Search Results (554)

Against the backdrop of economic recovery and ongoing market restructuring, China’s hotel industry is undergoing a significant shift from being service-based to becoming strategy-driven and competitive. This study aims to identify the key factors driving hotel competitiveness utilizing a multidimensional quantitative perspective. Based on a structured questionnaire survey administered to hotel managers across provinces and cities in China, primary data was collected from a total of 727 valid responses. As such, exploratory factor analysis, comprising 31 ranked items, and multiple regression analysis were performed using SPSS, identifying four dimensions that significantly affect hotel competitiveness: namely, operational characteristics, service quality, customer satisfaction, and competitive performance. The results show that operational characteristics are the primary determinants of hotel competitiveness. Specifically, sustainable development strategy, digital technology adoption, product and service innovation, and pricing strategies were the most significant factors leading to competitive advantage. Unlike previous studies that emphasized service quality and customer satisfaction as the dominant drivers of competitiveness, this study finds that a hotel’s competitive advantage relies heavily on developing strategic operational innovation and resource allocation capabilities. This study’s novelty lies in its use of national empirical data to validate the multidimensional composition and inherent logical relationships for competitive advantage. It also proposes a multidimensional framework for analyzing hotel competitiveness, specifically designed for the developmental characteristics of China’s hotel industry, highlighting the need to transform from a service-oriented to a strategy-driven operational approach. The findings of this paper offer empirical evidence for hotel enterprises to refine management structures, foster innovation, and thereby develop strong capabilities for a sustainable competitive advantage. Full article

In an era where economies increasingly rely on knowledge and innovation, sustaining long-term growth depends on understanding how education drives productivity beyond conventional measures. Yet, existing studies on the education–growth nexus remain fragmented, often focusing narrowly on schooling attainment while overlooking the complementary roles of lifelong learning and public investment in human capital. Addressing this critical gap, the present study adopts a multidimensional approach to evaluate how educational attainment, adult learning participation, and government expenditure on education collectively shape economic performance across the 27 European Union (EU) member states. Drawing on an unbalanced Eurostat panel dataset (2013–2022), the study employs a fixed-effects regression model with White cross-section robust standard errors to account for heteroskedasticity and serial correlation. The empirical results reveal that all three educational dimensions exert positive and statistically significant effects on GDP, with government educational expenditure emerging as the most influential driver, followed by adult learning participation, underscoring the transformative role of continuous skill renewal in dynamic labor markets. These findings advance Human Capital Theory by framing education not merely as an individual asset but as an interactive, systemic driver of national productivity and resilience. The study offers actionable insights for policymakers, calling for integrated strategies that align formal education, lifelong learning systems, and sustained public investment to foster inclusive, knowledge-driven, and sustainable economic growth across the EU. Full article

Poor diet is the leading preventable risk factor for death worldwide, associated with over 10 million premature deaths and USD 8 trillion related costs every year. Artificial intelligence or AI is rapidly emerging as the most historically disruptive, innovatively dynamic, rapidly scaled, cost-efficient, and economically productive technology (which is increasingly providing transformative countermeasures to these negative health trends, especially in low- and middle-income countries (LMICs) and underserved communities which bear the greatest burden from them). Yet widespread confusion persists among healthcare systems and policymakers on how to best identify, integrate, and evolve the safe, trusted, effective, affordable, and equitable AI solutions that are right for their communities, especially in public health nutrition. We therefore provide here the first known global, comprehensive, and actionable narrative review of the state of the art of AI-accelerated nutrition assessment and healthy eating for healthcare systems, generated by the first automated end-to-end empirical index for responsible health AI readiness and maturity: the Responsible Health AI readiness and Maturity Index (RHAMI). The index is built and the analysis and review conducted by a multi-national team spanning the Global North and South, consisting of front-line clinicians, ethicists, engineers, executives, administrators, public health practitioners, and policymakers. RHAMI analysis identified the top-performing healthcare systems and their nutrition AI, along with leading use cases including multimodal edge AI nutrition assessments as ambient intelligence, the strategic scaling of practical embedded precision nutrition platforms, and sovereign swarm agentic AI social networks for sustainable healthy diets. This index-based review is meant to facilitate standardized, continuous, automated, and real-time multi-disciplinary and multi-dimensional strategic planning, implementation, and optimization of AI capabilities and functionalities worldwide, aligned with healthcare systems’ strategic objectives, practical constraints, and local cultural values. The ultimate strategic objectives of the RHAMI’s application for AI-accelerated public health nutrition are to improve population health, financial efficiency, and societal equity through the global cooperation of the public and private sectors stretching across the Global North and South. Full article

