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The International Journal of Production Research at 55: a content-driven review and analysis

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  • Jian (Jeff) Guan
  • Andrew S. Manikas
  • Lynn H. Boyd

Abstract

The articles published in the International Journal of Production Research (IJPR) since inception have made a significant contribution to operations management (OM) research, firmly establishing IJPR as one of the most important outlets for OM research. This paper uses a text mining technique called Latent Semantic Analysis to identify the core areas of research published in IJPR since inception, and reveals how the focus on topics has evolved over time. The data consist of the abstracts of all articles published in IJPR from the inception of the journal through December 2015. The study identifies 16 core areas of research and provides a detailed analysis of how these core areas have evolved over time. The results from this data-driven analysis of 55 years of research in IJPR not only provide a comprehensive examination of past research in the journal but also important insights into the evolution of key areas of research in operations management.

Suggested Citation

  • Jian (Jeff) Guan & Andrew S. Manikas & Lynn H. Boyd, 2019. "The International Journal of Production Research at 55: a content-driven review and analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4654-4666, August.
    • Handle: RePEc:taf:tprsxx:v:57:y:2019:i:15-16:p:4654-4666
    DOI: 10.1080/00207543.2017.1296979
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    Cited by:

    1. Romero-Silva, Rodrigo & de Leeuw, Sander, 2021. "Learning from the past to shape the future: A comprehensive text mining analysis of OR/MS reviews," Omega, Elsevier, vol. 100(C).
    2. Karen Paul & Carlos M. Parra, 2021. "Corporate social responsibility in international business literature: results from text data mining of the Journal of International Business Studies," International Journal of Corporate Social Responsibility, Springer, vol. 6(1), pages 1-14, December.

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