Search Results (1,748)

Digital transformation has fundamentally reshaped hospitality distribution ecosystems, altering how hotels connect with customers, manage commercial relationships, and access market demand. While early digitalization narratives anticipated a process of disintermediation, the growing influence of platform-based intermediaries suggests a different trajectory. This study examines how digital transformation has reconfigured hotel distribution ecosystems through a comparative temporal analysis combining reservation-channel data for the 2023 operating period collected from a survey of Madrid hotels, with European benchmark studies spanning 2011–2023. Distribution channels were classified as traditional channels, direct digital channels, and digitally intermediated integrated channels (DIICs) according to their degree of technological integration and intermediary control. The harmonized evidence indicates a decline in the harmonized traditional channel, moderate growth in direct digital channels, and higher DIIC reservation shares across the harmonized benchmark evidence. Early European benchmark studies generally reported DIIC shares of approximately 22–24%, whereas the participating Madrid hotels recorded an average share of 49.3%. Overall, the harmonized evidence is consistent with a long-term shift towards digitally intermediated integrated channels, suggesting that digital transformation has reinforced digital reintermediation rather than effective disintermediation. The study contributes to the literature by providing comparative evidence of long-term changes in hotel distribution structures and by introducing the DIIC framework as an analytical lens for examining digitally mediated intermediation. More broadly, the findings support perspectives that conceptualize tourism digital transformation as a process of platformization and ecosystem reconfiguration rather than simply the adoption of new technologies. Full article

The automatic inspection of airport infrastructure, specifically horizontal surface markings and Airfield Ground Lighting (AGL), is a critical task for maintaining aviation safety and operational efficiency. As the aviation industry shifts from manual surveys to automated visual inspections utilizing unmanned aerial vehicles (UAVs) and smart service vehicles, the demand for robust, real-time computer vision systems has surged. However, deploying computationally intensive deep learning models in the field introduces severe Size, Weight, and Power (SWaP) constraints. This paper presents a comprehensive framework for the semantic segmentation of runway/taxiway markings and the point-localization of AGL lamps, specifically focusing on the deployment paradigm shift from the expensive, GPU-accelerated heterogeneous system on chip (SoC) to highly efficient, dedicated Neural Processing Units (NPUs). We evaluate the performance of U-Net, LinkNet, U-Net-Point and HRNet-Lite-Point architectures trained on a custom dataset from the Poznań-Ławica Airport. Crucially, this study conducts a rigorous comparative hardware analysis between the flagship NVIDIA Jetson AGX Orin and a highly cost-effective heterogeneous setup comprising a Raspberry Pi 5 augmented with an NPU Hailo-8 AI accelerator. Experimental results demonstrate that while both platforms achieve real-time inference, the Hailo-8 integration fundamentally disrupts the traditional cost-to-performance ratio. Furthermore, the Hailo-8 configuration consumed less electrical power and memory footprint required by the Jetson, proving that dedicated NPUs are vastly superior for continuous, battery-operated edge deployment in autonomous airport maintenance systems. Specifically, the Raspberry Pi setup with the Hailo-8 accelerator demonstrated superior energy efficiency, requiring a significantly lower energy consumption per processed video frame compared to the Jetson platform. Full article

Responsible tourism practices are essential for sustainable tourism development, yet evidence on their implementation across different types of tourism enterprises remains limited. This study examines reported responsible tourism practices, together with the motivations and barriers influencing their implementation among tourism enterprises in Kien Giang province, Vietnam. A mixed-methods approach was employed, involving focus group discussions with 24 participants to develop the measurement indicators and a questionnaire survey of 125 tourism business representatives and 70 employees. Descriptive analysis revealed that only a few responsible tourism practices were reported at very high levels, including employee welfare, customer protection, fair recruitment, price transparency, avoidance of legally protected wild flora and fauna, and the provision of multiple waste bins. Most economic, social, and environmental practices were reported at lower levels, indicating substantial room for improvement. The main motivations were environmental protection, long-term business sustainability, tourist satisfaction, operational efficiency, and ethical responsibility, whereas inadequate training, limited awareness, insufficient implementation knowledge, and weak institutional support were the principal barriers. These findings suggest that targeted capacity building and stronger institutional support are needed to address implementation gaps and strengthen responsible tourism practices in Kien Giang province and other emerging tourism destinations. Full article

