Awj Aloys Borgers

Transport stated choice responses: effects of task complexity, presentation format and literacy

The impact of respondent burden and task complexity on quality of stated choice (SC) data remains an issue in transportation research. Furthermore, little is known on the applicability of the technique to less literate individuals in developing countries. This study describes the results of a SC experiment involving the choice of transport mode for a work trip in the South-African context. The complexity of choice task and presentation method of choice alternatives were varied independently in an SC experiment. The findings suggest that the presentation method has no significant impacts and task complexity does have significant effects on data quality. We find no effect on data quality related to literacy level.

City centre entry points, store location patterns and pedestrian route choice behaviour: A microlevel simulation model

The aim of this paper is to formulate and test a microlevel simulation model of pedestrian route choice and allocation behaviour within city centres. The model is developed to predict the likely effect of transportation plans and retail planning measures on pedestrian behaviour and hence on the profitability of shopping streets. The model captures the main characteristics of pedestrian behaviour as found so far in empirical studies. The model is tested in the city of Maastricht. The results indicate that the model gives a satisfactory description of pedestrian route choice and allocation behaviour. The paper is concluded by discussing some potential improvements of the model.

Residential Choice Behaviour of Dual Earner Households: A Decompositional Joint Choice Model

The residential location decision process has been studied for several decades with use of different approaches. One such approach that has received considerable attention in urban planning is the decompositional approach. This approach involves measuring individual preferences. Residential choice behaviour is, however, often the result of a joint decisionmaking process, especially in the case of dual earner households. In the present paper, the original modelling approach is therefore extended to a model of joint decisionmaking. The results of an empirical application in the context of residential choice behaviour in the Netherlands are described.

Utility-Maximizing Model of Household Time Use for Independent, Shared, and Allocated Activities Incorporating Group Decision Mechanisms

Existing activity-based models of transport demand typically assume an individual decision-making process. The focus on theories of individual decision making may be partially due to the lack of behaviorally oriented modeling methodologies for group decision making. Therefore, an attempt has been made to develop a new model (called the g-Logit household time-use model) for time-use analysis that incorporates group decision-making mechanisms. To do that, it is proposed that household utility function be defined in the form of multilinear utility function, which can represent interactions among household members and interactions among their activities (four types of activity: in-home, out-of-home independent, allocated, and shared). By introducing this household utility function into the time allocation approach, each member’s time-use functions for different types of activities are obtained. The function for independent activities has a structure similar to the one for allocated activities, except the weight parameters are different. In contrast, the time-use function for shared activities has a completely different structure, which results from the complicated processes and strategies for household decision making. The effectiveness of the proposed model is confirmed with activity-travel diary data.

Choice model specification, substitution and spatial structure effects : a simulation experiment

Several choice models are compared on their ability to reproduce two types of simulated data sets. The sets belonging to the first type were generated by using a probit model which is able to account for substitution effects while the data sets of the second type were generated by using a probit model which is able to account for spatial structure effects. The main conclusion of the experiment is that simple models like the multinomial logit model, although they perform less than the models used to generate the data, are sufficiently robust to reproduce the simulated data.

MODELING TRAVELER CHOICE BEHAVIOR USING THE CONCEPTS OF RELATIVE UTILITY AND RELATIVE INTEREST

Individual choice behavior usually involves a complex decision-making process, and is often context-dependent reflecting the influence of choice environment and the fact that the individual has limited information processing ability and varying levels of interest in alternatives. However, the existing models in transportation have not represented these behavioral mechanisms satisfactorily, although to avoid the Independence of Irrelevant Alternatives (IIA) property of the widely used multinomial logit (MNL) model, a variety of non-IIA models have been suggested in the literature. This paper will propose another random utility choice model by introducing the concepts of relative utility and relative interest. A revised MNL model and a revised Nested-MNL model will be developed. Both of these models do not have the IIA property. The performance of these new models will be assessed using conjoint-based activity diary data about the choice of destination and stop pattern.

Urban Form, Road Network Type, and Mode Choice for Frequently Conducted Activities: A Multilevel Analysis Using Quasi-Experimental Design Data

The question of whether characteristics of urban form influence travel behaviour has a long tradition in transportation and urban planning. Positive evidence has been found, however, that serious methodological objections can be raised against many of these studies. Often no explicit attempt was made to disentangle the effects of spatial characteristics against personal and household characteristics. In addition, if both kinds of variables were included in the analysis, researchers were often not aware of the specific statistical problems that relate to the fact that the observations are made at different levels of aggregation. In this paper, therefore, the authors adopt a multilevel analysis to examine the relationship between urban form and travel behaviour.

Inducing heuristic principles of tourist choice of travel mode: a rule-based approach.

This article argues that tourists do not necessarily maximize their utility in selecting a travel mode; rather, their choice behavior is context dependent. Given particular conditions related to their family, the environment, and other aspects of the tourist experience, they are assumed to use different heuristics. The present study elicits these choice heuristics from observed data using a tree induction algorithm based on the chi-squared automatic interaction detection (CHAID) algorithm. The induced decision rules are presented in decision tables because this formalism allows one to verify the exhaustiveness, exclusiveness, and consistency of a set of decision rules. It is shown that the choice of transport mode is a highly complex decision. The results of the analyses indicate that this methodology can be applied successfully to better understand tourist choice behavior. Moreover, the statistical properties of the decision table generated are satisfactory, especially when probabilistic rules are used.

An Agent-Based Model of Residential Choice Dynamics in Nonstationary Housing Markets

This paper presents an agent-based model developed to simulate residential choice behaviour in a nonstationary housing market. The model is built around the assumption that agents have incomplete and imperfect knowledge, and thus have to base their decisions on beliefs. The aim is to illustrate how the agents deal with the uncertainty inherent in these beliefs, both at the level of a single agent, deciding among a set of successive actions, and at the level of a group of agents, negotiating over the price of a house.

A model of multi-purpose shopping trip behavior

Existing utility-based models of complex choice behavior do not adequately deal with the interdependencies of chained choices. In this paper, we introduce a model of multi-purpose shopping which is aimed at overcoming this shortcoming. In the proposed model, dependencies between choices within as well as between trips are covered by a recursive definition of trip utility. The standard log-likelihood estimation procedure is used to calibrate the model. Simulation experiments show that estimation results are satisfactorily accurate and robust. Comparison of the model to a conventional choice model using simulated data indicates that even low tendencies to make multi-purpose trips have a significant influence on predicted destination choice. Furthermore, it is shown that conventional models do not satisfactorily predict simulated multi-purpose behavior.