Size Variables Research Articles

UKURAN PERUSAHAAN, PROFITABILITAS DAN KEBIJAKAN DIVIDEN TERHADAP NILAI PERUSAHAAN MELALUI FINANCIAL DISTRESS

This research aims to determine the influence of company size, company size and dividend policy on company value with financial distress as a mediating variable. The population in this study are mining companies listed on the Indonesia Stock Exchange (BEI) for the 2019-2023 period. The total sample tested was 30 companies, multiplied by 5 years of observations selected using purposive sampling techniques. The data analysis technique uses Partial Least Square (PLS) with the SmartPLS 4 program. The research results show that the variables of company size and dividend policy have a positive and significant effect on company value, while profitability has a negative and insignificant effect on company value. Company size, dividend policy have effect on financial distress, while profitability has no significant effect on financial distress, while the effect of financial stress on company value has a negative and significant effect.

Dividend policy and residual dividend theory: evidence from Indonesia

PurposeUsing the residual dividend theory, this study examines the impact of capital expenditures and working capital on the dividend policies of publicly listed companies in Indonesia.Design/methodology/approachUsing data on public companies (other than those in the financial sector) listed on the Indonesia Stock Exchange from 2011 to 2020, this study collected 870 observations (firm-years). This study employs a regression analysis technique using the STATA application program. The main variables in this study are capital expenditure and working capital, and the control variables are sales growth, firm size, leverage, profitability, liquidity and dummy variables for state-owned enterprises. The dependent variable of dividend policy is proxied by the dividend payout ratio.FindingsThis study’s results support the residual dividend theory’s hypothesis, in which capital expenditure negatively affects a company’s dividend policy. This study also analyzes this effect on companies that pay cash dividends at quantile positions of 25, 30, 50 and 60. The results show that the effect of capital expenditure on cash dividend payments is more pronounced in the case of companies whose cash dividends are in the 50th quantile. This result holds across different specification and endogeneity tests.Originality/valueThis study analyzes the residual dividend theory in Indonesian companies, focusing on localized factors and investment priorities. It challenges traditional Western dividend policies and provides empirical data that enhances the theory’s robustness. The findings have practical implications for investors, policymakers and corporate decision-makers in the Indonesian market.

PENGARUH PENGUNGKAPAN EMISI KARBON, ECO- EFFIENCY, DAN GREEN INNOVATION TERHADAP NILAI PERUSAHAAN

The main purpose of a company is to maximize company value and create financial prosperity for company owners and interested parties. Basically, investors use company value as an indicator in assessing company performance. However, the reality is that the rapid development of the industry is also accompanied by increasing environmental problems, but many companies do not consider environmental impacts in their operational activities. In this context, it is important for companies to not only focus on economic aspects, but also consider environmental aspects in order to increase company value. There are several factors that can affect firm value. Therefore, this study was conducted with the aim of examining the disclosure of carbon emissions, eco-efficiency, and green innovation on firm value. This research is quantitative research using hypothesis testing. The independent variables used in this study are disclosure of carbon emissions, eco-efficiency, and green innovation. The dependent variable is firm value. This study uses control variables of company size and profitability. The object of this research is all manufacturing sector companies listed on the IDX in 2019-2022. The analysis technique used in this research is multiple regression analysis. The results of this study prove that eco-efficiency and green innovation have a positive influence on firm value. This means that the more companies that implement eco-efficiency and green innovation will encourage an increase in firm value. On the other hand, carbon emission disclosure has no influence on firm value. This is because the level of disclosure made by the company is still low so that it has not been able to affect the firm value.

Overall survival prediction and risk stratification in patients with neuroblastoma through machine learning in the large multi-institutional PRIMAGE cohort.

