Hjp Harry Timmermans

Stated preference and choice models applied to recreation research: A review

Abstract This article discusses the use and usefulness of stated preference and choice models in recreation/leisure research. Stated preference and choice models require one to design decision experiments to study recreational and leisure decisions made in hypothetical or simulated markets. Historically, such experiments were uncommon in recreation and leisure research; therefore we pay particular attention to comparisons of the stated preference modeling approaches with modeling approaches based on observations of choices made in real markets, such as the analysis of discrete choices using conditional and nested multinomial logit models. The conceptual and theoretical bases of stated preference and choice models are discussed; and procedures for developing such models, including different design strategies, are outlined. Potential uses of these models in recreation research are illustrated with reference to several recent empirical applications.

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.

Social Networks, Social Interactions, and Activity-Travel Behavior: A Framework for Microsimulation

We argue that the social networks and activity-travel patterns of people interact and coevolve over time. Through social interaction, people exchange information about activity-travel choice alternatives and adapt their latent and overt preferences for alternatives to each other. At the same time, social networks are not static: new social links emerge and existing social links may dissolve in time, depending on activity-travel schedules and the attributes of persons. In this paper we propose a theoretical framework to incorporate these dynamics in microsimulations of activity-travel patterns. A core assumption of the proposed theory is that the utility that a person derives from social interaction is a function of dynamic social and information needs, on the one hand, and of similarity between the relevant characteristics of the persons involved, on the other. Furthermore, persons tend to adapt their preferences so as to increase the utility they derive from their social networks. We derive the theory and models from basic principles and discuss results of a first round of simulations conducted to examine the behavior of the model. We argue that the model is consistent with existing theories and findings in social network analysis.

A Multipurpose Shopping Trip Model to Assess Retail Agglomeration Effects

Multipurpose shopping is a prominent and relevant feature of shopping behavior. However, no methodology is available to assess empirically how the demand for multipurpose shopping depends on retail agglomeration or, in general, the characteristics of retail supply, such as the numbers and types of stores in a shopping center or the number of categories in a supermarket. The authors propose a nested-logit model that captures retail agglomeration effects on consumer choice of shopping trip purpose (what to buy) and destination (where to buy). The authors estimate parameters representing trip purpose-adjustment and between-store attraction effects on shopping trip data collected from a sample of 1704 households in The Netherlands. Both effects are significant for each of the three categories for which the model is estimated. This is consistent with the idea of agglomeration effects. The findings suggest that agglomeration helps attract not only multipurpose but also single-purpose trips. A comparison of multi- and single-purpose trip model predictions shows that single-purpose models underpredict the number of trips to larger shopping centers.

Activity pattern similarity : a multidimensional sequence alignment method

The classification of activity patterns is an important research topic in activity analysis. First, it constitutes the basis for analyzing activity patterns, for instance by correlating the derived classification with spatial and/or socio-economic variables. Secondly, the underlying mechanisms can be used to assess the degree of correspondence between observed activity patterns and activity patterns predicted by some activity-based model of transport demand. Traditionally, conventional Euclidean distance measures have been used for the comparison of activity patterns. Consequently, the sequence information embedded in activity patterns has not been explicitly considered when comparing activity patterns. More recently, sequence alignment methods have been proposed. Although these methods have some advantages, they are uni-dimensional and hence cannot incorporate the interdependencies between attributes. This paper therefore proposes a multidimensional sequence alignment method to measure differences in both sequential and interdependency information embedded in activity patterns.

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.

Store-Switching Behavior

This study describes temporal aspects of consumer shopping behavior.Most cross-sectional studies either explicitly or implicitly assumethat consumer choice behavior is constant over time. The results ofthis study, which is based on scanner panel data for twenty-one grocerystores for three years in Missouri, indicates that consumers areinvolved in substantial store-switching and variety-seeking behavior,the degree of which is related to a set of sociodemographic variables.

Consumer choice of shopping centre : an information integration approach

Timmermans H. (1982) Consumer choice of shopping centre: an information integration approach, Reg. Studies 16, 171–82. This paper is concerned with the relationships between the physical attributes of the retailing system, consumer decision-making and overt behaviour. The appropriateness of an approach, which is based on information integration theory and functional measurement, as a means of predicting consumer response to changes in physical attributes of shopping centres, is considered, both from an empirical and methodological point of view. The results of the empirical study tend to provide general support for the approach. Several methodological issues are raised which deserve further investigation in order to refine the approach.

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.