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http://dx.doi.org/10.7232/JKIIE.2014.40.3.342

Empirical Analysis on the Relationship between R&D Inputs and Performance Using Successive Binary Logistic Regression Models  

Park, Sungmin (Department of Business Administration, Baekseok University)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.40, no.3, 2014 , pp. 342-357 More about this Journal
Abstract
The present study analyzes the relationship between research and development (R&D) inputs and performance of a national technology innovation R&D program using successive binary Logistic regression models based on a typical R&D logic model. In particular, this study focuses on to answer the following three main questions; (1) "To what extent, do the R&D inputs have an effect on the performance creation?"; (2) "Is an obvious relationship verified between the immediate predecessor and its successor performance?"; and (3) "Is there a difference in the performance creation between R&D government subsidy recipient types and between R&D collaboration types?" Methodologically, binary Logistic regression models are established successively considering the "Success-Failure" binary data characteristic regarding the performance creation. An empirical analysis is presented analyzing the sample n = 2,178 R&D projects completed. This study's major findings are as follows. First, the R&D inputs have a statistically significant relationship only with the short-term, technical output, "Patent Registration." Second, strong dependencies are identified between the immediate predecessor and its successor performance. Third, the success probability of the performance creation is statistically significantly different between the R&D types aforementioned. Specifically, compared with "Large Company", "Small and Medium-Sized Enterprise (SMS)" shows a greater success probability of "Sales" and "New Employment." Meanwhile, "R&D Collaboration" achieves a larger success probability of "Patent Registration" and "Sales."
Keywords
Binary Logistic Regression; Government Subsidy; R&D Collaboration; R&D Logic Model; Small and Medium-Sized Enterprise;
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