Understanding the Trend of Scientific Productivity Analysis: Literature Review of Relevant Papers

Ren Ren, Koichi Murata
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Abstract

The productivity of academic scientific world is an important indicator for the allocation of university research funds. In order to understand the current state of research on dissertation productivity, this study organizes 21 papers on dissertation productivity published between 1986 to 2021 and compiles tables to understand research on dissertation productivity and discuss related items. The results obtained from the summary table show that case studies of papers tend to focus on one-unit influencing factors, and the analytical perspective is not comprehensive. Many papers make database decisions based on the authoritative nature of the database. It becomes clear that the method of analyzing productivity in the papers is overwhelmingly a statistical mathematical analysis. When a government or organization wants to evaluate scientific productivity, it should not focus on efficiency, but should choose the appropriate scientific productivity evaluation indicators according to the needs. The ease of data acquisition suggests that country-level scientific productivity is more suitable for qualitative analysis, while organization-level or individual-level factors are suitable for quantitative analysis studies.
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认识科学生产力分析的趋势:相关文献综述
学术科学界的生产力是衡量高校科研经费分配的重要指标。为了了解论文生产率的研究现状,本研究整理了1986年至2021年间发表的21篇论文生产率,并编制了表格来了解论文生产率的研究并讨论相关项目。汇总表的结果表明,论文的案例研究往往侧重于单一的影响因素,分析视角不够全面。许多论文根据数据库的权威性作出数据库决策。很明显,论文中分析生产力的方法绝对是一种统计数学分析。当政府或组织要评价科学生产力时,不应该只关注效率,而应该根据需要选择合适的科学生产力评价指标。数据获取的便利性表明,国家层面的科学生产力更适合进行定性分析,而组织层面或个人层面的因素更适合进行定量分析研究。
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