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Financial education represents a powerful tool for improving economic literacy of citizens. This paper presents results from an experiment providing a group of 136 workers in an Italian university (administrative staff) an online, synchronous course. Classes were organized in 5 sessions of 2h each and covered basic topics about personal finance. The effectiveness of the course is assessed through a rigorous randomized controlled trial (RCT). In addition to the analysis of improvements in financial knowledge, financial self‐efficacy and the role of prior attitudes and behaviors were explored. Participants obtained post‐test scores statistically higher than individuals in the control group, with an average effect size of 0.55 SD. The effect is particularly relevant for participants starting with low levels of financial knowledge. Moreover, two novel findings emerge: financial self‐efficacy increases (0.51 SD) after the course, and pre‐treatment individuals' financial attitudes and behaviors shed further light on the financial learning process. [ABSTRACT FROM AUTHOR]

Autoregressive models in time series are useful in various areas. In this article, we propose a skew-t autoregressive model. We estimate its parameters using the expectation-maximization (EM) method and develop the influence methodology based on local perturbations for its validation. We obtain the normal curvatures for four perturbation strategies to identify influential observations, and then to assess their performance through Monte Carlo simulations. An example of financial data analysis is presented to study daily log-returns for Brent crude futures and investigate possible impact by the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

To achieve a competitive advantage, corporations are growingly adopting strategies to effectively promote their market demand. Trade credit payment and pricing strategies provided by corporates can efficiently influence customers' purchasing behavior. Although granting a trade credit strategy can increase corporations' market share, such a strategy is a risk-based financing program for corporations. Therefore, corporates should choose whether to use trade credit financing in their long-term. This paper proposes an analytical model to investigate the evolutionary behaviors of retailers regarding pricing and trade credit strategies in the long term. In the study under investigation, retailers can use two financing strategies: risk-based trade credit and non-trade credit (i.e., pricing). This study provides both numerical and analytical findings. Our findings demonstrate that the risk-based trade credit strategy is the stationary financing solution for retailers in the long term. The result indicates that when customers are financially constrained, providing a trade credit scheme to customers is a successful marketing policy in both short-term and long-term frameworks. [ABSTRACT FROM AUTHOR]

Artificial intelligence methods based on deep learning (DL) have recently made significant progress in many different areas including free text classification and sentiment analysis. We believe that corporate governance is one of these areas, where DL can generate very valuable and differential knowledge, for example, by analyzing the biographies of independent directors, which allows for qualitative modeling of their profile in an automatic way. For this technology to be accepted it is important to be able to explain how it generates its results. In this work we have developed a six-dimensional labeled dataset of independent director biographies, implemented three recurrent DL models based on LSTM and transformers along with four ensembles, one of which is an innovative proposal based on a multi-layer perceptron (MLP), trained them using Spanish language and economics and finance terminology and performed a comprehensive test study that demonstrates the accuracy of the results. We have also performed a complete study of explainability using the SHAP methodology by comparatively analyzing the developed models. We have achieved a mean error (MAE) of 8% in the modeling of the open text biographies, which has allowed us to perform a case study of time analysis that has detected significant variations in the composition of the Standard Expertise Profile (SEP) of the boards of directors, related to the crisis of the period 2008–2013. This work shows that DL technology can be accurately applied to free text analysis in the finance and economic domain, by automatically analyzing large volumes of data to generate knowledge that would have been unattainable by other means. [ABSTRACT FROM AUTHOR]

What drives groundbreaking research in economics? Nobel-prize-winning work has had an important impact on public policies, but we still do not understand well what drives such breakthroughs. We collect data on all nobel-prize discoveries in economics to address this question. We find that major advances in the field of economics are brought about by methodological innovation: by developing new and improved research methods. We find that developing for example econometrics in 1933, randomised controlled trials in 1948 and new game theory methods in 1950 were essential to opening the new fields of corporate finance, experimental economics and information economics, respectively. We identify the development of new methods as the main mechanism driving new discoveries and research fields. Fostering this general mechanism (generating novel methods) holds the potential to greatly increase the rate at which we make new breakthroughs and fields. We also show that many of the main methods of economics – such as randomised controlled trials, natural experiments, regression discontinuity, instrumental variables and other statistical methods – had been developed and used in other fields like public health, before economists adopted them. This shift towards more powerful empirical methods in the field has important implications on developing new and better methods and adopting them from related fields to make new advances more rapidly. [ABSTRACT FROM AUTHOR]

With the rapid development of the economy, a large amount of financial data will be generated during the continuous growth of enterprises. However, due to the explosive growth of the financial data range index, the use of machine learning methods to mine and analyse financial data is extremely important. Among them, accurate financial risk evaluation is an effective measure to prevent and resolve corporate financial crises. In this article, we use fuzzy clustering method to establish a financial risk early warning and evaluation model. Specifically, we use fuzzy C‐mean (FCM), half‐suppressed FCM, and interval FCM clustering algorithms‐based state construction financial risk early warning and evaluation models, to give an evaluation from two aspects of corporate financial indicators and non‐financial indicators system. In order to verify the feasibility and effectiveness of the fuzzy clustering algorithms used in financial data mining, we conducted experiments in financial data mining and early warning in real estate companies and ST companies. The experimental results show that the fuzzy clustering algorithms represented by the FCM clustering algorithm has achieved good results in financial data mining, and can achieve good results in financial risk analysis and financial risk early warning. [ABSTRACT FROM AUTHOR]

Developing green finance is an important measure for China to achieve a win-win situation between economy and ecology. This study adopts the implementation of Green Credit Guidelines (GCG) in China in 2012 as an intervening event and empirically examines its relative impact on corporate financing and investment using Difference-in-Difference and Difference-in-Difference-in-Difference models. Employing the financial data of A-share listed enterprises from 2009 to 2015, we find that the implementation of GCG restrains the financing and investment behavior of heavily polluting enterprises. The effects of GCG are influenced by institutional factors, and GCG has a more inhibitory effect in the higher polluting, state-owned, and eastern region registered enterprises. This result reveals the importance of GCG in adjusting financial leverage and promoting environmental protection. Policy implications, such as governments should improve incentive and punishment mechanism for heavily polluting enterprises and financial institutions should innovate in green credit business, are proposed. [ABSTRACT FROM AUTHOR]

