Asset Efficiency Research Articles

Assessing Financial Health: Impact of Current Ratio, Debt Equity Ratio, Return Assets on Banking Sector Returns

This study provides modern insights into the impact of Current Ratio, Debt-to-Equity Ratio, and Return on Assets on stock returns in the banking sector listed on the Indonesia Stock Exchange during 2018–2022. Unlike previous studies that indicated a positive relationship, this study found that these three factors had a negative and significant impact on stock returns. These findings underscore the need for more effective regulatory strategies to manage financial ratios and enhance the attractiveness of stocks in the capital market. A quantitative approach emphasizing numerical data analysis was employed. The study involved 10 conventional commercial banks. Secondary data was used, and it was determined that there were no symptoms of heteroscedasticity. Multiple linear regression analysis revealed that the independent variables Current Ratio, Debt-to-Equity Ratio, and Return on Assets negatively influenced the dependent variable, Stock Returns. The study emphasizes the importance of regulatory recommendations for banking companies to improve asset efficiency and maximize profits to attract higher stock demand. Additionally, the results provide valuable insights for investors, helping them consider financial factors for more informed investment decisions.

Enhancing Financial Decision-Making Through Automated Business Intelligence Systems

In today's competitive IT market, integrating BI tools is crucial for optimizing financial data analysis and decision-making. This study focuses on an automated approach: constructing a robust data warehouse, segmenting data with a hybrid method, and applying advanced data mining for processing complex financial data. The research showcases significant impacts across Metric Companies A, B, and C, which operate in Company A achieved a 15% revenue growth through real-time financial analysis and trend identification, while Company B improved profitability by 20% via insights into cost management and strategic pricing adjustments. Additionally, Company C enhanced asset efficiency and financial performance by 25% by optimizing asset allocation strategies. This study emphasizes the pivotal role of automated BI systems in enhancing financial performance and decision-making across various organizational contexts.

Analisis Laporan Keuangan Perbandingan Kinerja Keuangan Perusahaan Sektor Perdagangan di Indonesia (Studi pada PT. Alfamidi PT. Alfamart PT. Indofood PT. Hero Supermarket Periode 2019-2023)

This research aims to analyze the financial performance of trade sector companies in Indonesia, specifically PT. Alfamidi, PT. Alfamart, PT. Indofood, and PT. Hero Supermarket, in the period 2019-2023. This study uses a variety of financial ratios as a measuring instrument for assessing company performance, such as liquidity ratios (current ratios and quick ratios), activity ratios (receiving receivables, inventory, and fixed assets), and profitability ratios (profit margins, returns on assets, and return on equity). Through comparison of these ratios, this study aims to provide a comprehensive picture of the efficiency, profitability, and financial stability of each company. The results of the analysis show that PT. Hero Supermarket has a relatively superior performance in terms of return on equity (ROE) and return on assets (ROA), while PT. Indofood faces challenges in maintaining profitability and asset efficiency. PT. Alfamidi and PT. Alfamart showed stable performance even though he still had room for improvement in operational efficiency. This finding provides useful insights for stakeholders in making investment decisions as well as for these companies in formulating better financial management strategies in the future.

