Evaluating voluntary travel behaviour change: Suggested guidelines and case studies

Stopher, Peter; Clifford, Eoin; Swann, Natalie; Zhang, Yun

doi:10.1016/j.tranpol.2009.10.007

Cited by 56 publications

(35 citation statements)

References 11 publications

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“…In the illustration the test presented in this paper is, though small scaled, in line with other studies on the effects of MM-campaigns, e.g. [9,38]. The result indicates that there is a significant change in the stage of behavioural change regarding daily car use.…”

Section: Future Improvementssupporting

confidence: 85%

“…There are thus authors that take a thorough look into relevant issues in order to evaluate MM programs, [8,9]. Bonsall [8] concludes that although the published results show a degree of consistency, serious questions remain about the reliability of the methods used to produce these results, and about the possibility of systematic bias.…”

Section: Introduction 11 Backgroundmentioning

confidence: 99%

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Can Mobility Management Campaigning Contribute to Pro-Environmental Behaviour in General? Development of an Analytical Tool

Hiselius

2014

PROMET

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Section: Future Improvementssupporting

confidence: 85%

Section: Introduction 11 Backgroundmentioning

confidence: 99%

Can Mobility Management Campaigning Contribute to Pro-Environmental Behaviour in General? Development of an Analytical Tool

Hiselius

2014

PROMET

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“…Compared with those self-report surveys, mobile phones might be more accurate. Experiments of Stopher et al [6] show, e.g., that the average number of trips per person per day is significantly higher from GPS respondents than from dairy respondents. Yang et al [7] present how accelerometer and GPS features may be used to recognize physical activity, in particular to classify a stationary, walking, running, cycling or in-vehicle mode.…”

Section: Using Mobile Phones To Measure Urban Mobilitymentioning

confidence: 97%

User Behaviour Captured by Mobile Phones

Teeuw

Koolwaaij

Peddemors

2012

Communications in Computer and Information Science

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Abstract. The i-Zone initiative proposes a new approach to urban mobility management by using the latest mobile ICT technologies. It is about mobile phones that measure and analyse user behaviour in order to influence travel behaviour. By providing feedback to the traveller (self monitoring), by information sharing, or by providing positive incentives to travellers by road authorities and other stakeholders, improved mobility in a city may be achieved. The information is targeted on individual travel behaviour, and thus allows a personalized approach to influence travel behaviour. This enables a shift from a focus on intelligent transport systems, with the emphasis on infrastructure and car-to-car systems, to a more human-centric approach based on ambient intelligence.

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“…Between 2012 and 2014, as part of evaluating this program, daily travel data were collected using GPS in suburbs of inner northern Adelaide, by the Institute of Transport and Logistics Studies (ITLS) of the University of Sydney (Stopher et al 2009(Stopher et al , 2013. Individuals in the households aged over 14, carried a portable GPS device everywhere for a period of 15 days during March-May for each year from 2012 to 2014, providing a total of three waves of panel data.…”

Section: Data Collectionmentioning

confidence: 99%

Social marketing and the built environment: What matters for travel behaviour change?

Mulley

Liu

2016

Transportation

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Social marketing and the built environment are two important 'tools' to manage travel demand which have had significant attention in the literature separately. Most previous studies evaluating the effects of social marketing programs have relied on preand post-surveys, using self-reported measures without any objective measures of travel behaviour change. Further, there is a lack of evidence on whether the effects of the built environment are synergistic when combined with other intervention programs, such as social marketing programs. This study contributes by quantitatively evaluating the relative and combined effects of the TravelSmart and the built environment on travel behaviour using objective GPS measurements. Between 2012 and 2014, daily travel data were collected using GPS equipment in suburbs of inner northern Adelaide, South Australia. Individuals in the households aged over 14 carried a portable GPS device everywhere for a period of 15 days during March-May in each year from 2012 to 2014, providing a total of three waves of panel data. The empirical analysis suggests that the TravelSmart program as a 'treatment' significantly reduced the car trips soon after implementation with longer term effects on reducing car trips in high-walkable neighbourhoods. For walking and bus trips, the TravelSmart program increased these 1 year after the 'treatment' with stronger effects on travel behaviour change for the participants living in high-walkable neighbourhoods than for those living in low-walkable neighbourhoods.

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Evaluating voluntary travel behaviour change: Suggested guidelines and case studies

Cited by 56 publications

References 11 publications

Can Mobility Management Campaigning Contribute to Pro-Environmental Behaviour in General? Development of an Analytical Tool

Can Mobility Management Campaigning Contribute to Pro-Environmental Behaviour in General? Development of an Analytical Tool

User Behaviour Captured by Mobile Phones

Social marketing and the built environment: What matters for travel behaviour change?

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