Search Results (38)

The building sector holds a significant position in the global energy consumption share, and its environmental impact continues to intensify, making the construction industry a key player in sustainable development. The application of life cycle assessment on buildings (LCA-B) is widely employed to evaluate building energy and environment performance, and thus is of great significance for ensuring the sustainability of the project. This work aims to provide a systematic overview of LCA-B development based on reviewed literature. A three-stage mixed research method is adopted in this study: Firstly, an overall analysis framework is constructed, and 327 papers related to building life cycle assessment published between 2009 and 2025 are screened out by using the bibliometric method; Then, through scientometrics analysis, the journal regions, sources, scholars, and keyword evolution are revealed and analyzed using VOSviewer tool, and the hotspots in the field of LCA-B (e.g., integration of building information modeling (BIM) in LCA-B, multi-dimensional framework of environment–society–culture) are preliminarily explored based on the selected highly cited papers. The research finds that: (1) the performance of low energy buildings is better than that of net zero energy buildings from the perspective of LCA; (2) software compatibility and data exchange are the main obstacles in the integration of BIM-LCA; (3) a multi-dimensional LCA framework covering the social or cultural aspects is expected for a comprehensive assessment of building performance. This study provides a systematic analysis and elaboration of review articles related to LCA-B and thereby provides researchers with in-depth insight into this field. Full article

The Paris Agreement’s pressing global mandate to limit global warming to 1.5 degrees Celsius above pre-industrial levels by 2030 has placed immense pressure on energy-consuming industries and businesses to deploy robust, advanced, and accurate monitoring and tracking of carbon footprints. This critical issue is examined through a systematic review of English-language studies (2015–2024) retrieved from three leading databases: Scopus (n = 1528), Web of Science (n = 1152), and GreenFILE (n = 271). The selected literature collectively highlights key carbon footprint tracking methods. The resulting dataset is subjected to bibliometric and scientometric analysis after refinement through deduplication and screening, based on the PRISMA framework. Methodologically, the analysis integrated the following: (1) evaluating long-term trends via the Mann–Kendall and Hurst exponent tests; (2) exploring keywords and country-based contributions using VOSviewer (v1.6.20); (3) applying Bradford’s law of scattering and Leimkuhler’s model; and (4) investigating authorship patterns and networks through Biblioshiny (v4.3.0). Further, based on eligibility criteria, 35 papers were comprehensively reviewed to investigate the emerging carbon footprint tracking technologies such as life cycle assessment (LCA), machine learning (ML), artificial intelligence (AI), blockchain, and data analytics. This study identified three main challenges: (a) lack of industry-wide standards and approaches; (b) real-time tracking of dynamic emissions using LCA; and (c) need for robust frameworks for interoperability of these technologies. Overall, our systematic review identifies the current state and trends of technologies and tools used in carbon emissions tracking in cross-sectors such as industries, buildings, construction, and transportation and provides valuable insights for industry practitioners, researchers, and policymakers to develop uniform, integrated, scalable, and compliant carbon tracking systems and support the global shift to a low-carbon and sustainable economy. Full article

In an era of evolving scholarly ecosystems, machine learning (ML) and artificial intelligence (AI) have become pivotal in advancing research impact analysis. Despite their transformative potential, the fragmented body of literature in this domain necessitates consolidation to provide a comprehensive understanding of their applications in multidimensional impact assessment. This study bridges this gap by employing bibliometric methodologies, including co-authorship analysis, citation burst detection, and advanced topic modelling using BERTopic, to analyse a curated corpus of 1608 scholarly articles. Guided by three core research questions, this study investigates how ML and AI enhance research impact evaluation, identifies dominant methodologies, and outlines future research directions. The findings underscore the transformative potential of ML and AI to augment traditional bibliometric indicators by uncovering latent patterns in collaboration networks, institutional influence, and knowledge dissemination. In particular, the scalability and semantic depth of BERTopic in thematic extraction, combined with the visualisation capabilities of tools such as CiteSpace and VOSviewer, provide novel insights into the dynamic interplay of scholarly contributions across dimensions. Theoretically, this research extends the scientometric discourse by integrating advanced computational techniques and reconfiguring established paradigms for assessing research contributions. Practically, it provides actionable insights for researchers, institutions, and policymakers, enabling enhanced strategic decision-making and visibility of impactful research. By proposing a robust, data-driven framework, this study lays the groundwork for holistic and equitable research impact evaluation, addressing its academic, societal, and economic dimensions. Full article

