2) Barney, J. B., Types of Competition and the Theory of Strategy: Toward an Integrative Framework. Academy of Management Review, 11(4), 791-800 (1986).https://doi.org/10.2307/258397 3) Mizukami, Y., Honda, K. & Nakano, J., Study on research trends on the Internet of things using network analysis. International Journal of Japan Association for Management Systems, 10(1), 27-35 (2018).https://doi.org/10.14790/ijams.10.27 4) Mizukami, Y., & Nakano, J., Using the Academic Literature Database to Evaluate the International Interdisciplinary Fusion in IoT Research Through Coauthor Analysis. Proceedings of the Institute of Statistical Mathematics, 68(2), 265-285 (2020). (in Japanese).─ 14 ─of these disciplines as innovation. This study examines how each country is promoting research from the perspective of innovation. The analysis method includes measuring the “intrapersonal diversity” of Schumpeterian competition, which is an innovation strategy in Barney’s three major types of interorganizational competition. Intrapersonal diversity is evaluated as an organization’s competitiveness (in this study, a country/region) by accumulating intrapersonal diversity. For example, in Region A, if the disciplines of clinical medicine and computer science are strongly connected (many researchers are involved in research in both disciplines), the knowledge of these disciplines will be combined. In this case, it is likely that new value (knowledge) is created by fusing the knowledge of these disciplines.The reader may wonder why this study did not focus on the development of each field instead of innovation-type development. These are the ideas of IO-type and Chamberlain-type competition in Barney’s three major interorganizational competitions. However, both are suited to industries where the business environment is fairly stable and the future is reasonably foreseeable. However, the current business environment may be different. Globalization, deregulation, and, above all, rapid development and digitization of IT have accelerated change in the business environment. D’aveni (1994) refers to this environment as “hypercompetition,” meaning that the type of competition is adapting to the Schumpeterian model14). This study attempts to gain knowledge on competitive strategies that are appropriate for this hypercompetitive economic situation.This study categorized the styles of cross-disciplinary fusion into three patterns in big data. Group 1 comprised India, China, and South Korea, with a complete network of chemistry, clinical medicine, and engineering (3‒4‒7). Group 2 included Spain, Australia, and Italy, with a strong network of biology and biochemistry, and environment/ecology (2‒8). Group 3 consisted of Canada, Germany, the United States, and England, with a strong network of clinical medicine, and molecular biology & genetics (4‒14). These are considered to be the forms of innovation of those groups.To summarize the results of this study, in Big Data-related research, Europe and the U. S. are considered to be advancing research that comprehensively combines biological knowledge, while Asia is advancing research that combines scientific and engineering knowledge, with a focus on clinical medicine. In addition, since there are no unexpected connections among the three groups, the results suggest that there is a strong tendency toward the deepening of knowledge.The limitations of this study and directions for future research are discussed. The style of cross-disciplinary fusion presented in this paper is to examine patterns of connections among currently mainstream research fields and to discuss the exploration of knowledge and the exploitation of knowledge based on the specificity of these patterns. On the other hand, since the exploration of knowledge is a new endeavor, there could be a viewpoint of classifying knowledge by patterns focusing on weak connections and discussing the exploration of knowledge. A possible direction for future research is to discuss the exploration of knowledge by classifying by patterns focusing on weak connections.This research is a project of the Interdisciplinary Innovation Research Group, College of Industrial Technology, Nihon University. This work was supported by JSPS KAKENHI Grant Number 17K04710.1) March, J. G., Exploration and Exploitation in Organizational Learning. Organization Science, 2(1), 71-87 (1991).https://doi.org/10.1287/orsc.2.1.715) Chesbrough, H., Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business School Publishing (2003).6) Rothaermel, F. T. & Alexandre, M. T., Ambidexterity in Technology Sourcing: The Moderating Role of Absorptive Capacity. Organization Science, 20(4), 759-780 (2009).https://doi.org/10.1287/orsc.1080.0404AcknowledgmentsReferences
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