Non-financial Factors Research Articles

The Non-Financial Factors that Can Explain the Low Graduation Rate of Black Students in Higher Education

Aim/Purpose: The purpose of this paper is to evaluate literature that considers how non-financial factors can influence the enrollment and the low graduation rates of Black students in higher education institutions. Background: Non-financial factors such as the academic, social, and family environments can have a significant impact on the school trajectory of individuals in Black communities. In this paper, we reviewed and analyzed qualitative and quantitative papers that examined school environmental factors as well as social and family environmental factors. Methodology: This paper is a review of the recent literature around the social factors influencing Black students’ academic experience. Findings: The main social factors retained from the literature that affect the graduation rate of Black students in higher education are adjustment and challenges, type of school and structure, stereotypes and prejudices; family background and structure effect, peers’ effect/role models and students’ social status, and non-linear academic path. Impact on Society: We seek to highlight information about how family and social environmental elements intersect with the school environment and how this intersection affects academic success and dropout rate.

The IRDiRC Chrysalis Task Force: making rare disease research attractive to companies.

The International Rare Diseases Research Consortium (IRDiRC) is an international initiative that aims to use research to facilitate rapid diagnosis and treatment of rare diseases. IRDiRC launched the Chrysalis Task Force to identify key financial and nonfinancial factors that make rare disease research and development attractive to companies. The Chrysalis Task Force was comprised of thought leaders from companies, patient advocacy groups, regulatory agencies, and research funders. The Task Force created a survey that was distributed to companies of different sizes with varied investment portfolios and interests in rare disease research. Based on the survey results, the Task Force then conducted targeted interviews. The survey and interview respondents identified several factors that make rare disease research and development attractive (e.g. a good understanding of the underlying biology) as well as barriers (e.g. absence of an advocacy organization representing the affected community's needs). The concept of Return On Investment allowed the exploration of factors that were weighed differently by survey and interview respondents, depending on a number of intrinsic and extrinsic issues. The Chrysalis Task Force identified factors attributable to rare disease research and development that may be of interest to and actionable by funders, academic researchers, patients and their families, companies, regulators, and payers in the medium term to short term. By addressing the identified challenges, involved parties may seek solutions to significantly advance the research and development of treatments for rare diseases.

Analysis Of Financial and Non-Financial Factors That Influence Tax Aggressiveness in Registered Companies on The Indonesia Stock Exchange Year Of 2016 – 2019

Analysis Of Financial and Non-Financial Factors That Influence Tax Aggressiveness in Registered Companies on The Indonesia Stock Exchange Year Of 2016 – 2019

ОЦІНКА ІНВЕСТИЦІЙНОЇ ПРИВАБЛИВОСТІ ПІДПРИЄМСТВА

In order to form an investment portfolio on the basis of both own and external funds, the enterprise, as part of its development strategy, needs to develop a series of measures aimed at strengthening its investment attractiveness, which includes, first of all, its assessment – a set of indicators that includes quantitative and qualitative characteristics of the enterprise's activity, the level of competitiveness, the company's focus on satisfying consumer expectations, the innovation of all processes in general. The article defines measures to increase the investment attractiveness of the enterprise within the framework of both general and investment development strategies, and provides a scheme for using such a financial instrument as factoring. It is noted that in the matter of assessing and increasing the investment attractiveness of the enterprise, it is important to constantly monitor all processes with the aim of changing and leveling activities in case of deviation from the intended plan. This will allow attracting the amount of financial resources needed by the enterprise, increase profitability and implement the processes of business planning and budgeting, control over the achievement of the planned result, and increase the efficiency of all processes. When implementing the ways of increasing investment attractiveness indicated in the work, investors will consider the enterprise as a profitable object for investment, capable of effectively mastering investment funds and providing the required level of income. It is concluded that there is currently no universal method for assessing the investment attractiveness of an enterprise. At the same time, there is no accurate and effective system for assessing the attractiveness of investing resources in a particular enterprise. The vast majority of assessment models do not take into account the impact of a large number of hard-to-predict external factors, including changes in the competitive environment, the company's sensitivity to exchange rate fluctuations, interest rates, etc. One of the solutions is the consideration of the company's strategic indicators, which include financial and non-financial factors. It is the integrated approach that will give the most accurate result of the analysis of the investment attractiveness of the enterprise, while highlighting not unified indicators, but really important ones, significant for this specific enterprise.

