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IT is recognized as the engine of the digital world. The fact that this technology has multiple sub-sectors makes it the driving force of the economy. With these characteristics, the sector is becoming the center of attention of investors. Considering that investors prioritize profitability, it becomes a top priority for managers to make accurate and reliable profitability forecasts. The aim of this study is to estimate the profitability of IT sector firms traded in Borsa Istanbul using machine learning methods. In this study, the financial data of 13 technology firms listed in the Borsa Istanbul Technology index and operating between March 2000 and December 2023 were used. Return on assets (ROA) and return on equity (ROE) were estimated using machine learning methods such as neural networks, multiple linear regression and decision tree regression. The results obtained reveal that the performance of artificial neural networks (ANN) and multiple linear regression (MLR) are particularly effective. [ABSTRACT FROM AUTHOR]

The study investigates the efficacy of an enzymatic preparation primarily with α-galactosidase activity for improving the quality of white sugar from poor-quality sugar beets. Focused on overcoming raffinose accumulation challenges in sugar beets, especially those harvested prematurely or stored for extended periods, an innovative exploration of enzymatic application in an industrial setting for the first time was conducted. By integrating theoretical calculations and experimental data, the findings reveal that α-galactosidase preparation notably diminishes raffinose content in beet juice, thus enhancing the sucrose yield and overall sugar quality. A reliable method to process lower-quality beets, promising enhanced efficiency in sugar production, was presented. The study also highlights the economic benefits of incorporating enzyme preparation into the production process, demonstrating a notable return on investment and underscoring the potential of enzymatic treatments to address industry challenges. [ABSTRACT FROM AUTHOR]

This study assessed the accounting-based variables and value-based management (VBM) variables that jointly affect firm value and performance. The study applied the causality test and variance decomposition to determine the variability of the variables, and further empirically employed fully modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) techniques to justify the results. Data covering 356 industries were purposively sampled to arrive at 61 companies spanning 2011–2020. Overall, the causality test found no relationship between economic value added and market value added but only found unidirectional causality from shareholder returns to MVA, EVA to shareholder returns, ROA to MVA, ROE to MVA, EVA to MVA, MVA to EVA, ROE to ROA, EVA to ROA, and EVA to ROE. A very strong bidirectional causality relationship was found between return on asset and shareholder return as a measure of company performance. Further results from the forecast error of the variance decomposition showed that shareholder returns are explained only by its own shock, contributing 45.38 percent in the long run, while the remaining variables, namely market value added, return on asset, return on equity, and economic value added, contribute about 35.96%, 14.06%, 4.08%, and 0.51%, respectively, to predicting the future values of shareholder return. This confirms the relationships between the variables from the short run to the long run. Additionally, results from the FMOL and DOL revealed that all accounting variables and VBM are good approaches for evaluating company performance as the empirical result from ROA, ROE, and EVA revealed positive and significant relationships. This confirms that a combination of both variables would produce a better evaluation as the accounting variables and VBM variables jointly relate to shareholder returns. This study serves as a guide to companies' management and boards of directors in having better ways to evaluate company performance. Consequently, it is recommended that managers select combinations of accounting and VBM variables that suit their operations and jointly apply them in the performance evaluation of the company. This will be useful in providing both the relative and incremental performance information needed for diverse decision-making. [ABSTRACT FROM AUTHOR]

Climate change impacts will continue to worsen with rising greenhouse gas (GHG) emissions, underscoring the growing necessity to foresee and comprehend the impact of climate change risks on economic activity. Using quarterly firm-level data of 209 firms from the People's Republic of China (PRC) over the period Q1 2018–Q2 2022, this study estimates the impact of firms' exposure to climate-related risks on their financial performance. The results indicate a notable adverse effect of climate change exposure on firms' rate of return, with a lag of around two years. Firms located in more climate-vulnerable coastal areas and high-income provinces experience relatively greater negative impacts on their financial returns. Our findings have important policy implications for firms aiming to maximize their returns through enhanced climate change mitigation and adaptation efforts. [ABSTRACT FROM AUTHOR]

This research aims to analyse the financial performance of companies using one of the most used profitability indicators, the return on investment (ROI), which measures the company's performance in terms of the profit generated over time. To this end, several different methods are used to calculate the ROI indicator, considering the different calculation methods used by different authors over the years. The use of different ROI calculation formulas has been identified in the literature, leading to different conclusions. Based on a sample of 2805 Portuguese companies, it examines how the different indicators react to the different variables analysed, using nine different econometric models. Through this study, it is possible to verify that the different variables that depend on the return on investment have different results, namely that the variables "age" and "size" have a negative effect on the return on investment. On the other hand, "financial leverage" and "ROA" have a positive impact on the contribution to the return on investment. We also found that the different variables behave similarly for virtually all types of ROI calculation, although not completely harmonious, especially in terms of impact. The results are empirically vital, as they alert researchers and companies to the need for standardised formulas for calculating variables such as ROI so that results are not distorted. Using one to the detriment of the other impacts the results obtained and the analyses to be carried out. How empirical research will continue to use the ROI metric will always depend on its users' discretion and free will. [ABSTRACT FROM AUTHOR]

In the context of implementing the new agricultural strategy, "Generation Green 2020–2030", Moroccan agricultural SMEs are benefiting from specific lines of credit and significant financial incentives. This study focuses on assessing how the capital structure influences the financial performance of these medium-sized enterprises, based on an analysis of a sample of 30 agricultural SMEs over a period of 4 years from 2019 to 2022. This examination delves into the effects of debt, government subsidies, and their combined impact on the return on equity and assets of these SMEs. The findings reveal a significant negative correlation between capital structure and the financial performance of agricultural SMEs. This underscores the importance of advocating for self-financing in line with the pecking order theory, as debt appears to significantly diminish asset returns. Additionally, although government subsidies alone do not significantly influence enterprise profitability, their interplay with capital structure—especially long-term debt—exhibits a detrimental moderating effect on asset returns. This suggests that subsidies play a significant role in moderating the relationship between capital structure and SME financial performance, albeit with an adverse effect. [ABSTRACT FROM AUTHOR]

Citizen-driven approaches are promising to overcome the challenges in the energy transition of geographical islands. However, the economic profitability of related activities must be ensured to achieve the intrinsic and sustainable uptake of related solutions in an island's communities. Here, we investigate the long-term (2020–2054) economic profitability of solar-based prosumption on islands belonging to the European Union (EU), soft-linking energy system modelling and actor-related cash-flow analysis. This combination considerably extends common assessments of the profitability of renewable energy technology and long-term projections of island energy systems. We base our case study on the French overseas territory of Mayotte, discussing household affordability and the socio-economic impact of prosumerism. These topics are relevant to transferability on non-EU islands. The profitability of investments in PV depends on (i) the size of the PV system, with larger systems (>9 kWp) profiting from lower specific investment costs compared to smaller systems; (ii) the time of investment, with more profitable investments to be expected in early periods; (iii) the level of decarbonization of the entire energy sector, with an ongoing decarbonization reducing the compensation or energy-saving possibilities; and (iv) the market behavior, with the practice of feeding in all electricity produced rather than self-consuming energy offering a higher expected return on investment under current feed-in-tariff (FiT) compensation schemes. We introduce various policy measures to improve solar rooftop PV profitability and discuss their trade-offs and effectiveness. While indirect subsidies via FiT are generally effective in improving PV profitability, they undermine efforts to incentivize decentralized self-consumption. From the perspective of harmonizing efforts in the energy transition of African and European islands, we recommend a careful evaluation of the trade-offs in relevant regulations required for the economic incentivization of prosumers to achieve compatibility with the principles of a citizen-driven and just energy transition. Particular attention must be paid to context-specific socio-economic characteristics, including low access to financial resources and non-financial access barriers, including legal status. [ABSTRACT FROM AUTHOR]

