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Exploring the Intellectual Structure and International Cooperation in Information Management : A Bibliometric Overview Using 2-Tuple Linguistic Model

Author

Listed:
  • Huaige Zhang

    (Guangdong University of Finance and Economics)

  • Xianpei Hong

    (Guangdong University of Finance and Economics)

  • Qing Li

    (HZAU - Huazhong Agricultural University [Wuhan])

  • Yeming Gong

    (EM - EMLyon Business School)

  • Shan Liu

    (Xjtu - Xi'an Jiaotong University)

Abstract

To make a comprehensive literature review and identify the development trends, this study maps the intellectual structure of the research information management based on co-keyword analysis, the 2-tuple linguistic technique, and social network analysis. This study reveals the intellectual structure by analyzing the topological structure, conceptual structure, and strategic diagram. From the perspective of topological structure, the research of the information management field can be divided into three layers including the nucleus layer, middle layer, and marginal layer. In terms of the conceptual structure, the research of information management can be divided into four sub-fields including health information management, information systems, information technology, and information management application. The four subfields can be repartitioned into seven clusters by using a 2-tuple linguistic model, which means that the 2-tuple linguistic model can improve co-keyword analysis.

Suggested Citation

  • Huaige Zhang & Xianpei Hong & Qing Li & Yeming Gong & Shan Liu, 2021. "Exploring the Intellectual Structure and International Cooperation in Information Management : A Bibliometric Overview Using 2-Tuple Linguistic Model," Post-Print hal-04325614, HAL.
    • Handle: RePEc:hal:journl:hal-04325614
    DOI: 10.4018/JGIM.294577
    Note: View the original document on HAL open archive server: https://hal.science/hal-04325614v1
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    Cited by:

    1. Huosong Xia & Juan Weng & Sabri Boubaker & Zuopeng Zhang & Sajjad M. Jasimuddin, 2024. "Cross-influence of information and risk effects on the IPO market: exploring risk disclosure with a machine learning approach," Annals of Operations Research, Springer, vol. 334(1), pages 761-797, March.

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