Amalia Polydoropoulou

Extended Framework for Modeling Choice Behavior

We review the case against the standard model of rational behavior and discuss the consequences of various ‘anomalies’ of preference elicitation. A general theoretical framework that attempts to disentangle the various psychological elements in the decision-making process is presented. We then present a rigorous and general methodology to model the theoretical framework, explicitly incorporating psychological factors and their influences on choices. This theme has long been deemed necessary by behavioral researchers, but is often ignored in demand models. The methodology requires the estimation of an integrated multi-equation model consisting of a discrete choice model and the latent variable model system. We conclude with a research agenda to bring the theoretical framework into fruition.

TRAVEL SIMULATORS FOR DATA COLLECTION ON DRIVER BEHAVIOR IN THE PRESENCE OF INFORMATION

Abstract Understanding traveler response to potential ATIS services is critical for designing such services and evaluating their effectiveness. Extensive data is required for developing the models necessary to provide this understanding. In this paper we examine one source of such data: traveler simulators. We make a distinction between travel simulators, used to study the travelers response to information acquisition, and driving simulators, which are elaborate tools used mainly for human factors research. Traveler simulators have the potential to provide a wealth of data collected relatively inexpensively under controlled conditions. However the data may suffer from biases introduced because of the laboratory nature of travel simulators. We examine various existing simulators and comment on their advantages and disadvantages. We make recommendations for simulator design characteristics that increase the reliability of the data collected and suggest enhancements so that current simulators can be used for the collection of data related to access and acquisition of ATIS products as well. We conclude the paper with recommendations for future research in the area.

Combined Revealed and Stated Preference Nested Logit Access and Mode Choice Model for Multiple Mass Transit Technologies

A combined stated preference (SP) and revealed preference nested logit model of access and main mode choice was developed for the Tel Aviv metropolitan area. The data used for model estimation include a conventional travel-activity survey and a customized, computerized SP survey. The model incorporates a generic mass transit alternative that represents any possible combination of existing and new technologies, such as heavy rail, enhanced bus, light rail, and suburban rail. The lower level of the nested logit model represents the access choice to the bus or mass transit alternatives, including walk, park and ride, kiss and ride, and bus access alternatives; the upper level represents the mode choice among bus, mass transit, car driver, and car passenger alternatives. Travel time reliability and seat availability are among the attributes of the public transportation alternatives.

IMPACT OF ADVANCED PUBLIC TRANSPORTATION SYSTEMS ON TRAVEL BY DIAL-A-RIDE

The degree to which Advanced Public Transportation Systems (APTS) are expected to increase ridership is studied. The responses from a survey of Dial-a-Ride users to estimate the parameters of statistical models of user behavior were used. The respondents were asked to rank hypothetical scenarios in which level of service was varied. Level-of-service attributes included, among other variables, changes in travel time and ability to reserve the trip in advance. The respondents were asked to state how many trips they would have made during the past week of travel, given the hypothetical service attributes described in the question. The models developed link the average number of trips per week using Dial-a-Ride and the level of service offered by the Dial-a-Ride system. The modeling framework attempts to resolve the bias issues inherent in the use of stated preferences (SP) data, where respondents are asked to answer questions about a hypothetical situation. A basic methodology of combining revealed preferences and SP data is provided to evaluate the effect of different APTS configurations on ridership.

Development of a Latent Variable Model to Capture the Impact of Risk Aversion on Travelers' Switching Behavior

This paper presents a case study on travelers’ response to traffic information using data collected from the Puget Sound Region (PSRC). The data come from travel diaries (collected in 2000), where individuals were asked about the traveler information sources consulted on each trip and how the information was used. Traveler information sources, available in the region, encompass both conventional forms of information, such as radio traffic reports, and advanced traveler information systems, such as variable message signs (VMS) and web sites. The objective of this research is to examine the impact of information acquisition on switching travel behavior and to identify and quantify the role of attitudes and perceptions on switching behavior. A combined choice and latent variable model has been developed and estimated. The estimated model shows that travel pattern characteristics, the primary reason for seeking information, the source and the content of provided information, as well as the attitude of individuals towards risk significantly affect commuters’ response to information.

Forecasting Paratransit Ridership Using Discrete Choice Models with Explicit Consideration of Availability

In most developed countries, the population of the elderly and disabled is growing rapidly. These individuals require transportation service suited to their needs. Such service may be provided by applying emerging technologies to dial-a-ride transit. This research develops a methodology to quantitatively evaluate the impact of paratransit services on a traveler’s mode choice behavior. The mode choice model explicitly considers availability of alternative modes and includes latent factors to account for taste heterogeneity. Stated preferences are also used to elicit preferences for new paratransit services. The methodology is empirically tested with data collected in Winston-Salem, North Carolina. The model system developed is applied to evaluate the effect of improving service attributes and the impact of the introduction of new cost-effective modes on modal shares. Results of the policy analysis indicate that (a) transit policy changes, such as fare reduction, would have little effect on automobile driver and automobile passenger shares; (b) an improved reservation system for dial-a-ride services would produce shifts in mode share; (c) the proposed new bus deviation service was favored; (d) free bus service reduces dial-a-ride share; and (e) an increase in awareness of a dial-a-ride system would significantly increase its share.

