Search Results (1,268)

Natural resource assets inherently integrate tripartite synthesis of legal, economic, and ecological attributes. They serve dual critical functions as foundational elements supporting the evolution of new-quality productive forces and pivotal mechanisms safeguarding ecosystemic integrity. It has become a global consensus and direction of action to advance comprehensive supervision of natural resource assets and practice the concept of “Community of Life for Human and Nature”. Under the background of the super-ministry system restructuring in China, comprehensive supervision of natural resource assets remains challenged by system fragmentation in supervision objectives and multifaceted interest conflicts among stakeholders. In light of this, this research focuses on the theoretical justification and system optimization of the comprehensive supervision of natural resource assets in China. Using comparative analysis and normative analysis methods, we validate the system’s function on the comprehensive supervision of natural resource assets, summarize foreign experiences, and ultimately aim to explore the optimization pathway of the legal system for the comprehensive supervision of natural resource assets. The results show the following: (1) The choice of the legal system for the comprehensive supervision of natural resource assets emerges as the functional product aligning societal objectives, the rational paradigm for achieving efficient resource allocation, and the adaptive response to the external effects of common property. (2) The system supply of comprehensive supervision of natural resource assets in foreign countries is characterized by normative convergence in conceptual elements and typological categorization in objectives and objects. Therefore, this research recommends that, in order to optimize the system of the comprehensive supervision of natural resource assets in China, (1) in terms of protection of source, natural resource assets should be categorized, with operational natural resource assets focusing on management and public welfare natural resource assets focusing on conservation. (2) In terms of valuation, the economic valuation of natural resource assets should be integrated with ecosystem service assessments to enhance fair market equity. (3) In terms of method, the big data center should be established to enable the synergistic integration of technological innovation and system reforms. (4) In terms of subject, requiring the participation of various government departments, non-governmental organizations, the general public, and other parties could realize the connection of different legal bases for the comprehensive supervision of natural resource assets and the balance of multiple rights and interests, which should help to achieve balanced resource efficiency and biodiversity conservation and safeguard national ecological security. Full article

With the rapid development of technology, an increasingly competitive environment, and evolving consumer behaviour, the use of modern marketing tools has become a key challenge for companies of various types (manufacturing, providing services, sports organizations, universities, etc.). Although sustainable digital communication methods are gaining prominence, existing research often focuses merely on describing communication trends without providing decision-making frameworks for strategy optimisation. This paper addresses this gap by mapping the current state of marketing communication strategies among large telecommunication companies in Slovakia and assessing their impact on customer behaviour and market position. Data were analysed through a combination of qualitative and quantitative research methods, including document analysis, annual reports, surveys, and personal observations. One enterprise was selected for detailed data analysis. The results confirm a significant relationship between the use of communication channels and the company’s market position, brand popularity, and the strong influence of employee recommendations. Unlike previous studies, which predominantly describe marketing communication trends and tools, this research integrates the evaluation of communication strategy effectiveness with a systematic management decision-making model based on the PDCA (Plan-Do-Check-Act) continuous improvement cycle. This approach enables continuous optimisation of sustainable communication strategies and provides actionable managerial guidance for improving resource allocation, market position, and organisational adaptability in dynamic market environments. Full article

This study examines the impact of environmental, social, and governance (ESG) practices on green innovation and financial performance among 174 publicly listed firms across ASEAN countries over the period from 2019 to 2023. Utilizing an unbalanced panel dataset of firms from key ASEAN economies, the analysis employs panel regression techniques. Green innovation performance is measured through innovation disclosures related to environmental technologies, while financial success is assessed via return on assets (ROA) and Tobin’s Q. The findings reveal that environmental and governance disclosure scores positively influence green innovation, whereas social scores exert a more immediate impact on financial performance. Moreover, green innovation is found to partially mediate the relationship between overall ESG practices and long-term market valuation. These results highlight the strategic role of ESG transparency in enhancing innovation-driven competitiveness, responsible business conduct, and sustainable employment across Southeast Asian markets. Implications are discussed for corporate managers, policymakers, and socially responsible investors. The study reinforces the case for ESG-aligned strategy as a pathway to both innovation, inclusive economic growth, and long-term competitiveness in ASEAN markets. Full article

