Operations in the On-Demand Economy: Staffing Services with Self-Scheduling Capacity

  • Itai GurvichEmail author
  • Martin Lariviere
  • Antonio Moreno
Part of the Springer Series in Supply Chain Management book series (SSSCM, volume 6)


Motivated by recent innovations in service delivery such as ride-sharing services and work-from-home call centers, we study capacity management when workers self-schedule. Our service provider chooses capacity to maximize its profit (revenue from served customers minus capacity costs) over a horizon. Because demand varies over the horizon, the provider benefits from flexibility to adjust its capacity from period to period. However, the firm controls its capacity only indirectly through compensation. The agents have the flexibility to choose when they will or will not work and they optimize their schedules based on the compensation offered and their individual availability. To guarantee adequate capacity, the firm must offer sufficiently high compensation. An augmented newsvendor formula captures the tradeoffs for the firm and the agents. If the firm could keep the flexibility but summon as many agents as it wants (i.e., have direct control) for the same wages it would not only generate higher profit, as is expected, but would also provide better service levels to its customers. If the agents require a “minimum wage” to remain in the agent pool they will have to relinquish some of their flexibility. To pay a minimum wage the firm must restrict the number of agents that can work in some time intervals. The costs to the firm are countered by the self-scheduling firm’s flexibility to match supply to varying demand. If the pool of agents is sufficiently large relative to peak demand, the firm earns more than it would if it had control of agents’ schedules but had to maintain a fixed staffing level over the horizon.


  1. Allon G, Bassamboo A, Çil E (2012) Large-scale service marketplaces: the role of the moderating firm. Manag Sci 58(10):1854–1872CrossRefGoogle Scholar
  2. Bassamboo A, Randhawa R, Zeevi A (2010) Capacity sizing under parameter uncertainty: safety staffing principles revisited. Manag Sci 56(10):1668–1686CrossRefGoogle Scholar
  3. Bergstrom T, Bagnoli M (2005) Log-concave probability and its applications. Econ Theory 26:445–469CrossRefGoogle Scholar
  4. Cachon G, Daniels K, Lobel R (2017) The role of surge pricing on a service platform with self-scheduling capacity. Manuf Serv Oper Manag 19(3):368–384CrossRefGoogle Scholar
  5. Campbell H (2015) Delivering for doordash: what was my doordash orientation like? The ride share guy Accessed 22 Feb 2018
  6. Hall J, Krueger A (2016) An analysis of the labor market for Uber’s driver-partners in the United States. National Bureau of Economic Research. Working paper No. 22843Google Scholar
  7. Ibrahim R (2018) Managing queueing systems where capacity is random and customers are impatient. Prod Oper Manag 27(2):234–250CrossRefGoogle Scholar
  8. Kalanick T (2012) Surge pricing follow up. Accessed 12 Jan 2012
  9. Kirsner S (2014) What happened when Boloco founder John Pepper became an Uber driver. Accessed 22 Feb 2018
  10. Laffont J, Martimort D (2009) The theory of incentives: the principal-agent model. Princeton and Oxford University Press, Princeton/OxfordCrossRefGoogle Scholar
  11. Levine D, McBride S (2015) Uber, Lyft face crucial courtroom test over driver benefits. Reuters Accessed 22 Feb 2018Google Scholar
  12. Moreno A, Terwiesch C (2015) Doing business with strangers: reputation in online service marketplaces. Inf Syst Res 25(4):865–886CrossRefGoogle Scholar
  13. Netessine S, Yakubovich V (2012) The Darwinian workplace. Harv Bus Rev 90(5):25Google Scholar
  14. Petruzzi N, Dada M (1999) Pricing and the newsvendor problem: a review with extensions. Oper Res 47(2):183–194CrossRefGoogle Scholar
  15. Riquelme C, Banerjee S, Johari R (2015) Pricing in ride-share platforms: a queueing-theoretic approach. SSRN Working paper, Accessed 22 Feb 2018Google Scholar
  16. Salanie B (1997) The economics of contracts: a primer. The MIT Press, CambridgeGoogle Scholar
  17. Stouras K, Girotra K, Netessine S (2016) First ranked first to serve: strategic agents in a service contest. INSEAD. Working paperGoogle Scholar
  18. Taylor T (2018) On-demand service platforms. Manufacturing and service operations management. Published online: 23 July 2018. CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Itai Gurvich
    • 1
    Email author
  • Martin Lariviere
    • 2
  • Antonio Moreno
    • 3
  1. 1.Cornell TechNew YorkUSA
  2. 2.Kellogg School of ManagementEvanstonUSA
  3. 3.Harvard Business SchoolBostonUSA

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