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Efficiency analysis of forestry journals: Suggestions for improving journals’ quality

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  • Petridis, Konstantinos
  • Malesios, Chrisovalantis
  • Arabatzis, Garyfallos
  • Thanassoulis, Emmanuel

Abstract

In this paper we attempt to assess the impact of journals in the field of forestry, in terms of bibliometric data, by providing an evaluation of forestry journals based on data envelopment analysis (DEA). In addition, based on the results of the conducted analysis, we provide suggestions for improving the impact of the journals in terms of widely accepted measures of journal citation impact, such as the journal impact factor (IF) and the journal h-index. More specifically, by modifying certain inputs associated with the productivity of forestry journals, we have illustrated how this method could be utilized to raise their efficiency, which in terms of research impact can then be translated into an increase of their bibliometric indices, such as the h-index, IF or eigenfactor score.

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  • Petridis, Konstantinos & Malesios, Chrisovalantis & Arabatzis, Garyfallos & Thanassoulis, Emmanuel, 2013. "Efficiency analysis of forestry journals: Suggestions for improving journals’ quality," Journal of Informetrics, Elsevier, vol. 7(2), pages 505-521.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:2:p:505-521
    DOI: 10.1016/j.joi.2013.02.002
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    Cited by:

    1. Lee, Hakyeon & Shin, Juneseuk, 2014. "Measuring journal performance for multidisciplinary research: An efficiency perspective," Journal of Informetrics, Elsevier, vol. 8(1), pages 77-88.
    2. Chen, Kun & Ren, Xian-tong & Yang, Guo-liang, 2021. "A novel approach for assessing academic journals: Application of integer DEA model for management science and operations research field," Journal of Informetrics, Elsevier, vol. 15(3).
    3. Grigoroudis, Evangelos & Petridis, Konstantinos & Arabatzis, Garyfallos, 2014. "RDEA: A recursive DEA based algorithm for the optimal design of biomass supply chain networks," Renewable Energy, Elsevier, vol. 71(C), pages 113-122.
    4. Ortega, Francisco J. & Gavilan, Jose M., 2013. "The measurement of production efficiency in scientific journals through stochastic frontier analysis models: Application to quantitative economics journals," Journal of Informetrics, Elsevier, vol. 7(4), pages 959-965.
    5. Gavilan, José M. & Ortega, Francisco J., 2020. "Productive efficiency analysis of quantitative economics journals through Stochastic Frontier Analysis using panel data || Análisis de eficiencia productiva de revistas de economía cuantitativa a trav," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 30(1), pages 297-311, December.

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