The captive breeding of marine ornamental fish with specialized larval requirements—such as Chaetodontoplus mesoleucus—remains a major bottleneck in aquaculture, largely due to the lack of techniques tailored to their unique morphological and nutritional needs. The global marine ornamental aquaculture market is valued at approximately USD 2.15 billion annually; however, only around 10% of marine ornamental species are currently supplied through captive breeding, highlighting a substantial technological gap. The artificial propagation of C. mesoleucus is particularly challenging due to the species’ small mouth gape and high nutritional demands during early development. To address this issue, we evaluated the effects of three live-prey types—Euplotes sp., Brachionus sp., and Bestiolina coreana—as well as a mixed diet containing all three, on larval performance. From 3 days post-hatch, larvae were fed each prey type at equal densities (15–20 individuals/mL), and water quality was carefully maintained to minimize external influences. Survival and total length were assessed at 14 dph. At the end of the trial, the mixed-diet group showed the highest survival rate (36.2 ± 5.6%), whereas larvae fed only B. coreana exhibited the greatest total length (7.4 ± 1.2 mm) and a high metamorphosis rate (97.8%). These findings demonstrate that prey selection significantly influences the early survival and growth in C. mesoleucus larvae and highlight the critical role of copepods in promoting growth performance. However, as larval biomass was not quantified, the findings should be interpreted with caution, and future studies incorporating biomass assessments are needed to draw more conclusive inferences. The successful mass rearing of this species supports the feasibility of captive production to reduce wild harvesting, protect coral-reef biodiversity, and promote sustainable ornamental aquaculture. Full article

Background/Objectives: Self-adhesive flowable resins (SAFR) entered the market, eliminating the adhesive system application due to their self-adhesive technology. Guided by the PICO framework (Population, Intervention, Comparison, Outcome), the aim was to conduct a systematic review of clinical studies to compare the clinical performance of Self Adhesive Flowable Resin (SAFRs) with conventional flowable resins used for direct restorations. Methods: The protocol of this systematic review was registered in the International Prospective Register of Systematic Reviews (CRD42023394297) and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline. Five databases (PubMed, Embase, Web of Science, Scopus, and Cochrane Library) were searched from inception to July 2025. Nine randomized clinical trials were included, totaling 493 restorations in 232 patients. Clinical performance was assessed using USPHS or FDI criteria, with follow-up periods ranging from 6 months to 5 years. Data were pooled using a random-effects meta-analysis to calculate risk differences (RD) and 95% confidence intervals (CI) for marginal adaptation, retention, marginal staining, post-operative sensitivity, color stability, surface roughness, secondary caries, and anatomical form. Results: Meta-analysis showed no significant differences between SAFRs and CFRCs for in terms of: marginal adaptation (RD = 0.01; 95% CI: −0.02 to 0.04; p = 0.53; I² = 0%), retention (RD = 0.00; 95% CI: −0.02 to 0.03; p = 0.81; I² = 0%), marginal staining (RD = 0.01; 95% CI: −0.01 to 0.02; p = 0.51; I² = 0%), and post-operative sensitivity (RD = −0.01; 95% CI: −0.03 to 0.02; p = 0.62; I² = 0%). The certainty of the evidence for all outcomes was rated as moderate to high according to the GRADE assessment. Conclusions: SAFR restorations demonstrated comparable clinical performance to conventional resins; however, heterogeneity in follow-up duration and the scarcity of long-term data (>5 years) warrant caution. Full article

