Abstract
The yearly increase in government R&D investment and top-down national R&D investment allocation requires a more quantitative decision-making system that maximizes R&D performance and efficient budget allocation. Sound decision-making is necessary at both the selection stage and the pursuit stage in order to maximize limited national R&D resources. We study Korean smart farms as an example to examine national R&D investment from the various R&D actors (academia, industry, and research institutes) perspectives. The objective of our research is to evaluate the theoretical efficiency of R&D investment on specific technologies in smart farms and compare the results with expert opinions where the reality is reflected. To be specific, our study is to provide the quantitative approach in making decision among policymakers by reflecting the field experiences and opinions. We use a data envelopment analysis with an assurance region model, which integrates an analytic hierarchy process and a data envelopment analysis. The weights of output in DEA model by the R&D actors are similar to the overall weight by all actors, implying that investment allocation decisions in the smart farm sector are not significantly affected by the R&D actors. We realized that the relative efficiency of some R&D technologies increases after reflecting qualitative ideas of experts. In reality, it is necessary to invest in these technology groups, but they excluded from top-down decision-making. This also shows that a government's top-down decision-making can distort its investment allocation. This study proposes a new approach to compensate for the difference between theoretical virtual prices and actual prices in data envelopment analysis. In particular, when comparing the only quantitative results on investment priorities with analysis results by additionally reflecting the opinions of experts in each sector, we found that the Korean government's investment priorities in the smart farm field are considerably distorted. Therefore, this study is expected to be used as an alternative for policy makers to compensate for the quantitative distortion might be caused by top-down national R&D investment decisions.
Highlights
We study Korean smart farms as an example to examine national R&D investment from the various R&D actors perspectives
We develop a scale that can measure the efficiency in producing various outcomes compared to the R&D expenditure input and the relative importance qualitatively considered for individual performance indicators by industry, academia, and research institutes
In terms of the economic effect, research institutes consider the employment inducement and value-added inducement effects to be substantial, whereas academia values the forward and backward industry link effects. These results indicate that academia and research institutes
Summary
According to Romer [2], unlike public and other existing goods, technology (or knowledge) is nonrival, which means it can be shared by many people without depleting its availability. It is excludable, and can be protected by laws or institutions to limit its use. Knowledge that is less likely to be excluded, such as basic science, is usually examined in universities or public research institutions These characteristics allow for appropriate government intervention in order to achieve an efficient resource allocation. It requires government to challenge how to utilize the available but limited resources best for its science and technology research In this regards, the priority setting is important when it comes to national R&D investment. The decision-making for setting the R&D investment priority is very complicated process which involves various stakeholders from scientific experts to policy, business and community representatives
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