This study presents a scientometric analysis of renewable energy applications in low-temperature regions, focusing on green hydrogen production, carbon storage, and emerging trends. Using bibliometric tools such as RStudio and VOSviewer, the research evaluates publication trends from 1988 to 2024, revealing an exponential growth in renewable energy studies post-2021, driven by global policies promoting carbon neutrality. Life cycle assessment (LCA) plays a crucial role in evaluating the environmental impact of energy systems, underscoring the need to integrate renewable sources for emission reduction. Hydrogen production via electrolysis has emerged as a key solution in decarbonizing hard-to-abate sectors, while carbon storage technologies, such as bioenergy with carbon capture and storage (BECCS), are gaining traction. Government policies, including carbon taxes, fossil fuel phase-out strategies, and renewable energy subsidies, significantly shape the energy transition in cold regions by incentivizing low-carbon alternatives. Multi-objective optimization techniques, leveraging artificial intelligence (AI) and machine learning, are expected to enhance decision-making processes, optimizing energy efficiency, reliability, and economic feasibility in renewable energy systems. Future research must address three critical challenges: (1) strengthening policy frameworks and financial incentives for large-scale renewable energy deployment, (2) advancing energy storage, hydrogen production, and hybrid energy systems, and (3) integrating multi-objective optimization approaches to enhance cost-effectiveness and resilience in extreme climates. It is expected that the research will contribute to the field of knowledge regarding renewable energy applications in low-temperature regions. Full article

The use of vegetable fibers (VFs) in cement-based composites has increased in recent years owing to their minimal environmental impact and notable particular properties. VFs have aroused interest within the scientific community because of their potential as a sustainable alternative for construction. This study presents a comprehensive bibliometric analysis of VFs in cement composites using data from the Scopus database and scientometric tools to explore publication trends, influential sources, and research directions. Key findings reveal a steady increase in publications, with Construction and Building Materials identified as a leading journal in the field and China and Brazil as prominent contributors in terms of publications and citations. The analysis highlights a strong focus on mechanical properties and durability, reflecting the interest of the scientific community in optimizing VF composites for construction. Furthermore, this study includes a revision of the most influential studies addressing VF classification, durability improvements, and advanced applications of VFs in building applications. Finally, future research opportunities are outlined, emphasizing Life Cycle Assessment (LCA), industry integration, CO₂ absorption, and the application of machine learning techniques to advance the development of VF composites. This work provides a comprehensive overview of the field, suggesting future guidelines and promoting collaborative research. Full article

This manuscript continues the series of research publications on Sustainable Development Goals 8 and 9 (SDGs 8 and 9). Innovations play an essential role in the global and national economies, as they contribute to the growth of economic productivity, the creation of new products, services, and jobs, and improve the quality of life. In the context of innovation, economy and artificial intelligence (AI) are the ideological and technological components of the innovation process. The authors hypothesized that the Polish system for assessing the importance of scientific economic journals is ineffective for social development and for creating an innovation-based economy. The research methods are a scientometric analysis of 795,070 scientific sources by the keywords “Economy” and “Artificial Intelligence”, a bibliometric analysis of 219,739 sources by the keywords “Economy”, “Economic productivity”, and “Innovation”, correlation analysis, and testing statistical hypotheses. The study led to the adoption of an alternative statistical hypothesis, which is a strong confirmation of the basic hypothesis. A new model for assessing the weight of scientific journals was created based on the existing system. Two management recommendations were formulated in the rules for determining the weight of journals. The high R² value indicates that the new model effectively predicts the result. The correlation coefficient of the weight of journals in the new model is more than 98%. When verifying statistical hypotheses, a high significance level of 99.0 was used. The study’s practical significance is in the movement of Polish science to a leading place in the world market of scientific products. Full article

