Exploring the relationship between chatbots, service failure recovery and customer loyalty: A frustration–aggression perspective

Wilson Ozuem, S. Ranfagni, Michelle Willis, Giada Salvietti, Kerry Howell
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Abstract

An increasing number of companies are introducing chatbot‐led contexts in service failure recovery. Existing studies are inconclusive on whether humanlike chatbot‐driven service failure recovery enhances customer loyalty. Grounding our work in phenomenological hermeneutics and utilizing frustration–aggression theory, we concentrate on the historical circumstance and the participatory nature of understanding customers' chatbot‐driven interactions and loyalty. We conducted 47 in‐depth interviews with millennials from four countries (United States, France, Italy, and the United Kingdom). By analyzing interview data through thematic analysis, our study offers two significant contributions. First, through thematic analysis, we define the dynamics occurring between customers and chatbots in a service recovery journey, such as customers' priorities and expectations. Second, we present a chatbot‐led service failure recovery typology framework that identifies four types of customers based on their interactions with a chatbot and their emotions, specifically frustration and aggression, and the effects of the interactions on their brand loyalty and intention to use chatbots. The identification of four customer types can help managers shape strategies to effectively turn negative customer experiences into opportunities to strengthen their loyalty, such as making more than one touchpoint available (human and chatbot). Our study shows that customers' emotions, specifically frustration and aggression, affect not only customer loyalty but also technology adoption. The concluding section suggests future avenues for research in the service recovery literature.
探索聊天机器人、服务故障恢复与客户忠诚度之间的关系:挫折-攻击视角
越来越多的公司在服务故障恢复中引入了聊天机器人。现有研究对类似人类的聊天机器人驱动的服务故障恢复是否能提高客户忠诚度尚无定论。我们的工作以现象学诠释学为基础,利用挫折-攻击理论,专注于了解客户在聊天机器人驱动下的互动和忠诚度的历史环境和参与性质。我们对来自四个国家(美国、法国、意大利和英国)的千禧一代进行了 47 次深入访谈。通过对访谈数据进行主题分析,我们的研究做出了两项重大贡献。首先,通过主题分析,我们确定了客户和聊天机器人在服务恢复过程中的动态关系,如客户的优先事项和期望。其次,我们提出了一个聊天机器人主导的服务故障恢复类型学框架,根据客户与聊天机器人的互动、客户的情绪(尤其是挫败感和攻击性)以及互动对客户品牌忠诚度和使用聊天机器人意愿的影响,确定了四种类型的客户。确定四种客户类型有助于管理者制定战略,有效地将负面客户体验转化为增强客户忠诚度的机会,例如提供多个接触点(人工和聊天机器人)。我们的研究表明,客户的情绪,尤其是挫败感和攻击性,不仅会影响客户忠诚度,还会影响技术的采用。结论部分提出了服务恢复文献的未来研究方向。
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