Information Asymmetries in Sustainable Operations: Incentivizing Agents with Hidden Rewards

This talk highlights a grand challenge in advancing sustainability analytics for operations management: tackling information asymmetries through integrated data- driven incentive structures and environmental monitoring. Towards this challenge, the talk explores an unexplored information asymmetry scenario prevalent in contexts such as forest conservation contracts in payment for ecosystem services (PES) and utility-aggregator contracts for renewable energy integration. In this scenario, an incentivizing principal solely watches the actions of an incentivized selfish learning agent while remaining uninformed about the agent's rewards. We propose a robust data-driven incentive design framework, at the interface of online learning and repeated principal-agent games, that jointly addresses: i) the consistent estimation of the agent's rewards, and ii) the provision of adaptive, low-regret incentives to lead the agent.

Short Bio

Ilgin Dogan is currently completing her Ph.D. studies in Industrial Engineering and Operations Research at the University of California, Berkeley. Prior to joining Berkeley, she earned B.S. and M.S. degrees in Industrial Engineering from the Middle East Technical University. During her graduate studies, she gained industry experience in data science and advanced analytics teams with leading technology and supply chain companies, such as Apple and Meta. Her research specializes in designing stochastic models and computational algorithms for data-driven and sustainable operations management. She is particularly interested in incentive design to navigate information asymmetries among strategic agents, with a focus on applications in environmental sustainability analytics.


Middle East Technical University
Department of Industrial Engineering Seminar
Friday, March 1, 2024, 4:00 pm


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