Objective: This study investigates the relationship between social media use and consumer purchase intentions or out-of-home food choices in the Polish gastronomic market, focusing specifically on variations across generations. Methodology: Data were collected between May and July 2024 through a diagnostic survey using the Computer-Assisted Web Interviewing (CAWI) technique (N = 1099). Respondents were recruited via a non-probability quota sampling approach based on strict demographic inclusion criteria. To test the research hypotheses regarding generational variations in market behaviour, a multivariate discriminant function analysis was performed using Statistica 13.1 PL. A preliminary pilot study (N = 30) confirmed the initial questionnaire readability and overall consistency (Cronbach’s alpha = 0.87), while subscales were treated independently during the main analysis. Results: Multivariate models were found to be highly significant, revealing clear differences between age groups. The youngest cohort (aged 18–35) relies heavily on Instagram and TikTok, showing distinct patterns regarding visual triggers such as “instagrammable” aesthetics, digital validation, and menu uniqueness alongside weight loss claims. Conversely, seniors (aged 61 and older) lean unexpectedly towards X. This older segment displays pragmatic, utility-driven motives, searching for detailed textual data about ingredients and the health-promoting properties of food. General product quality and calorie control were identified as universal factors that do not vary by generation. Conclusions and Managerial Implications: The digital transformation of the Polish restaurant industry does not follow a single path. Social media is closely linked to modern customer journeys, with physical dining spots frequently serving as spaces for socialisation. Consequently, restaurant operators should move away from mass communication and adopt a selective omnichannel strategy, where message formats shift from visual appeal to factual, nutrition-oriented text that is tailored to the digital literacy and dietary needs of each generation. Full article

Corporate social responsibility (CSR) can create value through stakeholder responses, but credence-goods settings make it important to distinguish broad reputational evaluations from trust-based reliance on the producer. Integrating signaling and stakeholder theories, this study examines corporate reputation and employee-perceived customer trust as parallel mechanisms linking CSR to employee-perceived firm performance in Yunnan’s tea industry. The study builds on prior CSR mediation research by using a signal–response conversion perspective to clarify how signaling and stakeholder theories differentiate two established stakeholder responses: accumulated evaluative standing (corporate reputation) and perceived relational reliance (employee-perceived customer trust). Survey data from 489 employees were analyzed using a covariance-based seven-factor CFA under explicit maximum-likelihood estimation, observed-composite path regressions, one 5000-resample percentile-bootstrap mediation analysis, and hierarchical moderation tests. Both indirect effects were significant, while the post-mediation direct effect was not (B = 0.083, SE = 0.086, t = 0.967, p = 0.334, 95% CI [−0.086, 0.252]). The customer-trust pathway had the larger point estimate, but the bootstrap contrast was not significant (difference = 0.081, 95% CI [−0.011, 0.177]). Firm size did not moderate the CSR–performance relationship. The findings support two distinct stakeholder-response pathways without establishing that one is statistically stronger; because credence intensity was not itself measured, the industry setting is treated as the theoretical context rather than as an empirically tested moderator. Full article

Large language model-enabled virtual patients may expand access to clinical skills practice by supporting explicitly defined practice tasks. This program evaluation examined medical students’ awareness, use, and perceptions of the McMaster Virtual SP Tool, a custom generative artificial intelligence tool developed to supplement clinical skills practice. We conducted an anonymous, single-institution cross-sectional survey of students across three cohorts at McMaster University. Quantitative responses were summarized descriptively, and free-text responses were analyzed using qualitative content analysis informed by task-aligned fidelity, deliberate practice, learner-centred feedback, and simulation instructional design. Thirty-five students responded; 23 (65.7%) were aware of the tool and 16 (45.7%) had used it. Among the 16 users, 15/16 (93.8%) found the tool at least somewhat easy to navigate; 13 (81.3%) would use it again; and 13 (81.3%) would recommend it. Across all respondents, 14/35 (40.0%) reported using AI-enabled virtual patients for OSCE preparation. Users valued its accessibility, independent low-stakes rehearsal, and usefulness for focused history-taking, question wording, and clinical reasoning. Perceived limitations included reduced human connection, nonverbal and emotional realism, physical examination practice, and feedback specificity. AI-enabled virtual patients may therefore be considered as adjuncts for selected cognitive and structural rehearsal tasks. Objective educational outcomes were not assessed. Full article

