Purpose The proliferation of picture and video-based visual electronic word-of-mouth (VeWOM) is gaining popularity. However, few studies have compared the effects of traditional text-based eWOM against next-generation VeWOM. Drawing on the cognitive theory of multimedia processing and dual coding, the purpose of this study is to investigate the effects of positive and negative VeWOM on travel intentions via mental imagery processing, attitudes toward the information, and perceived message credibility. The authors further examine the moderating role played by destination image.Design/methodology/approach Collecting data from Zambian frequent travellers and using a 2 & times;2 between-subjects factorial design, partial least squares structural equation modelling was employed to test research hypotheses.Findings The results show that when compared to text-based eWOM, both positive and negative VeWOM significantly influence tourists' travel intentions.Research limitations/implications These findings advance understanding of VeWOM effects on tourist behaviours. Destination marketers should leverage user-generated visual content to build trust and manage negative VeWOM to reduce reputational risks.Originality/value Unlike previous papers that solely focused on traditional text-based eWOM, they study new-generation VeWOM and make several contributions towards eWOM, tourism, hospitality and mental imagery processing literature.

This study aims to cultivate an initial understanding of travelers' engagement with generative artificial intelligence (GAI) during the travel planning phase. It focuses on its influence on decision-making and intentions for continuous usage in planning tourism activities. Utilizing the stimulus-organism-response framework and domain literature, data were gathered through semi-structured interviews (UK) and scenario-based questionnaires (USA). The study reveals complex aspects of travelers' behavior, uncovering that while GAI recommendations mitigate the risk of information overload, their influence does not necessarily streamline decision-making. Trust and information retrieval skills surfaced as moderate determinants of the relationship between recommendations and information overload. This work is a pioneer in empirically exploring and quantifying continuance intentions of generative artificial intelligence (GAI) usage, contributing novel insights to electronic Word of Mouth and decision-making literature.

Delegation to agentic artificial intelligence (AI) is increasing as these systems can plan, decide, and execute tasks through external tools across everyday and organizational settings. However, users do not judge delegation only by outcome quality or speed. They also judge whether the AI acted within the goals, constraints, permissions, and remedies that they authorized. We develop Delegated Agency Theory (DAT) to explain this judgment through the concept of delegation fidelity, which refers to users’ perceived alignment between the delegation contract they believe they set and the behavior they later experience. We argue that delegation outcomes depend on four higher-order design dimensions: contract specification quality, capability-context fit, governance visibility, and recovery capacity. These dimensions reduce adverse selection before handoff and moral hazard during execution, thereby increasing delegation fidelity. Higher delegation fidelity improves users’ functional, symbolic, and ethical evaluations, which together shape value-in-delegation, continued reliance, complaint intention, and switching. By positioning delegation fidelity as the central mediating mechanism, DAT offers a more precise explanation than that provided by adjacent concepts such as trust, transparency, or algorithmic appreciation alone. We also outline an empirical pathway through the user Delegation Quality Index (uDQI), which captures the quality of delegation design and supports future measurement and validation across contexts and cultures.

Grounded in Diffusion of Innovation (DOI) theory, this paper critically reassesses its assumptions within contemporary environments characterised by mis/disinformation and AI-amplified media. Using a conceptual synthesis supported by illustrative case studies on generative AI and 5G technologies, we demonstrate how misleading narratives distort perceptions of innovations, leading to delayed, distorted, or derailed adoption. The paper concludes with theoretical implications highlighting specific DOI assumptions challenged by misinformation and practical recommendations for managing digital technology diffusion in an era of pervasive ‘post-truth’ information disorder.

