The impact of telecommuting on personal vehicle usage and environmental sustainability

  • P. Zhu
  • S. G. Mason
Original Paper


To understand whether telecommuting could be part of the policy solutions for greenhouse gas (GHG) reduction in the transportation sector, this study uses instrumental variable Tobit models and data from 2001 and 2009 National Household Travel Surveys to explore whether telecommuting reduces or increases the daily work and non-work vehicle miles traveled (VMT). Our findings suggest telecommuters have more VMT for both daily work and non-work trips than non-telecommuters. Adding the findings that telecommuting has no impact on other non-working household member’s daily total (non-work) trips, we can possibly argue that households with telecommuter(s) tend to have higher daily total VMT. Our estimated marginal effect of telecommuting on worker’s daily total trips indicates that a telecommuter on average travels 38 vehicle miles more on a daily basis in 2001 and 45 vehicle miles more in 2009 compared with a non-telecommuter. These increases in VMT translate into a rather large increase in GHG emissions in the US equivalent to adding 7,248,845 cars in 2001 and 8,808,165 in 2009 to the road. Moreover, the difference of this marginal effect between 2001 and 2009 suggests the impact of telecommuting on worker’s daily total VMT had increased over time. With the emerging work arrangements to work from home, telecommuting has been welcomed in this changing environment, not only by individual workers and employers but also policymakers. But the outcomes seem to be opposite to what policy makers may have expected for GHG emission reductions.


Greenhouse gas Sustainability Telecommuting Vehicle miles traveled 



We want to thank the editor and reviewers for their comments.

Supplementary material

13762_2014_556_MOESM1_ESM.docx (107 kb)
Supplementary material 1 (DOCX 106 kb)


