Many countries plan and implement various programs to provide direct and indirect support for small and medium businesses to undertake technological innovation. This study focuses on R&D planning support programs, which are one of the policies designed to provide indirect support and improve investment efficiency. This study compares cases of R&D planning support programs in Korea to identify the differences between demanding companies and beneficiary companies and evaluates whether the implementation of the policy was efficient. To compare the characteristics of differing groups of companies, we applied an analysis method based on data mining to profile the characteristics of the companies. In addition, to help improve the efficiency of policy implementation in the future, we used discriminant analysis to present a model for forecasting how high the demand for R&D planning support will be among start-up companies. Based on the model we propose in this study, companies that have experienced R&D planning support have a very different profile from those that are in need of planning support. In other words, we found a mismatch between companies that have been beneficiaries of the policy and demanding companies, those that are still in need of the support. This study proposes a demand forecasting model to redress this mismatch, which we hope will contribute to enhancing the efficiency of R&D support policies and the evidence based decision making.
Jun, S. P., Kim, S. G., & Park, H. W. (2017). The mismatch between demand and beneficiaries of R&D support programs for SMEs: Evidence from Korean R&D planning programs. Technological Forecasting and Social Change, 116, 286–298. https://doi.org/10.1016/j.techfore.2016.10.007