Incentive Design

Mechanism design and game theory for e-commerce platforms, team formation, and kidney exchange — aligning individual incentives with collective outcomes.

Incentive Design

Incentive Design

Mechanism design and game theory that aligns selfish behavior with collective outcomes — in e-commerce, team formation, and kidney exchange.

Rational agents pursue their own interests — but well-designed rules can make selfish behavior lead to good collective outcomes. We apply mechanism design and game theory to build systems where honesty and cooperation are the optimal strategy, from e-commerce to organ donation.

Research Areas

  • Strategic Information Disclosure in E-Commerce — Disclosure mechanisms that improve buyer decisions and platform welfare simultaneously on platforms like Amazon, without sacrificing honesty or profit.
  • Strategy-Proof Team Formation — Mechanisms where truth-telling about skills is the dominant strategy, guaranteeing effective team composition even when participants have incentives to misreport.
  • Kidney Exchange Optimization — Credit-based incentive systems for paired donation programs that prevent strategic withholding of compatible pairs, increasing overall transplant rates while preserving fairness.

Technical Approach

Our work combines classical mechanism design theory (VCG, strategyproofness, incentive compatibility) with computational methods — simulations, algorithmic game theory, and empirical behavioral analysis. Each mechanism comes with formal proofs and is validated against real-world platform data.

Impact

The information disclosure mechanisms have been implemented in real e-commerce settings. Kidney exchange work contributes to national transplant policy discussions. Team formation mechanisms are deployed in organizational settings involving thousands of participants.

Related Publications

2017

  1. Enhancing Comparison Shopping Agents Through Ordering and Gradual Information Disclosure
    2017
    Chen Hajaj, Noam Hazon, and David Sarne
    Autonomous Agents and Multi-Agent Systems
  2. Selective Opportunity Disclosure at the Service of Strategic Information Platforms
    2017
    Chen Hajaj, and David Sarne
    Autonomous Agents and Multi-Agent Systems
  3. Enhancing Crowdworkers’ Vigilance
    2017
    Avshalom Elmalech, David Sarne, Esther David, and Chen Hajaj
    Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17)

2016

  1. Extending Workers’ Attention Span Through Dummy Events
    2016
    Avshalom Elmalech, David Sarne, Esther David, and Chen Hajaj
    Proceedings of the AAAI Conference on Human Computation and Crowdsourcing

2015

  1. Improving Comparison Shopping Agents’ Competence Through Selective Price Disclosure
    2015
    Chen Hajaj, Noam Hazon, and David Sarne
    Electronic Commerce Research and Applications
  2. Strategy-Proof and Efficient Kidney Exchange Using a Credit Mechanism
    2015
    Chen Hajaj, John P Dickerson, Avinatan Hassidim, Tuomas Sandholm, and David Sarne
    In proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence

2014

  1. Advanced Service Schemes for a Self-Interested Information Platform
    2014
    Chen Hajaj, David Sarne, and Lea Perets
    Proceedings of the 2014 international conference on Autonomous agents and multi-agent systems
  2. Ordering Effects and Belief Adjustment in the Use of Comparison Shopping Agents
    2014
    Chen Hajaj, Noam Hazon, and David Sarne
    Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2014)
  3. Strategic Information Platforms: Selective Disclosure and the Price of Free
    2014
    Chen Hajaj, and David Sarne
    Proceedings of the Fifteenth ACM conference on Economics and Computation

2013

  1. Search More, Disclose Less
    2013
    Chen Hajaj, Noam Hazon, David Sarne, and Avshalom Elmalech
    In proceedings of the Twenty-Seventh AAAI Conference on Artificial Intelligence