Predicting Sustainable Media Innovation Adoption: Multi-Model Analysis of AI Diffusion in Emerging Markets
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Abstract
The given paper will discuss the diffusion of artificial intelligence (AI) in the emerging markets and how this impacts the sustainable media innovation. We come up with a multi-model model that integrates ARIMA time-series forecasting, use of proportional adoption rate with beta regression and binary adoption rate with logistic regression. On a monthly adoption indicator of 2020-2025, and a firm level covariate (with more focus on firm size), we identify a transparent regime shift around 2023-2024: the adoption switches to a long plateau of the high-forty percent range to a stable higher equilibrium of the low-fifties. Estimates of beta indicate higher rates of adoption in larger companies and logistic outcomes indicate a steep, non-linear growth in the probability of adoption when organizational capacity crosses a threshold, and then levels off. Cumulative logistic S-curve displays the milestones of diffusion and maturity in the market approximately 80-90 percent of the potential level. Combined, the models offer convergent evidence that diffusion trajectories are determined by resource asymmetries. Recommendations can be categorized under policy and management such as specific support of SMEs, investment in digital infrastructure and skills to promote inclusive and sustainable media ecosystems. The study's main limitations are discussed, along with recommendations for future longitudinal validation.
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Publication Details
- Type of Publication:
- Conference Name: "International Conference on Challenges and Trends in Arts and Social Sciences (ICCTASS 2025)"
- Date of Conference: 11/12/2025 - 11/12/2025
- Venue: American International University-Bangladesh
- Organizer: Faculty of Arts and Social Sciences