Authors - Marybell Materum, Daniel Dasig Jr, Lucila Magalong, Emelyn Libunao, Shirley Padua, Sonia Pascua, Rizza Gerente and Sharon Sanchez Abstract - Broadband infrastructure has become a critical enabler of digital trans formation, technological competitiveness, and economic sustainability across OECD economies. This study proposes a hybrid technological intelligence framework integrating descriptive analytics, temporal trend modeling, compara tive broadband evaluation, and predictive business interpretation using OECD broadband subscription datasets. The dataset comprised 11,324 broadband obser vations covering fixed, mobile, and fiber-optic technologies across multiple countries and annual periods. A quantitative explanatory research design was em ployed using statistical preprocessing, longitudinal analysis, and machine learn ing-oriented analytical procedures to identify broadband growth dynamics and digital infrastructure disparities. Results revealed substantial asymmetry in broadband adoption patterns, with the United States, Japan, Korea, France, and the United Kingdom demonstrating dominant subscription trajectories and accel erated digital infrastructure expansion. Fiber-optic and mobile broadband tech nologies exhibited the highest growth rates, particularly after 2018, reflecting in tensified digital transformation and remote connectivity demands. The findings demonstrate that broadband intelligence analytics can support strategic business forecasting, digital competitiveness evaluation, telecommunications planning, and evidence-based policy formulation within Industry 4.0 and smart governance ecosystems.
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