Research on Default Prediction Model of Corporate Credit Risk Based on Big Data Analysis Algorithm

In recent years, with the rise of many technologies such as big data and artificial intelligence, the digitalization and information transformation of enterprises have gradually penetrated into the financial industry. Based on different big data analysis algorithms, we aim to establish a default prediction model for corporate credit risk, further optimize different models, compare the model performance, and analyze the robustness of the optimal model. We collect 21 items of financial and non-financial index data from more than 1,000 listed companies, standardize, balance and normalize the data, use correlation coefficient to screen the index, and establish two in-depth learning models, convolutional neural network model and recurrent neural network model, based on Pytorch framework of Spark platform, to complete the model optimization, and compare them with two traditional machine learning models: random forest model and logistic regression model. Finally, the comparison experiment shows that the recurrent neural network is the optimal model with an accuracy rate of 0.93, a recall rate of 0.96 and a F1 value of 0.93. For the optimal recurrent neural network model, the robustness of the model is analyzed by modifying the number of indicators, changing the number of samples and eliminating non-financial factors. The results show that the evaluation indicators of the model do not change much under the three conditions, and the model has a good robustness.

Estimation of Impact of ESG Practices’ Performance and Their Disclosure on Company's Value

Recently businesses began to consider different initiatives of integrating ESG activities into business decision-making process. The key initiative is maintaining non-financial reporting and performance integration when aligning value creation activities with Sustainable Development Goals (SDG's) and communicating to stakeholders. Particularly, this is true for ESG positioning of the company in the context of the ESG performance-disclosure dichotomy. The purpose of the paper is to understand what kind of ESG practices’ factors influence value of companies from oil & gas and industrials sectors of the economy in developed capital markets the most in ESG performance-disclosure dichotomy. Our sample consists of 5388 observations of oil & gas and industrials companies for the period from 2016 to 2021. The results showed that investors do not appreciate either performance or disclosure separately, but they look at the activity of the firm in complex. Therefore, the company should employ both practices in order to be sound ESG-responsible company in the eyes of the market. The conclusions of the study could be of interest to companies building an ESG strategy to increase investor loyalty and improve financial performance. As well as to potential investors to evaluate companies and build an investment strategy implementing non-financial factors into decision making process.

The Impact of State Expenditure on Education and on Student Academic Achievement

Due to the impact of quarantine measures against COVID-19, the quality of education in the country’s schools has decreased. This issue is relevant and is on the agenda from the administration of the Head of State to university rectors and teachers, school principals and educators, students and their parents. Most of the participants in the discussion believe that too little money is allocated to the school. This article examines the impact of government spending on education and on students’ academic achievements. According to the literature review, it was revealed that an increase in financial support for secondary schools from the state will lead to an increase in the quality of education. To solve these research questions, we used a correlation analysis between student academic performance and government spending, and household spending. On the basis of the selected variables, a correlation analysis was carried out by the method of rank correlation of the relationship between student performance and the amount of state funding for education. The study concluded that the success of students in education is influenced by non-financial factors, such as educational standards and appropriate teaching methods. At the same time, a paradoxical situation has been revealed, almost every year the government increases annual spending on education in secondary schools, but student academic performance is constantly falling. In addition, there was no strong statistical relationship between student performance and the amount of State funding for education. Therefore, the question arises about the effectiveness of the use of allocated public funds for education.

경영자의 자기과신성향이 ESG 평가정보에 미치는 영향

[Purpose] The purpose of this study is to investigate the relationship between the ESG evaluation information of the Korea Corporate Governance Service and the CEO’s overconfidence tendency, which is a representative characteristic mentioned when referring to the manager’s personal characteristics.
 [Methodology] The dependent variables of the model were ESG evaluation grade(integration, environment, society, governance), and independent variables were CEO’s overconfidence variables, and the residual analyzed as total asset growth and sales growth. The study sample performed a regression analysis with 2,646 companies.
 [Findings] There is a contradiction between the CEO’s self－confidence tendency and the ESG evaluation grade(ESG environmental and ESG governance). As a result of analyzing companies with positive (＋) and negative (－) overconfidence of CEO, it is shown that the difference in overconfidence of managers has little effect on ESG grade. And as a result of the analysis using the CEO’s overconfidence tendency dummy variable, only the CEO’s overconfidence tendency dummy, ESG environmental, and social grade show a negative (－) correlation.
 [Implications] This study is meaningful in that it investigated the relationship between CEO’s overconfidence tendency, one of the main characteristics of CEO, using ESG evaluation, a non－financial factor, in addition to financial factors for sustainable management.

