Search Results (107)

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability. Full article

Heart failure is a heterogeneous disorder that can lead to cardiogenic shock. Mechanical circulatory support (MCS) devices can replace the cardiac function in an attempt to bridge patients to transplant or they can serve as destination therapy to improve overall patient functionality and in turn quality of life. Currently utilized MCS devices include devices such as Left Ventricular Assist Devices (LVADs), Biventricular Assist Devices (BiVADs), Impella, Total Artificial Hearts (TAHs), and extracorporeal membrane oxygenation (ECMO). This literature review examines a range of studies, case reports, and meta-analyses to present current approaches to mechanical circulatory support (MCS), along with the challenges and limitations of existing devices, common complications, and overall survival and long-term outcomes following MCS therapy. Full article

This study addresses the increasing emphasis on sustainability and the importance of understanding how environmental risk influences business failure, a factor unexplored in traditional financial prediction models. Environmental risk, or environmental financial exposure, refers to the potential percentage of a company’s revenue at risk due to the environmental damage it causes. Previous research has not sufficiently integrated environmental variables into failure prediction models. This study aims to determine whether environmental risk significantly predicts business failure and how it interacts with conventional financial indicators. Utilizing data from 971 Spanish cooperative companies in 2022, including financial ratios, the VADIS bankruptcy propensity indicator, and the TRUCAM environmental risk score, the study employs the Extreme Gradient Boosting (XGBoost) machine learning algorithm, chosen for its robustness in handling multicollinearity and nonlinear relationships. The methodology involves training and validation samples, cross-validation for hyperparameter tuning, and interpretability techniques such as variable importance analysis and partial dependence plots. Results demonstrate that the variable related to environmental risk (TRUCAM) ranks among the top predictors, alongside liquidity, profitability, and labor costs, with higher TRUCAM values correlating positively with failure risk, underscoring the importance of sustainable cost management. These findings suggest that firms facing substantial environmental risk are more prone to financial distress. By incorporating this environmental variable into a machine learning framework, this work contributes to the interaction between sustainability practices and corporate viability. Full article

In recent years, corporate ESG performance has been widely incorporated into investment decisions and capital allocation considerations, becoming a focal point and hot topic for research by governments and organizations worldwide. However, due to various reasons, significant discrepancies have emerged in ESG ratings for the same company across different institutions, and this growing divergence in ESG ratings has increasingly drawn the attention of scholars. Studying the differences in ESG (environmental, social, and corporate governance) ratings is of great significance. This not only helps to understand the root causes of differences, improve the objectivity, consistency, and comparability of ratings, but also helps users better understand the meaning and limitations of rating results. It is beneficial for investors to understand the focus of different ratings and develop more effective investment strategies. It can promote rated companies to improve the quality and transparency of ESG-related information disclosure. It can also provide a reference for regulatory agencies and policymakers, identify market failures and potential risks, and promote the development of more unified standards and frameworks. At the same time, this study can also promote the in-depth development of relevant academic research and theories. Based on this, this study systematically reviews the relevant literature on ESG rating divergence, focusing on its existence, causes, influencing factors, and impacts. The study finds that, in addition to the widespread existence of rating divergence in corporate ESG performance, scholars also disagree on the measurement and methods of this divergence. The reasons for rating divergence are mainly that ESG is a qualitative indicator; top-level design, intermediate calculations, and bottom-level data collection across multiple stages exacerbate divergence; and controversies in practice further deepen divergence, among others. The influencing factors and impact effects of ESG rating divergence are diverse. Given the existence of ESG rating divergence, all parties should treat ESG ratings with caution. This paper offers corresponding recommendations and looks forward to the future, providing a foundation for subsequent research. Full article

