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Optimal time switching from tayloristic to holistic workplace organization

Author

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  • Thomas Vallée

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

  • Eva Moreno-Galbis

    (GAINS - Groupe d'Analyse des Itinéraires et des Niveaux Salariaux - UM - Le Mans Université)

Abstract

The introduction of information and communication technologies in firms over recent decades has engendered a process of internal workplace reorganization in order to maximize performance. Using a two-stage optimal control technique, this paper provides analytical solutions for the conditions under which a firm adopts a new organizational regime characterized by multitasking and an horizontal hierarchical structure (holistic organization). We consider two flexibility options: (a) the possibility that only a part of the labor force is switched to the new organization and, (b) the possibility that any loss of productivity is not permanent. In all cases we conclude that the new organization is adopted if, and only if, the productivity gains in the capital-goods sector compensate both the loss of expertise suffered by workers and the drop in consumption.

Suggested Citation

  • Thomas Vallée & Eva Moreno-Galbis, 2011. "Optimal time switching from tayloristic to holistic workplace organization," Post-Print hal-03193658, HAL.
    • Handle: RePEc:hal:journl:hal-03193658
    DOI: 10.1016/j.strueco.2011.04.001
    Note: View the original document on HAL open archive server: https://hal.science/hal-03193658
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    Cited by:

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    2. Stefan Wrzaczek & Michael Kuhn & Ivan Frankovic, 2020. "Using Age Structure for a Multi-stage Optimal Control Model with Random Switching Time," Journal of Optimization Theory and Applications, Springer, vol. 184(3), pages 1065-1082, March.
    3. Elke Moser & Andrea Seidl & Gustav Feichtinger, 2014. "History-dependence in production-pollution-trade-off models: a multi-stage approach," Annals of Operations Research, Springer, vol. 222(1), pages 457-481, November.

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