Multi-factor comprehensive evaluation model based on the selection of objective weight assignment method

Saixiang Zhong, Peng Hu, Ximing Xue, Shuo Yang, Peijuan Zhu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

The selection of weight assignment methods in multi-factor comprehensive evaluation has been rarely discussed in geographical research. There are fewer reports concerning comprehensive evaluation of human geography journals. In this paper we propose a selection model of weight assignment methods (SWAM) for multi-factor comprehensive evaluation so as to obtain rational and appropriate weight assignment methods among a pool of candidates. Specifically, each weight assignment method SWAM conducted a 'Similar- Different' comparison to analyze the change of weight distribution, as well as the evaluation score and indicator order, according to different parameter settings and adoption of clustering. Then through the comparison of 'Good-Bad', the rational and appropriate indicator-weight assignment methods were picked up. Focusing on seven objective weight assignment methods, SWAM was finally applied for comprehensive evaluation of 70 journals of human geography sorted as geography in the database of "Journal Citation Reports" from the scientific network (Web of Science, WoB) in which the data spans from 1st January 1900 to 31st December 2012. The research results show: (1) Objective weight assignment methods in this research can be divided into five groups, namely maximizingDev, variationCoe, factorAna; greyCor-0.5; entropy; principalComAna- 0.8; informationGra- 0.5; (2) Change of indicator clustering parameters led to change of indicator clustering results, and has influence on weight assignment; (3) SWAM selects maximizingDev, variationCoe, factorAna- 0.9 and informationGra-0.5 as the rational methods for the case study; (4) When the size of sample is relatively large, the output of grade in multi-factor comprehensive evaluation is more informative than the output of order; (5) 14 journals, led by Global Environmental Change- Human and Policy Dimensions, are marked as first-grade high-prestige group in 70 human geography journals in JCR; (6) Journal's impact factor is important, but the H-index, the distribution of authors of citing articles and the quality of citing articles, can better reflect the journal's level and international influence. This study highlights to improve the multi-factor comprehensive evaluation research and enrich the knowledge about human geography journals.

Original languageEnglish
Pages (from-to)2011-2031
Number of pages21
JournalDili Xuebao/Acta Geographica Sinica
Volume70
Issue number12
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • Evaluation of academic journals
  • Journals of human geography
  • Multi-factor comprehensive evaluation
  • Objective weight assignment methods
  • Selection model of Weight Assignment Methods (SWAM)

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