Corporate performance is increasingly impacted by environmental issues, but their specific role in business failure remains underexplored, which leads to a gap in research that is often focused exclusively on financial metrics. By investigating the relationship between environmental financial exposure and business failure, this study addresses this gap, integrating financial ratios and environmental variables to understand how environmental performance affects financial viability. A novel dual-stage methodology was employed, first using Extreme Gradient Boosting (XGBoost) for feature selection to identify the most significant predictors of failure from a dataset of Spanish companies (N = 38,456) using 2022 ORBIS data. Next, a fuzzy-set qualitative comparative analysis (fsQCA) was applied to analyze the sufficient causal configurations leading to a high propensity for business failure. The analysis identified three distinct causal configurations associated with failure. All highlighted poor financial performance indicators, such as low results per employee and low profit per employee. Notably, one configuration identified high environmental risk (measured by TRUCAM) as a core condition contributing significantly to financial distress. These findings highlight the critical link between environmental responsibility and financial health, demonstrating the benefits of combining fsQCA with machine learning to identify intricate causal configurations and providing information to companies and governments who want to support long-term financial stability and corporate sustainability. Full article

This conceptual paper introduces Macro Stewardship (Ma-S) as a transformative approach in sustainable finance to challenge financial market failures that contribute to systemic collective action issues such as climate change, biodiversity loss, and inequality. It argues that traditional Environmental, Social, and Governance (ESG) strategies focus on individual corporate actions and often fail to drive systemic change. Ma-S, on the other hand, leverages the power of financial institutions to engage governments, policymakers, and stakeholders in addressing market failures tied to sustainability. Unlike Micro Stewardship (Mi-S) or ESG approach, which centers on corporate-level engagement, Ma-S promotes collaborative interventions to align the interests of businesses, governments, and society. This approach aims to influence regulatory changes, shape public policy, and support the United Nations Sustainable Development Goals (SDGs). The paper is guided by the research question: How can Macro Stewardship by financial institutions serve as a transformative approach in sustainable finance to achieve systemic change? It proposes a definition for Ma-S, outlines its practical applications, identifies implementation challenges, and presents a research agenda to evaluate its effectiveness and impact. In doing so, the paper lays a foundation for future empirical studies and calls for a shift in how financial systems contribute to global sustainability. Full article

This study examines the feasibility of using financial ratios and non-financial variables to predict audit opinions (qualified or unqualified) for firms listed on the Athens Exchange (ATHEX) from 2018 to 2022. Using 450 firm-year observations from 90 non-financial firms, we applied a logit regression model to analyze the relationship between 11 financial ratios and non-financial factors, such as auditor quality, auditor turnover, and corporate performance. While the results indicate that auditor characteristics, particularly auditor quality, have significant explanatory power, the predictive strength of financial ratios varies, suggesting that audit opinions in Greece may be influenced by broader governance and institutional factors rather than financial indicators alone. The study provides empirical insights that contribute to the development of predictive models for audit opinion assessment. These findings are particularly relevant in emerging economies like Greece, where audit risk and firm failures are heightened due to economic and regulatory challenges. By identifying key determinants of audit opinions, the study enhances understanding of audit risk assessment and its alignment with International Standards on Auditing (ISA 520). However, its findings are limited by the sample size and Greece’s unique regulatory environment. Future research should explore the integration of additional governance and institutional variables and assess the model’s applicability in larger and more developed markets. Full article

This article describes the Heritage Sustainability Index (HSI), a benchmarking tool that draws on a series of key indicators to rate company actions as they relate to the protection of cultural heritage. The purpose of the HSI is to provide an independent framework for lenders, borrowers, and civil society, including Indigenous Peoples, to evaluate corporate safeguard policies and practices related to cultural heritage, enabling informed decision making. Given their importance and influence, the HSI focuses on the practices of Global Systemically Important Banks (G-SIBs), which were chosen to represent a baseline for comparison across all industry sectors. The HSI’s indicators (n = 12) and sub-indicators (n = 48) were successful in illustrating the variability that exists among the G-SIBs. Corporations with an HSI value below the upper quartile of the distribution should take steps to enhance their cultural heritage safeguard practices. This is crucial because scores below this value reflect weak practices, indicating higher financial and reputational risk exposures and poor outcomes for cultural heritage. By focusing on improving their HSI values, these corporations can better mitigate potential risks and enhance their overall sustainability profile. The success and longevity of the HSI will depend on industry goodwill and the perceived risk that cultural heritage poses to corporate financial performance and reputation. Given the potential financial and reputational damage from a significant failure in cultural heritage stewardship, corporations are expected to recognize these advantages and find it an easy decision to support the adoption of the HSI. Full article

