This scientometric analysis significantly advances the understanding of landslide risk assessment and economic losses, focusing on scientometric insights. This study aims at analyzing the global trends and structures of landslide risk and economic loss research from 2002 to 2023 using scientometric techniques such as co-authorship, co-word, co-citation, cluster analysis, and trend topics, among others. Thus, analysis of 92 studies gathered from Scopus and Web of Science databases reveals a continuous growth in environmental, social, and quantitative research topics. Predominant contributions hail mainly from China and Italy. The research identifies critical themes, including risk analysis, vulnerability, fragility, and economic losses. The current identified research combines advanced statistical methods, including logistic regression, with climate change scenarios and susceptibility assessments to reveal intricate connections between climatic shifts, hydrogeological hazards, and their economic and environmental impacts. This study provides researchers and practitioners with a comprehensive understanding of the status quo and research trends of ontology research landslide risk and its economic losses. It also promotes further studies in this domain.

Wavelet power spectrum (WPS) and wavelet coherence analyses (WCA) are used to examine the co-movements among oil prices, green bonds, and CO₂ emissions on daily data from January 2014 to October 2022. The WPS results show that oil returns exhibit significant volatility at low and medium frequencies, particularly in 2014, 2019–2020, and 2022. Also, the Green Bond Index presents significant volatility at the end of 2019–2020 and the beginning of 2022 at low, medium, and high frequencies. Additionally, CO₂ futures’ returns present high volatility at low and medium frequencies, expressly in 2015–2016, 2018, the end of 2019–2020, and 2022. WCA’s empirical findings reveal (i) that oil returns have a negative impact on the Green Bond Index in the medium term. (ii) There is a strong interdependence between oil prices and CO₂ futures’ returns, in short, medium, and long terms, as inferred from the time–frequency analysis. (iii) There also is evidence of strong short, medium, and long terms co-movements between the Green Bond Index and CO₂ futures’ returns, with the Green Bond Index leading.

The analysis of green bonds and the composition of portfolio investments has gained importance in recent research. The current global context of Sustainable Development Goals requires investors to be environmentally, politically, and socially sustainable, in which the financing of green innovations has occupied a central role. Through the Web of Science and Scopus databases, we focused on analyzing recent trends and further research on green bonds into portfolio investments. The study was performed on 102 studies using Tree of Science (ToS), VOSviewer, and Bibliometrix techniques. We recognize the principal authors and sources, the most influential studies, and the bibliography coupling of studies and authors to identify their importance in the topic analysis. In order to expand the green bond market, particularly at the small and medium enterprise level, more policy instruments are needed. Thus, this study provides an extensive understanding of the research status of the analysis of green bonds and portfolio investments research as an essential input for market participants, researchers, policymakers, and decision-makers.

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.

In this study, we examined the extant literature on the dynamic association between oil prices and financial assets with special emphasis on the methodologies for measuring the dependence among oil prices, exchange rates, stock prices, energy markets, and assets related to sustainable finance. We performed a scientometric review of the structure and global trends of the dynamic association among oil prices and financial assets, based on research from 1982 to 2022 (September) using techniques such as the analysis of (i) sources, (ii) authors, (iii) documents, and (iv) cluster analysis. A total of 746 bibliographic records from Scopus and Web of Science databases were analyzed to generate the study’s research data through scientometric networks. The findings indicate that the most promising areas for further research in this field are represented by co-movement, copula, wavelet, dynamic correlation, and volatility analysis. Furthermore, energy markets and assets related to sustainable finance emerge as crucial trends in investigating dynamic co-movements with oil prices. They also suggest a research gap in analyzing by means of machine learning, deep learning, big data, and artificial intelligence for measuring dynamic co-movements among oil prices and assets in financial and energy markets, especially in emerging countries. Thus, these methodologies can be implemented in further research because these methods could more robustly quantify the association among such variables. The analysis provides researchers and practitioners with a comprehensive understanding of the existing literature and research trends on the dynamic association among oil prices and financial assets. It also promotes further studies in this domain. The identification of these relations presents benefits in risk diversification, hedges, speculation, and inflation targeting.

Green bonds play a pivotal role in the financing of sustainable infrastructure systems. Likewise, CO₂ emissions and oil prices can cause an impact on the green bonds market. In order to better understand this issue, this study analyzes the relationship among green bonds, CO₂ futures’ prices, and oil prices using a daily data set that includes 2,206 observations corresponding to daily information from 1 January 2014 to 15 June 2022. The Granger Causality Test and the Dynamic Conditional Correlation (DCC-Garch) Model were employed to conduct this analysis. Furthermore, a sensitivity analysis was performed to identify crisis periods concerning the sample period and provide an analysis of DCC-Garch results during extreme market conditions like the COVID-19 pandemic and the Russian invasion of Ukraine. The Granger Causality Test results present a unidirectional causality running from the Green Bond Index to the oil price returns. Also, there is a unidirectional causality running from the Green Bond Index to the CO₂ futures’ returns. Additionally, a unidirectional causality runs from the oil price returns to the CO₂ futures’ returns. The results for the DCC-Garch indicate a positive dynamic correlation between the Brent oil price return and the CO₂ futures’ returns. Finally, the Green Bond Index shows a negative dynamic correlation to the oil return and the CO₂ futures’ returns presenting a strong correlation in uncertainty periods.