Background: Patellar tendinopathy (PT) involves anterior knee pain and functional. Platelet-rich fibrin matrix (PRFM) is a promising biological therapy for tendinopathies. We examined a cohort of PT patients treated with tendon debridement and autologous PRFM at the 24-month follow-up to assess whether the combined treatment facilitated return to sports and yielded satisfactory clinical and functional scores. Methods: Baseline and 24-month visual analogue scale (VAS), Victorian Institute of Sport Assessment Scale for Patellar Tendinopathy (VISA-P), Tegner Activity Scale (TAS), and Blazina scores were compared to evaluate treatment effectiveness. The Friedman test was used to compare repeated observations of VAS, VISA-P, TAS, and Blazina Score values. Return to sport rate, Tampa Scale of Kinesiophobia (TKS) score and patient satisfaction were collected at 24 months. Results: The postoperative clinical scores demonstrated significant improvement compared with their preoperative values (all p < 0.001). Specifically, the VISA-P score was 80.32 (±20.58), 92.10% of patients had resumed sports activities and patient satisfaction was 9.21 (±1.21) at 24 months. Conclusions: Surgical debridement and autologous PRFM application in patients with chronic PT resulted in a higher rate of return to sports when compared to solely surgical treatment, significantly improved clinical outcomes and excellent patient satisfaction at 24 months. [ABSTRACT FROM AUTHOR]

The valuation of Goodwill (GW) has remained one of the several critical issues in financial analysis. This aspect is particularly important for mergers and acquisitions due to the significance of intangible assets. This study delves into the capitalization method of super profit (CMSP), a prominent technique for GW valuation, enhanced by the integration of statistical tools. Assessing a company's excess profits over its average return on tangible assets is part of the CMSP. Finding the variables that have a significant impact on GW valuation, such as average profit, capital employed, and rate of return, is the main goal of this research. These issues are thoroughly investigated through statistical analysis to give stakeholders useful information for well-informed decision-making. Additionally, the study seeks to identify the external elements influencing this process as well as the internal aspects influencing GW valuation. Regression analysis, correlation matrices, response analysis and ANOVA are used to improve GW assessment and comprehension of the complex relationships between different factors. [ABSTRACT FROM AUTHOR]

The purpose of this study was to examine the key determinants of corporate governance in selected financial institutions. Using South African financial institutions as a unit of analysis, namely insurance companies and banks, the study employed a panel generalised method of moments (GMM) model using a data set for the period from 2007 to 2020, to assess key determinants of corporate governance proxies identified for the study. The study sampled 21 South African financial institutions composed of Johannesburg Securities Exchange (JSE) listed and unlisted banks and insurance companies. To measure corporate governance, the study developed a composite index employing the principal components analysis (PCA) method. The findings revealed a positive and significant association between the corporate governance index and its lagged variables. Furthermore, a significant and positive link was found between the efficiency ratio and corporate governance index and capital adequacy ratio (CAR); corporate governance index and firm size; corporate governance index and leverage ratio (LEV); and corporate governance index and return on assets (ROA). However, a negative and significant correlation was found between financial stability and the corporate governance index. The link between return on equity (ROE) and corporate governance was insignificant. A small cohort of financial institutions was excluded because it was challenging to obtain complete annual reports to extract the required data. The study was limited to only five corporate governance measures, namely board diversity, board size, board composition (independent non-executive directors and non-executive directors), and board remuneration. The findings are anticipated to persuade developing countries to pay special attention to how corporate governance is measured. [ABSTRACT FROM AUTHOR]

This study presents a hybrid multicriteria decision-making approach for evaluating stocks in the Saudi Stock Market. The objective is to provide investors and stakeholders with a robust evaluation methodology to inform their investment decisions. With a market value of USD 2.89 trillion dollars in September 2022, the Saudi Stock Market is of significant importance for the country's economy. However, navigating the complexities of stock market performance poses investment challenges. This study employs the best–worst method and the technique for order preference by similarity to identify an ideal solution to address these challenges. Utilizing data from the Saudi Stock Market (Tadawul), this study evaluates stock performance based on financial criteria, including return on equity, return on assets, net profit margin, and asset turnover. The findings reveal valuable insights, particularly in the banking sector, which exhibited the highest net profit margin ratios among sectors. The hybrid multicriteria decision-making-based approach enhances investment decisions. This research provides a foundation for future investigations, facilitating a deeper exploration and analysis of additional aspects of the Saudi Stock Market's performance. The developed methodology and findings have implications for investors and stakeholders, aiding their investment decisions and maximizing returns. [ABSTRACT FROM AUTHOR]

This study rigorously investigates the intricate dynamics between Corporate Social Responsibility (CSR), quantified through Environmental, Social, and Governance (ESG) scores, and financial performance (FP), measured via the return on assets (ROA) and return on equity (ROE), within the UK banking sector. Our analysis is based on a comprehensive dataset from Bloomberg. This research encapsulates data from 32 banks publicly listed on the London Stock Exchange over a six-year span from 2017 to 2022. Employing panel data regression models while controlling leverage and bank size, we delve into the relationship between banks' CSR engagements, as reflected in their ESG scores, and their financial outcomes. Our findings indicate a negative correlation between the ESG score and both the ROA and ROE, suggesting that elevated CSR commitments may inversely impact short-term financial returns. This finding not only challenges prevailing narratives within the sector but also fosters a crucial discourse on the balance between ethical banking practices and profitability. The implications of this research study are manifold, extending to policymakers, banking executives, and investors, suggesting a revaluation of CSR strategies in alignment with long-term value creation and sustainable banking. This study not only enriches academic discourse on CSR within the financial sector but also serves as a beacon for future inquiries into the evolving landscape of responsible banking, advocating for a nuanced understanding of CSR's role in shaping the financial and ethical contours of the banking industry. [ABSTRACT FROM AUTHOR]

A random-effects meta-analysis was conducted to investigate the effect of mycotoxins (MT) without or with the inclusion of yeast cell wall extract (YCWE, Mycosorb®, Alltech, Inc., Nicholasville, KY, USA) on laying hen performance. A total of 25 trials were collected from a literature search, and data were extracted from 8 of these that met inclusion criteria, for a total of 12 treatments and 1774 birds. Laying hens fed MT had lower (p < 0.05) body weight (BW) by −50 g, egg production by −6.3 percentage points, and egg weight by −1.95 g than control fed hens (CTRL). Inclusion of YCWE during the mycotoxin challenges (YCWE + MT) resulted in numerically greater (p = 0.441) BW by 12.5 g, while egg production and egg weight were significantly (p < 0.0001) higher by 4.2 percentage points and 1.37 g, respectively. Furthermore, economic assessment calculations indicated that YCWE may not only support hen performance but also resulted in a positive return on investment. In conclusion, mycotoxins can play a role in negatively impacting laying hen performance and profitability. Inclusion of YCWE in feed with mycotoxin challenges provided benefits to egg production and egg weight and may support profitability. As such, the inclusion of YCWE could play an important role in minimizing mycotoxin effects and in turn aid farm efficiency and profitability. [ABSTRACT FROM AUTHOR]

