Evolution of AI in Information Systems: A Bibliometric Study

Authors

  • Afsana Mimi Begum Rokeya University, Bangladesh
Pages Icon

DOI:

https://doi.org/10.51519/journalisi.v6i4.928

Keywords:

Keywords: Artificial intelligence, Information systems, Bibliometric analysis, R, VOSviewer

Abstract

Significant challenges for traditional information systems are posed due to the ever-growing volume and complexity of data. Artificial intelligence has emerged as a powerful solution to address these challenges by adapting and making intelligent decisions. Valuable insights can be gained from data to automate repetitive tasks and optimize the operations. This study examines how the researchers are concentrating to explore multifaceted impact of AI on the design, implementation, and optimization of information systems. AI is transforming the landscape of information systems with progresses in machine learning, text mining, cognitive computing and other AI technologies by enhancing the efficiency and adaptability across various domains. This study delves into this emerging landscape by conducting a comprehensive bibliometric analysis of Artificial intelligence in Information systems research. This bibliometric study retrieved a dataset of publications from Scopus database spanning from 1960 to 2023 to find out the insights hidden within the scientific papers. The analysis encompasses key bibliometric indicators, such as citation patterns, co-authorship networks, and thematic clusters etc. to represent historical development of research in Artificial intelligence within the context of Information systems. This study fills a gap in AI and IS literature, drawing on 306 publications, with key contributions from the USA, China, UK, Germany, India and leading authors like OGIELA L (Lidia Ogiela) and CIMINO JJ ( James J.  Cimino). Co-authorship networks highlight the dominance of collaborative research hubs in countries like USA, China, Canada, Australia, while citation patterns underscore the influence of seminal works and cross-disciplinary contributions. The findings presented in this paper offer valuable insights for researchers, practitioners, and policymakers seeking a deeper understanding of the growing AI-IS landscape. As this is the first paper which takes the attempt to conduct a bibliometric analysis on artificial intelligence in information systems, this paper serves as a roadmap for navigating the rich tapestry of research, fostering collaboration, and guiding future investigations in this rapidly evolving and interdisciplinary field.

Downloads

Download data is not yet available.

References

P. J. Ågerfalk, K. Conboy, K. Crowston, J. Eriksson Lundström, S. L. Jarvenpaa, S. Ram, and P. Mikalef, “Artificial Intelligence in Information Systems: State of the Art and Research Roadmap,” Communications of the Association for Information Systems, vol. 50, no. 1, pp. 420-438, 2022.

C. Collins, D. Dennehy, K. Conboy, and P. Mikalef, “Artificial intelligence in information systems research: A systematic literature review and research agenda,” International Journal of Information Management, vol. 60, 2021.

Q. Zhang, A. R. Abdullah, C. W. Chong, and M. H. Ali, “E-Commerce Information System Management Based on Data Mining and Neural Network Algorithms,” Computational Intelligence and Neuroscience, vol. 2022, pp. 11, Apr, 2022.

G. Vandewiele, F. De Backere, K. Lannoye, M. Vanden Berghe, O. Janssens, S. Van Hoecke, V. Keereman, K. Paemeleire, F. Ongenae, and F. De Turck, “A decision support system to follow up and diagnose primary headache patients using semantically enriched data 08 Information and Computing Sciences 0801 Artificial Intelligence and Image Processing 08 Information and Computing Sciences 0806 Information Systems,” BMC Medical Informatics and Decision Making, vol. 18, no. 1, 2018.

D. Y. Jiang, H. Zhang, H. Kumar, Q. N. Naveed, C. Takhi, V. Jagota, and R. Jain, “Automatic Control Model of Power Information System Access Based on Artificial Intelligence Technology,” Mathematical Problems in Engineering, vol. 2022, pp. 6, Mar, 2022.

T. T. Liu, Z. X. Gao, and H. H. Guan, “Automatic Control Model of Power Information System Access Based on Artificial Intelligence Technology,” Complexity, vol. 2021, pp. 13, May, 2021.

Y. Liu, P. S. Hinds, J. Wang, H. Correia, S. Du, J. Ding, W. J. Gao, and C. Yuan, “Translation and linguistic validation of the pediatric patient-reported outcomes measurement information system measures into simplified chinese using cognitive interviewing methodology,” Cancer Nursing, vol. 36, no. 5, pp. 368-376, 2013.

D. Mattyasovszky-Philipp, and B. Molnár, “Cognitive Information Systems and Related Architecture Issues,” Acta Polytechnica Hungarica, vol. 20, no. 5, pp. 91-108, 2023.

L. Minsheng, “Application of interactive information system in college personnel management by using BP neural network algorithm,” Soft Computing, 2023.

M. Mokarram, J. Aghaei, M. J. Mokarram, G. P. Mendes, and B. Mohammadi-Ivatloo, “Geographic information system-based prediction of solar power plant production using deep neural networks,” IET Renewable Power Generation, vol. 17, no. 10, pp. 2663-2678, 2023.

P. Infante, G. Jacinto, D. Santos, P. Nogueira, A. Afonso, P. Quaresma, M. Silva, V. Nogueira, L. Rego, J. Saias, P. Góis, and P. R. Manuel, “Prediction of Road Traffic Accidents on a Road in Portugal: A Multidisciplinary Approach Using Artificial Intelligence, Statistics, and Geographic Information Systems,” Information (Switzerland), vol. 14, no. 4, 2023.

