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Guidelines for advancing theory and practice through bibliometric research

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  • Mukherjee, Debmalya
  • Lim, Weng Marc
  • Kumar, Satish
  • Donthu, Naveen

Abstract

Bibliometric research presents unique opportunities to contribute to theory and practice. Top journals and scholars from various disciplines have published numerous highly impactful articles utilizing bibliometric techniques to study different fields’ evolutionary nuances and capture emerging trends. However, studies using bibliometric techniques have often attracted criticism for failing to adequately link their derived analytical and visual outputs with theory building and practice improvement. Consequently, we ask the following question: How can bibliometric research contribute to theory and practice? To this end, this editorial (i) premiers the characteristics and distinct contributions of bibliometric research and (ii) proposes a multifaceted approach that (a) researchers can utilize to develop and demonstrate the potential contributions of their bibliometric research and (b) referees (e.g., editors and reviewers) can rely on to effectively decipher and evaluate the framing, positioning, and contributions of bibliometric research. In doing so, we hope to enhance the understanding and contributions of bibliometric research in advancing theory and practice.

Suggested Citation

  • Mukherjee, Debmalya & Lim, Weng Marc & Kumar, Satish & Donthu, Naveen, 2022. "Guidelines for advancing theory and practice through bibliometric research," Journal of Business Research, Elsevier, vol. 148(C), pages 101-115.
  • Handle: RePEc:eee:jbrese:v:148:y:2022:i:c:p:101-115
    DOI: 10.1016/j.jbusres.2022.04.042
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    References listed on IDEAS

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    12. 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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