Integrating Corporate Social Responsibility (CSR) into business strategy requires organizational practices that convert sustainability- and stakeholder-related intentions into measurable and managerially usable information. This study examines whether distinct Business Performance Measurement (BPM) maturity profiles can be identified among hospitality SMEs and how these profiles are associated with sustainability- and stakeholder-oriented measurement practices. BPM maturity is defined as a multidimensional organizational capability reflected in the breadth, integration, monitoring, interpretation, and use of performance information, rather than merely in the possession of a formal measurement system. Using cross-sectional survey data from 600 decision-makers in Hungarian and Romanian accommodation and food service SMEs, the study applies Principal Component Analysis and Two-Step Cluster Analysis. Three profiles emerge: Integrated, Transitional, and Low BPM Maturity. Firms in the Integrated profile report broader use of financial, customer-related, employee-related, sector-specific, and sustainability-oriented performance information, whereas firms in the Low profile report more limited measurement practices. Sustainability- and development-related measurement practices provide the strongest relative contribution to profile differentiation in both national models. The findings demonstrate systematic associations between BPM maturity profiles and sustainability- and stakeholder-oriented measurement practices. They are consistent with the theoretical interpretation that BPM maturity may provide organizational conditions supporting the operationalization of responsible management intentions. However, the cross-sectional design does not establish causal direction, and the study does not directly measure formal CSR implementation or sustainability outcomes. Full article

Self-checkout (SCO) systems have become an integral part of modern retail, yet their increasing popularity has also revealed a number of technical and usability challenges that influence customer experience and technology acceptance. This paper investigates human–machine interaction in self-checkout systems based on a survey conducted among 419 young adults in Poland. The study combines quantitative and qualitative analyses to identify the most commonly reported technical difficulties, users’ attitudes toward current self-checkout systems, and their expectations regarding future technological developments. The results indicate that although self-checkout systems are generally perceived as intuitive, convenient, and time-saving, their broader acceptance is limited by recurring self-reported problems related to age verification, weighing scales, product recognition, and the need for employee intervention. Respondents consistently emphasized that future technological innovations should build upon reliable and user-centered existing systems by addressing current usability limitations before introducing entirely new functionalities. At the same time, they expressed a positive attitude toward AI-assisted solutions, including automated product recognition and intelligent age verification, provided that these technologies increase perceived reliability and preserve users’ sense of control. The findings highlight that successful technological innovation in self-checkout systems should be driven by human-centered design, with improvements in usability forming the foundation for the adoption of future AI-assisted solutions. Full article

The proliferation of Edge-AI in personalized healthcare has driven significant demand for energy-efficient Systems-on-Chip (SoCs) capable of executing high-accuracy, real-time disease detection. Conventional accelerator architectures struggle to simultaneously accommodate disparate AI models. Specifically, memory-intensive Convolutional Neural Networks (CNNs) for high-fidelity feature extraction and event-driven Spiking Neural Networks (SNNs) for ultra-low-power, brain-inspired computation. To address this bottleneck, this paper presents a comprehensive survey of Reconfigurable Hybrid Neural Networks (RHNNs), an emerging paradigm that dynamically merges the strengths of CNNs and SNNs to meet the stringent resource constraints of biomedical edge devices. We establish a comprehensive taxonomy of existing RHNN architectures, categorizing them by hardware interconnection topologies, dataflow orchestration strategies, and internal structural adaptation mechanisms. Furthermore, we examine the integration of these hybrid accelerators within the open-source RISC-V processor ecosystem, evaluating how custom instruction set extensions optimize control efficiency and minimize energy overhead. The survey also analyzes commonly used datasets based on three major biomedical signal modalities, including electroencephalography (EEG), electrocardiography (ECG), and electromyography (EMG), in the context of processing systems for hardware accelerators. Finally, we highlight the open research challenges and outline future research directions to guide the development of next-generation biomedical intelligent systems. Full article

