Abstract
The present study compares the performance creation behavior between for-profit institutions and not-for-profit institutions within a national technology innovation research and development (R&D) program. Based on the stepwise performance creation chain structure of typical R&D logic models, a series of successive binary logistic regression models is newly proposed. Using the models, a sample of n = 2076 completed government-sponsored R&D projects was analyzed. For each institution type, its distinctive behavior is diagnosed, and relevant implications are suggested for improving the R&D performance.
Highlights
One of the major research topics of research and development (R&D) performance evaluation is the discussion of determining factors on R&D performance
In addition to the quantitative efficiency perspective, the qualitative effectiveness viewpoint is underscored in the field of R&D performance evaluation with the consideration of a clear relationship between R&D inputs and crucial performance created by GSPs (Ruegg 2006; Korea Institute of S&T Evaluation and Planning (KISTEP) 2011; Ministry of Knowledge Economy (MKE)·Korea Institute for Advancement of Technology (KIAT) 2012; STAR METRICS 2014)
Representative national technology innovation R&D programs can be found such as the Advanced Technology Program (ATP) under the Department of Commerce (DOC), the Industrial Technology Development Program (ITDP) administered by the Ministry of Economic Affairs (MEA) with the Taiwanese government, and the Knowledge Economy Technology Innovation Program (KETIP) conducted by the Ministry of Knowledge Economy (MKE) with the Korean government (Ruegg and Feller 2003; Shipp et al 2005; Ruegg 2006; Hsu and Hsueh 2009; Korea Evaluation Institute of Industrial Technology (KEIT) 2010, 2011, 2013)
Summary
One of the major research topics of research and development (R&D) performance evaluation is the discussion of determining factors on R&D performance. It implies that the sales performance creation success probability odds ratio decreases significantly when the institution type changes from for-profit institutions to not-for-profit institutions as follows: SME (1st) → Large Company (2nd) → Research Laboratory (3rd) → University
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