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Self-Selected Task Allocation

Author

Listed:
  • Refael Hassin

    (Department of Statistics and Operations Research, School of Mathematical Sciences, Tel Aviv University, Tel Aviv 6997801, Israel)

  • Adam Nathaniel

    (Department of Statistics and Operations Research, School of Mathematical Sciences, Tel Aviv University, Tel Aviv 6997801, Israel)

Abstract

Problem definition : Tasks sequentially arrive, and their values to the workers who are going to perform them are independent random variables. The common way to allocate tasks to workers is according to the first-in, first-out order. But this method both is inefficient and seems unfair to those who receive a low-valued task after a long wait. We are looking for a better allocation method. Academic/practical relevance : Finding a fair and efficient task allocation method is an aspiration of manpower firms that employ a pool of workers, such as salespersons, technicians, emergency medical stuff, nurses, or taxi drivers. We present many more implementations, such as turn taking and load management. Methodology : We propose a self-selected task allocation method and discuss its importance and implementations. The proposed method is defined as a cyclic queueing game with a fixed number of players. Every unit of time a prize with a random value is offered to the players according to their order in the queue, and a player who accepts a prize moves to the end of the queue. The process of choosing which prizes to accept in each position is presented as a noncooperative multiplayer game. We analyze strategies and symmetric equilibria for three variations. Results : We provide closed-form solutions and suggest a novel intuitive interpretation to find equilibria via calculating maximum-profit strategies. We complement the theoretical results by conducting a numerical study. Managerial implications : The proposed method is natural and easy to implement, its outcome is better than the common allocation by seniority, and the ratio of the expected value obtained under the two methods is unbounded.

Suggested Citation

  • Refael Hassin & Adam Nathaniel, 2021. "Self-Selected Task Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 23(6), pages 1669-1682, November.
  • Handle: RePEc:inm:ormsom:v:23:y:2021:i:6:p:1669-1682
    DOI: 10.1287/msom.2020.0904
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    References listed on IDEAS

    as
    1. Francis Bloch & David Cantala, 2017. "Dynamic Assignment of Objects to Queuing Agents," Post-Print halshs-03968341, HAL.
    2. Lauren Xiaoyuan Lu & Jan A. Van Mieghem & R. Canan Savaskan, 2009. "Incentives for Quality Through Endogenous Routing," Manufacturing & Service Operations Management, INFORMS, vol. 11(2), pages 254-273, July.
    3. Björn Brügemann & Pieter Gautier & Guido Menzio, 2019. "Intra Firm Bargaining and Shapley Values," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 86(2), pages 564-592.
    4. Ralf Borndörfer & Christof Schulz & Stephan Seidl & Steffen Weider, 2017. "Integration of duty scheduling and rostering to increase driver satisfaction," Public Transport, Springer, vol. 9(1), pages 177-191, July.
    5. Ernst, A. T. & Jiang, H. & Krishnamoorthy, M. & Sier, D., 2004. "Staff scheduling and rostering: A review of applications, methods and models," European Journal of Operational Research, Elsevier, vol. 153(1), pages 3-27, February.
    6. Francis Bloch & David Cantala, 2017. "Dynamic Assignment of Objects to Queuing Agents," American Economic Journal: Microeconomics, American Economic Association, vol. 9(1), pages 88-122, February.
    7. Refael Hassin & Moshe Haviv, 1997. "Equilibrium Threshold Strategies: The Case of Queues with Priorities," Operations Research, INFORMS, vol. 45(6), pages 966-973, December.
    8. Xuanming Su & Stefanos A. Zenios, 2006. "Recipient Choice Can Address the Efficiency-Equity Trade-off in Kidney Transplantation: A Mechanism Design Model," Management Science, INFORMS, vol. 52(11), pages 1647-1660, November.
    9. Dimitris Bertsimas & Vivek F. Farias & Nikolaos Trichakis, 2012. "On the Efficiency-Fairness Trade-off," Management Science, INFORMS, vol. 58(12), pages 2234-2250, December.
    10. Israel David & Uri Yechiali, 1985. "A Time-dependent Stopping Problem with Application to Live Organ Transplants," Operations Research, INFORMS, vol. 33(3), pages 491-504, June.
    11. Man Yu & Roman Kapuscinski & Hyun-Soo Ahn, 2015. "Advance Selling: Effects of Interdependent Consumer Valuations and Seller’s Capacity," Management Science, INFORMS, vol. 61(9), pages 2100-2117, September.
    12. Xia, Li, 2014. "Service rate control of closed Jackson networks from game theoretic perspective," European Journal of Operational Research, Elsevier, vol. 237(2), pages 546-554.
    13. Mor Armony & Amy R. Ward, 2010. "Fair Dynamic Routing in Large-Scale Heterogeneous-Server Systems," Operations Research, INFORMS, vol. 58(3), pages 624-637, June.
    14. A C Brooms & E J Collins, 2013. "Stochastic Order Results and Equilibrium Joining Rules for the Bernoulli Feedback Queue," Birkbeck Working Papers in Economics and Finance 1305, Birkbeck, Department of Economics, Mathematics & Statistics.
    15. Jinhong Xie & Steven M. Shugan, 2001. "Electronic Tickets, Smart Cards, and Online Prepayments: When and How to Advance Sell," Marketing Science, INFORMS, vol. 20(3), pages 219-243, June.
    16. David R. Karger & Sewoong Oh & Devavrat Shah, 2014. "Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems," Operations Research, INFORMS, vol. 62(1), pages 1-24, February.
    17. Francis Bloch & David Cantala, 2017. "Dynamic Assignment of Objects to Queuing Agents," PSE-Ecole d'économie de Paris (Postprint) halshs-03968341, HAL.
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