ICT R&D and Technology Knowledge Flows in Korea

ICT R&D and Technology Knowledge Flows in Korea

Woo-Jin Jung, Sang-Yong Tom Lee
Copyright: © 2018 |Pages: 19
DOI: 10.4018/JDM.2018100103
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Abstract

This study measured the R&D outcomes of Korea's firms by analyzing the changes and patterns of technology knowledge flows and tried to see whether the outcomes of ICT R&D were better than those of non-ICT R&D. Using the registered patent data from 2008 and 2009, the authors computed the technology cycle time (TCT) and various centrality indexes with social network analysis (SNA), a popular method in patent citation analyses (PCA). In particular, the authors developed a technology spillover network and industry absorption network for the SNA. Having done these analyses, this study additionally conducted a confirmatory statistical test to compare ICT R&D with non-ICT R&D in terms of their performances. The authors found that Korea's ICT R&D has achieved higher levels of technology development speed, technology spillover and industry absorption when compared to non-ICT segments. The authors were also able to determine which particular ICT R&D is in an important position in terms of technology knowledge flows.
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Introduction

It is no secret that the ICT industry has been a principal force behind the economic growth in Korea for the last couple of decades. According to the International Telecommunication Union (ITU)’s ICT development index that is annually announced, Korea has been ranked no lower than first or second since 2010 (https://www.mist.go.kr). However, comparison between ICT R&D and non-ICT R&D in perspective of knowledge flow is yet to be explored.

R&D investment priorities would better be determined based on the nature of knowledge flows and their characteristics such as the centrality and the rapidity. If a certain sector has better knowledge flows (i.e., more strongly and positively affects other sectors), the priority needs to be given to that industry. For that purpose, this study tried to empirically confirm whether ICT R&D would show higher outcomes in perspective of knowledge flow. Also, the authors intended to see which particular ICT industries are in important positions.

The authors measured the outcomes of knowledge acquired from ICT R&D from three perspectives: technology cycle time (TCT) to measure the technology development speed, technology spillover effect, and industry absorption effect with social network analysis (SNA), a popular method in patent citation analyses (PCA). The paper is organized as follows: it began with discussing literature on connections between technology knowledge performances and R&D outcomes. Next, data and methodology, including a description of TCT and various centrality indexes by the SNA, were presented, followed by the results of the findings. Finally, based on the conclusions, a new focus for future research was suggested.

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