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智能机器人的拟人化特征显著影响顾客使用意愿。基于社会认知理论、恐怖谷理论和情绪一致性理论，本文深入探讨了智能机器人拟人化特征的匹配策略对顾客使用意愿的影响，并考察了顾客技术焦虑和顾客外向性在这一过程中的调节作用。实证研究结果表明，智能机器人有用性和温暖的不匹配策略能显著提升顾客使用意愿。随着顾客技术焦虑提升，以有用性为核心的积极效应会逐渐降低；随着顾客外向性增加，以温暖为中心的积极效应会逐渐减弱。因此，酒店管理者应该依据顾客特征提供合适的智能机器人匹配策略。对于技术焦虑较低的顾客来说，应优先实施以有用性为中心的智能机器人匹配策略，以提高顾客的使用意愿和满意度；对于外向性较低的顾客来说，应更多地采用以温暖为中心的智能机器人匹配策略，以增强顾客与智能机器人的情感联系和互动体验。通过合理的匹配策略，酒店管理者可以更好地满足顾客的需求，提升服务质量和顾客忠诚度。
Abstract：Based on social cognitive theory, the uncanny valley theory, and the theory of emotional congruence, this paper thoroughly explores the impact of anthropomorphic features of intelligent robots and the matching strategies on customers' willingness to use them. The paper also examines the moderating effects of customer technology anxiety and customer extraversion in this process. Empirical research results indicate that mismatch strategies of usefulness and warmth of intelligent robots can significantly enhance customers' willingness to use them. As customer technology anxiety increases, the positive effect centered on usefulness gradually diminishes, and as customer extraversion rises, the positive effect centered on warmth gradually weakens. Therefore, hotel managers should provide appropriate intelligent robot matching strategies based on customer characteristics. For customers with lower levels of technology anxiety, priority should be given to implementing intelligent robot matching strategies centered on usefulness to enhance their willingness to use and satisfaction. For customers with lower levels of extraversion, more strategies centered on warmth should be adopted to enhance their emotional connection and interactive experience with intelligent robots. Through reasonable matching strategies, hotel managers can better meet customer needs, improve service quality, and enhance customer loyalty.
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基本信息:
DOI：10.16366/j.cnki.1000-2359.2024.01.13
中图分类号:F719.2;F274;F713.55;TP242
引用信息:
[1]李纲,张铎.智能机器人服务效应与顾客使用意愿的匹配策略——基于纵向跟踪调查的实证研究[J].河南师范大学学报(哲学社会科学版),2024,51(01):93-98.DOI:10.16366/j.cnki.1000-2359.2024.01.13.
基金信息:
河南省高等学校哲学社会科学创新团队支持计划(2024-CXTD-10)
2024-01-05
2024-01-05
2024-01-05