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.

Exploring the relationship between chatbots, service failure recovery and customer loyalty: A frustration–aggression perspective / Ozuem, Wilson; Ranfagni, Silvia; Willis, Michelle; Salvietti, Giada; Howell, Kerry. - In: PSYCHOLOGY & MARKETING. - ISSN 0742-6046. - 41:10(2024), pp. 2253-2273. [10.1002/mar.22051]

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

Ranfagni, Silvia;Salvietti, Giada;
2024-01-01

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.
2024
Exploring the relationship between chatbots, service failure recovery and customer loyalty: A frustration–aggression perspective / Ozuem, Wilson; Ranfagni, Silvia; Willis, Michelle; Salvietti, Giada; Howell, Kerry. - In: PSYCHOLOGY & MARKETING. - ISSN 0742-6046. - 41:10(2024), pp. 2253-2273. [10.1002/mar.22051]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11381/3000533
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