Background/Objectives: Although efficacious in randomized trials, the real-world adoption of AI-driven dietary management applications remains uncertain across diverse dining contexts and populations. Methods: This field-based observational study was conducted over 18 days at three real-world dining sites in Shanghai, China, enrolling 181 participants stratified into three groups based on food service style and customer attribute. A cross-sectional survey was administered on day 9, followed by a 9-day prospective usage tracking period. Results: After adjusting for sex, Group 2 (staff cafeteria with fixed-portion dishes) had the highest adjusted mean usability score at 71.20 (p < 0.001). Group 3 (community canteen) had the highest mean scores for information quality (16.57, p = 0.03) and perceptions of intended use in nutrition (12.01, p = 0.08). However, Group 3 recorded zero active usage sessions despite favorable initial perceptions. Conclusions: Favorable user perceptions of this AI-driven dietary management tool did not automatically translate into adoption. Scenario-specific usability and digital divide constraints define the boundary of real-world efficacy; moreover, AI may amplify existing dietary self-management behaviors rather than creating them de novo. Full article

Background: The transition towards a more sustainable global economy requires meaningful changes in the way organisations purchase products across industrial value chains. Whilst extensive research has explored sustainable consumption within the business-to-consumer (B2C) space, comparatively little research has examined the antecedents of sustainable purchasing intent within business-to-business (B2B) environments. Existing literature has predominantly focused on individual behavioural determinants, and has under-explored the organisational, informational and product-level antecedents that shape sustainable purchasing decisions within industrial contexts. Objectives: This research explores the antecedents of sustainable purchasing intent within the chemical and ingredients value chain, and develops a novel integrated framework, the Business-to-Business Sustainable Buying Behaviour (B2B-SBB) Model, capable of explaining sustainable purchasing intent within the B2B setting. Methods: An abductive, mixed-methods, single-case study design was adopted, set within the customer base of a global chemical and ingredient distributor. Twelve semi-structured interviews were conducted with purchasing professionals across six end-market segments, and a quantitative survey generated 57 complete responses from a global customer base. Qualitative data were analysed through thematic analysis, and quantitative data through descriptive statistics and Wilcoxon Signed Rank testing. Results: The findings indicate that organisational antecedents, including buying centre process and responsibilities, corporate sustainability commitments, and information flow, exert materially greater influence on B2B sustainable purchasing intent than individual behavioural antecedents. Product sustainability claim variables emerge as a distinct and material antecedent, with a strong and statistically significant preference for third-party assured claims over self-declared claims. A structural value–action gap is also observed between publicly stated sustainability commitments and observed purchasing behaviour. Conclusions: The findings indicate that sustainable purchasing intent within the B2B chemical value chain is best understood through an integrated framework combining individual, organisational, environmental, product sustainability and information-flow antecedents. The proposed B2B-SBB Model provides such a framework, and offers both theoretical extension of existing scholarship and practical application for organisations seeking to accelerate the adoption of more sustainable products within industrial value chains. Full article

Background: Traditional osteopathic manipulative medicine (OMM) instruction relies on laboratory sessions constrained by scheduling, faculty availability, and practice partner variability. Virtual reality (VR) may address these limitations by providing on-demand access to standardized training scenarios. This pilot feasibility and acceptability study evaluated first-year osteopathic medical students’ motivational responses and perceptions of a novel VR training module focused on thoracic spine assessment techniques. Methods: This pilot single-arm observational study enrolled 45 first-year students at the New York Institute of Technology College of Osteopathic Medicine to assess the feasibility and acceptability of VR-based OMM instruction. A VR training module developed using Unity 3D and deployed on Oculus Quest headsets included 40 interactive assessment items covering thoracic diagnostic techniques. Participants received one-week access to the program then completed the Reduced Instructional Materials Motivation Survey (RIMMS) based on the Attention, Relevance, Confidence, and Satisfaction (ARCS) model and a custom 10-item feedback survey. Session duration and assessment scores were automatically recorded. Descriptive statistics and Pearson correlation analysis were performed. Results: The Relevance domain achieved the highest RIMMS composite mean (3.98), while Attention demonstrated the greatest opportunity for enhancement (3.49). The overall RIMMS composite score was 3.81, indicating favorable motivational reception. Feedback survey results showed that 89.2 percent of participants endorsed the VR experience as educationally positive, and 81.1 percent supported expansion to additional OMM procedures. Performance analysis revealed minimal correlation between session duration and assessment scores (R² = 0.0169). Conclusions: First-year osteopathic medical students demonstrated positive motivational responses and favorable perceptions toward VR-based OMM training. Based on student perception and feasibility, these findings suggest VR is well-received and perceived by students as a potentially viable supplement to traditional OMM instruction, though attention-capturing elements and interface usability warrant refinement. This pilot study did not measure learning outcomes or skill acquisition. Full article

