Precision medicine has received a lot of attention in recent years and we have not yet found any research cases that apply Data Envelopment Analysis (DEA) to investment decision making in this area. The purpose of this study is to analyze the relative efficiency of candidate technology sectors in order to determine priorities for government investment in precision medicine. The results of the efficiency analysis can be used as an important reference for government policy makers to determine the amount of government investment in the next year for each candidate technology sector. The candidate technology for government investment in precision medicine was decided for 23 sectors based on the data analysis and the opinions of expert committees. This study applies the input-oriented DEA in regard to 23 technology sectors, which is widely used to analyze relative efficiency in terms of inputs versus outputs and to enhance efficiency through the propositional reduction of inputs. The input variables include the government’s research and development (R&D) investment and forward and backward industry linkage effects. The output variables are the employment creation effect, value-added effect, number of Korean patents, and number of Korean papers. Our analysis results show that the 23 technology sectors in precision medicine overall have a high efficiency, with the exception of the biobank technology sector. Therefore, since the Biobank technology sector has strong infrastructure characteristics, it seems to require continuous investment. The efficiency of DEA is high in most precision medicine sectors; therefore, overall, investing in these technologies is expected to yield good benefits.
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