Studying the state of general financial stability from the perspective of commercial banks and the extent of their application of its indicators is one of the important topics that has received great attention internationally. The problem of the study, which bears the title (Analysis of the impact of financial stability using the general aggregate index technique for a sample of Iraqi banks for the period from 2015 to 2021) is focused on the question: Next: Do commercial banks in Iraq have an impact in achieving financial stability in Iraq if the financial stability rates applied by the Central Bank are applied? The study came in two main parts, the first of which dealt with the theoretical framework of financial stability in terms of the concept, challenges, risks, characteristics and components, while the second dealt with the theoretical framework of financial stability in terms of the concept, challenges, risks, characteristics and components. He touched on showing the extent to which the study sample of commercial banks in Iraq applied financial stability rates through financial analysis of indicators. Thus, the study showed a number of conclusions. One of the most important conclusions was that the state of financial stability in Iraq depends to a large extent in achieving it on commercial banks, which must be developed. And keeping pace with the external environment, other global indicators must be applied, and the position of the commercial banks in the research sample was concluded on the basis of financial analysis, which shows an impact in achieving financial stability. [ABSTRACT FROM AUTHOR]

Domestic and international risk shocks have greatly increased the demand for systemic risk management in China. This paper estimates China's multi-layer financial network based on multiple financial relationships among banks, assets, and firms, using China's banking system data in 2021. An improved PageRank algorithm is proposed to identify systemically important banks and other economic sectors, and a stress test is conducted. This study finds that China's multi-layer financial network is sparse, and the distribution of transactions across financial markets is uneven. Regulatory authorities should support economic recovery and adjust the money supply, while banks should differentiate competition and manage risks better. Based on the PageRank index, this paper assesses the systemic importance of large commercial banks from the perspective of network structure, emphasizing the role of banks' transaction behavior and market participation. Different industries and asset classes are also assessed, suggesting that increased attention should be paid to industry risks and regulatory oversight of bank investments. Finally, stress tests confirm that the improved PageRank algorithm is applicable within the multi-layer financial network, reinforcing the need for prudential supervision of the banking system and revealing that the degree of transaction concentration will affect the systemic importance of financial institutions. [ABSTRACT FROM AUTHOR]

Universal health coverage relies on providing essential medical services and shielding individuals from financial risks. Our study assesses the progressivity of out-of-pocket (OOP) payments, identifies factors contributing to healthcare expenditure inequality, and examines catastrophic health expenditures (CHE) prevalence in Kazakhstan from 2018 to 2021. Using retrospective analysis of National Statistics Bureau data, we employed STATA 13 version for calculations CHE incidence, progressivity, Lorenz and concentration curves. In 2020–2021, OOP expenditures in Kazakhstan decreased, reflecting a nearly twofold reduction in the CHE incidence to 1.32% and 1.24%, respectively. However, during these years, we observe a transition towards a positive trend in the Kakwani index to 0.003 and 0.005, respectively, which may be explained by household size and education level factors. Increased state financing and quarantine measures contributed to reduced OOP payments. Despite a low healthcare expenditure share in gross domestic product, Kazakhstan exhibits a relatively high private healthcare spending proportion. The low CHE incidence and proportional expenditure system suggest private payments do not significantly impact financial resilience, prompting considerations about the role of government funding and social health insurance in the financing structure. [ABSTRACT FROM AUTHOR]

This article thoroughly examines the influence of digital transformation on the efficiency of corporate supply chains. As global economic integration accelerates and technological innovations deepen, digital transformation has become key to enhancing core corporate competitiveness. This research, utilizing data from A-share listed companies in China between 2007 and 2022, analyzes how companies improve supply chain efficiency through digital transformation. Furthermore, the study establishes a theoretical framework that demonstrates how digital transformation facilitates supply chain efficiency from the perspectives of internal governance and external competition. The research indicates that digital transformation plays a key role in significantly enhancing supply chain efficiency. Furthermore, the results of the mechanism analysis confirmed that digital transformation contributes to enhancing corporate supply chain efficiency by improving the level of corporate governance and the degree of market competition. The study also finds that the effect of digital transformation on supply chain efficiency varies with different corporate backgrounds, indicating its heterogeneous impact. Lastly, an analysis of economic consequences shows that the increased supply chain efficiency resulting from digital transformation can reduce future external transaction costs, strengthening the company's market position and financial performance. This research provides strategic guidance for firms to develop robust strategies amid the digital wave and offers strong policy recommendations for promoting digital supply chain management and enhancing market adaptability. [ABSTRACT FROM AUTHOR]

Objectives Analysis of laboratory value often lacks assessment of the laboratory's impact on quality of care. In this study, we aimed to determine the impact of bringing a heparin-induced thrombocytopenia (HIT) antibody assay in-house on a quality metric—patient hospital length of stay (LOS)—and assess any associated cost savings. Methods A retrospective review of patient visits with a HIT antibody assay over a 7-year period determined the mean LOS in send-out vs in-house HIT antibody assay cohorts as well as cohorts of positive and negative results. Our systemwide mean LOS and metrics of acuity were analyzed. We performed a financial analysis of estimated cost savings. Results We found a mean LOS reduction of 3.97 days in the in-house cohort, with no evidence of a systemwide LOS decrease or a decline in patient acuity. This reduction was largely driven by a reduction in LOS among patients with a negative assay result. We found an estimated total cost savings of $3.9 million and an estimated mean savings per patient of $7,305, despite escalating health care costs over time. Conclusions We demonstrated a reduction in LOS following the introduction of an in-house HIT antibody assay that cannot be attributed to either systemwide initiatives or reduced patient acuity and was driven largely by patients with negative assays. This reduction was associated with significant estimated cost savings. [ABSTRACT FROM AUTHOR]