Cloud providers offer various purchasing options to enable users to tailor their costs according to their specific requirements, including on-demand, reserved instances, and spot instances. On-demand and spot instances satisfy short-term workloads, whereas reserved instances fulfill long-term instances. However, there are workloads that fall outside of either long-term or short-term categories. Consequently, there is a notable absence of services specifically tailored for medium-term workloads. On-demand services, while offering flexibility, often come with high costs. Spot instances, though cost-effective, carry the risk of termination. Reserved instances, while stable and less expensive, may have a remaining period that extends beyond the duration of users' tasks. This gap underscores the need for solutions that address the unique requirements and challenges associated with medium-term workloads in the cloud computing landscape. This paper introduces a new cloud broker that introduces IaaS services for medium-term workloads. On one hand, this broker strategically reserves resources from providers, and on the other hand, it interacts with users. Its interaction with users is twofold. It collects users' preferences regarding commitment term for medium-term workloads and then transforms the leased resources based on commitment term, aligning with the requirements of most users. To ensure profitability, the broker sells these services utilizing an auction algorithm. Hence, in this paper, an auction algorithm is introduced and developed, which treats cloud services as virtual assets and integrates the depreciation over time. The findings affirm the lack of services that fulfill medium workloads while ensuring the financial viabilty and profitability of the broker, given that the estimated return on investment (ROI) is acceptable. [ABSTRACT FROM AUTHOR]

Audit committees are appointed by the board of directors of corporations to oversee the financial reporting process, monitor financial control processes, hire and assess independent auditors, and communicate findings with management and auditors. We propose two new measures of audit oversight quality. The first measure is purely subjective, in that it scores audit committees on a scale based on their ability to fulfill one or more of their responsibilities, as mentioned in annual reports, Form 10-K and DEF 13A. The second measure concerns audit committee activity, as it measures the number of times the term 'audit committee' is mentioned in these documents. Both measures were obtained for U.S. pharmaceutical companies and energy companies from 2010 to 2022. The audit oversight quality measures were regressed in regard to profitability (measured by return on assets and return on equity), debt capacity (measured by equity multiplier), and firm value (measured by Tobin's q and economic value added). Audit oversight quality, using both measures, reduces the return on equity. Audit oversight quality, using both measures, had a disciplining effect on debt. Increases in the oversight of increasing debt discourage the propensity to increase borrowing using collateral (debt capacity), and reduce investor returns through investment in debt-financed projects (return on equity). Audit oversight quality, using both measures, exhibited a size effect on the firm's value, in that an increase in the firm size with high audit oversight quality increases the firm's value. However, it is possible that only the first measure of audit oversight quality significantly increased the firm's value, as only the first measure exhibited robustness to the endogeneity effect of size. [ABSTRACT FROM AUTHOR]

This paper identifies the CEO characteristics that have an impact on the performance of family businesses listed in the Euronext in the post-COVID 19 period. CEO characteristics are evaluated on two dimensions, i.e., personal characteristics and corporate governance mechanisms. A sample of 137 firm-year observations from Portugal, Luxembourg, the Netherlands, Ireland, France, and Belgium was chosen. CEO attributes of age, gender, education, and family membership were combined with corporate governance mechanisms of ownership concentration, CEO duality, CEO directorships, and CEO tenure, to predict return on assets and return on equity, using OLS regression. GMM estimation and Two-Stage Least Squares were employed to establish the robustness of the results. Among CEO personal characteristics, CEO family membership has a positive impact on return on assets, and a positive impact on return on equity. Among corporate governance mechanisms, CEO duality had a negative impact on return on assets, and a negative impact on return on equity. CEO ownership, and CEO tenure had a positive impact on return on assets, and a positive impact on return on equity. This paper's value lies in its evaluation of the under-researched area of family businesses of Euronext-listed firms. It can be used by family businesses in the region, for the selection and training of CEOs to fulfill the goal of achieving superior financial performance. [ABSTRACT FROM AUTHOR]

The paper examines the nexus between working capital management (WCM) and financial performance of listed non-financial firms in Ghana. An unbalanced panel data for the period 2008 to 2021 was used for the study. It is observed that the residual terms of the models were cross-sectionally independent and all the series were first-differenced stationary and cointegrated in the long term The elasticities of the predictors were explored via the Fully Modified Ordinary Least Squares (FMOLS) and the Dynamic Ordinary Least Squares (DOLS) techniques. The findings of the study indicate that WCM proxied by accounts receivable period (ACP), accounts payment period (APP), and inventory turnover period (ITP) have significant positive effect on firms' financial performance measured by return on assets (ROA), return on equity (ROE), and return on capital employed (ROCE). This suggests that the working capital management practices of non-financial firms in Ghana improve their financial performance. Also, firm size and asset growth improve firm financial performance. On the causalities between the variables, bidirectional causalities between ACP, APP, ITP, size, and thecompanies' ROA, ROE, and ROCE are disclosed. Finally, causality from growth to the ROA, ROE, and ROCE of the firms are unraveled. It is recommended that policy makers of non-financial firms in Ghana should not overlook WCM practices in their financial decisions, since ignoring them could seriously compromise the firms' short- and long-term sustainability. [ABSTRACT FROM AUTHOR]

Fintech companies are relatively young and operate in a rapidly evolving and ever-changing industry, which makes it important to understand how different factors, including shareholder presence in management roles, affect their performance. This study investigates the impact of shareholder presence in director and manager positions on the financial performance of Latvian fintechs. Our investigation centers on essential financial ratios, including Return on Assets, Return on Equity, Profit Margin, Liquidity Ratio, Current Ratio, and Solvency Ratio. Our findings suggest that the presence of shareholders in director and manager roles does not significantly affect the financial performance of fintech companies. Although the statistical analysis did not yield significant results, it is important to consider additional insights garnered from Cliff's Delta effect sizes. Specifically, despite the lack of statistical significance, practical significance indicates that fintech companies in which directors and managers are shareholders show slightly better performance than other fintech companies. Beyond shedding light on the intricacies of corporate governance in the fintech sector, this research serves as a valuable resource for investors, stakeholders, and fellow researchers seeking to understand the impact of shareholder presence in director and manager roles on the financial performance of fintechs. [ABSTRACT FROM AUTHOR]