Amid accelerating climate change, climate-related hazards—such as floods, wildfires, hurricanes, and sea-level rise—increasingly drive land transformations and pose growing risks to housing markets by affecting property valuations, insurance availability, mortgage performance, and broader financial stability. This review synthesizes recent progress in two distinct domains and their linkage: (1) assessing climate-related financial risks in housing markets, and (2) applying AI-driven remote sensing for hazard detection and land transformation monitoring. While both areas have advanced significantly, important limitations remain. Existing housing finance studies often rely on static models and coarse spatial data, lacking integration with real-time environmental information, thereby reducing their predictive power and policy relevance. In parallel, remote sensing studies using AI primarily focus on detecting physical hazards and land surface changes, yet rarely connect these spatial transformations to financial outcomes. To address these gaps, this review proposes an integrative framework that combines AI-enhanced remote sensing technologies with financial econometric modeling to improve the accuracy, timeliness, and policy relevance of climate-related risk assessment in housing markets. By bridging environmental hazard data—including land-based indicators of exposure and damage—with financial indicators, the framework enables more granular, dynamic, and equitable assessments than conventional approaches. Nonetheless, its implementation faces technical and institutional barriers, including spatial and temporal mismatches between datasets, fragmented regulatory and behavioral inputs, and the limitations of current single-task AI models, which often lack transparency. Overcoming these challenges will require innovation in AI modeling, improved data-sharing infrastructures, and stronger cross-disciplinary collaboration. Full article

In the present era where digitalization, FinTech, and blockchain technologies are reshaping the global financial landscape, traditional measures of bank performance need to evolve. This paper introduces a hybrid approach that combines multi-criteria efficiency assessment and econometric modeling to evaluate bank performance within the context of digital transformation in emerging economies. Focusing on a panel of banks across selected emerging markets, this study first applies a multi-criteria decision-making technique (Data Envelopment Analysis) to assess operational efficiency using both conventional indicators and digitalization-driven metrics, such as mobile banking penetration and blockchain adoption. We then employ a panel econometric model to investigate the factors that shape efficiency outcomes, with special attention to FinTech and blockchain innovations as potential drivers. The results reveal a nuanced picture of how digital technologies can influence bank performance, highlighting both opportunities and constraints for financial institutions in less developed markets. The findings offer actionable insights for bank managers, regulators, and policymakers striving to balance traditional operational priorities with the demands of digital transformation. By linking efficiency measurement with an examination of the digitalization process, this paper provides a timely contribution to the literature on banking and financial innovation, serving as a foundation for future research and strategic decision-making in the FinTech and blockchain era. Full article

Across the world, people are exploring fields where AI (Artificial Intelligence) and VR (Virtual Reality) can be harnessed to unlock new possibilities and drive innovation. The aim of this article was to review the potential and assess the feasibility of using virtual reality technology in soft skills training (including people management, stress management, communication, conflict resolution, and sales). A project was developed featuring an application that utilizes virtual reality and artificial intelligence to facilitate communication with a virtual coach. The application operates on Meta Quest 3 virtual reality goggles (Meta Platforms, Inc., Menlo Park, CA, USA). Tests of the presented solution confirm market trends, highlighting the potential for achieving positive training outcomes through immersive technologies. The conclusions outline opportunities for improvement and further development of such solutions. This study applied a quasi-experimental model with pretest, posttest, and four-week follow-up measurements. The effectiveness of VR training was evaluated using a knowledge test (0–100%), a self-assessment scale of soft skills (Likert 1–5), expert behavior observation (0–10 scale), and posttraining surveys. The VR group demonstrated significantly higher gains in knowledge, soft skills, and behavioral performance with knowledge retention reaching 89% after four weeks. These results confirm the effectiveness of immersive VR training and its alignment with current market trends in innovative professional development. Full article

As vital outcomes of agricultural technological innovation, new animal breeds are not only foundational to rural revitalization but also central to preserving ecological diversity. At present, China lacks a clear and coherent legal framework of protection for new animal breeds, making it difficult to accommodate practical demands posed by modern breeding technologies such as gene editing. The results show that international models for protecting intellectual property in new animal breeds generally fall into three categories: granting patents for animal breeds, granting patents for breeding methods, and establishing sui generis rights for animal breeds. The sui generis protecting model of animal breed rights provides stronger protection and better reflects genetic specificity of such breeds. This research recommends that, on ethical review, stricter oversight of animal welfare and genetic data usage should be implemented to promote responsible innovation. On safety assessment, detailed standards should be developed for food and environmental risk assessment to ensure biodiversity and ecological sustainability. On risk balance evaluation, efforts should be made to ensure effective alignment among animal breed rights, animal welfare, and fair competition in the market, while also striking an appropriate balance of interests between breeders and other stakeholders such as farmers, who act as conservers and providers of germplasm resources. Full article

