Search Results (106)

As vital material carriers of human civilization, earthen sites are experiencing continuous surface deterioration under the combined effects of weathering and anthropogenic damage. Traditional surface conservation techniques, due to their poor compatibility and limited reversibility, struggle to address the compound challenges of micro-scale degradation and macro-scale deformation. With the deep integration of digital twin technology, spatial information technologies, intelligent systems, and sustainable concepts, earthen site surface conservation technologies are transitioning from single-point applications to multidimensional integration. However, challenges remain in terms of the insufficient systematization of technology integration and the absence of a comprehensive interdisciplinary theoretical framework. Based on the dual-core databases of Web of Science and Scopus, this study systematically reviews the technological evolution of surface conservation for earthen sites between 2000 and 2025. CiteSpace 6.2 R4 and VOSviewer 1.6 were used for bibliometric visualization analysis, which was innovatively combined with manual close reading of the key literature and GPT-assisted semantic mining (error rate < 5%) to efficiently identify core research themes and infer deeper trends. The results reveal the following: (1) technological evolution follows a three-stage trajectory—from early point-based monitoring technologies, such as remote sensing (RS) and the Global Positioning System (GPS), to spatial modeling technologies, such as light detection and ranging (LiDAR) and geographic information systems (GIS), and, finally, to today’s integrated intelligent monitoring systems based on multi-source fusion; (2) the key surface technology system comprises GIS-based spatial data management, high-precision modeling via LiDAR, 3D reconstruction using oblique photogrammetry, and building information modeling (BIM) for structural protection, while cutting-edge areas focus on digital twin (DT) and the Internet of Things (IoT) for intelligent monitoring, augmented reality (AR) for immersive visualization, and blockchain technologies for digital authentication; (3) future research is expected to integrate big data and cloud computing to enable multidimensional prediction of surface deterioration, while virtual reality (VR) will overcome spatial–temporal limitations and push conservation paradigms toward automation, intelligence, and sustainability. This study, grounded in the technological evolution of surface protection for earthen sites, constructs a triadic framework of “intelligent monitoring–technological integration–collaborative application,” revealing the integration needs between DT and VR for surface technologies. It provides methodological support for addressing current technical bottlenecks and lays the foundation for dynamic surface protection, solution optimization, and interdisciplinary collaboration. Full article

University campuses face significant challenges in balancing energy efficiency, renewable energy adoption, and sustainable transportation while meeting budgetary constraints and sustainability goals. While existing optimization approaches typically address these as separate problems, this study presents an innovative multi-objective optimization framework that integrates building efficiency, renewable energy, electric vehicle charging, and sustainability scoring criteria into a unified model. The approach formulates a mixed-integer non-linear programming model with three competing objectives: minimizing primary energy consumption, minimizing investment cost, and maximizing sustainability metrics, addressing the critical need for comprehensive campus energy management tools. The optimization model was applied to the R&D Park Building of Erciyes University, utilizing actual building parameters, time-variable electricity pricing, and commercially available renewable energy technologies. Our analysis of the Pareto-optimal solutions reveals distinct trade-offs between the objectives, with primary energy consumption ranging from 1,317,860 to 4,642,770 GJ/year, investment costs between $25,735 and $485,674, and sustainability scores between 366 and 1034. Most significant for practical implementation is the balanced performance solution ($127,064), which achieves minimum energy consumption (1,367,010 GJ/year) while securing a substantial sustainability score of 538 points. The results demonstrate that while inherent trade-offs exist between competing objectives, significant sustainability improvements are achievable at intermediate investment levels, making meaningful environmental progress accessible to a broad spectrum of higher education institutions. This comprehensive optimization framework provides campus administrators with a practical decision-support tool for aligning energy systems with institutional priorities, budgetary constraints, and sustainability commitments. Full article