This work aimed to examine the effect of corporate cash holdings on financial performance. The data covered 536 non-financial firms for the 2006–2020 period from 11 MENA region countries. This study used fixed- and random-effects testing models. To the best of the authors' knowledge, this is the first study that aimed to study the effect of corporate cash holdings on financial performance in MENA countries in two aspects: linear and non-linear relationships. By using the return on assets, return on equity, earnings before interest, and the tax margin as the indicators of financial performance, we developed two groups of models investigating the linear and non-linear relationships between cash holdings and profitability measures. The models included several control variables, namely leverage, firm size, sales growth rate, tangibility, dividend pay-out ratio, and gross domestic product (GDP) growth rate. The results of this study revealed that both the linear and non-linear models produced significant results for the return on assets and the return on equity, but for the earnings before interest and tax margins, the linear model was insignificant. The non-linear models indicated an optimal level of cash holdings. In this context, the policymakers must actively evaluate these policies, such as working capital management and its effect on financial performance. In addition, the policymakers must consider macroeconomic conditions when designing corporate cash-holding policies. [ABSTRACT FROM AUTHOR]

This paper aims to examine the impact of natural disasters on banking stability across different levels of economic development. Utilizing bank-level data from 1242 banks in 72 countries, combined with natural disaster data from the Center for Research on the Epidemiology of Disasters, we contribute to the literature in three ways. Firstly, we directly assess the influence of natural disasters on banking stability. Secondly, we focus on bank-level data instead of country-level data. Thirdly, we expand on existing research by using different thresholds for the total number of people affected to population ratio, surpassing the previously suggested threshold of 0.5%. Our panel regression analysis with banks and year-fixed effects reveals that natural disasters significantly affect bank stability, particularly in middle- and low-income countries. These effects are robust across alternative measures and estimations, leading to higher non-performing loans, lower return on assets, and decreased capital and return on equity ratios, indicating a negative impact on bank performance. [ABSTRACT FROM AUTHOR]

Continuous-cover forestry (CCF), which maintains a relatively intact forest cover through selective harvesting, has emerged over the last few decades as a popular alternative to rotational forest management (RFM). Coast redwood, which is native to the western United States, grows rapidly in New Zealand and is well suited to CCF as it has high shade tolerance, an ability to coppice from the cut stem, and resistance to pests, diseases, wind and fire. A forest estate model was used to compare the carbon sequestration, timber production and profitability of redwood CCF, RFM and permanent carbon forestry (PCF) regimes at a regional level within New Zealand. Through linear programming, this model optimised carbon accumulation and harvesting decisions across a large forest to meet a series of constraints associated with each regime. All three regimes represented good investment decisions, but CCF had the highest soil expectation value (SEV) within most North Island regions while PCF had a slightly higher SEV within the South Island regions. Under the transitional CCF (CCFt), revenue from carbon initially increased before levelling out at 40 years, after which time a sustainable harvest of high-value timber commenced in perpetuity without additional revenue from carbon. The CCFt regime transitioned to a steady-state condition, with a uniform age class distribution from year 150 onwards (CCFs), after which time a very high SEV was attained that exceeded that of CCFt by four-fold in the North Island (NZD 136,126/ha vs. NZD 34,430/ha) and seven-fold (NZD 44,714 vs. NZD 6267/ha) in the South Island. This study highlights the profitability of managing redwood under CCF and how initial carbon revenue can be used to finance the transition of the forest to a steady-state condition that produces a stream of valuable timber with a very high rate of return. [ABSTRACT FROM AUTHOR]

The inspirational paper by Ash, Dowler, and Varsi in 1978, proposing to utilize in situ resources on Mars (ISRU) rather than bringing them from Earth, originated the field of Mars ISRU that has been the subject of research ever since. In this paper, we reviewed significant research reported on Mars ISRU since 1978 and reported briefly on accomplishments. We found that prior to 2014, progress on small tasks was sporadic and intermittent, always at low Technology Readiness Level (TRL). In 2014, the National Aeronautics and Space Administration (NASA) took a bold, imaginative, unprecedented step to fund a major project in Mars ISRU: the so-called "MOXIE" (Mars Oxygen In Situ Experiment), in which an oxygen production plant based on solid oxide electrolysis (SOEC) was developed, and finally demonstrated on Mars in 2022 and 2023. While MOXIE leaves behind it a wealth of accomplishments, there remains the need to close remaining gaps with additional laboratory and field work. Solid-oxide electrochemical cell (SOEC) technology has become a major area of worldwide investment for terrestrial energy and CO2 control. There is a very strong overlap between this terrestrial technology and Mars ISRU. NASA has already leveraged the terrestrial development work via MOXIE. NASA can leverage further advances with a comparatively small investment beyond 2023. Because NASA is engaged in a major program to return humans to the Moon, NASA's focus is on lunar ISRU. Unfortunately, the mission impact and return on investment for lunar ISRU does not compare to that for Mars ISRU. NASA's concept for Mars ISRU is futuristic, involving autonomous mining, transporting, and processing large amounts of Mars regolith. This might well occur long after initial human landings which could better profit in the near-term from MOXIE technology. By continuing further development of SOEC technology beyond MOXIE, while leveraging large investments in terrestrial applications, NASA can develop the Mars ISRU appropriate to nearer term human missions at modest investment. The goal of this paper is to place the relatively mature MOXIE technology advance and solid oxide electrolysis in general in perspective to the historical evolution of low TRL Mars ISRU technology. [ABSTRACT FROM AUTHOR]

In the context of national efforts to promote country-wide distributed photovoltaics (DPVs), the installation of distributed energy storage systems (DESSs) can solve the current problems of DPV consumption, peak shaving, and valley filling, as well as operation optimization faced by medium-voltage distribution networks (DN). In this paper, firstly, a price elasticity matrix based on the peak and valley tariff mechanism is introduced to establish a master–slave game framework for DN-DESSs under the DPV multi-point access environment. Secondly, the main model optimizes the pricing strategy of peak and valley tariffs with the objective of the lowest annual operating cost of the DN, and the slave model establishes a two-layer optimization model of DESSs with the objective of the maximum investment return of the DESSs and the lowest daily operating costs and call the CPLEX solver and particle swarm optimization algorithm for solving. Finally, the IEEE33 node system is used as a prototype for simulation verification. The results show that the proposed model can not only effectively reduce the operating cost of the distribution network but also play a role in improving the energy storage revenue and DPV consumption capacity, which has a certain degree of rationality and practicality. [ABSTRACT FROM AUTHOR]

The study focuses on the selected aspects of investment measurement and management for the support of financial and economic decision-making of investors in wood-processing sectors. The aim of the study was to analyze the indicators for the structure and cost of capital of furniture and paper/forest branches in Slovakia, quantify the actual expected return on investment based on the selected methodology, and consequently find out the fundamental differences resulting from the specific conditions of given sectors. Methodologically, the study uses procedures for the weighted average cost of capital (WACC), capital asset pricing model (CAPM) for determining the cost of equity, and calculation of the beta coefficient considering the risk premium. The results of the study demonstrated a similar levered beta in both analyzed sectors (1.17 in furniture, 1.20 in paper/forest), but in each sector for a different reason. The expected rate of return is higher in furniture (7.84%) compared to paper/forest products at the level of 6.04%. The findings provide the possibility of comparing the required and expected rate of return on invested capital and making the appropriate long-term investment decisions. [ABSTRACT FROM AUTHOR]

