基于专业知识的机构研究项目组合管理的粗粒度和细粒度层次框架

Abhirup Nandy, H. Lathabai, V. Singh
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引用次数: 0

摘要

机构绩效评估是包括国家和机构决策者在内的各种利益相关者面临的主要挑战之一。现有流行的绩效评估方法依赖于研究产出之外的各种因素,这些方法受到了各种理由的批评。在这项工作中,我们提出了一个科学-文本框架,在两个层面上评估机构的核心能力/专业知识:基于WoS主题类别的广泛主题层面,以及基于索引关键词的更精细的主题层面。绩效指标即x_d指数和x指数分别用于广泛和精细主题水平的评估。国家政策制定者可以利用x_d指数来增强国家学术生态系统,机构政策制定者和机构的其他利益相关者可以从整体使用该框架中受益,以改善其更广泛的专业知识多样性,并在适当的学科范围内提高其高级专业知识水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Expertise-based Framework for Research Portfolio Management of Institutions at coarse- and fine-grained levels
Institutional performance assessment is one of the major challenges for various stakeholders including national and institutional policymakers. Existing popular approaches to performance measurement rely on various factors besides research output, which have been criticized on various grounds. In this work, we present a sciento-text framework to assess the core competency/expertise of an institution at two levels: a broad thematic level, based on WoS subject categories, and a finer thematic level based on indexed keywords. The performance measures namely x_d- index and x-index are used for assessment at broad and fine thematic levels, respectively. While national policymakers can make use of x_d- index for the enhancement of national scholarly ecosystem, institutional policymakers and other stakeholders of the institution can make benefit from the wholistic usage of the framework to work for improving its broader expertise diversity as well as enhancing its fine level expertise within suitable disciplines.
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