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State of the art in business analytics: themes and collaborations

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  • Seyed Mohammad Jafar Jalali

    (Allameh Tabataba’i University)

  • Han Woo Park

    (YeungNam University)

Abstract

In this study, we illustrate the most recent stage in the scholarly development of the field of Business Analytics. Using around 23,000 research publications collected from the Web of Science, we network-analyzed four types of dataset that include keywords, titles, institutions, and countries. It is noteworthy that we found a thematic cluster focusing on analytical techniques and tools, particular with the rapid dissemination of “big data”-related studies. It is not surprising that universities and institutions in advanced countries in the West still occupy the central position of the collaboration network. However, we can discern a global shift toward certain developing and transitional economies in the world science base.

Suggested Citation

  • Seyed Mohammad Jafar Jalali & Han Woo Park, 2018. "State of the art in business analytics: themes and collaborations," Quality & Quantity: International Journal of Methodology, Springer, vol. 52(2), pages 627-633, March.
    • Handle: RePEc:spr:qualqt:v:52:y:2018:i:2:d:10.1007_s11135-017-0522-7
    DOI: 10.1007/s11135-017-0522-7
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    References listed on IDEAS

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    Cited by:

    1. Keshav Singh Rawat & Sandeep Kumar Sood, 2021. "Emerging trends and global scope of big data analytics: a scientometric analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(4), pages 1371-1396, August.
    2. Han Woo Park & Jungwon Yoon, 2019. "Structural characteristics of institutional collaboration in North Korea analyzed through domestic publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 771-787, May.
    3. Adasa Nkrumah Kofi Frimpong & Ping Li & Millicent Amoah & Md Altab Hossin, 2021. "From the algorithmic and emergent mindset to the heuristic mindset of reviewing literature," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(4), pages 1419-1455, August.
    4. Maxim Kotsemir, 2019. "Unmanned aerial vehicles research in Scopus: an analysis and visualization of publication activity and research collaboration at the country level," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2143-2173, July.
    5. Barbara S. Lancho-Barrantes & Hector G. Ceballos-Cancino & Francisco J. Cantu-Ortiz, 2021. "Comparing the efficiency of countries to assimilate and apply research investment," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(4), pages 1347-1369, August.
    6. Iman Raeesi Vanani & Laya Mahmoudi & Seyed Mohammad Jafar Jalali & Kim-Hung Pho, 2022. "Using text mining algorithms in identifying emerging trends for recommender systems," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1293-1326, June.
    7. Yang Bai & Hongxiu Li & Yong Liu, 2021. "Visualizing research trends and research theme evolution in E-learning field: 1999–2018," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1389-1414, February.
    8. Nauman Majeed & Sulaiman Ainin, 2021. "Visualizing the evolution and landscape of socio-economic impact research," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 637-659, April.
    9. Hyo Chan Park & Jonghee M. Youn & Han Woo Park, 2019. "Global mapping of scientific information exchange using altmetric data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(2), pages 935-955, March.
    10. Wullianallur Raghupathi & Viju Raghupathi, 2021. "Contemporary Business Analytics: An Overview," Data, MDPI, vol. 6(8), pages 1-11, August.

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