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Research on the evaluation of academic journals based on structural equation modeling

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  • Liping, Yu
  • Yuqing, Chen
  • Yuntao, Pan
  • Yishan, Wu

Abstract

This paper classifies common journal evaluation indicators into three categories, namely three first-level indicators. They are respectively the indicators on journal impact, on timeliness, and on journal characteristics. The data used here is drawn from the medical journals in CSTPCD, a citation database built by the Institute of Scientific and Technical Information of China. The three categories of indicators are correlated with one another, so a structural equation may be established. Then we calculate the value of three first-level indicators and give subjective weights to the indicators. The comprehensive evaluation upon the medical journals yields satisfactory results. By simulating the complex relationship among journal indicators, the structural equation can be used for the estimation of some implicit indicators and the screening of indicators. This approach provides a new perspective for scientific and technological evaluation in general sense. It should be noted that the availability of basic data and the rationality of modeling bear much upon the evaluation results.

Suggested Citation

  • Liping, Yu & Yuqing, Chen & Yuntao, Pan & Yishan, Wu, 2009. "Research on the evaluation of academic journals based on structural equation modeling," Journal of Informetrics, Elsevier, vol. 3(4), pages 304-311.
    • Handle: RePEc:eee:infome:v:3:y:2009:i:4:p:304-311
    DOI: 10.1016/j.joi.2009.04.002
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    1. Michela Nardo & Michaela Saisana & Andrea Saltelli & Stefano Tarantola & Anders Hoffman & Enrico Giovannini, 2005. "Handbook on Constructing Composite Indicators: Methodology and User Guide," OECD Statistics Working Papers 2005/3, OECD Publishing.
    2. Weiping Yue & Concepción S. Wilson, 2004. "Measuring the citation impact of research journals in clinical neurology: A structural equation modelling analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 60(3), pages 317-332, August.
    3. Thed N. Van Leeuwen & Martijn S. Visser & Henk F. Moed & Ton J. Nederhof & Anthony F. J. Van Raan, 2003. "The Holy Grail of science policy: Exploring and combining bibliometric tools in search of scientific excellence," Scientometrics, Springer;Akadémiai Kiadó, vol. 57(2), pages 257-280, June.
    4. Sagar, Ambuj D. & Najam, Adil, 1998. "The human development index: a critical review," Ecological Economics, Elsevier, vol. 25(3), pages 249-264, June.
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    Cited by:

    1. Civera, Alice & Lehmann, Erik E. & Paleari, Stefano & Stockinger, Sarah A.E., 2020. "Higher education policy: Why hope for quality when rewarding quantity?," Research Policy, Elsevier, vol. 49(8).
    2. Rajesh Kr Singh & Sachin Kumar Mangla & Manjot Singh Bhatia & Sunil Luthra, 2022. "Integration of green and lean practices for sustainable business management," Business Strategy and the Environment, Wiley Blackwell, vol. 31(1), pages 353-370, January.
    3. Gouri Ginde & Snehanshu Saha & Archana Mathur & Sukrit Venkatagiri & Sujith Vadakkepat & Anand Narasimhamurthy & B. S. Daya Sagar, 2016. "ScientoBASE: a framework and model for computing scholastic indicators of non-local influence of journals via native data acquisition algorithms," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1479-1529, September.

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