BASEL III LIQUIDITY REQUIREMENTS AND BANK PROFITABILITY

This paper examines the impact of Basel III liquidity requirements, specifically the Liquidity Coverage Ratio (LCR) and the Net Stable Funding Ratio (NSFR), on the profitability of banks in Nigeria, using regression discontinuity design (RDD) to analyze data from 14 banks over the period from 2009 to 2020. The study provides empirical insights into how these regulations influence bank performance, focusing on return on assets (ROA) and return on equity (ROE). The results reveal that the LCR has a significant positive impact on ROA, indicating that holding adequate high-quality liquid assets improves asset efficiency. However, its effect on ROE is insignificant, suggesting that enhanced liquidity does not necessarily translate into higher returns for shareholders. Similarly, the NSFR shows a significant positive impact on ROA but an insignificant effect on ROE, highlighting the benefits of long-term funding stability for asset profitability without significantly boosting shareholder returns. These findings suggest that while Basel III liquidity requirements contribute to enhancing bank stability and operational performance, they may not immediately result in higher equity returns in the Nigerian context. The study recommends that banks optimize their capital allocation and liquidity management strategies to achieve a balance between regulatory compliance and shareholder value. Additionally, regulators, particularly the Central Bank of Nigeria (CBN), should periodically review liquidity requirements to reflect the unique challenges of the Nigerian banking environment. This study contributes to the existing literature by providing empirical evidence on the impact of Basel III liquidity requirements on bank profitability in the Nigerian context. The use of Regression Discontinuity Design offers a robust approach to identifying causal effects, enriching the understanding of how liquidity management practices affect financial performance, particularly in emerging markets where liquidity risks are more pronounced.

Analysis of Sustainable Growth Rate in Manufacturing and Construction Firms: Evidence from Selected Western Balkan Countries

This research’s primary goal is to examine the factors influencing organizations’ sustainable growth rates (SGR) between 2013 and 2022. A panel regression analysis was done to extensively assess the variables linked with SGR. The study included data from 92 manufacturing and construction companies in selected Western Balkan countries, resulting in a dataset of 1,012 observations. According to the study, asset efficiency and sales growth have a positive and significant impact, while leverage negatively impacts the SGR. These results are important to companies because they provide useful insights that can help them achieve their planned SGR. Management can make informed decisions to improve business performance by better understanding the impact of factors such as asset efficiency, leverage ratio, and sales growth on SGR. This informed decision-making not only ensures a healthy growth path but also helps avoid major financial problems. The study underlines that the findings serve as a significant tool for business management in long-term planning and strategy formulation. By providing insight into the company’s growth goals and prospects, this congruence also benefits numerous internal and external stakeholders. Additionally, it makes it possible to examine the company’s overall business situation more precisely and helps forecast its long-term performance.

Analisis Rasio Keuangan pada PT. Bank BCA, PT. Bank BNI, PT. Bank Mega, PT. Bank BRI di Indonesia Periode Tahun 2019-2023

This study aims to analyze the financial performance of four major banks in Indonesia, namely PT Bank Central Asia (BCA), PT Bank Negara Indonesia (BNI), PT Bank Mega, and PT Bank Rakyat Indonesia (BRI), during the period 2019–2023. The analysis was conducted using financial ratios that include liquidity (current ratio, quick ratio), profitability (return on assets, return on equity), solvency (debt to equity ratio, debt to total asset ratio), efficiency (net interest margin), and market ratio (price to earnings ratio, dividend yield). This study uses a descriptive qualitative method with secondary data obtained from annual financial reports. The results of the study show significant differences in financial management among the banks analyzed. Bank BNI stands out in terms of liquidity, while Bank BRI excels in profitability and asset efficiency. Bank BCA shows good financial stability, while Bank Mega dominates in market attractiveness and dividend policy. However, each bank also faces challenges, such as low asset efficiency at Bank BNI, performance fluctuations at Bank BRI, and challenges in increasing profitability at Bank BCA.

