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

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Abstract

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 pre- and 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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References

  • Ajzen, I.: The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50, 179–211 (1991)

    Article  Google Scholar 

  • Ampt, E., Rooney, A.: Reducing the impact of the car—a sustainable approach: TravelSmart Adelaide, Australia Transport Research Forum (ATRF) (1998)

  • Athey, S., Imbens, G.: Identification and Inference in Nonlinear Difference-in-Differences Models. National Bureau of Economic Research, Cambridge (2002)

    Book  Google Scholar 

  • Bagley, M.N., Mokhtarian, P.L.: The impact of residential neighborhood type on travel behavior: a structural equations modeling approach. Ann. Reg. Sci. 36, 279–297 (2002)

    Article  Google Scholar 

  • Bamberg, S., Fujii, S., Friman, M., Gärling, T.: Behaviour theory and soft transport policy measures. Transp. Policy 18, 228–235 (2011)

    Article  Google Scholar 

  • Bertrand, M., Duflo, E., Mullainathan, S.: How Much Should We Trust Differences-in-Differences Estimates?. National Bureau of Economic Research, Cambridge (2002)

    Book  Google Scholar 

  • Boarnet, M.G., Sarmiento, S.: Can land-use policy really affect travel behaviour? A study of the link between non-work travel and land-use characteristics. Sage Urban Studies Abstracts 26 (1998)

  • Brög, W.: Individualized marketing: implications for transportation demand management. Transp. Res. Rec. 1618, 116–121 (1998)

    Article  Google Scholar 

  • Brög, W., Erl, E., Ker, I., Ryle, J., Wall, R.: Evaluation of voluntary travel behaviour change: experiences from three continents. Transp. Policy 16, 281–292 (2009)

    Article  Google Scholar 

  • Cameron, A.C., Miller, D.L.: A practitioner’s guide to cluster-robust inference. J. Hum. Resour. 50, 317–372 (2015)

    Article  Google Scholar 

  • Cao, X.: Exploring causal effects of neighborhood type on walking behavior using stratification on the propensity score. Environ. Plan. A 42, 487–504 (2010)

    Article  Google Scholar 

  • Cao, X., Handy, S., Mokhtarian, P.: The influences of the built environment and residential self-selection on pedestrian behavior: evidence from Austin, TX. Transportation 33, 1–20 (2006)

    Article  Google Scholar 

  • Cao, X., Mokhtarian, P., Handy, S.: Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach. Transportation 34, 535–556 (2007)

    Article  Google Scholar 

  • Cao, X., Mokhtarian, P.L., Handy, S.L.: Examining the impacts of residential self-selection on travel behaviour: a focus on empirical findings. Transp. Rev. 29, 359–395 (2009)

    Article  Google Scholar 

  • Card, D., Krueger, A.B.: Minimum Wages and Employment: A Case Study of the Fast Food Industry in New Jersey and Pennsylvania. National Bureau of Economic Research, Cambridge (1993)

    Book  Google Scholar 

  • Carr, L.J., Dunsiger, S.I., Marcus, B.H.: Walk score™ as a global estimate of neighborhood walkability. Am. J. Prev. Med. 39, 460–463 (2010)

    Article  Google Scholar 

  • Cole, R., Dunn, P., Hunter, I., Owen, N., Sugiyama, T.: Walk Score and Australian adults’ home-based walking for transport. Health Place 35, 60–65 (2015)

    Article  Google Scholar 

  • Cooper, C.: Successfully changing individual travel behavior: applying community-based social marketing to travel choice. Transp. Res. Rec. 2021, 89–99 (2007)

    Article  Google Scholar 

  • Crane, R.: On form versus function: will the new urbanism reduce traffic, or increase it? J. Plan. Educ. Res. 15, 117–126 (1996)

    Article  Google Scholar 

  • Dill, J., Mohr, C.: Long term evaluation of individualized marketing programs for travel demand management. Oregon Transportation Research and Education Consortium (OTREC) (2010)

  • Duncan, D.T., Aldstadt, J., Whalen, J., Melly, S.J., Gortmaker, S.L.: Validation of Walk Score® for estimating neighborhood walkability: an analysis of four US metropolitan areas. Int. J. Environ Res. Public Health 8, 4160–4179 (2011)

