Title
Task Allocation and On-the-job Training
Author(s)
Mariagiovanna Baccara Mariagiovanna Baccara (Washington University in St. Louis)
SangMok Lee SangMok Lee (Washington University in St. Louis)
Leeat Yariv Leeat Yariv (Princeton University)
Abstract
We study dynamic task allocation when service providers' expertise evolves. Clients arrive sequentially seeking service. Seniors provide superior service but entail waiting in a queue, which progresses at a speed dependent on their volume. Juniors o§er service without wait and become seniors with experience. We show that clients choose senior service too frequently, generating longer waits and little training relative to the social optimum. Welfare gains from centralization are greater for larger institutions, better training technologies, and lower waiting costs. Finally, monitoring the seniors' queue increases welfare but may decrease training. Methodologically, we explore a matching setting in which agents' types are endogenous, and illustrate the usefulness of queuing theory techniques.
Creation Date
2020-10
Section URL ID
Paper Number
270
URL
http://lyariv.mycpanel.princeton.edu//papers/TaskAllocation.pdf
File Function
Jel
J22
Keyword(s)
Dynamic Matching, Training-by-Doing, Market Design
Suppress
false
Series
3