In the context of Industry 4.0, digital transformation is reshaping global energy systems. Among the key enabling technologies, Digital Twin (DT)—a dynamic, virtual replica of physical systems—has emerged as a critical tool for improving the performance, reliability, and safety of clean energy infrastructure. In line with the United Nations Sustainable Development Goals (SDGs)—particularly SDG 7 (Affordable and Clean Energy) and SDG 11 (Sustainable Cities and Communities)—the integration of DTs presents unprecedented opportunities to enhance operational efficiency and support proactive decision making. This state-of-the-art review, focused on studies published in 2020–2025, summarizes applications of DTs across the energy value chain, encompassing a broad spectrum of sectors—including solar, wind, hydropower, hydrogen, geothermal, bioenergy, nuclear, and tidal energy—and their critical role in building-to-grid integration. It synthesizes foundational concepts, assesses the evolution of the DT from a predictive tool to a system-level risk-management platform, and provides a critical analysis of its impact. Furthermore, this review discusses the key challenges hindering widespread adoption, including the critical need for interoperability across systems, ensuring the cybersecurity of socio-technical infrastructure, and addressing the complexities of the human-in-the-loop problem. Key research gaps are identified to guide future innovation. Ultimately, this study underscores the transformative potential of DTs as essential tools for accelerating the digital transformation of the energy sector, offering a robust framework for both methodological development and practical deployment. Full article

The global production of electronic waste (e-waste) has increased due to the quick turnover of electronic devices, creating urgent problems for resource management and environmental sustainability. As a result, e-waste-derived materials (EWDMs) are being explored in pavement engineering research as sustainable substitutes in line with Sustainable Development Goals (SDGs), specifically SDG 9 (Industry, Innovation, and Infrastructure), 11 (Sustainable Cities and Communities), 12 (Responsible Consumption and Production), and 13 (Climate Action). Therefore, to assess global research production and the effectiveness of EWDMs in asphalt applications, this review combines scientometric mapping and systematic evidence synthesis. A total of 276 relevant publications were identified via a thorough search of Web of Science, Scopus, and ScienceDirect (2010–2025). These were examined via coauthorship structures, keyword networks, and contributions at the national level. The review revealed that China, India, and the United States are prominent research hubs. Additionally, experimental studies have shown that EWDMs, such as printed circuit board powder, fluorescent lamp waste glass, high-impact polystyrene, and acrylonitrile–butadiene–styrene, improve the fatigue life, Marshall stability, rutting resistance (up to 35%), and stiffness (up to 28%). However, issues with long-term field durability, microplastic release, heavy metal leaching, and chemical compatibility still exist. These restrictions highlight the necessity for standardised toxicity testing, harmonised mixed-design frameworks, and performance standards unique to EWDMs. Overall, the review shows that e-waste valorisation can lower carbon emissions, landfill build-up, and virgin material extraction, highlighting its potential in the circular pavement industry and promoting sustainable paving practices in accordance with SDGs 9, 11, 12, and 13. This review suggests that further studies on large-scale field trials, life cycles, and technoeconomic assessments are needed to guarantee the safe, long-lasting integration of EWDMs in pavements. It also advocates for coordinated research, supportive policies, and standardised methods. Full article

