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The effects of choice of database and data retrieval methods on research performance evaluations of Asian universities

机译:数据库选择和数据检索方法对亚洲大学研究绩效评估的影响

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Purpose - The purpose of this paper is to study the effects of the choice of database and data retrieval methods on the research performance of a number of selected Asian universities from 33 countries using two different indicators (publication volume and citation count) and three subject fields (energy, environment and materials) during the period 2005-2009. Design/methodology/approach - To determine the effect of the choice of database, Scopus and Web of Science databases were queried to retrieve the publications and citations of the top ten Asian universities in three subject fields. In ascertaining the effect of data retrieval methods, the authors proposed a new data retrieval method called Keyword-based Data Retrieval (KDR), which uses relevant keywords identified by independent experts to retrieve publications and their citations of the top 30 Asian universities in the Environment field from the entire Scopus database. The results were then compared with those retrieved using the Conventional Data Retrieval (CDR) method. Findings - The Asian university ranking order is strongly affected by the choice of database, indicator, and the data retrieval method used. The KDR method yields many more publications and citation counts than the CDR method, shows better understanding of the university ranking results, and retrieves publications and citations in source titles outside those classified by the database. Moreover the publications found by the KDR method have a multidisciplinary research focus. Originality/value - The paper concludes that KDR is a more suitable methodology to retrieve data for measuring university research performance, particularly in an environment where universities are increasingly engaging in multidisciplinary research.
机译:目的-本文的目的是使用两种不同的指标(出版量和引用次数)和三个学科领域,研究选择数据库和数据检索方法对来自33个国家的许多亚洲选定大学的研究绩效的影响(能源,环境和材料)在2005-2009年期间。设计/方法/方法-为确定数据库选择的效果,查询了Scopus和Web of Science数据库,以检索三个学科领域中亚洲前十所大学的出版物和引用。为了确定数据检索方法的效果,作者提出了一种新的数据检索方法,称为基于关键字的数据检索(KDR),该方法使用独立专家确定的相关关键字来检索环境中排名前30位的亚洲大学的出版物及其引用整个Scopus数据库中的字段。然后将结果与使用常规数据检索(CDR)方法检索的结果进行比较。调查结果-亚洲大学的排名顺序受到数据库,指标和所用数据检索方法的选择的强烈影响。与CDR方法相比,KDR方法产生的出版物和引文计数要多得多,可以更好地理解大学排名结果,并且可以检索数据库分类之外的出版物中的出版物和引文。此外,通过KDR方法发现的出版物具有多学科的研究重点。原创性/价值-本文得出的结论是,KDR是一种更合适的方法来检索数据以衡量大学的研究绩效,尤其是在大学越来越多地从事跨学科研究的环境中。

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