I feel great. For the past eleven years, I have researched and lived in a wonderful environment in California, but a part of me may have missed my alma mater. I am particularly delighted and grateful to be able to continue my research and interact with students at the Gwanak campus, where I spent much of my 20s studying intensely and enjoying myself.

2. Why did you decide to specialize in strategy?

I majored in economics as an undergraduate student. I liked courses such as Industrial Organization, Public Economics, and Economics of Catch-up because of my interest in the market environment and the laws and policies affecting businesses. I was also active in the Law Economics Society (LES). However, I then thought economics was overly centered on mathematical models and econometrics at that time (which, in retrospect, was partly a misconception on my part) and wanted to study technological innovations in companies through applied econometrics using real-world data. So, I pursued my master’s degree in the Business School, specializing in strategy and international management, and continued my doctoral at UC Berkeley’s Business and Public Policy program, which specializes in strategy and innovation based on economic theories and methodologies.

In terms of research, strategic management is a fascinating field that balances the practical relevance of research topics with the rigor of research methodologies. It is because you analyze actual companies that you can easily encounter every day but employ microdata and econometric methods to analyze the activities and strategies of these companies rigorously. That being said, strategy is a field where there is a considerable difference between what you learn as an undergraduate student and what you research in graduate school. While discussions based on individual case studies are emphasized in the undergraduate program, graduate programs emphasize data analysis for inferring causal relationships. I plan to gradually introduce this type of strategic research to our undergraduate students.

3. It seems you are researching various fields such as price fixing, non-competition, visa, and AI. How are these topics connected, and what are your future research plans?

My research examined how societal policies and systems, such as the Monopoly Regulation and Fair Trade Act, which regulates price fixing, the non-compete clause, which restricts employees from changing jobs between companies, and short- to long-term visa policy, which regulates workers from moving internationally, impact technological innovation in companies. From a broad perspective, they share a common aspect in that one examines how a company’s innovation incentives capabilities change due to various institutional factors.

Price fixing can bring excess profits to companies by artificially raising market prices, but it also reduces consumer welfare and results in social deadweight loss. Price fixing has particularly strong adverse effects in industries that mass-produce standardized products. However, the importance of technological innovation is increasing in contemporary society. As suggested by Schumpeter, the improbability of the market should be somewhat resolved, and financial resources for R&D investment should be guaranteed so that companies can take risks and make long-term investments in technological innovation. From this perspective, I collected all the price-fixing cases detected in the United States over the past 50 years and analyzed the innovative activities of companies before and after the price fixing. The results empirically showed that in fast-growing, technology-intensive industries, price fixing could expedite technological innovation.

While non-compete clauses enable long-term investment in workers, they also limit workers’ freedom to choose jobs. The U.S. federal government recently introduced regulations to limit such clauses, and I was pleased to learn that my paper was cited during this process. This has been somewhat helpful for American workers and businesses. Receiving a thank you letter from the Chair of the Federal Trade Commission was also memorable.

Recently, I have been researching how AI affects workers and organizations. Papers that analyze how professional Go players learn to play after the emergence of AlphaGo, how the effects differ by the players’ nationality, gender, and capacity, and how the standard rules of Go, which have been passed down for centuries, have been reevaluated and changed due to AI, will soon be published. In addition, I am finalizing a paper that uses internal hospital data to analyze how AI technology analyzing chest X-ray images in emergency departments in university hospitals affected patient management, referral requests for specialty care, and improvements in patients’ symptoms.

I plan to continue conducting research that focuses on three pillars—companies, institutions, and technological innovation—that could have implications for companies and society.

As a first-year student, I woke up at 8:50 am when I lived in the now-remodeled dormitory. My lecture started at 9 am at the College of Social Sciences Building No. 16, so I remember grabbing my bag and running and barely making it in time for the class. What I am most grateful for Seoul National University is the fact that this is where I met my wife. I remember spending my free time in the evening going to the university art museum to see exhibits as an excuse to go on dates with her.

5. Do you have any words of advice for Business School students?

The rapid development of AI technology is transforming the qualities of talent that our society seeks. Whereas the ability to understand and acquire given knowledge was valued in the past, it may no longer be as highly regarded in the future. By the time you become the main actor in society, the expertise to evaluate and verify AI-generated outputs, the social skills to communicate and persuade based on this expertise, and the leadership to reconcile conflicts and lead teams will be even more important. Such changes can be a great challenge or opportunity, depending on how we prepare and respond. I hope you can grow the capacities required for the future by actively utilizing various discussion-centered classes and team projects provided by our Business School.

Moreover, as important as equipping yourself with core competencies is finding a career path that will allow you to utilize them effectively. Carefully analyze your strengths and aptitudes in this fast-changing environment, and based on this analysis, strategically set your career path beyond conventional boundaries.

I, too, will dedicate myself to research, share your concerns, and walk this journey with you for your growth and the future of the Business School.

After earning my bachelor’s degree and PhD in physics at KAIST, I conducted cross-disciplinary research at various institutions, including the Santa Fe Institute, Oxford University, MIT Media Lab, and Harvard Kennedy School. Before joining Seoul National University, I worked as a professor at Northwestern University, where I taught and researched complex systems and computational sociology. I am pleased and excited to be able to contribute and share my experience and knowledge here.