  1. Alam JB, Wadud Z, Polak JW (2013) Energy demand and economic consequences of transport policy. Int J Environ Sci Technol 10:1075–1082CrossRefGoogle Scholar
  2. Balker T (2005) The quiet success: telecommuting’s impact on transportation and beyond. Reason foundation. California, Los Angeles. Retrieved 9 Jun 2013
  3. Bound J, Jaeger DA, Baker RM (1995) Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. J Am Stat Assoc 90(430):443–450Google Scholar
  4. Buliung RN (2007) Broadband technology and metropolitan sustainability: an interpretive review. Report available from the University of Toronto focus on research. Retrieved 9 Jun 2013
  5. Coroama VC, Hilty LM, Birtel M (2012) Effects of internet-based multiple-site conferences on greenhouse gas emissions. Telemat Inform 29(4):362–374CrossRefGoogle Scholar
  6. Cox W (2009) Improving quality of life through telecommuting. The informational Technology and Innovation Foundation, Washington DCGoogle Scholar
  7. Cuenot F, Fulton K, Staub J (2012) The prospect for modal shifts in passenger transport worldwide and impacts on energy use and CO2. Energy Policy 41:98–106Google Scholar
  8. EPA (2011a) Inventory of U.S. greenhouse gas emissions and sinks: 1990–2009 (April 2011). USEPA #430-R-11-005. Retrieved 23 Nov 2011
  9. EPA (2011b) Office of transportation and air quality. EPA-420-F-11-04, December 2011. Questions and answers: greenhouse gas emissions from a typical passenger vehicle. Retrieved 8 Jun 2013
  10. EPA (2013) Light-duty automotive technology, carbon dioxide emissions, and fuel economy trends: 1975 through 2012. Appendix A database details and calculation methods (March 2013). Retrieved 12 Feb 2014
  11. Fox M (1995) Transport planning and the human activity approach. J Transp Geogr 3(2):105–116Google Scholar
  12. Fragkias M, Lobo J, Strumsky D, Seto KC (2013) Does size matter? Scaling of CO2 emissions and U.S. urban areas. PLoS One 8(6):e64727. doi: 10.1371/journal.pone.0064727 CrossRefGoogle Scholar
  13. Fuhr JP, Pociask S (2011) Broadband and telecommuting: helping the U.S. environment and the economy. Low Carbon Econ 2:41–47CrossRefGoogle Scholar
  14. Greene WH (1997) Econometric analysis, 3rd edn. Prentice Hall, Upper Saddle River, NJGoogle Scholar
  15. Hall AR, Rudebusch GD, Wilcox DW (1996) Judging instrument relevance in instrumental variables estimation. International Economic Review 37(2):283–298Google Scholar
  16. Holden E, Linnerud K (2011) Troublesome leisure travel: the contradictions of three sustainable transport policies. Urban Stud 48(14):3087–3106CrossRefGoogle Scholar
  17. Horvath A (2010) Environmental analyses of telework: what we know, and what we do not know and why? In: Paper presented at the 2010 IEEE international symposium on sustainable systems and technology 17–19 May 2010; Arlington, VAGoogle Scholar
  18. IEA (2008) Energy and technology perspectives 2008: scenarios and strategies in 2050. International energy agency, Organization for Economic Co-operation and the Development (OECD); Paris, FranceGoogle Scholar
  19. Jones CM, Kammen DM (2011) Quantifying carbon footprint reduction opportunities for U.S. households and communities. Environ Sci Technol 45:4088–4095Google Scholar
  20. Kate L, Harnish T (2011) The state of telework in the U.S.; how individuals business and government benefit. Telework Research Network, San DiegoGoogle Scholar
  21. Khan A (2010) Telecommuting as a strategy for reducing energy consumption and greenhouse gas emissions in multi-nucleated urban regions. In: 12th WCTR 11–15 July; Lisbon, PortugalGoogle Scholar
  22. Kitou E, Horvath A (2003a) Energy related emission from telework. Environ Sci Technol 37(16):3467–3475CrossRefGoogle Scholar
  23. Kitou E, Horvath A (2003b) Transportation choices and air pollution effects of telework. J Infrastruct Syst 12(2):121–134CrossRefGoogle Scholar
  24. Kitou E, Horvath A (2008) External air pollution costs of telework. Int J Life Cycle Manag 13(2):155–165CrossRefGoogle Scholar
  25. Liao CH, Chang CL, Su CY, Chiueh PT (2013) Correlation between land-use change and greenhouse gas emissions in urban areas. Int J Environ Sci Technol 10:1275–1286CrossRefGoogle Scholar
  26. Markus M, Andrey J, Johnson LC (2006) The sustainability of telework: an ecological-footprinting approach. Sustain Sci Pract Policy 2(1):3–14Google Scholar
  27. Marletta P, Pasquini A, Stacey G, Vicario L (2004) The environmental impact of ISTs, E-living project reportGoogle Scholar
  28. Matthews HS, Williams E (2005) Telework adoption and energy use in building and transport sectors in the United States and Japan. J Infrastruct Syst 11(1):21–30CrossRefGoogle Scholar
  29. McCollum D, Yang C (2009) Achieving deep reductions in US transport greenhouse gas emissions: scenario analysis and policy implications. Energy Policy 37:5580–5596CrossRefGoogle Scholar
  30. Nelson P (2004) Emissions trading with telecommuting credits: regulatory background an institutional barriers. Resources for the future, WashingtonGoogle Scholar
  31. Nelson D, Niles J (2000) Observations on the causes of nonwork travel growth. In: Transportation research board paper. No. 00-1242, 79th annual meeting, Jan 9–13, Washington, DCGoogle Scholar
  32. New York Times (2011) Carmakers back strict new rules for gas mileage. By Bill Vlasic Published: 28 July 2011. Retrieved 23 Nov 2011
  33. Roth KW, Rhodes T, Ponnum R (2008) The energy and greenhouse gas emission impacts of telecommuting in the U.S. proceedings from the 2008 IEEE international symposium on electronics and the environment, pp 1–6Google Scholar
  34. Santos G, Behrendt H, Teytelboym A (2010) Part II: Policy instruments for sustainable road transport. Res Transp Econ 28:46–91Google Scholar
  35. Shafizadeh KR, Niemeier DA, Mokhtarian PL, Salomon I (2007) Cost and benefits of home-based telecommuting: a Monte Carlo simulation model incorporating telecommuter, employer, and public sector perspectives. J Infrastruct Syst 13(1):12–25CrossRefGoogle Scholar
  36. Shea J (1997) Instrument relevance in multivariate linear models: a simple measure. Rev Econ Stat 79:348–352Google Scholar
  37. Srinivasan S, Ferreira J (2002) Travel behavior at the household level: understanding linkages with residential choice. Transp Res Part D: Transp Environ 7(3):225–242Google Scholar
  38. Staiger D, Stock JH (1997) Instrumental variables regression with weak instruments. Econom 65(3):557–586Google Scholar
  39. Steve W, Bishins A, Kooshian C (2009) Cost-effective GHG reductions through smart growth and improved transportation choices: an economic case for investment of cap-and-trade revenues. Center for Clear Air Policy, WashingtonGoogle Scholar
  40. Strathman JG, Dueker KJ, Davis JS (1994) Effects of household structure and selected travel characteristics on trip chaining. Transp 21:23–45Google Scholar
  41. Tang W, Mokhtarian PL, Handy S (2011) The impact of the residential built environment on work at home adoption and frequency: an example from Northern California. J Transp Land Use 4(3):3–22Google Scholar
  42. Tayyaran MR, Khan AM (2003) The effects of telecommuting and intelligent transportation systems on urban development. J Urban Technol 10(2):87–100CrossRefGoogle Scholar
  43. Urban Land Institute (2009) Moving cooler: an analysis of transportation strategies for reducing greenhouse gas emissions. Urban Land Institute, WashingtonGoogle Scholar
  44. U.S. Bureau of Labor Statistics (2012) Labor force statistics from the current population survey data, 2009 annual average-house data-tables form employment and earnings. In: Employment status of the civilian noninstitutional population, 1940s to date. Retrieved 24 July 2012
  45. Zhu P (2011) Telecommuting, travel behavior and residential location choice: can telecommuting be an effective policy to reduce travel demand? Ph.D. Dissertation, University of Southern CaliforniaGoogle Scholar
  46. Zhu P (2012) Are telecommuting and personal travel complements or substitutes? Ann Reg Sci 48(2):619–639CrossRefGoogle Scholar
  47. Zhu P (2013) Telecommuting, household commute and location choice. Urban Stud. doi: 10.1177/0042098012474520

Copyright information

© Islamic Azad University (IAU) 2014

Authors and Affiliations

  1. 1.Department of Community and Regional PlanningBoise State UniversityBoiseUSA

Personalised recommendations