The present study is an evaluation of published papers in the field of scientometrics–bibliometrics in veterinary or animal studies. The objective was the quantitative evaluation of the scientific content and the bibliometric details of papers that had used scientometrics as a methodological approach to assess various topics within the broad field of veterinary or animal studies. For the search of published papers, the Web of Science database was used; the search string {ALL FIELDS = [scientometric* OR bibliometric*]} AND {ALL FIELDS = [veterinary OR animal*]} was employed. In all, 163 papers were evaluated individually. There was a progressive increase in the number of papers published annually (slope 0.314 ± 0.063) which originated from 58 countries, mostly from the United States of America (n = 24) and 306 organizations. The databases employed most frequently for record search were the Web of Science, Scopus and PubMed (in 105, 60 and 21 papers, respectively); the median timespan of the searches was 25 years (interquartile range (IQR): 31) and the median number of records was 1082.5 (IQR: 4708) (min.: 14, max.: 207,894). The papers were published in 106 journals (Animals (n = 21), Scientometrics (n = 8)), classified into 56 Web of Science categories (‘veterinary sciences’ (n = 26 journals)). Searches related to 88 different topics. There were 517 unique keywords in the papers, among which ‘bibliometric(s)’ (n = 45) occurred most often. The median number of co-authors per paper was 4 (IQR: 3) (min.: 1, max.: 17), with a total of 689 individual authors. Most papers (n = 110 (67.5%)) were published under open access. The median number of citations received per paper was 4 (IQR: 9) (max.: 68) and the h-index was 21. In multivariable analysis, the higher number of cited references in papers and the inclusion of specific animal species in the record search emerged as significant for the number of citations received per paper yearly. Full article

This study examines the current trajectory and future research directions of environmental, social, and governance (ESG) integration within the banking industry. Utilizing bibliometric and scientometric approaches, it highlights trend topics, influential studies, and notable contributors. Drawing from an analysis of 681 studies from Scopus and Web of Science databases, a comprehensive dataset was curated using scientometric networks with VOSviewer and Bibliometrix tools. This study emphasizes the evolving nature of ESG integration within banking, emphasizing an interdisciplinary shift encompassing environmental, social, and governance considerations. Keyword analysis reveals emerging trends, including the influence of ESG factors on banks’ financial performance, regional variations in ESG integration within banking, and risk assessment related to ESG factors and credit risk in banks. By offering insights into the evolving topic of ESG integration within banking and identifying promising avenues for further exploration, such as the fundamental connection between ESG and sustainability, particularly in climate change and green finance, this research contributes to ongoing discussions surrounding ESG integration in the banking industry, guiding future research efforts in this vital financial sector. Full article

(1) Background: The demand for electricity in rural and urban areas has given rise to numerous related industries, resulting in perilous working conditions and a significant number of safety accidents for workers. In recent years, there has been an increasing focus on improving occupational safety and health in the electric power industry. However, the lack of a systematic review or the integration of disaggregated studies has hindered our understanding of the state of the development of this research field. This study aims to provide bibliometric and scientometric network analyses and explore the untapped potential of digital pathways. (2) Methods: A bibliometric analysis focused on the research cooperation, author keywords, and journal co-citation patterns of studies was carried out, while a temporal trend analysis was employed to identify topical focuses and trends for further research on the occupational safety and health of electrical workers. Papers were searched for across three databases, namely Web of Science, Scopus, and Google Scholar. Using “occupational safety and health” and “electric power industry” as keywords, the articles published from 1991 to 2022 were retrieved. (3) Results: A total of 608 articles published from 1991 to 2022 were collected for the bibliometric analysis. Four clusters were successfully recognized in the search results after adopting the process of cluster analysis based on a total of 608 articles. As for the countries, most of the publications and citations came from the United States. The most frequent keywords were safety, exposure assessment, electrocution, and electrical injury. (4) Conclusions: This is the first study to highlight occupational safety and health in the electric power industry and provides valuable insights into the knowledge structure, emerging trends, and future directions through the lens of digital pathways. This study sheds light on the importance of digital pathways in enhancing occupational safety and health practices within the industry. The findings contribute to the fields of occupational safety management and health promotion, providing a foundation for future research and interventions aimed at improving safety conditions and promoting the well-being of personnel in the electric power industry. Full article

This study investigates the relationship between cultural heritage and climate change, assessing the global implementation of advanced technologies in line with UNESCO’s Thematic Indicators for Cultural Sustainability. Few studies have been conducted on this topic; hence, theoretical background examines the keywords related to cultural heritage preservation, conservation, restoration, climate change mitigation, and adaptation, as well as the intersection of culture and climate change. It also analyses the definitions provided by leading global organizations and explores the use of advanced technologies in protecting cultural heritage. The research methodology is based on an analytical method consisting of a bibliometric assessment and a scientometric assessment. The bibliometric and scientometric analyses map occurrences, frequencies, and intercorrelations of these keywords with UNESCO Thematic Indicators and advanced technology utilization. The findings reveal a predominance of conservation-related Thematic Indicators, suggesting a conservative approach to cultural sustainability, particularly for environmental resilience, wealth, and livelihoods. In terms of advanced technologies, laser scanning and photogrammetry are used for both conservation and restoration purposes, while chromatography and virtual tours are mainly applied to conservation and preservation practices. Otherwise, infrared thermography, X-ray imaging, and online platforms are used, respectively, for heritage preservation, restoration, and conservation. On the other hand, ground-penetrating radar and remote sensing exhibit fewer connections to heritage protection. The mapping of culture and climate change also highlights the importance of conservation in responding to changing climate conditions. Climate adaptation is closely linked to both conservation and preservation efforts, highlighting the critical role of cultural heritage in fostering climate resilience. Full article

