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Many firms are investing in digital services to improve customer experiences. Virtual service agents, or “e-service agents” (“e-agents”) such as chatbots, are examples of these efforts. Chatbots are types of virtual-assistant software programs that interact with users through speech or text. This paper aims to investigate whether the perceived hedonic and utilitarian attributes of chatbots can influence customer satisfaction and, consequently, their relationships with brands.

Data were collected through a questionnaire-based survey among a sample of Italian consumers. A convenience sampling technique was used. Data were then analyzed through Partial Least Squares Structural Equation Modeling to provide a prediction-oriented model assessment. The findings were then complemented with an importance–performance map analysis (IPMA) to gain more detailed insights and actionable guidelines for managers.

The findings highlighted that the perceived hedonic and utilitarian attributes of chatbots positively influenced customer satisfaction and improved customer relationships with the brands. However, the IMPA highlighted that the performance levels of two most important attributes – system quality and experience with chatbot – could be improved resulting in additional improvements of customer satisfaction.

This study suggests the importance of firms’ investments in and adoption of e-agents to strengthen consumer–brand relationships and of considering both the hedonic and utilitarian attributes of their e-agents.

This article attempts to enrich and consolidate the growing body of literature concerning the impacts of new technologies – and, specifically, chatbots – in service marketing.

Based on stimulus-organism-response theory, this study aims to explore how digital service communication strategies affected customers’ e-service agent use intentions through perceived warmth and competence.

A 2 × 2 scenario-based experiment was conducted to test the proposed relationships.

Findings indicated when a high-authority conversation party was engaged in digital service communications, customers showed higher e-service agent use intentions through perceived warmth and competence in an emoji-presence conversation style.

To the best of the authors’ knowledge, this study is the first to explore the effects of digital service communication strategies on customers’ internal and behavioral responses.

基于刺激-有机体-反应理论, 本研究探讨了数字服务沟通策略如何通过感知亲切和感知能力的方式影响了顾客对电子服务代理的使用意愿。

本研究进行了一项基于2x2情境的实验, 以测试所提出的关系。

研究结果表明, 当高权威的对话方参与数字服务沟通时, 顾客在表情存在的对话风格中通过亲切和能力的认知表现出更高的电子服务代理使用意愿。

本研究调查了对话方和对话方式作为数字服务沟通策略在顾客-数字服务互动中的影响。

本研究是第一个探讨数字服务沟通策略对顾客内部和行为反应影响的研究。

The concept and practice of e-services has become essential in business transactions. Yet there are still many organizations that have not developed e-services optimally. This is especially relevant in the context of Indonesian Airline companies. Therefore, many airline customers in Indonesia are still in doubt about it, or even do not use it. To fill this gap, this study attempts to develop a model for e-services adoption and empirically examines the factors influencing the airlines customers in Indonesia in using e-services offered by the Indonesian airline companies. Taking six Indonesian airline companies as a case example, the study investigated the antecedents of e-services usage of Indonesian airlines. This study further examined the impacts of motivation on customers in using e-services in the Indonesian context. Another important aim of this study was to investigate how ages, experiences and geographical areas moderate effects of e-services usage.

The study adopts a positivist research paradigm with a two-phase sequential mixed method design involving qualitative and quantitative approaches. An initial research model was first developed based on an extensive literature review, by combining acceptance and use of information technology theories, expectancy theory and the inter-organizational system motivation models. A qualitative field study via semi-structured interviews was then conducted to explore the present state among 15 respondents. The results of the interviews were analysed using content analysis yielding the final model of e-services usage. Eighteen antecedent factors hypotheses and three moderating factors hypotheses and 52-item questionnaire were developed. A focus group discussion of five respondents and a pilot study of 59 respondents resulted in final version of the questionnaire.

In the second phase, the main survey was conducted nationally to collect the research data among Indonesian airline customers who had already used Indonesian airline e-services. A total of 819 valid questionnaires were obtained. The data was then analysed using a partial least square (PLS) based structural equation modelling (SEM) technique to produce the contributions of links in the e-services model (22% of all the variances in e-services usage, 37.8% in intention to use, 46.6% in motivation, 39.2% in outcome expectancy, and 37.7% in effort expectancy). Meanwhile, path coefficients and t-values demonstrated various different influences of antecedent factors towards e-services usage. Additionally, a multi-group analysis based on PLS is employed with mixed results. In the final findings, 14 hypotheses were supported and 7 hypotheses were not supported.

The major findings of this study have confirmed that motivation has the strongest contribution in e-services usage. In addition, motivation affects e-services usage both directly and indirectly through intention-to-use. This study provides contributions to the existing knowledge of e-services models, and practical applications of IT usage. Most importantly, an understanding of antecedents of e-services adoption will provide guidelines for stakeholders in developing better e-services and strategies in order to promote and encourage more customers to use e-services. Finally, the accomplishment of this study can be expanded through possible adaptations in other industries and other geographical contexts.

Taking into account the importance of e‐commerce and the current applications of AI techniques in this area, this research aims to adequate the design of a multi‐agent system for the provisioning of e‐services in u‐commerce environments. This proposal is centred on the methods of evaluation in a u‐e‐commerce environment.

