Research Interest

I mainly write theoretical papers on the rational design of digital organizing. IT artifacts that may alter our understanding of organizational intelligence are of particular interest. Methodologically, I use a combination of computational modeling, simulation, and econometric analysis. My work is organized around three connected streams.

1. Decentralized Organizational Design with Blockchain Technology (i.e., Regime)
   Investigating how distributed ledgers and smart contracts enable new governance regimes and reconfigure coordination in organizations.
2. Managing Wisdom of Crowds in Crowdsourcing (i.e., Human Component)
   Exploring how digital platforms can harness human diversity and judgment, and under what conditions crowd wisdom exceeds the sum of individual pearls.
3. Managing Wisdom of AI in Organizational Rationality (i.e., Machine Component)
   Examining the integration of algorithmic agents into organizational decision-making, and the implications for bounded rationality, learning, and search.

Conference Papers

Li, J., Zhou, J., and Hahn, J. (2024). Loosely Coupled Search in Crowd-based Innovation: A Simulation-based Theory Development. Conference on Information Systems and Technology, 2024.

Li, J., Zhou, J., and Hahn, J. (2024). Faceted Search and Crowd-based Innovation. Academy of Management Proceedings, 2024(1), 10095.

Li, J., Hahn, J., and Tayi, G. K. (2023). Meta-Organizational Learning Through Digital Consensus. International Conference of Information Systems Proceedings, Hyderabad, India. Available at: https://aisel.aisnet.org/icis2023/blockchain/blockchain/16/

Li, J., Zhou, J., and Hahn, J. (2023). Solving Problem with Generalists and Specialists: An Agent-based Simulation Model. Academy of Management Proceedings, 2023(1), 13364.