Thesis (M.Sc.) - Carleton University, 2006. / Includes bibliographical references (p. 70-71). Also available in electronic format on the Internet.

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Social media platforms have the potential to influence destination choice among potential travellers.Before potential travellers embark on a trip, they are faced with decision-making processes on whereto go, what to do, the best time to go, how to get there among other things. These pre-travel planning decisions can be influenced by their expectation of the experiences they will encounter at the destination and based on their perception of the destination. Their perception of destinations isusually informed by information found on social media platforms or passed on by family and friendswho have encountered similar travel experiences. Using Crompton’s model of destination choice set,this study explores the roles of social media platforms on destination choice among international students in the Umea university.

This thesis compared revealed-preference automobile morning work commute trip data from GPS-equipped instrumented vehicles of Commute Atlanta participants with transit commute alternatives identified in the regional planning model transit network. The Transit Capacity and Quality of Service Manual (TCQSM) travel time level of service (LOS) measure for transit was applied to these GPS automobile and modeled transit data. To quantify system-level transit availability, the TCQSM service coverage LOS was applied to the Atlanta region and Atlanta s transit service area LOS was calculated as C. Most of the commuters in this study would experience transit-auto travel time LOS of F. The analyses revealed that revealed automobile travel times were 45% shorter than the model-reported automobile travel time skims for the same origin and destination zones. Transit traces, calculated by manually tracing the trips from origin to destination via the most preferable transit mode, were about 24% longer than the minimum travel-demand-modeled transit skims. Only about 9% of commuters drove directly to work more than 95% of the time and only 6% of commuters left home within five minutes of their median departure time more than 95% of the time, indicating that the convenience and flexibility of the automobile is likely to be a significant element in these commute mode decisions. Commuters perceive the total transit trip time as between being 1.25 and 2.5 as long as the actual (modeled) time, and only about 25% of commuters could take transit without having to transfer. The calculated total cost of driving to work exceeded the cost of transit, but automobile operating costs alone did not exceed transit costs for about half the sample.

Due to recent pricing studies that have revealed substantial variability in values of time among decision makers with the same socioeconomic characteristics, there is substantial interest in modeling the observed heterogeneity. This study addresses this problem by revealing a previously overlooked connection between choice set and choice behavior. This study estimates a discrete choice model for mode plus route plus time choice, subdivides the population according to empirically formed choice sets, and finds systematic variations among four choice set groups in user preferences for price managed lanes. Rather than assume the same values of the coefficients for all users, the model is separately estimated for each choice set group, and the null hypothesis of no taste variations among them is rejected, suggesting that choice set is an indicator for choice behavior. In the State Route 91 study corridor, the price-managed lanes compete with at least two other congestion-avoiding alternatives. The principal hypothesis is that a person’s willingness to pay depends on whether or not he perceives as personally feasible the option to bypass some congestion in a traditional carpool lane or by traveling outside the peak period. The procedure for estimating the choice sets empirically is predicated on the notion that individuals operate within a wide array of unobservable constraints that can establish the infeasibility of either alternative. The universal choice set includes eight combinations of mode and time and route, wherein there are exactly two alternatives for each. Choice sets are formed from an assumed minimum set, which is expanded to one of three others whenever a non-zero choice probability for either ridesharing, or shoulder period travel, or both is revealed in a person’s history of choice behavior. Based on the test of taste variations, this author finds different values of time across the four choice set groups in the study sample. If these relationships can be validated in other locations, this would make a strong case for modeling choice behavior in value pricing as a function of choice set.

This thesis studies the problem of measuring freedom of choice. It analyzes the concept of freedom of choice, discusses conditions that a measure should satisfy, and introduces a new class of measures that uniquely satisfy ten proposed conditions. The study uses a decision-theoretical model to represent situations of choice and a metric space model to represent differences between options. The first part of the thesis analyzes the concept of freedom of choice. Different conceptions of freedom of choice are categorized into evaluative and non-evaluative, as well as preference-dependent and preference-independent kinds. The main focus is on the three conceptions of freedom of choice as cardinality of choice sets, representativeness of the universal set, and diversity of options, as well as the three conceptions of freedom of rational choice, freedom of eligible choice, and freedom of evaluated choice. The second part discusses the conceptions, together with conditions for a measure and a variety of measures proposed in the literature. The discussion mostly focuses on preference-independent conceptions of freedom of choice, in particular the diversity conception. Different conceptions of diversity are discussed, as well as properties that could affect diversity, such as the cardinality of options, the differences between the options, and the distribution of differences between the options. As a result, the diversity conception is accepted as the proper explication of the concept of freedom of choice. In addition, eight conditions for a measure are accepted. The conditions concern domain-insensitivity, strict monotonicity, no-choice situations, dominance of differences, evenness, symmetry, spread of options, and limited function growth. None of the previously proposed measures satisfy all of these conditions. The third part concerns the construction of a ratio-scale measure that satisfies the accepted conditions. Two conditions are added regarding scale-independence and function growth proportional to cardinality. Lastly, it is shown that only one class of measures satisfy all ten conditions, given an additional assumption that the measures should be analytic functions with non-zero partial derivatives with respect to some function of the differences. These measures are introduced as the Ratio root measures.

