Search Results (36)

Traditional evaluations of artificial intelligence (AI) systems in the dynamic, operator-dependent, and time-sensitive field of interventional radiology (IR), focusing solely on algorithmic performance, often fail to capture their real-world clinical impact. This narrative review aims to provide an overview of the current state of the art of AI integration in IR through human–AI interaction (HAI), while offering a critical perspective on their clinical integration, limitations, and future directions. A comprehensive survey of recent literature was performed, focusing on AI applications across procedural phases. The review emphasizes systems providing decision support, real-time procedural verification, and immersive interfaces (augmented and virtual reality), while critically evaluating determinants of effective clinical adoption. AI has shown preliminary potential to support operator performance in selected interventional radiology tasks, although most applications remain experimental, retrospective, or evaluated in phantom or preclinical settings. Potential benefits include structuring uncertainty in patient selection and procedural planning, supporting assessment of device positioning and treatment outcomes, and integrating AI-derived outputs into the operator’s spatial field through immersive technologies. The clinical utility of these systems appears to be influenced by human–AI interaction, with interpretability, workflow integration, and trust calibration representing key determinants of effective use beyond algorithmic accuracy alone. The potential value of AI in interventional radiology appears to derive from its integration into human decision-making rather than from standalone predictive performance alone. A human-centered, interaction-based model supports understanding current applications, address challenges, and guide the development of adaptive, real-time systems for dynamic procedural environments. Full article

Digital commerce ecosystems increasingly depend on the alignment between social media advertising formats and digital payment systems, yet existing research has examined these mechanisms in isolation, overlooking their combined influence on consumer behaviour, conversion, and long-term value creation. This study addresses that gap by developing an integrative conceptual framework that examines how advertising formats and payment infrastructures jointly shape sustainable digital monetisation within an Environmental, Social, and Governance (ESG) framework. Methodologically, the study adopts a structured narrative literature review of interdisciplinary peer-reviewed studies and selected high-quality institutional reports, drawn from Scopus, Web of Science Core Collection, and Google Scholar, covering publications from 2015 to April 2026. A four-stage PRISMA-adapted selection protocol was applied to ensure transparency, replicability, and analytical rigour across the review process. The findings demonstrate that advertising formats including native advertising, influencer marketing, user-generated content, short-form video, live streaming, and augmented reality drive consumer attention and purchase intention, while payment systems encompassing digital wallets, BNPL services, and in-platform checkout shape transactional trust and friction. Conversion and customer lifetime value emerge as joint outcomes of this interaction, mediated by consumer trust and transaction friction. The study further identifies key sustainability tensions related to digital carbon footprints from data-intensive formats, financial vulnerability associated with frictionless credit tools, and governance concerns surrounding transparency, privacy, and platform power concentration. The study contributes an integrative conceptual model linking advertising formats, payment systems, consumer behaviour, and ESG dimensions within a unified framework, supported by six theoretically grounded hypotheses (H1–H6) to guide future empirical research in sustainable digital commerce. Full article

Digital retail is undergoing a paradigm shift driven by the deep integration of artificial intelligence (AI) and augmented reality (AR). Although prior studies have examined the independent effects of AI-based personalized recommendation (cognitive path) and AR-enabled immersion (experiential path), how their integration systematically shapes user behavior through internal psychological mechanisms remains an important unresolved theoretical gap. To address this gap, this study develops an integrated model grounded in the stimulus–organism–response (S-O-R) framework and trust transfer theory. Specifically, the model examines how personalized recommendation, as a dynamic external stimulus, influences users’ cognitive state (perceived usefulness) and experiential state (immersion); how the overall trust of users in the integrated platform can be used as a key boundary condition to adjust the transformation efficiency from the above stimulus to the internal state; and how the above cognitive and experiential states can ultimately drive the continued usage intention through the mediation of positive emotional response. Based on survey data from 400 Chinese consumers with AR shopping experience on Taobao, analyzed using structural equation modeling (SEM), the results indicate that (1) personalized recommendation positively affects both immersion and perceived usefulness; (2) platform trust significantly and positively moderates the effects of personalized recommendation on both immersion and perceived usefulness; (3) both cognitive and experiential states stimulate positive emotions, which in turn enhance continued usage intention, with perceived usefulness exerting a stronger effect; (4) a key theoretical finding is that there is a significant positive correlation between perceived usefulness and immersion, revealing the coupling of psychological paths in an integrated environment; however, immersion does not moderate the effect of personalized recommendation on emotional responses, suggesting that the current integration mode emphasizes the formation of a stable psychological structure rather than real-time interaction. This study makes three contributions to the existing literature. First, it extends the application of S–O–R theory in a complex technological environment by analyzing the “organism” as a parallel and related cognitive-experience dual path and confirming its coupling relationship. Second, it elucidates the enabling role of trust as a moderating mechanism rather than a direct antecedent, thereby enriching micro-level evidence for trust transfer theory in the context of technology integration. Finally, by contrasting path coupling with process regulation, this study provides a more detailed distinction for understanding the theoretical connotations and boundaries of AI–AR technology integration, which may mainly be a kind of structural integration. Full article