Methodological Aspects of Valuation of Credit Institutions under External Uncertainty

The article is devoted to the research of the issues of commercial bank business valuation under the conditions of uncertainty. The study aims to develop a model for forecasting the value of total assets and loan portfolio of a commercial bank within the framework of value estimation under external uncertainty. The relevance of the paper is that in the context of the COVID‑19 pandemic, military actions and sanctions pressure it is difficult to justify the market value of credit institutions due to the difficulties in implementing the methodology of assessment of banks whose business is associated with increased risks. The scientific novelty of the study lies in the development of a regression model that allows forecasting the value of total assets and the loan portfolio of a commercial bank as key value factors under external uncertainty. The authors used the following methods of scientific research: deduction, induction, correlation and regression analysis, and logical method. The key factors of business valuation of Russian banks are systematized. The authors propose to build a model within the framework of the income approach, based on the forecast of external cost factors: total assets and loan portfolio of the banking sector. A leading indicator that affects total assets and loan portfolio is justified. A model has been developed which makes it possible to forecast the total assets and loan portfolios of the banking sector and find the required value of the assets of the bank being evaluated through the market share. The model is tested on the example of the valuation of Sber. The authors conclude that the model developed by the authors makes it possible to build scenarios for future cash flows and quantify the valuation interval of a commercial bank. The prospect of further research is related to evaluating the influence of internal financial and non-financial factors in the context of the valuation management system. The article will be useful to practicing appraisers in business valuation and investors.

Bankruptcy Risk Factors of Russian Companies

The bankruptcy of Russian companies in the existing environment has become rather common. Determination of bankruptcy risk factors allows predicting the prospects for business development. The authors set the task to determine the relative influenceof individual financial and non-financial factors on the probability of a company’s bankruptcy. To study risk factors, the authors analyzed 3184 large Russian companies (with revenues of more than 2 billion rubles per year and more than 250 employees) of various industries operating from 2009 to 2020. The total number of observations is 38,208. For analysis, 30 factors were selected and divided into five groups: profitability, liquidity, turnover, financial stability and general (non-financial) factors. For the study, one of the machine learning methods was used – the random forest method. The sample consists of companies from seven industries, including manufacturing, retail, construction, electric power, mining, agricultural production, and water supply, as well as other industries, which include companies in education, healthcare, agriculture, and hospitality. The analysis was carried out both in aggregate for the entire sample without being distributed by industry, and for samples distributed by manufacturing, retail, and service industries. In the sample as a whole, the tested model in 86% of cases correctly predicted the possibility of a company going bankrupt for the period under review. This result confirmed that machine learning methods (in particular, the random forest algorithm) are highly effective in solving the problem of bankruptcy prediction for a company. Based on the data obtained, the paper concludes that profitability factors have the most significant impact on the probability of bankruptcy for manufacturing and retail companies. For service companies, it is financial stability factors. Solving the problem of determining the bankruptcy risk factors of Russian companies will ensure a reduction in the number of bankrupt enterprises, which, in turn, will contribute to the recovery and development of the national economy.

FACTORS INFLUENCING DIVIDEND PAYOUT POLICY: EVIDENCE FROM LISTED NON-FINANCIAL FIRMS OF THE ZAGREB STOCK EXCHANGE

This paper aims to assess the impact of financial factors on the dividend payout ratio, and the purpose is to research factors affecting dividend payout in less developed markets and compare them with the results of previous studies. We use the global research platform Screener.co, and the financial statements available on Zagreb Stock Exchange to collect the data. Our sample consists of companies listed on the Zagreb Stock Exchange that paid dividends at least once in the last three years. In the model applied, we covered five years (dividends paid from 2017 to 2021, based on financial fundamentals preceding dividends from 2016 to 2020) using hierarchical linear regression analysis that consists of four explanatory variables: return on equity, return on assets, financial leverage, and free cash flow to revenue. First, the research found high fluctuations in the dividend payout ratio and return on equity variability. Secondly, we found no statistically significant causality between the dividend payout ratio and explanatory variables. The results suggest that other long-term non-financial factors, such as the investors’ expectations, history of paying dividends, and large cash reserves backed by high retained earnings, may have a decisive impact on the dividend payout ratio rather than recent financial factors.

Determinan Peringkat Sukuk di Indonesia Periode 2015-2019

This research aims to find out the whether the financial and non-financial factors affect corporate sukuk rating (dependent variable) in Indonesia in 2015-2019. In this research, we employ profitability, liquidity, leverage, secure and firm size as the independent variables. This research uses the secondary data from financial statements available at Indonesia Stock Exchange and the company’s web. The object of this research is all companies receiving rating sukuk from PT PEFINDO. This research uses a quantitative approach with ordinal logistic regression while the sample is obtained through a purposive sampling method. The results show that profitability, liquidity, secure and firm size have a significant effect on sukuk rating, meanwhile leverage does not have a significant effect on sukuk rating.

