Artificial Intelligence in the Creative Economy: A Systematic Bibliometric Review and Future Research Agenda
DOI:
https://doi.org/10.38035/dijms.v7i4.6507Keywords:
Artificial Intelligence, Creative Economy, Bibliometric Analysis, Digital Transformation, Dynamic CapabilityAbstract
The rapid development of artificial intelligence (AI) has driven significant transformation in the creative economy, a sector fundamentally rooted in creativity, knowledge, and innovation. Although the number of publications addressing AI in the creative economy has increased substantially in recent years, the intellectual structure, thematic evolution, and research gaps within this field remain insufficiently mapped, particularly within the domains of business and management. This study aims to systematically map the scholarly landscape of AI in the creative economy using a systematic bibliometric review approach. Data were collected from the Scopus database through a structured search strategy and predefined inclusion criteria, resulting in a dataset of 128 articles analyzed using VOSviewer software. The citation analysis reveals a total of 2,107 citations, with an average of 16.46 citations per article and an H-index of 22, indicating that this research area is in a growing phase with an emerging core literature. Co-occurrence analysis identifies four major thematic clusters: digital transformation and innovation in the creative economy, technological impacts on economic growth, AI-driven entrepreneurship, and human–AI collaboration in the future of work. Overlay visualization indicates a shift in research focus from macro-level perspectives toward organization-based perspectives, while density visualization highlights that themes such as AI readiness, organizational capabilities, and human capital development in AI-driven creative environments remain underexplored. This study contributes theoretically by demonstrating a shift from industry-based perspectives toward capability-based perspectives in understanding AI adoption within the creative economy. The findings also provide directions for future research and offer practical implications for creative organizations and policymakers in developing sustainable AI adoption strategies.
References
Amankwah-Amoah, J., Khan, Z., Wood, G., & Knight, G. (2024). The impending disruption of creative industries by generative AI: Opportunities, challenges, and research agenda. International Journal of Information Management, 74, 102716. https://doi.org/10.1016/j.ijinfomgt.2023.102716
Boussioux, L., Fahrenkopf, N., Fleming, L., & Srivastava, M. (2024). The crowdless future? Generative AI and creative problem-solving. Organization Science, 35(1), 1–21. https://doi.org/10.1287/orsc.2023.1765
Bucea-Manea-Țoniş, R., Bucea-Manea-Țoniş, R., Simion, V. E., & Ilic, D. (2022). Artificial intelligence potential in higher education institutions enhanced learning environment in Romania and Serbia. Sustainability, 14(11), 6457. https://doi.org/10.3390/su14116457
Chowdhury, S., Dey, P. K., Joel-Edgar, S., Bhattacharya, A., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2022). AI-employee collaboration and business performance: Integrating knowledge-based view, socio-technical systems and organisational socialisation framework. Journal of Business Research, 144, 31–49. https://doi.org/10.1016/j.jbusres.2022.01.069
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
Holford, W. D. (2019). The future of human creative knowledge work within the digital economy. Futures, 105, 143–154. https://doi.org/10.1016/j.futures.2018.10.002
Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192015-1765-5
Naveed, K., Watanabe, C., & Neittaanmäki, P. (2017). Co-evolution between streaming and live music leads a way to the sustainable growth of music industry—Lessons from the US experiences. Technology in Society, 50, 1–19. https://doi.org/10.1016/j.techsoc.2017.03.005
Sharma, A., Jain, R., Gupta, P., & Chowdhury, A. (2023). Implementation of artificial intelligence in agriculture. Journal of Computational and Cognitive Engineering, 2(1), 1–11. https://doi.org/10.47852/bonviewJCCE22022010
Song, H., & Kim, J. (2021). Predictors of consumers’ willingness to share personal information with fashion sales robots. Journal of Retailing and Consumer Services, 63, 102712. https://doi.org/10.1016/j.jretconser.2021.102712
Taylor, M., Floridi, L., & Van der Sloot, B. (2020). Operator 4.0 or maker 1.0? Exploring the implications of Industrie 4.0 for innovation, safety and quality of work in small economies and enterprises. Computers & Industrial Engineering, 139, 105996. https://doi.org/10.1016/j.cie.2019.105996
Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207–222. https://doi.org/10.1111/1467-8551.00375
Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Wang, Y., Zhang, J., & Li, H. (2023). Achieving sustainable development goal 9: A study of enterprise resource optimization based on artificial intelligence algorithms. Resources Policy, 85, 103834. https://doi.org/10.1016/j.resourpol.2023.103834
Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/1094428114562629
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