In developing countries, technology-based startups (TBSs) play a vital role in driving innovation, and they significantly contribute to the generation of jobs and economic development. However, despite their importance, startups have a high failure rate worldwide, and a major contributing factor is a lack of funding. The objective of this study is to compare the existing financing mechanisms in Ethiopia, Uganda, and Kenya and determine the relative position of Ethiopia in the financing landscape. This study was based on resource-based theory and signaling theory. A desk research methodology was employed, and a total of 70 sources were reviewed. The data sources include academic literature, publications from the World Bank, local reports, government policies of the three nations, articles published in reputable journals, and global database indexes. Articles were also selected based on their relevance to the research question and the credibility of the publication. The comparison was carried out based on identifying similarities and differences in economic indicators, the innovation performance of the countries, the innovation eco-system, the types of existing financing mechanisms in each country, and various government policies and initiatives. We also validated our findings by cross-checking information from multiple sources to avoid bias. The results reveal that Ethiopia is lagging behind in most of the parameters set for comparison, while its neighbors, Uganda and Kenya, have a relatively better status in general. Finally, this study has theoretical and practical implications. Full article

Background: This study examines how national innovation performance shapes the diffusion of advanced diagnostic technologies across European healthcare systems. Strengthening technological capacity through innovation is increasingly essential for resilient and efficient health services. The analysis quantifies the influence of innovation capacity on the availability of medical imaging technologies in 26 EU Member States between 2018 and 2024. Methods: A balanced panel dataset was assembled from Eurostat, the European Innovation Scoreboard, and World Bank indicators. Dynamic relationships between innovation performance and the adoption of CT, MRI, gamma cameras, and PET scanners were estimated using a two-step approach combining General-to-Specific (GETS) outlier detection with Robust Least Squares regression to address heterogeneity and specification uncertainty. Results: Higher innovation scores significantly increase the diffusion of R&D-intensive technologies such as MRI and PET, while CT availability shows limited responsiveness due to market maturity. Public health expenditure supports frontier technologies when strategically targeted, whereas GDP growth has no significant effect. Population size consistently enhances technological capacity through scale and system-integration effects. Conclusions: The findings show that innovation ecosystems, rather than economic growth alone, drive the modernization of diagnostic infrastructure in the EU. Integrating innovation metrics into health-technology assessments offers a more accurate basis for designing innovation-oriented investment policies in European healthcare. Full article

An effective housing policy must ensure affordability for individuals across all income levels by integrating advanced technological innovations with comprehensive socioeconomic strategies. Affordable housing fosters social inclusion, whereas sustainability supports long-term environmental protection and economic stability. The success and long-term sustainability of affordable housing initiatives are heavily influenced by current socioeconomic conditions, emphasizing the need for context-specific, inclusive, and sustainable housing solutions. Benchmarks are crucial in affordable housing to determine if it is climate-positive, aligning with the goals of the United Nations’ Sustainable Development Goal 11.1, which seeks to provide affordable and sustainable housing for everyone by 2030. This study uses the Scopus database to perform a scientometric analysis of 595 publications (2015–2024) on sustainability and affordability in housing. Using R-Studio 2025.05.1 + 513.pro3 and VOSviewer 1.6.20, it examines bibliographic trends, research gaps, and collaboration patterns across countries and journals. This study highlights performance thresholds related to economic, environmental, energy, territorial, and climatic factors. However, cost and ecological objectives can cause conflict with each other practically, and hence a balanced approach including green practices, efficient materials, and subsidies is crucial. There is a need for policymakers to address market gaps to prevent socially exclusive or environmentally harmful outcomes, maintain long-term urban resilience, and ensure sustained urban resilience and equitable access to affordable, sustainable housing by 2030. Integrating sustainable materials, circular and climate-resilient design, smart technologies, inclusive governance, and evidence-based policies is crucial for advancing affordable, equitable, and resilient housing. This approach guides future research and policy toward long-term social, economic, and environmental benefits. The findings and recommendations promote sustainable, affordable housing, emphasizing the need for further research on climate-resilient, energy-efficient, and cost-effective building solutions. Full article