The effects of Environmental, Social, and Governance (ESG) scores on firm values in ASEAN member countries

This study examines the effect of Environmental, Social, and Governance (ESG) scores on firm value in ASEAN. This study uses data from 184 public companies listed on the stock exchanges of each country from 2010 to 2019. This study finds that ESG scores have a negative effect on firm value (Tobin's Q). This finding shows that the higher the ESG value, the lower the firm value (undervalued) in ASEAN. Furthermore, this study shows the influence of each pillar, namely the environmental, social, and governance. The environmental and social pillars negatively affect firm value, while the governance pillar has no effect. In ASEAN, a high ESG score is not considered an advantage for a company. This research has implications for companies to consider increasing information and compliance with environmental and social aspects of the company to increase their values. In addition, it also adds to the literature regarding the determinants of firm value on non-financial factors.

Study of Bond Issuer Companies Listed on IDX and on PT Pefindo Rating List: The Effect of Financial and Non-Financial Factors on Bond Rating

The aim of this study is to determine the effect of liquidity, leverage, profitability, bond securities, and maturity variables on bond ratings of entities that issue bonds on the Indonesia Stock Exchange and PT Pefindo's rating list for the period 2019 - 2021. The objects used in this study are all bond issuer companies that have been recorded in PT Pefindo and have complete financial reports on the Indonesia Stock Exchange for 2019 - 2021. There are 11 bond issuer companies used as samples with 3 years of observation so that a sample of 33 is obtained. Sampling is determined by using a purposive sampling, while the insightful strategy utilized is calculated relapse examination. The result shows that liquidity (CR), leverage (DER), profitability (ROA), bond securities and maturity affect on the bond rating. This shows that liquidity, leverage, profitability, bond securities, and maturity have an impact on bond ratings for bond issuer’s entities.

The Non-Financial Factors Affecting Corporate Social Responsibility Disclosure (CSRD)

This study looks at the relationship of non-disclosure factors to the company corporate social responsibility (CSR). The research focuses on companies that focus on the energy and pulp and paper industries listed on the Indonesia Stock Exchange (IDX). An energy company is a company that uses natural resources as the main raw material in the production of the company's products until they are finally sold to the public. The research was conducted from 2011-2021. Non-financial variables that support the company's CSR activities are corporate governance, independent board, board meeting, risk, and company size. The results of the study show that non-financial factors, namely the independent board, board meetings, company size, and risk have an effect on the company's CSRD. This research cannot be generalized to all companies, because it only focuses on industries engaged in energy and pulp and paper. Future research is expected to use all listed companies and add variables for the company's non-financial factors.

The Impact of ESG Controversies on Bank Value and Risk-taking

ESG performance is one of the most important non-financial factors investors pay attention to when valuing a bank. Previous studies, devoted to bank ESG performance, rely solely on ESG ratings. The contribution of this paper to the existing literature is investigation of a new measure of ESG performance – ESG controversies. ESG controversies are covered in the media negative news that reflect a bank failure in ESG performance. The goal of this paper is to investigate the influence of negative ESG news on market value and stability of companies in a banking sector.A cross-country sample of 134 banks and data on 1,200 controversies from 2016 to 2020 are used in this study. Our results provide evidence that ESG controversies negatively affect bank value and have no impact on its stability. However, the effect on share prices is not unified: it is stronger for banks that are in the scope of investor attention, and this relation is observed for developed markets with high freedom of press exclusively. Moreover, investors take into consideration the reason of ESG controversy occurrence. They react strongly to negative ESG news, related to community and workforce.

The Security Team Organizational Commitment

According to a survey, one of the world's largest financial firms, the ideal time to stay in a job is 3-5 years. Meanwhile, the tenure of PT.Suprama Security Team as of January 1, 2020 is 6-23 years, stating that they have strong organizational commitment. Organizational commitment influences the decision whether or not to stay in organization, which has an impact on performance, employee turnover, absenteeism, organizational climate and employee attitudes in the team. To capture this situation, qualitative research methods were used with in-depth interview techniques conducted on 10 out of 30 informants. The results show that organizational commitment is formed by financial and non-financial factors such as a comfortable work environment, good relationships with colleagues, clarity of status as permanent employees, friendly superiors, and conscientious work operational standards. It shows that the organizational commitment the security team has is dominated by continuous commitment, affective commitment and normative commitment, respectively.