10054 Background: Neuroblastoma (NB) is the most prevalent solid cancer in childhood in which imaging plays a pivotal role at every step of the patient's journey. This investigation aimed to develop a machine learning model using clinical, molecular (MycN amplification), and magnetic resonance (MR) radiomics features at diagnosis to predict patient’s overall survival (OS) and improve their risk stratification. Methods: A database comprising clinical, molecular, and International Neuroblastoma Risk Group (INRG) staging on 513 patients with accessible MR imaging (discovery cohort) was employed for model training, validation, and testing. An additional 22 patients from non-discovery cohort hospitals served as an external validation group. Tumor segmentations of NB were manually and semi-automatically performed on corresponding T2-weighted MR images by an experienced radiologist. In total, 107 radiomics features were extracted and harmonized across MR scan manufacturers and magnetic field strengths using the nested ComBat methodology to correct both batch effects. These radiomics features, combined with clinical and molecular data, were utilized as input for the models. A nested cross-validation approach was employed for model development to determine the optimal preprocessing, machine learning algorithm, and model configuration. Results: The discovery cohort yielded a C-index of 0.788 ± 0.049 in the test partitions, with a random survival forest (RSF) exhibiting the best performance. In the validation cohort, a C-index of 0.934 was achieved. Interpretability analysis identified lesion heterogeneity, size, and molecular variables as crucial factors in OS prediction. The model demonstrated superior predictive performance and patient stratification compared to conventional staging systems in both cohorts. Conclusions: The RSF predictive model exhibited high performance, emphasizing the significant contribution of radiomics features and alignment with established clinical and molecular variables. The model stratified NB patients into low-, intermediate-, and high-risk categories and suggests that radiomics features potentially could improve current risk stratification systems. Additional external validation is warranted as this may present new evidence for enhancing patient care and clinical decision-making for NB patients.

A Research on the Impact of Carbon Emissions on Financial Performance of Companies in the Borsa Istanbul Sustainability Index

The goal of this study is to reveal the relationship between the amount of carbon emissions that firms emit into the atmosphere and financial performance of the firms. In this context, the data of 41 firms listed in the “Borsa Istanbul Sustainability Index” between 2017-2021 are examined. “Panel data analysis” methods were administered in the research. As consequences of the research, it is inferred that carbon emission intensity, size, leverage and growth variables have a significant impact on “Tobin’s Q Ratio and ROA”. Only the “growth” variable has a significant impact on “ROE”. However, the study shows that total carbon emission has no significant impact on “ROA, Tobin’s Q Ratio and ROE”. Limited research with in this content has been found in the national literature. Within this scope, the study is a pioneering research on determining the relationship between carbon emissions and financial performance of companies traded in the "BIST Sustainability Index" and is assessed to contribute to practitioners and the literature regarding the findings obtained.

Factors Affecting Employee Performance in the Business Recovery Process at Listed Banks in Vietnam

Purpose: In recent years, many disruptions have occurred in the Vietnamese economy, which has caused listed banks to suffer many consequences, so listed banks must recognize the factors that promote recovery. Although studies on this issue have been conducted, the amount is quite limited and there is little focus on human resource factors. This empirical study was conducted to demonstrate the factors that affect employee performance and its impact on the recovery of business operations of listed banks. Design/methodology/approach: In this study, the author used questionnaires to collect data from 850 listed bank employees between 15th August 2023 and 26th December 2023. This study developed a questionnaire that used measures from many previous empirical studies to build a model to measure the impact of human resources on a company's ability to recover performance, using a five-point Likert-style scale (from 1 level equals to totally disagree; to 5 level equals to totally agree). After collecting data, this study used the SPL Smart application, to find the relationship between the role of human resources and the ability to recover business performance. From that analysis, the author will provide an objective perspective on the role of human resources in promoting the recovery performance of listed banks in Vietnam. Findings: Research results show that performance appraisal variables positively impact employee performance. On the other hand, career development and training and development do not affect employee performance. Finally, the analysis shows that there is a positive relationship between employee performance and business recovery at listed banks. Research limitations/implications: This study shows that human resources play a very important role in the recov-ery process of Vietnamese listed banks. Learning about the factors that influence employee performance will help banks align their HR strategies with organizational goals, ensuring that the workforce has the right skills and com-petencies necessary force. This process will help listed banks in Vietnam increase their ability to recover from disruptions and enhance their competitiveness. However, this study still has limitations including sample size and number of independent variables not large enough to show the importance of human resources in the recovery process of listed banks in Vietnam. Originality/value: This study contributes to emphasizing that human resources play an important key in the recov-ery process for Vietnamese listed banks. From an objective perspective, it provides insights into the role of human resources and factors to improve employee performance in listed banks.

