Significant Negative Influence Research Articles

Does institutional quality complement the relationship between ownership structure and corporate social responsibility?

The key purpose of the Study is to examine if institutional quality complements the relationship between Ownership Structure and Corporate Social Responsibility disclosure and performance in the light of legitimacy and agency theory. To the best of my knowledge, it is the first study in literature of finance. The sample comprises of 112 top-performing listed firms (based on market capitalization) at Pakistan Stock Exchange from 2010 to 2019. Institutional quality comprised of world governance indicators which is developed via principal component analysis, an instrumental variable approach and content analysis are used for CSR Disclosure Index to demonstrate the relationship between ownership structure and CSR. The resources complementary phenomenon is adopted to examine the institutional quality's role. Our results show significantly positive impact of Institutional and Foreign Ownerships on CSR while negative significant influence of CEO Duality and Family Ownership on CSR, suggesting that well governed firms will be more socially responsible. In addition, the findings suggest the institutional quality's positive moderating role on the relationship between ownership structure and CSR, signifying the institutional quality's complementary role for the weak corporate environment in Pakistan. Our findings are robust to a series of tests by using Generalized Method of Moment (GMM).

Dynamics effect of volatility index, interest rates, and commodity prices on Indonesian bond yields

Several factors influence the movements and dynamics of bond yields in financial markets. The determination of monetary policy, specifically the decisions regarding interest rates made by central banks, is a critical factor. Moreover, bond yields can be influenced by various factors such as geopolitical events, financial volatility, market sentiment, and investor risk appetite. These factors can impact the demand and supply dynamics in bond markets. This research aims to analyze the influence of Interest Rates, IDR to USD Exchange Rates, Volatility Index (VIX), Gold and Oil Prices on Bond Yields in Indonesia. The data used in this research is secondary data, which consists of time series data from 2019-2023. This research investigates the impact of financial and commodity prices on bond yields in Indonesia by using the autoregressive distributed lag (ARDL) model to examine both the long-run correlation and short-run effect. Empirical results found that Interest Rate, Volatility Index (VIX), and Oil Prices have a significant positive influence. Meanwhile, the Gold Price variable has a significant negative influence. This research has several crucial policy implications for investors concerning the national monetary policy, exchange rate fluctuation, and global volatility index to create profitable and sustainable portfolio strategies. Moreover, investment managers and investors should be concerned about the global commodities prices that will affect bond yield performances. This research contributes to the recent literature presenting causal relations of global volatility index (VIX) on Indonesian bond yield.

ANALISIS KINERJA KEUANGAN BANK UMUM KONVENSIONAL KBMI 3 TAHUN 2017-2022

In general, the purpose of an established company is to make a profit for its owners. A company that performs well can generate high profits with a long period of time and is able to attract investors to invest its funds. One form of information that can be used to determine the condition and development of a company is the financial statements reported at the end of each period as a report on management accountability for the management of a company. Company performance is a description of the financial condition of a company that is analyzed with various financial analysis tools, so that it can be known about the good and bad financial condition of a company that reflects performance achievements in a certain period. This study aims to analyse the financial performance of core capital group (KMBI) 3 banks using Otoritas Jasa Keuangan (OJK) report data for the period 2017 - 2022 which is processed using the Eviews application. The results of the study found that Capital Adequacy Ratio (CAR) has a significant positive influence on company performance in this case Return On Asset, Non Performing Loan (NPL) does not have a significant effect on Return On Asset, Loan To Deposit Ratio (LDR) has a significant positive influence on Return On Asset and Operating Expense to Opeating Income (BOPO) has a significant negative influence on Return On Asset. Key words: Financial Performance, Commercial Banks, Core Capital Bank Group 3

Environmental sustainability and government health expenditure in Africa: is there a nexus?

PurposeThis study aims to explore the impact of environmental sustainability on government health expenditure in Africa for the period 2000–2021.Design/methodology/approachThe study employs the generalized method of moments (GMM) technique and utilizes a sample of 43 African countries.FindingsThe study reveals that carbon dioxide (CO2) emissions and renewable energy consumption have a positive relationship with health expenditure. For the control factors, we demonstrate that economic growth, urbanization and industrialization have a significant negative influence on health expenditure, while the impact of education on health expenditure is positive.Practical implicationsThe study proposes several policy recommendations, including prioritizing investment in renewable energy sources and promoting the use of cleaner energy sources such as wind, solar and hydroelectric power. These measures would help improve environmental quality and reduce government health expenditure.Originality/valueThe study contributes to the limited research on the relationship between environmental quality and health expenditure in Africa. Moreover, it goes beyond previous studies that only considered CO2 emissions and explores the impact of adopting cleaner energy sources on health expenditure.

