Internalization of R&D outsourcing: An empirical study

Sang Yun Han, Sung Joo Bae

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


From the absorptive capacity perspective, this study investigates the extent to which a firm that uses external knowledge attained through R&D outsourcing can increase its performance, and how this effect is moderated by a firm's absorptive capacity via internal R&D efforts and organizational composition of the firm's R&D division. More specifically, we use R&D intensity, a traditional measure of absorptive capacity, and five variables of organizational composition to measure their moderating effect between R&D outsourcing effort and the firm's resulting performance. We use a fixed-effect model to analyze panel data from 19,570 Korean manufacturing firms between 2002 and 2007. Our findings show that the intensity of R&D outsourcing in high technology industries has a direct and positive effect on a firm's performance. We also identify the differences between high- and medium/low-technology industries and analyze how having an R&D staff of highly skilled researchers can moderate the effect of R&D outsourcing on a firm's performance. We find that for high-technology industries, R&D outsourcing is strongly associated with a firm's positive performance when the ratio of researchers with Ph.D. degrees in R&D organization is high. However, in low-technology industries, our study indicates that while the ratio of researchers in R&D to R&D staff has a direct effect on firm performance, it does not actually moderate the effect of R&D outsourcing on firm performance. We provide an interpretation of these empirical findings, emphasizing the importance of a firm's absorptive capacity via organizational composition of the R&D division in maximizing R&D outsourcing results.

Original languageEnglish
Pages (from-to)58-73
Number of pages16
JournalInternational Journal of Production Economics
Publication statusPublished - 2014 Apr

Bibliographical note

Funding Information:
We used a firm-level merged data set composed of financial data from the Korea Investors Service (KIS) and the R&D Survey in Science and Technology. We used firm identifying numbers for merging these two data sets. KIS is financial information service for Korean firms. We utilized data from the Korean Ministry of Education, Science and Technology's 2002–2007 R&D Survey in Science and Technology in accordance with the OECD Frascati Manual for the equivalent years. First, the survey of R&D in Science and Technology was conducted from 2002 to 2007. The survey data includes 59,911 companies with separate R&D departments. We matched 97,407 firms’ financial data from KIS with the above R&D survey in Science and Technology (2002–2007) using firms’ registered business number. Finally, a data pool for this study was generated by integrating these two data sets from 19,570 firms ( Table 1 ). 4.3

All Science Journal Classification (ASJC) codes

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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