IDEAS home Printed from https://ideas.repec.org/a/bla/popmgt/v30y2021i10p3599-3614.html
   My bibliography  Save this article

Agents’ Self‐Routing for Blended Operations to Balance Inbound and Outbound Services

Author

Listed:
  • Benjamin Legros

Abstract

This study aims to evaluate the cost of agents’ self‐routing in a service system with inbound and outbound customers. We assume that inbound customers arrive over time depending on the waiting time offered, while outbound customers can be contacted at all times. Furthermore, agents are in control of routing decisions and are aware of the state of the system. Accordingly, they decide whether to serve an inbound or outbound customer, or to idle. The system manager seeks to provide a suitable trade‐off between agents’ choice of serving inbound and outbound customers by incentivizing their actions through linear payouts. Hence, there arises a problem of determining the cost of agents’ self‐routing, which can be interpreted as a variant of the principal‐agent problem where the agents’ efforts are directed toward selecting their routing policy. Through a Markov decision process, we show that the agents’ optimal policy is a reservation threshold policy for inbound customers, and express the compensation parameters that minimize staffing cost. We conclude that motivating idling decisions through linear payouts incurs high costs. This justifies the current practice of using automated routing in call centers. Moreover, paying for idling cannot reduce staffing cost. However, discriminating between delayed and non‐delayed customers in the reward structure presents a high potential of reducing agents’ pay. Finally, in situations where agents do not know the status of their colleagues, our analysis argues in favor of not revealing the state of the system to them through delay announcements when the objective waiting time is low.

Suggested Citation

  • Benjamin Legros, 2021. "Agents’ Self‐Routing for Blended Operations to Balance Inbound and Outbound Services," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3599-3614, October.
  • Handle: RePEc:bla:popmgt:v:30:y:2021:i:10:p:3599-3614
    DOI: 10.1111/poms.13452
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/poms.13452
    Download Restriction: no

