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Cooperation in Service Systems

Author

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  • Shoshana Anily

    (Faculty of Management, Tel Aviv University, Tel Aviv 69978, Israel)

  • Moshe Haviv

    (Department of Statistics, The Hebrew University of Jerusalem, Jerusalem 91905, Israel)

Abstract

We consider a number of servers that may improve the efficiency of the system by pooling their service capacities to serve the union of the individual streams of customers. This economies-of-scope phenomenon is due to the reduction in the steady-state mean total number of customers in the system. The question we pose is how the servers should split among themselves the cost of the pooled system. When the individual incoming streams of customers form Poisson processes and individual service times are exponential, we define a transferable utility cooperative game in which the cost of a coalition is the mean number of customers (or jobs) in the pooled system. We show that, despite the characteristic function is neither monotone nor concave, the game and its subgames possess nonempty cores. In other words, for any subset of servers there exist cost-sharing allocations under which no partial subset can take advantage by breaking away and forming a separate coalition. We give an explicit expression for all (infinitely many) nonnegative core cost allocations of this game. Finally, we show that, except for the case where all individual servers have the same cost, there exist infinitely many core allocations with negative entries, and we show how to construct a convex subset of the core where at least one server is being paid to join the grand coalition.

Suggested Citation

  • Shoshana Anily & Moshe Haviv, 2010. "Cooperation in Service Systems," Operations Research, INFORMS, vol. 58(3), pages 660-673, June.
  • Handle: RePEc:inm:oropre:v:58:y:2010:i:3:p:660-673
    DOI: 10.1287/opre.1090.0737
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    References listed on IDEAS

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    Cited by:

    1. Shoshana Anily, 2018. "Full characterization of the nonnegative core of some cooperative games," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(4), pages 303-316, June.
    2. Shuo Zeng & Moshe Dror, 2019. "Serving many masters: an agent and his principals," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 90(1), pages 23-59, August.
    3. Frank Karsten & Marco Slikker & Geert-Jan van Houtum, 2015. "Resource Pooling and Cost Allocation Among Independent Service Providers," Operations Research, INFORMS, vol. 63(2), pages 476-488, April.
    4. Loe Schlicher & Marco Slikker & Willem van Jaarsveld & Geert-Jan van Houtum, 2020. "Core Nonemptiness of Stratified Pooling Games: A Structured Markov Decision Process Approach," Mathematics of Operations Research, INFORMS, vol. 45(4), pages 1445-1465, November.
    5. Bendel, Dan & Haviv, Moshe, 2018. "Cooperation and sharing costs in a tandem queueing network," European Journal of Operational Research, Elsevier, vol. 271(3), pages 926-933.
    6. Lotty E. Westerink‐Duijzer & Loe P. J. Schlicher & Marieke Musegaas, 2020. "Core Allocations for Cooperation Problems in Vaccination," Production and Operations Management, Production and Operations Management Society, vol. 29(7), pages 1720-1737, July.
    7. Malaki, Saha & Izady, Navid & de Menezes, Lilian M., 2023. "A framework for optimal recruitment of temporary and permanent healthcare workers in highly uncertain environments," European Journal of Operational Research, Elsevier, vol. 308(2), pages 768-781.
    8. Westerink-Duijzer, L.E. & Schlicher, L.P.J. & Musegaas, M., 2019. "Fair allocations for cooperation problems in vaccination," Econometric Institute Research Papers EI2019-06, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    9. Riccardo Colini-Baldeschi & Marco Scarsini & Stefano Vaccari, 2018. "Variance Allocation and Shapley Value," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 919-933, September.
    10. Schlicher, L.P.J. & Musegaas, M. & Westerink-Duijzer, L.E., 2019. "Resource location games," Econometric Institute Research Papers EI2019-05, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Loe Schlicher & Marco Slikker & Geert‐Jan van Houtum, 2017. "Probabilistic resource pooling games," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(7), pages 531-546, October.
    12. Lu, Liang & Qi, Xiangtong & Liu, Zhixin, 2014. "On the cooperation of recycling operations," European Journal of Operational Research, Elsevier, vol. 233(2), pages 349-358.
    13. Chakravarthy, Srinivas R., 2016. "Queueing models with optional cooperative services," European Journal of Operational Research, Elsevier, vol. 248(3), pages 997-1008.
    14. Ulaş Özen & Marco Slikker & Greys Sošić, 2022. "On the core of m$m$‐attribute games," Production and Operations Management, Production and Operations Management Society, vol. 31(4), pages 1770-1787, April.
    15. Shoshana Anily & Moshe Haviv, 2014. "Subadditive and Homogeneous of Degree One Games Are Totally Balanced," Operations Research, INFORMS, vol. 62(4), pages 788-793, August.

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