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Temporal workload in economic organizations: A hidden non-linear condition of economic efficiency

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  • von Schéele, Fabian
  • Haftor, Darek M.

Abstract

A temporal workload model is introduced to identify the relationship between the work time and economic performance of the activities conducted by a human agent in the context of an economic organization. The model's novelty derives from the account of time perception and its consequent cognitive time distortion, the latter being understood as a discrepancy between physical and cognitive time. Current praxis, both theoretical and empirical, assumes only physical time. This assumption is challenged here through the inclusion of time perception and cognitive time distortion in estimating the temporal workload of an economic agent. This inclusion enables a novel comprehension of frequent operational challenges, such as work delays, human stress, output quality issues, and economic inefficiencies. The main contribution to the literature is a specification of a new condition that governs the performance of any economic organization where human agents conduct time assessments.

Suggested Citation

  • von Schéele, Fabian & Haftor, Darek M., 2018. "Temporal workload in economic organizations: A hidden non-linear condition of economic efficiency," Journal of Business Research, Elsevier, vol. 88(C), pages 415-420.
    • Handle: RePEc:eee:jbrese:v:88:y:2018:i:c:p:415-420
    DOI: 10.1016/j.jbusres.2018.01.042
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    References listed on IDEAS

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    Cited by:

    1. von Schéele, Fabian & Haftor, Darek M. & Pashkevich, Natallia, 2020. "Cognitive time as a service price determinant: Hidden dynamics and price collapse," Journal of Business Research, Elsevier, vol. 112(C), pages 248-253.
    2. Pashkevich, Natallia & von Schéele, Fabian & Haftor, Darek M., 2023. "Accounting for cognitive time in activity-based costing: A technology for the management of digital economy," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    3. Fabian Schéele & Darek M. Haftor & Natallia Pashkevich, 2022. "Predicting delays in service operations," Service Business, Springer;Pan-Pacific Business Association, vol. 16(2), pages 211-226, June.

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