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Fifty years of information management research: A conceptual structure analysis using structural topic modeling

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  • Sharma, Anuj
  • Rana, Nripendra P.
  • Nunkoo, Robin

Abstract

Information management is the management of organizational processes, technologies, and people which collectively create, acquire, integrate, organize, process, store, disseminate, access, and dispose of the information. Information management is a vast, multi-disciplinary domain that syndicates various subdomains and perfectly intermingles with other domains. This study aims to provide a comprehensive overview of the information management domain from 1970 to 2019. Drawing upon the methodology from statistical text analysis research, this study summarizes the evolution of knowledge in this domain by examining the publication trends as per authors, institutions, countries, etc. Further, this study proposes a probabilistic generative model based on structural topic modeling to understand and extract the latent themes from the research articles related to information management. Furthermore, this study graphically visualizes the variations in the topic prevalences over the period of 1970 to 2019. The results highlight that the most common themes are data management, knowledge management, environmental management, project management, service management, and mobile and web management. The findings also identify themes such as knowledge management, environmental management, project management, and social communication as academic hotspots for future research.

Suggested Citation

  • Sharma, Anuj & Rana, Nripendra P. & Nunkoo, Robin, 2021. "Fifty years of information management research: A conceptual structure analysis using structural topic modeling," International Journal of Information Management, Elsevier, vol. 58(C).
    • Handle: RePEc:eee:ininma:v:58:y:2021:i:c:s0268401221000098
    DOI: 10.1016/j.ijinfomgt.2021.102316
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    Citations

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    Cited by:

    1. Roshni Das, 2023. "Does public service motivation predict performance in public sector organizations? A longitudinal science mapping study," Management Review Quarterly, Springer, vol. 73(3), pages 1237-1271, September.
    2. Yogesh K. Dwivedi & A. Sharma & Nripendra P. Rana & M. Giannakis & P. Goel & Vincent Dutot, 2023. "Evolution of Artificial Intelligence Research in Technological Forecasting and Social Change: Research Topics, Trends, and Future Directions," Post-Print hal-04292607, HAL.
    3. Kang, Inje & Yang, Jiseong & Lee, Wonjae & Seo, Eun-Yeong & Lee, Duk Hee, 2023. "Delineating development trends of nanotechnology in the semiconductor industry: Focusing on the relationship between science and technology by employing structural topic model," Technology in Society, Elsevier, vol. 74(C).
    4. Li Tang & Jennifer Kuzma & Xi Zhang & Xinyu Song & Yin Li & Hongxu Liu & Guangyuan Hu, 2023. "Synthetic biology and governance research in China: a 40-year evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5293-5310, September.
    5. Dominika Krol-Smetak & Ireneusz Miciula & Apoloniusz Kurylczyk & Malgorzata Chojnacka & Karolina Rogowska & Monika Rozycka, 2023. "Analysis of the Impact of Implemented IT Systems on the Economic Efficiency of Enterprises in the Construction Industry in the Context of Sustainable Development in Poland," European Research Studies Journal, European Research Studies Journal, vol. 0(3), pages 901-915.
    6. Mohamed M. Mostafa, 2023. "A one-hundred-year structural topic modeling analysis of the knowledge structure of international management research," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3905-3935, August.
    7. Das, Kallol & Patel, Jayesh D. & Sharma, Anuj & Shukla, Yupal, 2023. "Creativity in marketing: Examining the intellectual structure using scientometric analysis and topic modeling," Journal of Business Research, Elsevier, vol. 154(C).
    8. Farheen Naz & Anil Kumar & Abhijit Majumdar & Rohit Agrawal, 2022. "Is artificial intelligence an enabler of supply chain resiliency post COVID-19? An exploratory state-of-the-art review for future research," Operations Management Research, Springer, vol. 15(1), pages 378-398, June.
    9. Kraus, Sascha & Kumar, Satish & Lim, Weng Marc & Kaur, Jaspreet & Sharma, Anuj & Schiavone, Francesco, 2023. "From moon landing to metaverse: Tracing the evolution of Technological Forecasting and Social Change," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    10. Silva, Lucas Emmanuel Nascimento & Gomes, Leonardo Augusto de Vasconcelos & Faria, Aline Mariane de & Borini, Felipe Mendes, 2024. "Innovation processes in ecosystem settings: An integrative framework and future directions," Technovation, Elsevier, vol. 132(C).
    11. Julie Ulstein, 2024. "Structural topic modeling as a mixed methods research design: a study on employer size and labor market outcomes for vulnerable groups," Quality & Quantity: International Journal of Methodology, Springer, vol. 58(5), pages 4331-4351, October.
    12. Farheen Naz & Rohit Agrawal & Anil Kumar & Angappa Gunasekaran & Abhijit Majumdar & Sunil Luthra, 2022. "Reviewing the applications of artificial intelligence in sustainable supply chains: Exploring research propositions for future directions," Business Strategy and the Environment, Wiley Blackwell, vol. 31(5), pages 2400-2423, July.
    13. Mehrotra, Ankit & Agarwal, Reeti & Khalil, Ashraf & Alzeiby, Ebtesam Abdullah & Agarwal, Vaishali, 2024. "Nitty-gritties of customer experience in metaverse retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    14. Rohit Agrawal & Vishal A. Wankhede & Anil Kumar & Sunil Luthra & Abhijit Majumdar & Yigit Kazancoglu, 2022. "An Exploratory State-of-the-Art Review of Artificial Intelligence Applications in Circular Economy using Structural Topic Modeling," Operations Management Research, Springer, vol. 15(3), pages 609-626, December.
    15. Goodell, John W. & Kumar, Satish & Li, Xiao & Pattnaik, Debidutta & Sharma, Anuj, 2022. "Foundations and research clusters in investor attention: Evidence from bibliometric and topic modelling analysis," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 511-529.
    16. Roshni Das, 2024. "What do we know about High Performance Work Systems? A bibliometric summary of 30 years of research," Management Review Quarterly, Springer, vol. 74(1), pages 415-438, February.

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