The European Union (EU) is advancing a digital twin of its electricity grid as a flagship initiative to accelerate the dual transitions of decarbonization and digitalization. By creating a real-time virtual replica of the EU-27 power network, policymakers and industry stakeholders aim to enhance grid efficiency, resilience, and renewable energy integration. This review provides a comprehensive analysis of the three critical dimensions shaping the digital twin’s development: (1) regulatory barriers, including fragmented policies, inconsistent data governance frameworks, and the need for harmonized standards and incentives across member states; (2) technological challenges, such as achieving interoperability, integrating real-time data, developing robust cybersecurity measures, and ensuring scalable infrastructure; and (3) economic opportunities, centered on potential cost savings, optimized asset management, new flexibility services, and pathways for innovation and investment. Drawing on European Commission policy documents, regulatory reports, academic studies, and industry projects like the Horizon Europe TwinEU initiative, this review highlights that significant groundwork has been laid to prototype and federate local grid twins into a cohesive continental system. However, achieving the full potential of a pan-European digital twin will require additional regulatory harmonization, more mature data-sharing protocols, and sustained financial commitment. This review concludes with an outlook on the strategic convergence of policy reforms, collaborative R&D, and targeted funding, emphasizing how institutional momentum, federated architectures, and cross-sector integration are advancing a secure, resilient, and economically viable digital twin that is envisioned as a foundational layer in the operational and planning infrastructure of Europe’s future electricity system. Full article

The application of intelligent robots will change the service model of hotels. However, users’ willingness to use robots in hotels is not so strong. The research aims to identify the factors influencing potential consumers’ intention to use hotel robots. Based on the technology acceptance model and social presence theory, this study constructs a hotel robot acceptance model (HRAM), and this model includes seven variables: social presence, perceived playfulness, trust, perceived ease of use, perceived usefulness, attitude, and willingness to use hotel robots. The research involved a combination of quantitative (N = 261) and qualitative (N = 20) methods used to collect data on potential hotel customers in China, and structural equation modeling was applied for verification. The research results showed that social presence positively influences perceived playfulness, attitude, and trust, with an indirect influence on users’ behavioral intention to use hospitality robots. Perceived ease of use has a positive impact on perceived usefulness; it also positively affects users’ attitudes. Perceived playfulness, perceived usefulness, attitude, and trust positively influence consumers’ behavioral intention to use hospitality robots. This research reveals the influence of social presence, perceived playfulness, trust, perceived ease of use, perceived usefulness, and attitude on users’ willingness to use hotel robots. This research expands the technology acceptance model and its application fields so that the model can serve as a theoretical framework for studies on hotel user behaviors. The findings can provide reference and guidance for the design of hospitality robots, the innovation of hospitality service models, and the decision-making of hospitality managers. The R&D of new hotel robots can lead to higher user acceptance and expand the model applications, thus advancing the sustainable development of hotel tourism. Full article

As the climate crisis intensifies, corporate operations face unprecedented challenges from increasing climate risks, necessitating rigorous investigation into their resultant economic ramifications. This study employs text analysis and machine learning methods to construct climate risk perception indicators for a sample of China’s A-share listed energy sector firms (2014–2023). A two-way fixed effects panel model is then applied to study the impact of climate risk perception on corporate performance in the energy industry. The empirical results demonstrate that in China’s energy sector, a 1% rise in climate risk perception corresponds to a 0.104% decline in ROE, mediated through diminished financial flexibility (β = −0.075 **) and elevated R&D intensity (β = 0.649 ***). Moderating effect testing indicates that firms with higher levels of administrative spending effectively buffer against the adverse effects of heightened climate risk perception. Furthermore, this study shows that climate risk perception has more pronounced negative effects on corporate performance in state-owned enterprises (β = −0.113 **), heavily polluting enterprises (β = −0.131 *), carbon-intensive industries, and non-carbon trading pilot regions (β = −0.119 ***). These findings empirically demonstrate how climate risk perception reshapes corporate resource allocation and management, ultimately affecting performance. This study also proposes policy recommendations to enhance corporate climate risk responsiveness, promote technological innovation, accelerate the energy sector’s green transition, optimize corporate capital structure, and advance sustainable development goals. Full article