This thesis studies the problem of measuring freedom of choice. It analyzes the concept of freedom of choice, discusses conditions that a measure should satisfy, and introduces a new class of measures that uniquely satisfy ten proposed conditions. The study uses a decision-theoretical model to represent situations of choice and a metric space model to represent differences between options. The first part of the thesis analyzes the concept of freedom of choice. Different conceptions of freedom of choice are categorized into evaluative and non-evaluative, as well as preference-dependent and preference-independent kinds. The main focus is on the three conceptions of freedom of choice as cardinality of choice sets, representativeness of the universal set, and diversity of options, as well as the three conceptions of freedom of rational choice, freedom of eligible choice, and freedom of evaluated choice. The second part discusses the conceptions, together with conditions for a measure and a variety of measures proposed in the literature. The discussion mostly focuses on preference-independent conceptions of freedom of choice, in particular the diversity conception. Different conceptions of diversity are discussed, as well as properties that could affect diversity, such as the cardinality of options, the differences between the options, and the distribution of differences between the options. As a result, the diversity conception is accepted as the proper explication of the concept of freedom of choice. In addition, eight conditions for a measure are accepted. The conditions concern domain-insensitivity, strict monotonicity, no-choice situations, dominance of differences, evenness, symmetry, spread of options, and limited function growth. None of the previously proposed measures satisfy all of these conditions. The third part concerns the construction of a ratio-scale measure that satisfies the accepted conditions. Two conditions are added regarding scale-independence and function growth proportional to cardinality. Lastly, it is shown that only one class of measures satisfy all ten conditions, given an additional assumption that the measures should be analytic functions with non-zero partial derivatives with respect to some function of the differences. These measures are introduced as the Ratio root measures.

Discrete choice experiments are used when choice alternatives can be described in terms of attributes. The objective is to infer the value that respondents attach to attribute levels. Respondents are presented sets of profiles based on attributes specified at certain levels and asked to select the profile they consider best. When the number of attributes or attribute levels becomes large, the profiles in a single choice set may be too numerous for respondents to make precise decisions. One strategy for reducing the size of choice sets is the sub-setting of attributes. However, the optimality of these reduced size choice sets has not been examined in the literature. We examine the optimality of reduced size choice sets for 2^n experiments using information per profile (IPP) as the optimality criteria. We propose a new approach for calculating the IPP of designs obtained by dividing attributes into two or more subsets with one, two, and in general, r overlapping attributes, and compare the IPP of the reduced size designs with the original full designs. Next we examine the IPP of choice designs based on 3^n factorial experiments. We calculate the IPP of reduced size designs obtained by sub-setting attributes in 3^n plans and compare them to the original full designs. / Statistics

People with disabilities tend to face more difficulties and constraints when they are travelling for tourism purposes, compared to non-disabled people. This is problematic because mobility in general (and tourism in particular) is, more or less, seen as a ‘human right’ and has the potential to contribute to peoples’ well-being. Tourism travel should, therefore, be available for everyone. This thesis aims to contribute to the understanding of tourism travel for people with mobility-disabilities by studying the experiences of parents to wheelchair carried children with cerebral palsy. The main study objectives are threefold, namely: (1) which constraints these families face throughout the tourism travel chain; (2) how the child’s disability affect these families’ destination decision processes; and (3) which improvements that can be made in order to make it easier for these families to participate in tourism travel. An interview study was made including 13 parents to wheelchair children with cerebral palsy and these interviews were analysed by using thematic analysis. The findings show that different constraints and barriers (intrinsic, interactive and environmental) are evident during all different phases of the tourism travel chain and affect these families’ choices regarding type of tourism trip, which destination they travel to, which transport modes that they can use, which requirements they have in terms of accommodation and which limitations they face when participating in different activities. Some suggestions regarding improvements are also provided, based on what the parents require in order to make tourism travel easier for them.

This thesis presents a prism- and gap-based approach for modelling shopping destination choice in the Travel/Activity Scheduler for Household Agents (TASHA). The gap-location choice model improves upon TASHA’s existing destination choice model in 3 key ways: 1) Shifting from a zone-based to a disaggregate location choice model, 2) Categorizing shopping trips into meaningful types, and 3) Accounting for scheduling constraints in choice set generation and location choice. The model replicates gap and location choices reasonably well at an aggregate level and shows that a simple yet robust model can be developed with minimal changes to TASHA’s existing location choice model. The gap-based approach to destination choice is envisioned as a small but significant step towards a more comprehensive location choice model in a dynamic activity scheduling environment.