Using AHP to measure the perception gap between current and potential users of bus services

Abstract

This study develops a multicriteria evaluation of user perception towards bus transit services and measures the gap in the perceptions held by current and potential users. A review of the transport quality literature indicates that both preference and satisfaction measures have been implemented to provide a comprehensive perception-based evaluation of bus quality. Although attempts have been made to evaluate user perception through a separate analysis of each (preference and/or satisfaction), the application of multicriteria quality measures are limited. A multicriteria quality measure not only offers more than just information on the daily experience of users but also knowledge of the internal process of quality evaluation (drivers/barriers). The multicriteria measure utilises the data of 512 questionnaires, whereby user perceptions were expressed through judgments of importance and satisfaction based on a set of 29 quality indicators classified into six attributes. Firstly, the study develops analytical hierarchy process (AHP) models to measure user preference. Secondly, a weighted perception index (WPI) of both preference and satisfaction is developed through a multicriteria model. Finally, multivariate analysis of variance (MANOVA) is conducted to identify the level of variation in the perception of both current and potential users towards bus service quality. The results show that although both current and potential users place a higher importance towards the same indicators, they do not share the same pattern of preferences (values and/or order). In addition, the study found that the interaction between preferences and satisfaction generated new patterns of subjective evaluation, and that these patterns vary significantly by user category.     

Deregulating the bus industry in Britain: a reply

In the last four years, some 20 urban areas in the UK have commissioned or considered conducting Integrated Transport Studies, which are designed to develop a transport strategy for the next 20–30 years. Such studies represent a new approach to transport policy formulation, since they respond to a vision of the future for the area, treat a wide range of transport and land use policy instruments, emphasize synergy between those instruments, and provide a framework for facilitating action rather than a rigid blueprint for the future. They also differ from past studies in the speed with which they have been conducted, and in the analytical techniques which have made this possible. This paper reviews the background to these studies, the evaluation approach adopted, the policy instruments considered and the analytical methods developed for the studies. It concludes with an assessment of the policy implications stressing in particular the need to reduce trip length, the crucial impact of pricing as an instrument of transport policy, the importance of achieving synergy in strategy development, and the requirement for a common basis for evaluating and financing different transport policy instruments.     

The influence of habit formation on modal choice —a Heuristic model

Most modal split models have been based on the assumption of rational behaviour in an individual's choice evaluation of the generalised costs of modal alternatives. This paper integrates conceptual and empirical information from a wide range of sources and points towards an alternative way of looking at modal choice. The main conclusion is that the car is usually perceived as the superior mode for vehicular travel and that the potential user is committed to its use largely through the act of purchasing it. The conceptual structure of a sequential modal split model is outlined as one that is based on a four-stage decision-making framework which considers the role of learning and habit-formation. In the conclusion, the implications of this approach are considered in terms of the conventional modal split and trip generation submodels, and certain policy measures are assessed.     

Multicriteria Evaluation of High-speed Rail,Transrapid Maglev and Air Passenger Transport in Europe

This article deals with a multicriteria evaluation of High-Speed Rail, Transrapid Maglev and Air Passenger Transport in Europe. Operational, socio-economic and environmental performance indicators of the specific high-speed transport systems are adopted as the evaluation criteria. By using the entropy method, weights are assigned to particular criteria in order to indicate their relative importance in decision-making. The TOPSIS method is applied to carry out the multicriteria evaluation and selection of the preferable alternative (high-speed system) under given circumstances.     