Decoding depression: Analyzing social network insights for depression severity assessment with transformers and explainable AI

Depression is a mental state characterized by recurrent feelings of melancholy, hopelessness, and disinterest in activities, having a significant negative influence on everyday functioning and general well-being. Millions of users express their thoughts and emotions on social media platforms, which can be used as a rich source of data for early detection of depression. In this connection, this work leverages an ensemble of transformer-based architectures for quantifying the severity of depression from social media posts into four categories — non-depressed, mild, moderate, and severe. At first, a diverse range of preprocessing techniques is employed to enhance the quality and relevance of the input. Then, the preprocessed samples are passed through three variants of transformer-based models, namely vanilla BERT, BERTweet, and ALBERT, for generating predictions, which are combined using a weighted soft-voting approach. We conduct a comprehensive explainability analysis to gain deeper insights into the decision-making process, examining both local and global perspectives. Furthermore, to the best of our knowledge, we are the first ones to explore the extent to which a Large Language Model (LLM) like ‘ChatGPT’ can perform this task. Evaluation of the model on the publicly available ‘DEPTWEET’ dataset produces state-of-the-art performance with 13.5% improvement in AUC–ROC score.

Firm risk associated with environmental and corporate social disclosure: The moderating role of board gender diversity

AbstractThis study examines the relationship among corporate social and environmental disclosures, firm risk, and board gender diversity. This paper offers fresh insights into the relationship between corporate social and environmental disclosures and gender diversity and firm risk., Using panel data of Chinese nonfinancial A‐share‐listed companies from 2008 to 2020, we discover that the correlation between gender diversity on the board and corporate social and environmental disclosures has a significant negative influence on firm risk. The findings also revealed that the impact of gender diversity and corporate social and environmental disclosures is more pronounced to mitigate firm risk in nonstate‐owned enterprises than in state‐owned enterprises. For robustness, we used the generalized method of moments to control for reverse causality and endogenous variables' existence; the findings are similar to the main results. The study contributes to the literature by offering a contingency approach to examine the relationship between corporate social and environmental disclosures and firm risk and sheds light on the relationship in the context of a developing economy.

Nexus between boardroom independence and firm financial performance: evidence from South Asian emerging market

This study empirically investigates the linkage between boardroom independence and the financial performance of non-financial firms in an emerging market featured by family-controlled businesses and concentrated ownership. The relationship is tested in a sample of 152 non-financial firms listed on the Pakistan Stock Exchange over a period from 2003 to 2018. Firms’ financial performance is measured through return on assets (ROA), return on equity (ROE), market-to-book ratio (MBR), and Tobin’s Q (TQ), while boardroom independence is measured through the proportion of non-executive directors on the corporate board. Using the dynamic GMM approach to address the possibility of endogeneity, it was found that boardroom independence is significantly negatively related to the financial performance of the sample firms. This negative impact is due to the reason of close ties of outside independent directors (non-executive directors) with dominant shareholders and management in personal, financial, and social terms. A significant negative influence of the board size and CEO duality on firms’ financial performance was also observed. The present study will add to the existing literature on corporate governance and firm financial performance using firm-level manually collected data. Further, our findings will also help the policymakers by providing empirical insights for strengthening corporate governance mechanisms in emerging market economies, specifically in the context of Pakistan.

Proposed Marketing Strategy to Increase Repurchase Intention of Brand.ABC

This study aims to determine the extent to which Customer Satisfaction can affect Brand Loyalty. Customer Satisfaction can affect Repurchase Intention, and Brand Loyalty can affect Repurchase Intention at Brand ABC The sample of this research is 309 customer respondents who have purchased products at Brand ABC In this study, the authors used data collection methods through interviews and questionnaires. The data analysis technique in this study uses a validity test, reliability test and Structural Equation Modelling Partial Least Square (SEM-PLS) test. From the SEM-PLS test results obtained, BL = 0.981 CS + E1 and RI = -0.220 CS + 1.194 BL + E2., There is a strong and statistically significant positive influence between Customer Satisfaction and Brand Loyalty of Brand ABC customers. In addition, there is a strong and statistically significant negative influence between Customer Satisfaction and Repurchase Intention. Meanwhile, Brand Loyalty of Brand ABC customers has a positive and significant effect on their future Repurchase Intention.

Acceptance of voice assistant technology in dental practice: A cross sectional study with dentists and validation using structural equation modeling.

