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Drawing on the social presence theory, this study aims to explore how supplier–customer social media interactions influence supplier observers’ trust in the customers and what mechanisms contribute to variation in trust experience.

A total of 36 semi-structured interviews were conducted with Chinese suppliers using WeChat for business-to-business interactions. Data were analyzed in three steps: open coding, axial coding and selective coding.

Findings reveal that varied trust is based not only on the categories of social presence of interaction – whether social presence is embedded in informative interactions – but also on the perceived selectivity in social presence. Observer suppliers who experience selectivity during social and affective interactions create a perception of hidden information and an unhealthy relationship atmosphere, and report a sense of emotional vulnerability, thus eroding cognitive and affective trust.

The findings contribute new understandings to social presence theory by exploring the social presence of interactions in a supplier–supplier–customer triad and offer valuable insights into business-to-business social media literature by adopting a suppliers’ viewpoint to unpack the mechanisms of how social presence of interaction positively and negatively influences suppliers’ trust and behavioral responses.

Social commerce (s-commerce) has gained widespread popularity as a social platform where customers engage in resource-sharing activities such as information exchange, advice-seeking and expressing their opinions on mutual interests. However, existing studies have not fully comprehended the drivers of electronic customer-to-customer interaction (eCCI) and how such behavior contributes to the customer “stick” on s-commerce sites. This study develops the Motivation–Opportunity–Ability (MOA) theory and investigates the impact of MOA factors on eCCI, which in turn affects customer stickiness.

A survey was used to acquire data from 455 valid respondents, and the research employed a combination of fuzzy-set qualitative comparative analysis (fsQCA) and structural equation modeling.

The results revealed associations between perceived self-efficacy, intrinsic motivation, tie strength with other customers, eCCI and customer stickiness.

Considering the limited availability of complete eCCI frameworks in existing scholarly works, the authors present valuable perspectives on the role of consumer characteristics as both antecedents and consequences of eCCI. Additionally, this study proposes a research agenda for the field of eCCI on s-commerce sites.

The user experience during the use of activities and services is a fundamental aspect for sports managers and can provide a competitive advantage. The purpose of this study was to identify the dimensions of experiential quality and the relationship of this construct with customer trust and customer satisfaction in achieving behavioral intention.

Using a convenience sampling technique, a total of 322 gym users in Turkey participated. A two-step approach was used to test both the model and the research hypotheses [confirmatory factor analysis (CFA) and structural equation modeling (SEM)].

The interaction quality, physical environmental quality, outcome quality and enjoyment quality were positively related to experiential quality. Similarly, the experimental quality was positively related to customer satisfaction and customer trust. Finally, customer satisfaction was related to behavioral intentions.

This study provides empirical evidence about the importance of experiential quality to gain a competitive advantage in the context of fitness centers.

This study explores how emotional intelligence, customer orientation, deep acting and surface acting influence job satisfaction among middle managers in their interactions with customers, colleagues and business partners. By examining these factors, we aim to provide insights into their collective impact on job satisfaction and interpersonal dynamics within organizational contexts.

By involving 95 middle managers at Indonesian Internet service providers as respondents, this research used a questionnaire to collect data. Next, the data were analyzed using the partial least square-structural equation modeling (PLS-SEM) technique, which evaluated measurement models and structural models. A total of twelve hypotheses were tested in this study.

This study found that customer orientation does not have a significant effect on deep acting, thereby nullifying its indirect effect on job satisfaction. Conversely, it's demonstrated that both deep acting and surface acting serve as partial mediators in the relationship between emotional intelligence and job satisfaction. Furthermore, surface acting emerges as a partial mediator in the connection between customer orientation and job satisfaction.

By exploring the relationship between customer orientation, emotional intelligence and job satisfaction among employees, this study seeks to reveal novel insights. The study examines the impact of these critical elements, which are necessary for middle managers to effectively manage their emotions and cultivate significant connections, on their overall job satisfaction and interpersonal dynamics in their diverse responsibilities.

In an era where complex technological advances increasingly govern service delivery, it is incumbent on service firms to pioneer innovative strategies to sustain customer engagement and cultivate loyalty. This conceptual paper examines the transformative potential of artificial intelligence (AI) in the realm of online customer communities, with a particular focus on its creation, management and enhancement facets. The authors explore how AI can revolutionize the dynamics of customer interaction, feedback mechanisms and overall engagement within the service industry.

This conceptual paper draws from marketing and management literature focusing on customer communities and AI in service and customer engagement contexts with a robust future research agenda.

A classification of online customer community engagement is provided along with a conceptual framework to guide our understanding of the integration of AI into online customer communities.

This exploration underscores the imperative for service firms to embrace AI-driven approaches to online customer community management, not only as a means to optimize their operations but as a vital strategy to stay competitive in the ever-evolving digital landscape. This paper examines the novel combination of AI with online customer communities and provides the framework in the form of an input-process-output (IPO) model for future research into this integration.