PRESCRIPTIVE MAINTENANCE ON THE FACTORY FLOOR: ANALYTICAL THEORETICAL REFLECTION

Purpose: Analyze the perceptions of researchers and experts in the implementation of Prescriptive Maintenance on the factory floor in companies located in Espírito Santo, Southeast Region of Brazil considering the strategies recommended by carrying out the SWOT analysis. Methodology/Approach: The methodological procedures used were a combination of three data collection mechanisms, a bibliographical research, considering the impacts of Prescriptive Maintenance on the factory floor and an empirical work, by sending a questionnaire to researchers and experts to analyze their perceptions. Furthermore, the application of the SWOT analysis (Strengths, Weaknesses, Opportunities and Threats) to evaluate the strategic considerations arising from said analysis. Findings: The study provides recommendations for managers and professionals working on the factory floor, showing the needs for improvement in maintenance tasks that is, considering the strategic impacts of Prescriptive Maintenance and the importance of digitizing the factory floor. Research, practical & social implications: The results of this study offer valuable perspectives for the formulation of strategic policies aimed at attracting the efficiency of physical assets. They also have important implications for Maintenance Management and can serve as a reference for future studies on the topic. Originality/ Value: Based on the data obtained, the authors present the importance of organizational synchronization between different sectors of companies considering the systemic view, therefore, recommending this model for small companies, due to the existence of barriers in the implementation of technological modernization in companies of this size using new methodologies of research.

Perbandingan Kinerja Antar 3 Perusahaan pada PT Gudang Garam Tbk, PT HM Sampoerna Tbk dan PT Indonesia Tobacco Tbk Periode 2019-2023

This study discusses the comparison of the financial performance of three tobacco companies in Indonesia, namely PT Gudang Garam Tbk, PT HM Sampoerna Tbk, and PT Indonesia Tobacco Tbk in the 2019-2023 period. The analysis was conducted using financial ratios including liquidity, activity, solvency, profitability, and market to evaluate the operational performance and financial structure of each company. The results showed that PT HM Sampoerna Tbk consistently had the best performance in terms of operational efficiency, profitability, and solvency. Meanwhile, PT Gudang Garam Tbk excels in dividend policy, despite facing challenges in asset efficiency and profitability. PT Indonesia Tobacco Tbk, despite showing improvement in some solvency ratios, still faces high financial risk and low operational efficiency. This study provides important insights for investors and stakeholders to understand the competitive position and opportunities for improvement of corporate strategies in the tobacco industry.

THE INFLUENCE OF ASSET EFFICIENCY, FINANCIAL PERFORMANCE, AND FINANCIAL LEVERAGE ON SUSTAINABLE GROWTH RATE THROUGH GOOD CORPORATE GOVERNANCE

This study aims to examine the Effect of Asset Efficiency, Financial Performance and Financial Leverage on Sustainable Growth Rate Through Good Corporate Governance. This study is classified as an associative quantitative study. The type of data used is secondary data obtained from www.idx.co.id and the company's website. The population in this study is the Manufacturing Companies in the Consumer Goods Industry Sector listed on the IDX for the 2018-2022 Period. While the sample of this study was determined by the sampling technique used in this study is non-probability sampling, namely purposive sampling so that 20 sample companies were obtained that met the criteria. The analysis method used is Panel Data Model Regression analysis. The results of this study indicate that asset efficiency does not affect the Sustainable Growth Rate (1), financial performance does not affect the Sustainable Growth Rate (2), financial leverage affects the Sustainable Growth Rate (3), asset efficiency affects Good Corporate Governance (4), financial performance affects Good Corporate Governance (5), financial leverage affects Good Corporate Governance (6). Sustainable Growth Rate has an effect on Good Corporate Governance (7), Asset Efficiency does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (8), Financial Performance does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (9), Financial Performance does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (10). Leverage does not have a significant effect on the Sustainable Growth Rate variable through the Good Corporate Governance variable (10).

Ratio Analyses Estimating Financial Risk: Econometric Study Retail Companies the Indonesia Stock Exchange 2020-2023

