工商管理学院知识库

随着人工智能技术的不断进步，聊天机器人在营销领域的运用日渐深入，其功能定位也由早期的任务辅助者跃升至承载多重职能的社会互动角色。学术界关于聊天机器人角色（如助手、仆人、专家、朋友等）的探究，大多数基于技术接受模型、任务技术匹配理论等传统框架，分析它们对消费者的品牌满意度及购买意愿等产生的影响。作为模拟人类交互模式与消费者进行深度互动的关键角色，聊天机器人推荐在消费者购买决策过程中的作用不断增强。关于聊天机器人角色对消费者推荐接受意愿的作用机制有待深入探讨。特别是在不同服务情境下，聊天机器人角色如何发挥最大化效应的作用机制仍待商榷。

本文从消费者对于聊天机器人功能/情感的诉求出发，结合具体的智能推荐服务场景，提出以下问题：比较聊天机器人在扮演“助手”和“朋友”两种社会角色的情境下，消费者对其的信任存在怎样的差异？不同服务环境下消费者对聊天机器人角色期望及信任需求的差异化特征？企业应该匹配哪种聊天机器人角色提升消费者推荐接受意愿？研究结论对企业在设计与应用聊天机器人时具有何种实际指导价值？

综上，本文基于SOR理论和社会交换理论，梳理聊天机器人角色、服务类型、消费者推荐接受意愿等相关研究文献，理清了聊天机器人角色对消费者推荐接受意愿的作用机理。通过实验发现：助手型聊天机器人更能激发消费者的认知信任；朋友型聊天机器人更能激发消费者的情感信任；对体验服务，朋友型聊天机器人角色更能促进消费者的情感信任，进而提高消费者的推荐接受意愿。相反，对信任服务，助手型聊天机器人角色更能促进消费者的认知信任，进而提高消费者的推荐接受意愿。通过深入探究聊天机器人角色对消费者推荐接受意愿的影响机制，不仅可以推动聊天机器人服务能力的优化升级，而且还能为企业提供有效的指导策略，使其能够更精准地服务于顾客。

With the continuous advancement of artificial intelligence technology, chat robots are increasingly used in the field of marketing, and their functional positioning has also jumped from early task assistants to social interaction roles that carry multiple functions. Most of the academic research on the role of chat robots (such as assistants, servants, experts, friends, etc.) is based on traditional frameworks such as technology acceptance model and task technology matching theory to analyze their impact on consumers' brand satisfaction and purchase intention. As a key role in simulating the deep interaction between human interaction mode and consumers, chatbot recommendation plays an increasingly important role in consumers' purchasing decision-making process. The mechanism of the role of chatbots on consumers' willingness to accept recommendations needs to be further explored. Especially in different service situations, the mechanism of how the role of chatbots maximizes the effect remains to be discussed.

Based on the consumer's appeal for the function/emotion of the chat robot, combined with the specific intelligent recommendation service scenario, this paper puts forward the following questions: What are the differences in consumers' trust in the two social roles of "assistant"and" friend" in the chat robot? Different characteristics of consumers' role expectations and trust needs for chatbots in different service environments? What kind of chat robot roles should enterprises match to enhance consumers' willingness to accept recommendations? What practical guiding value does the research conclusion have for enterprises in the design and application of chat robots?

In summary, based on SOR theory and social exchange theory, this paper sorts out relevant research literature on the role of chat robots,  service types, and consumers' willingness to accept recommendations, and clarifies the mechanism of the role of chat robots on consumers' willingness to accept recommendations. Through experiments, it is found that the assistant chat robot can better stimulate consumers' cognitive trust; friendly chat robots can stimulate consumers' emotional trust; for experience service, the role of friend chat robot can promote consumers' emotional trust, and then improve consumers' willingness to accept recommendations. On the contrary, for trust services, the assistant chatbot role can promote consumers' cognitive trust and thus improve consumers' willingness to accept recommendations. By deeply exploring the influence mechanism of the role of chatbots on consumers' willingness to accept recommendations, it can not only promote the optimization and upgrading of chatbot service capabilities, but also provide effective guidance strategies for enterprises to enable them to serve customers more accurately.