Directors' and officers' liability insurance: a systematic literature review

PurposeWe review and synthesize the existing research on directors' and officers’ (D&O) liability insurance. Our objectives are (1) to examine the institutional forces and regulatory requirements that have influenced the development of D&O liability insurance; (2) to identify the factors that influence firms to purchase D&O liability insurance and explore the consequences associated with its usage and (3) to identify gaps in the current literature and provide recommendations for future research on D&O liability insurance.Design/methodology/approachWe perform a systematic literature review (SLR) using the Preferred Reporting Items for a Systematic Review of Meta-Analysis (PRISMA) guidelines to examine archival studies that investigate the determinants and consequences of D&O liability insurance. Using a Boolean search strategy on the “Web of Science” (WoS) and PRISMA selection criteria, we review 64 published archival research articles and three working papers from 1987 to October 2023.FindingsOur review reveals that disclosing detailed information regarding D&O liability insurance, such as total insurance premiums and coverage limit, is predominantly voluntary, except in Taiwan. Our findings suggest that the decision to purchase D&O liability insurance is influenced by litigation risk, which is determined by factors such as firm size, complexity and corporate governance variables. We also find that D&O liability insurance has implications for financial reporting, audit outcomes, investment behavior and capital market performance.Practical implicationsIn the post-COVID era, where firms face pressure due to financial constraints, our research emphasizes the practical importance of carefully considering and understanding the impact of D&O liability insurance, particularly as it concerns the demand for such insurance.Originality/valueTo the best of our knowledge, this study represents the first systematic review of previous research on D&O liability insurance. Our review highlights some research gaps, particularly in relation to the implications for financial reporting practices, auditing outcomes, firm investment behavior and capital market consequences.

A Meta-Analysis to Evaluate the Reliability of Depth-to-Water Maps in Predicting Areas Particularly Sensitive to Machinery-Induced Soil Disturbance

The careful planning of the extraction routes is one of the most important best management practices to limit soil disturbance related to ground-based forest operations. Over the recent years, this task has been commonly addressed in the framework of boreal forestry, by developing soil trafficability maps based on the depth-to-water (DTW) topographic index. The basic concept of trafficability maps developed with the DTW index is that soils at low DTW index, namely <1, could be more prone to soil compaction and rutting as they tend to have higher moisture content. However, previous studies that tried to assess the reliability of these maps reported contrasting results. Therefore, the present meta-analysis was developed to evaluate if soils at low DTW index (≤1) are actually more sensitive to soil compaction and rutting than soils at higher DTW index (>1). A database was created containing all the studies that assessed soil compaction and rutting in soils at low DTW index (experimental treatment) and high DTW index (control treatment), and a multivariate meta-analysis was used to check the presence of statistically significant effect size. Then the influence on the effect size of variables like soil texture, number of machine passage and weight of the machine, was checked by applying sub-group meta-analysis and meta-regression. Finally, a sensitivity analysis was performed by removing possible outliers from the database and repeating the analyses. No statistical differences were found in soil compaction and rutting severity in areas at low DTW index in comparison to the control areas (DTW index ≥1). The results showed that soil texture, number of machine passage and weight of the machine did not have a significant influence on the effect size. The sensitivity analysis developed after removing outliers from the database fully confirmed the obtained results. Thus our meta-analysis showed that the DTW index in its current form is not a fully reliable predictor of soil areas that could be particularly sensitive to machinery-induced disturbance. It is therefore recommended to use the DTW index to create trafficability maps, always taking into account that the results of the algorithms should be validated in the field before starting harvesting operations.

Effectiveness of an Evidence-Based Practice Education Program for Undergraduate Nursing Students: A Systematic Review and Meta-Analysis.

The search, conducted through PubMed, Cochrane Library, EMBASE, CINAHL, and Web of Science up to December 2023, included studies published in English and Korean and adhered to PRISMA guidelines. Qualitative appraisal of the studies was conducted using the revised ROB II for randomized trials and the ROBINS-I for non-randomized trials. For the meta-analysis, the effect size of the intervention was calculated as a standardized mean difference. In our study, 11 studies met our inclusion criteria, and 8 studies of those were included in the meta-analysis. The effect sizes for EBP competency, critical thinking, and problem-solving ability were 1.55, 1.29, and 0.65, respectively. The meta-regression analysis indicated that tailored education programs of 4-7 weeks and being in the 4th grade significantly enhanced EBP competency. These findings support the development of a customizable and applied EBP education actively for students, preparing nursing students to effectively implement EBP in clinical settings after graduation. Despite the significant effect size of the outcome variables, the high heterogeneity suggests the need for further investigation to validate the EBP educational outcomes for nursing students.

