Forecasting Global Digital Infrastructure Capacity with an Optimized Discrete Grey Model
DOI:
https://doi.org/10.52812/ijgs.105Keywords:
Grey Model, Forecast, Digital Infrastructure, Data Centre, Strategic Management, Capacity PlanningAbstract
The rapid expansion of digital infrastructure presents significant forecasting and strategic planning challenges for investors and corporate decision-makers. This study applies the DGM (1,1,α) grey forecasting model to project the growth of four critical variables to 2030: global network traffic, data creation, data centre supply, and data centre demand, using secondary data. The model demonstrates high in-sample accuracy, with Mean Absolute Percentage Errors (MAPE) below 1.35%. A comparative analysis with industry benchmarks reveals strong alignment, validating the model's robustness. Key findings project sustained near-exponential growth and a critical narrowing of the global supply-demand margin. The results highlight impending market tightness and provide a quantitative framework for strategic capacity planning, capital allocation, and risk mitigation in the digital infrastructure sector, directly supporting data-driven management science applications.
References
ABAC. (2025). Powering the Digital Economy – The Data Center Dilemma. Asia Pacific Foundation of Canada. https://www.asiapacific.ca/sites/default/files/publication-pdf/Powering-the-Digital-Economy-The-Data-Center-Dilemma_WEB_0.pdf
Al-Atroshi, C., & Zeebaree, S. R. (2024). Distributed Architectures for Big Data Analytics in Cloud Computing: A Review of Data-Intensive Computing Paradigm. The Indonesian Journal of Computer Science, 13(2), 2389-2406. https://doi.org/10.33022/ijcs.v13i2.3812
Armstrong, J. S. (2001). Selecting forecasting methods. In Principles of forecasting: A handbook for researchers and practitioners (pp. 365-386). Boston, MA: Springer US. https://doi.org/10.1007/978-0-306-47630-3_16
Boamah, V. (2021). Forecasting the Demand of Oil in Ghana: A Statistical Approach. Management Science and Business Decisions, 1(1), 29-43. https://doi.org/10.52812/msbd.25
Bunn, D. W. (1996). Non-traditional methods of forecasting. European Journal of Operational Research, 92(3), 528-536. https://doi.org/10.1016/0377-2217(96)00006-9
CBRE. (2025). Global Data Center Trends 2025. CBRE. https://www.cbre.com/insights/reports/global-data-center-trends-2025
Cudjoe, D., Brahim, T., & Zhu, B. (2023). Assessing the economic and ecological viability of generating electricity from oil derived from pyrolysis of plastic waste in China. Waste Management, 168, 354-365. https://doi.org/10.1016/j.wasman.2023.06.015
Daim, T., & Suntharasaj, P. (2009). Technology diffusion: forecasting with bibliometric analysis and Bass model. Foresight, 11(3), 45-55. https://doi.org/10.1108/14636680910963936
Duarte, C., & Rua, A. (2007). Forecasting inflation through a bottom-up approach: How bottom is bottom?. Economic Modelling, 24(6), 941-953. https://doi.org/10.1016/j.econmod.2007.03.004
Gartner. (2024). Gartner Predicts Power Shortages Will Restrict 40% of AI Data Centers By 2027. Gartner. https://www.gartner.com/en/newsroom/press-releases/2024-11-12-gartner-predicts-power-shortages-will-restrict-40-percent-of-ai-data-centers-by-20270
Graf, H. G. (2002). Economic Forecasting for Management: Possibilities and Limitations. USA: Bloomsbury Publishing.
Hussain, A. (2024). The Tale of Technology: A Guide to Understanding Technology Business in the 21st Century. India: Notion Press.
Javed, S. A. (2023). Posterior Variance Test: Ex ante Evaluation of Grey Forecasting model. International Journal of Grey Systems, 3(1), 17-28. https://doi.org/10.52812/ijgs.71
Javed, S. A., & Cudjoe, D. (2021). A novel Grey Forecasting of Greenhouse Gas Emissions from four Industries of China and India. Sustainable Production and Consumption, 29, 777-790. https://doi.org/10.1016/j.spc.2021.11.017
Javed, S.A., Mahmoudi, A., Tao, L., & Dong, W. (2025). Electric vehicle stock forecasting and planning in the USA. Environment, Development and Sustainability. https://doi.org/10.1007/s10668-025-06659-6
Ju-Long, D. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288-294. https://doi.org/10.1016/S0167-6911(82)80025-X
Maak, N. (2022). Server Manifesto: Data Center Architecture and the Future of Democracy (Vol. 12). Berlin: Hatje Cantz Verlag.
