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Unifying temporal and organizational scales in multiscale decision-making

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  • Wernz, Christian
  • Deshmukh, Abhijit

Abstract

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

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    Cited by:

    1. Hui Zhang & Christian Wernz & Anthony D. Slonim, 2016. "Aligning incentives in health care: a multiscale decision theory approach," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 4(3), pages 219-244, November.
    2. Hui Zhang & Christian Wernz & Danny R. Hughes, 2018. "Modeling and designing health care payment innovations for medical imaging," Health Care Management Science, Springer, vol. 21(1), pages 37-51, March.
    3. Peter A. Beling, 2013. "Multi-scale decision making: challenges in engineering and environmental systems," Environment Systems and Decisions, Springer, vol. 33(3), pages 323-325, September.
    4. Aditya U. Kulkarni & Christian Wernz, 2020. "Optimal incentives for teams: a multiscale decision theory approach," Annals of Operations Research, Springer, vol. 288(1), pages 307-329, May.
    5. Andrew Henry & Christian Wernz, 2015. "A multiscale decision theory analysis for revenue sharing in three-stage supply chains," Annals of Operations Research, Springer, vol. 226(1), pages 277-300, March.
    6. 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.
    7. Christian Wernz & Yongjia Song & Danny R. Hughes, 2021. "How hospitals can improve their public quality metrics: a decision-theoretic model," Health Care Management Science, Springer, vol. 24(4), pages 702-715, December.

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