Exploring the Intersection of AI, Big Data and Business Networks: A Bibliometric and Scientific Mapping Study
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The combination between Artificial Intelligence (AI), Big Data and Business Networks has substantially transformed the system of performance of organizations and has enhanced inter-firm cooperation leading to innovation in various industries. This current bibliometric and scientific mapping research paper examines the intellectual environment of this interdisciplinary discipline in terms of the PRISMA model. The analysis is based on meta-data obtained on Web of Science (2015 to 2025). A package of visualizations (geographical distribution, annual publication patterns, author productivity, major journals, country output and keyword co-occurrence) are done by using RStudio and Vos viewer are used to map the central research topics and developing areas. Important groups draw the major themes and transformational research patterns. The ten most influential papers are put in the spotlight, which provides a selective reference to the background and breakthrough articles. The interpretation of the results on the collected data allows one to have a general picture of the evolution of the field among scholars. The findings indicate the constant growth of the academic contributions toward the entire world, with countries such as the United States, China and the United Kingdom taking the top table in terms of matters regarding research production. Key journals and authors are proposed, confirming the increased significance of AI and Big Data in optimization of the business networks in terms of its agility and efficiency. This work provides valuable lessons to artists and scholars due to its ability to capture the most up-to-date trends and highlight potential future directions of research that could benefit the resilience, scale and innovation in Networked Business context.
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Abayomi Abraham Adesina, Toluwalase Vanessa Iyelolu, & Patience Okpeke Paul. (2024). Leveraging predictive analytics for strategic decision-making: Enhancing business performance through data-driven insights. World Journal of Advanced Research and Reviews, 22(3), 1927–1934. https://doi.org/10.30574/wjarr.2024.22.3.1961
Aguiar Lima Dos Santos, L. M., da Costa, M. B., Kothe, J. V., Benitez, G. B., Schaefer, J. L., Baierle, I. C., & Benitez Nara, E. O. (2021). Industry 4.0 collaborative networks for industrial performance. JOURNAL OF MANUFACTURING TECHNOLOGY MANAGEMENT, 32(2), 245–265. https://doi.org/10.1108/JMTM-04-2020-0156
Albarrati, A. M., Nazer, R., Abdelwahab, S. I., & Albratty, M. (2025). Artificial intelligence applications and aging (1995-2024): Trends , challenges, and future directions in frailty research. ARCHIVES OF GERONTOLOGY AND GERIATRICS, 134. https://doi.org/10.1016/j.archger.2025.105837
Andres, B., Urze, P., Araujo, E., & Camarinha-Matos, L. M. (2025). Artificial intelligence use in collaborative network processes. JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 47. https://doi.org/10.1016/j.jii.2025.100883
Arasteh, S. T., Kuhl, C., Saehn, M.-J., Isfort, P., Truhn, D., & Nebelung, S. (2023). Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning. SCIENTIFIC REPORTS, 13(1). https://doi.org/10.1038/s41598-023-49956-8
Ben Yahia, N., Eljaoued, W., Ben Saoud, N. B., & Colomo-Palacios, R. (2021). Towards sustainable collaborative networks for smart cities co-governance. INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 56. https://doi.org/10.1016/j.ijinfomgt.2019.11.005
Benaben, F., Fertier, A., Montarnal, A., Mu, W., Jiang, Z., Truptil, S., Barthe-Delanoe, A.-M., Lauras, M., Mace-Ramete, G., Wang, T., Bidoux, L., & Lamothe, J. (2020). An AI framework and a metamodel for collaborative situations: Application to crisis management contexts. JOURNAL OF CONTINGENCIES AND CRISIS MANAGEMENT, 28(3, SI), 291–306. https://doi.org/10.1111/1468-5973.12310
Camarinha-Matos, L. M., Oliveira, A. I., Ferrada, F., & Thamburaj, V. (2017). Collaborative services provision for solar power plants. INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 117(5), 946–966. https://doi.org/10.1108/IMDS-06-2016-0246
Cantu, C. L., & Tunisini, A. (2023). A circular innovation strategy in a supply network context: evidence from the packaging industry. Journal of Business and Industrial Marketing, 38(13), 220 – 238. https://doi.org/10.1108/JBIM-07-2021-0325