Innovation-driven labor markets play a pivotal role in economic development, yet significant disparities exist in how efficiently countries transform innovation inputs into labor market outcomes. This study addresses the critical gap in benchmarking multi-stage innovation efficiency by developing an integrated framework combining Data Envelopment Analysis (DEA) Super Slack-Based Measure (Super-SBM) for static efficiency evaluation and the Malmquist Productivity Index (MPI) for dynamic productivity decomposition, enhanced with cooperative game theory for robustness testing. Focusing on the top 20 innovative economies over a 5-year period, we analyze key inputs (Innovation Index, GDP, trade openness) and outputs (labor force, unemployment rates), revealing stark efficiency contrasts: China, Luxembourg, and the U.S. demonstrate optimal performance (mean scores > 1.9), while Singapore and the Netherlands show significant underutilization (scores < 0.4). Our results identify a critical productivity shift period (average MPI = 1.325) driven primarily by technological advancements. This study contributes a replicable, data-driven model for cross-domain efficiency assessment and provides empirical evidence for policymakers to optimize innovation-labor market conversion. The methodological framework offers scalable applications for future research in computational economics and productivity analysis. Full article

Palatability is a critical determinant of pet food performance, directly influencing voluntary intake, nutrient utilization, and therapeutic efficacy. In this systematic review, we examine peer-reviewed research publications, patent filings, and commercial product data pertaining to palatant technologies in dry and wet pet food from 2014 to 2024. Major palatant classes—including fats, proteins, yeast extracts, and novel plant-derived or insect-based hydrolysates—are evaluated for their physicochemical properties, flavor-release mechanisms, and stability during processing. We analyze formulation techniques such as microencapsulation, Maillard-reaction enhancement, and multilayer coating systems, focusing on their impact on aromatic compound retention and palatability consistency. Patent landscape assessment identifies over 15 key innovations in delivery systems, life-stage-specific palatant modulation, and dual-phase release architectures. Dual-phase release architectures are defined as systems that deliver active compounds in two sequential phases, such as immediate and sustained release. Sensory evaluation methodologies—ranging from multivariate preference mapping to descriptive analysis—are critically appraised to correlate human-panel metrics with canine and feline feeding behavior. We also discuss strategic integration of palatants at different processing stages (pre-conditioning, extrusion, and post-extrusion) and the challenges of balancing taste masking with nutritional requirements, particularly in formulations containing alternative proteins for sustainability. Despite rapid market growth in functional palatant-infused products, peer-reviewed literature remains relatively limited, suggesting opportunities for further research on species-specific flavor drivers, synbiotic flavor–nutrient interactions, and novel delivery platforms. This comprehensive overview of palatant science, patent innovations, and market evolution provides evidence-based guidance for researchers, formulators, and veterinarians seeking to optimize organoleptic properties and consumer acceptance of next-generation pet foods. Full article

Modern technologies are transforming occupational health and safety training by enhancing education, innovation, fire prevention, and promoting sustainability conditions in various sectors of industries. Digital tools such as virtual reality, artificial intelligence, and interactive simulations improve learning efficiency, engagement, and risk awareness. By integrating the technologies, companies can better prepare employees for hazardous situations, reduce workplace accidents, and ensure compliance with safety regulations. Fire courses on fire prevention and control are an essential element in health and safety trainings, and a crucial aspect of safety management. In any business, employees should be prepared for emergency situations, including fires by using modern tools like artificial intelligence. This article aimed to assess the implementation of modern technologies in Polish occupational health and safety training across various industrial sectors. Additionally, this research considered variations in training program development based on company size and financial capacity, highlighting the importance of integrating training, education, and innovative technologies into the company’s overall development strategy. The relationships between safety training programs, education, and innovation in 597 industrial companies were evaluated. The research findings suggest that integrating innovative technologies into training can improve working conditions in a more sustainable way and enhance the market competitiveness of enterprises. Full article