Assessment of Environmental, Social, Governance and Technogenic Components of Investment Risks

Introduction. To assess the investment attractiveness (IA) and development opportunities for investment objects (IO), non-financial factors characterizing the environmental, social, governance and technogenic (ESGT) features of objects of possible financing have been increasingly used recently. The purpose of this data analysis is to establish how the ESGT-parameters of IO may reflect their financial health and performance prospects in a rapidly changing world. Having built an ESGT risk profile with the help of mathematical models, the IA of the object of study and the strategy of practical measures to increase it are determined. When modeling these processes, one should consider the growing uncertainty of the modern world due to the emergence of new risks; a large number of systemic links between the structures of the modern technosphere; the power-law nature of the distribution of the probability density of catastrophe damage, which decreases more slowly than the Gaussian dependence. In addition, the efficiency of complex production systems is largely determined by the balance of their individual links. Therefore, to assess investment risks, new methods are required to formalize the dependence of IA on ESGT-factors for the integrated management of the level of credit, market, insurance and operational risks under conditions of uncertainty. The purpose of the article is to develop mathematical methods for quantifying IA and determining real costs to improve the management, social and technological structure of IO, and minimize environmental pollution. Results. A mathematical model has been developed for assessing the environmental, social, managerial and technogenic leaving risks of investment, which makes it possible to determine the optimal strategies for increasing the IA of a possible IO. For a comprehensive risk assessment, methods of the theory of singularities of smooth reflections (TOGO) and the method of analysis of hierarchies (MAH) are used. The following algorithm for estimating IA is proposed: 1) determining the indices of the ESGT-components of risk; 2) calculation of bifurcation index values; 3) determination of the weakest links, which are associated with a decrease in IA; 4) identification of priority measures to prevent the reduction of IA or restore it to a predetermined level and minimize the negative impacts of extreme events and ensure sustainable development. Conclusions. The obtained results show that mathematical models based on the use of TOGO and MAH methods are an important tool for estimating IA under conditions of uncertainty. They allow: 1) to calculate the degree of approximation of the parameters characterizing the functioning of the object to their critical values ??when the IA changes; 2) to determine effective controls to minimize the risk of losing IA or minimize the time and losses for returning IA; 3) to consider the uncertainty factor associated with the features of the decision-making process. The development of this work is aimed at creating an information system for assessing IA for the integrated management of the level of credit, market, insurance and operational risks in the face of uncertainty and determining effective scenarios for minimizing investment risks. Keywords: mathematical modeling, system analysis, investment risks.

The EU Taxonomy’s (Potential) Effects on the Banking Sector and Bank Lending to Firms

Abstract One of the key pillars of the European Green Deal is a renewed sustainable finance strategy to finance sustainable growth and to channel private investments towards projects that support the transition to a climate-neutral economy. The aim of this policy is to make the private sector take into account sustainability-related non-financial factors when making financing and investment decisions. Within this framework, the EU Taxonomy provides a uniform definition and classification system of environmentally sustainable economic activities. In addition, the EU Taxonomy itself provides the basis for further legislation and regulation. Banks as the main financiers of firms in Europe and therefore important players in directing capital flows towards sustainable projects are thus targeted with several requirements based on the Taxonomy. The question then is how banks’ lending to firms is affected by these regulatory changes and whether an impact on the greening of firms’ economic activities can be achieved. The existing literature provides evidence that firms’ environmental, social and governance (ESG) risks, profiles and performance influence their loan conditions, but it is unclear whether better funding conditions lead to reduced carbon emissions or “greener” activities at the firm level.

Pengaruh Faktor - Faktor Non Keuangan Terhadap Pengungkapan Islamic Social Reporting pada Perusahaan yang Terdaftar di Jakarta Islamic Index 70

Companies that are guided by Islamic values over time are so fast and the birth of companies based on Islamic values with increasing public needs will prioritize all their activities in accordance with Islamic principles. This company has social responsibility obligations to the community or the surrounding environment. Islamic Social Reporting (ISR) is a manifestation of a company based on Islamic religious values. The purpose of this study is to examine the effect of non-financial factors, namely awards, media exposure, size of the board of commissioners, managerial ownership, institutional ownership, audit committees, independent commissioners, industry type and company age on ISR disclosures in companies listed in the Jakarta Islamic Index (JII) 70 period 2018 - 2020. The results of the study state that ISR disclosure cannot be influenced by awards, media exposure, board of commissioners size, managerial ownership and industry type. Meanwhile, institutional ownership, audit committee, independent commissioner and company age affect the ISR disclosure. The results of the coefficient of determination test show that all independent variables can affect 22.5% and the rest are not examined in this study.