David Iyanuoluwa Ajiga, Ndubuisi Leonard Ndubuisi, Onyeka Franca Asuzu, Oluwaseyi Rita Owolabi, Tula Sunday Tubokirifuruar, & Rhoda Adura Adeleye. (2024). Ai-Driven Predictive Analytics in Retail: a Review of Emerging Trends and Customer Engagement Strategies. International Journal of Management & Entrepreneurship Research, 6(2), 307–321. https://doi.org/10.51594/ijmer.v6i2.772
Domenteanu, A., Cotfas, L.-A., Diaconu, P., Tudor, G.-A., & Delcea, C. (2025). AI on Wheels: Bibliometric Approach to Mapping of Research on Machine Learning and Deep Learning in Electric Vehicles. ELECTRONICS, 14(2). https://doi.org/10.3390/electronics14020378
Dsouza, V. S., Leyens, L., Kurian, J. R., Brand, A., & Brand, H. (2025). Artificial intelligence (AI) in pharmacovigilance: A systematic review on predicting adverse drug reactions (ADR) in hospitalized patients. RESEARCH IN SOCIAL & ADMINISTRATIVE PHARMACY, 21(6), 453–462. https://doi.org/10.1016/j.sapharm.2025.02.008
Ekundayo, T. C., Olasehinde, T. A., Okaiyeto, K., & Okoh, A. I. (2021). Microbial Pathogenesis and Pathophysiology of Alzheimer’s Disease: A Systematic Assessment of Microorganisms’ Implications in the Neurodegenerative Disease. FRONTIERS IN NEUROSCIENCE, 15. https://doi.org/10.3389/fnins.2021.648484
Galib, M., Haerani, S., Mamimg, J., & Munir, A. R. (2022). The Role of SMT and Business Network Accentuation on Value Distribution and Performance Consequences. Journal of Distribution Science, 20(5), 97 – 104. https://doi.org/10.15722/jds.20.05.202205.97
Ghaouri, M. H., Kassim, S., & Rashid, H. (2023). Waqf-Linked Islamic Fintech Microfinance as a Business Enabler in Post-pandemic Economy: The Experience of Hal Microfinance, Kenya. Studies in Systems, Decision and Control, 470, 357 – 370. https://doi.org/10.1007/978-3-031-28314-7_30
González, E. P., Martín Martín, J. M., Martínez, J. M. G., & Khodja, H. H. A. (2022). The Disruptive Effect of Technological Innovation in the Tourist Accommodation Industry. International Journal of Innovation and Technology Management, 19(1). https://doi.org/10.1142/S0219877021400083
Hirt, R., Kühl, N., Martin, D., & Satzger, G. (2025). Enabling inter-organizational analytics in business networks through meta machine learning. Information Technology and Management, 26(1), 57 – 81. https://doi.org/10.1007/s10799-023-00399-7
Holland, C. P., Thornton, S. C., & Naude, P. (2020). B2B analytics in the airline market: Harnessing the power of consumer big data. INDUSTRIAL MARKETING MANAGEMENT, 86. https://doi.org/10.1016/j.indmarman.2019.11.002
Keegan, B. J., Iredale, S., & Naude, P. (2023). Examining the dark force consequences of AI as a new actor in B2B relationships. INDUSTRIAL MARKETING MANAGEMENT, 115, 228–239. https://doi.org/10.1016/j.indmarman.2023.10.001
Liao, S.-H., Hu, D.-C., & Chen, S.-T. (2022). Supply chain integration, capability and performance – a business-to-business network cooperation. Journal of Business and Industrial Marketing, 37(5), 1127 – 1137. https://doi.org/10.1108/JBIM-10-2020-0467
Papa, A., Chierici, R., Ballestra, L. V., Meissner, D., & Orhan, M. A. (2021). Harvesting reflective knowledge exchange for inbound open innovation in complex collaborative networks: an empirical verification in Europe. JOURNAL OF KNOWLEDGE MANAGEMENT, 25(4, SI), 669–692. https://doi.org/10.1108/JKM-04-2020-0300
Pardo, C., Wei, R., & Ivens, B. S. (2022). Integrating the business networks and internet of things perspectives: A system of systems (SoS) approach for industrial markets. Industrial Marketing Management, 104, 258 – 275. https://doi.org/10.1016/j.indmarman.2022.04.012
Patrick Azuka Okeleke, Daniel Ajiga, Samuel Olaoluwa Folorunsho, & Chinedu Ezeigweneme. (2024). Predictive analytics for market trends using AI: A study in consumer behavior. International Journal of Engineering Research Updates, 7(1), 036–049. https://doi.org/10.53430/ijeru.2024.7.1.0032
Penttinen, V., & Frösén, J. (2022). Shared analytical capabilities in business networks. Industrial Marketing Management, 106, 308 – 322. https://doi.org/10.1016/j.indmarman.2022.08.018
Pinter, D. G., & Ihasz, P. L. (2019). Bridging Natural Language Processing AI techniques and Corporate Communications: towards an integrative model. INFORMACIOS TARSADALOM, 19(4), 77–99.