O. Ellegaard, and J. A. Wallin, “The bibliometric analysis of scholarly production: How great is the impact?,” Scientometrics, vol. 105, no. 3, pp. 1809-1831, 2015.

I. Passas, “Bibliometric Analysis: The Main Steps,” Encyclopedia, vol. 4, no. 2, pp. 1014-1025, 2024.

N. Donthu, S. Kumar, D. Mukherjee, N. Pandey, and W. M. Lim, “How to conduct a bibliometric analysis: An overview and guidelines,” Journal of Business Research, vol. 133, pp. 285-296, 2021.

P. Ahmad, J. A. Asif, M. K. Alam, and J. Slots, “A bibliometric analysis of Periodontology 2000,” Periodontol 2000, vol. 82, no. 1, pp. 286-297, Feb, 2020.

H. Derviş, “Bibliometric Analysis using Bibliometrix an R Package,” Journal of Scientometric Research, vol. 8, no. 3, pp. 156-160, 2020.

S. BÜYÜKkidik, “A Bibliometric Analysis: A Tutorial for the Bibliometrix Package in R Using IRT Literature,” Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, vol. 13, no. 3, pp. 164-193, 2022.

K. Ragazou, I. Passas, A. Garefalakis, E. Galariotis, and C. Zopounidis, “Big Data Analytics Applications in Information Management Driving Operational Efficiencies and Decision-Making: Mapping the Field of Knowledge with Bibliometric Analysis Using R,” Big Data and Cognitive Computing, vol. 7, no. 1, 2023.

Y. Gao, L. Ge, S. Shi, Y. Sun, M. Liu, B. Wang, Y. Shang, J. Wu, and J. Tian, “Global trends and future prospects of e-waste research: a bibliometric analysis,” Environmental Science and Pollution Research, vol. 26, no. 17, pp. 17809-17820, 2019.

B. M. Abdel-Karim, N. Pfeuffer, and O. Hinz, “Machine learning in information systems - a bibliographic review and open research issues,” Electronic Markets, vol. 31, no. 3, pp. 643-670, 2021.

E. Peters, T. Kliestik, H. Musa, and P. Durana, “Product decision-making information systems, real-time big data analytics, and deep learning-enabled smart process planning in sustainable industry 4.0,” Journal of Self-Governance and Management Economics, vol. 8, no. 3, pp. 16-22, 2020.

L. Ogiela, “Semantic analysis and biological modelling in selected classes of cognitive information systems,” Mathematical and Computer Modelling, vol. 58, no. 5-6, pp. 1405-1414, 2013.

K. Siau, and X. Tan, “Technical communication in information systems development: The use of cognitive mapping,” IEEE Transactions on Professional Communication, vol. 48, no. 3, pp. 269-284, 2005.

L. Ogiela, “Computational intelligence in cognitive healthcare information systems,” Studies in Computational Intelligence, vol. 309, pp. 347-369, 2010.

F. Maiwald, C. Lehmann, and T. Lazariv, “Fully automated pose estimation of historical images in the context of 4d geographic information systems utilizing machine learning methods,” ISPRS International Journal of Geo-Information, vol. 10, no. 11, 2021.

F. F. Ahmadi, and N. F. Layegh, “Integration of artificial neural network and geographical information system for intelligent assessment of land suitability for the cultivation of a selected crop,” Neural Computing & Applications, vol. 26, no. 6, pp. 1311-1320, Aug, 2015.

X. Zhang, and L. Chen, “College English Smart Classroom Teaching Model Based on Artificial Intelligence Technology in Mobile Information Systems,” Mobile Information Systems, vol. 2021, 2021.

R. Kozik, M. Choraś, W. Hołubowicz, and R. Renk, "Extreme learning machines for Web layer anomaly detection." pp. 226-233.

Downloads

Published

2024-12-31

Issue

Vol. 6 No. 4 (2024): December

Section

Articles

License

Authors Declaration

  1. The Authors certify that they have read, understood, and agreed to the Journal of Information Systems and Informatics (JournalISI) submission guidelines, policies, and submission declaration. The submission has been prepared using the provided template.
  2. The Authors certify that all authors have approved the publication of this manuscript and that there is no conflict of interest.
  3. The Authors confirm that the manuscript is their original work, has not received prior publication, is not under consideration for publication elsewhere, and has not been previously published.
  4. The Authors confirm that all authors listed on the title page have contributed significantly to the work, have read the manuscript, attest to the validity and legitimacy of the data and its interpretation, and agree to its submission.
  5. The Authors confirm that the manuscript is not copied from or plagiarized from any other published work.
  6. The Authors declare that the manuscript will not be submitted for publication in any other journal or magazine until a decision is made by the journal editors.
  7. If the manuscript is finally accepted for publication, the Authors confirm that they will either proceed with publication immediately or withdraw the manuscript in accordance with the journal’s withdrawal policies.
  8. The Authors agree that, upon publication of the manuscript in this journal, they transfer copyright or assign exclusive rights to the publisher, including commercial rights

How to Cite

[1]
A. Mimi, “Evolution of AI in Information Systems: A Bibliometric Study”, journalisi, vol. 6, no. 4, pp. 2837–2855, Dec. 2024, doi: 10.51519/journalisi.v6i4.928.

Most read articles by the same author(s)