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@article{Lim2023,

title = {Environmental, Social, and Governance (ESG) and Artificial Intelligence in Finance: State-of-the-Art and Research Takeaways},

author = {Tristan Lim},

url = {https://europepmc.org/article/ppr/ppr651155

https://www.researchgate.net/profile/Tristan_Lim5/publication/370228369_Environmental_Social_and_Governance_ESG_and_Artificial_Intelligence_in_Finance_State-of-the-Art_and_Research_Takeaways/links/64474633017bc07902d798dc/Environmental-Social-and-Governance-ESG-and-Artificial-Intelligence-in-Finance-State-of-the-Art-and-Research-Takeaways.pdf},

doi = {10.21203/rs.3.rs-2849051/v1},

year  = {2023},

date = {2023-04-01},

urldate = {2023-04-01},

abstract = {The rapidly growing research landscape in finance, encompassing environmental, social, and governance (ESG) topics and associated Artificial Intelligence (AI) applications, presents challenges for both new researchers and seasoned practitioners. This study aims to systematically map the research area, identify knowledge gaps, and examine potential research areas for researchers and practitioners. The investigation centers around three research questions: key research themes for ESG and AI in finance, research intensity and interest evolution, and the use and progression of AI techniques within these themes. Eight archetypical research domains were identified: (i) Trading and Investment, (ii) ESG Disclosure, Measurement and Governance, (iii) Firm Governance, (iv) Financial Markets and Instruments, (v) Risk Management, (vi) Forecasting and Valuation, (vii) Data, and (viii) Responsible Use of AI. Distinctive AI techniques were found to be employed across these archetypes. The study contributes to consolidating knowledge on the intersection of ESG, AI, and finance, offering an ontological inquiry and key takeaways for practitioners and researchers. Important insights include the popularity and crowding of the Trading and Investment domain, the growth potential of the Data archetype, and the high potential of Responsible Use of AI, despite its low publication count. By understanding the nuances of different research archetypes, researchers and practitioners can better navigate this complex landscape and contribute to a more sustainable and responsible financial sector.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Reyes2023,

title = {Bibliometric Analysis and Comprehensive Review of Stormwater Treatment Wetlands: Global Research Trends and Existing Knowledge Gaps},

author = {Nash Jett Reyes and Franz Kevin F. Geronimo and Heidi B. Guerra and Lee-Hyung Kim},

url = {https://www.mdpi.com/2071-1050/15/3/2332},

doi = {10.3390/su15032332},

issn = {2071-1050},

year  = {2023},

date = {2023-01-27},

urldate = {2023-01-27},

journal = {Sustainability},

volume = {15},

number = {3},

abstract = {Stormwater treatment wetlands are widely recognized as efficient and cost-effective solutions to growing stormwater problems. This study presented a new approach to evaluating the current status and trends in stormwater treatment wetlands research. The annual scientific productivity of different states was identified using a bibliometric analysis approach. The number of publications related to stormwater treatment wetlands has exhibited an increasing trend since the earliest record of publication. USA and China were among the states that had the most number of stormwater treatment wetlands-related publications and international collaborations. In terms of the population-to-publication ratio, Australia, Canada, and South Korea were found to have a higher level of scientific productivity. Analysis of frequently used keywords and terms in scientific publications revealed that the efficiency of stormwater treatment wetlands and the processes involved in the removal of nutrients and trace elements were adequately investigated; however, inquiries on the removal of organic micropollutants and emerging pollutants, such as pharmaceuticals and personal care products, microplastics, and industrial compounds, among others, are still lacking. Through the comprehensive review of related scientific works, the design, components, and primary factors affecting the performance of stormwater treatment wetlands were also identified. Future works that address the aforementioned knowledge gaps are recommended to optimize the benefits of stormwater treatment wetlands.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jaramillo2021,

title = {Load modelling and non-intrusive load monitoring to integrate distributed energy resources in low and medium voltage networks},

author = {Andres F. Moreno Jaramillo and David M. Laverty and D. John Morrow and Jesús Martinez del Rincon and Aoife M. Foley},

url = {https://www.sciencedirect.com/science/article/pii/S0960148121010612},

doi = {https://doi.org/10.1016/j.renene.2021.07.056},

issn = {0960-1481},

year  = {2021},

date = {2021-12-01},

urldate = {2021-12-01},

journal = {Renewable Energy},

volume = {179},

pages = {445-466},

abstract = {In many countries distributed energy resources (DER) (e.g. photovoltaics, batteries, wind turbines, electric vehicles, electric heat pumps, air-conditioning units and smart domestic appliances) are part of the ‘Green Deal’ to deliver a climate neutral society. Policy roadmaps, despite providing a framework and penetration targets for DER, often lack the network planning strategies needed to transition from passive to active distribution networks. Currently, DER's dynamic performance parameters and location identification techniques are not fully standardised. In fact, it can be very ad hoc. Standardised distributed load modelling and non-intrusive load monitoring (NILM) for equipment manufacturers, installers and network operators is critical to low and medium voltage network management in order to facilitate better balancing, flexibility and electricity trading across and within the power system for mass DER deployment. The aim of this paper is to fill this load modelling and NILM knowledge gap for DERto inform the ‘Green Deal’ transition and support standardisation. In the paper, existing load modelling techniques and NILM methodologies are critically examined to inform and guide research activity, equipment development and regulator thinking, as well as network operators. Seven key findings that need urgent attention are identified to support a smooth power system reconfiguration.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Malanski2019b,

