과학기술 경쟁력 제고를 위한 대형연구시설 및 장비평가모형 분석: 모형의 신뢰성 및 타당성 검토를 중심으로

초록

The purpose of this study is to construct the evaluation model for the major science research facilities and equipments to enhance the competitiveness of the science and technology and also to test the reliability and validity of the model. To achieve the purposes, this study theoretically reviews the concept of the major science research facilities and equipments and their characteristics. Through a review of literature, this study draws 11 criteria for evaluating the priorities of the major science research facilities and equipments. These criteria are categorized as two dimensions - 'science & technology' and 'national policy'. The dimension of science & technology includes scientific importance, technological readiness, utilization rate, common utilization rate, and ability of management and operation. The national policy dimension contains degree of correspondence with national science development, imperativeness of national policy, science and technical effectiveness, economic and industrial effectiveness, responsiveness of research demand, and equity among the related institutions. The competitiveness of the science and technology consists of these two dimensions. The evaluation model is established on the framework of criteria. The 18 major science research facilities and equipments are selected through a series of Delphi. The survey of experts (BT, ET, IT, NT and ST) is also implemented to evaluate the 18 major science research facilities and equipments by 11 criteria. The overall results indicate that the reliability and validity of the model are good. The reliability tests show that the five indicators of science & technology and the six indicators of national policy have high internal consistencies. The confirmatory factor analyses reveal that the two constructs - 'science & technology' and 'national policy' - have high convergent and discriminant validity. The correlational analyses also show that the criteria-related validity between them is high. Furthermore, the results of higher order factor analysis indicate that the fit indices of the model are high and suggest a good fit to the data. Based on these findings, the policy implications of the model are discussed.