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Modeling the Choice of Work Schedule with Flexible Work Hours

Author

Listed:
  • Anthony J. Moore

    (Civil Engineering Department, Northwestern University, Evanston, Illinois)

  • Paul P. Jovanis

    (Civil Engineering Department, Northwestern University, Evanston, Illinois)

  • Frank S. Koppelman

    (Civil Engineering Department, Northwestern University, Evanston, Illinois)

Abstract

Flexible work hours have been promoted as a low cost approach to improve the productivity of the existing transportation system. However, analytical tools are needed to evaluate the impact such policies have on workers' arrival time choices. This paper develops a behaviorally based structure, using utility maximization concepts, to relate travel, family, workplace and individual influences to the workers' choices of arrival times with flextime. The accuracy of this conceptual structure is explored through the development of disaggregate probability distribution models using maximum likelihood estimation techniques. These models investigate several specifications and examine the use of market segmentation to differentiate varying work arrival time behavior by different subsets of the population. Major findings include: older workers and those living at greater distances from the workplace tend to arrive earlier, and households constrained by the presence of a working spouse and young children have less flexibility to alter arrival times with flextime.

Suggested Citation

  • Anthony J. Moore & Paul P. Jovanis & Frank S. Koppelman, 1984. "Modeling the Choice of Work Schedule with Flexible Work Hours," Transportation Science, INFORMS, vol. 18(2), pages 141-164, May.
  • Handle: RePEc:inm:ortrsc:v:18:y:1984:i:2:p:141-164
    DOI: 10.1287/trsc.18.2.141
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    Citations

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    Cited by:

    1. Robin Lindsey, 2004. "Existence, Uniqueness, and Trip Cost Function Properties of User Equilibrium in the Bottleneck Model with Multiple User Classes," Transportation Science, INFORMS, vol. 38(3), pages 293-314, August.
    2. André De Palma & Cédric Fontan & Asad J. Khattak, 2004. "Analyzing work departure time variability in Brussels," Reflets et perspectives de la vie économique, De Boeck Université, vol. 0(4), pages 89-110.
    3. Saleh, Wafaa & Farrell, Séona, 2005. "Implications of congestion charging for departure time choice: Work and non-work schedule flexibility," Transportation Research Part A: Policy and Practice, Elsevier, vol. 39(7-9), pages 773-791.
    4. Chen, Dongxu & Sun, Yu & Yang, Zhongzhen, 2020. "Optimization of the travel ban scheme of cars based on the spatial distribution of the last digit of license plates," Transport Policy, Elsevier, vol. 94(C), pages 43-53.
    5. Wöhner, Fabienne, 2022. "Work flexibly, travel less? The impact of telework and flextime on mobility behavior in Switzerland," Journal of Transport Geography, Elsevier, vol. 102(C).
    6. Wilfredo Yushimito & Xuegang Ban & José Holguín-Veras, 2015. "Correcting the Market Failure in Work Trips with Work Rescheduling: An Analysis Using Bi-level Models for the Firm-workers Interplay," Networks and Spatial Economics, Springer, vol. 15(3), pages 883-915, September.
    7. Fosgerau, Mogens & Engelson, Leonid, 2011. "The value of travel time variance," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 1-8, January.
    8. André De Palma & Denis Rochat, 1999. "Understanding individual travel decisions: results from a commuters survey in Geneva," Transportation, Springer, vol. 26(3), pages 263-281, August.
    9. He, Sylvia Y., 2013. "Does flexitime affect choice of departure time for morning home-based commuting trips? Evidence from two regions in California," Transport Policy, Elsevier, vol. 25(C), pages 210-221.
    10. Richard Arnott, 1986. "Information and Time-Of-Use Decisions in Stochastically Congestable Facilities," Discussion Papers 788, Northwestern University, Center for Mathematical Studies in Economics and Management Science.

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