The multi‐agent systems (MAS) approach is based on an MAS model developed for AmI that has been redesigned to support u‐commerce. The use of a recommendation system, previously developed by the research group, is suggested for this MAS. The methodological proposal centres on the evaluation of this type of system.

The evaluation of this type of system is the principal problem of current research. Therefore, this is the main contribution of the paper.

The different evaluation methods that are proposed, whether qualitative or quantitative, offer the possibility of measuring the added value that the context can give to the use of e‐services in different domains of application. Qualitative evaluation should consider the customer as a central piece in the system. In addition, quantitative methods should objectively evaluate the contribution of context to the application.

At present, there is no single method for evaluating the benefits of different u‐commerce systems, so a new method needs to be found based on these techniques.

The research proposes an MAS designed for u‐commerce domains, analyzes the capacity of trust management techniques in this environment, and proposes several evaluation methods to show the benefits of context information in the use of e‐services. Several real developments are described to show the different applications of MAS in u‐commerce and how evaluation is carried out.

The purpose of this study is to measure the perception and the behavioural intention of web-users who interact with a virtual agent on a web site. The author wants to measure the added value of this technology in terms of providing e-service and measure web-users' desire to have a concrete experience with a firm after experiencing its web site.

The author integrated a virtual agent on a restaurant's web site and conducted an online survey. The author asked respondents to interact with the virtual agent and then fill in the questionnaire. The author used the expanded version of the technology acceptance model (TAM) for measuring the intention of potential customers to accept a new technology and for evaluating the characteristics of the virtual agent. In order to measure the e-service quality, the author adapted items of WebQual to restaurant industry. As the author had several latent variables, the author used partial least squares (PLS), a variance-based structural equation modeling method.

Results show that the utilitarian and hedonic values of the virtual agent increase significantly the desire of potential clients to experiment the restaurant. Hedonic value seems to play a major role. This is a crucial factor for restaurant and hotel industries which can be considered as hedonic industries.

This research can help firms to manage relationships with current and potential clients through their web site. The nature of the company plays an important role in the success of the virtual agent's implementation. Even if in the case the author applied the virtual agent to a hedonic industry, a lot of companies in other sectors can benefit from having a virtual agent, especially if the company in question is service-oriented (e.g. bank, airline, etc.).

According to the author's knowledge, virtual agents have never been applied to restaurant/hotel industries before. The results of this research significantly advanced the understanding of the impact of virtual agents, especially in the hospitality industry. Moreover, the author applied the TAM to the characteristics of virtual agent, which is very new for the academic world. Finally, the framework the author presented in this research could be used as a basis of measurement of virtual agent effectiveness.

Reverse engineering methodology paves an efficient way for simulating and manufacturing existing objects with complex shapes, and a range of applications also has shown this approach to be feasible and efficient. However, in many applications, a lot of sub‐tasks in reverse engineering are usually not done in the same place, they need to be done cooperatively over the Internet or Intranet. So, this paper is concerned with developing a novel e‐service platform for remote service in reverse engineering applications based on mobile agent technology, and some correlative enabling technologies such as data compression, security considerations, agent models and so on. The framework was programmed using the Java Sevlets and Java Beans component models, and data transferring and processing were implemented based on the dispatch/retract mechanisms of mobile agents. The mobile agent is developed with IBM's Aglets Workbench, and the feasibility of the proposed method has been verified by a case.

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.

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.

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.

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.

This study aims to investigate the impact of AI chatbots on customer trust in AI chatbots for hotel services.

The probability sampling method was employed to develop a research sample. The research uses correlation analysis and structural equation modeling to analyze the data of 413 valid observations collected in the structured questionnaire survey in Vietnam.

The paper reports that empathy response, anonymity and customization significantly impact interaction. Empathy response is found to be the strongest influence on interaction. Meanwhile, empathy response and anonymity were revealed to indirectly affect customer trust. This paper also contributes several implications for hotel providers in emerging economies.

To the best of the authors’ knowledge, this is the first study to shed light on the role of AI chatbots in explaining customers’ behavior. The results provide an enhanced understanding of how the AI chatbot system influences customers’ decision-making. It has been used to plan the chatbot application and highlight which implementation issues need the most attention in the hospitality industry.

This study aims to explore the role of artificial intelligence (AI)-powered chatbot marketing efforts (CMEs) in the establishment of relationships between brands and their customers, extending the link between relationship marketing and online consumer behavioral intentions.

Data are collected from 1,072 customers in the USA, who used chatbot marketing activities from any of 30 brands leading their industries in messaging innovation. Structural equation modeling is used for data analysis.

Results show that interaction, information, accessibility, entertainment and customization are important CMEs components. CMEs have significant direct effects on the quality of communication with chatbot agents and indirectly affect customer–brand relationships (CBR) and customer response. In addition, the findings demonstrate that CBR mediates the association between communication quality and customer response.

Implications of this study can enable practitioners to understand the effects of AI on user experiences and provide a guide for the development of CMEs strategies and relationship building.