Profit or Growth? Dynamic Order Allocation in a Hybrid Workforce

Eryn Juan He () and Joel Goh ()
Additional contact information
Eryn Juan He: Institute of Operations Research and Analytics, National University of Singapore, Singapore 117602
Joel Goh: Department of Analytics and Operations, NUS Business School, Singapore 119245, Singapore; NUS Global Asia Institute, National University of Singapore, Singapore 119076, Singapore; Harvard Business School, Boston, Massachusetts 02163

Management Science, 2022, vol. 68, issue 8, 5891-5906

Abstract: Modern digital technology has enabled the emergence of the hybrid workforce in service organizations, where a firm uses on-demand freelancers to augment its traditional labor supply of employees. Freelancers are typically supplied by an electronic platform. How should demand be allocated between employees and freelancers? Under what conditions is the system (comprising the firm and its platform) sustainable in the long run? We investigate these questions in the context of last-mile delivery. We develop a discrete-time, stochastic dynamic program that captures the system’s profit from serving demand and the platform’s growth dynamics. The dynamic model incorporates a service constraint for the platform and a simple version of a stochastic network effect. We find that the answers to our research questions critically depend on two key parameters: the mean and variance of the cross-network effect . We conduct a numerical study with data from a last-mile delivery firm in Vietnam to illustrate our findings.

Keywords: on-demand platform; market thickness; cross-network effects; dynamic order allocation (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://dx.doi.org/10.1287/mnsc.2021.4177 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:ormnsc:v:68:y:2022:i:8:p:5891-5906

Access Statistics for this article

More articles in Management Science from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().