Agriculture and silviculture offer interesting opportunities for food, energy, and construction sectors, but to transform such raw materials into valuable products, multiple engineering works must be carried out within R&D, innovation projects, and programs. The classical official decision to promote or supervise such projects involves many agents and criteria but rarely considers engineering quality, reusability, or other valuable and measurable attributes considered in ISO 25.000 or in value engineering guidelines. Missing them would increase technological, business, and programmatic risks, potentially wasting public money or credibility. Large projects are not free from these risks, and it is not a kind of madness to derive R&D and innovation funds to enable access to such valuable knowledge comprehensively, with models. In this context, communications and services, construction, and renewables play a crucial role in smart rural environments. Model-Based Systems Engineering (MBSE) and generative Artificial Intelligence (AI), combined with Natural Language Processing (NLP), are expected to help Knowledge Management (KM) in engineering and governance to supervise value engineering and their relationship with other metrics. Starting with a motivational and multidisciplinary framework for a smart rural transformation for System of Systems (SoS), the authors conduct specific bibliographic research on MBSE-NLP-AI use for automatizing systems engineering supervision at program governance levels. Full article

Family businesses are a significant part of the global economy, yet defining them and understanding their features remains a topic of debate. Despite the suggestion that family ownership may lead to conservative innovation strategies, recent research indicates that family businesses can embrace strategic risk in innovation. Governance of innovation in family firms is a growing area of interest, with corporate governance influencing R&D and innovation decisions. The role of CEOs in family businesses is critical for innovation strategies, with family CEOs often prioritizing long-term interests. However, research on innovation in Turkish family businesses is lacking, offering an open area for exploration. This article investigates the influence of CEO type (family vs. non-family) on product innovation, innovation management processes, strategic decision-making, risk-taking behaviors, technology adoption, and emotional attachment within Turkish family businesses. A survey methodology was employed, reaching out to Turkish family businesses with a CEO involved in product innovation. The study found that, while family CEOs exhibit a stronger emotional attachment compared to non-family CEOs, there was no significant difference in the perceived influence of CEOs on product innovation. Non-family CEOs were not significantly more likely to implement formal innovation management processes or prioritize long-term strategic goals over short-term profits. Similarly, there was no significant evidence supporting the notion that non-family CEOs are more likely to engage in risk-taking behaviors compared to family CEOs. The study suggests a need for further research using a larger sample and diverse methodologies to deepen understanding of family business dynamics, particularly in the context of innovation. Full article

The high-quality and sustainable development of the digital economy cannot be achieved without the support of the policy system. The purpose of this article is to scientifically analyze the laws and characteristics of the policy system that supports the sustainability of the digital economy. Specifically, based on public policy theory, this article constructs an analytical framework of “policy objectives—policy tools—organizational management” and incorporates the “central-local” relationship with Chinese characteristics into the framework. Meanwhile, text analysis was used to quantitatively analyze 971 digital economy policies issued by the central and local governments in China from 2000 to 2022. Research shows that the central government of China has taken the lead in introducing digital economy policies, and local governments are able to respond quickly. The central government’s digital economy policy goals fluctuate and change, while local governments pay more stable attention to the digital product service industry. Both central and local governments widely use supply oriented policy tools and environmental-oriented policy tools, while demand-oriented policy tools are not widely applied. The vertical relationship between central and local data management agencies is still unclear, and the degree of cross departmental and cross regional cooperation is not high. Meanwhile, empirical analysis based on the two-way fixed effects model shows that technological innovation, R&D funding, and industrial structure have a significant impact on changes in digital economy policies. This article summarizes the characteristics of the evolution of digital economy policies in the Chinese context, providing policy design references for promoting the sustainability of the digital economy and methodological insights for policy research in other fields. Full article

The transition to electric vehicles is a critical step toward achieving carbon neutrality and environmental sustainability. This shift relies on advancements across multiple technological domains, driving the need for strategic technology intelligence to anticipate emerging technology convergence opportunities. To address this challenge, this study aimed at providing an analytical framework for identifying technology convergence opportunities using node2vec graph embedding. A dual-level prediction framework that combines similarity-based scoring and machine learning-based classification was proposed to systematically identify new potential technology linkages between previously unrelated technology areas. The patent co-classification network was used to generate graph embeddings, which were then processed to calculate edge similarity among unconnected nodes and to train the classifier model. A case study in the EV market demonstrated the framework can reliably predict future patterns across disparate technology domains. Consequently, advancements in battery protection, thermal management, and composite materials emerged as relevant for future technology development. These insights not only deepen our understanding of future innovation trends but also provide actionable guidance for optimizing R&D investments and shaping policy strategies in the evolving electric vehicle market. The findings contribute to a systematic approach to forecasting technology convergence, supporting innovation-driven growth in the evolving EV sector. Full article