Objective: With rapid urbanization in countries like India, understanding the nutritional status and needs of urban populations, particularly among underprivileged groups such as people living in slums, is crucial. This study investigates the prevalence, characteristics, and determinants of child malnutrition in the urban slums of the Kolkata Municipal Corporation (KMC) and Siliguri Municipal Corporation (SMC) in West Bengal, India. Methods: A cross-sectional study was conducted among 736 children aged 6–59 months. Data were collected using structured interviews to gather socioeconomic, demographic, and dietary information, alongside anthropometric measurements. The analysis employed the Composite Index of Anthropometric Failure (CIAF), and multiple linear regression (MLR) models to identify key factors influencing malnutrition. Results: The findings revealed a high prevalence of stunting (24.1%), underweight (22.3%), and wasting (15.4%) among children aged 6–59 months, with significant variations observed between the two study sites. Key predictors of anthropometric malnutrition include low household income, incidence of recent illness, low maternal nutrition, and delayed initiation of breastfeeding. Conclusions: Addressing child malnutrition in urban slums requires integrated strategies encompassing income-generation opportunities, health-sensitive urban planning, and focused maternal and child health interventions. Full article

Background/Objectives: Microorganisms are the leading cause of infections in the root canal system, contributing to the failure of endodontic treatments. This in vitro study aimed to compare the antimicrobial effects of four different endodontic sealers: Endomethasone N (Septodont, Saint Maur-des-Fossés, France), Sealapex (Kerr Corporation, Orange, CA, USA), AH Plus Jet (Dentsply DeTrey GmbH, Konstanz, Germany), and MTA Fillapex (Angelus, Londrina, Brazil). Methods: The sealers were tested against common oral pathogens, including Enterococcus faecalis, Staphylococcus aureus, Escherichia coli, Candida albicans, and Streptococcus mutans, using the agar diffusion method. Inhibition zones were measured at 24, 48, and 72 h to assess antimicrobial efficacy. Results: The results showed that Endomethasone was the most effective sealer against all tested microorganisms, demonstrating consistent inhibition across all time intervals. MTA Fillapex also exhibited a significant antimicrobial effect, particularly against Streptococcus mutans, with its efficacy increasing over time. AH Plus Jet displayed limited effectiveness, showing significant results only against Staphylococcus aureus. Conclusions: Overall, this study confirms the superior antimicrobial performance of Endomethasone, while the other materials, particularly MTA Fillapex and Sealapex, also showed notable effects in experimental conditions. The antimicrobial activity of all materials, except AH Plus Jet, increased over the 72-h period. Full article

The proper allocation of corporate capital is critical to sustainable business development, and misallocation of resources can impede sustainable economic growth and competitive markets. This study investigates the relationship between market power and capital misallocation in Chinese A-share listed companies, with a novel focus on the mediating role of total factor productivity (TFP). Using a comprehensive dataset of 20,818 firm-year observations from 2009 to 2021, we employ linear regression analysis to elucidate the mechanisms through which market power influences capital allocation efficiency. The results reveal a significant positive correlation between market power and capital misallocation, with TFP partially mediating this relationship. Specifically, a one-unit increase in the market power index is associated with a 1.106 unit decrease in TFP, and a 0.028 unit increase in the capital misallocation, indicating potential threats to long-term sustainability. This effect is more pronounced in non-state-owned enterprises, firms located in eastern regions, and those without shareholdings in financial institutions. These results contribute to the literature on market structure and resource allocation by providing empirical evidence of the detrimental effects of market power on capital allocation efficiency, operating through the channel of reduced productivity. Our findings have important implications for policymakers and firm managers, suggesting the need for targeted antitrust measures, promotion of market competition, and strategies to enhance TFP. This research advances our understanding of the complex interplay between market power, productivity, and capital allocation in emerging economies, offering valuable insights for addressing market failures, improving allocative efficiency and actively promoting sustainable business and sustainable socio-economic development in the Chinese context. Full article