Voice assistant technologies (VAT) has been part of our daily lives, as a virtual assistant to complete requested tasks. The integration of VAT in dental offices has the potential to augment productivity and hygiene practices. Prior to the adoption of such innovations in dental settings, it is crucial to evaluate their applicability. This study aims to assess dentists' perceptions and the factors influencing their intention to use VAT in a clinical setting. A survey and research model were designed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). The survey was sent to 7,544 Ohio-licensed dentists through email. The data was analyzed and reported using descriptive statistics, model reliability testing, and partial least squares regression (PLSR) to explain dentists' behavioral intention (BI) to use VAT. In total, 257 participants completed the survey. The model accounted for 74.2% of the variance in BI to use VAT. Performance expectancy and perceived enjoyment had significant positive influence on BI to use VAT. Perceived risk had significant negative influence on BI to use VAT. Self-efficacy had significantly influenced perceived enjoyment, accounting for 35.5% of the variance of perceived enjoyment. This investigation reveals that performance efficiency and user enjoyment are key determinants in dentists' decision to adopt VAT. Concerns regarding the privacy of VAT also play a crucial role in its acceptance. This study represents the first documented inquiry into dentists' reception of VAT, laying groundwork for future research and implementation strategies.

Unethical Behaviour and Corporate Performance in University System: A study of Nigerian Private Universities

The study investigated whether there exists a relationship between unethical behaviour and corporate performance in the university system, and hence determined the impact of unethical behavior on corporate performance in the Nigerian university system with private universities as reference. A survey design was employed with a questionnaire instrument administered to 250 university staff drawn from four private universities in South-west, Nigeria, using a combination of purposive and random sampling techniques. The response data were analyzed using both descriptive and inferential analysis. The descriptive analysis showed that unethical behaviour exists in Nigerian private universities. A multivariate Partial Least Squares Structural Equation Model (PLS-SEM) was used for the inferential analysis and to specify the relationships among the construct variables in the study. The bootstrapping technique of the PLS-SEM was used to estimate the parameters in the model, with the aid of the Smart-3 software. The result of the factor loadings, reliability test, convergent and discriminant validity revealed that the construct variables are fit for the PLS-SEM. The path analysis revealed that financial malpractices are a major unethical behavior affecting corporate performance adversely. Furthermore, unethical behaviours from university staff and university administration have significant negative influence on corporate performance. The study concludes that unethical behaviour is a key driver of poor corporate performance in the Nigerian university system. Therefore, it is recommended that policy makers in the university should adopt a holistic approach to ethical management that is oriented toward zero tolerance for unethical behavior in the university system

When Agency Fails: An Analysis of the Association Between Hospital Agency Staffing and Quality Outcomes.

Staffing is critical to hospital quality, but recent years have seen hospitals grappling with severe shortages, forcing them to rely on contract or agency staff for urgent patient care needs. This shift in staffing mix has raised questions about its impact on quality. Consequently, this study investigated whether the increased use of agency staff has affected healthcare quality in hospitals. Given the limited recent research on this topic, practitioners remain uncertain about the effectiveness of their staffing strategies and their potential impact on quality. Drawing from agency theory, data were obtained from Definitive Healthcare which consolidates information from numerous public access databases pertaining to hospitals such as the American Hospital Association Annual Survey (hospital profile) and the Hospital Value-Based Purchasing Program (quality data). We conducted a cross-sectional study using a multivariable linear regression model (2021-2022) with appropriate organizational and market- level control variables. Quality was measured across eight variables while the independent variable of interest was agency labor cost ratio operationalized as the percentage of net patient revenue consumed by agency labor expense. Our results suggested that the employment of agency staff was significantly and negatively associated with six of eight quality measures tested, including the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) star rating, Hospital Compare rating, the hospital Total Performance Score (TPS), and three of the four sub-domains that comprise the TPS: clinical domain score, person and community engagement domain score, and the efficiency and cost reduction score. Our results indicated that the increased use of agency labor may have a significant negative influence on quality outcomes at the hospital level. Our findings support the premise that interventions that promote full-time staffing may be more supportive of the quality of care delivered as well as patients' perceptions of care.

Kemiskinan Perkotaan dan Angka Partisipasi Pendidikan Tinggi di Indonesia

This research aims to investigate the relationship between urban poverty and higher education participation in Indonesia using time series data during the 1998-2021 period. The analytical model used is simple linear regression which is then estimated using the ordinary least squares (OLS) approach. Through empirical data analysis, this research finds that urban poverty has a significant negative influence on higher education participation, indicating that high levels of poverty in urban environments can be a barrier to higher education access and participation for economically marginalized communities.