Aims: This study analyses the effect of activity ratios, sales growth, profitability, and company size on the financial distress of retail companies on the Indonesia Stock Exchange from 2020 to 2023. Study Design: The study uses data on activity ratios, sales growth, profitability, and company size as independent variables and financial distress as the dependent variable. Place and Duration of Study: The research was conducted in retail companies listed on the Indonesia Stock Exchange with a population of retail company subsectors and using purposive sampling criteria. The research data used financial reports published in 2020-2023. Methodology: This type of research is quantitative. The research was tested with SPSS 25 using logistic regression. The total population in the study was 32 types of companies in the retail subsector with several types of companies such as drug retail & distributors, food retail & distributors, supermarkets & convenience stores (minimarkets), department stores, apparel & textile, automotive retail, and electronic retail. Purposive sampling obtained 108 unbalance data for 4 years of observation listed on the Indonesia Stock Exchange in 2020-2023 financial distress was tested with the Altman Z-Score method through logistic regression test. Result: Utilizing logistic regression and the Altman Z-Score, the study reveals that activity ratios and profitability significantly negatively affect financial distress, while sales growth and company size do not have a significant impact. Conclusion: These findings provide valuable insights for stakeholders, emphasizing the importance of optimizing asset efficiency and profitability to mitigate financial distress.

COST BENEFIT ANALYSIS UNDER MIXED CROPPING SPECIAL CONTEXT WITH COCONUT, ARECA NUT, PEPPER, BANANA AND PINEAPPLE -CASE STUDY DAKSHINA KANNADA DISTRICT

One of the essential elements of sustainable agriculture in Dakshina Kannada involves Mixed cropping System. This cropping system includes various crops such as coconut, areca nut, banana, pineapple and pepper. This paper analyses the cost-benefit mechanisms of these structures, concentrating on their environmental, social, and economic consequences. Coconut-centred multi cropping utilises the corresponding expansion structures of intercrops, enhancing land usage and asset efficiency. Financial analysis examines the improved earning capacity of multi cropping due to diversified income avenues along with decrease in reliance on a mono plantation. Ecological advantages include enhanced soil health, dec5rease in soil erosion, and enhanced water maintenance, providing to enduring environmental balance. These structures offer enhanced job prospects and nourishment safety, encouraging flexibility in agrarian societies Moreover, disputes such as labour severity, increase in foundational costs, and wider market reach for multicrops pose challenges to implementation. Moreover, disputes such as pest and disease management, employee scarcities, and market price volatility pose restrictions to wider implementation. The results highlight the necessities for farmer training, targeted policy interventions, and infrastructure growth to unlock the full potential of integrated harvesting in the areas like Dakshina Kannada. KEYWORDS: Mixed Cropping System, Cost Benefit Analysis, Environmental Impact, Integrated Harvesting

The mechanism of cryptocurrency adoption as a means of payment in business

This article examines the theoretical foundations and conceptual specifics of the mechanism for adopting cryptocurrencies as a payment method in business. It discusses the definition and key features of this mechanism, along with summarizing essential recommendations for the use of cryptocurrencies and crypto assets in business payments. The cryptocurrency adoption framework is analyzed through the organizational–economic mechanism, aiming to achieve practical objectives such as cost reduction, improved access to cross–border payments, and transaction security with crypto assets. The article stresses the importance of risk analysis related to cryptocurrency use and the development of risk mitigation methods through proactive management and the application of appropriate tools. The conclusions highlight the feasibility and benefits of using an organizational–economic mechanism to incorporate crypto assets into business payment processes, ensuring efficiency and adaptability of crypto assets or other alternative payment instruments. The study’s novelty lies in its contribution to the development of a mechanism for integrating cryptocurrencies into business operations, while its theoretical value is in the synthesis and clarification of key issues related to cryptocurrency acceptance in business. The proposed concept and vision of the organizational–economic mechanism to enhance the efficiency of cryptocurrency use in business payments offer valuable insights for future research and practical implementation.

