Working Papers:

Aspiration Formation and Adaptation  (with Lusi Yang, David W. Lehman, and Jungpil Hahn)

• Firms set goals on a monthly, quarterly, or yearly basis, what if they need to set goals for projects that occur sporadically?  This study extends our understanding of how goals are determined in such contexts. 

The Dynamics of Agentizing Routines  (with Yifei Wei, and Jungpil Hahn)

• Organizational routines are increasingly performed through agentic workflows. Despite strong task-level performance in prototypes and bounded environments, organizations often struggle to convert local gains into organizational performance. We develop a theory of agentizing organizational routines that integrates routine dynamics and task interdependency perspectives.

Structural Pitfalls in Algorithmic Decision Making  (with Jungpil Hahn)

• Decision makers make both Type I and Type II errors when evaluating algorithmic advice. This study examines the effectiveness of decision structures in shaping how human and algorithmic inputs are generated, evaluated, and aggregated into organizational decisions.

AI Adoption and Organizational Restructuring (with Seongjin Kim, and Jungpil Hahn)

• Enterprise AI can improve individual productivity while degrading organizational capability by substituting for human-to-human knowledge transactions. We examine how enterprise AI weakens the emergent knowledge structures on which communication, coordination, and expertise depend within a global manufacturer.

Red Queen Race: Coevolution with AI  (with Jungpil Hahn)

• What happens when AI can be leveraged by all firms within an industry? Our analysis reveals a Red Queen race in which firms are compelled to use AI to improve immediate performance, yet this competition ultimately leads to a lose-lose situation over time.

The Cave: A Systems Investigation of Crowdsourcing Effectiveness  (with Jungpil Hahn)

• Crowdsourcing helps firms discover high-quality solutions, but what constitutes "high quality" is defined by the firm -- one that has a limited knowledge base and therefore turns to crowdsourcing. This study helps firms escape the cave of crowdsourcing.  

Anticipating the Unintended Outcomes of Algorithmic Coordination in Digital Platforms  (with Jonas Andersen, Christoph Mueller-bloch, and Jungpil Hahn)

• Algorithmic matching can generate emergent, system-level outcomes through mismatches and subsequent adaptation. Drawing on complex adaptive systems theory, we develop a multilevel framework showing how feedback across users, platforms, and ecosystems produces dynamic and path-dependent outcomes over time.

Publication:

Organizing for Software Product Development: The Effects of Team Structure, Product Complexity, and Cross-Team Coordination (with Jungpil Hahn, Gwanhoo Lee, and Vasilii Zorin)

• How you structure your teams matters just as much as how you write your code. This study offers theoretical insights into designing teams for optimal performance under varying levels of problem complexity. 

Make the Crowd Wiser: (Re)combination through Teaming in Crowdsourcing (with Jungpil Hahn)

• Teams are expected to outperform individual solvers in problem solving, but what if team formation also shifts the overall distribution of solutions?  This study examines the impact of forming teams on the likelihood of discovering extreme-value outcomes in crowdsourcing.