Traditionally, entrepreneurs build long-term companies that generate profits by selling goods and services. Nowadays, entrepreneurs are building companies solely to sell them to larger corporations to profit from early 'exits' due to the glorifying media characteristic. Based on an Israeli case study, this article examines how media outlets portray the 'exit' catchphrase. An analysis of semi-structured interviews with Israeli tech journalists and a thematic analysis of news articles is used to identify the three main narratives appearing in the media for encouraging exits: High-tech entrepreneur (individual), company (entity), and the industry (macro point of view). [ABSTRACT FROM AUTHOR]

Using mean and variance causality analysis, this study examines the volatility relationship between Turkish and G7 stock markets. Weekly return data from May 29, 2009, to June 6, 2023, is utilized for the analysis. The Hong mean and variance causality analysis method is employed as the methodology. Based on the results of the study, Turkey and Japan's stock markets have a significant mean causality relationship. Moreover, the variance causality analysis demonstrates a strong relationship between Turkey and stock markets of Canada, France, Germany, Japan, and the United States. The findings contribute to portfolio diversification strategies and highlight the importance of understanding the dynamics of international financial markets. [ABSTRACT FROM AUTHOR]

This paper proposes a dual-feedback process that links watershed plan actions with raw water charges. A dedicated decision support model is created to implement this process and allow long-term financial sustainability analysis. The model offers real-time analysis of various watershed actions using customizable prioritization criteria integrated with different water pricing configurations, including user-polluter pays and beneficiary-pays principles, as well as other funding sources. Application to the Piracicaba–Capiravi–Jundiaí Basins in Brazil shows how important water management and water quality improving actions can be funded through water charges and how finance gaps can be resolved through a shared Vision Modelling approach. [ABSTRACT FROM AUTHOR]

In this paper, the STIRPAT model was developed to study the role of financial development in urban low-carbon economic transformation. The statistical analysis used data from 281 prefecture-level cities in China from 2009 to 2019. The results show that: (1) there is a positive U-shaped nonlinear relationship between financial development and urban low-carbon economic transformation. (2) Financial development not only directly affects the transformation of the low-carbon economy, but also indirectly affects it through three transmission channels: environmental regulation, industrial structure, and urbanization. (3) The financial development itself and the level of urbanization have a threshold effect on the transformation of the low-carbon economy. Under the threshold effect of environmental regulation and industrial structure, the role of financial development in the transformation of low-carbon economies presents a process of 'first decrease and then increase'. Therefore, improving the intensity of environmental regulation, implementing differentiated financial and industrial development policies, and controlling the urbanization process are effective measures to promote the transformation of low-carbon economies. [ABSTRACT FROM AUTHOR]

This study investigates the intangible assets related to the circular economy, defined as 'circular patents', that are classified and measured to be bundled into the innovation capabilities of a firm. The impact of a business's capabilities on its level of circular patent activism is empirically analysed in this study in a theoretical framework of dynamic capabilities. To this end, a model of the cause-and-effect relationship between the circular patents held by firms and their capabilities is designed using partial least squares structural equation modelling (PLS-SEM) and is tested using a sample of 120,406 patents in 2216 Spanish companies. In this analysis, patents that can foster the sharing economy and the circular economy in sensu latu are also considered circular patents, in addition to waste patents and other green patents, offering an enhanced measurement of the intangible assets related to the circular economy. Based on these results, this study provides new insight of how accounting can enable or constrain the transition to a circular economy business model through the measurement and valuation of related intangible assets and the specific business' capabilities in an environmental management framework. [ABSTRACT FROM AUTHOR]

This work surveys the use of directed weighted graphs in conducting comparative static analyses. The paper discusses the implementation of a computer-aided process for building spreadsheet-based graph models for inter- and intra-regional financial flows. The graph-theoretic techniques are programmed to enable the interactive visualization and analysis of financial data using Wolfram technologies (i.e., Mathematica software v. 11.3 or later, Wolfram player v. 12 or later). The paper describes the workflow for several interactive visualizations applicable to financial networks. The author provides four programs, written in the Wolfram language, that customize input–output financial models by combining the Manipulate command with built-in Mathematica functions and functions of the IGraph package (IGraph/M). The study is a tutorial article for the generation of a suite of visual schemes that provide patterns, practices, and roadmaps of the financial markets across the globe. [ABSTRACT FROM AUTHOR]

Background: The popularity of robotic-assisted surgery for rectal cancer is increasing, but its superiority over the laparoscopic approach regarding safety, efficacy, and costs has not been well established. Methods: A retrospective single-center study was conducted comparing consecutively performed robotic-assisted and laparoscopic surgeries for rectal cancer between 1 January 2016 and 31 September 2021. In total, 125 adult patients with sporadic rectal adenocarcinoma (distal extent ≤ 15 cm from the anal verge) underwent surgery where 66 were operated on robotically and 59 laparoscopically. Results: Severe postoperative complications occurred less frequently with robotic-assisted compared with laparoscopic surgery, as indicated by Clavien–Dindo classification grades 3b–5 (13.6% vs. 30.5%, p = 0.029). Multiple logistic regression analyses after backward selection revealed that robotic-assisted surgery was associated with a lower rate of total (Clavien–Dindo grades 1–5) (OR = 0.355; 95% CI 0.156–0.808; p = 0.014) and severe postoperative complications (Clavien–Dindo grades 3b–5) (OR = 0.243; 95% CI 0.088–0.643; p = 0.005). Total inpatient costs (median EUR 17.663 [IQR EUR 10.151] vs. median EUR 14.089 [IQR EUR 12.629]; p = 0.018) and surgery costs (median EUR 10.156 [IQR EUR 3.551] vs. median EUR 7.468 [IQR EUR 4.074]; p < 0.0001) were higher for robotic-assisted surgery, resulting in reduced total inpatient profits (median EUR −3.196 [IQR EUR 9.101] vs. median EUR 232 [IQR EUR 6.304]; p = 0.004). Conclusions: In our study, robotic-assisted surgery for rectal cancer resulted in less severe and fewer total postoperative complications. Still, it was associated with higher surgery and inpatient costs. With increasing experience, the operative time may be reduced, and the postoperative recovery may be further accelerated, leading to reduced surgery and total inpatient costs. [ABSTRACT FROM AUTHOR]

