科技资源配置效率研究述评及数字时代下的研究展望

A Review of the Research on the Allocation Efficiency of Scientific and Technological Resources and the Prospect of Research in the Digital Age

摘要:

近年来我国稳居世界第二大研发投入国，但科技资源配置效率还有待进一步提升。为更加科学地测度科技资源配置效率，从而优化资源配置路径、完善配置机制，助力科技创新，从传统科技资源配置效率的概念、内涵和主要测度对象、测度方法、测度指标体系等维度对已有相关文献进行系统梳理，厘清领域研究动态和发展趋势，分析相关指标体系常见问题以及提出改进建议，并结合数字化技术优势提出展望。基于中外重要期刊的33篇科技资源配置效率文献的研究结果显示：测度对象中，以针对地区等中观层面的研究最为丰富，并以面板数据为主，但科技资源配置效率较低的区域未得到较深入、有针对性的研究；测度方法一般采用经典的多元统计分析方法、计量分析方法等，近10年采用最多的是数据包络分析方法，也不乏采用多种方法/模型的组合，但利用大数据技术基于全样本的研究较为缺乏；测度指标体系通常包括科技资源的投入和产出指标体系，分别设置有一二级指标甚至更多级别的指标，但指标构建在系统性、科学性和独立性等方面仍有待改进，其中一级指标财力资源投入中未包括R&D经费外部支出、科技信息资源指标下的各二级指标项均已包含在科技财力资源的一级指标中、知识形态产出中包含多项相关性较强的二级指标等。基于此，针对上述存在问题，依据《中国科技统计年鉴》等权威信息文献，改进构建新的区域整体科技资源配置效率测度指标体系，其中以科技人力资源和科技财力资源作为决定性投入要素，选择R&D人员全时当量、R&D经费内外部总支出分别纳入相应的二级指标中。最后基于数字时代背景，展望科技资源配置效率研究的领域延伸、方法改进、指标完善和政策支持，强调单列数据要素作为科技资源优化配置的测度指标，使科技资源配置方式更加智能、高效和开放。

Abstract:

In recent years, China has been the world's second largest R&D investor, but the efficiency of science and technology resource allocation needs to be further improved. In order to measure the allocation efficiency of science and technology resources more scientifically, optimize the allocation path, improve the allocation mechanism, and help scientific and technological innovation, this paper systematically combs the existing literature on the allocation efficiency of traditional science and technology resources from the aspects of concept, connotation, main measurement objects, measurement methods, and measurement index system, and makes clear the research trends and development trends in the field. The common problems of related index system are analyzed and suggestions for improvement are put forward, and prospects are put forward based on the advantages of digital technology. The research results of 33 literatures on the allocation efficiency of science and technology resources in important Chinese and foreign journals show that: Among the measurement objects, the most abundant researches are on the mesolevel such as regions, and the panel data are the main ones. However, the regions with low allocation efficiency of science and technology resources have not received in-depth and targeted researches. The measurement methods generally adopt classical multivariate statistical analysis methods and quantitative analysis methods, etc. In recent 10 years, the most used method is data enveloping analysis, and there are also many combinations of methods/models. However, there are few researches based on full samples using big data technology. The measurement index system usually includes the input and output index system of scientific and technological resources, with one or two levels of indicators or even more, but the index construction still needs to be improved in terms of systematicness, scientificity and independence. Among them, the first-level financial resource investment does not include the external expenditure of R&D funds, the second-level indicators under the index of scientific and technological information resources have been included in the first-level indicators of scientific and technological financial resources, and the output of knowledge form contains a number of second-level indicators with strong correlation. Based on this, in view of the above problems, a new index system for measuring the efficiency of overall regional science and technology resource allocation is improved and constructed according to authoritative information documents such as China Science and Technology Statistical Yearbook. In this system, scientific and technology human resources and financial resources are taken as decisive input factors, and the full-time equivalent of R&D personnel and the total internal and external expenditure of R&D funds are selected to be included in the corresponding secondary indicators respectively. Finally, based on the background of the digital age, the paper looks forward to the extension of the field, improvement of methods, perfection of indicators and policy support of the research on the efficiency of science and technology resource allocation, and emphasizes the single data element as the measurement index of the optimal allocation of science and technology resources, so as to make the allocation of science and technology resources more intelligent, efficient and open.