title = {Characteristics of “work in agriculture” scientific communities. A bibliometric review},

author = {Priscila Duarte Malanski and Sandra Mara de Alencar Schiavi and Benoît Dedieu },

url = {https://link.springer.com/article/10.1007/s13593-019-0582-2},

doi = {10.1007/s13593-019-0582-2},

year  = {2019},

date = {2019-06-19},

urldate = {2019-06-19},

journal = {Agronomy for Sustainable Development},

volume = {39},

number = {36},

abstract = {Work is a central concern for sustainable farming systems and rural communities, especially regarding specific issues of the agricultural sector, as the strong decrease in rural employment and the less attractive working conditions. Many articles covering diverse related topics have been published. However, the few studies analyzing the state of worldwide scientific research on work in agriculture give only a fragmented view, since they focus on specialized topics and disciplines. To fill this knowledge gap, the aim of this study was to review the state of research on work in agriculture addressed by the scientific literature, through a bibliometric analysis by country, institution, journal, author, and keywords. Our main finds are that (1) work in agriculture issues is divided into six main research domains: occupational health and safety, labor market and rural employment, labor and farm sustainability, work organization, agricultural policy and agrarian changes, and labor and family farms; (2) these research domains are analyzed by five scientific communities: ergonomics, agricultural economics, livestock farming systems, rural sociology, and agricultural policy; (3) the reference authors, most-cited articles, and main journals were identified for each scientific community; (4) USA, France, and China arise as leaders in the scientific landscape. We show for the first time the characteristics of the main scientific communities worldwide that have performed the most relevant research related to work in agriculture over the past 10 years. This review provides a benchmark for future research on agricultural work-related topics and encourages collaborations between researchers from different scientific communities for interdisciplinary innovation, which support sustainable working conditions in agriculture.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{matos2018canyons,

title = {Canyons pride and prejudice: Exploring the submarine canyon research landscape, a history of geographic and thematic bias},

author = {Fábio L Matos and Steve W Ross and Veerle ann ida Huvenne and Jaime Davies and Marina R Cunha},

url = {https://doi.org/10.1016/j.pocean.2018.04.010},

doi = {10.1016/j.pocean.2018.04.010},

year  = {2018},

date = {2018-01-01},

urldate = {2018-01-01},

journal = {Progress in Oceanography},

publisher = {Elsevier},

abstract = {We mapped submarine canyon research using a scientometric approach to define and characterize its scientific landscape based on a comprehensive bibliographic dataset. The abundance of studies covering structural and functional aspects of submarine canyons allowed us to identify the existing knowledge clusters, historical trends, and emergent topics in canyon research. Our analysis documented a network of knowledge clusters of which four were particularly relevant: a strong cluster on “Geology & Geophysics”, well established since the beginnings of canyon research; a cluster on “Biology & Ecology” that gained strength primarily over the past two to three decades; a cluster on “Oceanographic Processes” which occupied a central position in the network and connected strongly to almost all the other clusters and especially to the fourth main cluster on “Modelling”. A smaller, but also well connected, cluster on “Biogeochemistry” related closely to “Biology & Ecology”, and three other small clusters (“Sedimentology”, “Sediments & Tidal Currents”, “Canyon Sampling”) bridged the main clusters. Finally, we identified three small, but specific satellite clusters (“Oil & Gas”, “Chemosynthetic Communities”, “Molecular & Symbionts”). The high-level structure of the knowledge network reflects a latent interdisciplinarity in canyon research. However, the evolution of the research lines over the past nine decades suggests that this pattern arose mostly in the new millennium. Emergent research topics in the last decade also reveal a concern regarding anthropogenic impacts and climate-driven processes. Our results also show a well implemented and international collaboration network, although research efforts have been mainly directed towards only a few canyon systems. A geographical and thematic bias also characterizes canyon research, with specific topics addressed preferentially in particular canyons by different leading research institutions. This spatial and thematic bias, together with the paucity of truly inter-disciplinary studies, may be the most important limitation to integrated knowledge and development in canyon research and hinders a global, more comprehensive understanding of canyon patterns and processes. The scientific landscape mapping and the complementary results are made available as an open and interactive platform that canyon stakeholders can use as a tool to identify knowledge gaps, to find key players in the global collaboration network and to facilitate planning of future research in submarine canyons.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}