This paper examines how Generative Artificial Intelligence (GAI) influences word-of-mouth (WOM) in travel and hospitality, focusing on synthetic WOM (syWOM). It explores how GAI-driven WOM reshapes traveler interactions and decision-making in an experience-centric industry. Using a literature review and conceptual analysis approach1, this study examines the integration of GAI tools, such as ChatGPT, to enhance travel experiences. The analysis presented in this study highlights GAI's potential in inducing syWOM and its effects on traveler perceptions and behaviors. Additionally, it addresses the emerging role of GAI in WOM, emphasizing the need for further research on its impact on travel planning and engagement. This study presents a fresh view of the interaction of syWOM with GAI in travel, aiming to inform future research and practical applications of personalized traveler engagement.

This study examines the influence of electronic Word-of-Mouth (eWOM) on consumer expectations and intentions to adopt emerging technologies, specifically focusing on cryptocurrency payment methods. Employing the Elaboration Likelihood Model (ELM), the research utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) and Multi-Group Analysis (PLS-MGA) to analyze data from a diverse sample of 505 respondents sourced from MTurk. The findings reveal that the quality, consistency, and volume of eWOM significantly shape consumer expectations. Notably, the two-sidedness of online reviews does not have any substantial impact on both expectations and adoption behaviors toward cryptocurrency payment methods. Furthermore, factors such as the time spent online, and the frequency of online shopping were found to partially moderate the effects of eWOM on adoption behavior. This research contributes pioneering insights into the role of eWOM in influencing consumer attitudes towards cutting-edge technologies, extending existing knowledge beyond traditional consumer decisions to include technological adoption, particularly in digital finance. This offers valuable implications for technology firms and digital marketers aiming to harness eWOM to promote new technological solutions.

Purpose Based on the key dimensions of the Metaverse environment (immersiveness, fidelity and sociability), this paper aims to develop the concept of sensory word-of-mouth (WOM) in Metaverse – the metaWOM. It attempts to upgrade the Reviewchain model and suggests the utilization of non-transferable tokens (NTTs) in curbing the explosion of fake WOM. Design/methodology/approach Following Macinnis’ (2011) approach to conceptual contributions, the authors browsed the currently available literature on WOM, Metaverse and NTT to portray the emergence of metaWOM. Findings By relying on Metaverse’s three building blocks, the authors map out the persuasiveness of metaWOM in the Metaverse-like environment. By incorporating NTT in the Reviewchain model, the authors upgraded it to provide a transparent, safe and trusted review ecosystem. An array of emerging research directions and research questions is presented. Research limitations/implications This paper comprehensively analyzes the implications of a Metaverse-like environment on WOM and debates on technologies that can enhance the metaWOM persuasiveness. The proposed model in this paper can assist various stakeholders in understanding the complex nature of virtual information-seeking and giving. Originality/value This is the original attempt to delineate the sensory aspect of WOM in the Metaverse based on three crucial aspects of the Metaverse environment: immersiveness, fidelity and sociability. This paper extends the discussion on the issue of fake reviews and offers viable suggestions to curb the ever-growing number of fraudulent WOM.

The proliferation of Voice Controlled Smart Assistants (VCSAs) is increasing, and this is expected to continue in the future. There is much promise in how the growing capabilities of these Artificial Intelligence-powered devices can affect user experiences, usage and habit yet little is known about these areas. This study aims to contribute to knowledge in these areas by utilizing an interpretive philosophy and a qualitative approach. A tri-phased data collection process was utilized which included the collation of diary data from fourteen participants over an eight-week period. This short paper provides insight into the key findings identified which highlight: how usage evolves over time, and factors that affect this evolution. The paper also discusses further steps the researchers will take to progress this study.

While the importance of s-commerce is implicitly recognized, inconsistencies in extant empirical research pose significant challenges. Based on perspectives from trust, social presence, and socio-technical theories, this study develops an integrated model of the factors that influence intention and use behavior, with particular attention to the role of trust in s-commerce. The model is tested using meta-analytic structural equation modeling techniques on 201 observations from 83 s-commerce studies. Implications for research and practice are discussed.

