Purpose: The purpose of this paper is to analyze user behavior toward multi-screen services by employing neural networks to predict overall customer satisfaction and to prioritize the factors that influence customer intentions. Design/methodology/approach: Multi-screen experiences require a new approach incorporating multiple methods. A proposed multi-state analytic approach in which the research model is tested using structural equation modeling was utilized. The results were then used as inputs for a neural network model to predict multi-screen adoption. Findings: The findings indicate that multi-screen quality significantly influences usability, which subsequently affects the adoption of the technology. Practical implications: The policy and managerial implications of multi-screen development are discussed based on the models of acceptance and diffusion. Social implications: The emergence of multi-screen services as well as the simultaneous and sequential engagement of users with multiple devices throughout the day challenges the ability of marketers to develop effective communication strategies. Originality/value: This study provides an in-depth analysis and heuristic data regarding user drivers, market dynamics, and policy implications in the one-source multi-use ecosystem.
All Science Journal Classification (ASJC) codes
- Economics and Econometrics
- Sociology and Political Science
- Multi-device experience
- Multi-screen strategy
- Neural network
- One-source multi-use