The purpose of this study is to comprehend how AI aids marketers in engaging customers and generating value for the company by way of customer engagement (CE). CE is a popular area of research for scholars and practitioners. One area of research that could have far-reaching ramifications with regard to strengthening CE is artificial intelligence (AI). Consequently, it becomes extremely important to understand how AI is helping the marketer reach customers and create value for the firm via CE.

A detailed approach using both systematic review and bibliometric analysis was used. It involved identifying key research areas, the most influential authors, studies, journals, countries and organisations. Then, a comprehensive analysis of 50 papers was carried out in the four identified clusters through co-citation analysis. Furthermore, a content analysis of 42 articles for the past six years was also conducted.

Emerging themes explored through cluster analysis are CE concepts and value creation, social media strategies, big data innovation and significance of AI in tertiary industry. Identified themes for content analysis are CE conceptualisation, CE behaviour in social media, CE role in value co-creation and CE via AI.

CE has emerged as a topic of great interest for marketers in recent years. With the rapid growth of digital media and the spread of social media, firms are now embarking on new online strategies to promote CE (Javornik and Mandelli, 2012). In this review, the authors have thoroughly assessed multiple facets of prior research papers focused on the utilisation of AI in the context of CE. The existing research papers highlighted that AI-powered chatbots and virtual assistants offer real-time interaction capabilities, swiftly addressing inquiries, delivering assistance and navigating customers through their experiences (Cheng and Jiang, 2022; Naqvi et al., 2023). This rapid and responsive engagement serves to enrich the customer’s overall interaction with the business. Consequently, this research can contribute to a comprehensive knowledge of how AI is assisting marketers to reach customers and create value for the firm via CE. This study also sheds light on both the attitudinal and behavioural aspects of CE on social media. While existing CE literature highlights the motivating factors driving engagement, the study underscores the significance of behavioural engagement in enhancing firm performance. It emphasises the need for researchers to understand the intricate dynamics of engagement in the context of hedonic products compared to utilitarian ones (Wongkitrungrueng and Assarut, 2020). CEs on social media assist firms in using their customers as advocates and value co-creators (Prahalad and Ramaswamy, 2004; Sawhney et al., 2005). A few of the CE themes are conceptual in nature; hence, there is an opportunity for scholarly research in CE to examine the ways in which AI-driven platforms can effectively gather customer insights. As per the prior relationship marketing studies, it is evident that building relationships reduces customer uncertainty (Barari et al., 2020). Therefore, by using data analysis, businesses can extract valuable insights into customer preferences and behaviour, equipping them to engage with customers more effectively.

The rapid growth of social media has enabled individuals to articulate their thoughts, opinions and emotions related to a brand, which creates a large amount of data for VCC. Meanwhile, AI has emerged as a radical way of providing value content to users. It expands on a broader concept of how software and algorithms work like human beings. Data collected from customer interactions are a major prerequisite for efficiently using AI for enhancing CE. AI not only reduces error rates but, at the same time, helps human beings in decision-making during complex situations. Owing to built-in algorithms that analyse large amounts of data, companies can inspect areas that require improvement in real time. Time and resources can also be saved by automating tasks contingent on customer responses and insights. AI enables the analysis of customer data to create highly personalised experiences. It can also forecast customer behaviour and trends, helping businesses anticipate needs and preferences. This enables proactive CE strategies, such as targeted offers or timely outreach. Furthermore, AI tools can analyse customer feedback and sentiment across various channels. This feedback can be used to make necessary improvements and address concerns promptly, ultimately fostering stronger customer relationships. AI can facilitate seamless engagement across multiple digital channels, ensuring that customers can interact with a brand through their preferred means, be it social media, email, or chat. Consequently, this research proposes that practitioners and companies can use analysis performed by AI-enabled systems on CEB, which can assist companies in exploring the extent to which each product influences CE. Understanding the importance of these attributes would assist companies in developing more memorable CE features.

This study examines how prominent CE and AI are in academic research on social media by identifying research gaps and future developments. This research provides an overview of CE research and will assist academicians, regulators and policymakers in identifying the important topics that require investigation.

Effective customer journey design (ECJD) is considered a key variable in customer experience management and an essential source of brand meaning and pro-brand behavior. Although previous research has confirmed its importance for driving brand attitudes and loyalty, the role of consumer-brand identification as a social identity-based influence in this relationship has not yet been discussed. Drawing on construal level and social identity theories, this paper aims to investigate whether effective journeys and the resulting overall journey experience are equally powerful in driving brand loyalty among customers with different levels of consumer-brand identification.

The present article develops and tests a research model using data from the European and US service sectors (N = 1,454) to investigate how and when ECJD affects service brand loyalty.

