"Flexible contracting with heterogeneous agents and stochastic demand" by Dashi I. Singham, Wenbo Cai et al.
 

Flexible contracting with heterogeneous agents and stochastic demand

Document Type

Article

Publication Date

1-1-2021

Abstract

While the predominant pricing scheme for services is a set of long-term contracts stipulating a fixed fee for a level of usage, many service providers now offer flexible contracts. These contracts include flexibility in usage level and the option to opt out of the service in certain time periods. We study the effectiveness of flexible contracts in aligning the interests between the service provider and the customers in the presence of customers with different discrete demand distributions. This work develops a unified principal–agent framework to examine multiple versions of flexible contracts under ex post information asymmetry. We explore two types of contract variations. The first is aggregated versus differentiated contracts across an agent's random demand values, the second is whether an agent may decline participation in a future time period after committing to a set of contract options. We find that the principal always prefers differentiation to aggregation, and under differentiation prefers to require participation at each time period. However, when demand variability is grouped together under aggregated contracts, we derive a sufficient condition for when is it more profitable to allow the agents the flexibility to opt out of participating in future time periods. Furthermore, the agents’ preference and the overall social utility depends on agents’ value functions and demand distributions. Our study provides insights that help decision makers price their services to better satisfy customers’ varying needs while improving the profitability of the service.

Identifier

85086826036 (Scopus)

Publication Title

International Journal of Production Economics

External Full Text Location

https://doi.org/10.1016/j.ijpe.2020.107840

ISSN

09255273

Volume

231

Grant

CMMI-1535762

Fund Ref

National Science Foundation

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