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A comparative analysis of emerging scientific themes in business analytics

Author

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  • Iman Raeesi Vanani
  • Seyed Mohammad Jafar Jalali

Abstract

The purpose of this research is to investigate the emerging scientific themes in business analytics through the utilisation of burst detection, text-clustering and word occurrence analysis in top information systems journals in order to provide an insight about the future scientific trends of business analytics for scholars and practitioners in the field. Researchers have gathered a rich set of business analytics articles from top journals which are indexed in the well-known scientific database of web of science (WoS) core collection. The study provides clues, directions, and knowledge-based guidelines on the recent business analytics scientific trends through the utilisation of mentioned algorithms over paper abstracts, titles, and keywords. This study also highlights the most important areas of research and the future research directions that might be interesting to business analysts through an in-depth analytical discussion.

Suggested Citation

  • Iman Raeesi Vanani & Seyed Mohammad Jafar Jalali, 2018. "A comparative analysis of emerging scientific themes in business analytics," International Journal of Business Information Systems, Inderscience Enterprises Ltd, vol. 29(2), pages 183-206.
    • Handle: RePEc:ids:ijbisy:v:29:y:2018:i:2:p:183-206
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    Citations

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    Cited by:

    1. Martin Potančok & Jan Pour & Wui Ip, 2021. "Factors Influencing Business Analytics Solutions and Views on Business Problems," Data, MDPI, vol. 6(8), pages 1-12, August.
    2. Mona Razaghzadeh Bidgoli & Iman Raeesi Vanani & Mehdi Goodarzi, 2024. "Predicting the success of startups using a machine learning approach," Journal of Innovation and Entrepreneurship, Springer, vol. 13(1), pages 1-27, December.
    3. Wullianallur Raghupathi & Viju Raghupathi, 2021. "Contemporary Business Analytics: An Overview," Data, MDPI, vol. 6(8), pages 1-11, August.

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