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What Drives Telecommuting? The Relative Impact of Worker Demographics, Employer Characteristics, and Job Types

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Author Info

  • Margaret Walls

    ()
    (Resources for the Future)

  • Safirova, Elena

    ()
    (Resources for the Future)

  • Jiang, Yi

Abstract

We analyze a 2002 survey of Southern California residents to evaluate the relative importance of factors that affect workers’ propensity to telecommute and telecommuting frequency. The survey collected a wealth of individual demographic information as well as job type, industry, and employer characteristics from about 5,000 residents. In agreement with previous studies, we find that the propensity to telecommute is increasing with worker age and educational attainment. At the same time, we conclude that the propensity to telecommute depends to a large extent on a worker’s job characteristics and that the quantitative effects of job characteristics are at least as important as demographic factors. We also study what factors affect telecommuting frequency based on a one-week commuting diary of the telecommuters in the survey. The industry and occupation categories that play a significant role in affecting propensity to telecommute do not have similar effects on telecommuting frequency. On the contrary, some other job-related factors show substantial influences.

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Bibliographic Info

Paper provided by Resources For the Future in its series Discussion Papers with number dp-06-41.

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Date of creation: 19 Oct 2006
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Handle: RePEc:rff:dpaper:dp-06-41

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Related research

Keywords: telecommuting; telework; transportation planning; econometric estimation; telecommuting frequency; telecommuting propensity;

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References

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  1. Walls, Margaret & Safirova, Elena, 2004. "A Review of the Literature on Telecommuting and Its Implications for Vehicle Travel and Emissions," Discussion Papers dp-04-44, Resources For the Future.
  2. Mokhtarian, Patricia L. & Salomon, Ilan, 1997. "Modeling the Desire to Telecommute: The Importance of Attitudinal Factors in Behavioral Models," University of California Transportation Center, Working Papers qt29z267km, University of California Transportation Center.
  3. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 31(3), pages 129-137.
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Cited by:
  1. Tang, Wei & Mokhtarian, Patricia L & Handy, Susan L, 2008. "The Role of Neighborhood Characteristics in the Adoption and Frequency of Working at Home: Empirical Evidence from Northern California," Institute of Transportation Studies, Working Paper Series qt13x2q3rb, Institute of Transportation Studies, UC Davis.

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