The upstream oil and gas (O&G) industry faces persistent challenges, including volatile oil prices, declining reserves, and the increasing prominence of renewable energy sources. In response, the Indonesian government has set an ambitious target to increase national O&G production by 70% by 2030. This goal requires upstream O&G producers to adopt innovative approaches that enhance performance and resilience. This study emphasizes organizational agility as a critical capability for organizations in VUCA environments to remain resilient and competitive. This study examines the influence of relevant agility enablers on Indonesian upstream O&G, ensuring that no critical factors are overlooked in the implementation of agility. The human–technology–organization (HTO) framework was used to conceptualize and examine its role in supporting organizational agility. Data were collected from 103 managerial-level respondents representing 27 producer companies representing more than 75% of Indonesia’s overall O&G production. PLS-SEM was employed to examine whether relationships existed among predictor variables and organizational agility. The results highlight HTO, leadership, and innovation capacity as significant enablers of organizational agility. This study contributes theoretically and practically by integrating the HTO framework into the agility discourse and offering a comprehensive view of agility enablers that foster transformation, resilience, and sustainability of Indonesia’s upstream O&G sector. Full article

The rising presence of artificial intelligence (AI) across European industries is gradually reshaping how societies manage resources, reduce waste, and pursue long-term sustainability. While researchers widely acknowledge the economic and social implications of AI, they have not yet sufficiently explored its contribution to advancing a circular economy. This study examines how varying levels of AI adoption across EU Member States relate to material footprint, resource productivity, waste generation, and recycling performance. The analysis draws on harmonized Eurostat data from 2023, the most recent year for which complete and comparable indicators are available, enabling a coherent cross-sectional perspective that reflects the period when AI began to exert a more visible influence on economic and environmental practices. By combining measures of AI uptake with key circular economy indicators and applying factor analysis, neural network modelling, and cluster analysis, the study identifies underlying patterns and country-specific profiles. The results suggest that higher AI adoption is often associated with greater resource productivity and more efficient material use. However, its effects on waste generation and recycling remain uneven across Member States. These findings indicate that AI can support circular economy objectives when embedded in coordinated national strategies and supported by robust institutional frameworks. Strengthening the alignment between digital innovation and sustainability goals may help build more resilient, resource-efficient economies across Europe. Full article

This study examines the impact of Green Entrepreneurial Orientation (GEO), Managerial Environmental Concerns (MECs), and Green Absorptive Capacity (GAC) on the environmental performance of Pakistani SMEs. The Dynamic Capabilities View (DCV) and Natural Resource-Based View (NRBV) demonstrate that innovation focused on sustainability and competitive advantage is enhanced by managerial engagement, knowledge capability, and environmental awareness. A cross-sectional survey involving 350 managers of SMEs in Pakistan utilized covariance-based structural equation modeling (CB-SEM). The MEC-to-GEO direction was insignificant, and this implies that the issue of managerial concern is not a driving force towards the initiation of green entrepreneurial endeavors. The confirmatory factor analysis model for the 350 SMEs demonstrates a satisfactory fit (CFI = 0.947; RMSEA = 0.073), along with reliability and validity. GEO and EP are positively influenced by GAC and MECs, with R² values of 0.204 and 0.526, respectively. The findings indicate that the absorptive and managerial capabilities of SMEs can integrate environmental responsibility into strategic decision-making, exceeding regulatory criteria to foster proactive environmental innovation. The study emphasizes ethical leadership, environmental competitiveness, and social responsibility through green information management and cooperative networks. The sustainability ideas and GEO are enhanced in developing nations by linking global green initiatives with local institutions and cultural contexts. Organizational management and policymakers should promote environmental education, ecological innovations, and sustainable practices within sectors. The limitations of the study include the use of self-reported data and cross-sectoral replication utilizing objective environmental indicators. Full article