The objective of this study was the presentation of quantitative characteristics regarding the scientific content and bibliometric details of the relevant publications. In total, 156 papers were considered. Most papers presented original studies (n = 135), and fewer were reviews (n = 21). Most original articles (n = 101) referred to work involving cattle. Most original articles described work related to the diagnosis (n = 72) or pathogenesis (n = 62) of mastitis. Most original articles included field work (n = 75), whilst fewer included experimental (n = 31) or laboratory (n = 30) work. The tissue assessed most frequently in the studies was milk (n = 59). Milk was assessed more frequently in studies on the diagnosis (61.1% of relevant studies) or pathogenesis (30.6%) of the infection, but mammary tissue was assessed more frequently in studies on the treatment (31.0%). In total, 47 pathogens were included in the studies described; most were Gram-positive bacteria (n = 34). The three bacteria most frequently included in the studies were Staphylococcus aureus (n = 55 articles), Escherichia coli (n = 31) and Streptococcus uberis (n = 19). The proteomics technology employed more often in the respective studies was liquid chromatography-tandem mass spectrometry (LC-MS/MS), either on its own (n = 56) or in combination with other technologies (n = 40). The median year of publication of articles involving bioinformatics or LC-MS/MS and bioinformatics was the most recent: 2022. The 156 papers were published in 78 different journals, most frequently in the Journal of Proteomics (n = 16 papers) and the Journal of Dairy Science (n = 12). The median number of cited references in the papers was 48. In the papers, there were 1143 co-authors (mean: 7.3 ± 0.3 co-authors per paper, median: 7, min.–max.: 1–19) and 742 individual authors. Among them, 15 authors had published at least seven papers (max.: 10). Further, there were 218 individual authors who were the first or last authors in the papers. Most papers were submitted for open access (n = 79). The median number of citations received by the 156 papers was 12 (min.–max.: 0–339), and the median yearly number of citations was 2.0 (min.–max.: 0.0–29.5). The h-index of the papers was 33, and the m-index was 2. The increased number of cited references in papers and international collaboration in the respective study were the variables associated with most citations to published papers. This is the first ever scientometrics evaluation of proteomics studies, the results of which highlighted the characteristics of published papers on mastitis and proteomics. The use of proteomics in mastitis research has focused on the elucidation of pathogenesis and diagnosis of the infection; LC-MS/MS has been established as the most frequently used proteomics technology, although the use of bioinformatics has also emerged recently as a useful tool. Full article

This scientometric analysis delves into the current trajectory and anticipated prospects of assessing fiscal sustainability, emphasizing methodologies, trends, and pivotal literature in this critical economic realm. This study analyzed 324 studies from Scopus and Web of Science databases to generate the dataset through scientometric networks, using VOSviewer and Bibliometrix tools. Through a comprehensive review of scientific literature, this research traces the developmental trajectory of fiscal sustainability, trend topics, influential studies, and key contributors employing bibliometric and scientometric tools. The study maps the landscape of fiscal sustainability exploration, underscoring an evolving shift towards interdisciplinary methods encompassing environmental, social, and political factors. Furthermore, the keywords analysis accentuates three emergent trends, mainly (i) the relation between fiscal sustainability and economic growth, (ii) the methodologies and models for assessing fiscal sustainability, and (iii) demographic concerns and their impact on fiscal sustainability. This research provides insights into the evolving terrain of fiscal sustainability exploration and anticipates promising avenues for further studies. The examination reveals the significance of methodologies such as panel data, multicointegration analysis, probabilistic debt analysis, Markov-switching models, and wavelets analysis in assessing fiscal sustainability. By offering a comprehensive overview, this analysis aspires to direct forthcoming inquiries and contribute to the ongoing discussion surrounding the assessment of fiscal stability. Full article

