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Measuring journal performance for multidisciplinary research: An efficiency perspective

机译:测量跨学科研究的期刊绩效:效率视角

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One of the flaws of the journal impact factor (IF) is that it cannot be used to compare journals from different fields or multidisciplinary journals because the IF differs significantly across research fields. This study proposes a new measure of journal performance that captures field-different citation characteristics. We view journal performance from the perspective of the efficiency of a journal's citation generation process. Together with the conventional variables used in calculating the IF, the number of articles as an input and the number of total citations as an output, we additionally consider the two field-different factors, citation density and citation dynamics, as inputs. We also separately capture the contribution of external citations and self-citations and incorporate their relative importance in measuring journal performance. To accommodate multiple inputs and outputs whose relationships are unknown, this study employs data envelopment analysis (DEA), a multi-factor productivity model for measuring the relative efficiency of decision-making units without any assumption of a production function. The resulting efficiency score, called DEA-IF, can then be used for the comparative evaluation of multidisciplinary journals' performance. A case study example of industrial engineering journals is provided to illustrate how to measure DEA-IF and its usefulness.
机译:期刊影响因子(IF)的缺陷之一是,它不能用于比较不同领域的期刊或多学科期刊,因为IF在各个研究领域之间都存在显着差异。这项研究提出了一种新的衡量期刊绩效的方法,该方法可以捕获不同领域的引文特征。我们从期刊引文生成过程的效率角度看期刊的绩效。连同用于计算IF的常规变量,输入的文章数以及作为输出的总引文数,我们还另外考虑了两个字段不同的因素,即引文密度和引文动态,作为输入。我们还分别记录了外部引文和自我引文的贡献,并结合了它们在衡量期刊绩效中的相对重要性。为了适应关系未知的多个输入和输出,本研究采用数据包络分析(DEA),这是一种多要素生产率模型,用于在不假设任何生产函数的情况下测量决策单位的相对效率。由此产生的效率得分称为DEA-IF,可用于对多学科期刊的绩效进行比较评估。提供了一个工业工程期刊的案例研究示例,以说明如何测量DEA-IF及其有用性。

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