Industrial technological progress, as an essential industrial-technological and institutional phenomenon, brings with it the possibility of high profits for firms but also implies new norms and rules of competition, which affect the willingness and propensity of firms to bear the costs of undertaking venture capital projects. This study empirically investigates the causal impact of industrial-technological progress on corporate risk-taking and the mechanism of digital financial growth on the relationship between the two, based on data from China's A-share listed businesses from 2011 to 2020. This paper finds that (1) industrial technological progress improves enterprise risk-taking levels. Moreover, digital financial development has an incentive effect on industrial technological progress and enterprise risk-taking levels. (2) Industrial technological progress under digital financial development generates financing constraint relaxation effects, input capital return enhancement effects, and innovation performance incentive effects, increasing enterprise risk-taking. (3) The positive moderating effect of digital financial development on the relationship between industrial technological progress and the risk-taking level of enterprises in the eastern regions and enterprises in the high-tech industry is more prominent. The study's findings provide a theoretical foundation and policy insights on the crucial elements of industrial-technological progress and enterprises' increased ability to take risks throughout the development of digital finance. [ABSTRACT FROM AUTHOR]

In this study, we explored the dynamic field of fuzzy logic and artificial intelligence (AI) in financial analysis from 1990 to 2023. Utilizing the bibliometrix package in RStudio and data from the Web of Science, we focused on identifying mathematical models and the evolving role of fuzzy information granulation in this domain. The research addresses the urgent need to understand the development and impact of fuzzy logic and AI within the broader scope of evolving technological and analytical methodologies, particularly concentrating on their application in financial and banking contexts. The bibliometric analysis involved an extensive review of the literature published during this period. We examined key metrics such as the annual growth rate, international collaboration, and average citations per document, which highlighted the field's expansion and collaborative nature. The results revealed a significant annual growth rate of 19.54%, international collaboration of 21.16%, and an average citation per document of 25.52. Major journals such as IEEE Transactions on Fuzzy Systems, Fuzzy Sets and Systems, the Journal of Intelligent & Fuzzy Systems, and Information Sciences emerged as significant contributors, aligning with Bradford's Law's Zone 1. Notably, post-2020, IEEE Transactions on Fuzzy Systems showed a substantial increase in publications. A significant finding was the high citation rate of seminal research on fuzzy information granulation, emphasizing its mathematical importance and practical relevance in financial analysis. Keywords like "design", "model", "algorithm", "optimization", "stabilization", and terms such as "fuzzy logic controller", "adaptive fuzzy controller", and "fuzzy logic approach" were prevalent. The Countries' Collaboration World Map indicated a strong pattern of global interconnections, suggesting a robust framework of international collaboration. Our study highlights the escalating influence of fuzzy logic and AI in financial analysis, marked by a growth in research outputs and global collaborations. It underscores the crucial role of fuzzy information granulation as a mathematical model and sets the stage for further investigation into how fuzzy logic and AI-driven models are transforming financial and banking analysis practices worldwide. [ABSTRACT FROM AUTHOR]

This study explored the multi-layered nature of the work–life experiences of dual income parents in the Philippines by attuning to the voices within their narratives. The border theory was utilized as a framework in understanding these experiences. Semi-structured interviews were conducted among twelve individuals in dual income relationships. All participants had at least one child. The Listening Guide was used to analyze the qualitative data. Four stories emerged from the analysis: stories of financial struggle and security, stories of childcare, stories of connection, and stories of self-denial and self-care. Various voices within these stories were identified and discussed. Findings highlight the importance of balance and social support for dual income couples, as well as the relevance of socio-cultural nuances that impact work–life experiences. Practical implications, particularly how organizations can support their employees in dual income relationships, are discussed. [ABSTRACT FROM AUTHOR]

This work investigates the SMEs of the Italian automotive supply chain, testing the impact of an innovation policy created with the target of supporting investments in Industry 4.0. In detail, the authors examine the impact of this policy on SMEs' access to the capital market (i) and their financial performance (ii). The former is an appropriate proxy to measure the effectiveness of such policy; while the latter is a good candidate to evaluate the sustainability of this program after its conclusion. According to our results, SMEs with access to the incentives of this innovation policy are those observations with higher rates of admission to external financial resources (i.e., 0.3 higher debt ratio) and higher financial performance (i.e., 2 times the odds of having a positive profit, and 0.01 higher financial indexes). Hence, evidence suggests a positive evaluation of this public intervention, as well as positive expectations on its sustainability. In view of these insights, several policy implications are formulated to lead governments into the fourth industrial revolution. [ABSTRACT FROM AUTHOR]

This study aims to analyze the financial performance of the National Amil Zakat Agency of Lumajang Regency in 2018 to 2022. In analyzing financial performance in this study using activity ratios, efficiency ratios, amil fund ratios, liquidity ratios, and growth ratios in accordance with guidelines issued by the National Amil Zakat Agency's strategic study center. This research uses a qualitative descriptive approach. The types and sources of data used are secondary data in the form of financial reports of BAZNAS Lumajang Regency in 2018 - 2022 with data collection methods, namely documentation. The results showed that the average activity ratio of BAZNAS Lumajang Regency was effective, and showed good results in terms of collecting and distributing Zakat, Infaq, Sadaqah (ZIS) funds. Based on the average efficiency ratio, it shows efficient results even though the ratio of operational costs to total amil rights is still inefficient. Based on the ratio of amil funds good results were obtained. Based on the average results of the liquidity ratio is not good because it indicates the obligation to distribute ZIS funds that have not been realized. Based on the ratio of collection growth the results obtained also show not good. [ABSTRACT FROM AUTHOR]