Development of a methodology for diagnosing faults in bearings operating under variable operating conditions based on self-supervised learning

Predictive maintenance plays a crucial role in ensuring the efficiency and availability of industrial assets. Bearings, essential components in rotating machinery, are subject to diverse and complex operating conditions, necessitating advanced fault diagnosis methods. Traditional diagnostic approaches often rely on supervised learning, which requires extensive labeled datasets, a process that is both costly and impractical under varying conditions. This work proposes a novel methodology for diagnosing bearing faults using self-supervised learning, which leverages unlabeled data to generate useful representations for fault detection. The proposed approach aims to develop an end-to-end system that processes raw vibration signals to accurately diagnose the current state of bearings, including fault detection, localization, and severity assessment. The methodology is validated using experimental data from a test rig simulating various fault conditions and will be further tested on real industrial machinery. This research contributes to the development of more efficient and generalizable diagnostic tools for rotating machinery, particularly under variable operational conditions.

FOREX EFFICIENCY AND FINANCIAL PERFORMANCE OF INDIAN DEFENCE COMPANIES – EXAMINING CONNECTION

This study explores the impact of financial performance on forex efficiency of the selected Indian Defence companies. To meet this objective the sample of five companies selected from nifty defence index based on availability of data. This research uses a descriptive research design and the analysis spans over ten years from April 2014 to March 2024. The financial performance indicators, including profitability, liquidity, asset efficiency, and solvency are examined in relation to forex efficiency through correlation and panel regression analysis. This research aims to address two key questions: the overall relationship between financial performance and forex efficiency in selected Defence companies and the influence of selected financial indicators on forex efficiency. The previous studies have explored related themes but they have not specifically targeted the Defence sector or detailed how particular financial indicator impact forex efficiency. This study fills this gap by providing a meticulous analysis of how financial performance influences forex efficiency. This contributes in valuable insights for strategic financial management and policy formulation in the Defence industry.

Development of Information System for Asset Management

An information system for asset management in a university is very important, especially in a faculty with many majors. There are a lot of assets, including laboratories and items inside. In this research, the authors present the development of an information system using feature-driven development (FDD) methodology, which is one of the agile methods, giving flexible and collaborative methods prioritizing main users. To communicate between stakeholders, the development of initial models using UML diagrams, such as use case diagrams, sequence diagrams, and deployment diagrams. The modules on this asset management website are administration for building and room data, asset categorization, asset search, and asset maintenance and problem reporting. The website was developed using PHP with a Laravel framework and MySQL database. This website is beneficial for increasing the efficiency of assets, with future development involving more advanced technology.

ANALISIS EFISIENSI, KUALITAS ASET DAN STABILITAS BANK PEMBANGUNAN DAERAH SEBELUM DAN SESUDAH KONVERSI MENJADI BANK SYARIAH

This study aims to compare the efficiency, asset quality and stability of regional development bank before and after conversion to Islamic banks. This research is classified as a comparative descrictive research. The population of this study is Islamic commercial banks in Indonesia.The type of data used is secondary data obtained from financial reports uploaded on each bank's website and the OJK website. The sampling method is Purposive Sampling with quarterly reports of Aceh Bank and NTB Bank, each 15 before conversion and 15 after conversion, so a total of 30 samples before and 30 samples after. Efficiency variables use the ratio of CIR (Cost Income Ratio), Quality with APB (Problematic Earning Assets) and Stability with EAR (Equity to Asset Ratio). Testing data analysis using Paired T test, while the normality test using Shapiro-Wilk and Wilcoxon. Based on the results of the analysis and testing, it can be concluded that there are insignificant differences in the efficiency and quality of assets but there are significant differences in stability. The efficiency of the bank before conversion is higher than after but the asset quality and stability of the bank after conversion is highe

Dupont System Analysis For Measure Financial Performance At Automotive Component Industry In Indonesia

The purpose of this study is to evaluate the financial performance of several automotive component industry companies in Indonesia. The research used of descriptive-quantitative research method, the research of attempted to collect and present data from companies for analysis so as to provide a fairly clear picture of the object under study. The type of data used in this research is quantitative data, namely data in the form of explanations or statements in the form of numbers, namely financial reports from several companies listed on the Indonesian Stock Exchange which are used as the population in the research, including; AUTO, ASII, DRMA, BOLT, SMSM, GJTL and INDS for the 2019-2023 period. By using the Dupont system method as an analysis method. Analysis of the Dupont system method also shows that factors such as net profit margin, asset efficiency and financial leverage influence the financial performance of companies in the automotive components industry. The results of this research explain how the dupon system determines between six similar companies providing company performance data in terms of Net Profit Margin (NPM), Total Asset Turn Over (TATO), Equity Multiplier (EM) and Return on Equity which can be used by potential investors in investing in automotive component industry companies in Indonesia.