Institutional issues in planning for more uncertain futures

Future travel demand has always been difficult to estimate. Recent trends of a slow down or stagnation in traffic growth combined with substantial demographic, economic, and technological shifts further complicate that task. This poses a significant planning challenge given that decision-making is often based on the benefits of infrastructure investments which accrue over periods as long as 60 years. In contrast to the changing ideas around what mobility in the future will look like and the types of demand it may need to service, the practice of forecasting future travel demand remains largely unchanged as do the decision-making processes which flow from this. Alternative approaches to thinking about futures such as scenario planning exist but have had more limited deployment in the transport sector. This paper explores the institutional issues surrounding the purpose, practice and barriers to changing the approaches of forecasting and decision-making through an exploration of the state of practice in the UK drawing on interviews with 23 practitioners. Drawing on Hall’s work on policy change, the research finds that there is a strong policy paradigm built around the relationships between transport investment and traffic growth. This has strengthened since the recession with an increased focus on the relationship between transport and job creation. The forecasting approaches in use today are an important part of a complex decision-making apparatus reflective of specialized policy arenas like transport. Challenges in acknowledging, representing and communicating uncertainty are identified leaving a growing tension between planning visions and planning practice. We conclude by reflecting on events which may stimulate a broader reframing of how we plan for transport futures whilst embracing key uncertainties.

     

How,when and why integrated choice and latent variable models are latently useful

Integrated Choice and Latent Variable (ICLV) models are an increasingly popular extension to discrete choice models that attempt explicitly to model the cognitive process underlying the formation of any choice. This study was born from the discovery that an ICLV model can in many cases be reduced to a choice model without latent variables that fits the choice data at least as well as the original ICLV model from which it was obtained. The failure of past studies to recognize this fact raised concerns about other benefits that have been claimed with regards to the framework. With the objective of addressing these concerns, this study undertakes a systematic comparison between the ICLV model and an appropriately specified reduced form choice model. We derive analytical proofs regarding the benefits of the framework and use synthetic datasets to corroborate any conclusions drawn from the analytical proofs. We find that the ICLV model can under certain conditions lead to an improvement in the analyst's ability to predict outcomes to the choice data, allow for the identification of structural relationships between observable and latent variables, correct for bias arising from omitted variables and measurement error, reduce the variance of parameter estimates, and abet practice and policy, all in ways that would not be possible using the reduced form choice model. We synthesize these findings into a general process of evaluation that can be used to assess what gains, if any, might be had from developing an ICLV model in a particular empirical context.     

Economic appraisal of European transport projects: The state-of-the-art revisited

Substantial investment has been made at national and European level in transport infrastructure over the past 50 years and is likely to continue in the future. The need to appraise transport projects in economic and social terms has developed alongside this in both scope and complexity. The state-of-the-art in the economic appraisal of transport projects is reviewed, progress is assessed and future challenges are identified. The review addresses the general framework, treatment of major impacts, presentation of outputs and issues such as uncertainty. It draws on national practice in Western European countries, which varies substantially reflecting a range of cultural and economic differences. Some points of commonality exist and the principle of monetizing direct transport impacts is generally accepted. Progress has been made towards the measurement of environmental impacts, but the assessment of the wider impacts remains under-developed. Increased sophistication and complexity has brought increasing data and presentation requirements, where computerized decision support methods have potential. Many challenges exist for the future of appraisal and the review is concluded with a discussion of some key issues. At the heart of these is the continuing debate over the relative roles of national and European government in decision-making and resource allocation.     

Time-dependent congestion pricing system for large networks: Integrating departure time choice,dynamic traffic assignment and regional travel surveys in the Greater Toronto Area

Congestion pricing is one of the widely contemplated methods to manage traffic congestion. The purpose of congestion pricing is to manage traffic demand generation and supply allocation by charging fees (i.e., tolling) for the use of certain roads in order to distribute traffic demand more evenly over time and space. This study presents a framework for large-scale variable congestion pricing policy determination and evaluation. The proposed framework integrates departure time choice and route choice models within a regional dynamic traffic assignment (DTA) simulation environment. The framework addresses the impact of tolling on: (1) road traffic congestion (supply side), and (2) travelers’ choice dimensions including departure time and route choices (demand side). The framework is applied to a simulation-based case study of tolling a major freeway in Toronto while capturing the regional effects across the Greater Toronto Area (GTA). The models are developed and calibrated using regional household travel survey data that reflect the heterogeneity of travelers’ attributes. The DTA model is calibrated using actual traffic counts from the Ontario Ministry of Transportation and the City of Toronto. The case study examined two tolling scenarios: flat and variable tolling. The results indicate that: (1) more benefits are attained from variable pricing, that mirrors temporal congestion patterns, due to departure time rescheduling as opposed to predominantly re-routing only in the case of flat tolling, (2) widespread spatial and temporal re-distributions of traffic demand are observed across the regional network in response to tolling a significant, yet relatively short, expressway serving Downtown Toronto, and (3) flat tolling causes major and counterproductive rerouting patterns during peak hours, which was observed to block access to the tolled facility itself.     

