Daniel Yue, assistant professor of IT Management at the Scheller College of Business, has been awarded the prestigious Best Dissertation Award by the Technology and Innovation Management Division of the Academy of Management. The recognition celebrates the most impactful doctoral research in the field of business and innovation.
Yue’s dissertation, developed during his Ph.D. at Harvard Business School, explores a paradox at the heart of the AI industry: why do firms openly share their innovations, like scientific knowledge, software, and models, despite the apparent lack of direct financial return? His work sheds light on the strategic and economic mechanisms that drive this openness, offering new frameworks for understanding how firms contribute to and benefit from shared technological progress.
“We typically think of firms as trying to capture value from their innovations,” Yue explained. “But in AI, we see companies freely publishing research and releasing open-source software. My dissertation investigates why this happens and what firms gain from it.”
Yue’s research spans a series of papers, each examining a different facet of firm openness in the AI sector. His job market paper, “I, Google: Estimating the Impact of Corporate Involvement on AI Research,” introduces the concept of knowledge spillback. Spillback occurs when firms benefit from the broader ecosystem’s use of their shared knowledge, which in turn enhances their own operations.
Another paper, titled “Igniting Innovation: Evidence from PyTorch on Technology Control in Open Collaboration,” is Yue’s effort to formalize what tech leaders mean when they vaguely say they want to “control their destiny” by contributing to open-source projects. They do not own the software since it is publicly available, but companies can still exert control through strategic contributions that influence governance standards and what features get built.
“I’ve been thinking about this topic for over four years,” Yue said. “It’s been incredible to see how the rise of AI has made these questions more urgent and economically relevant.”
Yue hopes his work will empower managers to make informed decisions about openness and encourage more firms to contribute to shared technology innovation. He also sees broader implications for scholars as they continue to navigate an evolving understanding of how technology innovation occurs, including the development of practical frameworks that guide companies in deciding when and how to share emerging technologies.
“Each generation studies its own technology,” Yue noted. “I hope this research helps build a more complete story of how innovation works in today’s economy.”
Yue’s dissertation is currently under journal review. In the meantime, his work continues to influence both academic and industry conversations around AI, openness, and innovation strategy.
