Search results

Despite the promising development and marketing potential of the metaverse, our understanding of how realistic metaverse environments impact user engagement and behaviours remains limited. This study investigates the role of perceived realism in influencing user engagement, thereby affecting external search behaviour and visit intentions.

We surveyed 270 active metaverse users to test the research model. The data were analysed using partial least squares structural equation modelling (PLS-SEM).

The results of our study show that three dimensions of realism – avatar involvement, perceptual pervasiveness and social realism – significantly enhance user engagement, which in turn influences external search behaviour and visit intention. In contrast, simulation realism and freedom of choice have minimal effects on absorption and dedication.

This study highlights the role of perceived realism in enhancing user engagement with the metaverse and its impact on physical world behaviours. It contributes to metaverse literature by demonstrating that engagement within the metaverse significantly influences physical world behaviours, including visit intentions and external search behaviours.

This study offers practical guidance for developers to enhance user engagement in metaverse environments. Specifically, our findings advocate for visual and audio quality enhancements, greater persuasiveness of virtual spaces, improved avatar representativeness and a closer alignment of metaverse activities with real-life events.

This study advances the theoretical understanding of perceived realism by examining how its dimensions – such as visual and audio quality, avatar representativeness and alignment with real-life events – impact user engagement in the metaverse. It also explores how this engagement influences offline behaviours, thus bridging the gap between virtual and real-world interactions.

There are two main objectives in this study. First, we aim to develop a set of constructs for health task management support (HTMS) features to evaluate which health-related tasks are supported by mobile health application (mHealth app) functions. Second, drawing on innovation resistance theory (IRT), we examine the impacts of the newly developed HTMS dimensions on perceived usefulness, alongside other barrier factors contributing to technology anxiety.

Using a mixed-method research design, this research seeks to develop new measurement scales that reflect how mHealth apps support older adults’ health-related needs based on interviews. Subsequently, data were collected from older adults and exploratory factor analysis was used to confirm the validity of the new scales. Partial least squares structural equation modeling (PLS-SEM) was used to analyze survey data from 602 older adults.

The PLS-SEM results indicated that medical management task support, dietary task support, and exercise task support were positively associated with perceived usefulness, while perceived complexity and dispositional resistance to change were identified as antecedents of technology anxiety. Perceived usefulness and technology anxiety were found to positively and negatively influence adoption intention, respectively.

This study enriches the information systems literature by developing a multidimensional construct that delineates how older adults’ health-related needs can be supported by features of mHealth apps. Drawing on IRT, we complement the existing literature on resistance to innovation by systematically examining the impact of five types of barriers on technology anxiety.

Through the theoretical lenses of media richness, perceived realism and customer engagement, this study aims to investigate the mechanisms that promote customer engagement in metaverse-mediated environments in the meetings, incentives, conferences and exhibitions (MICE) context, as well as the impact of customer engagement on customers’ metaverse usage intensity and future visit intention.

A survey of customers who have experience with metaverse-mediated MICE activities was conducted. Data from 267 respondents were analysed using partial least squares-structural equation modelling and fuzzy-set qualitative comparative analysis (fsQCA) to test our research framework.

Media richness dimensions, including multiple cues, immediate feedback and personal focus, were found to enhance perceived metaverse realism, which in turn affects the dimensions of customer engagement, leading to customers’ metaverse usage intensity and future visit intention. The fsQCA analysis identifies three configurations that lead to high event visit intention.

This research helps developers and marketers better understand how rich media contents create realistic experiences in the metaverse, aiding them to devise strategies for customer engagement and improve resource allocation.

Despite its potentially revolutionary impacts, empirical studies on the mechanisms driving customer engagement in the metaverse and its effects are scarce. This study contributes by revealing the multiple-phase mechanism of the customer engagement journey in the metaverse-mediated MICE context. By expanding the media richness theory into this area, our study provides new insights by illustrating how media richness dimensions create multisensory experiences and real-time interactions, enhancing perceived metaverse realism and customer engagement. It also addresses the debate on whether metaverse-mediated events substitute or complement real-life events.

The chapter identifies the COVID-19 pandemic as not just a public health crisis but also an information crisis. The authors argue that a deeper understanding of the role of culture in information practices is critical for the future of research and theoretical development around humanity’s relationship to information (i.e., why information is or is not created, represented, avoided, sought, retrieved, used, shared, or hidden). This chapter highlights the Black Feminist Information Community (BFIC) framework, especially the voice and information aspect of the model in the context of community justice.

This chapter explains the phenomenon of artificial intelligence (AI) powered by big data in technology and its contribution in knowledge-based marketing in B2B and its impact on rational decision-making in B2B marketing that affects business performance. This chapter is literature review prepared by compiling and reviewing previous literature, studies, articles, books and other sources related to the contribution of big data-enabled AI to B2B marketing. According to the information analysed, the findings show that big data supported by AI plays a significant role in creating user knowledge, external knowledge and customer knowledge, all of which are factors that significantly influence the ability of business-to-business marketers to make rational decisions that affect the performance of their companies. This chapter explains to them the phenomena of AI powered by big data and its effect on B2B marketing rational decision that will enhance company performance and its contribution on knowledge-based marketing in B2B. This chapter contributes to understanding main functions and interactions of AI system powered by big data and how such a system helps in B2B marketing by generating knowledge about customers, users and markets.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.