The Importance of Cybersecurity and Protecting of Digital Assets and Understanding the Role of Cybersecurity Laws in Safeguarding Digital Assets

In the technologically advanced landscape, companies increasingly leverage cutting-edge technology to enhance operations. However, this progression also amplifies the risk of cyberthreats. Cybersecurity emerges as a pivotal element for safeguarding digital assets, encompassing networks, financial data, intellectual property (IP) and personal information. This note underscores the significance of shielding digital assets from cyberassaults, providing actionable guidance for individuals and businesses. Cybersecurity regulations play a vital role, establishing protective frameworks for sensitive data, IP and critical infrastructure. Compliance with these standards bolsters confidence, national security and global cooperation, elevating cybersecurity consciousness. Amid our digitally driven culture, prioritising cybersecurity ensures the safety and efficiency of digital assets. Implementing robust protocols fortifies individuals and organisations against online threats, facilitating secure navigation of the digital realm while upholding data integrity.

Physics-guided federated learning as an enabler for digital twins

Digital twins bring the potential to increase the efficiency of assets, systems, and processes by building virtual replicas through real-time data and modeling. However, data are often confidential and distributed, high-fidelity models based on physical principles tend to be slow and require detailed knowledge about the asset design that may not be available, simplified models lack accuracy, and data-driven models are not interpretable and limited to their training space. We demonstrate the interplay of two enabling technologies, namely federated learning and hybrid analysis and modeling, to combine the strengths of physics-based and data-driven models on distributed data sets that are kept confidential by different stakeholders. Throughout the work, an ensemble of physics-guided neural networks is designed, optimized, and validated to infer the parameters of digital twin components. The physics-guided neural network is injected with output from a simplified physics-based model in intermediate layers for increased performance, and the injection layer is optimized through weight regularization. The model is then integrated into a simulation of the digital twin asset and validated there. It is shown that the model outperforms the simplified physics-based and the data-driven models both on component and on asset level. In the final step, the physics-guided neural network is trained using federated methods, which allows training on confidential data owned by different stakeholders without requiring the stakeholders to share their data. We show that federated hybrid models can – with the right training strategy – by design achieve results that are always identical and potentially superior to models trained on a central data set. The problem chosen for this demonstration is the prediction of airfoil lift and drag coefficients based on the airfoil shape and the angle of attack, which is a task crucial for simulating wind turbines. Using the physics-guided neural network, the estimation of the airfoil coefficients experiences a speedup of several orders of magnitude compared to the high-fidelity simulation, and integration into blade element momentum theory shows that the turbine thrust, torque, and mechanical power can be accurately calculated. The federated approach makes it possible to extend the training of the model to any number of distributed confidential data sets from both simulations and experiments to further increase the model’s accuracy.

The Impact of Low-Carbon Pilot City Policy on Corporate Asset Efficiency: Evidence from China's A-Share Listed Companies

This study employs machine learning and the difference-in-differences (DID) approach to analyze the impact of China's "Low-Carbon City" pilot policy on the asset efficiency of A-share listed companies. The findings indicate that the policy has generally suppressed corporate asset efficiency, particularly in state-owned enterprises and large-scale companies. The study also reveals that the policy's impact is not significant in enterprises located in the eastern regions. Further robustness checks are conducted through predictive analysis using the random forest model, confirming the stability of the results. This research provides a basis for optimizing low-carbon policies and is of significant importance for promoting corporate low-carbon transformation and sustainable economic development.