    File URL: https://libkey.io/10.1111/poms.13452?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sanjay Jain, 2012. "Self-Control and Incentives: An Analysis of Multiperiod Quota Plans," Marketing Science, INFORMS, vol. 31(5), pages 855-869, September.
    2. Gérard P. Cachon & Kaitlin M. Daniels & Ruben Lobel, 2017. "The Role of Surge Pricing on a Service Platform with Self-Scheduling Capacity," Manufacturing & Service Operations Management, INFORMS, vol. 19(3), pages 368-384, July.
    3. Rouba Ibrahim, 2018. "Managing Queueing Systems Where Capacity is Random and Customers are Impatient," Production and Operations Management, Production and Operations Management Society, vol. 27(2), pages 234-250, February.
    4. 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.
    5. Naor, P, 1969. "The Regulation of Queue Size by Levying Tolls," Econometrica, Econometric Society, vol. 37(1), pages 15-24, January.
    6. Tuan Phung-Duc & Wouter Rogiest & Yutaka Takahashi & Herwig Bruneel, 2016. "Retrial queues with balanced call blending: analysis of single-server and multiserver model," Annals of Operations Research, Springer, vol. 239(2), pages 429-449, April.
    7. Shiliang Cui & Senthil Veeraraghavan, 2016. "Blind Queues: The Impact of Consumer Beliefs on Revenues and Congestion," Management Science, INFORMS, vol. 62(12), pages 3656-3672, December.
    8. Srinagesh Gavirneni & Vidyadhar G. Kulkarni, 2016. "Self-Selecting Priority Queues with Burr Distributed Waiting Costs," Production and Operations Management, Production and Operations Management Society, vol. 25(6), pages 979-992, June.
    9. Ehud Kalai & Morton I. Kamien & Michael Rubinovitch, 1992. "Optimal Service Speeds in a Competitive Environment," Management Science, INFORMS, vol. 38(8), pages 1154-1163, August.
    10. Dimitrakopoulos, Y. & Burnetas, A.N., 2016. "Customer equilibrium and optimal strategies in an M/M/1 queue with dynamic service control," European Journal of Operational Research, Elsevier, vol. 252(2), pages 477-486.
    11. Terry A. Taylor, 2018. "On-Demand Service Platforms," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 704-720, October.
    12. Xin Geng & Woonghee Tim Huh & Mahesh Nagarajan, 2015. "Fairness Among Servers When Capacity Decisions Are Endogenous," Production and Operations Management, Production and Operations Management Society, vol. 24(6), pages 961-974, June.
    13. Ragavendran Gopalakrishnan & Sherwin Doroudi & Amy R. Ward & Adam Wierman, 2016. "Routing and Staffing When Servers Are Strategic," Operations Research, INFORMS, vol. 64(4), pages 1033-1050, August.
    14. Duane Christ & Benjamin Avi-Itzhak, 2002. "Strategic Equilibrium for a Pair of Competing Servers with Convex Cost and Balking," Management Science, INFORMS, vol. 48(6), pages 813-820, June.
    15. Xiaoyang Long & Javad Nasiry, 2020. "Wage Transparency and Social Comparison in Sales Force Compensation," Management Science, INFORMS, vol. 66(11), pages 5290-5315, November.
    16. Shan Li & Kay-Yut Chen & Ying Rong, 2020. "The Behavioral Promise and Pitfalls in Compensating Store Managers," Management Science, INFORMS, vol. 66(10), pages 4899-4919, October.
    17. Noah Gans & Yong-Pin Zhou, 2003. "A Call-Routing Problem with Service-Level Constraints," Operations Research, INFORMS, vol. 51(2), pages 255-271, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hung Q. Nguyen & Tuan Phung-Duc, 2022. "Strategic customer behavior and optimal policies in a passenger–taxi double-ended queueing system with multiple access points and nonzero matching times," Queueing Systems: Theory and Applications, Springer, vol. 102(3), pages 481-508, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Legros, Benjamin, 2022. "The principal-agent problem for service rate event-dependency," European Journal of Operational Research, Elsevier, vol. 297(3), pages 949-963.
    2. Benjamin Legros, 2022. "The principal-agent problem for service rate event-dependency," Post-Print hal-03605421, HAL.
    3. Dongyuan Zhan & Amy R. Ward, 2019. "Staffing, Routing, and Payment to Trade off Speed and Quality in Large Service Systems," Operations Research, INFORMS, vol. 67(6), pages 1738-1751, November.
    4. Leon Yang Chu & Zhixi Wan & Dongyuan Zhan, 2018. "Harnessing the Double-edged Sword via Routing: Information Provision on Ride-hailing Platforms," Working Papers 18-04, NET Institute.
    5. Terry A. Taylor, 2018. "On-Demand Service Platforms," Manufacturing & Service Operations Management, INFORMS, vol. 20(4), pages 704-720, October.
    6. Jiaqi Zhou & Ilya O. Ryzhov, 2021. "Equilibrium analysis of observable express service with customer choice," Queueing Systems: Theory and Applications, Springer, vol. 99(3), pages 243-281, December.
    7. De Munck, Thomas & Chevalier, Philippe & Tancrez, Jean-Sébastien, 2023. "Managing priorities on on-demand service platforms with waiting time differentiation," International Journal of Production Economics, Elsevier, vol. 266(C).
    8. Zhao, Chen & Wang, Zhongbin, 2023. "The impact of line-sitting on a two-server queueing system," European Journal of Operational Research, Elsevier, vol. 308(2), pages 782-800.
    9. Saif Benjaafar & Ming Hu, 2020. "Operations Management in the Age of the Sharing Economy: What Is Old and What Is New?," Manufacturing & Service Operations Management, INFORMS, vol. 22(1), pages 93-101, January.
    10. Luyi Yang & Zhongbin Wang & Shiliang Cui, 2021. "A Model of Queue Scalping," Management Science, INFORMS, vol. 67(11), pages 6803-6821, November.
    11. Gérard P. Cachon & Fuqiang Zhang, 2007. "Obtaining Fast Service in a Queueing System via Performance-Based Allocation of Demand," Management Science, INFORMS, vol. 53(3), pages 408-420, March.
    12. Jiaru Bai & Kut C. So & Christopher S. Tang & Xiqun (Michael) Chen & Hai Wang, 2019. "Coordinating Supply and Demand on an On-Demand Service Platform with Impatient Customers," Manufacturing & Service Operations Management, INFORMS, vol. 21(3), pages 556-570, July.
    13. Ghosh, Souvik & Hassin, Refael, 2021. "Inefficiency in stochastic queueing systems with strategic customers," European Journal of Operational Research, Elsevier, vol. 295(1), pages 1-11.
    14. Jacob, Jagan & Roet-Green, Ricky, 2021. "Ride solo or pool: Designing price-service menus for a ride-sharing platform," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1008-1024.
    15. Wang, Haiyan & Olsen, Tava Lennon & Liu, Guiqing, 2018. "Service capacity competition with peak arrivals and delay sensitive customers," Omega, Elsevier, vol. 77(C), pages 80-95.
    16. Ming Hu, 2021. "From the Classics to New Tunes: A Neoclassical View on Sharing Economy and Innovative Marketplaces," Production and Operations Management, Production and Operations Management Society, vol. 30(6), pages 1668-1685, June.
    17. Vasiliki Kostami & Sampath Rajagopalan, 2014. "Speed–Quality Trade-Offs in a Dynamic Model," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 104-118, February.
    18. Qiuping Yu & Gad Allon & Achal Bassamboo & Seyed Iravani, 2018. "Managing Customer Expectations and Priorities in Service Systems," Management Science, INFORMS, vol. 64(8), pages 3942-3970, August.
    19. Manlu Chen & Ming Hu & Jianfu Wang, 2022. "Food Delivery Service and Restaurant: Friend or Foe?," Management Science, INFORMS, vol. 68(9), pages 6539-6551, September.
    20. Benioudakis, Myron & Zissis, Dimitris & Burnetas, Apostolos & Ioannou, George, 2023. "Service provision on an aggregator platform with time-sensitive customers: Pricing strategies and coordination," International Journal of Production Economics, Elsevier, vol. 257(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:popmgt:v:30:y:2021:i:10:p:3599-3614. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1937-5956 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.