Modeling disaggregate behavioral modal switching models based on intention data

doi:10.1016/0191-2615(90)90029-X

Transportation Research Part B: Methodological

Volume 24, Issue 1, February 1990, Pages 15-25

https://doi.org/10.1016/0191-2615(90)90029-X Get rights and content

Abstract

The purpose of this paper is to develop a disaggregate behavioral model which directly predicts traveler's modal switching behavior due to a transport service change. Based on the random utility theory, several disaggregate modal switching models are formulated, which incorporate resistance to change in modal switching behavior. These models are estimated using stated preference data obtained from an originally designed questionnaire survey. An empirical examination shows that it is very important to incorporate state dependence effects into disaggregate modal choice models.

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Citation Excerpt :
It is theoretically possible and practically fruitful to study modal diversion with the same method normally used for mode choice models, i.e. the random utility approach within an econometric context where the attributes of the alternative modes are the independent variables. The commonest improvement of such models to study modal behaviours changes is the joint use of both revealed preferences and stated intentions data [9–14]. The above represents the framework of most analyses made by economists, planners and transport engineers.
We analyse past research efforts that focus on modal diversion in the transport sector, as opposed to the classical mode choice concept, showing the added value of this alternative framework that emerges from the existing scientific literature. The modal diversion paradigm is then used to assess the relative importance of the technical performances of transport services on one hand and of the subjective factors of its potential users on the other, when forecasting the use of a new means among a group of white-collars working in a French research institute. We quantitatively show that multimodal habits and cognitive attitudes have an importance that is in general not negligible for this group, compared to that of the transport services performances, even if only these latter are routinely considered by engineers and planners. Beyond this, we find that the role of self-related factors further increased when the group was less familiar with the technological background and the subsequent operation of the new system, such as in the case of demand responsive transport services.
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Transportation Research Part B: Methodological

Abstract

References (14)

Toward a dynamic discrete-choice model of household automobile fleet size and composition

Transpn. Res. B

Application of multinomial probit to a two-period panel data set

Transpn. Res. A

Discrete Choice Analysis—Theory and Application to Travel Demand

Some issues of dynamics in forecasting travel behavior—A discussion paper

Transportation

Multinomial probit with time series data—Unifying state dependence and serial correlation models

Environment and Planning A

Urban Travel Demand—A Behavioral Analysis

Habit and hysteresis in mode choice

Urban Studies

Cited by (15)

From mode choice to modal diversion: A new behavioural paradigm and an application to the study of the demand for innovative transport services

Desire to change one's multimodality and its relationship to the use of different transport means

Determinants Affecting Public Intention to Use Micro-Vertical Farming: A Survey Investigation

Should I stay or should I go? Investigating route switching behavior from revealed preferences data

Measuring Long-Run Price Elasticities in Urban Travel Demand

Estimating modal shift by introducing transit priority strategies under congested traffic using the multinomial logit model