Digital Transformation in Enterprise Risk Management: A Bibliometric Study and Research Trends
DOI:
https://doi.org/10.58812/wsshs.v3i03.1769Keywords:
Digital Transformation, Bibliometric Analysis, Artificial Intelligence, Risk Assessment, CybersecurityAbstract
This study examines digital transformation research using bibliometric analysis, identifying key trends, collaborative networks, and thematic areas. Findings reveal that "digital transformation" is central, closely linked to "decision making," "artificial intelligence," and "risk assessment." Over time, research has shifted from broad technological advancements to domain-specific applications like healthcare and telemedicine. Co-authorship analysis highlights strong academic networks, particularly in the U.S., U.K., and China, though interdisciplinary collaboration remains a challenge. The study emphasizes the need for ethical AI governance, enhanced cybersecurity, and inclusive global research participation to ensure balanced technological progress.
References
[1] Z. Wang, “Digital transformation and risk management for SMEs: a systematic review on available evidence,” Adv. Econ. Manag. Polit. Sci., vol. 65, pp. 209–218, 2023.
[2] S. Pupentsova and M. Livintsova, “The enterprises risk management in the context of digital transformation,” in International Scientific Siberian Transport Forum, Springer, 2021, pp. 1159–1167.
[3] S. V Pupentsova and E. A. Gromova, “Risk management in business valuation in the context of digital transformation,” Real Estate Manag. Valuat., vol. 29, no. 2, pp. 97–106, 2021.
[4] I. Zupic and T. Čater, “Bibliometric methods in management and organization,” Organ. Res. methods, vol. 18, no. 3, pp. 429–472, 2015.
[5] A. G. Sokolov, V. M. Abramov, E. P. Istomin, E. A. Korinets, V. A. Bolshakov, and T. V Vekshina, “Digital transformation of risk management for natural-industrial systems while climate change,” in IOP conference series: materials science and engineering, IOP Publishing, 2020, p. 12003.
[6] S. Grima, E. Thalassinos, M. Cristea, M. Kadłubek, D. Maditinos, and L. Peiseniece, Digital transformation, strategic resilience, cyber security and risk management. Emerald Publishing Limited, 2023.
[7] J. S. Menzefricke, I. Wiederkehr, C. Koldewey, and R. Dumitrescu, “Socio-technical risk management in the age of digital transformation-identification and analysis of existing approaches,” Procedia CIRP, vol. 100, pp. 708–713, 2021.
[8] K. Rauniyar, X. Wu, S. Gupta, S. Modgil, and A. B. Lopes de Sousa Jabbour, “Risk management of supply chains in the digital transformation era: contribution and challenges of blockchain technology,” Ind. Manag. Data Syst., vol. 123, no. 1, pp. 253–277, 2023.
[9] Y. Masuda, S. Shirasaka, S. Yamamoto, and T. Hardjono, “Risk management for digital transformation in architecture board: a case study on global enterprise,” in 2017 6th IIAI international congress on advanced applied informatics (IIAI-AAI), IEEE, 2017, pp. 255–262.
[10] A. Creazza, C. Colicchia, S. Spiezia, and F. Dallari, “Who cares? Supply chain managers’ perceptions regarding cyber supply chain risk management in the digital transformation era,” Supply Chain Manag. An Int. J., vol. 27, no. 1, pp. 30–53, 2022.
[11] E. Casey and T. R. Souvignet, “Digital transformation risk management in forensic science laboratories,” Forensic Sci. Int., vol. 316, p. 110486, 2020.
[12] S. C. Agarwal John Driscoll Xavier Gabaix David Laibson et al., “Federal Reserve Board 20th and Constitution Ave,” 2007.
[13] D. Ivanov, A. Dolgui, and B. Sokolov, “The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics,” Int. J. Prod. Res., vol. 57, no. 3, pp. 829–846, 2019.
[14] Y. Pan and L. Zhang, “Roles of artificial intelligence in construction engineering and management: A critical review and future trends,” Autom. Constr., vol. 122, p. 103517, 2021.
[15] P. Yang, N. Xiong, and J. Ren, “Data security and privacy protection for cloud storage: A survey,” Ieee Access, vol. 8, pp. 131723–131740, 2020.
[16] H. S. Birkel, J. W. Veile, J. M. Müller, E. Hartmann, and K.-I. Voigt, “Development of a risk framework for Industry 4.0 in the context of sustainability for established manufacturers,” Sustainability, vol. 11, no. 2, p. 384, 2019.
[17] K. Wach et al., “The dark side of generative artificial intelligence: A critical analysis of controversies and risks of ChatGPT,” Entrep. Bus. Econ. Rev., vol. 11, no. 2, pp. 7–30, 2023.
[18] N. Malik, S. N. Tripathi, A. K. Kar, and S. Gupta, “Impact of artificial intelligence on employees working in industry 4.0 led organizations,” Int. J. Manpow., vol. 43, no. 2, pp. 334–354, 2021.
[19] J. Baptista, M.-K. Stein, S. Klein, M. B. Watson-Manheim, and J. Lee, “Digital work and organisational transformation: Emergent Digital/Human work configurations in modern organisations,” J. Strateg. Inf. Syst., vol. 29, no. 2, p. 101618, 2020.
[20] D. Ivanov, A. Dolgui, A. Das, and B. Sokolov, “Digital supply chain twins: Managing the ripple effect, resilience, and disruption risks by data-driven optimization, simulation, and visibility,” Handb. ripple Eff. supply Chain, pp. 309–332, 2019.
[21] N. R. Mosteanu and A. Faccia, “Digital systems and new challenges of financial management–FinTech, XBRL, blockchain and cryptocurrencies,” Qual. to Success, vol. 21, no. 174, pp. 159–166, 2020.
[22] F. Rowe, “Contact tracing apps and values dilemmas: A privacy paradox in a neo-liberal world,” Int. J. Inf. Manage., vol. 55, p. 102178, 2020.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Loso Judijanto, Rival Pahrijal, Tera Lesmana
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Facebook 
Instagram 
Twitter 
Youtube 
westscience.journals@gmail.com