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Modeling the Choice of Telecommuting: 3. Identifying the Choice Set and Estimating Binary Choice Models for Technology-Based Alternatives

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  • P L Mokhtarian

    (Department of Civil and Environmental Engineering and Institute of Transportation Studies, University of California, Davis, CA 95616, USA)

  • I Salomon

    (Department of Geography, Hebrew University, Jerusalem 91905, Israel)

Abstract

In previous papers in this series we have presented a conceptual model of the individual decision to telecommute and explored relationships among constraints, preference, and choice. In a related paper we developed a binary model of the preference for home-based telecommuting. Noting that there is a wide gap between preferring to telecommute (88% of the sample) and actually telecommuting (13%), in this paper we develop binary logit models of telecommuting adoption. Two approaches to dealing with constraints are compared: incorporating them directly into the utility function, and using them to define the choice set. Models using the first approach appear to be statistically superior in this analysis, explaining 63–64% of the information in the data. Variables significant to choice include those relating to work and travel drives, and awareness, manager support, job suitability, technology, and discipline constraints. The best model was used to analyze the impact of relaxing three key constraints on the 355 people in the sample for whom telecommuting was previously identified to be a preferred impossible alternative (PIA). When unawareness, lack of manager support, and job unsuitability constraints are relaxed, 28% of the people in the PIA category would be expected to adopt telecommuting. The importance of behavioral models to forecast telecommuting adoption accurately is emphasized and is suggested to have wider implications for predicting technology-based activity changes.

Suggested Citation

  • P L Mokhtarian & I Salomon, 1996. "Modeling the Choice of Telecommuting: 3. Identifying the Choice Set and Estimating Binary Choice Models for Technology-Based Alternatives," Environment and Planning A, , vol. 28(10), pages 1877-1894, October.
    • Handle: RePEc:sae:envira:v:28:y:1996:i:10:p:1877-1894
    DOI: 10.1068/a281877
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    References listed on IDEAS

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    1. Mannering, Jill S. & Mokhtarian, Patricia L., 1995. "Modeling the Choice of Telecommuting Frequency in California: An Exploratory Analysis," University of California Transportation Center, Working Papers qt08s817dr, University of California Transportation Center.
    2. Mokhtarian, Patricia L. & Salomon, Ilan, 1997. "Modeling the desire to telecommute: The importance of attitudinal factors in behavioral models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(1), pages 35-50, January.
    3. P L Mokhtarian & I Salomon, 1996. "Modeling the Choice of Telecommuting: 2. A Case of the Preferred Impossible Alternative," Environment and Planning A, , vol. 28(10), pages 1859-1876, October.
    4. Mokhtarian, Patricia L. & Salomon, Ilan, 1995. "Modeling the Preference for Telecommuting: Measuring Attitudes and Other Variables," University of California Transportation Center, Working Papers qt2kn111m8, University of California Transportation Center.
    5. Genç, Murat, 1994. "Aggregation and heterogeneity of choice sets in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 28(1), pages 11-22, February.
    6. Manski, Charles F & Lerman, Steven R, 1977. "The Estimation of Choice Probabilities from Choice Based Samples," Econometrica, Econometric Society, vol. 45(8), pages 1977-1988, November.
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    1. Mokhtarian, Patricia L. & Salomon, Ilan, 1997. "Modeling the desire to telecommute: The importance of attitudinal factors in behavioral models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 31(1), pages 35-50, January.
    2. Mokhtarian, Patricia L., 2020. "Wenn die Telekommunikation den Verkehr so gut ersetzen kann, warum gibt es dann immer mehr Staus?," Forschungsberichte der ARL: Aufsätze, in: Reutter, Ulrike & Holz-Rau, Christian & Albrecht, Janna & Hülz, Martina (ed.), Wechselwirkungen von Mobilität und Raumentwicklung im Kontext gesellschaftlichen Wandels, volume 14, pages 167-195, ARL – Akademie für Raumentwicklung in der Leibniz-Gemeinschaft.
    3. Singh, Rajesh & Orazem, Peter F. & Song, Moohoun, 2006. "Broadband Access, Telecommuting and the Urban-Rural Digital Divide," Working Papers 18214, Iowa State University, Department of Economics.
    4. Becky P. Y. Loo & Bo Wang, 2018. "Factors associated with home-based e-working and e-shopping in Nanjing, China," Transportation, Springer, vol. 45(2), pages 365-384, March.
    5. Ory, D T & Mokhtarian, Patricia L, 2005. "Don’t Work, Work at Home, or Commute? Discrete Choice Models of the Decision for San Francisco Bay Area Residents," Institute of Transportation Studies, Working Paper Series qt71q8b94r, Institute of Transportation Studies, UC Davis.
    6. Shafizadeh, Kevan R. & Mokhtarian, Patricia L. & Niemeier, Debbie A. & Salomon, Ilan, 2000. "The Costs and Benefits of Home-Based Telecommuting," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt49c1n7hg, Institute of Transportation Studies, UC Berkeley.
    7. Ory, David T. & Mokhtarian, Patricia L., 2005. "Modeling the Joint Labor-Commute Engagement Decisions of San Francisco Bay Area Residents," University of California Transportation Center, Working Papers qt7600m6qv, University of California Transportation Center.
    8. 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.
    9. Haddad, Hebba & Lyons, Glenn & Chatterjee, Kiron, 2009. "An examination of determinants influencing the desire for and frequency of part-day and whole-day homeworking," Journal of Transport Geography, Elsevier, vol. 17(2), pages 124-133.
    10. Varma, Krishna & Ho, Chaang-Iuan & Stanek, David & Mokhtarian, Patricia, 1998. "Duration and Frequency of Telecenter Use: Once a Telecommuter, Always a Telecommuter?," Institute of Transportation Studies, Working Paper Series qt61t9j2vb, Institute of Transportation Studies, UC Davis.
    11. Nijland, Linda & Dijst, Martin, 2015. "Commuting-related fringe benefits in the Netherlands: Interrelationships and company, employee and location characteristics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 77(C), pages 358-371.
    12. Nayak, Suchismita & Pandit, Debapratim, 2021. "Potential of telecommuting for different employees in the Indian context beyond COVID-19 lockdown," Transport Policy, Elsevier, vol. 111(C), pages 98-110.
    13. Pawlak, Jacek & Polak, John W. & Sivakumar, Aruna, 2015. "Towards a microeconomic framework for modelling the joint choice of activity–travel behaviour and ICT use," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 92-112.
    14. José M. Ortiz-Lozano & Pedro C. Martínez-Morán & Víctor L. de Nicolás, 2022. "Teleworking in the Public Administration: An Analysis Based on Spanish Civil Servants’ Perspectives During the Pandemic," SAGE Open, , vol. 12(1), pages 21582440221, March.
    15. Hynes, Mike, 2016. "Developing (tele)work? A multi-level sociotechnical perspective of telework in Ireland," Research in Transportation Economics, Elsevier, vol. 57(C), pages 21-31.
    16. Wilton, Robert D. & Páez, Antonio & Scott, Darren M., 2011. "Why do you care what other people think? A qualitative investigation of social influence and telecommuting," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 269-282, May.
    17. Mokhtarian, Patricia L & Henderson, Dennis, 2000. "Analyzing the Travel Behavior of Home-Based Workers in the 1991 CALTRANS Statewide Travel Survey," University of California Transportation Center, Working Papers qt6qp7q90q, University of California Transportation Center.

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