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The COVID-19 pandemic and global food security: a bibliometric analysis and future research direction

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  • Hashem Abdullah AlNemer

Abstract

Purpose - This study aims to analyse the nature and trends in the knowledge discovery process on COVID-19 and food insecurity using a comprehensive bibliometric analysis based on the indexing literature in the Scopus database. Design/methodology/approach - Data were extracted from Scopus using the keywords COVID-19 and food security to ensure extensive coverage. A total of 840 research papers on COVID-19 and food security were analysed using VOSviewer and RStudio software. Findings - The findings of the bibliometric analysis in terms of mapping of scientific research across countries and co-occurrence of research keywords provide the trends in research focus and future directions for food insecurity research during times of uncertainty. Based on this analysis, the focus of scientific research has been categorised as COVID-19 and food supply resilience, COVID-19 and food security, COVID-19 and public health, COVID-19 and nutrition, COVID-19 and mental health and depression, COVID-19 and migration and COVID-19 and social distancing. A thematic map was created to identify future research on COVID-19 and food security. Practical implications - This analysis identifies potential research areas such as food supply and production, nutrition and health that may help set future research agendas and devise policy supports for better managing food insecurity during uncertainty. Originality/value - This analysis provides epistemological underpinnings for knowledge generation and acquisition on COVID-19 and food insecurity.

Suggested Citation

  • Hashem Abdullah AlNemer, 2023. "The COVID-19 pandemic and global food security: a bibliometric analysis and future research direction," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 50(5), pages 709-724, January.
  • Handle: RePEc:eme:ijsepp:ijse-08-2022-0532
    DOI: 10.1108/IJSE-08-2022-0532
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    Cited by:

    1. Sariyer, Gorkem & Mangla, Sachin Kumar & Kazancoglu, Yigit & Jain, Vranda & Ataman, Mustafa Gokalp, 2023. "Data-driven decision making for modelling covid-19 and its implications: A cross-country study," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

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