Our article offers insights on the role of operational research (OR) in understanding financial and economic systems' risks and dynamics. It presents the latest methods in OR to address risks and uncertainties in these systems, covering topics such as options pricing, portfolio optimization, banking resilience, and the analysis of financial and economic co-movements. The included studies utilize advanced analytical tools, like stochastic programming, decision analysis, and machine learning, to create robust models for complex systems. These contributions aim to be valuable for academics, practitioners, policymakers, and regulators in the field. [ABSTRACT FROM AUTHOR]

Multi-criteria decision analysis (MCDA) applications consist of techniques that enable the decision maker to make clearer decisions in scenarios where there is more than one alternative and criterion. The general approach for sensitivity analysis in MCDA applications implies sensitivity to the weight coefficient. In this study, as an alternative approach, we reinterpret sensitivity by using the statistical relationship between the final ranking produced by an MCDA method and a constant external factor. Thus, we both verify through an anchor and reveal to what extent the change in the weight coefficient changes the external relations of MCDA. The motivation for this study is to propose an alternative sensitivity methodology. On the other hand, brand value is a parameter that contains critical information about the future of the company, which has not integrated into financial performance studies made with MCDAs before. To that end, the financial performance of 31 companies with the highest brand value in Turkey and trading on Borsa Istanbul between 2013 and 2022 was analyzed with seven different MCDA applications via integrating brand value into the criteria for the first time. The study's findings revealed that the proposed innovative sensitivity tests produced similarly robust results as traditional tests. In addition, brand value has been proved to be an advantageous criterion to be implemented into MCDAs for financial performance problems through the sensitivity analysis made. [ABSTRACT FROM AUTHOR]

Shutdowns of photovoltaic installations are a problem that has been increasingly affecting private investors who have built home installations of several to a dozen kWp over the last few years. This problem, most often caused by outdated infrastructure, appears in many countries and impacts energy production. This work focuses on three aspects of the problem. The first one answers the question of how shutdowns of the photovoltaic installation affect production, and how significant the energy loss happens when the PV inverter is not working or is in the restart phase. The second aspect proposes an original, low-cost method that reduces the number of shutdowns. This method relates to the auto-consumption mechanism associated with domestic water heaters and the system for measuring voltage and energy consumption from the electrical network. The solution is based on constant monitoring of the network voltage and the switching of heaters based on a dedicated algorithm. Additionally, continuous analysis also allows for reporting observed irregularities to the electricity supplier. The third and final factor corresponds to the real impact of shutdowns on the long-term aspect of the investment and the extension of its payback period, and to what extent the proposed solution shortens this period. Through a detailed analysis on the issue of shutdowns, the proposed solution allows for a reduction in the number of shutdowns by over 40%. However, due to the fact that it discusses a specific case, this solution requires a calibration and adjustment process, which is discussed in the article. [ABSTRACT FROM AUTHOR]

The establishment of green finance reform and innovation (GFRI) pilot zone is an important measure of the Chinese government to urge enterprises to develop green transformation. This paper explores the impact of pilot policies in the GFRI pilot zone on corporate environmental investment. Based on 819 A-share listed enterprises from 2010 to 2020, our staggered difference-in-differences (staggered DID) estimation documents revealed that enterprises in the GFRI pilot zone significantly increased the corporate environmental investment efficiency but reduced the scale of corporate environmental investment.This conclusion remained robust after Propensity Scores Matching difference-in-differences (PSM-DID), replacing dependent variables, and shortening the time window. We contend that the increased research and development (R&D) expenditure and technological innovation are the potential mechanisms at work. Heterogeneity analysis showed that the establishment of GFRI improved the environmental investment efficiency of polluting enterprises but had no effect on green enterprises.Meanwhile, the effect of GFRI exhibited heterogeneity in the type of enterprise ownership. This paper evaluates the implementation effect of GFRI from the perspective of corporate environmental investment, and provides theoretical support and an empirical basis for green finance policy to serve China's green economy. [ABSTRACT FROM AUTHOR]

In this study, a three-parameter modification of the Burr XII distribution has been developed through the integration of the weighted version of the alpha power transformation family of distributions. This newly introduced model, termed the modified alpha power-transformed Burr XII distribution, exhibits the unique ability to effectively model decreasing, right-skewed, or unimodal densities. The paper systematically elucidates various statistical properties of the proposed distribution. The estimation of parameters was obtained using maximum likelihood estimation. The estimator has been evaluated for consistency through simulation studies. To gauge the practical applicability of the proposed distribution, two distinct datasets have been employed. Comparative analyses involving six alternative distributions unequivocally demonstrate that the modified alpha power-transformed Burr XII distribution provides a better fit. Additionally, a noteworthy extension is introduced in the form of a location-scale regression model known as the log-modified alpha power-transformed Burr XII model. This model is subsequently applied to a dataset related to stock market liquidity. The findings underscore the enhanced fitting capabilities of the proposed model in comparison to existing distributions, providing valuable insights for applications in financial modelling and analysis. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has brought a series of challenges to various economic sectors around the world, directly affecting the insurance industry. In this sense, the purpose of this article is to address the financial response of insurance companies HDI, Liberty and Mapfre during the pandemic, focusing on the period from 2020 to 2022, through an analysis of the financial statements. In light of what has been mentioned, the general objective of this article is to carry out a comprehensive assessment of the financial impacts generated by the pandemic, focusing specifically on insurance companies, as well as understanding how they adapted to the challenges imposed. This assessment will be conducted through detailed analyzes of the financial statements, with an emphasis on key indicators of liquidity, debt and profitability. The research method adopted is based on the investigation and collection of data available on the insurers' institutional websites. The relevance of understanding how this sector, which plays a crucial role in managing risks for society, responded to the crisis. As a theoretical reference, Insurance in Brazil and Analysis of Financial Statements will be addressed. The research is characterized as applied, with qualitative and quantitative approach methods, a predominant descriptive objective and data collection as a technical procedure. Based on the research carried out, it was identified that insurance companies adopted specific approaches and different responses in the face of the scenario imposed by the pandemic. [ABSTRACT FROM AUTHOR]

