Impact of service agents on customer satisfaction and loyalty: mediating role of Chatbots

IF 1.8 Q3 MANAGEMENT
Muhammad Hasnain Abbas Naqvi, Hongyu Zhang, Mishal Hasnain Naqvi, Li Kun
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引用次数: 0

Abstract

Purpose This study aims to determine whether or not fashion retail brands can maintain their essence by providing personalized care through conventional face-to-face interactions or the use of e-services. Design/methodology/approach An exploratory investigation is being conducted to attain this goal. According to the findings of this research, Chatbots have an impact on consumer loyalty. The quality of a Chatbot’s system, service and information are all critical to providing a positive consumer experience. Findings The study concluded that Chatbot e-services might potentially enable dynamic and fascinating interactions between firms and their consumers. To personalize a Chatbot, firms might change the tone of the language used. Customers are more likely to use a Chatbot if it resembles a real person, which increases their pleasure and confidence in the product. Originality/value More precisely, the emphasis of the inquiry was on Chatbot, a relatively new digital tool that offers user-friendly, personalized and one-of-a-kind support to customers. Using information supplied by consumers, the authors examine a five-dimensional model that gauges how customers feel about Chatbots in terms of their ability to communicate with users, offer amusement, be trendy, personalize interactions and solve problems.
客服座席对客户满意度和忠诚度的影响:聊天机器人的中介作用
目的本研究旨在确定时尚零售品牌是否可以通过传统的面对面互动或使用电子服务提供个性化护理来保持其本质。设计/方法/方法为了实现这一目标,正在进行一项探索性调查。根据这项研究的结果,聊天机器人对消费者忠诚度有影响。聊天机器人的系统、服务和信息的质量对于提供积极的消费者体验至关重要。研究结果该研究得出结论,聊天机器人电子服务可能会在公司和消费者之间实现动态而迷人的互动。为了使聊天机器人个性化,公司可能会改变所用语言的语气。如果聊天机器人像真人,客户更有可能使用它,这会增加他们对产品的乐趣和信心。创意/价值更准确地说,调查的重点是聊天机器人,这是一种相对较新的数字工具,为客户提供用户友好、个性化和独一无二的支持。利用消费者提供的信息,作者研究了一个五维模型,该模型衡量了客户对聊天机器人的感受,包括他们与用户沟通、提供娱乐、时尚、个性化互动和解决问题的能力。
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来源期刊
CiteScore
5.50
自引率
12.50%
发文量
52
期刊介绍: Journal of Modelling in Management (JM2) provides a forum for academics and researchers with a strong interest in business and management modelling. The journal analyses the conceptual antecedents and theoretical underpinnings leading to research modelling processes which derive useful consequences in terms of management science, business and management implementation and applications. JM2 is focused on the utilization of management data, which is amenable to research modelling processes, and welcomes academic papers that not only encompass the whole research process (from conceptualization to managerial implications) but also make explicit the individual links between ''antecedents and modelling'' (how to tackle certain problems) and ''modelling and consequences'' (how to apply the models and draw appropriate conclusions). The journal is particularly interested in innovative methodological and statistical modelling processes and those models that result in clear and justified managerial decisions. JM2 specifically promotes and supports research writing, that engages in an academically rigorous manner, in areas related to research modelling such as: A priori theorizing conceptual models, Artificial intelligence, machine learning, Association rule mining, clustering, feature selection, Business analytics: Descriptive, Predictive, and Prescriptive Analytics, Causal analytics: structural equation modeling, partial least squares modeling, Computable general equilibrium models, Computer-based models, Data mining, data analytics with big data, Decision support systems and business intelligence, Econometric models, Fuzzy logic modeling, Generalized linear models, Multi-attribute decision-making models, Non-linear models, Optimization, Simulation models, Statistical decision models, Statistical inference making and probabilistic modeling, Text mining, web mining, and visual analytics, Uncertainty-based reasoning models.
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