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Research constituents, intellectual structure, and collaboration pattern in the Journal of Forecasting: A bibliometric analysis

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  • H. Kent Baker
  • Satish Kumar
  • Debidutta Pattnaik

Abstract

This study provides a retrospective of the Journal of Forecasting (JoF) between 1982 and 2019. Evidence shows a considerable increase in JoF's productivity and influence since 1982. For example, a JoF article, on average, receives more than 18 citations, and contributions from 65 nations appear in the journal. All articles have a forecasting implication, but JoF encourages a wide range of contexts recently featuring value‐at‐risk and financial econometrics. Factors with a positive association with JoF citations include the number of references, article length, article age, special issue, and number of authors.

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  • H. Kent Baker & Satish Kumar & Debidutta Pattnaik, 2021. "Research constituents, intellectual structure, and collaboration pattern in the Journal of Forecasting: A bibliometric analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(4), pages 577-602, July.
    • Handle: RePEc:wly:jforec:v:40:y:2021:i:4:p:577-602
    DOI: 10.1002/for.2731
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    References listed on IDEAS

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    2. Goodell, John W. & Kumar, Satish & Lim, Weng Marc & Pattnaik, Debidutta, 2021. "Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).

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