Managing Supply in the On-Demand Economy: Flexible Workers, Full-Time Employees, or Both?

Dong, Jing; Ibrahim, Rouba

The rise of the blended workforce, which is identified as one of the top current workplace trends, is prompting firms to reevaluate their staffing strategies. A blended workforce melds as a deliberate business strategy flexible workers (for example, independent contractors or freelancers) with full-time employees. Because flexible workers are free to determine their own work schedules, the supply (total number of workers) is uncertain. In "Managing Supply in the On-Demand Economy: Flexible Workers, Full-Time Employees, or Both?," Dong and Ibrahim examine the optimal staffing strategy for flexible workers and full-time employees to effectively balance operating costs, time variability in customer demands, and supply-side uncertainty while not compromising on the quality of service offered to customers. This work gleans insights on the appropriateness of alternative workforce models, which are especially relevant for the gig economy. There are different workforce models in the "gig" economy. Although some on-demand service providers rely strictly on either traditional employees or independent contractors, others rely on a blended workforce, which melds a layer of contingent workers with a core of permanent employees. In deciding on the "right number of right people to staff at the right time," managers must appropriately weigh the pertinent tradeoffs. In this paper, we study cost-minimizing staffing decisions in service systems where the manager must decide on how many flexible (contractors) and/or fixed (full-time) agents to staff in order to effectively balance operating costs, varying customer demand patterns, and supply-side uncertainty while not compromising on the quality of service offered to customers. We consider a queueing-theoretic framework where the number of servers is random, because part of the workforce is flexible. Because the staffing problem with a random number of servers is analytically intractable, we formulate two problem relaxations based on fluid and stochastic fluid formulations, and we establish their accuracies in large systems by relying on an asymptotic, many-server mode of analysis. We derive the optimal staffing policy and glean insights into the appropriateness of alternative workforce models in on-demand services. We also shed light on the distinction between demand-side (customer arrival rates) and supply-side (number of servers) uncertainties in queueing systems.

CONTINGENT employment; BUSINESS planning; GIG economy; EMPLOYEES; WORKING hours

Operations Research, 2020, Vol 68, Issue 4, p1238

1526-5463

Academic Journal

10.1287/opre.2019.1916