Virtual fitting rooms have come a long way, incorporating augmented reality, artificial intelligence, and body scanning technologies to enhance the shopping experience. While the extant literature has provided systematic examinations of consumers’ experience for virtual fitting rooms, factors that affect consumers’ virtual model selection and intention to use virtual fitting rooms remain understudied. This study aims to explore how consumers’ body esteem influences virtual model selection, trust in virtual models, and intention to use virtual fitting rooms. The results of an empirical study in China showed that consumers with high (vs. low) body esteem were more willing to select virtual models with body sizes that were congruent with (vs. larger than) their own, and they were more likely to trust virtual models and use virtual fitting rooms. The preference for thin models and the need for uniqueness produced a moderating effect. These results provide valuable insights into consumers’ intention to use virtual fitting rooms in e-commerce. Full article

Industry 4.0 is steadily advancing a reality of deepening integration between humans and technology, a phenomenon aptly described by the metaphor of the “technologically augmented human”. This study identifies the digital and personal factors that predict a preference for the “digital centaur” strategy among adolescents and young adults. This strategy is defined as a model of human–AI collaboration designed to enhance personal capabilities. A sample of 1841 participants aged 14–39 completed measures assessing digital centaur preference and identification, emotional intelligence (EI), mindfulness, digital competence, technology attitudes, and AI usage, as well as AI-induced emotions and fears. The results indicate that 27.3% of respondents currently identify as digital centaurs, with an additional 41.3% aspiring to adopt this identity within the next decade. This aspiration was most prevalent among 18- to 23-year-olds. Hierarchical regression showed that interpersonal and intrapersonal EI and mindfulness are personal predictors of the digital centaur preference, while digital competence, technophilia, technopessimism (inversely), and daily internet use emerged as significant digital predictors. Notably, intrapersonal EI and mindfulness became non-significant when technology attitudes were included. Digital centaurs predominantly used AI functionally and reported positive emotions (curiosity, pleasure, trust, gratitude) but expressed concerns about human misuse of AI. These findings position the digital centaur as an adaptive and preadaptive strategy for the technologically augmented human. This has direct implications for education, highlighting the need to foster balanced human–AI collaboration. Full article

With the digital transformation of the construction industry toward intelligent construction, advanced digital technologies—including Artificial Intelligence (AI), Digital Twins (DTs), and Internet of Things (IoT)—increasingly support Human–Robot Collaboration (HRC), offering productivity gains while introducing new safety risks. This study presents a systematic review of digital technology applications and risk management practices in HRC scenarios within intelligent construction environments. Following the PRISMA protocol, this study retrieved 7640 publications from the Web of Science database. After screening, 70 high-quality studies were selected for in-depth analysis. This review identifies four core digital technologies central to current HRC research: multi-modal acquisition technology, artificial intelligence learning technology (AI learning technology), Digital Twins (DTs), and Augmented Reality (AR). Based on the findings, this study constructed a systematic framework for digital technology in HRC, consisting of data acquisition and perception, data transmission and storage, intelligent analysis and decision support, human–machine interaction and collaboration, and intelligent equipment and automation. The study highlights core challenges across risk management stages, including difficulties in multi-modal fusion (risk identification), lack of quantitative systems (risk assessment), real-time performance issues (risk response), and weak feedback loops in risk monitoring and continuous improvement. Moreover, future research directions are proposed, including trust in HRC, privacy and ethics, and closed-loop optimization. This research provides theoretical insights and practical recommendations for advancing digital safety systems and supporting the safe digital transformation of the construction industry. These research findings hold significant important implications for advancing the digital transformation of the construction industry and enabling efficient risk management. Full article

