Research on cybersecurity and business: A bibliometric review (2004-2023)
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Published
21-03-2025
Luciano Barcellos-Paula
Anna M. Gil-Lafuente
José M. Merigó
https://orcid.org/0000-0003-4249-0565
Anna M. Gil-Lafuente
José M. Merigó
Abstract
Cybersecurity poses a significant risk for companies due to the rise in cyberattacks worldwide, leading to increased uncertainty in security management and putting the sustainability of businesses at risk. Despite some academic contributions, limited bibliometric studies on integrating cybersecurity and business information exist. The research aims to assist academics, policymakers, and decision-makers in cybersecurity management. The authors conducted a bibliometric review using scientific mapping and performance analysis. The study used the Web of Science database and Bibliometrix software to analyze 410 articles and 1,355 authors across nine bibliometric indicators between 2004 and 2023. This article is novel in proposing a bibliometric review of cybersecurity and business, as the other studies addressed specific sectors and do not allow for an integrated view of information on these two topics. The main findings showed an annual growth of 27.63% and an international co-authorship of 31.46%. The United States of America has the highest scientific production, followed by the United Kingdom and China. Business Horizons and IEEE Access are the most influential journals in this field of research. This study can improve the analysis of academics, policymakers, and decision-makers in companies regarding security management. Future studies could propose management models to improve cybersecurity in organizations.
How to Cite
Barcellos-Paula, L., Gil-Lafuente, . A. M., & Merigó, . J. M. (2025). Research on cybersecurity and business: A bibliometric review (2004-2023). Cuadernos De Gestión, 25(1), 19–36. https://doi.org/10.5295/cdg.242288lb
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Keywords
Cybersecurity, Business, Safety Management, Scientific Mapping, Bibliometrix, Risk
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Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011a). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of In-formetrics, 5(1), 146–166. https://doi.org/10.1016/j.joi.2010.10.002
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011b). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology, 62(7), 1382–1402. https://doi.org/10.1002/asi.21525
Corallo, A., Lazoi, M., & Lezzi, M. (2020). Cybersecurity in the context of industry 4.0: A structured classification of critical assets and business impacts. Computers in Industry, 114, 103165. https://doi.org/10.1016/j.compind.2019.103165
Corallo, A., Lazoi, M., Lezzi, M., & Luperto, A. (2022). Cybersecurity awareness in the context of the Industrial Internet of Things: A systematic literature review. Computers in Industry, 137, 103614. https://doi.org/10.1016/j.compind.2022.103614
Corallo, A., Lazoi, M., Lezzi, M., & Pontrandolfo, P. (2023). Cybersecurity Challenges for Manufacturing Systems 4.0: Assessment of the Business Impact Level. IEEE Transactions on Engineering Management, 70(11). https://doi.org/10.1109/TEM.2021.3084687
Garfield, E. (1955). Citation indexes for science. Science, 122(3159). https://doi.org/10.1126/science.122.3159.108
Ghobakhloo, M. (2020). Determinants of information and digital technology implementation for smart manufacturing. International Journal of Production Research, 58(8), 2384–2405. https://doi.org/10.1080/00207543.2019.1630775
Gil-Aluja, J. (1999). Elements for a Theory of Decision in Uncertainty (Vol. 32). Springer US. https://doi.org/10.1007/978-1-4757-3011-1
Gupta, S., Meissonier, R., Drave, V. A., & Roubaud, D. (2020). Examining the impact of Cloud ERP on sustainable per-formance: A dynamic capability view. International Journal of Information Management, 51. https://doi.org/10.1016/j.ijinfomgt.2019.10.013
Hasanova, H., Baek, U. jun, Shin, M. gon, Cho, K., & Kim, M. S. (2019). A survey on blockchain cybersecurity vulner-abilities and possible countermeasures. International Journal of Network Management, 29(2). https://doi.org/10.1002/nem.2060
Hayat, R. F., Aurangzeb, S., Aleem, M., Srivastava, G., & Lin, J. C. W. (2022). ML-DDoS: A Blockchain-Based Multilevel DDoS Mitigation Mechanism for IoT Environments. IEEE Transactions on Engineering Management. https://doi.org/10.1109/TEM.2022.3170519
Hayes, A. (2020). Business Definition. Investopedia.
Hosseini Shirvani, M., Rahmani, A. M., & Sahafi, A. (2018). An iterative mathematical decision model for cloud migration: A cost and security risk approach. Software - Practice and Experience, 48(3). https://doi.org/10.1002/spe.2528
Jalali, M. S., Razak, S., Gordon, W., Perakslis, E., & Madnick, S. (2019). Health Care and Cybersecurity: Bibliometric Analysis of the Literature. Journal of Medical Internet Research, 21(2), e12644. https://doi.org/10.2196/12644
Javaheri, D., Gorgin, S., Lee, J. A., & Masdari, M. (2023). Fuzzy logic-based DDoS attacks and network traffic anomaly detection methods: Classification, overview, and future perspectives. Information Sciences, 626. https://doi.org/10.1016/j.ins.2023.01.067
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