Relevant bibliographies by topics / ESG Scoring Engine

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Academic literature on the topic 'ESG Scoring Engine'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "ESG Scoring Engine"

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Liu, Yiting, Joerg Osterrieder, Branka Hadji Misheva, Nicole Koenigstein, and Lennart Baals. "Navigating the Environmental, Social, and Governance (ESG) landscape: constructing a robust and reliable scoring engine - insights into Data Source Selection, Indicator Determination, Weighting and Aggregation Techniques, and Validation Processes for Comprehensive ESG Scoring Systems." Open Research Europe 3 (July 26, 2023): 119. http://dx.doi.org/10.12688/openreseurope.16278.1.

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This white paper explores the construction of a reliable Environmental, Social, and Governance (ESG) scoring engine, with a focus on the importance of data sources and quality, selection of ESG indicators, weighting and aggregation methodologies, and the necessary validation and benchmarking procedures. The current challenges in ESG scoring and the importance of a robust ESG scoring system are addressed, citing its increasing relevance to stakeholders. Furthermore, different data types, namely self-reported data, third-party data, and alternative data, are critically evaluated for their respec
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Burnaev, Evgeny, Evgeny Mironov, Aleksei Shpilman, Maxim Mironenko, and Dmitry Katalevsky. "Practical AI Cases for Solving ESG Challenges." Sustainability 15, no. 17 (2023): 12731. http://dx.doi.org/10.3390/su151712731.

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Artificial intelligence (AI) is a rapidly advancing area of research that encompasses numerical methods to solve various prediction, optimization, and classification/clustering problems. Recently, AI tools were proposed to address the environmental, social, and governance (ESG) challenges associated with sustainable business development. While many publications discuss the potential of AI, few focus on practical cases in the three ESG domains altogether, and even fewer highlight the challenges that AI may pose in terms of ESG. The current paper fills this gap by reviewing practical AI applicat
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Olawale, Habeeb Olatunji, Adegbola Oluwole Ogedengbe, Maxwell Nana Ameyaw, Temitayo Oluwaseun Jejeniwa, and Solomon Christopher Friday. "Standardizing Compliance Practices across AML, ESG, and Transaction Monitoring for Financial Institutions." Journal of Frontiers in Multidisciplinary Research 5, no. 2 (2024): 75–93. https://doi.org/10.54660/.jfmr.2024.5.2.75-93.

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In today’s complex regulatory landscape, financial institutions face mounting pressure to standardize compliance practices across Anti-Money Laundering (AML), Environmental, Social, and Governance (ESG), and transaction monitoring frameworks. Fragmented compliance efforts often lead to operational inefficiencies, regulatory breaches, and reputational damage. This study proposes an integrated compliance standardization framework that unifies AML, ESG, and transaction monitoring through data-driven governance, cross-functional controls, and risk-based alignment. The goal is to develop a cohesive
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Ge, Dongdong, Luhui Hu, Bo Jiang, Guangjun Su, and Xiaole Wu. "Intelligent site selection for bricks-and-mortar stores." Modern Supply Chain Research and Applications 1, no. 1 (2019): 88–102. http://dx.doi.org/10.1108/mscra-03-2019-0010.

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Purpose The purpose of this paper is to achieve intelligent superstore site selection. Yonghui Superstores partnered with Cardinal Operations to incorporate a tremendous amount of site-related information (e.g. points of interest, population density and features, distribution of competitors, transportation, commercial ecosystem, existing own-store network) into its store site optimization. Design/methodology/approach This paper showcases the integration of regression, optimization and machine learning approaches in site selection, which has proven practical and effective. Findings The result w
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Tam, Prohim, Sa Math, and Seokhoon Kim. "Priority-Aware Resource Management for Adaptive Service Function Chaining in Real-Time Intelligent IoT Services." Electronics 11, no. 19 (2022): 2976. http://dx.doi.org/10.3390/electronics11192976.

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The growth of the Internet of Things (IoT) in various mission-critical applications generates service heterogeneity with different priority labels. A set of virtual network function (VNF) orders represents service function chaining (SFC) for a particular service to robustly execute in a network function virtualization (NFV)-enabled environment. In IoT networks, the configuration of adaptive SFC has emerged to ensure optimality and elasticity of resource expenditure. In this paper, priority-aware resource management for adaptive SFC is provided by modeling the configuration of real-time IoT ser
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Hubbard, Janie. "Notable Trade Book Lesson Plan Jane Addams: Champion of Democracy Written by Judith Bloom Fradin & Dennis Brindell Fradin." Social Studies Research and Practice 6, no. 1 (2011): 128–40. http://dx.doi.org/10.1108/ssrp-01-2011-b0010.

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Jane Addams: Champion of Democracy is a biography incorporating history and social justice. This lesson involves students in grades 5-8 exploring social justice issues related to economic equality, racial equality, gender equality, health equality, peace, and justice. Students trace Jane Addams’s public service activities, in these areas of social justice, while simultaneously examining significant, external historical events and people, between 1860 and 1939, through the lens of Addams’s life. Students create a timeline and engage in ongoing discussions related to Addams’s involvement in thes
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Recker, Amy, Ellen McCreedy, Rosa Baier, et al. "EVALUATING NURSING HOME-BASED INTERVENTIONS ON COMPETENCY LEVELS." Innovation in Aging 8, Supplement_1 (2024): 422–23. https://doi.org/10.1093/geroni/igae098.1375.

