Skip to main content

Advertisement

SpringerLink
Log in

How the longer term success of a social marketing program is influenced by socio-demographics and the built environment

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

Urban sprawl is pervasive in Australian cities arising from the low density development of dwellings with the consequence that private vehicle use dominates daily travel in Australia. This paper examines a community based social marketing program, TravelSmart, which targeted reducing vehicle kilometres travelled as part of a transport demand management strategy. This paper uses 3-year panel data collected by GPS tracking and a conventional survey methodology in northern Adelaide, South Australia, to examine whether TravelSmart had a sustained impact and whether this was impacted by socio-economic and built-environment factors. A latent growth model is employed and demonstrates TravelSmart led to a declining trend in private car driving over the 3 years at both individual and household levels with effects being sustained beyond 1 year and up to 2 years. There is some evidence of compensatory behaviour between household members. Socio-demographic factors are significant with males decreasing their driving times faster than females. Built environment impacts were also significant with different levels of walkability showing different trajectories in the reduction of car trips after the implementation of TravelSmart, suggesting social marketing interventions work better when supported by hard policies such as a supportive built environment.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

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

    Article  Google Scholar 

  • Bamberg, S.: Changing environmentally harmful behaviors: a stage model of self-regulated behavioral change. J. Environ. Psychol. 34, 151–159 (2013)

    Article  Google Scholar 

  • Bamberg, S., Hunecke, M., Blobaum, A.: Social context, personal norms and the use of public transportation: two field studies. J. Environ. Psychol. 27, 190 (2007)

    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 

  • Bassett Jr., D.R., Pucher, J., Buehler, R., Thompson, D.L., Crouter, S.E.: Walking, cycling, and obesity rates in Europe, North America, and Australia. J. Phys. Act. Health 5, 795–814 (2008)

    Article  Google Scholar 

  • Ben-Elia, E., Avineri, E.: Response to travel information: a behavioural review. Transp. Rev. 35, 352–377 (2015)

    Article  Google Scholar 

  • BITRE: Urban public transport: updated trends, Information Sheet 59, BITRE, Canberra (2014). https://bitre.gov.au/publications/2014/files/is_059.pdf. Accessed 8 Sept 2017

  • 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 

  • 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 

  • Chan, D.: Data analysis and modeling longitudinal processes. Group Organ. Manage. 28, 341–365 (2003)

    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 

  • Curran, P.J., Obeidat, K., Losardo, D.: Twelve frequently asked questions about growth curve modeling. J. Cognit. Dev. 11, 121–136 (2010)

    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)

  • Ding, D., Gebel, K., Phongsavan, P., Bauman, A.E., Merom, D.: Driving: a road to unhealthy lifestyles and poor health outcomes. PLoS ONE 9, e94602 (2014)

    Article  Google Scholar 

  • Duncan, T.E., Duncan, S.C.: An introduction to latent growth curve modeling. Behav. Ther. 35, 333–363 (2004)

    Article  Google Scholar 

  • 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 

  • Friman, M., Larhult, L., Gärling, T.: An analysis of soft transport policy measures implemented in Sweden to reduce private car use. Transportation 40, 109–129 (2013)

    Article  Google Scholar 

  • Government of South Australia: TravelSmart Households in the West. Department of Transport, Energy and Infrastructure, Adelaide (2009). http://dpti.sa.gov.au/__data/assets/pdf_file/0019/134290/TravelSMART_Households_in_the_West.pdf. Accessed 8 Sept 2017

  • Hox, J.J., Moerbeek, M., van de Schoot, R.: Multilevel Analysis: Techniques and Applications. Routledge, Abingdon (2010)

    Google Scholar 

  • Hu, L.-T., Bentler, P.M.: Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. 6, 1–55 (1999)

    Article  Google Scholar 

  • James, B., Brög, W., Erl, E., Funke, S.: Behaviour change sustainability from individualised marketing. In: Australasian Transport Research Forum (ATRF), 23RD, 1999, Perth, Western Australia, vol. 23, part 2 (1999)

  • Laird, N.M., Ware, J.H.: Random-effects models for longitudinal data. Biometrics 38(4), 963–974 (1982)

    Article  Google Scholar 

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

    Article  Google Scholar 

  • McArdle, J.J., Nesselroade, J.R.: Growth curve analysis in contemporary psychological research. In: Handbook of Psychology, vol. 3 (Chap 18), pp. 447–480 (2003)

