Chinh Ho

Intra-household interactions in transport research: a review

Abstract Recognition that individuals do not make their travel decisions in isolation of the household context has produced a growing interest in intra-household interactions and group decision-making. The behavioural realism of travel demand models that explicitly accommodate intra-household interactions is expected to provide more insight into travel behaviour and a more credible analysis of travellers’ response to transport policy than models that deal with household interactions in a ‘black box’. This paper reviews the literature on group decisions and intra-household interactions. How intra-household interactions influence the way in which decisions are made is expounded and empirical findings are drawn upon to argue for why the study of intra-household interactions is important. Various analytical techniques and data requirements are discussed to show how intra-household interactions can be handled. Drawing on this review, the impact of intra-household interactions on travel behaviour and implications for transport policy are identified and directions for further study suggested.

Incorporating Intrahousehold Interactions into a Tour-Based Model of Public Transport Use in Car-Negotiating Households

Intrahousehold interactions in travel are fundamental to an understanding of activity travel behavior, as reflected by the substantial percentage of regional travel that is made jointly. The development of travel demand models that incorporate intrahousehold interactions is crucial to a credible analysis of traveler response to policies. A tour-based modeling framework is used to examine intrahousehold interactions in travel mode choice with a focus on public transport use in households having differences in car availability. An important distinction is made between car-sufficient households (in which there are at least as many cars in the household as license holders) and car-negotiating households (households that have fewer cars than license holders). Intrahousehold interactions and temporal–spatial constraints are explicitly represented by different patterns of joint household tours, with home-based tours as the unit of analysis. The empirical analysis is based on a nested logit model that was developed to integrate intrahousehold interactions with tour-based mode choices; Sydney Household Travel Survey data are used. The results show that joint household travel accounts for more than half of weekday home-based tours in Sydney, Australia. The arrangement of joint household tours is shown to depend on household context, situational factors, and social constraints. Mode choice associated with different joint tour patterns is influenced by household and individual characteristics, tour attributes, and transport-related fringe benefits.

Random Regret Minimization and Random Utility Maximization in the Presence of Preference Heterogeneity: An Empirical Contrast

Random regret minimization (RRM) interpretations of discrete choices are growing in popularity as a complementary modeling paradigm to random utility maximization (RUM). While behaviorally very appealing in the sense of accommodating the regret of not choosing the best alternative, studies to date suggest that the differences in willingness to pay estimates, choice elasticities, and choice probabilities compared to RUM are small. However, the evidence is largely based on a simple multinomial logit (MNL) form of the RRM model. This paper revisits this behavioral contrast and moves beyond the multinomial logit model to incorporate random parameters, revealing the presence of preference heterogeneity. The important contribution of this paper is to see if the extension of RRM-MNL to RRM-mixed logit in passenger mode choice widens the behavioral differences between RUM and RRM. The current paper has identified a statistically richer improvement in fit of mixed logit compared to multinomial logit under RRM (and RUM) but found small differences overall between the empirical outputs of RUM and RRM, with no basis of an improved model fit between these two nonnested model forms. The inclusion of both model forms should continue to inform the likely range of behavioral outputs during investigation of a broader range of process heuristics designed to capture real world behavioral response.

Understanding the Determinants of Walking as the Basis for Social Marketing Public Health Messaging

Abstract The chapter was prompted by the trend towards providing public health messaging through social marketing. The purpose is to understand the determinants of walking within a city in terms of framing policy to promote greater physical activity (PA). This is demonstrated through the context of Sydney, New South Wales (NSW), Australia. The chapter provides a literature review and showcases a case-study. Descriptive statistics are presented on how far Sydneysiders walk using Household Travel Survey data and how this might be changed if short motorised trips are converted to walking. Modelling walking time follows to see if there are policy levers that could be used to increase walking time. Over 78% of Sydney’s population do not meet the recommended PA target of 30 minutes per day. Converting short motorised to walking provides marginal improvement. Walking to access activities contributes more to total walking time than walking to/from public transport. Modelling suggests potential policy levers to increase PA. Targeting driving licence holders, households without cars and promoting walkable environments are found most effective. Promoting undertaking more activities on foot is likely to be more successful than promoting walking for short trips. The chapter provides an overview of PA around the world and an empirical case study of walking in Sydney, NSW, Australia. In turn this provides an evidence base for more successful targeting of social marketing messaging for public health.

Greening demand chains in urban passenger transport: emissions saving from complex trip chains

It is well known that a significant amount to passenger trip activity involves multiple modes, destinations and trip purposes. For example, with multi-worker households, we observe a car commuter taking a child to a child care centre en route to work and also dropping their partner off at another location such as a railway station. This example is one of many trip chain configurations that represent the complexity of travel activity, and which have important implications on how we represent travel demand in transport planning models. What is not well understood is the impact that trip chaining has on greening the demand chain. We are unaware of any studies that have investigated the greening of passenger demand chains associated with the complexity of trip chains. This chapter uses the Sydney Household Travel Survey and an econometric model to identify the impact that the changing nature of trip chains has on CO2 emission. Results suggest that trip chains were stable in Sydney over a period of 15-year from 1997/98 to 2011/12. Emissions saving from chaining multiple activities into a single chain were found to vary between 5 and 19 % depending on whether the mode of travel is car, bus, or train.

A Parking Space Levy: A Case Study of Sydney, Australia

Abstract Purpose This chapter provides a case study of the implementation of the Parking Space Levy (PSL) in Sydney, Australia. Introduced by the Parking Space Levy Act 1992, the scheme places a levy on business use of off-street car parking spaces with the revenues from the levy being hypothecated to public transport improvements. The chapter outlines the implementation of what is now a relatively mature scheme and examines how the revenues raised by the scheme have been spent. Methodology/approach This chapter offers a review of the introduction of the levy in Sydney and explores its impact in implementation with respect to changes to the number of parking spaces and an analysis of the way in which the hypothecated revenue has been spent. The implementation of the PSL is evaluated against the literature on hypothecation of funds and includes a discussion of policy issues for Sydney in the light of the evidence presented. Findings Whilst off-street parking availability is a major contributor to peak period traffic, the implementation of the PSL as a single rate of application has not led to a decrease in total number of available parking places in the City of Sydney. The number of concessions for unused spaces, whereby the levy was not imposed, increased when the levy rate was doubled in 2009 although this was accompanied by a fall in the number of exemptions from the levy. The revenue from the PSL has been dedicated to improvements in public transport infrastructure, primarily interchanges and commuter car parks although the more recent provisions to spend on ‘soft’ measures to improve sustainable travel have not been taken up. Practical implications Whilst a stated objective of the PSL was to reduce congestion, the chapter concludes that the PSL had more than this single objective which makes it more difficult to assess whether its implementation has been a success. Originality/value of chapter This chapter provides an overview of the introduction, implementation and outcomes of the PSL in Sydney, relating it to the PSL in Melbourne (Chapter 13) and the WPL in Nottingham (Chapter 15). No other study to date evaluated the PSL in Sydney against the literature relating to hypothecation nor tracked the impacts of implementation of the PSL to evaluate its success.