Clarifying the levers of carbon emission reduction in compact cities in China: A multi-sectoral approach

Compact city policies have gained global attention for their potential to combat urban sprawl, conserve suburban open spaces, reduce energy consumption, and cultivate vibrant urban living environments. While these policies are widely believed to contribute to urban low-carbon objectives, empirical evidence has been lacking. This study focuses on the pivotal elements of compact city development, investigating impacts on sectoral urban carbon emissions and uncovering spatial heterogeneity. The research outcomes affirm that density and accessibility indicators exert significant negative influences on carbon intensity for the energy, industrial, household, and transportation sectors. While public transport, despite its fundamental role in compact city theory, does not show effectiveness in reducing urban carbon emissions as expected. The study highlights that as an approach toward achieving urban sustainability under the scope of climate change adaptation, compact city development strategies necessitate a careful balance in their application. Further, we underscore the importance of complementing compact city policies with greener energy strategies to effectively realize low-carbon urban transportation goals.

ALZHEIMER’S DISEASE DETECTION USING DEEP LEARNING

Image processing is a technique for applying various procedures to a picture in order to improve it or extract some relevant information from it. It is a kind of signal processing where the input is an image and the output may either be another picture or features or characteristics related to that image. Image processing is one of the technologies that is currently expanding quickly. It is a primary subject of research in both the engineering and computer science fields. For dementia, Alzheimer's disease (AD) is the most prevalent kind. It often shows itself as a steadily declining memory and cognitive function, which makes it difficult for the affected person to live independently and has a significant negative influence on both the affected personand society. At the moment, AD diagnosis depends on medical history analysis, blood testing, behavior analysis, brain imaging, and cognitive testing. But because these processes are arbitrary and uneven, it is difficult to provide a precise forecast for the early phases of AD challenging. A dynamic dual-graph fusion convolutional network is suggested in this paper to enhance the accuracy of Alzheimer's disease (AD) diagnosis. The key contributions of the paper are as follows: The proposed architecture can dynamically adjust the graph structure for GCN to produce better diagnosis outcomes by learning the optimal underlying latent graph, propose a novel dynamic GCN architecture, which is an end-to-end pipeline for diagnosing AD, incorporate feature graph learning and dynamic graph learning, giving those useful features of subjects more weight while reducing the weights of other noise features. Experiments show that our approach achieves great classification results in AD diagnosis while offering flexibility and stability. This project is implemented for the Alzheimer disease classification using Graph convolutional network architecture like CNN with LSTM layer and fit the model in the training and testing and deploy the model for getting the test image output and then compare the accuracy of the model for getting the most perfect model for medical image classification and get theaccuracy of CNN- LSTM layer with 98%.

The Impact of Financial Ratios on Profit Growth of Public Health Sector Companies

The purpose of this research is to determine the influence of Debt to Asset Ratio, Total Asset Turnover, and Return on Asset on the profit growth of public healthcare sector companies listed on the Indonesia Stock Exchange during the period of 2017-2021. The population of this study consists of public healthcare sector companies listed on the Indonesia Stock Exchange. The sample was determined using purposive sampling technique, and the selected sample consists of 3 public healthcare sector companies. The data analysis technique used in this research is panel data regression analysis with the assistance of EViews 12 software. The research findings indicate that the variable Debt to Asset Ratio does not have a significant influence on profit growth, Total Asset Turnover has a significant negative influence on profit growth, while the variable Return on Asset has a significant positive influence on profit growth. Keywords: Debt to Asset Ratio, Total Asset Turnover, Return on Asset, profit growth, healthcare sector

Urban industrial land misallocation and green total factor productivity: Evidence from China's Yellow River Basin regions

AbstractThis study aims to investigate the repercussions of urban industrial land misallocation on green total factor productivity (GTFP) within the context of China's Yellow River Basin regions. Utilising data from 99 prefecture‐level cities over the period from 2007 to 2020, the analysis reveals that the misallocation of urban industrial land exhibits regional variations and exerts a significant and persistent negative influence on GTFP, with notable regional disparities. Further analysis shows the mechanism of this effect is the obstacle to urban innovation due to industrial land misallocation. In addition, education expenditure plays a moderating role both directly and indirectly. These findings imply the need to continuously improve the performance evaluation and financial system of local governments, reduce government intervention, and make use of the market mechanism in the allocation of urban industrial land.