PENGARUH PROFITABILITAS, LEVERAGE, DAN UKURAN PERUSAHAAN TERHADAP KETEPATAN WAKTU PENYAMPAIAN LAPORAN KEUANGAN

The research was conducted to see the effect of the variables of profitability, leverage, and company size as independent variables on the timeliness of financial report submission as the dependent variable. The profitability variable in this study uses ROE as a measuring tool, for leverage using DER as a measuring tool, and finally Ln is used as a measuring tool for the company size variable. This research uses the property and real estate sector industry listed on the IDX for the 2020-2022 period. 48 companies were obtained for the population so that the research sample was 144. This research uses quantitative methods and uses secondary data sourced from the IDX. The sampling process applies purposive sampling technique. The analysis test processed using the SPSS 25 application shows that there is a simultaneous influence on profitability and leverage, and company size on the timeliness of financial report submission. It was found that profitability and leverage did not have a significant influence on the timeliness of submitting financial reports, while company size showed a positive influence on the timeliness of submitting financial reports.. Keywords: Leverage, Company Size, Timeliness of Submitting Financial Statements

Size Perusahaan Memoderasi Hubungan Good Corporate Governance, Green Supply Chain Management dan Green Accounting Terhadap Kinerja Keuangan Perusahaan

This research aims to examine how company size influences the relationship between Good Corporate Governance, Green Supply Chain Management, and Green Accounting on Company Financial in Sri-Kehati index companies listed on the BEI from 2016 to 2022. This type of research is known as associative quantitative research . The population in this research is the Sri-Kehati index business actors listed on the Indonesia Stock Exchange between 2016 and 2022, totaling 25. The sampling approach is a saturated sampling technique. The sample for this research consists of 25 companies listed on the Indonesia Stock Exchange from 2016 to 2022, with 175 observation data obtained based on sample criteria. The data analysis method used is panel data regression analysis with Eviews-12.0. The findings of this study show that good corporate governance has a partial impact on company financial performance, while environmentally friendly supply chain management has a small impact and environmentally friendly accounting does not. The company size variable cannot moderate the influence of good corporate governance on the company's financial performance, the influence of green supply chain management on the company's financial performance, or the influence of green accounting on the company's financial performance.

Fuzzy based trusted malicious unmanned aerial vehicle detection using in flying ad-hoc network

The communication security of unmanned aerial vehicles (UAVs) or drones based on flying ad hoc networks (FANETs) can be enhanced and maintained by assessing vulnerabilities, threats, and attacks. Thus, trust, high mobility, and complex communication interfaces are crucial for effective coordination and segregation of malicious drones from the genuine. A new efficient honesty-based detection scheme for malicious drones has been proposed to distinguish between intentional and unintentional misbehavior of the UAVs. The proposed scheme configures a drone system for packet transmission within the FANET, specifying buffer size and packet size variables to control data flow and prevent congestion. It then computes energy used for packet reception and transmission, optimizes energy consumption, and evaluates the drone’s mobility through the link stability index (LSI) and honesty UAV. The honesty UAV parameter categorizes UAVs into unintentional malicious and intentional malicious categories. Fuzzy logic helps identify intentional and unintentional misbehaving drones and improves performance in the network. It continuously generates the malicious UAV detection mechanism by assessing the parameters i.e., energy, pattern of movements, and the honesty score about the UAVs as a whole. Thereby a dynamic rating system to adeptly identify and differentiate the cooperative and non-cooperative nature of drones from the network is assimilated in the paper. Simulation results show the proposed scheme approximately aligns with the actual cases for varying numbers of malicious drones. Finally, the observation of the simulation result reflects substantial enhancement in performance metrics, with a significant cutback in end to end delay and packet delivery ratio by 10–30% and 20–50% respectively, contrasting with the existing techniques.