As the main driving force for the digital transformation of the construction industry, the uncertainty of digital technology in the application process has seriously hindered the high-quality development of the construction industry. In order to promote the wide application of digital technology in the construction industry and clarify the key uncertainties in its application process, this paper identifies the uncertainty index system of digital technology application based on the LDA topic model and literature analysis; the DEMATEL-ISM method is used to construct the multilevel hierarchical structure model of the uncertainty indicators in the application of digital technology to study the mutual influence among the indicators and to find the key uncertainty indicators. The research results show that the uncertainty indicators of the application of digital technology in the construction industry are divided into five levels: policy, industry, personnel, economy and law, and that the perfection of the policy guarantee system is the key uncertainty indicator for the investment return period of digital technology application. The standard contract model for digital technology is a direct uncertainty indicator for the application of digital technology in the construction industry. The results of this study help researchers and practitioners to focus on the key barriers and provide a list of key elements for construction companies to promote the application of next-generation digital technologies to improve digitalization of the construction industry. This study also provides a policy reference to further promote the digital transformation of the construction industry. [ABSTRACT FROM AUTHOR]

A cryptocurrency is a non-centralized form of money that facilitates financial transactions using cryptographic processes. It can be thought of as a virtual currency or a payment mechanism for sending and receiving money online. Cryptocurrencies have gained wide market acceptance and rapid development during the past few years. Due to the volatile nature of the crypto-market, cryptocurrency trading involves a high level of risk. In this paper, a new normalized decomposition-based, multi-objective particle swarm optimization (N-MOPSO/D) algorithm is presented for cryptocurrency algorithmic trading. The aim of this algorithm is to help traders find the best Litecoin trading strategies that improve their outcomes. The proposed algorithm is used to manage the trade-offs among three objectives: the return on investment, the Sortino ratio, and the number of trades. A hybrid weight assignment mechanism has also been proposed. It was compared against the trading rules with their standard parameters, MOPSO/D, using normalized weighted Tchebycheff scalarization, and MOEA/D. The proposed algorithm could outperform the counterpart algorithms for benchmark and real-world problems. Results showed that the proposed algorithm is very promising and stable under different market conditions. It could maintain the best returns and risk during both training and testing with a moderate number of trades. [ABSTRACT FROM AUTHOR]

This article examines the factors contributing to the disparity in managers' disclosure tone from a signalling perspective. According to this viewpoint, managers intentionally choose their tone to convey information to the market. To determine the origin of tone inconsistency, we explored the association between future financial performance (as measured by the rate of return on assets (ROA) and rate of return on equity (ROE)) and future financial risk (as measured by the standard deviation of ROA and ROE) with the tone of management discussion and analyses (MD&As). The Loughran and McDonald dictionaries were utilised to assess managers' tone in the MD&As. Our dataset consisted of 1510 MD&As from 156 companies listed on the Tehran Stock Exchange, covering 2013 to 2022. Multiple regression analysis was employed, controlling for industry and year fixed effects. The findings revealed a significant relationship between future financial performance, future financial risk, and MD&A tone inconsistency. Thus, the biased tone observed in Iranian managers' MD&As can be explained by signalling theory. This study contributes to the existing literature by being the first to investigate signalling as a source of inconsistency in managers' disclosure tone. [ABSTRACT FROM AUTHOR]

As an emerging development model, green development requires the participation of the government, the market, and the public. It needs the formation of a positive interaction between policy guidance, market demand, and public will in order to realize a win–win situation comprising sustainable economic development and environmental protection. Thus, we explored green-development-related policies in China and defined four areas: industrial energy preservation, petrochemicals, agriculture, and the integration of the Yangtze River Economic Belt. Then, we analyzed how public attention relative to green development policies impacted the return of stock indices in the green industry using the Baidu search index. The research study was conducted on all trading days of A-shares in China from 1 January 2013 to 1 January 2023. In total, 2430 valid datasets were observed and curated over these 10 years. The public attention to green development policies was classified into four categories: industrial energy efficiency, petrochemicals, agriculture, and the Yangtze River Economic Zone. The attention focused on a category was measured by the number of searches of keywords that were the category's names on the Baidu platform. The number of searches was considered the variable representing the public's attention relative to each area of green development policies. The results showed that the increase in public attention to green development policies was not correlated with the increase in the return on investment (ROI) of green and carbon-neutral industries. In addition, information on green development policies had no significant effect on encouraging individuals to participate in investments in the green industry and had little effect on the financing of the carbon-neutral industry. The lack of details for green development policies and effective guidelines for potential investors needs to be overcome in order to encourage investment and financing. [ABSTRACT FROM AUTHOR]

Solar energy is a source of energy that can meet a significant part of the demand for heat and electricity. However, its acquisition is associated with high variability both during the year and on individual days. The construction of installations due to changes in tariff systems, investment costs and subsidy programs raises doubts as to their profitability. The aim of this study was to assess the profitability of photovoltaic investments for households, considering public financial support. This study used RetScreen Expert software 8.1.2.13 to perform the entire analysis and performance cost, risk and sensitivity simulations. Climate data were imported from ground monitoring stations or from NASA global satellite or analytical data. The conducted research showed the profitability of investments in photovoltaics, even without state support. Differences between regions were insignificant. However, the support system has changed, extending the period of return on investment. [ABSTRACT FROM AUTHOR]

Background: We assessed intraarticular injuries in patients after primary anterior traumatic shoulder dislocation by comparing magnetic resonance arthrography (MRA) results with concomitant arthroscopic findings. Methods: All patients with primary traumatic shoulder dislocation who underwent arthroscopic surgery between 2001 and 2020 with preoperative MRA were included in this study. MRA was retrospectively compared with arthroscopic findings. Postoperative shoulder function was prospectively assessed using the Disabilities of Arm, Shoulder and Hand score (quick DASH), the Oxford Shoulder Score (OSS), the Subjective Shoulder Value (SSV), as well as the rate of return to sports. Results: A total of 74 patients were included in this study. A Hill–Sachs lesion was consistently found in the corresponding shoulders on MRA and arthroscopy in 35 cases (p = 0.007), a Bankart lesion in 37 shoulders (p = 0.004), and a superior labrum from anterior to posterior (SLAP) lesion in 55 cases (p = 0.581). Of all cases, 32 patients were available for a clinical and functional follow-up evaluation. A positive correlation was found between the level of sport practiced and the Oxford Shoulder Score (redislocation subset) (p = 0.032) and between the age at the time of surgery and the follow-up SSV (p = 0.036). Conversely, a negative correlation was observed between the age at the time of surgery and the Oxford Instability Score (redislocation subset) (p = 0.038). Conclusions: The results of this study show a good correlation between MRA and arthroscopy. Therefore, MRA is a valid tool for the detection of soft tissue pathologies after primary anterior traumatic shoulder dislocation and can aid in presurgical planning. [ABSTRACT FROM AUTHOR]

