Research Performance Evaluation of Scientists: A Multi-Attribute Approach

In this paper, we highlight the fact that we cannot find a perfect index to evaluate output completely fairly and reasonably, and the research evaluation is a multi-attribute problem. This paper studies the method of multi-attribute comprehensive evaluation of scientists. Firstly, this paper chooses appropriate bibliometric indicators to evaluate research output. Following this, TOPSIS method is used to make a comprehensive research evaluation. Numerical examples are made regarding the purpose of testing the feasibility of the evaluation indicators and the evaluation method. Compared with traditional evaluation approaches on research performance, multi-attribute evaluation is more comprehensive and persuasive. It can overcome one-sidedness and reduce the bias of single indicator effectively.

[1]  E Garfield,et al.  Interview with Eugene Garfield, Chairman Emeritus of the Institute for Scientific Information (Isi) , 2001, Cortex.

[2]  Jin-Han Park,et al.  Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making , 2010, Third International Workshop on Advanced Computational Intelligence.

[3]  A. N. Guz,et al.  Scopus: A system for the evaluation of scientific journals , 2009 .

[4]  Leo Egghe,et al.  An h-index weighted by citation impact , 2008, Inf. Process. Manag..

[5]  A. D. Jackson,et al.  Measures for measures , 2006, Nature.

[6]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[7]  Pan Yuntao,et al.  Research on the evaluation of academic journals based on structural equation modeling , 2009 .

[8]  Ulrich Schmoch,et al.  How to use indicators to measure scientific performance: a balanced approach , 2010 .

[9]  T. V. Leeuwen.  Testing the validity of the Hirsch-index for research assessment purposes , 2008 .

[10]  Rodrigo Costas,et al.  The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level , 2007, J. Informetrics.

[11]  Ching-Lai Hwang,et al.  Multiple Attribute Decision Making: Methods and Applications - A State-of-the-Art Survey , 1981, Lecture Notes in Economics and Mathematical Systems.

[12]  L. Egghe,et al.  Theory and practise of the g-index , 2006, Scientometrics.

[13]  R. Rousseau,et al.  The R- and AR-indices: Complementing the h-index , 2007 .

[14]  Eugene Garfield,et al.  Interview with Eugene Garfield , 2006 .

[15]  Leo Egghe,et al.  Characteristic scores and scales based on h-type indices , 2010, J. Informetrics.

[16]  L. Bornmann,et al.  The state of h index research , 2009, EMBO reports.

[17]  Anthony F. J. van Raan.  Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups , 2013, Scientometrics.

[18]  J. E. Hirsch,et al.  An index to quantify an individual's scientific research output , 2005, Proc. Natl. Acad. Sci. USA.