Background: Traditional fermented foods from Türkiye are integral components of the nation’s culinary heritage, reflecting a remarkable diversity shaped by local practices and ecosystems. These products embody region-specific microbial communities, often conceptualized as a “microbial terroir,” which influence their sensory qualities, nutritional value, and health-promoting properties. Methods: This study followed the PRISMA 2020 guidelines and included a systematic review and bibliometric analysis. A structured search was conducted in the Web of Science Core Collection (WoSCC) on 15 January 2025 using predefined keywords related to Turkish fermented foods and fermentation processes. Records were screened based on language (English or Turkish) and document type (articles, reviews, book chapters, and early access). A total of 1464 studies met the eligibility criteria, reflecting a 2.81% annual growth rate and a 12.7% international co-authorship rate. Bibliometric analysis was performed using the bibliometrix R package (RStudio 2024.12.1) and the biblioshiny interface. Results: The analysis revealed that the diversity of microbial consortia in Turkish fermented foods contributes to their distinctive characteristics, including enhanced nutritional profiles, probiotic potential, and food safety attributes. Emerging studies employing omics technologies—such as next-generation sequencing, metagenomics, and metabolomics—have expanded our understanding of fermentation ecosystems. Additionally, the growing integration of artificial intelligence supports predictive modeling and process optimization for advanced quality control. Conclusion: This synthesis highlights the significant technological, nutritional, and cultural value of Türkiye’s traditional fermented foods. Future directions should include omics-based translational research, indigenous starter culture development, and strengthened international collaborations to support sustainable and competitive functional food innovation. Full article

This study investigates the factors that influence the acceptance of 3D concrete printing technology in South Africa. The purpose is to provide evidence-based insights to guide regulators in developing clear standards and certification pathways for 3DCP in South Africa. In a mixed-method research design, the study gathered data from professionals including architects, civil engineers, quantity surveyors, project managers, contractors, regulators, and local municipalities using a modified Unified Theory of Acceptance and Use of Technology framework, adapted to the institutional and infrastructure contextual nuances of South Africa. The findings indicate significant variability in awareness, exposure, and openness to 3DCP across professions and regions. Regulatory actors express caution due to the absence of national standards but also recognize the potential alignment with sustainable construction goals. Major enablers of acceptance include access to demonstrable case studies, technical training, and policy incentives. Barriers include a lack of local performance benchmarks, cost perceptions, and uncertainty regarding compliance pathways. By incorporating institutional variables such as regulatory clarity and policy maturity, the study advances a theoretical understanding of construction technology diffusion in the global south. The study offers a robust, context-specific model that can be adapted in similar economies seeking to balance innovation with regulatory oversight. Full article

This study presents a multi-factor coupled assessment of seismic disaster risk for approximately 635,000 individual building units in Ankang City, Shaanxi Province, China, utilizing a high-resolution dataset. The assessment methodology innovatively integrates the three core components of risk: seismic vulnerability V of load-bearing structures, site-specific seismic hazards R, and potential consequences C of damage, to formulate the Seismic Resilience Index I_SR = C·R·V. Crucially, the approach advances established risk assessment frameworks by enhancing the spatial resolution of the site influence coefficient R using a high-resolution national site classification map and detailed local geological data. The results reveal that the areas with the lowest I_SR values (indicating the lowest resilience and thus the highest risk) are predominantly concentrated in older residential districts of counties such as Ningshan, Hanyin, and Ziyang, where unreinforced masonry structures built prior to 1989 are widespread. The model assessment results align with expected structural performance characteristics, and the study concludes by offering quantified, priority-based recommendations for targeted structural intervention and seismic retrofitting in the identified highest-risk regions and building typologies. Full article

As digital and intelligent technologies become increasingly intertwined. Digital and Intelligent Transformation (DIT) emerges as a key catalyst for advancing high-quality economic and social development. Against this backdrop, as the core entities in green and low-carbon transition, corporate green innovation (GI) capabilities have garnered increasing attention. To evaluate the effects of DIT on corporate GI, the study employs the establishment of the “National New Generation Artificial Intelligence Innovation and Development Pilot Zones” (NAIPZ) as a quasi-natural experimental. This paper analyzes the impact and transmission channels of DIT on GI, using panel data from Chinese A-share listed companies (2011–2022). Employing a multi-period DID approach, the results indicate that the policy promotes GI. Additionally, the findings are supported by extensive robustness checks. Heterogeneity analysis reveals that the policy impact is moderated by firm size, and industry characteristics. Mechanism analysis reveals that urban DIT promotes corporate GI by enhancing government governance capacity, accelerating corporate digital transformation, and optimizing human capital structures. Based on these findings, we recommend tailored policy frameworks, strengthened innovation infrastructure, increased R&D support, and effective performance-tracking mechanisms. These measures can help maximize the potential of artificial-intelligence technology in advancing corporate GI. Full article