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The measurement of production efficiency in scientific journals through stochastic frontier analysis models: Application to quantitative economics journals

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  • Ortega, Francisco J.
  • Gavilan, Jose M.

Abstract

The importance of a scientific journal is usually established by considering the number of citations received by the papers that the journal publishes. In this way, the number of citations received by a scientific journal can be considered as a measure of the total production of the journal. In this paper, in order to obtain measures of the efficiency in the production process, the approach provided by stochastic frontier analysis (SFA) is considered, and econometric models are proposed. These models estimate a frontier production, which is the maximum achievable number of citations to the journal based on its resources. The efficiency can then be measured by considering the difference between the actual production and the estimated frontier. This approach is applied to the measurement of the productive efficiency of the journals of the JCR social sciences edition database, which belong simultaneously to the areas of “economics” and “social sciences, mathematical methods”.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:4:p:959-965
    DOI: 10.1016/j.joi.2013.09.004
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    Cited by:

    1. Lutz Bornmann & Alexander Butz & Klaus Wohlrabe, 2018. "What are the top five journals in economics? A new meta-ranking," Applied Economics, Taylor & Francis Journals, vol. 50(6), pages 659-675, February.
    2. 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.
    3. Klaus Wohlrabe, 2016. "Taking the Temperature: A Meta-Ranking of Economics Journals," CESifo Working Paper Series 5726, CESifo.
    4. 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).
    5. Gang, Cuiui & Li, Juanwei & Hu, Haiqing & Wei, Wei, 2023. "Dynamic co-movement between economic growth and language: A new perspective of technological progress," International Review of Economics & Finance, Elsevier, vol. 85(C), pages 705-721.
    6. Miao, Chenglin & Fang, Debin & Sun, Liyan & Luo, Qiaoling, 2017. "Natural resources utilization efficiency under the influence of green technological innovation," Resources, Conservation & Recycling, Elsevier, vol. 126(C), pages 153-161.

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    More about this item

    Keywords

    Production; Productivity; Efficiency; Scientific production; Frontier production models;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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