Incentive Design

Mechanism design for strategic decision-making in networks and crowdsourcing

Incentive Design

Mechanism design for strategic decision-making in networks and crowdsourcing

How do you design systems where selfish behavior leads to good outcomes? Through mechanism design—creating rules and incentives that align individual interests with collective goals. We develop strategies for e-commerce, team formation, and healthcare allocation.

Research Areas

E-commerce Platforms

Strategic information disclosure that helps buyers make better decisions while balancing platform profits and user welfare.

Team Formation

Strategy-proof mechanisms that make honesty the best policy. Form effective teams even when people might misreport skills.

Kidney Exchange

Credit-based systems preventing manipulation. Increase transplant efficiency while ensuring fairness.

Technical Approach

Mechanism Design Theory

Applying game theory and economic theory to design systems where truth-telling is the optimal strategy. Mathematical proofs of strategy-proofness and efficiency.

Strategic Intelligence

Understanding how information revelation affects decision-making. Timing and sequencing of information to improve outcomes.

Fairness and Efficiency

Balancing individual incentives with collective welfare. Ensuring systems are both efficient and fair.

Applications

Digital Platforms

E-commerce platforms implementing strategic information disclosure. Team formation systems for organizations.

Healthcare

Kidney exchange programs in hospital systems. Medical resource allocation mechanisms.

General Markets

Any system requiring coordination among self-interested parties. Applications in AI agent negotiations and blockchain consensus mechanisms.

Impact

Our research contributes to the design of digital platforms and healthcare systems. The work includes mechanisms implemented in real e-commerce platforms and kidney exchange programs, affecting millions of transactions and improving organ transplant outcomes.

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