This article explores how the relationship between crime and property values is reshaped by the transformation of houses into investible assets. Departing from neoclassical economics of crime, we introduce the notion of "capitalization of crime" to illustrate how crime is utilized to generate forward-looking financial expectations and shape housing markets in gentrifying neighborhoods. The study, based in Haifa, Israel, combines quantitative and qualitative data to demonstrate how investors and renters each play a role in constructing the value of crime by capitalizing crime in opposite directions. First, using a geographic information system to map crime alongside real-estate prices, we show that the effect of crime on property values is offset by prospects of future gentrification, thereby contributing to housing speculation. Second, using digital ethnography, we show how renters use "crime" to dampen investor expectations, reduce rents, and delay their displacement. Thus, our study adds to the established body of critical criminology, which examines the manipulation of crime for economic and political gains. It further contributes to emergent debates in urban criminology by explicating how the financialization of rental housing is remaking urban politics of crime and criminalization. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of financial risks, financial innovation supervision has become an important research issue, and excellent regulatory strategies are of great significance to maintain the stability and sustainable development of financial markets. Thus, this paper intends to analyze the financial regulation strategies through evolutionary game theory. In this paper, the delayed replication dynamic equation and the non-delayed replication dynamic equation are established, respectively, under different reward and punishment mechanisms, and their stability conditions and evolutionary stability strategies are investigated. The analysis finds that under the static mechanism, the internal equilibrium is unstable, and the delay does not affect the stability of the system, while in the dynamic mechanism, when the delay is less than a critical value, the two sides of the game have an evolutionary stable strategy, otherwise it is unstable, and Hopf bifurcation occurs at threshold. Finally, some numerical simulation examples are provided, and the numerical results show the correctness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Objective: To determine the most financially optimal surgical approach for testicular sperm retrieval for men with non‐obstructive azoospermia. Design: A decision tree was created examining five potential surgical approaches for men with non‐obstructive azoospermia pursuing one cycle of intracytoplasmic sperm injection. An expected financial net loss was determined for each surgical option based on couples' willingness to pay for one cycle of intracytoplasmic sperm injection resulting in pregnancy. The branch with the lowest expected net loss was defined as the most optimal financial decision (minimizing loss to a couple). Fresh testicular sperm extraction implied testicular sperm extraction was performed in conjunction with programmed ovulation induction. Frozen testicular sperm extraction implied testicular sperm extraction was performed initially, and ovulation induction/intracytoplasmic sperm injection was canceled if sperm retrieval failed. The surgical options included fresh conventional testicular sperm extraction, with and without "back‐up" sperm cryopreservation, fresh microsurgical testicular sperm extraction, with and without "back‐up" sperm cryopreservation, and frozen microsurgical testicular sperm extraction. Success was defined as pregnancy after one intracytoplasmic sperm injection cycle. Materials and methods: Probabilities of successful sperm retrieval with conventional testicular sperm extraction/microsurgical testicular sperm extraction, post‐thaw sperm cellular loss following frozen microsurgical testicular sperm extraction, ovulation induction/intracytoplasmic sperm injection cycle out‐of‐pocket costs, intracytoplasmic sperm injection pregnancy rates for men with non‐obstructive azoospermia, standard conventional testicular sperm extraction cost and average willingness to pay for intracytoplasmic sperm injection cycle were gathered from the systematic literature review. Costs were in USD and adjusted to inflation (as of April 2020). Two‐way sensitivity analysis was performed on varying couples' willingness to pay for one cycle of intracytoplasmic sperm injection and varying microsurgical testicular sperm extraction out‐of‐pocket costs. Results: According to our decision tree analysis (assuming minimum microsurgical testicular sperm extraction cost of $1,000 and willingness to pay of $8,000), the expected net loss for each branch was as follows: ‐$17,545 for fresh conventional testicular sperm extraction, ‐$17,523 for fresh microsurgical testicular sperm extraction, ‐$9,624 for frozen microsurgical testicular sperm extraction, ‐$17,991 for fresh conventional testicular sperm extraction with "backup", and ‐$18,210 for fresh microsurgical testicular sperm extraction with "backup". Two‐way sensitivity analysis with a variable willingness to pay values and microsurgical testicular sperm extraction and in‐vitro fertilization costs confirmed that frozen microsurgical testicular sperm extraction consistently presented the lowest net loss compared to other options. Interestingly, when directly comparing fresh microsurgical testicular sperm extraction and conventional testicular sperm extraction with "back‐up", scenarios with decreasing willingness to pay and lower microsurgical testicular sperm extraction costs demonstrated fresh conventional testicular sperm extraction with "back‐up" as more optimal than fresh microsurgical testicular sperm extraction with "back‐up". Conclusions: For those couples who must pay out of pocket, our study suggests that frozen microsurgical testicular sperm extraction is the most financially optimal decision for the surgical management of non‐obstructive azoospermia, regardless of microsurgical testicular sperm extraction cost and the couple's willingness to pay. [ABSTRACT FROM AUTHOR]

This study examines whether case-based learning (CBL) in a core finance class improves student performance. It analyzes students’ exam scores over two semesters at a regional U.S. public university. During the first semester, CBL is used to teach two sections of an intermediate corporate finance class. During the subsequent semester, the first half of the semester is taught using CBL while the second half of the semester is taught using problem- based learning (PBL). The difference-in-differences analysis shows that the advantage of CBL over PBL approach is noticeable. Additionally, the analysis of students’ grade distributions appears to show that the CBL approach lifts students at both the top and bottom strata. [ABSTRACT FROM AUTHOR]

