消费者使用在线购物应用程序的意图:比较分析
Mingqiang He1, Thuy Dung Pham Thi2, Huy Mach Tran3
1Zhejiang Shuren University, No.8 Shuren street, Hangzhou, Zhejiang, China.
Acta psychologica
|August 16, 2025
概括
这项研究发现,计划行为理论 (TPB) 和集成模型最能预测在线购物应用程序的使用情况. 提高应用程序功能和用户自我效能是增加应用程序采用率的关键.
科学领域:
- 行为经济学是一种行为经济学.
- 信息系统信息系统信息系统
- 消费者心理学 消费者心理学
背景情况:
- 了解消费者对在线购物应用程序的采用在数字经济中至关重要.
- 像TAM和TPB这样的现有模型提供了洞察力,但可能没有完全捕捉到采用驱动器.
- 整合任务技术合适 (TTF) 可以提供更全面的理解.
研究的目的:
- 实证地比较TAM,TPB,集成TAM/TPB和集成TAM/TTF模型的预测能力.
- 确定影响消费者使用在线购物应用的关键因素.
- 为增强在线购物应用程序的采用提供实际影响.
主要方法:
- 调查数据来自越南293名在线购物应用用户.
- 使用LISREL 12进行结构方程建模 (SEM).
- 四个理论模型的比较:TAM,TPB,TAM/TPB和TAM/TTF.
主要成果:
- 这四种模型都在解释使用意图方面表现出有效性.
- TPB和集成的TAM+TPB模型显示出最高的解释能力.
- 自我有效性和TTF,以及感知到的有用性和态度,显著影响了使用意图.
结论:
- 结合自效和TTF的综合模型为在线购物应用使用意图提供了更好的解释能力.
- 应用程序的特性如灵活性,互动性和兼容性至关重要.
- 开发人员应该专注于改进应用程序功能并提高用户的自我效能,以推动应用的采用.
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