Assessment of policies and detection of unintended effects: Guiding principles for the consideration of methods and tools in policy-packaging

Single policies or entire policy packages are often assessed using different methods aiming at a quantification of effects as well as the detection of undesired outcomes. The knowledge of potential impacts is essential to take informed policy actions. Hence, there is a constant need for efficient assessment approaches to support policy decision-making. A broad range of such assessment methods is used in policymaking. Some of them are using quantitative data; others are characterized by qualitative information, observations or opinions. Practical experiences with transport policy prove that these methods all have their pros and cons, but none of them are able to detect the full range of effects. This leads to important questions this article deals with, such as what are the strengths and limitations of the different tools and methods for assessing impacts, and how should different approaches be integrated into the policymaking processes?We analyze the ability of assessment methods to detect different kinds of intended and unintended effects, and introduce the concepts of structurally open (mainly qualitative) and structurally closed (mainly quantitative) methods. It is argued that these concepts support making the pros and cons of the tools and methods more explicit and, thus, allow integrating the different tools and methods into the process of policy packaging. Based on a policy package example, we provide practical recommendations on how to integrate different assessment methods adequately and show that both quantitative and qualitative tools should be used in different phases of the process. The main recommendation is to alternate the application of assessment methods with structurally open methods used in the beginning and the end of the policymaking process and applying structurally closed methods in between.     

A fuzzy multicriteria model to evaluate the privatization of the public bus operations

A double model based on fuzzy synthetic decision and a fuzzy multicriteria decision is presented for this study. In a basic level decision, we use a fuzzy synthetic decision to reduce the sub-criteria calculation work. In a higher level decision, the approximation reasoning allows the decision maker to make his best choice. These methods are more in accordance with the thinking processes of the human mind when complex issues are involved. Therefore, this paper will use a fuzzy linguistic approach, instead of the traditional approach to avoid the interference of the numerical estimates for weight and performance of alternatives. In the end, a heuristic algorithm for the evaluating process is developed and demonstrated in a case study.     

An integrated assessment of alternative land-based passenger transport policies: A case study in Tenerife

Over recent decades, there have been numerous cases of land-based transport policies that have lacked clear and coherent strategies. This has not only hampered the resolution of issues like road congestion, but has also created new ones (e.g. strong social opposition to new train infrastructures). The absence of such strategies highlights the need for long-term transport policies with a wider vision of the issues, since land-based transport cannot be considered from just a technical perspective.The main objective of this article is to implement a participatory integrated approach to facilitate the understanding of land-based passenger transport governance issues on Tenerife, in the Canary Islands. Relevant policy issues and alternatives are identified by the stakeholders involved. The inclusion of stakeholders in the assessment process is crucial to frame transport governance issues appropriately and to define and assess plausible policy alternatives. This assessment process even included a final step of validation of the results by stakeholders to foster discussion among them about transport issues and policy alternatives.Finally, due to the obstructive role played by some stakeholders in influencing past transport policies, an analysis of possible coalitions among stakeholders is also discussed.     

