Mousa Al-kfairy’s research while affiliated with Zayed University and other places

Purpose This study examines the factors influencing users' intentions to adopt virtual reality (VR) technologies in museums, emphasizing the role of social cognitive theory (SCT) constructs and trust dimensions (ability, integrity and benevolence). Design/methodology/approach A survey of 413 university students from the UAE, KSA and Kuwait was conducted, and partial least squares structural equation modeling (PLS-SEM) was applied to analyze the relationships between SCT constructs, trust and behavioral intention. Findings SCT constructs significantly impact trust and intention to use VR in museums. Trust is a key mediator whose dimensions play pivotal roles in shaping behavioral intentions. Gender moderates these relationships, while cultural and age differences have minimal effects. Originality/value This study advances understanding of the psychological and trust-based factors driving VR adoption in cultural contexts. It provides actionable insights for enhancing users’ adoption of Metaverse-based museums, supporting practitioners and policymakers in leveraging VR technologies within the Metaverse.

Companies that deliver food (food delivery services, or FDS) try to use customer feedback to identify aspects where the customer experience could be improved. Consumer feedback on purchasing and receiving goods via online platforms is a crucial tool for learning about a company’s performance. Many English-language studies have been conducted on sentiment analysis (SA). Arabic is becoming one of the most extensively written languages on the World Wide Web, but because of its morphological and grammatical difficulty as well as the lack of openly accessible resources for Arabic SA, like as dictionaries and datasets, there has not been much research done on the language. Using a manually annotated FDS dataset, the current study conducts extensive sentiment analysis using reviews related to FDS that include Modern Standard Arabic and dialectal Arabic. It does this by utilizing word embedding models, deep learning techniques, and natural language processing to extract subjective opinions, determine polarity, and recognize customers’ feelings in the FDS domain. Convolutional neural network (CNN), bidirectional long short-term memory recurrent neural network (BiLSTM), and an LSTM-CNN hybrid model were among the deep learning approaches to classification that we evaluated. In addition, the article investigated different effective approaches for word embedding and stemming techniques. Using a dataset of Modern Standard Arabic and dialectal Arabic corpus gathered from Talabat.com, we trained and evaluated our suggested models. Our best accuracy was approximately 84% for multiclass classification and 92.5% for binary classification on the FDS. To verify that the proposed approach is suitable for analyzing human perceptions in diversified domains, we designed and carried out excessive experiments on other existing Arabic datasets. The highest obtained multi-classification accuracy is 88.9% on the Hotels Arabic-Reviews Dataset (HARD) dataset, and the highest obtained binary classification accuracy is 97.2% on the same dataset.

Purpose This study investigates the impact of social cognitive theory (SCT) constructs and perceived risks on university students’ trusting intentions towards Metaverse-based educational platforms in the UAE. By examining factors such as self-efficacy, outcome expectations and vicarious learning (from SCT), alongside perceived risks like performance, time, social and security concerns, this research addresses critical gaps in understanding trust dynamics in educational technology. Design/methodology/approach A quantitative survey was conducted with 176 university students who experienced a Metaverse-based classroom prototype. Data were analyzed using structural equation modeling (SEM) to evaluate the relationships between SCT constructs, perceived risks and trusting intentions. Findings The results demonstrate that SCT constructs significantly enhance trust by fostering self-efficacy and providing positive learning experiences. Conversely, perceived risks reduce trust, emphasizing the need to mitigate security concerns and usability barriers to improve adoption. These insights underline the dual importance of managing risks and promoting psychological readiness among students. Practical implications The findings offer actionable guidance for educators, policymakers and developers to design secure, user-friendly Metaverse platforms that align with educational objectives. The study emphasizes the importance of addressing perceived risks, enhancing student engagement and fostering trust to enable effective technology adoption in education. Originality/value This research provides a novel perspective on trust in Metaverse-based education by integrating SCT constructs with risk perceptions, offering a comprehensive framework to guide the successful implementation of immersive learning environments.

The Metaverse is rapidly evolving into a transformative digital ecosystem, bringing with it unprecedented opportunities and a complex array of ethical challenges. This narrative review, based on an in-depth analysis of 105 full publications, explores the key ethical themes associated with the Metaverse, including privacy and data security, identity and behavior, digital inclusivity, mental and physical health, ethical AI, content moderation, intellectual property, governance, environmental sustainability, harassment, cultural representation, and economic implications. Proposed solutions for these challenges encompass privacy-by-design frameworks, robust identity verification systems, equitable access initiatives, explainable AI, and blockchain-based intellectual property protections. Additionally, the review examines governance and legal initiatives, such as frameworks developed by the World Economic Forum, European Commission, United Nations, and IEEE standards. These efforts aim to enhance transparency, ensure universal accessibility, promote ethical AI, and foster safety within the Metaverse. By synthesizing insights from this extensive body of literature, this review offers a thorough exploration of the ethical dimensions of the Metaverse and presents practical recommendations for fostering responsible and inclusive digital ecosystems.

Generative AI is revolutionizing the way organizations operate, offering transformative capabilities that span automated content creation, strategic decision-making, and customer engagement through AI-driven chatbots. This paper conducts a comprehensive literature review to explore the applications, challenges, and strategic requirements for adopting generative AI in organizational contexts, focusing on the distinct needs of Small and Medium Enterprises (SMEs) and large organizations. The findings reveal that generative AI can improve efficiency, drive innovation, and improve customer satisfaction, but its adoption pathways differ significantly between organizational sizes. For SMEs, the emphasis lies on cost-effective and scalable solutions that optimize resource-constrained operations. At the same time, large organizations leverage their extensive resources to scale AI applications, manage complex systems, and address ethical and regulatory challenges. The study highlights critical barriers, including data privacy concerns, integration with legacy systems, and resistance to change, alongside actionable recommendations for overcoming these challenges. By synthesizing insights from 38 high-quality studies, this research bridges the gap between theory and practice. It provides a roadmap for organizations of varying scales to harness generative AI as a cornerstone of their digital transformation journey. It also identifies key areas for future exploration, ensuring relevance in this rapidly evolving field.