Understanding and predicting customers' intentions to use smartphone-based online games: A deep-learning-based dual-stage modelling analysis

COMPUTERS IN HUMAN BEHAVIOR(2024)

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摘要
Building upon flow theory, the present research empirically investigates the impact of customers' attitudes on their intention to use smartphone-based online gaming. It also examines the mediating effects of customers' perceived flow and engagement between attitudes and customer's intention to use smartphone-based online gaming. Furthermore, customers' cognitive involvement was also examined as a moderator in between attitude and perceived flow. The data were analysed using a dual-stage hybrid method embedded with PLS-SEM and ANN. A sample of 688 smartphone-based online game players was surveyed, and the results support the notion that customers' attitudes, considered as a formative construct, significantly influence intention to use smartphone-based online gaming. The study further confirms that perceived flow and customer engagement mediate the relationship between attitudes and intention to use smartphone-based online gaming. The study also identifies the role of cognitive involvement as a significant moderator in between customers' attitudes and perceived flow. Contributions for both theory and practice are presented in the concluding sections.
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关键词
Online gaming,Smartphone,Attitude,Perceived flow,Customer intention,PLS-SEM,Artificial neural network
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