Sustainability Assessment of Transport Infrastructure Projects: A Review of Existing Tools and Methods

Abstract

Attempts to integrate sustainability in the decision-making process for transport infrastructure projects continue to gain momentum. A number of tools and methodological frameworks are available — such as rating systems, traditional decision-making techniques, checklists, and different evaluation frameworks and models. While these tools are highly valuable, some practical issues remain unsolved. There is also a need for more standardized tools to appraise the sustainability of transport projects. This paper is a presentation of a review on the current assessment tools of sustainability applied to transport infrastructure projects. The preliminary part of the paper is an explanatory and comparative analysis of the tools and methods in terms of their effectiveness to appraise sustainability. The analysis is a critical evaluation of the current state of the art to identify the limitations of existing approaches, point out new areas of research, and propose a sustainability appraisal agenda for the future.     

Quantifying the benefit of responsive pricing and travel information in the stochastic congestion pricing problem

This paper is concerned with roadway pricing amidst the uncertainty which characterizes long-term transportation planning. Uncertainty is considered both on the supply-side (e.g., the effect of incidents on habitual route choice behavior) and on the demand-side (e.g., due to prediction errors in demand forecasting). The framework developed in this paper also allows the benefits of real-time travel information to be compared directly against the benefits of responsive pricing, allowing planning agencies to identify the value of these policy options or contract terms in publicly-operated toll roads. Specifically, six scenarios reflect different combinations of policy options, and correspond to different solution methods for optimal tolls. Demonstrations are provided on both the Sioux falls and Anaheim networks. Results indicate that providing information to drivers implemented alongside responsive tolling may reduce expected total system travel time by over 9%, though more than 8% of the improvement is due to providing information, with the remaining 1% improvement gained from responsive tolling.     

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.     

Decision makers and socializers, social networks and the role of individuals as participants

Models explaining and predicting human travel behavior have gone through many changes in the past few decades. As researchers attempt to explain more and predict with more accuracy, the inclusion of social interactions in modeling and simulation is being recognized as a necessity. Among these efforts, researchers have focused on issues such as the composition of social networks, and the constraints and influences that others have on spatial decisions. An important aspect that has been understudied however is the variability or heterogeneity of individuals both as social network members and as participants in these social networks. Understanding the role individuals play in decision-making in different social networks can further define our models to include more accurate representations of human behavior. This research explores the differences between social network composition, and the decision roles members play within different social networks specifically when deciding where to participate in activities. A survey was conducted in Santa Barbara, California on social network involvement, network attributes and decision-making roles within each network. Two separate latent class cluster analysis models were developed to classify social network involvement and roles. Results show that there are clearly different types of social involvement and roles within networks. Further data collection and analysis will be used to better understand how these decision-making roles manifest themselves in activity decision-making.     

Fleeing from Hurricane Irma: Empirical Analysis of Evacuation Behavior Using Discrete Choice Theory

This paper analyzes the observed decision-making behavior of a sample of individuals impacted by Hurricane Irma in 2017 (n = 645) by applying advanced methods based in discrete choice theory. Our first contribution is identifying population segments with distinct behavior by constructing a latent class choice model for the choice whether to evacuate or not. We find two latent segments distinguished by demographics and risk perception that tend to be either evacuation-keen or evacuation-reluctant and respond differently to mandatory evacuation orders.Evacuees subsequently face a multi-dimensional choice composed of concurrent decisions of their departure day, departure time of day, destination, shelter type, transportation mode, and route. While these concurrent decisions are often analyzed in isolation, our second contribution is the development of a portfolio choice model (PCM), which captures decision-dimensional dependency (if present) without requiring choices to be correlated or sequential. A PCM reframes the choice set as a bundle of concurrent decision dimensions, allowing for flexible and simple parameter estimation. Estimated models reveal subtle yet intuitive relations, creating new policy implications based on dimensional variables, secondary interactions, demographics, and risk-perception variables. For example, we find joint preferences for early-nighttime evacuations (i.e., evacuations more than three days before landfall and between 6:00 pm and 5:59 am) and early-highway evacuations (i.e., evacuations more than three days before landfall and on a route composed of at least 50% highways). These results indicate that transportation agencies should have the capabilities and resources to manage significant nighttime traffic along highways well before hurricane landfall.     

