解析用户使用自主AI助手的决策心理，揭示认知-情感-行为链条
Examining Users' Behavioural Intention to Use OpenClaw Through the Cognition--Affect--Conation Framework
- 基于认知-情感-行动框架，分析用户对AI系统的感知如何影响使用意愿
- 436名用户数据显示，个性化与智能感提升使用意愿，隐私担忧则抑制使用
- 适合研究AI产品设计、人机信任机制及用户采纳行为的学者与开发者
本研究基于认知-情感-行动（CAC）框架，探讨用户对OpenClaw系统的使用意愿。研究考察系统认知感知如何影响情感反应，并进一步塑造行为意图。促进因素包括感知个性化、感知智能性与相对优势，抑制因素包括隐私担忧、算法不透明性与感知风险。基于436名OpenClaw用户的调查数据，采用结构方程模型分析发现：积极感知增强用户态度，提升使用意愿；消极感知则加剧不信任，降低使用意愿。研究揭示了自主AI代理采纳背后的心理机制。
原文摘要 · Abstract (English)
This study examines users' behavioural intention to use OpenClaw through the Cognition--Affect--Conation (CAC) framework. The research investigates how cognitive perceptions of the system influence affective responses and subsequently shape behavioural intention. Enabling factors include perceived personalisation, perceived intelligence, and relative advantage, while inhibiting factors include privacy concern, algorithmic opacity, and perceived risk. Survey data from 436 OpenClaw users were analysed using structural equation modelling. The results show that positive perceptions strengthen users' attitudes toward OpenClaw, which increase behavioural intention, whereas negative perceptions increase distrust and reduce intention to use the system. The study provides insights into the psychological mechanisms influencing the adoption of autonomous AI agents.
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