消费者对智能手表的意图中的心理因素:关于技术采用和行为行为的研究
1Decision Science and Information Systems Area, Indian Institute of Management Nagpur, 441108, India.
Acta psychologica
|January 10, 2026
概括
心理因素显著影响智能手表购买意图. 机器学习模型,特别是CatBoost,准确地预测消费者对可穿戴技术采用的行为.
科学领域:
- 心理学与技术 心理学与技术
- 消费者行为 消费者行为
- 可穿戴技术的采用 可穿戴技术的采用
背景情况:
- 消费者对智能手表的意图是复杂的,受到各种心理因素的影响.
- 了解这些驱动因素对于技术采用和营销策略至关重要.
- 现有的研究往往忽视了可穿戴设备的心理和技术方面之间的相互作用.
研究的目的:
- 为了确定预测消费者购买智能手表的购买意图的关键心理因素.
- 分析动机,技术亲和力,社会影响力,感知价值和品牌影响力的作用.
- 应用机器学习来发现可穿戴技术采用的重要心理驱动因素.
主要方法:
- 从消费者那里收集关于智能手表购买意向的调查数据.
- 机器学习模型的应用,包括CatBoost,随机森林,梯度提升和XGBoost.
- 基于准确性和AUC-ROC指标的模型的性能评估.
主要成果:
- CatBoost分类器表现出卓越的性能,准确度为86%,AUC-ROC为0.90.
- 基于集体的机器学习算法有效地识别了购买意向的心理和行为决定因素.
- 关键预测因素包括健康动机,技术亲和力,社会影响,感知价值和品牌影响.
结论:
- 技术和心理社会因素相互作用,在可穿戴设备市场上塑造消费者行为.
- 为了理解和预测技术采用,全面的心理观点是必不可少的.
- 机器学习为在智能设备的背景下解剖复杂的消费者决策过程提供了强大的工具.
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