In stock prediction problems, deep ensemble models are better adapted to dynamically changing stock market environments compared to single time-series networks. However, the existing ensemble models often underutilize real-time market feedback for effective supervision, and base models are pre-trained and fixed in their optimization, which makes them lack adaptability for evolving market environments. To address this issue, we propose a deep-reinforcement-learning-based dynamic ensemble model for stock prediction (DRL-DEM). Firstly, we employ deep reinforcement learning to optimize the weights of deep-learning-based time-series models. Secondly, existing deep-reinforcement-learning methods only consider environmental rewards. Thus we improve the reward function by introducing real-time investment returns as additional feedback signals for the deep-reinforcement-learning algorithm. Finally, an alternating iterative algorithm is used to simultaneously train the base predictors and the deep-reinforcement-learning model, allowing DRL-DEM to fully utilize the supervised information for global coordinated optimization. The experimental results show that in SSE 50 and NASDAQ 100 datasets, the mean square error (MSE) of the proposed method reached 0.011 and 0.005, the Sharpe ratio (SR) reached 2.20 and 1.53, and the cumulative return (CR) reached 1.38 and 1.21. Compared with the best results in the recent model, MSE decreased by 21.4% and 28.6%, SR increased by 81.8% and 82.1%, and CR increased by 89.0% and 89.1%, with higher forecasting accuracy and stronger investment return capability. [ABSTRACT FROM AUTHOR]

The Copernicus Sentinel-3 Surface Topography Mission (STM) Land Altimetry provides valuable surface elevation information over inland waters, sea ice, and land ice, thanks to its synthetic aperture radar (SAR) altimeter and its orbit that covers high-latitude polar regions. To ensure that these measurements are reliable and to maximise the return on investment, adequate validation of the geophysical retrieval methods, processing algorithms, and corrections must be performed using independent observations. The EU-ESA project St3TART (started July 2021) aims to generalise the concept of Fiducial Reference Measurements (FRMs) for the Copernicus Sentinel-3 STM. This work has gathered existing data, made new observations during field campaigns, and ensured that these observations meet the criteria of FRM standards so that they can be used to validate Sentinel-3 STM Land Altimetry products operationally. A roadmap for the operational provision of the FRM, including the definition, consolidation, and identification of the most relevant and cost-effective methods and protocols to be maintained, supported, or implemented, has been developed. The roadmap includes guidelines for SI traceability, definitions of FRM measurement procedures, processing methods, and uncertainty budget estimations. [ABSTRACT FROM AUTHOR]

The role of the agrifood industry is key to mitigating the impact of climate change, as it is one of the industrial sectors with the highest energy consumption. The optimisation of photovoltaic systems in agroindustries faces problems such as the fluctuation of energy prices or the evident seasonal nature of some producers. This paper provides a global view of the profitability and optimal sizing of photovoltaic (PV) systems in the new energy context. For this purpose, almost 4 million cases were analysed, including different consumption patterns, energy prices, etc. Some general conclusions can be drawn from the results. First, the adaptation to the new context requires adjustments in the sizing of PV systems in all industries analysed, which is also associated with changes in the return on investment. Second, seasonality strongly conditions the optimal size of PV installations, the return on the investment and the potential savings. Finally, in the face of future energy price variations, the ratio "Savings/payback" seems to be an appropriate reference for sizing, combining savings and profitability. In addition, they may justify special subsidies to seasonal industries. The conclusions of this paper should be considered to optimise the design of PVs. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a substantial and far-reaching impact on global economic growth, extending its effects to Indonesia as well. Various sectors have witnessed a decline in stock returns as a consequence. Interestingly, the telecommunications sector has bucked this trend by experiencing an increase in stock returns, defying the negative implications of the pandemic. The relationship between returns and risk is inherently intertwined, necessitating a meticulous risk assessment. In response to this need, the Value at Risk (VaR) method has emerged as a rapidly growing and widely adopted risk measurement tool. Among the techniques employed for VaR estimation, the Monte Carlo simulation stands out due to its flexibility and comprehensiveness in accommodating factors such as time variance, volatility, returns, fat tails, and extreme scenarios. The Gumbel copula method, known for its heightened sensitivity to high-risk events, is utilized for VaR estimation on abnormal stock returns. This study aims to quantify the Value at Risk by leveraging the estimated Gumbel copula parameter for the return on the shares of PT. Indosat Ooredoo Hutchison Tbk, and PT. Smartfren Telecom Tbk during the COVID-19 pandemic. At a 90% confidence level, the VaR is determined to be 7.6%. Notably, this estimate closely aligns with the actual values, underscoring the reliability of the VaR estimation conducted using the Gumbel copula parameter estimator. Therefore, this model serves as a robust reference, particularly suitable when dealing with investment return data that deviate from the normal distribution, while considering the unique stock return characteristics within each dataset. [ABSTRACT FROM AUTHOR]

There exists a considerable amount of evidence regarding short-term outcomes of shoulder arthroscopy in athletes; however, mid- to long-term data are limited. Therefore, the purpose of this review is to evaluate studies assessing mid- to long-term outcomes and rates of return to sport in athletes undergoing primary shoulder arthroscopy. A search for the systematic review was performed in PubMed, Scopus, and Embase on 14 March 2023. Study parameters, as well as their respective outcomes, were described in detail and compiled into diagrams. Five studies were included, which contained data on a total of 307 shoulders in patients with mean ages ranging from 20.3 to 26.9 years and mean follow-up times ranging from 6.3 to 14 years. The arthroscopic Bankart repair was the primary surgical intervention performed in all five studies. The overall rate of return to sport was 84% (range, 70–100%) across the studies. The rate of return to sport at pre-injury level was 65.2% (range, 40–82.6%) across four studies. The overall rate of recurrent instability was 17.3%, with redislocation specifically occurring in 13.7% of patients across all studies. The overall rate of revision surgery was 11.1%. Athletes who underwent primary shoulder arthroscopy demonstrated favorable outcomes and a high rate of RTS at a minimum follow-up of 5 years. However, rates of recurrent instability, redislocation, and revision surgery occurred at less than favorable numbers, which emphasizes the importance of proper patient selection when considering candidates for arthroscopic versus open repairs. [ABSTRACT FROM AUTHOR]

The digital twin (DT) research field is experiencing rapid expansion; yet, the research on industrial practices in this area remains poorly understood. This paper aims to address this knowledge gap by sharing feedback and future requirements from the manufacturing industry. The methodology employed in this study involves an examination of a survey that received 99 responses and interviews with 14 experts from 10 prominent UK organisations, most of which are involved in the defence industry in the UK. The survey and interviews explored topics such as DT design, return on investment, drivers, inhibitors, and future directions for DT development in manufacturing. This study's findings indicate that DTs should possess characteristics such as adaptability, scalability, interoperability, and the ability to support assets throughout their entire life cycle. On average, completed DT projects reach the breakeven point in less than two years. The primary motivators behind DT development were identified to be autonomy, customer satisfaction, safety, awareness, optimisation, and sustainability. Meanwhile, the main obstacles include a lack of expertise, funding, and interoperability. This study concludes that the federation of twins and a paradigm shift in industrial thinking are essential components for the future of DT development. [ABSTRACT FROM AUTHOR]