Personalized Federated Learning (PFL) has emerged as a key approach to address performance degradation in FL systems under heterogeneous client data. While existing surveys typically categorize PFL methods based on optimization strategies or system-level mechanisms, they often overlook a fundamental question: where is personalization embedded within the model architecture? In this survey, we bridge this knowledge gap and introduce a granularity-centered taxonomy that organizes PFL approaches according to the structural depth of personalization, ranging from head-layer and layer-wise adaptation to model-wise and parameter-wise customization. This novel perspective helps practitioners select appropriate personalization strategies based on model architecture, data heterogeneity, and system constraints. By analyzing representative works published between 2016 and 2026, we identify recurring design bottlenecks and highlight key opportunities for improving personalization across different granularity levels. While existing surveys focus solely on algorithms, our taxonomy provides practitioners and researchers with the informed guidance needed to design scalable and effective PFL systems. Building upon this analysis, we also formulate and discuss several unaddressed open challenges currently present in the field, highlighting specific roadblocks and unresolved questions that must be addressed to drive the future evolution of PFL methodologies. Full article

This study examines how immigrants build the everyday foundations of life in the host society through food provisioning practices. Many previous studies have explored immigrant adaptation from organizational or cultural perspectives. By contrast, this study focuses on the daily procurement of familiar food. It views food provisioning as part of the ongoing process of home in the making, through which home gradually takes shape in everyday life by linking material access, social relations, and cultural continuity. The desire for familiar food is common among immigrants and reflects the habitus embodied through everyday food practices. As migrants enter a new social and material field, this habitus is continuously negotiated and adapted, giving rise to new food provisioning practices. Against this theoretical background, this study examines how these everyday practices shape immigrants’ lives in the host society. This study takes Chinese residents in Japan as research subjects. Based on a questionnaire survey of 317 Chinese residents, this study shows that fresh vegetables and fruits are perceived as particularly difficult to obtain. Some Chinese residents therefore use diverse provisioning practices, including home gardening, sharing, exchange, and small-scale sales. The study then examines cases of Chinese residents’ home gardens and small-scale commercial gardens as sites of food provisioning. The qualitative cases reveal that crop choices, cultivation methods, circulation routes, and garden scale are flexibly adjusted according to family needs, customer demand, land access, labor capacity, and seasonality. These practices enable Chinese residents to secure familiar food, organize everyday life, and develop social relations with co-ethnic residents and members of the wider local society. The findings suggest that garden-based food provisioning represents an informal, everyday pathway of integration shaped by the material and social conditions of life in Japan. Full article

Online furniture commerce has expanded, yet sustaining continuance purchase intention (CPI) remains challenging because furniture is a high-involvement product that consumers prefer to inspect physically. Drawing on the Stimulus–Organism–Response (SOR) framework, this study examines how social media marketing activity, product quality, and customer experience are associated with CPI through transactional appraisals (perceived value and customer satisfaction) and relational appraisals (customer trust and customer loyalty). An exploratory sequential mixed-methods design combined a three-round e-Delphi study with 19 experts and a survey of 1351 Thai consumers who had purchased furniture online. Data were analyzed using covariance-based structural equation modeling, bootstrapped indirect-effect analysis, and fuzzy-set qualitative comparative analysis (fsQCA). Customer loyalty and customer trust showed the strongest positive associations with CPI. Customer satisfaction showed a negative direct but significant positive indirect association through customer loyalty. Constraining the SAT → CPI path to zero significantly worsened model fit; however, the negative coefficient did not support the hypothesized positive association and should be interpreted cautiously as a model-conditional association. The fsQCA identified multiple sufficient configurations associated with high CPI, illustrating equifinality. The findings extend SOR to high-involvement commerce by integrating transactional and relational appraisals and complementary symmetric and configurational evidence. Full article