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

Author:

Ozuem Wilson1,Ranfagni Silvia2ORCID,Willis Michelle3ORCID,Salvietti Giada4,Howell Kerry5

Affiliation:

1. University for the Creative Arts Farnham UK

2. University of Florence Florence Italy

3. London Metropolitan University London UK

4. University of Parma Parma Italy

5. Northumbria University Newcastle upon Tyne UK

Abstract

AbstractAn 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.

Publisher

Wiley

Reference98 articles.

1. Determining behavioural differences of Y and Z generational cohorts in online shopping

2. Amed I. Balchandani A. Berg A. Harreis H. Hurtado M. af Petersens S. Roberts R. &Sanchez Altable C.(2022 May 2). State of fashion technology report 2022. McKinsey & Company.https://www.mckinsey.com/industries/retail/our-insights/state-of-fashion-technology-report-2022

3. It's all part of the customer journey: The impact of augmented reality, chatbots, and social media on the body image and self‐esteem of Generation Z female consumers

4. “A Large Playground”: Examining the Current State and Implications of Conversational Agent Adoption in Organizations

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3