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Optimal monitoring schedule in dynamic contracts

Publication ,  Journal Article
Chen, M; Sun, P; Xiao, Y
Published in: Operations Research
September 1, 2020

Consider a setting in which a principal induces effort from an agent to reduce the arrival rate of a Poisson process of adverse events. The effort is costly to the agent and unobservable to the principal unless the principal is monitoring the agent. Monitoring ensures effort but is costly to the principal. The optimal contract involves monetary payments and monitoring sessions that depend on past arrival times. We formulate the problem as a stochastic optimal control model and solve the problem analytically. The optimal schedules of payment and monitoring demonstrate different structures depending on model parameters. Overall, the optimal dynamic contracts are simple to describe, easy to compute and implement, and intuitive to explain.

Duke Scholars

Published In

Operations Research

DOI

EISSN

1526-5463

ISSN

0030-364X

Publication Date

September 1, 2020

Volume

68

Issue

5

Start / End Page

1285 / 1314

Related Subject Headings

  • Operations Research
  • 3507 Strategy, management and organisational behaviour
  • 1503 Business and Management
  • 0802 Computation Theory and Mathematics
  • 0102 Applied Mathematics
 

Citation

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MLA
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Chen, M., Sun, P., & Xiao, Y. (2020). Optimal monitoring schedule in dynamic contracts. Operations Research, 68(5), 1285–1314. https://doi.org/10.1287/opre.2019.1968
Chen, M., P. Sun, and Y. Xiao. “Optimal monitoring schedule in dynamic contracts.” Operations Research 68, no. 5 (September 1, 2020): 1285–1314. https://doi.org/10.1287/opre.2019.1968.
Chen M, Sun P, Xiao Y. Optimal monitoring schedule in dynamic contracts. Operations Research. 2020 Sep 1;68(5):1285–314.
Chen, M., et al. “Optimal monitoring schedule in dynamic contracts.” Operations Research, vol. 68, no. 5, Sept. 2020, pp. 1285–314. Scopus, doi:10.1287/opre.2019.1968.
Chen M, Sun P, Xiao Y. Optimal monitoring schedule in dynamic contracts. Operations Research. 2020 Sep 1;68(5):1285–1314.

Published In

Operations Research

DOI

EISSN

1526-5463

ISSN

0030-364X

Publication Date

September 1, 2020

Volume

68

Issue

5

Start / End Page

1285 / 1314

Related Subject Headings

  • Operations Research
  • 3507 Strategy, management and organisational behaviour
  • 1503 Business and Management
  • 0802 Computation Theory and Mathematics
  • 0102 Applied Mathematics