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Flextime, Traffic Congestion and Urban Productivity

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  • Se-il Mun
  • Makoto Yonekawa

Abstract

How many firms choose to adopt flextime without any policy intervention? Does promoting flextime improve social welfare? This paper addresses these two questions. We extend the model of bottleneck congestion to describe the case in which some firms in a city adopt flextime. The model also incorporates effects on urban productivity via agglomeration economy. Each firm chooses whether to adopt flextime or not, taking into account the trade-off between productivity and congestion. Equilibrium determines the number of firms adopting flextime and commuters' departure patterns. We investigate the conditions in which flextime is adopted in equilibrium. Moreover, we demonstrate that multiple equilibria with respect to the number of firms adopting flextime may arise. The less efficient solution, the one without flextime, is likely to persist. We also examine the effect of a congestion toll on social welfare. © 2006 LSE and the University of Bath

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  • Se-il Mun & Makoto Yonekawa, 2006. "Flextime, Traffic Congestion and Urban Productivity," Journal of Transport Economics and Policy, University of Bath, vol. 40(3), pages 329-358, September.
    • Handle: RePEc:tpe:jtecpo:v:40:y:2006:i:3:p:329-358
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    Cited by:

    1. Takayama, Yuki, 2015. "Bottleneck congestion and distribution of work start times: The economics of staggered work hours revisited," Transportation Research Part B: Methodological, Elsevier, vol. 81(P3), pages 830-847.
    2. 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.
    3. Takayama, Yuki & Kuwahara, Masao, 2017. "Bottleneck congestion and residential location of heterogeneous commuters," Journal of Urban Economics, Elsevier, vol. 100(C), pages 65-79.
    4. Amirgholy, Mahyar & Gao, H. Oliver, 2017. "Modeling the dynamics of congestion in large urban networks using the macroscopic fundamental diagram: User equilibrium, system optimum, and pricing strategies," Transportation Research Part B: Methodological, Elsevier, vol. 104(C), pages 215-237.
    5. Eva Gutiérrez-i-Puigarnau & Jos N. Van Ommeren, 2012. "Start Time and Worker Compensation Implications for Staggered-Hours Programmes," Journal of Transport Economics and Policy, University of Bath, vol. 46(2), pages 205-220, May.
    6. Tao Li, 2020. "The Value of Access to Rail Transit in a Congested City: Evidence from Housing Prices in Beijing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 48(2), pages 556-598, June.
    7. Takayama, Yuki, 2020. "Who gains and who loses from congestion pricing in a monocentric city with a bottleneck?," Economics of Transportation, Elsevier, vol. 24(C).
    8. Hugo E. Silva & Robin Lindsey & André de Palma & Vincent A. C. van den Berg, 2017. "On the Existence and Uniqueness of Equilibrium in the Bottleneck Model with Atomic Users," Transportation Science, INFORMS, vol. 51(3), pages 863-881, August.
    9. Ramadurai, Gitakrishnan & Ukkusuri, Satish V. & Zhao, Jinye & Pang, Jong-Shi, 2010. "Linear complementarity formulation for single bottleneck model with heterogeneous commuters," Transportation Research Part B: Methodological, Elsevier, vol. 44(2), pages 193-214, February.
    10. Li, Zhi-Chun & Huang, Hai-Jun & Yang, Hai, 2020. "Fifty years of the bottleneck model: A bibliometric review and future research directions," Transportation Research Part B: Methodological, Elsevier, vol. 139(C), pages 311-342.
    11. Su, Qida & Wang, David Z.W., 2020. "On the commute travel pattern with compressed work schedule," Transportation Research Part A: Policy and Practice, Elsevier, vol. 136(C), pages 334-356.
    12. Takayama, Yuki, 2018. "Time-varying congestion tolling and urban spatial structure," MPRA Paper 89896, University Library of Munich, Germany.

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