Digital banks have profoundly changed the financial industry's operations. In this scenario, the study of digital banks has gained increasing attention in the academic community. However, there is still a lot of room to understand how this type of organization functions and impacts different contexts. Considering the information collected, partial findings, and the professional experience of those involved in a larger research project, the main objective of this study is to present the Brazilian scenario related to digital banks from the analytical perspective of the research group. The methodological approach included analysis of partial results of a larger research project, bibliographic research, analysis of public data about digital banks in Brazil, and multidisciplinary discursive approach to conduct debates with the support of academic literature and experience from top managers working in major Brazilian financial institutions. Data on key performance indicators (KPIs), including cost breakdown, net revenue, return on equity (ROE), and cost-to-income ratio, are presented and analyzed for both traditional and digital banks. Furthermore, this study puts forward potential avenues for future research within three main research domains: digital operational efficiency for banks, customer attraction strategies employed by digital banks, and the utilization of digital financial services in the retail industry. [ABSTRACT FROM AUTHOR]

System of Rice Intensification (SRI) practices are expected to be used in location-specific ways and thus will vary somewhat across countries and regions. This study undertook to identify a 'best-bet' version of SRI for conditions in northwestern Nigeria, considering what is feasible for farmer use. Two years of experimental data from 260 farmer-managed rice plots evaluating four of the SRI practices in Zamfara State were analyzed. The variables evaluated were seedling age at transplanting, plant density, irrigation schedule, and fertilizer application. Farm budget analysis showed that the best-bet SRI practices most productive given the natural environment and farming system were transplanting 11-day-old seedlings at 25 cm × 25 cm spacing, with alternate wetting-and-drying of fields, as well as providing full compost plus some inorganic fertilization. Net economic returns were found to be highest with best-bet SRI practices and ranged from USD 1450–2120 ha−1. While rice production was profitable under both SRI and more conventional management, the return on investment was at least 40% higher with SRI practices than with the other practices evaluated. Based on our data and analysis, we recommend that the Nigerian government and its development partners prioritize and expand the testing and promotion of SRI in the northwest and other regions of the country. This initiative can significantly enhance farmers' incomes and, ultimately, bolster food security. [ABSTRACT FROM AUTHOR]

The aim of this study was to investigate the financial sustainability of retail food SMEs for the 2016–2021 period, in Romania, from the perspective of financial equilibrium and performance. A multivariate analysis was used, including a correlation analysis, a principal component analysis (PCA), and a cluster analysis. The empirical results show a positive link between the financial performance and financial equilibrium indicators. We employed the PCA in order to build a composite financial index using financial equilibrium indicators (ratios of liquidity, solvency, collection, and payment period) and financial performance indicators (Return on Assets and Return on Equity). The results show that financial equilibrium and performance are the two main dimensions which the financial sustainability index (FSI) was constructed on. Taking into account the dimensions of financial sustainability, the analyzed SMEs were clustered in four homogeneous clusters. The research findings clearly demonstrated that the retail food SMEs with a good/acceptable financial sustainability also have a good/acceptable financial balance and performance situation. Furthermore, a significant part of the analyzed SMEs faces difficulties regarding financial sustainability, being characterized by the lowest values of FSI, determined by both an uncertain situation in terms of liquidity, leading to a financial disequilibrium, and a negative financial performance. Therefore, this research emphasizes some specific measures that need to be taken to boost financial sustainability of these businesses in the retail food sector. [ABSTRACT FROM AUTHOR]

This paper conducts an analysis of the impact of COVID-19 and digital transformation (DT) on the financial performance of European listed companies. Using a panel data regression model from 2015 to 2021, the study analyzed the financial performance of 2179 companies. The sample of companies was chosen based on the availability of financial statements and aimed to examine the effects of COVID-19 and DT on financial performance, as measured by return on assets (ROA). The study used a fixed-effect model and checked for robustness by introducing return on equity (ROE) as a dependent variable. The results indicated that COVID-19 had a negative significant impact on financial performance, while DT had a positive significant impact, consistent with previous research. This study provides valuable insights into the impacts of the COVID-19 pandemic and DT on the financial performance of listed companies. [ABSTRACT FROM AUTHOR]

Stock portfolio optimization is always an interesting and attractive research problem due to the variety of stock markets. To find a useful stock portfolio, metaheuristic-based approaches have been presented to obtain diverse group stock portfolios (DGSPs) by considering the diversity of stock portfolios in the past. However, in the existing DGSP algorithms, two problems remain to be solved. The first is how to set a suitable group size, and the second is that the evolution process is time-consuming. To solve these problems, in this paper, an approach using grouping genetic algorithms (GGAs) was proposed for optimizing a DGSP. For setting a suitable group size, the proposed approach utilized two attributes of group stocks, including the return on equity and the price/earnings ratio. Then, to derive better stock groups, a cluster validation factor was designed, which was used as part of a fitness function. To solve the time-consumption problem, using the designed temporary chromosome, the number of stock portfolios that need to be evaluated could be reduced in the proposed approach to speed up the evolution process. Finally, experiments on two real stock datasets containing 31 and 50 stocks were conducted to show that the proposed approach was effective and efficient. The results indicated that the proposed approach could not only achieve similar returns but also accelerate the evolution process when compared with the existing algorithms. [ABSTRACT FROM AUTHOR]

The European Union dairy sector plays a significant role in supplying dairy products to consumers all over the world. The aim of this study was to examine changes in the return on equity as one of the main financial indicators determining the economic viability of EU dairy farms in the years 2004–2020. The analysis based on the DuPont model was used to determine the main drivers of return on equity in dairy farms from the five studied EU countries. The research results show that (1) the lowest return on equity in the years 2004–2020 was calculated for average farms from the Netherlands, and the reason for this phenomenon was the use of significant assets in the production, mainly resources that are very expensive in the Netherlands—land and human labor; (2) the highest return on equity was characteristic of dairy farms from France, and the factor strongly determining the favorable value of this ratio was the high degree of financing assets with low-interest loans and credits; (3) despite the lowest production potential and small scale of milk production, average Polish farms in the years 2004–2020 were characterized by a relatively high return on equity, which ranged from 4.97% to 14.9%. [ABSTRACT FROM AUTHOR]

Planners face many obstacles during the planning phase of any new project, especially project scheduling due to the numerous details and complexity of each uniquely designed project; previous experience in similar projects and traditional scheduling methods are not sufficient. The 4D-BIM schedule is the best solution, as it can be integrated with other modern technologies such as UAS, which improves project scheduling by allowing the project team to access project plans, details, and time-related information to simulate construction sequences. Despite the benefits of using 4D-BIM, planners prefer traditional planning and scheduling methods because of the barriers to using modern technologies. This research proposes a structural equation model focusing on estimating the weights of BIM barriers in offshore construction projects, including: the investigation of barriers keeping the construction industry standing at 3D-BIM; the relationships between them; and the evaluation of the probability and impact of each, using fuzzy theory. To validate the proposed model, a case study of an offshore project was conducted. The most important latent variables were awareness, risk, demand, and management, while the most prominent observed variables were the uncertainty of the return on investment and the lack of experienced users. This research guides project managers on actions that can be taken for each key variable to enhance and develop the use of 4D-BIM in project scheduling. [ABSTRACT FROM AUTHOR]