Who emits more emission? the association between CO2 emissions and socio-economics characteristics of Indonesian household

Much research has been done on identifying socio-economic household links in developed countries. However, the study of household carbon emission (HCE) levels and related variables still needs to be examined, especially in developing countries. The study uses an ordinary least squares model to pinpoint the socio-economic elements that affect a household's carbon emission levels. SUSENAS (National Socio-economic Survey) data from March 2019 and 2021, covering 655,694 households, were used. This study used ordinary least squares (OLS) for the regression and dominance analyses (DA) to determine the most crucial factors affecting the HCE. The household characteristics, individuals, and residential conditions are used to measure socio-economic situations. The DA analysis shows that income and household size are the most crucial determinants of HCE. The OLS analysis reveals that the income variable exhibits a non-linear relationship with HCE as an inverted U-shape in the total HCE and most consumption categories. Wealthier households generate higher levels of household carbon emissions than poorer households. The variable of household size demonstrates a positive relationship with the HCE. The composition of household members also significantly affects household carbon emission levels, where the presence of working members and toddlers tends to increase household carbon emissions. The research also finds differences in consumption patterns between urban and rural households, resulting in varying levels of carbon emissions. The findings of this study can assist policymakers in formulating targeted policies to reduce household carbon emissions.

Factors influencing the development of artificial intelligence in orthodontics.

Since developing AI procedures demands significant computing resources and time, the implementation of a careful experimental design is essential. The purpose of this study was to investigate factors influencing the development of AI in orthodontics. A total of 162 AI models were developed, with various combinations of sample sizes (170, 340, 679), input variables (40, 80, 160), output variables (38, 76, 154), training sessions (100, 500, 1000), and computer specifications (new vs. old). The TabNet deep-learning algorithm was used to develop these AI models, and leave-one-out cross-validation was applied in training. The goodness-of-fit of the regression models was compared using the adjusted coefficient of determination values, and the best-fit model was selected accordingly. Multiple linear regression analyses were employed to investigate the relationship between the influencing factors. Increasing the number of training sessions enhanced the effectiveness of the AI models. The best-fit regression model for predicting the computational time of AI, which included logarithmic transformation of time, sample size, and training session variables, demonstrated an adjusted coefficient of determination of 0.99. The study results show that estimating the time required for AI development may be possible using logarithmic transformations of time, sample size, and training session variables, followed by applying coefficients estimated through several pilot studies with reduced sample sizes and reduced training sessions.

FINANCIAL PERFORMANCE OF SELECTED COMPANIES AFTER GST IMPLEMENTATION IN INDIA

There is mixed anticipation and different responses on GST from manufacturers, service providers, and different market intermediaries. There is lack of such studies, specifically in the context of India, that provide any empirical support on either positive or negative impact of GST. Thus, the present study sought to empirically analyze the performance of companies after one year of GST implementation. Probability sampling was used to get the relevant sample. A total of 192 BSE listed companies were taken for analysis. Financial parameters (total assets, profit, and market capitalization for FY2017 and FY 2018) and demographic variables (size and experience of companies) were used to analyze the impact of GST roll out. The results indicated that among all three financial parameters, only total assets were significantly different from the pre-GST time (FY2017). Further analysis highlighted that age and size of the company also affected the equation and were found significant in influencing the performance of companies after GST implementation. Detailed analysis and results were subsequently discussed in this paper. The study brought forth new insights on effect of new indirect tax regime on financial performance of the companies in order to fill the research gap. The results of the study will be useful for policy makers, strategists, and managers to cope up with the challenges posed by GST

THE INFLUENCE OF BRAND AWARENESS, PERCEIVED QUALITY, BRAND ASSOCIATIONS, AND BRAND LOYALTY ON THE BRAND EQUITY OF OPPO SMARTPHONES

Brand equity is a set of assets and values associated with a brand. Several factors influence it, namely brand awareness, perceived quality, brand associations, and brand loyalty. This research is expected to provide insight to understand the influence of brand awareness, perceived quality, brand associations, and brand loyalty on the brand equity of Oppo smartphones. This research used purposive sampling as the sampling method, the questionnaire as the data collection method, and distributed to 145 students of the Faculty of Business, PGRI University of Yogyakarta. The data were evaluated using validity and reliability tests and analyzed with partial, simultaneous, and multiple linear regression tests. Partial positive impact is shown by brand awareness, brand association, and brand loyalty on brand equity. However, perceived quality has a negative effect on brand equity. The simultaneous impact is shown by brand awareness, perceived quality, brand association, and brand loyalty on the brand equity of the Oppo smartphone. However, this research has a small sample size and limited variables used; future research is expected to expand the sample size and include new variables.