  • McFadden, D.: The choice theory approach to market research. Marke. Sci. 5, 275–297 (1986)

    Article  Google Scholar 

  • McKenzie-Mohr, D.: New ways to promote proenvironmental behavior: promoting sustainable behavior: an introduction to community-based social marketing. J. Soc. Issues 56, 543–554 (2000)

    Article  Google Scholar 

  • Möser, G., Bamberg, S.: The effectiveness of soft transport policy measures: a critical assessment and meta-analysis of empirical evidence. J. Environ. Psychol. 28, 10–26 (2008)

    Article  Google Scholar 

  • Muthén, B.O., Curran, P.J.: General longitudinal modeling of individual differences in experimental designs: a latent variable framework for analysis and power estimation. Psychol. Methods 2, 371 (1997)

    Article  Google Scholar 

  • Muthén, L.K., Muthén, B.O.: Mplus User’s Guide: Statistical Analysis with Latent Variables. Muthén & Muthén, Los Angeles, CA (2010)

    Google Scholar 

  • Prochaska, J.O., Velicer, W.F.: The transtheoretical model of health behavior change. Am. J. Health Promot. 12, 38–48 (1997)

    Article  Google Scholar 

  • 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. Part 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. Part A Policy Pract. 41, 351–364 (2007)

    Article  Google Scholar 

  • Rosenbloom, S.: Understanding women’s and men’s travel patterns: the research challenge. In: 3rd International Women’s Issues in Transportation, Chicago, USA, pp. 7–21 (2004)

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

    Article  Google Scholar 

  • Simon, H.A.: Models of Man; Social and Rational. Wiley, New York (1957)

    Google Scholar 

  • Stern, P.C.: New environmental theories: toward a coherent theory of environmentally significant behavior. J. Soc. Issues 56, 407–424 (2000)

    Article  Google Scholar 

  • Stern, P.C., Dietz, T., Abel, T.D., Guagnano, G.A., Kalof, L.: A value-belief-norm theory of support for social movements: the case of environmentalism. Hum. Ecol. Rev. 6, 81–97 (1999)

    Google Scholar 

  • Stopher, P.R., Moutou, C.J., Liu, W.: Sustainability of voluntary travel behaviour change initiatives—a 5-year study (2013). http://atrf.info/papers/2013/2013_stopher_moutou_liu.pdf. Accessed 8 Sept 2017

  • 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 

  • Taniguchi, A., Hara, F., Takano, S.E., Kagaya, S.I., Fujii, S.: Psychological and behavioral effects of travel feedback program for travel behavior modification. Transp. Res. Rec. 1839, 182–190 (2003)

  • Taylor, M.A.: Voluntary travel behavior change programs in Australia: the carrot rather than the stick in travel demand management. Int. J. Sustain. Transp. 1, 173–192 (2007)

    Article  Google Scholar 

  • Van Acker, V., Van Cauwenberge, B., Witlox, F.: MaxSumo: a new approach to the evaluation of mobility management projects. In: Rethinking Everyday Mobility: Results and Lessons Learned from the CIVITAS-ELAN Project. Založba FDV/The Publishing House of the Faculty of Social Sciences, pp. 131–151 (2012)

  • Zhang, Z.: Bayesian growth curve models with the generalized error distribution. J. Appl. Stat. 40, 1779–1795 (2013)

    Article  Google Scholar 

Download references

Acknowledgements

We are grateful to Professor Peter Stopher for providing the GPS data for this analysis and for talking to us about the background against it was collected. The analysis and interpretation and any errors are solely those of the authors. Material from this paper has been presented at the WCTR conference in Shanghai (July 2016) and at the Nanjing Workshop on “ICT, Activities, Time Use and Travel” (July 2016). This paper contributes to TfNSW program at the Institute of Transport and Logistics Studies associated with the Chair in Public Transport. Dr Liang Ma was a Research Associate at the Institute of Transport and Logistics Studies for the duration of this research.

Author information

Authors and Affiliations

  1. Institute of Transport and Logistics Studies, Business School, The University of Sydney, Sydney, Australia

    Corinne Mulley

  2. Centre for Urban Research, RMIT University, Melbourne, Australia

    Liang Ma

Authors
  1. Corinne Mulley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liang Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Corinne Mulley.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mulley, C., Ma, L. How the longer term success of a social marketing program is influenced by socio-demographics and the built environment. Transportation 45, 291–309 (2018). https://doi.org/10.1007/s11116-017-9817-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-017-9817-8

Keywords

Search

Navigation