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Impacts of Home-Based Telecommuting on Vehicle-Miles Traveled: A Nationwide Time Series Analysis

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  • Choo, Sangho
  • Mokhtarian, Patricia L.
  • Salomon, Ilan

Abstract

This study estimates the impact of telecommuting on personal transportation using a multi-variate time series analysis of aggregate nationwide data spanning 1966-1999 for all variables except telecommuting, and 1988-1998 for telecommuting. Three dependent variables were modeled, in direct and per-capita forms: ground vehicle miles traveled (VMT), airline passenger miles traveled (PMT), and the sum of those two variable, loosely referred to as total miles traveled. The first part of the analysis modeled each dependent variable (1966-1999) as a function of conventional variables representing economic activity, the cost of transportation transportation supply, and demographics. In the second part of the study, the residuals of the first part (1988-1998) were modeled as a function of the number of telecommuters. Secondary data sources were used for the study. After the modeling results are presented, the study offers several public policy recommendations, based on the conclusion that telecommuting appears to have a statistically significant, albeit modes in magnitude, effect on reducing travel.

Suggested Citation

  • Choo, Sangho & Mokhtarian, Patricia L. & Salomon, Ilan, 2002. "Impacts of Home-Based Telecommuting on Vehicle-Miles Traveled: A Nationwide Time Series Analysis," Institute of Transportation Studies, Working Paper Series qt2gj976x6, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt2gj976x6
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    References listed on IDEAS

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    Cited by:

    1. Choo, Sangho & Mokhtarian, Patricia L, 2008. "Telecommunications and travel demand and supply: Aggregate structural equation models for the US," University of California Transportation Center, Working Papers qt6q8518s4, University of California Transportation Center.
    2. Sangho Choo & Patricia Mokhtarian & Ilan Salomon, 2005. "Does telecommuting reduce vehicle-miles traveled? An aggregate time series analysis for the U.S," Transportation, Springer, vol. 32(1), pages 37-64, January.
    3. Okyere, Dennis Kwadwo & Poku-Boansi, Michael & Adarkwa, Kwasi Kwafo, 2018. "Connecting the dots: The nexus between transport and telecommunication in Ghana," Telecommunications Policy, Elsevier, vol. 42(10), pages 836-844.
    4. Kong, Hui & Moody, Joanna & Zhao, Jinhua, 2020. "ICT’s impacts on ride-hailing use and individual travel," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 1-15.
    5. Melo, Patrícia C. & de Abreu e Silva, João, 2017. "Home telework and household commuting patterns in Great Britain," Transportation Research Part A: Policy and Practice, Elsevier, vol. 103(C), pages 1-24.
    6. Choo, Sangho & Mokhtarian, Patricia L., 2007. "Telecommunications and travel demand and supply: Aggregate structural equation models for the US," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(1), pages 4-18, January.
    7. Mokhtarian, Patricia L & Salomon, Ilan & Choo, Sangho, 2004. "Data and Measurement Issues in Transportation, With Telecommuting as a Case Study," Institute of Transportation Studies, Working Paper Series qt9pt8s9jv, Institute of Transportation Studies, UC Davis.

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