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

适度 心理学 构造(python库) 形成性评价 对偶(语法数字) 计划行为理论 认知 技术接受模型 应用心理学 社会心理学 可用性 计算机科学 人机交互 数学教育 控制(管理) 人工智能 神经科学 程序设计语言 艺术 文学类
作者
Muhammad Sabbir Rahman,Surajit Bag,Farhana Habib Zinnia,Nripendra P. Rana,Mohammad Osman Gani
出处
期刊:Computers in Human Behavior [Elsevier]
卷期号:152: 108083-108083
标识
DOI:10.1016/j.chb.2023.108083
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 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 between attitudes and their 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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