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  • Author or Editor: Soo-Ryun Cho x
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Abstract  

In Open Access (OA) environment where article-based or author-based evaluation is important, a new evaluation system is needed to accommodate characteristics of Open Access Resources (OAR) and to overcome limitations of pre-existing evaluation systems such as journal-based evaluation. Primary and secondary evaluation factors were selected. Primary factors include hits and citations that constitutes composite index. Several secondary factors each for article and author evaluation were selected for normalization of the indexes. To validate superiority of newly developed normalized composite index systems compared to the monovariable index system, time-driven bias and power of discrimination were adopted. The results led to the conclusion that composite index proved to be a more stable index offsetting the negative effects from one element to another and normalization makes the composite index even more stable by controlling the bias from external elements.

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Abstract

This study describes the development process of Kor-Factor, which is a novel composite evaluation index that was developed to promote Korean domestic academic journals. As more data accumulate, the Kor-Factor's optimization process was modified in an attempt to address possible drawbacks of the original form; the result is presented in this study. This study compares Kor-Factor with the Impact Factor, which is the most well-known single element evaluation index. We found that Kor-Factor demonstrates a better power of differentiation and a greater capacity to reflect the reputability of key journals. The modified Kor-Factor, which has been developed through an optimization process, reveals a greater power of differentiation than the original Kor-Factor; however, the modified version has less capacity to reflect reputability. The evaluation elements of the modified Kor-Factor are better and are more evenly reflected on the index value than those of the original version. Finally, we propose the establishment of an appropriate data measurement period for the actual application of the index.

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