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利用基于研发利益相关者观点的数据包络分析方法,整合定量和定性方法来制定国家研发计划。

Integrating quantitative and qualitative methodologies to build a national R&D plan using data envelopment analysis based on R&D stakeholders' perspectives.

机构信息

Science and Technology Management Policy, University of Science & Technology, Daejeon Metropolitan City, Republic of Korea.

R&D Investment and Strategy Research Center, Korea Institute of Science and Technology Information, Seoul, Republic of Korea.

出版信息

PLoS One. 2022 Mar 11;17(3):e0265058. doi: 10.1371/journal.pone.0265058. eCollection 2022.

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.

摘要

政府研发投入的逐年增加和自上而下的国家研发投入分配要求建立一个更具定量决策系统,以最大限度地提高研发绩效和有效预算分配。为了最大限度地利用有限的国家研发资源,在选择阶段和追求阶段都需要进行合理的决策。我们以韩国智能农场为例,从学术界、产业界和研究机构等各种研发参与者的角度考察国家研发投资。我们的研究目的是评估特定技术在智能农场的研发投资的理论效率,并将结果与反映实际情况的专家意见进行比较。具体而言,我们的研究通过反映实地经验和意见,为决策者提供了一种在定量方法中做出决策的方式。我们使用带有保证区域模型的数据包络分析,该模型集成了层次分析法和数据包络分析。研发参与者的数据包络分析模型中的输出权重与所有参与者的总体权重相似,这意味着智能农场部门的投资分配决策不会受到研发参与者的显著影响。我们意识到,在反映专家定性意见后,一些研发技术的相对效率有所提高。在现实中,有必要对这些技术群体进行投资,但它们被排除在自上而下的决策之外。这也表明,政府的自上而下决策可能会扭曲其投资分配。本研究提出了一种新的方法来弥补数据包络分析中理论虚拟价格和实际价格之间的差异。特别是,当我们将仅基于定量结果的投资优先级与通过额外反映各部门专家意见的分析结果进行比较时,我们发现韩国政府在智能农场领域的投资优先级存在相当大的扭曲。因此,本研究有望作为决策者的替代方案,以弥补自上而下的国家研发投资决策可能导致的定量扭曲。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9d2d/8916661/6389436a8f98/pone.0265058.g001.jpg

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