Open Government efforts are criticized for providing limited value. Instead of looking at a value, we investigate the usefulness of web-based open government portals and apps. Specifically, we investigated the relationship between digital transparency and usefulness. We analyzed perceived digital transparency and usefulness in a survey of 112 respondents using Partial Least Square (PLS) and Structural Equation Modelling (SEM). The results show that perceived functionality, transparency, and efficiency influence usefulness but that functionality of apps and efficiency are more important than transparency. Usefulness can be created without having high levels of transparency, as the public wants answers to their questions. Apps should be designed for efficient use, as users have limited time and resources. Apps having pre-defined functional views can be useful to provide quick insight but might limit transparency by not offering other views and insights. Opening raw data using portals can provide higher levels of transparency, although more time and effort are needed to analyze. Both portals providing access to raw data and apps having pre-defined views are needed for open government and transparency as they serve other stakeholder groups and purposes.

Information plays an important role in consumer's decision-making process. Adoption of electronic word of mouth (eWOM) communications can change consumers' attitudes, and, as a result, have an impact on their purchase decisions. Researchers have investigated factors affecting credibility and usefulness of eWOM, which can help to predict eWOM adoption. However, findings are contradictory causing confusion among researchers and practitioners. Hence, this research aims to synthesise results from existing work on adoption of eWOM communications by using meta-analysis. The findings can help e-commerce companies to design more effective online review platforms. Additionally, this research will enhance the understanding of information processing by individuals.

Purpose Numerous studies have examined factors influencing electronic word of mouth (eWOM) providing behaviour. The volume of extant research and inconsistency in some of the findings makes it useful to develop an all-encompassing model synthesising results. Therefore, the purpose of this study is to synthesise findings from existing studies on eWOM by using meta-analysis, which will help to reconcile conflicting findings of factors affecting consumers’ intention to engage in eWOM communications. Design/methodology/approach The findings from 51 studies were used for meta-analysis, which was undertaken using comprehensive meta-analysis software. Findings Factors affecting eWOM providing behaviour were divided into four groups: personal conditions, social conditions, perceptual conditions and consumption-based conditions. The results of the meta-analysis showed that out of 20 identified relationships, 16 were found to be significant (opinion seeking, information usefulness, trust in web eWOM services, economic incentive, customer satisfaction, loyalty, brand attitude, altruism, affective commitment, normative commitment, opinion leadership, self-enhancement, information influence, tie strength, homophily and community identity). Research limitations/implications One of the limitations of this study is that the studies for this research were collected the only form from Web of Science, Scopus and Business Source such as databases, which result in a limited number of studies available for weight and meta-analysis. A wider range of databases should be used by future research. Also, this study only considered quantitative studies and excluded qualitative studies. Thus, future studies could include both types of studies in the meta-analysis. Practical implications By focussing on the best predictors of intention to provide eWOM communications (e.g. self-enhancement and trust in web eWOM services) managers can improve reader engagement and information assimilation. Knowing motivations to engage in eWOM helps platform operators design their service in a more customer-oriented way. By better understanding motivations to engage in eWOM communications marketers and researchers can influence individuals’ online information assimilation which can affect consumer purchase decisions, customer loyalty and consumer commitment to the community. Originality/value Applying meta-analysis helped the reconciliation of conflicting findings, enabled investigation of the strengths of the relationships between motivations and eWOM providing behaviour and offered a consolidated view. The results of this study facilitate the advancement of current knowledge of information dissemination on the internet, which can influence consumer purchase intention and loyalty.

Social media plays an important part in the digital transformation of businesses. This research provides a comprehensive analysis of the use of social media by business-to-business (B2B) companies. The current study focuses on the number of aspects of social media such as the effect of social media, social media tools, social media use, adoption of social media use and its barriers, social media strategies, and measuring the effectiveness of use of social media. This research provides a valuable synthesis of the relevant literature on social media in B2B context by analysing, performing weight analysis and discussing the key findings from existing research on social media. The findings of this study can be used as an informative framework on social media for both, academic and practitioners.