Is tax avoidance one of the purposes of financial data manipulation? The case of Romania

PurposeCompanies avoid taxes in a variety of ways and use different methods to do that, one of the most common being earnings management. The purpose of this paper is to investigate whether companies manipulate their financial data in order to reduce taxes paid.Design/methodology/approachWe considered a sample of 63 listed Romanian companies for the period 2016–2021. The Beneish model was used for estimating earnings management, and the effective tax rate was used to measure tax avoidance. The analysis was carried out using regression analysis in Stata13 software.FindingsThe findings of the research indicate a negative and statistically significant association between effective tax rate and earnings management, implying that one of the main reasons why companies manipulate their earnings to reduce tax burden and avoid taxes. Moreover, our results show that return on assets (ROA) has a statistically significant negative influence on the effective tax rate. Furthermore, our analysis reveals that firm size, growth, and Big4 audit have no effect on effective tax rate.Research limitations/implicationsBecause it analyzes concrete cases using financial data and provides some recommendations for addressing the issue of tax avoidance, this work is useful in advancing both quantitative and qualitative research on this topic. This research is relevant for businesses, governments, regulators, audit professionals and investors.Originality/valueThe study, by analyzing concrete cases using reported financial data, contributes in filling the gap within the literature that results from a lack of scientific research on the relationship between tax avoidance and earnings management, and then it clarifies the nature of the causal connection between them. Moreover, it considers a combination of firm related variables including performance, size and also audit quality.

Peningkatan Trust Berbelanja Online pada Mahasiswa Perguruan Tinggi di Wilayah Bandung Berbasis Information Privacy Concern Dan Privacy Policy

Before entering the era of online shopping, previously information systems were only intended for internal company parties such as company employees. In this era of artificial intelligence, accounting information systems are also operated by consumers. Consumers operate information systems to be able to complete purchases of goods or services online. Based on research results through mass media, it is known that consumers' current shopping tendencies are more towards shopping online. The reason consumers tend to prefer shopping online is because the prices offered by online companies are cheaper and they save time shopping. When consumers make online shopping transactions, concerns arise about sharing personal data with e-commerce companies. These concerns include the use of consumers' personal data by e-commerce companies. This research is descriptive verification research using a survey approach. This research is classified as quantitative research. The respondents who will be studied in this research are students spread across universities in the city of Bandung. The data analysis method uses SEM-PLS. The results of the research show that information privacy concerns have a significant negative influence on trust, privacy policy has a significant positive influence on trust and simultaneously information privacy concerns and privacy policy have a significant positive influence on trust. So it can be concluded that if there is an increase in information privacy concerns and privacy policies, it will have an impact on increasing trust in online shopping for university students in the Bandung City area.

Beyond conventional: Analysing the factors affecting the adoption of electric four-wheelers in an Indian metropolis

This study develops an integrated choice and latent variable (ICLV) model to analyse the impact of vehicle attributes, service attributes and supporting government schemes on the likelihood to choose an electric four-wheeler in Bengaluru, India. Further, the influence of socio-demographic variables, travel attributes and latent factors on electric four-wheeler adoption behaviour is also evaluated. The findings indicate purchase price, operating cost, and charging time have a significant negative influence on the intention to adopt electric four-wheelers, while driving range and charging facilities have a significant positive impact. Perceived risks studied in the context of safety and reliability are found to be the biggest barriers to the adoption of electric vehicles followed by lack of infrastructural readiness while environmental benefits are found to be the biggest motivators for electric four-wheeler adoption. These findings are expected to help decision-makers towards widespread adoption of electric four-wheelers in developing economies such as India.

The Effect of Tax Avoidance on Cost of Debt with Institutional Ownership as a Moderating Variable (Empirical Study of Energy Sector Companies Listed on The IDX 2020-2022)

This research aims to test the effect of tax avoidance on the cost of debt with institutional ownership as a moderating variable. In this research, tax avoidance is measured by the effective tax rate. The population in this research is energy sector companies listed on the Indonesia Stock Exchange for the 2020-2022 period. This type of research is quantitative research. The sample in this research was obtained using purposive sampling, namely selecting samples using predetermined criteria. Based on the purposive sampling method, 57 samples were obtained from 82 energy sector companies listed on the Indonesia Stock Exchange for the 2020-2022 period. The analytical methods used are simple linear regression analysis, Moderated Regression Analysis, partial test (t), and coefficient of determination test (R2) using the SPSS version 16 program. The results of this research show that tax avoidance has a significant negative influence on cost of debt. Institutional ownership can strengthen the tax avoidance and cost of debt variables.