Augmented reality (AR) technologies—such as Instagram filters—bridge the digital and physical worlds by allowing users to virtually try on clothing, thereby reducing the risk of virus transmission. In the T-shirt retail industry, AR enables product personalization, decreases the need for physical production, minimizes textile waste, and lowers carbon emissions. It also benefits individuals with limited mobility or those who prefer shopping online. This study tested several hypotheses on 105 active Instagram filter users using filters from the ’Apprecio’ account on mobile devices. Data analyzed using the partial least squares method revealed that interactivity significantly influences both purchase intention and continued use of digital platforms. While hedonic and vivid features enhance the user experience, they have a limited impact on driving purchases or long-term engagement. Customers’ engagement and buying intent are more strongly shaped by practical and interactive elements. The study recommends that companies invest in developing interactive AR features to boost customer satisfaction and foster trust. Future research should involve larger participant samples and investigate specific interactive elements—such as virtual try-on tools—to better understand their impact on consumer behavior. This study highlights the critical role of interactivity in AR for delivering meaningful and engaging shopping experiences. Full article

Large language models (LLMs) now match or exceed human performance on many open-ended language tasks, yet they continue to produce fluent but incorrect statements, which is a failure mode widely referred to as hallucination. In low-stakes settings this may be tolerable; in regulated or safety-critical domains such as financial services, compliance review, and client decision support, it is not. Motivated by these realities, we develop an integrated mitigation framework that layers complementary controls rather than relying on any single technique. The framework combines structured prompt design, retrieval-augmented generation (RAG) with verifiable evidence sources, and targeted fine-tuning aligned with domain truth constraints. Our interest in this problem is practical. Individual mitigation techniques have matured quickly, yet teams deploying LLMs in production routinely report difficulty stitching them together in a coherent, maintainable pipeline. Decisions about when to ground a response in retrieved data, when to escalate uncertainty, how to capture provenance, and how to evaluate fidelity are often made ad hoc. Drawing on experience from financial technology implementations, where even rare hallucinations can carry material cost, regulatory exposure, or loss of customer trust, we aim to provide clearer guidance in the form of an easy-to-follow tutorial. This paper makes four contributions. First, we introduce a three-layer reference architecture that organizes mitigation activities across input governance, evidence-grounded generation, and post-response verification. Second, we describe a lightweight supervisory agent that manages uncertainty signals and triggers escalation (to humans, alternate models, or constrained workflows) when confidence falls below policy thresholds. Third, we analyze common but under-addressed security surfaces relevant to hallucination mitigation, including prompt injection, retrieval poisoning, and policy evasion attacks. Finally, we outline an implementation playbook for production deployment, including evaluation metrics, operational trade-offs, and lessons learned from early financial-services pilots. Full article

Interaction with mobile platforms changes users’ emotional and cognitive engagements through various stimuli cues that respond to behavioural intentions. Emerging technologies such as artificial intelligence (AI) and augmented reality (AR) foster more engagements and transform a new user–platform interaction paradigm in the e-commerce industry. This study signifies the effects of artificial intelligence and augmented reality in assessing user experience for mobile platforms. In this paper, we develop an interaction–engagement–intention model that considers users’ continuance intention based on perceived user experience. The proposed model uniquely explains a nuanced understanding of how the user–platform interactions evolve interactivity, product fit, artificial intelligence-driven recommendation, and online reviews in perceiving spatial presence and subjective norm. This paper explores the importance of attitude and trust as emotional states that influence the user’s behavioural responses. We validate the consequences of user–platform interactions toward continuance intention by conducting an online questionnaire survey and assessing user experience in augmented reality environments. The results contribute to adopting the co-created values of user–platform interactions through cognitive and emotional engagements that affect users’ continuance intention. The platform industry can apply the research outcomes by considering user experience and its implications to enhance the platforms’ capability with a broader aspect. Full article

Air pollution poses a serious threat to both public health and the environment, contributing to millions of premature deaths worldwide each year. The integration of augmented reality (AR), blockchain, and the Internet of Things (IoT) technologies can provide a transformative approach to collaborative air quality monitoring (AQM), enabling real-time, transparent, and intuitive access to environmental data for community awareness, behavioural change, informed decision-making, and proactive responses to pollution challenges. This article presents a unified vision of the key elements and technologies to consider when designing such AQM systems, allowing dynamic and user-friendly immersive air quality data visualization interfaces, secure and trusted data storage, fine-grained data collection through crowdsourcing, and active community learning and participation. It serves as a conceptual basis for any design and implementation of such systems. Full article