Axial length and pharmacologic pupillary dilation in highly myopic patients.

To determine how high myopia impacts pharmacological pupillary dilation, and to evaluate the relationship between the extent of pharmacologic pupillary dilation and axial length. Patients were grouped into high myopes, defined as one or both eyes having a refractive error greater than - 6 diopters, and controls (between - 2 and + 2 diopters). Dilation was achieved with 1 drop each of tropicamide 1% and phenylephrine 2.5%. Pupil size was measured at full and dim light prior to dilation, then 15 and 30min after dilation. Biometry was measured for each patient. Statistical analyses were performed using the Mann-Whitney-Wilcoxon tests, two-sample Welch's t-tests, and linear mixed effect models and generalized estimating equations models accounting for inter-eye correlation. Forty patients (20 high myopes and 20 controls, 80 eyes total) participated in the study. High myopes had larger pupils at baseline and achieved significantly greater pupillary size (7.08mm, 95% CI: 6.97 to 7.19mm) than controls (6.23mm, 95% CI: 5.94 to 6.52mm) after 30min of dilation (P < .0005). Fully dilated pupil size at 30min was significantly correlated with both refractive error (r = - 0.57, P < .0005) and axial length (r = 0.47, P < .0005). Generalized estimating equations and linear mixed effect models identified other predictive variables of pupil size after dilation including age and white-to-white diameter. Highly myopic patients dilate to a larger pupillary size compared to other patients. Predicting dilation based on extent of myopia could facilitate intraocular surgery planning and reduce clinic wait times for myopic patients.

Cigarette Company Classification and Environmental Uncertainty with Risk Management Mediation in Predicting Excise Tax Returns

This research was conducted on the basis of the fact that the amount of excise returns as a deduction from state revenues from the excise sector is fluctuating and tends to increase over the last five years from 2018 to 2022. This research aims to conduct an analysis and obtain empirical evidence regarding the influence of Cigarette Company Classification on excise returns through the implementation of management. risks and the influence of Environmental Uncertainty on excise returns through the application of Risk Management. This research falls into the realm of quantitative research that adheres to a causality approach, the focus of which is testing cause-and-effect relationships between variables. Data collection and analysis were performed using quantitative methods, with a statistical testing approach through path analysis. The source of information used in this research comes from secondary data, namely financial report data from the Directorate General of Customs and Excise and Risk Management Values in the form of profiling tobacco products companies from 2015 to 2022. This research is different from previous research and shows a higher level of originality. because it uses Risk Management variables as mediators and utilizes a unique unit of analysis by adopting indicators of tobacco production capacity and the size of cigarette company capital ownership as a method for measuring company size variables.

FAKTOR – FAKTOR YANG MEMPENGARUHI NILAI PERUSAHAAN PADA PERUSAHAAN INDEX LQ45

The study was conducted to obtain empirical evidence of the effect of profitability. liquidity. Solvency, firm size. and dividend policy on firm value in companies listed on the LQ45 Index for the 2016 – 2019 period. The research design used is descriptive research using purposive sampling method and obtained 17 companies. This study uses multiple regression analysis which helps with the Eviews 10 application to test the data. The results obtained by the variables of profitability, solvency and firm size are able to have an influence on the firm value variable. This study also did not find a significant effect for liquidity and dividend policy. The implication of this research is the need for the company's attention to produce the ideal ratio, especially for profitability, solvency, and company size which will affect the value of the company and will provide a good signal for investors.

WASTE DISCLOSURE TO ENERGY SECTOR COMPANIES

Environmental problems still occur around, the main cause is company waste. The study was conducted with the aim of examining the effect of profitability, leverage and company size on waste disclosure. The data used are secondary data with quantitative methods. The purposive sampling method was used to select samples and obtain as many as 104 data on energy sector companies listed on the Indonesia Stock Exchange in 2021 – 2022. The results obtained by researchers show that the variables of profitability and company size have a significant positive effect on waste disclosure. While leverage has a significant negative effect on waste disclosure.