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The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.

Digital influencers, besides being a personal branding phenomenon, constitute, nowadays, important partners for brands in the digital environment. Despite the benefits for both parties, the brand and the endorser, there is a risk when the individuals or the brand take part in some scandal or questionable activity, which causes a loss of credibility and reputation. The contagious effect of personal or corporate brand crisis with the partners is well reported in the literature. However, there are no studies about such occurrence in the digital environment, considering that the phenomenon of digital influence has some particularities differing from traditional celebrity endorsement. This chapter focuses on the research of the consequences of a change in the credibility of influencers or brands, after the occurrence of a negative situation, and the way in which this change affects the two parties involved, the brand and the influencer. We conducted a netnographic study of the social media pages of three digital influencers and the social media pages of a recognized fast fashion brand recognized in the digital world. We analyzed 1500 social media comments from their audiences and found that influencers suffer from a loss in sympathy and credibility by scandals while crisis communication strategies in corporate brands can prevent such damages. Strategic implications for brand managers and digital influencers managing their endorsements are addressed in the discussion.

Service robots present a new frontier in the provision of services, with far-reaching implications for customers and managers alike. The purpose of this chapter is to examine how service robots impact service providers' current marketing strategies. For this, the authors perform an integrative, nonsystematic review of international gray and academic literature to understand how both practitioners and academics perceive the impacts of the technology. Based on this analysis, the present work identifies three key themes that emerge from the current state of practitioner and academic research, namely (1) service robots demand new core business capabilities and competencies, (2) service robots offer new value propositions, and (3) service robots impact not only service providers' cost structures but also revenue streams. These insights are combined into the Service Robot Innovation Canvas, a visual tool for service providers to identify the impact of service robot implementations on a company's marketing strategy. In addition, based on the analyzed literature, the most pressing questions for researchers are laid out in a research agenda.

This study aims to analyze the content on corporate social responsibility (CSR) of Gucci, Prada and Ermenegildo Zegna on the social networks Instagram, Facebook and TikTok in order to examine the focus of the publications of these luxury brands, what type of content is more frequent and which ones generate more interaction and engagement.

An interpretive content analysis of a sample of 92 posts on CSR published between December 2021 and June 2022 is used. For this purpose, an analysis sheet validated through theoretical constructs and pilot testing is used.

Most of the social responsibility content of the fashion brands analyzed is linked to the use of sustainable materials, the protection of natural spaces and, in the particular case of Prada, the protection of the oceans. The posts that achieve the highest interactions are videos and photo reels. Although the strategies that significantly increase brands' reach on social networks are collaborations and joint posts with other fashion brands, as is the case of Gucci with NorthFace and Prada with Adidas. Also, one of the main findings of this research has been to identify that brands may be using TikTok – perhaps experimentally – to reach stakeholders in Asian countries, especially China, where other platforms such as Instagram or Facebook may have a more limited reach.

This research shows that the social responsibility activities of luxury fashion brands leverage the content marketing strategy in social networks. It also demonstrates the importance of the Asian market (mainly Chinese) in the outreach strategies of brands, as is the case of Gucci and Prada, which bet on CSR activities for the protection of the Asian tiger in the framework of the year of the tiger in the Chinese horoscope, as well as the publication of certain content on TikTok.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

Consumer behavior has evolved because of technological development. Nowadays, consumers carry out the different stages of the decision-making process by combining multiple devices which has been defined as multi, cross and omnichannel behavior. These behaviors have attracted the attention of academics and become a hot topic in literature. As a result, vast amounts of studies on the subject need to be revised and clarified. Thus, the aim of this chapter is to synthetize the primary academic literature that analyzes multi, cross and omnichannel behavior from the consumer point of view. To do that, first, the main concepts (multi, cross and omnichannel) and their differences are clarified. Second, the major findings of channel mix literature regarding the topics, channel scope and theories are exposed and described. Third, the opportunities and future lines of research are presented. This chapter contributes to the literature by clarifying the conceptualization of multi, cross and omnichannel behaviors; offering a complete picture of the main topics, channel approaches and theories addressed in channel mix literature; and presenting future research opportunities and open research questions in a channel mix context that could serve as a starting point to build further research.

