Analysis of Market Diversification Trends and Network Characteristics Based on M&A Transactions in North America

Jinho Choi; Nina Shin; Chongho Pyo; Jukyeong Kwak; Changheon Nam

doi:10.5755/j01.ee.35.4.31671

Authors

Jinho Choi College of Business and Economics, Sejong University, Republic of Korea
Nina Shin College of Business and Economics, Sejong University, Republic of Korea
Chongho Pyo Desautels Faculty of Management, McGill University, Canada
Jukyeong Kwak College of Business, Korea Advanced Institute of Science and Technology, Republic of Korea
Changheon Nam College of Business and Economics, Sejong University, Republic of Korea

DOI:

https://doi.org/10.5755/j01.ee.35.4.31671

Keywords:

Mergers and Acquisitions (M&A), Market diversification, Convergence, Complex network, Network analysis

Abstract

Despite the increasing investment opportunities in emerging technologies, strategic alliance and dynamic investment strategy suffer from a limited understanding of the market investment trends and industry convergence. Therefore, this study aims to develop a structured framework to examine the market diversification trend and the industry-to-industry influential degree. The proposed framework utilizes M&A transaction activities from the interests of buyer and target industries from 2009 to 2018 in North America. The M&A network is then examined for the difference in the structural characteristics between the buyer and target industries. This study identifies market irregularity and diversification trends and applies the initial findings as market-level evidence to elucidate industry convergence potentials. Degrees of a specific industry’s influence on other industries are also presented and discussed from the perspectives of buyer and target industries. The findings of this study contribute to the development of industry convergence conceptual model and advances knowledge regarding market diversification, collaboration-driven industry convergence, and investment strategy.

Author Biographies

Jinho Choi, College of Business and Economics, Sejong University, Republic of Korea

Jinho Choi is a professor at the School of Business, Sejong University. He holds B.S. in Industrial Management and Industrial Design and M.S. and Ph.D. in Management Engineering from the Korea Advanced Institute of Science and Technology (KAIST). His research interests include technology forecasting, knowledge evolution and management, and business analytics. He has published in leading academic journals such as OMEGA, Information & Management, Scientometrics, Technological Forecasting, and Social Change, Computers in Human Behavior, Journal of Computer Information Systems, and Expert Systems with Applications.

Nina Shin, College of Business and Economics, Sejong University, Republic of Korea

Nina Shin is an associate professor at the Sejong University, Seoul, South Korea. She holds a B.S. degree in Industrial Engineering from the University of Washington, an M.E. degree in Operations Research and Information Engineering from Cornell University, and a Ph.D degree from Seoul National University. Her main research interests are sustainable operations and supply chain management. Her recent projects were on socially responsible partnerships, innovative technologies for service systems, and supply network resilience.

Chongho Pyo, Desautels Faculty of Management, McGill University, Canada

Chongho Pyo is a graduate student at McGill University, majoring in the Master of Management in Analytics. He earned his bachelor’s degree in Business Administration and Computer Science and Engineering from Sejong University. He worked as a research assistant at the Biz Intelligence Institute, Sejong University, and has practical experience as a recommender system developer and analytics engineer. His research interests cover data science, geospatial data analytics, and machine learning.

Jukyeong Kwak, College of Business, Korea Advanced Institute of Science and Technology, Republic of Korea

Jukyeong Kwak is a graduate student at Korea Advanced Institute of Science and Technology (KAIST), majoring in Management Engineering. She worked as a research assistant at the Biz Intelligence Institute, Sejong University, assisting the development of advanced decision making methodologies for this study. She double majored in Business Administration and in Business Analytics as an undergraduate. Her research interests include business analytics, machine learning, and operations management.

Changheon Nam, College of Business and Economics, Sejong University, Republic of Korea

Changheon Nam worked as a research assistant at Biz Intelligence Institute and majored in Business Administration and Business intelligence at Sejong University. He is interested in data processing and artificial intelligence for financial or social data. His research focuses on making risk measurements and predicting statistical figures. He has published a journal to the Korea Society of Information Technology Applications (KITA).