The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis

  • Chuan Ding Harbin Institute of Technology
  • Chao Liu University of Maryland
  • Yaoyu Lin Harbin Institute of Technology
  • Yaowu Wang Harbin Institute of Technology
Keywords: latent variable, mediating variable, discrete choice model, structural equation model, travel mode choice, car ownership, green commuting,

Abstract

Reducing car trips and promoting green commuting modes are generally considered important solutions to reduce the increase of energy consumption and transportation CO2 emissions. One potential solution for alleviating transportation CO2 emissions has been to identify a role for the employer through green commuter programs. This paper offers an approach to assess the effects of employer attitudes towards green commuting plans on commuter mode choice and the intermediary role car ownership plays in the mode choice decision process. A mixed method which extends the traditional discrete choice model by incorporating latent variables and mediating variables with a structure equation model was used to better understand the commuter mode choice behaviour. The empirical data were selected from Washington-Baltimore Regional Household Travel Survey in 2007-2008, including all the trips from home to workplace during the morning hours. The model parameters were estimated using the simultaneous estimation approach and the integrated model turns out to be superior to the traditional multinomial logit (MNL) model accounting for the impact of employer attitudes towards green commuting. The direct and indirect effects of socio-demographic attributes and employer attitudes towards green commuting were estimated. Through the structural equation modelling with mediating variable, this approach confirmed the intermediary nature of car ownership in the choice process. The results found in this paper provide helpful information for transportation and planning policymakers to test the transportation and planning policies effects and encourage green commuting reducing transportation CO2 emissions.

Author Biographies

Chuan Ding, Harbin Institute of Technology
Shenzhen Key Laboratory of Urban Planning and Decision Making Simulation, Shenzhen Graduate School
Chao Liu, University of Maryland
National Center for Smart Growth Research
Yaoyu Lin, Harbin Institute of Technology
Shenzhen Key Laboratory of Urban Planning and Decision Making Simulation, Shenzhen Graduate School
Yaowu Wang, Harbin Institute of Technology
Shenzhen Key Laboratory of Urban Planning and Decision Making Simulation, Shenzhen Graduate School

References

Horner MW. Spatial dimensions of urban commuting: a review of major issues and their implications for future geographic research. The Professional Geographer. 2004;56(2):160-173.

Rye T. Employer attitudes to employer transport plans: a comparison of UK and Dutch experience. Transport Policy. 1999;6(3):183-196.

Coleman C. Green commuter plans and the small employer: an investigation into the attitudes and policy of the small employer towards staff travel and green commuter plans. Transport Policy. 2000;7(2):139-148.

Bolduc D, Boucher N, Daziano RA. Hybrid choice modeling of new technologies for car choice in Canada. Journal of the Transportation Research Board. 2008;(2082):63-71.

Johansson MV, Heldt T, Johansson P. The effects of attitudes and personality traits on mode choice. Transportation Research Part A. 2006;40(6):507-525.

Kim JH, Bae YK, Chung JH. Effects of personal proenvironmental attitudes on mode choice behavior: new ecofriendly water transit system in Seoul, South Korea. Journal of the Transportation Research Board. 2012;(2274):175-183.

Ben-Akiva M, McFadden D, Garling T, Gopinath D, Walker J, Bolduc D, et al. Extended framework for modeling choice behavior. Marketing Letters. 1999;10(3):187-203.

Walker J, Ben-Akiva M. Generalized random utility model. Mathematical Social Sciences. 2002;43(3):303-343.

Choo S, Mokhtarian PL. What type of vehicle do people drive? The role of attitude and lifestyle in influencing vehicle type choice. Transportation Research Part A. 2004;38(3):201-222.

Sohn K, Yun J. Separation of car-dependent commuters from normal-choice riders in mode-choice analysis. Transportation. 2009;36(4):423-436.

Walker JL, Li J. Latent lifestyle preferences and household location decisions. Journal of Geographical Systems. 2007;9(1):77-101.

Schwanen T, Mokhtarian PL. What affects commute mode choice: neighborhood physical structure or preferences towards neighborhoods?. Journal of Transport Geography. 2005;13(1):83-99.

Gardner B, Abraham C. Going green? Modeling the impact of environmental concerns and perceptions of transportation alternatives on decisions to drive. Journal of Applied Social Psychology. 2010;40(4):831-849.

Cao X, Mokhtarian PL, Handy SL. Cross-sectional and quasi-panel explorations of the connection between the built environment and auto ownership. Environment and Planning. 2007;39(4):830-847.

Ben-Akiva M, Atherton TJ. Methodology for short-range travel demand predictions: analysis of carpooling incentives. Journal of Transport Economics and Policy. 1997;11(3):224-261.

Van Acker V., Witlox F. Car ownership as a mediating variable in car travel behavior research using a structure equation modelling approach to identify its dual relationship. Journal of Transport Geography. 2010;18(1):65-74.

Cao X, Mokhtarian PL, Handy SL. Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach. Transportation. 2007;34(5):535-556.

Scheiner J, Holz-Rau C. Travel mode choice: affected by objective or subjective determinants?. Transportation. 2007;34(4):487-511.

Yanez MF, Raveau S, Ortuzar JD. Inclusion of latent variables in Mixed Logit model: modelling and forecasting, Transportation Research Part A. 2010;44(9):744-753.

Raveau S, Alvarez-Daziane R, Yanez MF, Bolduc D, Ortuzar JD. Sequential and simultaneous estimation of hybrid discrete choice models: some new findings. Journal of the Transportation Research Board. 2010;(2156):131-139.

Ben-Akiva M, Walker J, Bernardino AT, Gopinath DA, Morikawa T, Polydoropoulou A. Integration of choice and latent variable models, in (H. Mashmassani Ed.) In Perpetual Motion: Travel behavior research opportunities and application challenges. Elsevier Science; 2002. p. 431-470.

Sherman R. Subsidies to relieve urban traffic congestion. Journal of Transport Economics and Policy. 1972;6(1):22-31.

Cullinane S. The relationship between car ownership and public transport provision: a case study of Hong Kong. Transport Policy. 2002;9(1): 29-39.

Paulley N, Balcombe R, Mackett R, Titheridge H, Preston J, Wardman M, et al. The demand for public transport: the effect of fares, quality of service, income and car ownership. Transport Policy. 2006;13(4):295-306.

Kline RB. Principles and practice of structural equation modeling. 2nd ed. New York: Guilford Press; 2005. p. 112.

Gao S, Mokhtarian PL, Johnston RA. Exploring the connections among job accessibility, employment, income, and auto ownership using structural equation modeling. Annals of Regional Science. 2008;42(2):341-356.

Aditjandra PT, Cao X, Mulley C. Understanding neighbourhood design impact on travel behaviour: an application of structural equations model to a British metropolitan data. Transportation Research Part A. 2012;46(1):22-32.

Boarnet MG. A broader context for land use and travel behavior, and a research agenda. Journal of the American Planning Association. 2011;77(3):197-213.

Gim THT. The relationships between land use measures and travel behavior: a meta-analytic approach. Transportation Planning and Technology. 2013;36(5):413-434.

Published
2014-04-26
How to Cite
1.
Ding C, Liu C, Lin Y, Wang Y. The Impact of Employer Attitude to Green Commuting Plans on Reducing Car Driving: A Mixed Method Analysis. Promet - Traffic&Transportation. 2014;26(2):109-1. DOI: 10.7307/ptt.v26i2.1332
Section
Articles