This article explores the sustainable management of construction and demolition waste (CDW) as part of a circular economy in Europe. It provides an overview of current European practices, identifies the main challenges associated with collecting, sorting and recycling waste, and highlights the need to design buildings and construction that encourage the reuse of materials. The study also draws on best practice from internationally recognised examples such as Japan, Singapore, California, the Netherlands and China, which highlights the effectiveness of a combination of strict regulations, economic incentives and advanced recycling technologies. These international cases provide valuable lessons that can be adapted to the European context to improve the situation and fill gaps in policy, innovation and education. This article recommends targeted measures to strengthen circular practices, such as harmonising European standards, promoting eco-design principles in public procurement, investing in research and development (R&D) and establishing green administrative practices. By adopting these strategies, Europe can significantly improve the management of CDW, fostering a more resilient, sustainable and integrated circular economy. Full article

As the world accelerates efforts to combat climate change and transition toward a green, low-carbon economy, the new energy vehicle (NEV) industry has become a key driver of carbon reduction. Its ability to innovate efficiently is critical to long-term sustainable development. This study builds on the innovation value chain theory and introduces an evaluation framework that accounts for undesirable outputs such as energy consumption and pollutant emissions. Using a super-efficiency network SBM–Malmquist model and Tobit regression, we analyze the technological innovation efficiency of 272 A-share listed NEV enterprises in China from 2016 to 2023. Expanding beyond traditional overall assessments, we examine efficiency at different stages of the industry chain and find that: (a) overall technological innovation efficiency has declined, mainly due to weak pure technical efficiency, underscoring the need for better R&D management and resource allocation; (b) efficiency varies across the industry chain, with midstream firms performing better than those upstream and downstream, reflecting differences in technological accumulation and market conditions; (c) R&D tax deductions and market competition significantly boost innovation efficiency by creating pressure-driven incentives, while mismatched labor skills, the “welfare dependence” effect of tax incentives and financing constraints hinder progress. By introducing a two-stage innovation efficiency evaluation framework, this study not only pinpoints where efficiency losses occur along the industry chain but also provides empirical insights to guide targeted policy decisions, offering valuable implications for the sustainable growth of the global NEV industry. Full article

The global building and construction industry faces increasing challenges related to efficiency, performance, and sustainability, which significantly impact project success, particularly in developing economies. The timely and successful completion of building and construction projects is crucial for economic development; however, various barriers hinder effective project execution. This study identifies and empirically analyzes the critical barriers affecting building and construction project performance in two developing countries with distinct economic profiles, Ghana and the Kingdom of Saudi Arabia (KSA). A comprehensive literature review and expert interviews identified fourteen key barriers to project performance, ensuring clarity and technical relevance. Using an empirical questionnaire survey targeting experienced professionals, including contractors, clients, and consultants, the study employed the Relative Importance Index (RII) and Spearman’s correlation analysis to rank and examine the interrelationships between these barriers. The findings reveal that poor communication (RII = 0.831, ranked 1st), project cost and schedule constraints (RII = 0.806, ranked 2nd), and inadequate monitoring and evaluation (RII = 0.786, ranked 3rd) are the most significant barriers to project success in both contexts. These challenges align with global sustainability concerns, particularly Sustainable Development Goal (SDG) 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities), which emphasize resilient infrastructure and sustainable urban development. The study highlights the crucial role of decision makers, regulatory frameworks, and financial planning in overcoming these barriers and enhancing project outcomes. By addressing these constraints, the study provides actionable insights for policymakers, project managers, and industry stakeholders to improve project execution efficiency and foster sustainable building and construction practices. Future research should explore adaptive mitigation strategies and technological innovations that enhance project delivery efficiency in developing economies. Full article