As far back as the industrial revolution, significant development in technical innovation has succeeded in transforming numerous manual tasks and processes that had been in existence for decades where humans had reached the limits of physical capacity. Artificial Intelligence (AI) offers this same transformative potential for the augmentation and potential replacement of human tasks and activities within a wide range of industrial, intellectual and social applications. The pace of change for this new AI technological age is staggering, with new breakthroughs in algorithmic machine learning and autonomous decision-making, engendering new opportunities for continued innovation. The impact of AI could be significant, with industries ranging from: finance, healthcare, manufacturing, retail, supply chain, logistics and utilities, all potentially disrupted by the onset of AI technologies. The study brings together the collective insight from a number of leading expert contributors to highlight the significant opportunities, realistic assessment of impact, challenges and potential research agenda posed by the rapid emergence of AI within a number of domains: business and management, government, public sector, and science and technology. This research offers significant and timely insight to AI technology and its impact on the future of industry and society in general, whilst recognising the societal and industrial influence on pace and direction of AI development.

The use of the internet and social media have changed consumer behavior and the ways in which companies conduct their business. Social and digital marketing offers significant opportunities to organizations through lower costs, improved brand awareness and increased sales. However, significant challenges exist from negative electronic word-of-mouth as well as intrusive and irritating online brand presence. This article brings together the collective insight from several leading experts on issues relating to digital and social media marketing. The experts' perspectives offer a detailed narrative on key aspects of this important topic as well as perspectives on more specific issues including artificial intelligence, augmented reality marketing, digital content management, mobile marketing and advertising, B2B marketing, electronic word of mouth and ethical issues therein. This research offers a significant and timely contribution to both researchers and practitioners in the form of challenges and opportunities where we highlight the limitations within the current research, outline the research gaps and develop the questions and propositions that can help advance knowledge within the domain of digital and social marketing.

Social media plays an important part in the digital transformation of businesses. This research provides a comprehensive analysis of the use of social media by business-to-business (B2B) companies. The current study focuses on the number of aspects of social media such as the effect of social media, social media tools, social media use, adoption of social media use and its barriers, social media strategies, and measuring the effectiveness of use of social media. This research provides a valuable synthesis of the relevant literature on social media in B2B context by analysing, performing weight analysis and discussing the key findings from existing research on social media. The findings of this study can be used as an informative framework on social media for both, academic and practitioners.

With the development of Internet and e-commerce, traditional word of mouth communications have evolved into electronic word of mouth (eWOM) communications, which significantly affect consumers in their decision-making process. Previous studies investigated how consumers process information online and how it affects consumer behaviour applying the Elaboration Likelihood Model (ELM). ELM distinguishes between two routes of information processing: central and peripheral. Existing literature has a mixed of findings regarding factors affecting information process using ELM and lacking a comprehensive review providing evaluation and a consolidated view of these factors. Thus, the aim of this research is to evaluate the use of ELM in the context of eWOM research by performing a systematic review and weight analysis of existing research findings. This will help consolidating the predictive power of the independent variables on the dependent variable, by taking into consideration the number of times a relationship has been previously examined. The model developed through weight analysis would allow eWOM practitioners to decipher more influential factors.

Social commerce (s-commerce) has gained prominence with advances in social media and social networking technologies over the last decade. Prior research has employed diverse theoretical perspectives to understand and explain consumer behavior within s-commerce but has also produced inconsistent results. This study integrates different theoretical perspectives including trust, social support, and social presence. The research portrays an integrated research model involving factors that impact behavioral intention and use behavior of s-commerce consumers whilst synthesizing prior empirical findings. A meta-analytic structural equation modeling (MASEM) method was used to synthesize 189 findings reported in 68 s-commerce studies and to analyze the structural model. Our findings show that trust and informational support have positive effects on behavioral intention while trust and emotional support have positive effects on use behavior. Furthermore, our findings highlight that behavioral intention influences use behavior and mediates the effect of trust and informational support on use behavior. The implications for research and practice are discussed in detail.