This study seeks to answer the question of whether we could use a bank’s past financial data to predict the bank failure in 2009 and proposes three new empirical proxies for loan quality (LQ), interest margins (IntMag), and earnings efficiency (OIOE) to forecast bank failure. Using the bank failure list from the Federal Deposit Insurance Corporation (FDIC) database, I match the banks that failed in 2009 with a control sample based on geography, size, the ratio of total loans to total assets, and the age of banks. The model suggested by this paper could predict correctly up to 94.44% (97.15%) for the failure (and non-failure) of banks, with an overall 96.43% prediction accuracy, (p = 0.5). Specifically, the stepwise logistic regression suggests some proxies for capital adequacy, assets/loan risk, profit efficiency, earnings, and liquidity risk to be the predictors of bank failure. These results partially agree with previous studies regarding the importance of certain variables, while offering new findings that the three proposed proxies for LQ, IntMag, and OIOE statistically and economically significantly impact the probability of bank failure. Full article

This paper explores different building maintenance strategies in commercial buildings in Sydney, Australia, focusing on corrective maintenance (CM) and preventive maintenance (PM). While CM involves rectifying issues after they occur, PM aims to enhance productivity by anticipating potential issues. Although PM seems more logical, the decision to implement this type of maintenance strategy are typically made based on item reliability, failure frequency, and downtime cost, commonly found in manufacturing facilities or critical environments. However, as found in the selected/surveyed commercial real estate buildings, CM was more frequently adopted in aged facilities with older infrastructure, and PM was favoured for buildings without structural deficiencies; however, operating equipment failures were common. However, in many cases, decision makers did not consider the broader effects of downtime beyond direct financial losses, costs associated with customer satisfaction, worker efficiency, rent abatements, and reputation damage. While each building is unique and may require a bespoke maintenance schedule, this study’s insights may help managers select the most appropriate maintenance strategy. Nonetheless, further research is needed to investigate the role of innovative technologies (such as machine learning and artificial intelligence) in enhancing maintenance efficacy and explore the influences of economic shifts, corporate and financial objectives, and the availability of technical resources. Full article

High thin-walled cold-formed steel purlins of the Z cross section are important elements of large-span steel structures in the construction industry. The present numerical study uses the finite element method to analyse the 300 mm and 350 mm high Z cross sections in-depth. The prepared numerical models are verified and validated at several levels with experiments that have been previously published. Significant agreement between the numerical models and the experimental results regarding Mises stress, proportional strain, failure mode, and force-deformation diagram have been obtained. With the verification, the presented procedure and partial findings can be applied to other similar problems. The results can be used to help research and corporate groups optimise the structural design of cold-formed thin-walled steel structures. Full article

Left ventricular (LV) longitudinal function is mechanically coupled to the elasticity of the ascending aorta (AA). The pathophysiologic link between a stiff AA and reduced longitudinal strain and the subsequent deterioration in longitudinal LV systolic function is likely relevant in heart failure with preserved ejection fraction (HFpEF). The proposed therapeutic effect of freeing the LV apex and allowing for LV inverse longitudinal shortening was studied in silico utilizing the Living Left Heart Human Model (Dassault Systémes Simulia Corporation). LV function was evaluated in a model with (A) an elastic AA, (B) a stiff AA, and (C) a stiff AA with a free LV apex. The cardiac model simulation demonstrated that freeing the apex caused inverse LV longitudinal shortening that could abolish the deleterious mechanical effect of a stiff AA on LV function. A stiff AA and impairment of the LV longitudinal strain are common in patients with HFpEF. The hypothesis-generating model strongly suggests that freeing the apex and inverse longitudinal shortening may improve LV function in HFpEF patients with a stiff AA. Full article