Technological innovation risk in major railway projects is high, and the risk factors in the innovation process are complex and variable. In order to successfully complete the goal of technological innovation in major railway projects. This paper identifies the risk factors of technological innovation in major railway projects, establishes a system dynamics model of technological innovation risk evolution, and carries out simulation analysis by taking the C railway project as an example, to understand the risk evolution process, clarify the key tasks of risk prevention, and finally draw the following research conclusions: (1) Technological innovation risk is categorized into innovation management risk, technology R&D risk, and technology application risk, of which innovation management risk has a greater impact on technological innovation risk. (2) During the construction process, the risk of technological innovation shows a general trend of increasing and then stabilizing, with the technology R&D stage being the centralized emergence stage of technological innovation risk. (3) Changes in the values of risk factors will have different degrees of impact on technological innovation risk, with changes in planning and implementation having the greatest impact on the technological innovation risk system, followed by the feasibility of results, and changes in the value of technological difficulties risk having a lesser impact on the system. The results of this study can provide lessons and references for the prevention of technological innovation risks in major railway projects. Full article

This study examines the potential constraints that firms may face when occupying central positions within supply chain networks, particularly in terms of innovation. While prior research highlights the benefits of centrality for resource acquisition and knowledge flow, our findings suggest that such positioning can, under certain conditions, hinder innovation. Using unbalanced panel data from Chinese A-share listed firms in Shanghai and Shenzhen (2009–2021), we conduct an empirical investigation into this effect, incorporating the mediating role of R&D investment and the moderating influence of ownership structure. The analysis reveals that supply chain network centrality has a significantly negative impact on total innovation output, invention patents, and low-end patents, with all effects statistically significant at the 0.001 level. This adverse impact is particularly pronounced in state-owned enterprises, where dependence on established networks further restrains innovation. These results suggest that supply chain centrality may hinder firms’ long-term innovation capacity, which could, in turn, weaken their sustainability by limiting their ability to adapt to technological change and evolving industrial environments. These findings suggest that policymakers could implement targeted incentives, such as R&D subsidies, to mitigate the innovation constraints faced by central firms. Meanwhile, corporate managers should adopt strategies like open innovation and supply chain diversification to sustain long-term innovation. Full article

Metropolitan areas increasingly confront complex challenges related to food security, social inequality, environmental degradation, and resource scarcity, exacerbated by rapid urbanization, climate change, and the reliance on extended, fragile supply chains. Urban and peri-urban agriculture (UPA) is recognized as a promising approach to mitigate these issues. For example, it enhances food security and nutrition by strengthening local food supply systems, improves livelihoods by providing employment and income for local residents, and promotes environmental sustainability through the creation of greening spaces and reduction of food miles. However, the full potential of UPA remains constrained by various technological, economic, and social barriers, such as limited growing spaces, lack of land tenure security, low economic efficiency, and insufficient public awareness and acceptance. Given that the technological innovations are critical in overcoming these barriers and maximizing the positive impacts of UPA, this review provides a state-of-the-art overview of advanced technologies and tools applicable to UPA, aiming to inform how these innovations can be better enabled to enhance UPA’s contributions to sustainable urban food systems. The review begins by defining UPA, categorizing its various forms, and exploring its multifunctional roles within urban contexts. It then presents a thorough analysis of a range of UPA technologies that serve specific purposes, including productivity and product quality improvement, space utilization optimization, resource recycling, and land use management. Furthermore, the review evaluates the current challenges faced by these technologies throughout the stages of research and development (R&D), dissemination and extension, and application and commercialization, employing an analytical framework adapted from Technology Life Cycle theories. In conclusion, the review emphasizes the crucial roles that UPA and relevant technological innovations play in transforming food systems and urban environments. It proposes four key recommendations: (1) enhancing funding mechanisms and fostering interdisciplinary collaboration for UPA R&D, (2) strengthening UPA technology dissemination systems, (3) promoting economic feasibility and market integration within UPA business models, and (4) establishing supportive environments among all stakeholders in the innovation process. These targeted strategies are essential for scaling UPA technologies, thereby strengthening food security, environmental sustainability, and socio-economic resilience in metropolitan areas. Full article