    Article  Google Scholar 

  • Ewing, R., Cervero, R.: Travel and the built environment. J. Am. Plan. Assoc. 76, 265–294 (2010)

    Article  Google Scholar 

  • Frank, L., Engelke, P.: Multiple impacts of the built environment on public health: walkable places and the exposure to air pollution. Int. Reg. Sci. Rev. 28, 193–216 (2005)

    Article  Google Scholar 

  • Government of South Australia: TravelSmart households in the west. Department of Transport, Energy and Infrastructure. http://dpti.sa.gov.au/__data/assets/pdf_file/0019/134290/TravelSMART_Households_in_the_West.pdf (2009). Accessed 29 April 2016

  • Handy, S.: Critical assessment of the literature on the relationships among transportation, land use, and physical activity, does the built environment influence physical activity? Examining the evidence–TRB Special Report 282 (2005)

  • Handy, S., Boarnet, M.G., Ewing, R., Killingsworth, R.E.: How the built environment affects physical activity: views from urban planning. Am. J. Prev. Med. 23, 64–73 (2002)

    Article  Google Scholar 

  • Handy, S., Cao, X., Mokhtarian, P.: Correlation or causality between the built environment and travel behavior? Evidence from Northern California. Transp. Res. D Transp. Environ. 10, 427–444 (2005)

    Article  Google Scholar 

  • James, B.: Changing travel behaviour through individualised marketing: application and lessons from South Perth, Australia Transport Research Forum (ATRF) (1998)

  • Kitamura, R., Mokhtarian, P.L., Laidet, L.: A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area. Transportation 24, 125–158 (1997)

    Article  Google Scholar 

  • Krizek, K.J.: Residential relocation and changes in urban travel: does neighborhood-scale urban form matter? J. Am. Plan. Assoc. 69, 265–281 (2003)

    Article  Google Scholar 

  • Manaugh, K., El-Geneidy, A.: Validating walkability indices: how do different households respond to the walkability of their neighborhood? Transp. Res. D Transp. Environ. 16, 309–315 (2011)

    Article  Google Scholar 

  • Newman, P., Kenworthy, J.: Sustainable urban form: the big picture. Achiev. Sustain. Urban Form, 109–120 (2000)

  • Richter, J., Friman, M., Gärling, T.: Soft transport policy measures: gaps in knowledge. Int. J. Sustain. Transp. 5, 199–215 (2011)

    Article  Google Scholar 

  • Rose, G., Ampt, E.: Travel blending: an Australian travel awareness initiative. Transp. Res. D Transp. Environ. 6, 95–110 (2001)

    Article  Google Scholar 

  • Rose, G., Marfurt, H.: Travel behaviour change impacts of a major ride to work day event. Transp. Res. A Policy Pract. 41, 351–364 (2007)

    Article  Google Scholar 

  • Shen, L., Stopher, P.R.: Using SenseCam to pursue “ground truth” for global positioning system travel surveys. Transp. Res. C Emerg. Technol. 42, 76–81 (2014)

    Article  Google Scholar 

  • Stopher, P.R., Moutou, C.J., Liu, W.: Sustainability of voluntary travel behaviour change initiatives—a 5-year study. In: 36th Annual Australasian Transport Research Forum ATRF (2013)

  • Stopher, P., Clifford, E., Swann, N., Zhang, Y.: Evaluating voluntary travel behaviour change: suggested guidelines and case studies. Transp. Policy 16, 315–324 (2009)

    Article  Google Scholar 

  • Taylor, M.A., Ampt, E.S.: Travelling smarter down under: policies for voluntary travel behaviour change in Australia. Transp. Policy 10, 165–177 (2003)

    Article  Google Scholar 

Download references

Acknowledgments

We are grateful to Professor Peter Stopher for providing the GPS data for this analysis. We also thank Dr Breno Sampaio for his consultation on econometric models. The analysis and interpretation and any errors are solely those of the authors.

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Correspondence to Corinne Mulley.

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Ma, L., Mulley, C. & Liu, W. Social marketing and the built environment: What matters for travel behaviour change?. Transportation 44, 1147–1167 (2017). https://doi.org/10.1007/s11116-016-9698-2

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