In recent decades, there has been a significant proliferation of literature pertaining to the evacuation of urban underground spaces. However, few studies have focused on scientometric reviews that identify research topics, evolution patterns, and trends in this field. To bridge this gap, the present study adopted a bibliometric approach by searching the literature related to underground space evacuations in the Web of Science (WOS) core database for the period 1992–2022, from which we visualized and analyzed the issuance status of the country, author, and institution, as well as the cooperation status, using Citespace software. The findings of this paper are as follows: First, there has been a consistent upward trend in the quantity of literature within this field over time. Second, Swedish authors and institutions have made important contributions to the advancement of research in this area. Third, the current research topics are concentrated on themes such as modeling and simulation, smoke control methods, integrative research on factors affecting pedestrian evacuation behavior, pedestrian walking speed under smoke-filled conditions, and the influence of wayfinding devices on exit selection/wayfinding. Finally, to advance the safety in underground spaces, future research trends should include improving basic data, refining simulation model parameters, assessing the evacuation capabilities of special populations, examining the impact of risk perception on evacuation behavior, and conducting specific research on the different risks in underground spaces. The findings may contribute to the managerial development of more comprehensive and effective emergency plans for underground spaces, thereby enhancing the survival rates and safety of pedestrians during disasters or other emergencies. Full article

Different standard methods for the assessment of the thermal performance of the building envelope are used: analogy with coeval building, theoretical method, heat flow meter measurement, simple hot box, infrared thermography, and thermometric method. Review papers on these methods, applied in situ and in laboratory, have been published, focusing on theory, equipment, metrological performance, test conditions and data acquisition, data analysis, benefits, and limitations. However, steps forward have been done and not been deepened in previous works: in fact, the representative points method and the weighted area method have been proposed, too, whilst artificial intelligence and data-driven methods have begun to prove the reliability also in the U-value prevision using available datasets. Considering this context, this work aims at updating the literature background considering exclusively in situ methods. The work starts from bibliometric and scientometric analysis not previously conducted: this helped to group the methods and to sketch the innovations and the future perspectives. Indeed, from the bibliometric and scientometric literature analysis what emerged was (i) the richness of the background on this topic, especially in the recent years, (ii) two macro-groups (methods with and without measurements), and (iii) the importance of paper keywords (otherwise, interesting papers are eluded by the output of simple database queries). The method study that followed aims at providing (i) a broader view of the thermal transmittance (U-value) assessment procedures, including the utmost recent applications, proposal, and outlooks in this field, (ii) the understanding on the fundamental theories of the techniques, (iii) practical advice for building-envelope assessment, focusing on the advantages and limitations useful for professionals and researchers involved in the energy audit, conservation, or refurbishment of building stock, (iv) the identification of the interconnection between the techniques that often rely on one another, and (v) final remarks and future perspective of the procedures, which embrace the use of artificial intelligence (AI). From the topic analysis, as a result, it emerged that this is an open field for future research, especially with the implementation of AI, which requires good datasets and trials on the models’ architectures, in terms of input layer, number of hidden layer and neurons, and percentage of data to be employed for model training and testing. Full article

Ground-penetrating radar (GPR) is an established technology with a wide range of applications for civil engineering, geological research, archaeological studies, and hydrological practices. In this regard, this study applies bibliometric and scientometric assessment to provide a systematic review of the literature on GPR-related research. This study reports the publication trends, sources of publications and subject categories, cooperation of countries, productivity of authors, citations of publications, and clusters of keywords in GPR-related research. The Science Citation Index Expanded (SCI-EXPANDED) and the Social Sciences Citation Index (SSCI), which can be accessed through the Web of Science Core Collection, are used as references. The findings report that the number of publications is 6880 between 2001 and 2021. The number of annual publications has increased significantly, from 139 in 2001 to 576 in 2021. The studies are published in 894 journals, and the annual number of active journals increased from 68 in 2001 to 215 in 2021. Throughout the study, the number of subject categories involved in GPR-related research fluctuated, ranging from 38 in 2001 to 68 in 2021. The research studies originated from 118 countries on 6 continents, where the United States and the People’s Republic of China led the research articles. The top five most common keywords are ground-penetrating radar, non-destructive testing, geophysics, electrical resistivity tomography, and radar. After investigating the clusters of keywords, it is determined that civil engineering, geological research, archaeological studies, and hydrological practices are the four main research fields incorporating GPR utilization. This study offers academics and practitioners an in-depth review of the latest research in GPR research as well as a multidisciplinary reference for future studies. Full article