Artificial intelligence (AI) soft skills have become increasingly vital in today’s technology-driven world, as they support decision-making systems, strengthen collaboration among stakeholders, and enable individuals to adapt to rapidly changing environments—factors that are fundamental for achieving the sustainability goals of smart cities. Even though AI soft skills are becoming more important, no scale specifically designed to identify and evaluate individuals’ AI soft skills has been found in the existing literature. Therefore, this paper aimed to develop a reliable and valid scale to identify the AI soft skills of individuals. A sample of 685 individuals who were employed in AI-active sectors, with a minimum of a bachelor’s degree, and at least one year of AI-related work experience, participated in the study. A sequential exploratory mixed-methods research design was utilized. Exploratory factor analysis (EFA) identified a five-factor structure that accounted for 67.37% of the total variation, including persuasion, collaboration, adaptability, emotional intelligence, and creativity. Factor loadings ranged from 0.621 to 0.893, and communalities ranged from 0.587 to 0.875. Confirmatory factor analysis (CFA) supported this structure, with strong model fit indices (GFI = 0.940, AGFI = 0.947, NFI = 0.949, PNFI = 0.833, PGFI = 0.823, TLI = 0.972, IFI = 0.975, CFI = 0.975, RMSEA = 0.052, SRMR = 0.035). Internal consistency for each factor was high, with Cronbach’s alpha values of dimensions ranging from 0.804 to 0.875, with a value of 0.921 for the overall scale. Convergent and discriminant validity analyses further confirmed the construct’s robustness. The finalized AI soft skills (AISS) scale, consisting of 24 items, offers a psychometrically valid and reliable tool for assessing essential AI soft skills in professional contexts. Ultimately, this developed scale enables the determination of the social and cognitive skills needed in the human-centered and participatory governance structures of smart cities, supporting the achievement of specific Sustainable Development Goals such as SDG 4, SDG 8, and SDG 11, and contributes to the design of policies and training programs to eliminate the deficiencies of individuals in these areas. Thus, it becomes possible to create qualified human resources that support sustainable development in smart cities, and for these individuals to take an active part in the labor market. Full article

Microalgae-based carbon sequestration is promising for implementing carbon neutrality and reducing greenhouse gas emissions. However, as the technology remains in its early developmental stages, it presents a range of risks that may deter potential investors. To address these risks, this study proposes a group-based decision-making framework for the risk evaluation of microalgae carbon sequestration projects. Fifteen risk indicators are identified and categorized into four groups, including economic, technical, market, and environmental. To handle uncertainty and vagueness in the assessment, the framework uses trapezoidal fuzzy numbers and hesitant fuzzy linguistic sets to evaluate benchmark values. An expert credibility model is developed to assign weights to expert opinions by combining the subjective RANCOM method and the objective centroid method, both adapted for a fuzzy linguistic environment. A generalized aggregation operator is then used to combine expert evaluations. This operator integrates weighted and ordered averaging techniques and converts probabilistic linguistic terms into trapezoidal fuzzy numbers. The final risk level is determined using a fuzzy comprehensive evaluation method. The results indicate a medium-high level of risk, with a similarity score of 0.960. This suggests that while microalgae carbon sequestration holds great promise, effective planning and risk management are essential. For project managers and investors, this proposed framework helps quantify risk. It provides practical guidance for improving decision-making and strengthening project management. Full article

The increasing integration of autonomous driving technologies into heavy-duty road transport requires a clear understanding of how these systems affect professional drivers’ working time, vehicle utilization, and regulatory compliance. This study develops a model-based comparative analysis to assess the cooperation between human drivers and autonomous trucks at SAE Levels 3 and 4. Using EU Regulation (EC) No 561/2006 as a legal framework, single-driver, double-driver, and ego vehicle scenarios were simulated to evaluate changes in working time classification and vehicle movement. The results indicate that Level 3 automation enables up to 13.25 h of daily vehicle movement while complying with working time regulations, compared with the 10-h limit for conventional operation. Level 4 automation further extends the effective movement time to 14.25 h in double-crew configurations, offering opportunities for increased efficiency without violating labor codes. The novelty of this work lies in the quantitative modeling of human–machine collaboration in professional transport under real regulatory constraints. These findings provide a foundation for regulatory updates, tachograph adaptation to AI-driven vehicles, and the design of hybrid driver roles. Future research will focus on validating these models in real-world transport operations and assessing the implications of Level 5 autonomy for logistics networks and labor markets. Full article