Objective: Relatively few dyad‐based studies have evaluated the shared psychosocial and financial toxicity (FT) experiences of hematologic patients and their caregivers, especially those undergoing bone marrow transplantations (BMTs). This study evaluated the association of FT with health‐related quality of life (QOL) among BMT patient‐caregiver dyads. Methods: Survey and electronic health record data were collected between April 2021 and January 2022 from BMT patients and their caregivers pre‐ (T1) and post‐intervention (T2). Thirty‐four patient‐caregiver dyads completed surveys; all dyads included a patient experiencing elevated T1 FT. The effect of the total FT score (i.e., the combination of psychological response, coping behaviors, and material conditions domain scores) on physical health, mental health, anxiety, depression and distress scores was evaluated using Actor‐Partner Interdependence Modeling (APIM). Results: Patients and caregivers who reported lower total FT scores had better physical and mental health, and lower anxiety, depressive symptoms, distress (APIM actor effects). None of the partner effects were significant in the APIM models. Other model findings indicated that compared with caregivers, patients had lower reported physical health; mental health scores were higher, on average, for all participants at the T2 compared with T1; and members of dyads whose caregiver took time off work reported better physical health and lower depressive symptoms and distress than those whose caregiver did not. Conclusions: Our study addresses a significant gap in dyad‐based cancer FT studies; the findings underscore the need for additional research to help develop tailored dyad‐level FT interventions for improving health‐related QOL among BMT patients. [ABSTRACT FROM AUTHOR]

Installation of hybrid systems with storage is a way to maximize the amount of energy generated through exploring the complementarity of different sources. Understanding hybrid power plant (HPP) operation is crucial for optimizing new systems and reconfiguring existing plants, to their enhance efficiency. Alongside technical aspects, economic feasibility is also a fundamental feature. This study simulated an off-grid HPP to consider the energy consumption of Casa Nova in Bahia, Brazil. The methodology consisted of the selection of energy sources, choosing a reference location, acquisition of generation and operational data, modeling and simulating the system in different scenarios, and a financial analysis. HOMER Pro software Version 3.16.2 was used to optimize the plant configuration, and the outputs were evaluated using the perspectives of levelized cost of energy (LCOE), simple payback, and power load fulfillment. As a result, scenario 3 was the most competitive, emphasizing that the use of different energy sources increased the system generation capacity. However, the addition of battery energy system storage (BESS) resulted in a high LCOE when compared to individual sources, which demonstrated that the cost of battery integration is not yet nationally competitive. Moreover, the results highlighted the importance of research investments, energy governance, and regulation in promoting hybrid system adoption. [ABSTRACT FROM AUTHOR]

There is an increasing push among development actors to engage men in gender-focused development efforts. This is also observed in initiatives organizing economically poor individuals into groups where members save and borrow among each other. This study investigates the influence of male membership on the savings group's profit-generating capacity. Further, the study aims to understand if this relationship is moderated by the level of gender equality in the country where the group is located. Drawing on random effects regression analysis on a sample of data on 81,853 savings groups from 30 African countries covering the period 2010 to 2017, the results show that the group's profit-generating capacity reduces as the percentage of male members increases. Further, gender inequality in the countries where these groups are located worsens the observed negative relation. The findings highlight the need to thoroughly evaluate policy initiatives aimed at such savings groups to avoid harming core group functions. [ABSTRACT FROM AUTHOR]

Irrigation plays a vital role in sustaining agricultural production during periods of low rainfall. While ensuring increased productivity and economic profitability, irrigation is associated with high electrical energy consumption. In 2018, Brazilian Decree 9642 eliminated discounts for rural consumers, established in 2013. Leveraging renewable energy sources for irrigation can mitigate nonrenewable energy dependence and reduce the electricity costs for irrigators. This study aimed to nationally compare the economic viability of on-grid photovoltaic systems as an alternative to conventional grid energy for agricultural irrigation, both pre- and post-Brazilian Decree 9642. We conducted a comprehensive life cycle cost (LCC) analysis for both systems before and after discount termination, facilitating more informed economic decisions. The LCC of the conventional grid energy increased by over 40% after the Decree, whereas the photovoltaic system saw a modest increase of 12%. The solar system's 28% cost advantage over the conventional grid post-Decree underscores its resilience to regulatory changes. The photovoltaic system demonstrated viability when its LCC was equal to or lower than the comparator system's LCC. Notably, the economic viability of the photovoltaic system extended across all geographic regions for the grid-connected system. This study highlights the competitive pricing, versatility, and economic impact of photovoltaic systems in the context of changes in Brazilian tariff legislation. [ABSTRACT FROM AUTHOR]

The financial mathematical model, comprised of multiple elements, represents a complex non-linear system. Within this non-linear system, deterministic instability during operation gives rise to financial chaos phenomena such as turbulent fluctuations in the financial market and financial crises. Economic growth and social stability have been profoundly negatively affected by these events. To suppress or eliminate the disorderly condition in the fractional-order nonlinear system, and effectively stabilize and control the chaotic cyclic or erratic recurring state in the chaotic attractor, a novel sliding mode controller has been proposed in this research article. This controller aims to modify the behavior of the original economic system and achieve a new spatiotemporal order structure. By utilizing this controller, it is possible to facilitate the evolution process of the financial system from a chaotic to a regular state. Firstly, the dynamic characteristics of the fractional financial system are examined, followed by the determination of the theoretical order and coefficient range of the system. Next, a novel sliding mode control method is introduced, whose stability is examined. Finally, a numerical simulation is carried out to evaluate the effectiveness of the proposed controller. The consequences of the experiment demonstrate that the controller holds practical significance in the macro-control of financial crises. [ABSTRACT FROM AUTHOR]

With China's economic rise and influence, financial statecraft has increasingly been deployed to serve the country's national interest. The growth of China's financial statecraft in the region has drawn greater media and academic attention. Notwithstanding the abundant literature on China's financial statecraft in Southeast Asia, the previous studies lack a detailed analysis of various financial statecraft instruments deployed by China. To get a better understanding of China's deployment of financial statecraft over the years under Xi Jinping's administration, this article fills the gap in the existing literature by delving into various factors that influenced various financial statecraft instruments with respect to the objectives, trends or patterns and agencies involved in the region. Given Xi's successful bid for continued political rule by eliminating a term limit on the presidency as well as the escalating China-US strategic rivalry, it is important to examine how the interaction of domestic and international forces has shaped the evolution of financial statecraft in Southeast Asia. Due to the changes in domestic politics and shifts in the geopolitics and geoeconomics, an important question that deserves our attention is how these changes has influenced China's deployment of various financial statecraft instruments in different Southeast Asian countries. The paper focuses on two middle-income countries (i.e., Malaysia and Thailand) and two low-income countries (i.e. Cambodia and Laos) in the region. [ABSTRACT FROM AUTHOR]