Rivera, N. V. (2024). Big data in sarcoidosis. CURRENT OPINION IN PULMONARY MEDICINE, 30(5), 561–569. https://doi.org/10.1097/MCP.0000000000001102
Sanchez-Lopez, M. D. (2023). Geopolitics of the Li-ion battery value chain and the Lithium Triangle in South America. Latin American Policy, 14(1), 22 – 45. https://doi.org/10.1111/lamp.12285
Santos, B., & Campos, P. (2023). SUWAN: A supervised clustering algorithm with attributed networks. INTELLIGENT DATA ANALYSIS, 27(2), 423–441. https://doi.org/10.3233/IDA-216436
Schroeder, A., Bigdeli, A. Z., Zarcos, C. G., & Baines, T. (2019). Capturing the benefits of industry 4.0: a business network perspective. PRODUCTION PLANNING & CONTROL, 30(16), 1305–1321. https://doi.org/10.1080/09537287.2019.1612111
Sun, Y., Qiao, F., Wang, W., Xu, B., Zhu, J., Mansour, R. F., & Qi, J. (2022). Dynamic Intelligent Supply-Demand Adaptation Model Towards Intelligent Cloud Manufacturing. CMC-COMPUTERS MATERIALS & CONTINUA, 72(2), 2825–2843. https://doi.org/10.32604/cmc.2022.026574
Uchenna Joseph Umoga, Enoch Oluwademilade Sodiya, Ejike David Ugwuanyi, Boma Sonimitiem Jacks, Oluwaseun Augustine Lottu, Obinna Donald Daraojimba, & Alexander Obaigbena. (2024). Exploring the potential of AI-driven optimization in enhancing network performance and efficiency. Magna Scientia Advanced Research and Reviews, 10(1), 368–378. https://doi.org/10.30574/msarr.2024.10.1.0028
Wang, H., Smith, D., & Demir, U. (2025). Scaling AI filmmaking with collaborative networking. IET COMMUNICATIONS, 19(1). https://doi.org/10.1049/cmu2.12877
Xavier, J. A., Siong, G. K., Yew, L. K., Jiang, N., & Alagappar, P. N. (2022). Fostering Business Growth through Generational Change: Is Guanxi Still Important? Translocal Chinese: East Asian Perspectives, 16(2), 228 – 248. https://doi.org/10.1163/24522015-16020004
Zhang, Q., Lu, J., & Jin, Y. (2021). Artificial intelligence in recommender systems. Complex and Intelligent Systems, 7(1), 439–457. https://doi.org/10.1007/s40747-020-00212-w
Zhu, Y. P., & Park, H. W. (2024). Publication, Collaboration, Citation Performance, and Triple Helix Innovation Gene of Artificial Intelligence Research in the Communication Field: Comparing Asia to the Rest of the World. JOURNAL OF THE KNOWLEDGE ECONOMY. https://doi.org/10.1007/s13132-024-02280-6
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