2. How did you become interested in strategy as a physics major?

I think strategy is a social science field that takes the most physical approach. I liked science as a child and went to a science high school. I was particularly fascinated by physics because it strives for mathematical precision but, at the same time, drastically revises mathematical theories when they do not fit with reality, which makes it shocking and fascinating at the same time. Such interest led me to study statistical physics, focusing on complex systems and network science. Statistical physics uses the dynamic interactions of microscopic particles, such as atoms and molecules, to explain macroscopic phenomena, such as the volume, pressure, and flow of air or water, and establishes theories based on big data. Through this approach, I could understand the network structures and mechanisms of complex systems, and this formed the basis of my research philosophy that connected my journey from the Department of Physics at KAIST to the Kellogg School of Management at Northwestern University.

However, I have encountered an intriguing challenge. Unlike molecules in physical systems, human society has another concept: strategy. I plan to use data and theories to explore ways to bridge this information gap here at Seoul National University.

First, I understand the change of basis based on the statistical rules and conventional structures identified in big data. By integrating my research findings, I create foundational theories and models of organizational change, which can be used to analyze the strategic choices of individual actors as a probabilistic structure. I would like to go one step further to study how such strategic decision-making affects the organization and society. For example, the strategic choices of individuals can be stochastically assigned by the social and organizational structure. Conversely, we can create models of how individual decisions and behaviors lead to patterns and achievements across organizations. My goal at Seoul National University is to provide strategic solutions to the challenges organizations and society face through such research.

3. You seem to conduct interdisciplinary research across various fields, including mathematics and computer science. What are your research interests and future research plans?

I research various social phenomena, such as interactions between the macroscopic and microscopic worlds. This type of research requires mathematical and computational structuring of phenomena. In other words, a qualitative phenomenon has to be converted into a quantitative one, which calls for cross-disciplinary cooperation among various fields. The mathematical tools used at this point are network theory and scale theory. More recently, I have also been applying machine learning and AI to explain various phenomena in social organizations.

For instance, a city may look like one big structure at the macroscopic level, but microscopically, it is a collection of networks comprising numerous people. If all cities, including Seoul, are converted into microdata of transport infrastructure and road networks, you can model urban expansion as an outcome of interactions between the microscopic and macroscopic world. Network and scale theories can be extremely useful at this point. This approach differs from the traditional approaches of urban science, economics, and sociology that individually study each area. You might feel unfamiliar with this concept because it differs from what you have learned from textbooks, but this is an emerging integrative methodology in complex systems and computational sociology.

Interestingly, this approach can also be applied to innovation research, a field that is also valued in strategy research. In the end, large technological trends emerge at the micro level through the combination and relationships between individuals and ideas so that they can be modeled, and new combinations can be predicted using machine learning and AI. In the same way, this can be applied to the study of social norms, superstitions, and collective intelligence. I have been focusing on developing such predictive models when I found myself questioning the “significance of predicting innovation that creates something out of nothing.” This led me to collaborate with mathematicians and computer scientists to use spatial concepts to interpret probabilistic predictions. I am trying to understand the rules, predictions found in data, and the changes in possibility and probability as spatial concepts. This is also related to the LLM algorithm, which has recently received much attention.

Exploring a new field and finding new insights is exciting and enjoyable, much like solving a complex puzzle. The joy of using physical, mathematical, and computational tools to identify the rules and universal meaning of various social phenomena, such as the city, organizations, innovation, creativity, success, superstitions, and language recognition, is incomparable, much like fitting in the last piece in a puzzle. Of course, not all attempts can be successful. Unlike the physical system, humans and society are immensely complex and cannot be explained using a single theory. This is why it is called a complex system. Nevertheless, I believe that such adventurous attempts deepen our understanding of society.

4. Do you have any goals you hope to achieve at the Seoul National University Business School?

Coming to Seoul National University after living abroad for a long time is a great challenge and a new opportunity in my academic journey. As shown in research on collective intelligence, I am excited to see how my unique background knowledge and methodology would create synergy with the excellent community here. There are so many things I would like to do with you all. I look forward to collaborating with my esteemed colleagues to explore new methodologies beyond traditional business management and push the boundaries between academic disciplines.

Recent advancements in data, platforms, machine learning, and AI technology have transformed our lives and society. Such changes call for new knowledge and mindsets, and my field, computational social science, is at the center of that change. With you, I want to reflect on these changes in my research and teaching so that business management studies can evolve with the times.

5. Do you have any words of advice for Business School students?

I encourage students to truly enjoy delving into their intellectual curiosities. This experience will empower them to take any threats from disruptive technologies as positive challenges that can be turned into their own opportunities for success. I hope students can cherish and enjoy this once-in-a-lifetime privilege of being a student to the fullest.

We now face an unprecedented era of changes. A vast amount of data on social phenomena is accumulating, and the computing power to process this is also explosively increasing, following Moore’s Law. Data generates even more data, which requires more intricate algorithms and higher computing capacity. This, in turn, leads to unprecedented advances in algorithms, including machine learning and AI.

Such technological advances present you with infinite possibilities. Unlike in the past, we can now make precise observations about reality and predict the future, and we can conduct in-depth analyses of a wide range of data to gain insights into complex social issues. New business models, strategies, and organizational management methods are emerging, enabling innovative approaches in sociology and management, such as computational sociology. I feel fortunate to study and research business management at this time of great change.

Personally, I think this period can be a watershed as well as an opportunity for us to expand the horizon of business management and develop new methodologies. I hope to identify meaningful rules in this endless stream of data and develop the mindsets and analytical skills to better understand this world with you at the Seoul National University Business School.