Changes in transport planning policy: Changes in transport planning methodology?

The 1990s saw the emergence of influential transport legislation both in the UK and in the USA. This "watershed" period appears to indicate that a significant turning point in transport policy is underway. There is now a need to re-evaluate how transport planning is done, and to consider changes to commonly used methods. Criticisms of urban transport planning are traced in the paper. These often focus on the four-stage modelling approach, but some authors also criticise the "rational comprehensive" paradigmatical framework within which the use of four-stage computer models is situated. It is argued that the rational comprehensive model of thinking is less useful today, due to the increasing complexity of the transport planning exercise; the rejection by the public of the transport planner as "expert"; and the highly political nature of transport planning. Alternative approaches are needed in order to address the new types of problems which transport planners face. The use of one such alternative approach, the Soft Systems Methodology, is illustrated as suitable for investigating complex decision-making systems in transport planning. It is suggested that this method could be beneficial in other problematic transport planning situations where the rational comprehensive approaches prove inadequate. Finally, the paper briefly looks ahead and considers the implications of a changing policy environment to the training of transport planners in the future.     

How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales

Much of the literature shows that a compact city with well-mixed land use tends to produce lower vehicle miles traveled (VMT), and consequently lower energy consumption and less emissions. However, a significant portion of the literature indicates that the built environment only generates some minor—if any—influence on travel behavior. Through the literature review, we identify four major methodological problems that may have resulted in these conflicting conclusions: self-selection, spatial autocorrelation, inter-trip dependency, and geographic scale. Various approaches have been developed to resolve each of these issues separately, but few efforts have been made to reexamine the built environment-travel behavior relationship by considering these methodological issues simultaneously. The objective of this paper is twofold: (1) to better understand the existing methodological gaps, and (2) to reexamine the effects of built-environment factors on transportation by employing a framework that incorporates recently developed methodological approaches. Using the Seattle metropolitan region as our study area, the 2006 Household Activity Survey and the 2005 parcel and building data are used in our analysis. The research employs Bayesian hierarchical models with built-environment factors measured at different geographic scales. Spatial random effects based on a conditional autoregressive specification are incorporated in the hierarchical model framework to account for spatial contiguity among Traffic Analysis Zones. Our findings indicate that land use factors have highly significant effects on VMT even after controlling for travel attitude and spatial autocorrelation. In addition, our analyses suggest that some of these effects may translate into different empirical results depending on geographic scales and tour types.     

Experimental design influences on stated choice outputs: An empirical study in air travel choice

Discrete choice experiments are conducted in the transport field to obtain data for investigating travel behaviour and derived measures such as the value of travel time savings. The multinomial logit (MNL) and other more advanced discrete choice models (e.g., the mixed MNL model) have often been estimated on data from stated choice experiments and applied for planning and policy purposes. Determining efficient underlying experimental designs for these studies has become an increasingly important stream of research, in which the objective is to generate stated choice tasks that maximize the collected information, yielding more reliable parameter estimates. These theoretical advances have not been rigorously tested in practice, such that claims on whether the theoretical efficiency gains translate into practice cannot be made. Using an extensive empirical study of air travel choice behaviour, this paper presents for the first time results of different stated choice experimental design approaches, in which respective estimation results are compared. We show that D-efficient designs keep their promise in lowering standard errors in estimating, thereby requiring smaller sample sizes, ceteris paribus, compared to a more traditional orthogonal design. The parameter estimates found using an orthogonal design or an efficient design turn out to be statistically different in several cases, mainly attributed to more or less dominant alternatives existing in the orthogonal design. Furthermore, we found that small designs with a limited number of choice tasks performs just as good (or even better) than a large design. Finally, we show that theoretically predicted sample sizes using the so-called S-estimates provide a good lower bound. This paper will enable practitioners in better understanding the potential benefits of efficient designs, and enables policy makers to make decisions based on more reliable parameter estimates.