Factors Behind Virtual Reality (VR) Enactment for Netflix Watching in Pakistan: An Integrated SEM-ANN-based Study

Keywords: Netflix, Virtual Reality, Perceived Ease of Use, Pakistan, Behavioral Intention


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From the Netflix perspective, "entertainment is just like you eat buffet." In this regard, Netflix services prefer to deploy modern technology solutions that facilitate the consumers regularly. By keeping in view the potential integration of modern technology in Netflix watching, the current study adopted an integrated SEM-ANN technique to scrutinize some basic characteristics of Netflix as dynamic mechanisms of Virtual Reality (VR) adoption in Pakistan. The current research used a self-proposed study model and randomly selected a sample of n= 400 students from n= 4 private sector universities in Islamabad. The analysis, using Structural Equation Modelling (SEM) results, indicated several significant associations. Specifically, it was observed that social influence, satisfaction, and relevance were notably linked with Netflix usage. Additionally, there was a robust and statistically significant relationship between Netflix usage, perceived ease of use, and behavioral intention. Furthermore, perceived ease of use and behavioral intention demonstrated significant correlations with virtual reality adoption. In the subsequent Artificial Neural Network (ANN) analysis, an accuracy of 51.1% was achieved during the training phase and a further improvement to 54.4% during the testing phase. In light of these results, while adopting technology in Pakistan may have been relatively gradual, the transition from conventional media to social TV, integrated with VR, marks the inception of a new technological era in the country. This shift holds important implications for the media landscape and consumer behavior. Finally, the study limitations and contributions have also been discussed accordingly.


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How to Cite
Ali, S., Pasha, S., & Hashmat, S. (2023). Factors Behind Virtual Reality (VR) Enactment for Netflix Watching in Pakistan: An Integrated SEM-ANN-based Study. UMT Artificial Intelligence Review, 3(2). https://doi.org/10.32350/umt-air.32.03