Investigating Company’s Technical Development Directions Based on Internal Knowledge Inheritance and Inventor Capabilities: The Case of Samsung Electronics

Fang Han, Sejun Yoon, Nagarajan Raghavan and Hyunseok Park
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Fang Han: National Science Library, Chinese Academy of Sciences, Beijing 100190, China
Sejun Yoon: Department of Information Systems, Hanyang University, Seoul 04763, Korea
Nagarajan Raghavan: Engineering Product Development Pillar, Singapore University of Technology and Design, Singapore 487372, Singapore
Hyunseok Park: Department of Information Systems, Hanyang University, Seoul 04763, Korea

Sustainability, 2022, vol. 14, issue 5, 1-19

Abstract: This paper proposes a new method to analyze technical development directions of a company using knowledge persistence-based main path analysis and co-inventor network analysis. Main path analysis is used for identifying internal technical knowledge flows and inheritances over time within a company, and knowledge persistence-based main path analysis can well identify major knowledge streams of each sub-domain within a relatively small knowledge network generated by one company without omission of significant inventions. A co-inventor network analysis is used for identifying key inventors who can be represented as the major technical capabilities of a company. The method is a meaningful attempt in that it applies knowledge persistence-based main path analysis to analyzing a company’s internal technical development and combines the two approaches to provide the information on both base technical capabilities and new technical characteristics. To test the method, this paper conducted an empirical study of Samsung Electronics. The results show that the method generated major knowledge flows and identified key inventors of Samsung Electronics. In particular, the method can identify the base technical knowledge as the ‘backbone’ and newly injected knowledge as ‘fresh blood’ for forecasting future technical development. Based on the identified clue information, this paper forecasted the potential future technologies for each sub-domain of Samsung Electronics with technical keywords and descriptions.

Keywords: knowledge persistence; main path analysis; social network analysis; corporate technology strategy; technology forecasting (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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