Most students of corporation finance dream of a time when corporate administration will be held to a high degree of required responsibility- a responsibility conceived not merely in terms of stockholders' rights, but in terms of economic government satisfying the respective needs of investors, workers, customers, and the aggregated community. [ABSTRACT FROM AUTHOR]

Financial statement analysis is a critical component of decision-making for businesses, investors, and financial professionals. To enhance the accuracy and effectiveness of such analysis, this paper introduces the application of an innovative approach known as the Intelligent Swarm Regression ARIMA Model. This advanced model combines the power of swarm intelligence with ARIMA (AutoRegressive Integrated Moving Average) time series forecasting, offering a robust methodology for predicting and analyzing key financial metrics. The study begins by providing an overview of the Intelligent Swarm Regression ARIMA model and its application to financial data. Through a comprehensive analysis of financial statements, including market capitalization, revenue, net income, and other crucial indicators, the model's efficacy in predicting future values is evaluated. Additionally, the paper examines the deviations between predicted and actual financial values, offering insights into the model's accuracy and areas for potential improvement. The findings of this research are invaluable for investors, financial analysts, and companies seeking to optimize their financial performance and strategic decision-making. By leveraging the Intelligent Swarm Regression ARIMA Model, stakeholders can make well-informed choices that lead to better financial outcomes and a competitive advantage in a dynamic economic landscape. This paper represents a significant step forward in the financial analysis, providing a practical methodology and a pathway to enhanced financial decision-making. As the importance of financial data continues to grow, this research offers a promising avenue for achieving financial success and stability. [ABSTRACT FROM AUTHOR]

The financial implications of long-term restoration projects for cultural heritage, as compared to regular maintenance efforts, often underscore a flawed decision-making process. This can result from years of neglect versus consistent, organized maintenance. Striking a balance between these strategies is paramount for preserving cultural legacies. This research aims to evaluate the trade-offs between the initial expenditures of restoration initiatives and the consistent costs of maintenance activities. We leverage Building Information Modelling (BIM) and its specialized application for heritage preservation, known as Heritage Building Information Modelling (HBIM). This offers a digital depiction of the heritage building's conservation state and associated intervention costs. Specifically, this study taps into the fifth dimension of BIM, cost estimation, to draw a comparative analysis between the financial ramifications of regular maintenance and long-term restoration projects. This assessment is exemplified through a case study on the "Aidkeen Al-Bendqdari Dome" located in historic Cairo, Egypt—a component of the Prince Taz Palace. The analysis integrates cost data to generate insights. The ultimate goal is to devise a comparative framework that can guide authorities in budgetary decisions and resource distribution. [ABSTRACT FROM AUTHOR]

This study examines the phenomenon of pseudo-decentralization and financial dependence in the context of regional autonomy implementation in Sumedang Regency, Indonesia. Using a case study approach and analyzing financial data from 2019-2022, this research investigates the extent to which Sumedang Regency relies on central and provincial governments for financial resources. The findings reveal a high level of financial dependence due to limited income sources provided by the central government to regions like Sumedang. Despite this dependency, Sumedang Regency has successfully executed development programs and received awards, partly due to effective political lobbying by regional leaders. However, this reliance on local elites may hinder the achievement of decentralization objectives and lead to unequal development outcomes. As a recommendation, the central government is urged to focus on implementing fiscal policies that distribute more lucrative and equitable financial resources to all regencies and cities, promoting genuine decentralization and fair development. [ABSTRACT FROM AUTHOR]

This study bridges finance and physics by applying thermodynamic concepts to model the limit order book (LOB) with high-frequency trading data on the Bitcoin spot. We derive the measures of Market Temperature and Market Entropy from the kinetic and potential energies in the LOB to provide a deeper understanding of order activities and market participant behavior. Market Temperature emerges as a robust indicator of market liquidity, correlating with liquidity measures such as Active Quote Volume, bid–ask spread and match volume. Market Entropy, on the other hand, quantifies the degree of disorder or randomness in the LOB, providing insights into the instantaneous volatility of price in the high-frequency trading market. Our empirical findings not only broaden the theoretical framework of econophysics but also enhance comprehensive understanding of the market microstructure and order book dynamics. [ABSTRACT FROM AUTHOR]

Purpose: Existing theories on the determining factors of corporate investment decisions raise the importance of financial market imperfections in explaining investment behavior. Many factors have been proposed as drivers of investment, mainly in developed economies, while emerging countries have almost been neglected. The main purpose of this study is to examine the effect of financing constraints on the investment behavior of a small context, namely, Jordan, with an imperfect environment. Design/methodology/approach: This study considers panel data regressions from the industrial companies traded at the Amman Stock Exchange with a total of 1,058 firm-year observations. Findings: The results are able to demonstrate that business size, tangibility, market-to-book ratio, profitability, financial slack and leverage are major drivers of investment choices. The results support the importance of information asymmetry in explaining the investment behavior of firms. Nonetheless, the Q-theory is in place, as is firm agility. Practical implications: Policies to reduce information asymmetry are immediately needed to help firms increase investments by providing them with access to training, technology and market information. They also should enhance the firms' opportunities for growth. Moreover, they should make it easier for businesses to access financial slack, such as by improving access to credit and financial institutions. They also can work to improve the financial infrastructure to meet the financing needs of businesses. Finally, smaller businesses should be assisted by improving their ability to invest and grow. Originality/value: To the best of the authors' knowledge, this is one of the first studies, if any, to investigate this issue in a distinct environment. Despite the unique characteristics of Jordan, the findings are applicable to other countries that experience comparable political and economic circumstances because Jordan has traits common to many emerging nations. [ABSTRACT FROM AUTHOR]