Across two cultural contexts, four service industries and 33 service brands, the results reveal that ECJD is a crucial driver of service brand loyalty for customers with low consumer-brand identification. Moreover, the findings show that different aspects of journey effectiveness positively impact the valence of customers’ experience related to those journeys – a process that is ultimately decisive for their brand loyalty.

This study is unique because it generates theoretical and practical knowledge by combining the literature streams of customer journey design, customer experience and branding. Furthermore, this work demonstrates that consumer-brand identification is a critical boundary condition to be considered in the relationship between ECJD and brand loyalty in services.

This study aims to explore the conversion of metaverse marketing (MVM) into strategic agility among SMEs based on dynamic capabilities (DC) and dynamic management capabilities (DMC) theories. This paper discusses how constructs such as immersive marketing technologies (IMT), customer immersion (CI) and managerial capabilities (MC) play critical role in the transformation of MVM into strategic agility (SA).

A theoretical framework based on DC and DMC theories, and a comprehensive review of the literature on MVM, IMT, CI, MC and SA, was developed in order to theoretically investigate the relationships between MVM and SA. In this theoretical framework, MVM is the independent variable, while the dependent variable is SA. Also, IMT and CI both mediate the association between MVM and SA, while MC moderate the association between MVM and SA in one stream; and CI and SA in another stream.

This research study develops a theoretical framework that recommends nine set of important research propositions in MVM. An extensive literature review was conducted to examine the theoretical framework on the effect of MVM on SA. The proposed theoretical framework suggests that brand community development and communication, experiential marketing and personalisation in MVM, once accessed through IMT (i.e. VR, AR, MR) and CI (i.e. customer engagement, customer absorption-customer acquisition and assimilation of knowledge, presence) can produce significant SA through customer experience management, value co-creation and process innovation.

This current study develops a theoretical framework that theorise the relationship between MVM and SA rooted in literature on MVM and SA, and also based on DC and DMC perspective. The moderating effect of MC on the relationship between IMT and SA on one hand, and CI and SA on the other, provides support to IMT and CI as mediators in the transformation of MVM into SA. This study also provides insight into SME adoption of MVM and how it generates SA. Lastly, the current study contributes to the body of knowledge on MVM, IMT, CI, MC and SA.

The proliferation of the coronavirus disease (COVID-19) has threatened the service industry, especially the restaurant sector, requiring innovative ways to help restaurants overcome this challenge. Thus, based on the stimulus–organism–response (SOR) model, the purpose of this study is to examine the role of customers' perception of a restaurant's innovativeness (CPRI) in brand evangelism by mediating customer engagement (CE). Additionally, this study examines the moderating role of customer openness to experience.

A Web-based survey collected the primary data from 483 Egyptian customers. The data were analysed using the partial least squares structural equation modelling method based on WarpPLS.7 software.

According to the findings, CPRI, which acts as a stimulus in the SOR model, positively affects CE (organism) and brand evangelism (response). CE positively affects restaurant evangelism. Additionally, CE mediates the relationship between CPRI and evangelism. Openness to experience moderates the relationship between CPRI, engagement and brand evangelism.

This study addresses the gaps in understanding CE and brand evangelism within the context of restaurant innovation. This study assesses restaurant innovativeness scales of developing economies in multiple dimensions. Egyptian restaurant marketing managers should innovate products, services, experiences, and promotions to increase consumer engagement and feedback through technology.

This study investigates how Egyptian restaurants engage with and evangelise customers through innovation. This is one of the few studies that examine brand evangelism in a restaurant setting from the perspective of the SOR theory. Additionally, this study analyses CE as a mediator and openness to experience as a moderator.

This paper aims to explore the dimensions that foster the effectiveness of artificial intelligence (AI) within a business strategy.

The paper reviews recent contributions to AI and business success and identifies the key pillars that support the achievement of good results.

The paper proposes that there are four critical dimensions for developing an effective business strategy with AI. This research finds that AI has the potential to drive significant development when it is leveraged along four main axes: a focused strategy for AI, knowledge of the customers, effective interactions with customers and effective implementation of AI. These four dimensions are essential for nurturing the critical dimensions of AI that enable successful integration with the business strategy. To achieve this integration, the business strategy must take advantage of the insights and capabilities provided by AI while also understanding and deeply knowing the customers through effective interactions with them. The development is structured in an organizational alignment where AI helps employees and learns from them. By continuously learning from the exploitation of knowledge and big data, the organization can enrich its use of AI.

The paper identifies four pillars of AI integration with the development of business strategy as areas for further empirical analysis by business researchers.

This paper offers strategies for managers and professionals to effectively integrate AI into business strategy.

The authors provide a novel perspective on using AI in business strategy by identifying four key axes of success in the current business landscape.