We conducted a study analyzing the impact of productivity shocks on equity returns in the U.S. economy from Q1 1960 to Q1 2022 using an RBC DSGE model. Our results suggest that while initial productivity shocks lead to higher equity returns, this effect fades within eight quarters. Nonetheless, such shocks can still provide valuable signals for investors to strategically allocate their investments in sectors that may benefit the most. Our study also found that the responses of key macroeconomic variables, including real GDP, are consistent with those observed in other calibration based DSGE models of the U.S. in previous research. [ABSTRACT FROM AUTHOR]

Given that risk-taking is an essential channel for companies to obtain high returns and realize value enhancement, the goal of this study is to holistically explore the determinants of corporate risk-taking using various machine learning algorithms. Based on the data from Chinese listed companies between 2010 and 2019, we document that the adaptive boosting (AdaBoost) model makes better predictions of corporate risk-taking. We further visualize the importance and influence of the firm basic characteristics, firm performance, and chief executive officer (CEO) characteristics and discover that in the AdaBoost model, the firm basic characteristics, and performance factors, such as the firm's fixed asset investments, size, and return on equity, are important in predicting corporate risk-taking, while CEO characteristics are less important. Finally, the role of variables in corporate risk-taking varies among large and small enterprises. Overall, our findings deepen the comprehension of what drives corporate risk-taking and provide a potential way for real-world firms seeking to adjust their risk-taking level. [ABSTRACT FROM AUTHOR]

The calculation of the return on investment (ROI) allows the estimation of the opportunity cost of a series of interventions and can therefore help to make allocative choices. The objective of this study is to estimate the ROI of three vaccinations (HPV for adolescents, HZ for adults, and influenza for the elderly) in the Italian context, considering the impact of increasing vaccination coverage based on target objectives of the National Immunization Plan (PNPV) 2017–2019 and accounting for different eligibility criteria of each vaccination. Three separate static cohort models were constructed, including the eligible population for these vaccinations on the basis of the PNPV 2017–2019 and following this population until death (lifetime horizon) or until vaccination waning. Each model compares the level of investment at current vaccine coverage rates (current VCRs scenario) with that of optimal NIP target VCRs with a non-vaccination scenario. The ROI for HPV vaccination was the highest among the programs compared and was always above 1 (range: 1.4–3.58), while lower values were estimated for influenza vaccination in the elderly (range 0.48–0.53) and for vaccination against HZ (range: 0.09–0.27). Our analysis showed that a significant proportion of savings generated by vaccination programs occurred outside the NHS perspective and might often not be estimated with other forms of economic evaluation. [ABSTRACT FROM AUTHOR]

This article studies the relationship between changes in the external business environment, a firm's innovation strategies towards customers, and performance. A model of relations was developed, as well as a hypothesis: "The use of the differentiation strategy has a positive effect on firm's performance. SMEs that use the differentiation strategy achieve better performance than those who use one of the other strategies (low-cost strategy, focus strategy, or an overtaking strategy)". The empirical study includes a population of 3007 SMEs and a sample of 163 SMEs. The firm's performance was measured using financial measures such as return on equity (ROE) and return on assets (ROA), operational measures such as economic value added (EVA) and comprehensive measures such as credit rating (CR). The structural equation modelling (SEM) approach was used for data analysis. Based on the results, we can confirm that changes in a firm's external environment affect the firm's strategy towards customers, which influences the performance of a firm. The empirical study confirmed that firms using the differentiation strategy indicate higher performances (ROA, EVA, and CR) than those using any other strategy. Results also show that high-performance SMEs incorporate customer perspectives into strategy selection. The most significant influence on the firm's selection of the differentiation strategy was found in cases when the firm cooperates with new customers with whom it has not collaborated thus far. SMEs that use a low-cost strategy, focus strategy, or overtaking strategy are less successful than companies that use a differentiation strategy. The developed model of relations in this research has special meaning for researchers and managers in the field of strategic management, strategy selection and implementation, as well as performance of SMEs. [ABSTRACT FROM AUTHOR]

When a fault occurs in photovoltaic systems, a human expert should be present at the scene and perform tests to determine the location and type of the fault. In such a situation, in order to maintain the safety of the specialist, protective measures such as shutting down the power plant or isolating the faulty part are usually taken. Given the fact that the equipment and technology of photovoltaic systems are expensive and their efficiency is currently relatively low (about 20%), a complete shutdown of the plant or part of it can be economical, return on investment and achieve profitability. Therefore, as much as possible, efforts should be made to detect and eliminate errors in the shortest possible time without shutting down the power plant. On the other hand, most solar power plants are located in desert areas, which make them difficult to access and visit. In this case, training skilled manpower and the constant presence of an expert on site can be very costly and uneconomical. Also, if these errors are not detected and fixed in time, they can lead to power loss (not using the maximum potential of the panel), device failure and eventually fire. In this research, using fuzzy detection method, a suitable method for detecting the error of partial shadow occurrence in solar cells is presented. Based on the simulation results, the efficiency of the proposed method is confirmed. [ABSTRACT FROM AUTHOR]

In the literature, there are many different photovoltaic (PV) component sizing methodologies, including the PV/inverter power sizing ratio, recommendations, and third-party field tests. This study presents the state-of-the-art for gathering pertinent global data on the size ratio and provides a novel inverter sizing method. The size ratio has been noted in the literature as playing a significant role in both reducing power clipping and achieving system optimization. The majority of researchers observed that due to varying irradiance distributions and operating temperatures at particular sites, the sizing ratios were dependent on geographic latitude. This study will identify the issue that makes it challenging to acquire dependable and optimum performance for the use of grid-connected PV systems by summarizing the power sizing ratio, related derating factor, and sizing formulae approach. The present study recommends a Deep Learning technique that might, due to the dynamic behavior of the PV technologies, provide fully automatic computation for the DC/AC sizing ratio, and effectively lower the whole return on investment (ROI) over a variety of circumstances and climatic changes. [ABSTRACT FROM AUTHOR]

The aim of this paper is to provide empirical evidence about the effect of organizational competition (OC) as a contextual factor on the relationship between the effectiveness of information technology governance (ITG), which informs accounting information systems, and the financial performance of banks. Financial performance is identified by return on investment (ROI), return on equity (ROE), and Tobin's Q. Averages of these variables were calculated for five years from 2015 to 2019. In fact, there is evidence for the general argument that banks will improve their performance by implementing ITG. Specifically speaking, the basic idea presented in this study is that the relation between ITG and bank performance depends on the appropriate interaction and matching between ITG and the OC. The study population includes the senior managers of banks in Jordan. Accordingly, a questionnaire consisting of 16 paragraphs was developed and distributed to senior managers in 23 banks during January to May 2021. As a result, 142 valid questionnaires were collected, which represented 61.7% of the questionnaires expected to be collected. Data are analyzed and processed by using descriptive statistical measures, t-test, exploratory factor analysis, along with multiple regression. The results show that despite the significant effect of OC on ITG, no relation exists between the interaction of ITG and OC, and bank performance in the three proxies of performance. The results of the study suggest that either banks do not benefit from ITG to improve their performance or that the chief executive officers' perceptions about ITG in their banks is erroneous. However, it should be clarified that the respondents could have been affected by their values and beliefs when evaluating effective ITG use in their banks. [ABSTRACT FROM AUTHOR]