Makridakis, S., & Bakas, N. (2016). Forecasting and uncertainty: A survey. Risk and Decision Analysis, 6(1), 37-64. https://doi.org/10.3233/RDA-150114
McKinsey. (2024). AI power: Expanding data center capacity to meet growing demand. McKinsey. https://www.mckinsey.com/industries/technology-media-and-telecommunications/our-insights/ai-power-expanding-data-center-capacity-to-meet-growing-demand
Moshiri, S., & Cameron, N. (2000). Neural network versus econometric models in forecasting inflation. Journal of forecasting, 19(3), 201-217. https://doi.org/10.1002/(SICI)1099-131X(200004)19:3%3C201::AID-FOR753%3E3.0.CO;2-4
Mossavar-Rahmani, F., & Zohuri, B. (2025). Forecasting the Future: How Artificial Intelligence Is Revolutionizing Global Energy Demand Prediction. Journal of Energy and Power Engineering, 19, 74-83. 10.17265/1934-8975/2025.02.004
Nookala, G. (2024). Adaptive data governance frameworks for data-driven digital transformations. Journal of Computational Innovation, 4(1), 1-20.
Nyman, R., Ormerod, P., Smith, R., & Tuckett, D. (2014, April). Big data and economic forecasting: A top-down approach using directed algorithmic text analysis. In Workshop on using big data for forecasting and statistics. European Central Bank (pp. 7-8).
Olorunlana, T. J. (2025). Securing the Global Cloud: Addressing Data Sovereignty, Cross-Border Compliance, and Emerging Threats in a Decentralized World. International Journal of Science, Architecture, Technology, and Environment, 2(5), 1394-1407. https://www.researchgate.net/publication/392079431
Ouali, M., Ramzan, B., Hanif, M. W., Bhatti, G. A., & Nawaz, M. (2024). Growth of Digital Infrastructure of China and USA: Application of Intelligent Grey Forecasting Model. International Journal of Grey Systems, 4(2), 23-31. https://doi.org/10.52812/ijgs.101
Pandey, A. K., Singh, P. K., Nawaz, M., & Kushwaha, A. K. (2023). Forecasting of non-renewable and renewable energy production in India using optimized discrete grey model. Environmental Science and Pollution Research, 30(3), 8188-8206. https://doi.org/10.1007/s11356-022-22739-w
Podrecca, M., & Sartor, M. (2023). Forecasting the diffusion of ISO/IEC 27001: a Grey model approach. The TQM Journal, 35(9), 123-151. https://doi.org/10.1108/TQM-07-2022-0220
Rajesh, R. (2025). Grey Data Analytics for Management and Social Sciences. Delhi: PHI Learning Pvt. Ltd.
Sanger, J., & Sriram, K. (2024). Global Data Centre – Insights 2024. Alvarez & Marsal. https://www.alvarezandmarsal.com/insights/global-data-centre-insights-2024
Shukla, S., Bisht, K., Tiwari, K., & Bashir, S. (2023). Comparative study of the global data economy. In Data economy in the digital age (pp. 63-86). Singapore: Springer Nature. https://doi.org/10.1007/978-981-99-7677-5_4
Tian, X., Wu, W., Ma, X., & Zhang, P. (2021). A new information priority accumulated grey model with hyperbolic sinusoidal term and its applications. International Journal of Grey Systems, 1(2), 5-19. https://doi.org/10.52812/ijgs.27
Tilson, D., Lyytinen, K., & Sorensen, C. (2010, January). Desperately seeking the infrastructure in IS research: Conceptualization of "digital convergence" as co-evolution of social and technical infrastructures. In 2010 43rd Hawaii International Conference on System Sciences (pp. 1-10). IEEE. https://doi.org/10.1109/HICSS.2010.141
TOI. (2025, Dec 21). Europe's biggest aerospace company Airbus wants to move critical systems away from AWS, Google and Microsoft; 'fear' this American law. Times of India.
Tsai, P. H., Berleant, D., Segall, R. S., Aboudja, H., Batthula, V. J. R., Duggirala, S., & Howell, M. (2023). Quantitative technology forecasting: a review of trend extrapolation methods. International Journal of Innovation and Technology Management, 20(04), 2330002. https://doi.org/10.1142/S0219877023300021
Wang, C. H., & Hsu, L. C. (2008). Using genetic algorithms grey theory to forecast high technology industrial output. Applied Mathematics and Computation, 195(1), 256-263.
Wang, M., & Wang, M. (2025). Forecasting the Demand for Human Resources in a Hospital using the Grey Forecasting Model. Management Science and Business Decisions, 5(1), 15–21. https://doi.org/10.52812/msbd.110
Xie, N. M., & Liu, S. F. (2009). Discrete grey forecasting model and its optimization. Applied Mathematical Modelling, 33(2), 1173-1186. https://doi.org/10.1016/j.apm.2008.01.011
Xu, Y., Zhou, C., & Lien, D. (2025). Forecasting weekly inflation in China with bottom-up, top-down, and combined frameworks. Applied Economics, 1-19. https://doi.org/10.1080/00036846.2025.2526852
.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Science Insight
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Creative Commons Non Commercial CC BY-NC: The work is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is properly attributed.