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Abstract The intervention at the heart of the 40WINKS sleep trial relies on a principle that can be applied to many other nursing home-based interventions: Progress through the intervention requires a gradual and consistent accumulation of skills that build upon one another. Without completing a fundamental level of the intervention (e.g., begin to hold staff huddles regularly), a nursing home’s team could not incorporate advanced concepts (e.g., engage in collaborative problem solving during huddles). With this in mind, the 40WINKS research team decided to evaluate the participating nursing h
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Alfeo, Antonio L., Mario G. C. A. Cimino, and Gigliola Vaglini. "Technological troubleshooting based on sentence embedding with deep transformers." Journal of Intelligent Manufacturing 32, no. 6 (2021): 1699–710. http://dx.doi.org/10.1007/s10845-021-01797-w.

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AbstractIn nowadays manufacturing, each technical assistance operation is digitally tracked. This results in a huge amount of textual data that can be exploited as a knowledge base to improve these operations. For instance, an ongoing problem can be addressed by retrieving potential solutions among the ones used to cope with similar problems during past operations. To be effective, most of the approaches for semantic textual similarity need to be supported by a structured semantic context (e.g. industry-specific ontology), resulting in high development and management costs. We overcome this li
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Proyag, Pal, Wang Zhiyuan, Zhu Xu, Chew Jiajia, Pruś Katarzyna, and Wei Xiangang. "AI-Based Credit Risk Assessment and Intelligent Matching Mechanism in Supply Chain Finance." Journal of Theory and Practice in Economics and Management 2, no. 3 (2025): 1–9. https://doi.org/10.5281/zenodo.15368771.

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<em>In the context of increasing complexity and globalization of supply chain finance (SCF), traditional credit risk assessment and loan matching mechanisms face significant challenges, including inefficiency, information asymmetry, and high default risks. These limitations hinder the development of inclusive financing, especially for small and medium-sized enterprises (SMEs) that often lack strong credit histories or tangible collateral. Recent advances in artificial intelligence (AI) and machine learning provide new opportunities to address these challenges through data-driven, adaptive, and
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Lau, Annie Y. S., and Pascal Staccini. "Artificial Intelligence in Health: New Opportunities, Challenges, and Practical Implications." Yearbook of Medical Informatics 28, no. 01 (2019): 174–78. http://dx.doi.org/10.1055/s-0039-1677935.

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Objectives: To summarise the state of the art during the year 2018 in consumer health informatics and education, with a special emphasis on the special topic of the International Medical Informatics Association (IMIA) Yearbook for 2019: “Artificial intelligence in health: new opportunities, challenges, and practical implications”. Methods: We conducted a systematic search of articles published in PubMed using a predefined set of queries that identified 99 potential articles for review. These articles were screened according to topic relevance and 14 were selected for consideration as best pape
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Conference papers on the topic "ESG Scoring Engine"

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John Tutor, Lucky, and Yi Cai. "Monitoring Rehabilitation of Stroke Patients Using Automated Fugl-Meyer Assessment." In 15th International Conference on Applied Human Factors and Ergonomics (AHFE 2024). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005059.

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The Fugl-Meyer Assessment (FMA) is a widely used method for evaluating the motor function of stroke patients. During the assessment, patients are instructed to perform a series of predefined motions outlined in the FMA manual, while an evaluator scores each motion using a 3-point Likert scale. A score of 2 is given for flawless execution, a score of 1 for partial completion, and a score of 0 for no execution or lack of motion. Traditional FMA assessments rely on manual visual inspection, but recent studies have explored automating the process using motion capture technology or IMU and EMG sens
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Alquraini, A. H., H. H. Al Sadah, M. M. AlBori, and M. S. Al-Kadem. "The Utilization of Machine Learning and Deep Learning to Predict Real-Time ESP Well Status." In SPE Artificial Lift Conference and Exhibition - Americas. SPE, 2024. http://dx.doi.org/10.2118/219541-ms.

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Abstract One of the most common, efficient and reliable artificial lift methods used for lifting high volumes of fluids from wellbores is the Electric Submersible Pump (ESP). Thus, monitoring the live status of this ESP is essential to determine whether a well is on stream or off. In this research, a new methodology that utilize advanced Machine Learning (ML) to recognize ESP performance status in real time and provide it to engineers instantaneously. In this research, the proposed methodology was to develop an intelligent system that consciously monitor ESP sensors and provide a reliable pred
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Reports on the topic "ESG Scoring Engine"

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Allen, Kathy, Andy Nadeau, and Andy Robertston. Natural resource condition assessment: Salinas Pueblo Missions National Monument. National Park Service, 2022. http://dx.doi.org/10.36967/nrr-2293613.

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The Natural Resource Condition Assessment (NRCA) Program aims to provide documentation about the current conditions of important park natural resources through a spatially explicit, multi-disciplinary synthesis of existing scientific data and knowledge. Findings from the NRCA will help Salinas Pueblo Missions National Monument (SAPU) managers to develop near-term management priorities, engage in watershed or landscape scale partnership and education efforts, conduct park planning, and report program performance (e.g., Department of the Interior’s Strategic Plan “land health” goals, Government
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Tabakovic, Momir, Stefan Savic, Andreas Türk, et al. Analysis of the Technological Innovation System for BIPV in Austria. Edited by Michiel Van Noord. International Energy Agency Photovoltaic Power Systems Programme, 2024. http://dx.doi.org/10.69766/aocp4683.

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This report analyses the Technological Innovation System (TIS) of Building Integrated Photovoltaics (BIPV) in Austria. The study’s scope is consistent with the IEA PVPS Task 15 report [1].The analysis aims to facilitate and support the innovation, development, and implementation of industrial solutions of BIPV technologies. In Austria, the use of BIPV is still a niche application and covers under 2% of all implemented PV systems [1]. BIPV technology in Austria has historically developed with the support of different public financial incentives, national and European. The history of BIPV is som
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