Study on the Factors Affecting the Adoption of AI-Based Churn Prediction Models in the OTT Industry

Abstract

In the study A Study on the Factors Affecting the Adoption of AI-Based Churn Prediction Models in the OTT Industry, an in-depth analysis is conducted to uncover the critical determinants influencing the integration of artificial intelligence (AI) for churn prediction within the Over-the-Top (OTT) media services sector. The research employs a robust methodology, incorporating Partial Least Squares Structural Equation Modelling (PLS-SEM) and Importance-Performance Map Analysis (IMPA) to dissect the data obtained from industry professionals. A purposive sampling technique was utilized for the study, targeting individuals familiar with churn prediction models. The sample size, determined using G* Power software, was set at 600 respondents to ensure statistical accuracy and robustness of the results, surpassing the minimum required size of 436.
Central to the findings is the significant role of organizational factors, underscoring the necessity of an enabling internal environment for the adoption of AI-driven solutions. This includes aspects like company culture, management support, and readiness for technological advancements. The study also highlights the considerable influence of perceived usefulness and ease of use on the adoption decision, stressing the importance of user-centric design and clear benefits in technology acceptance.
In contrast, technology factors, though relevant, exhibit a lower impact on adoption decisions, suggesting that technical attributes alone are not the primary motivators for adopting these models. External factors like market trends and regulatory considerations also show moderate importance, indicating their secondary role in the adoption process.
The study concludes by emphasizing the need for OTT organizations to focus on enhancing internal readiness and clearly articulating the practical benefits of AI technologies. These insights offer a strategic direction for OTT service providers and technology developers, pointing towards a balanced approach that considers both organizational readiness and the tangible benefits of AI in churn prediction.
Keywords: Artificial Intelligence, Churn Prediction, OTT Industry, Organizational Factors, Technology Adoption