This paper explores the similarities and differences in privacy attitudes, trust and risk beliefs between younger and older adults on social networking sites. The objective of the article is to ascertain whether any notable differences exist between younger (18–25 years old) and older (55+ years old) adults in how trust and risk are influenced by privacy concerns upon personal information disclosure on social media.

A Likert scale instrument validated in previous research was employed to gather the responses of 148 younger and 152 older adults. The scale was distributed through Amazon Mechanical Turk. Data were analyzed through partial least squares structural equation modeling.

No significant differences were found between younger and older adults in how social media privacy concerns related to trust and risk beliefs. Two privacy concern dimensions were found to have a significant influence on perceptions of risk for both populations: collection and control. Predictability and a sense of control are proposed as two conceptual approaches that can explain these findings.

This article is the first one to explore age differences in privacy concerns, trust and risk on social media employing conceptual developments and an instrument specifically tailored to the social media environment. Based on the findings, several strategies are suggested to keep privacy concerns on social media at a minimum, reduce risk perceptions and increase users' trust.

The article investigates different types of strategies for managing user-generated content (UGC) and provides some insights into their implications.

A unique sample of Italian hotels with current and prospective customers in the digital environment is investigated. A taxonomy of user-provider interactions mediated by UGC is developed. A mixed approach was designed to meet the study aims. Firstly, an exploratory factor analysis was performed in order to illuminate different strategies of UGC and electronic word-of-mouth (E-WOM) management. Secondly, a cluster analysis was implemented in order to explain hoteliers' behavior toward users' contents.

The study results suggested the existence of three clusters, which reflected three different types of interactions between hotels and customers in the digital domain. Interestingly, most of Italian hotels were found to adopt a reductionist approach to UGC and E-WOM management, turning out to be ineffective to exploit them for the purpose of quality improvement and hospitality service excellence.

Hotels were found to be largely unaware of the importance of UGC and web-based communication with customers to improve their digital business strategy. Tailored management approaches are needed to realize the full potential of hotels' online content responsiveness for the purpose of value co-creation and service co-production.

This is one of the first studies investigating the strategic and management perspectives embraced by hotels to handle their interactions with customers in the digital arena.

The purpose of this paper is to supplement and update previously published articles about artificial intelligence (AI) instruments and operations in banking sectors with the following objectives in mind: to understand the role of AI in banking sectors; to explore the themes and context in this area based on keywords, co-citations and co-words; and to identify future research direction by evaluating the trend and direction of previous research.

This study adopts a semi-inductive approach with the convolution of bibliometrics and literature review. This study used bibliometrics for the identification of literature across multiple databases and systematic literature review on identified articles to explore heterogeneous sectors within AI in banking and finance.

This study contributes a literature-based model that accounts for both the broadly in AI application in banking and finance: predictive modeling in risk assessment and detection; financial decision-making; client service delivery; and emerging FinTech applications of AI and machine learning.

This study is among the few to address the literature of tools and application of AI in banking through mixed-methods approach and produce a synthesized model for the same.

The purpose of this study is to examine the acceptance of artificial intelligence devices (AIDs) by customers in banking service encounters using the Artificially Intelligent Device Use Acceptance (AIDUA) model and thus test the validity of the AIDUA model in the context of the banking sector as well as extending the AIDUA model by incorporating two moderator variables, namely technology anxiety and risk aversion by regarding the nature of banking services, which are considered highly risky and technology-intensive.

About 575 valid face-to-face self-administered surveys were gathered using convenience sampling among real bank customers in Turkey. The structural equation modelling was used to test hypotheses involving both direct and moderation effects.

The current study has demonstrated that the AIDUA model is valid and reliable for the acceptance of AIDs in banking service encounters by modifying it. The study results have shown that the acceptance process of AIDs for bank customers consists of three phases. Furthermore, the study’s findings have demonstrated that technology anxiety and risk aversion have adverse moderation effects on the relationship between performance expectancy and emotion as well as on the relationship between emotion and willingness to accept AIDs, respectively.

The current study validates the AIDUA model for the banking industry. In addition, the present study is unique compared to other studies conducted in the literature since it applies the AIDUA model to the setting of banking services for the first time by considering the potential effects of two moderators.