Evaluating the impact of decision making during construction on transport project outcome.

Decisions made during the project construction phase may bear considerable impacts on the success of transport projects and undermine the ex-ante project evaluation. An innovative and holistic approach has been taken to assess and address this issue by (a) examining the decision process and procedure during project construction, through a field survey, (b) assessing the impact of decisions made during construction on respective transport project and, finally, (c) developing a quality monitoring framework model which links decisions made during the project implementation (construction) phase with the ex-ante and ex-post project evaluations. The framework model is proposed as a guiding and support tool for decision makers.

Generation Y’s Travel Behavior and Perceptions of Walkability Constraints

The aim of this study was to investigate the interrelationship between urban environment and walking to school and how teenagers’ perceptions of walkability (i.e., how friendly an area is to walking) constraints affected their mode choice. An advanced hybrid mode choice model was developed in which the utilities of the alternative modes depended on the mode characteristics, teenagers’ socioeconomic characteristics, weather conditions, and built environment characteristics, as well as a latent variable referring to walking constraints. The indicators of the latent variable included perceptions regarding the existence of stray animals, poor lighting, narrow sidewalks, parked cars that obscure visibility, unsignalized intersections, and probability of attack and safety en route. A questionnaire survey that took place at high schools of three distinct geographic areas in Greece (an urban area, a rural area, and an insular area) during 2011–2012 was the basis for a case study; 1,988 high school students aged 12 and 18 years old participated in the survey. Adolescents in rural areas walked a greater distance than did urban and insular adolescents. Model estimation results showed that teenagers from each geographical area were affected in different ways by weather conditions and they also perceived the built environment in different ways; this perception indicates how significant the sense of place is. The incorporation of the latent variable enhanced the explanatory power of the model, and the results of the study provide insights on policies that may help Generation Y to keep walking.

Chapter 9 Demand Models for Greek Passenger Shipping

Passenger shipping in Greece is an important sector of the economy and holds a significant share of the transport market for the movements of residents, business, and tourist travellers. This is more so in the Aegean archipelagos where shipping constitutes the main alternative for passenger travel from/to most of the islands, complemented in the case of the bigger islands by air travel. Over the last few years, the Greek passenger shipping industry has undergone several changes including the introduction of fast high-technology ships and a growth in the volume of passenger transport. These conditions have created an environment that is more competitive, demanding, and dynamic, making the application of advanced analysis techniques for forecasting the demand for travel of critical strategic importance. This chapter developed a methodological demand modelling framework based on understanding the choice behaviour of individuals addressing the competition and/or complementarity of ships and aeroplanes. The methodology was applied to a case study on the competition between passenger shipping and aviation in the Northern Aegean region, based on the analysis of individual choice data collected on an annual base for 2001-2005. The models developed included a Multinomial Logit Model with dependent variable, the choice among different types of shipping lines and airlines. The estimation results showed that travel times and travel costs of the alternative modes play significant role in the choice of the alternatives. Furthermore, socio-economic characteristics such as age, education level, purpose of trip, and experience represented by the prior frequency of travel with the specific mode were also found significant. In addition, response bias indicators were applied to capture the propensity of respondents to justify their prior choices and their travel-related constraint to be accompanied by their car in their trip. The models developed were used to calculate value of times for the alternative modes. These models can be also used for prediction of the market shares for the different alternative modes. The methodology and modelling results presented in this chapter offer a unique paradigm for applying innovative techniques of Decision-Making Theory that can be used by policy-makers and service providers to offer services better tailored to the passengers needs.

The Value of Privacy: Evidence From the Use of Mobile Devices for Traveler Information Systems

The emergence of location-based services has raised privacy to a hot-issue status. Clearly, there is a trade-off that needs to be considered. On the one hand, additional information can arguably improve the quality of the various services, not only for the individual, but also for the entire system. On the other hand, the collection of this additional information can be considered by some as a violation of their privacy. The objective of this article is twofold: on the one hand to provide a way to quantify the value of this privacy (loss), and on the other hand to present results from a case study applying this methodology. The methodology is generic and is based on the concept of the marginal rate of substitution between cost and a different variable (in this case privacy). The application is based on a stated-preference questionnaire that was specifically designed for this application and disseminated to respondents in Athens, Greece. An ordered probit model, in which all variables are interacted with the main service attributes (cost, accuracy, and privacy), is estimated based on this data. The empirical distribution of estimated willingness-to-accept for giving up part of the privacy (their current location and destination) was also calculated. The mean of the value of privacy (amount needed to give up one level of privacy) is found to be equal to 3.87€, while the median is equal to 2.50€ (reflecting the skewness of the distribution). This amount is considered reasonable since such services are commercially available for US