Journal ArticleOpen Access
Understanding and predicting customers’ intentions to use smartphone-based online games: A deep-learning-based dual-stage modelling analysis
Author Affiliations
North South University, Pôle Léonard de Vinci, Qatar University, Bangladesh University of Professionals
Published InComputers in Human Behavior
Year2023
Citations5
Abstract
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 explores the mediating effects of customers’ perceived flow and engagement between attitudes and their intention to use smartphone-based online gaming. Furthermore, customer 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 their intention to use smartphone-based online gaming. The study further confirms that perceived flow and customer engagement mediate the relationship…
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Fields & Keywords
Social SciencesDecision SciencesInformation Systems and ManagementTechnology Adoption and User BehaviourDigital Marketing and Social MediaFlow Experience in Various FieldsApplied psychologySocial psychologyHuman–computer interactionMathematics educationArtificial intelligenceNeuroscienceProgramming languageLiterature