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Unifying temporal and organizational scales in multiscale decision-making


  • Wernz, Christian
  • Deshmukh, Abhijit


In enterprise systems, making decisions is a complex task for agents at all levels of the organizational hierarchy. To calculate an optimal course of action, an agent has to include uncertainties and the anticipated decisions of other agents, recognizing that they also engage in a stochastic, game-theoretic reasoning process. Furthermore, higher-level agents seek to align the interests of their subordinates by providing incentives. Incentive-giving and receiving agents need to include the effect of the incentive on their payoffs in the optimal strategy calculations. In this paper, we present a multiscale decision-making model that accounts for uncertainties and organizational interdependencies over time. Multiscale decision-making combines stochastic games with hierarchical Markov decision processes to model and solve multi-organizational-scale and multi-time-scale problems. This is the first model that unifies the organizational and temporal scales and can solve a 3-agent, 3-period problem. Solutions can be derived as analytic equations with low computational effort. We apply the model to a service enterprise challenge that illustrates the applicability and relevance of the model. This paper makes an important contribution to the foundation of multiscale decision theory and represents a key step towards solving the general X-agent, T-period problem.

Suggested Citation

  • Wernz, Christian & Deshmukh, Abhijit, 2012. "Unifying temporal and organizational scales in multiscale decision-making," European Journal of Operational Research, Elsevier, vol. 223(3), pages 739-751.
  • Handle: RePEc:eee:ejores:v:223:y:2012:i:3:p:739-751
    DOI: 10.1016/j.ejor.2012.06.038

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    References listed on IDEAS

    1. Wernz, Christian & Deshmukh, Abhijit, 2010. "Multiscale decision-making: Bridging organizational scales in systems with distributed decision-makers," European Journal of Operational Research, Elsevier, vol. 202(3), pages 828-840, May.
    2. Christian Wernz & Andrew Henry, 2009. "Multi-Level Coordination and Decision-Making in Service Operations," Service Science, INFORMS, vol. 1(4), pages 270-283, December.
    3. Gfrerer, Helmut & Zapfel, Gunther, 1995. "Hierarchical model for production planning in the case of uncertain demand," European Journal of Operational Research, Elsevier, vol. 86(1), pages 142-161, October.
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    5. Ozdamar, Linet & Bozyel, M. Ali & Birbil, S. Ilker, 1998. "A hierarchical decision support system for production planning (with case study)," European Journal of Operational Research, Elsevier, vol. 104(3), pages 403-422, February.
    6. Vetschera, Rudolf, 2000. "A multi-criteria agency model with incomplete preference information," European Journal of Operational Research, Elsevier, vol. 126(1), pages 152-165, October.
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    Cited by:

    1. L. A. Shah & A. Etienne & A. Siadat & F. Vernadat, 2016. "Decision-making in the manufacturing environment using a value-risk graph," Journal of Intelligent Manufacturing, Springer, vol. 27(3), pages 617-630, June.


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