Cloud computing has witnessed rapid growth and notable technological progress in recent years. Nevertheless, it is still regarded as being in its early developmental phase, with substantial potential remaining to be explored—particularly through integration with emerging technologies such as the Metaverse, Augmented Reality (AR), and Virtual Reality (VR). As the number of service users increases, so does the demand for computational resources, leading data owners to outsource processing tasks to remote cloud servers. The internet-based delivery of cloud computing services consequently expands the attack surface and impacts the trust relationship between the service user and the service provider. To address these challenges, this study proposes a restricted access control framework based on homomorphic encryption (HE) and identity-based encryption (IBE) mechanisms. A formal analysis of the proposed model is also conducted under an unauthenticated communication model. Simulation results indicate that the proposed approach achieves a 20–40% reduction in encryption and decryption times, respectively, compared with existing state-of-the-art homomorphic encryption schemes. The simulation was performed using a 2048-bit key and data size, consistent with current industry standards, to improve key management efficiency. Additionally, the role-based hierarchy was implemented in a Salesforce cloud environment to ensure secure and restricted access control. Full article

Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), enables immersive experiences across various fields, including entertainment, healthcare, and education. However, its data-intensive and interactive nature introduces significant cybersecurity and privacy challenges. This paper presents a detailed adversary model to identify threat actors and attack vectors in XR environments. We analyze key risks, including identity theft and behavioral data leakage, which can lead to profiling, manipulation, or invasive targeted advertising. To mitigate these risks, we explore technical solutions such as Advanced Encryption Standard (AES), Rivest–Shamir–Adleman (RSA), and Elliptic Curve Cryptography (ECC) for secure data transmission, multi-factor and biometric authentication, data anonymization techniques, and AI-driven anomaly detection for real-time threat monitoring. A comparative benchmark evaluates these solutions’ practicality, strengths, and limitations in XR applications. The findings emphasize the need for a holistic approach, combining robust technical measures with privacy-centric policies, to secure XR ecosystems and ensure user trust. Full article

When users interact with mobile platforms in an Augmented Reality (AR) environment, cognitive and emotional engagements change through different stimuli cues that respond to users’ behavioral intentions. Although AR engages more interactions in mobile platforms, there is a significant gap in assessing UX, considering the physical distance between users and virtual products in a mobile platform. Considering the effect of user generation, the impacts of perceived engagements toward continuance intention through user-platform interactions are unexplored. This study investigated a nuanced understanding of how stimuli cues in augmented reality affect sense of immersion and sense of presence, followed by an Interaction-Engagement-Intention (I-E-I) model. A quantitative method was used to validate the proposed model. Based on an online survey with 886 responses, product fit, network quality, and Artificial Intelligence-driven Recommendation (AIR) influences were assessed for cognitive engagements. This study examined the importance of engaging satisfaction and trust as emotional engagements, influencing users’ continuance intention. The findings showed that sense of presence has a more significant influence on building trust and satisfaction. Also, trust has a more significant impact on the continuance intention to use AR mobile platforms. This study also explored the positive effects of user generation on continuance intention. This could enhance the capabilities of information system designers, researchers, marketing professionals, and solution providers to attain sustainable user retention. Full article

Recently, various emerging technologies have been introduced to host IoT applications. Edge computing, utilizing volunteer devices, could be a feasible solution due to the significant and underutilized resources at the edge. However, cloud providers are still reluctant to offer it as an edge infrastructure service because of the unpredictable nature of volunteer resources. Volunteer edge computing introduces challenges such as reliability, trust, and availability. Testing this infrastructure is prohibitively expensive and not feasible in real-world scenarios. This emerging technology will not be fully realized until dedicated research and development efforts have substantiated its potential for running reliable services. Therefore, this paper proposes VonEdgeSim, a simulation of volunteer edge computing. To the best of our knowledge, it is the first and only simulation capable of mimicking volunteer behavior at the edge. Researchers and developers can utilize this simulation to test and develop resource management models. We conduct experiments with various IoT applications, including Augmented Reality, Infotainment, and Health Monitoring. Our results show that incorporating volunteer devices at the edge can significantly enhance system performance by reducing total task delay, and improving task execution time. This emphasizes the potential of volunteers to provide reliable services in an edge computing environment. The simulation code is publicly available for further development and testing. Full article

The integration of Augmented Reality (AR) into Human–Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI with a focus on manufacturing, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved Situational Awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detailing the critical elements of AR necessary for advancing HRI. The framework outlines effective methods for continuously evaluating AR systems for HRI. The framework is supported with the help of two case studies and another ongoing research endeavor presented in this paper. This structured approach focuses on enhancing collaboration and safety, with a strong emphasis on integrating best practices from Human–Computer Interaction (HCI) centered around user experience and design. Full article