or breakeven) and operating schemes (frequency, fare, or both frequency and fare). For various combinations of economic objectives and operating schemes, the interaction between highway expansion and transit service is explored, as well as its impact on travelers’ mode choices and travel utilities. Further, for each combination, the conditions for occurrence of the Downs–Thomson Paradox are established. We show that the paradox never occurs when transit authority is profit-maximizing, but it is inevitable when the transit authority is running to maximize travelers’ utility while maintaining breakeven. This is because the former transit authority tends to enhance transit service (e.g., raise frequency or reduce fare) when facing an expanded highway; and on the contrary, the latter tends to compromise transit service (e.g., reduce frequency or raise fare). Both analytical and numerical examples are provided to verify the theoretical results.