Level Of Assets Research Articles

Bank Specific Factors on the Financial Performance of Commercial Banks in Nepal

Purpose-This study examines the bank-specific factors and financial performance of commercial banks in Nepal. The study period of Nepalese banks’ performance during a period ranging from 2013 to 2023. Design/methodology/approach- Descriptive research design has been used in analyzing the performance of commercial banks. Banks' performance is measured in terms of ROA, ROE, and NIM. Profitability has been taken as the proxy of performance of banks in this study. Based on the findings of the study. Findings- Nepali commercial banks are performing moderately. They are not able to increase their performance level significantly. Their performance measured in terms of profitability is not very satisfactory. However, observing the significant decrease in level of non-performing assets, it is concluded that the internal management, credit policy, and business management aspects of the Nepalese commercial banks have been improving. On the other hand, Nepalese commercial banks are well-capitalized and do not have solvency problems. Because of maintaining an adequate capital adequacy ratio, they have the capacity to absorb unexpected losses and safeguard the depositors, investors and creditors. Original/Value- Few studies have addressed the interplay of microfinance on poverty alleviation in Nepali context.

Aspirational Revolution or Aspiration Failure? Gendered Effect of Household Wealth on Educational Aspirations in China

ABSTRACTThis study investigates the gendered impact of household wealth on children's educational aspirations in China. Using two waves of longitudinal survey data of Chinese households from 2012 and 2016, we find that household assets have a differential impact on girls' and boys' educational aspirations. Household assets have a significant and positive impact on girls' aspirations for higher education, especially for graduate school, whereas boys' aspirations remain relatively stable across asset levels. We also demonstrate that this positive impact of household assets on girls' educational aspirations is limited to girls with same‐sex siblings. Girls with sisters are more likely to report an increase in aspirations for higher education with increasing levels of household assets. Conversely, for girls with brothers, household assets have a negative impact on their aspirations for higher education. Our findings suggest that traditional gender norms and family investment strategies play a critical role in shaping educational aspirations, particularly in families with both sons and daughters.

Analisis profitabilitas dalam isu perubahan iklim global pada CV. Kelapa Inti Murni

Climate change is a global issue that remains a significant topic of discussion among many countries, including Indonesia. This is clearly expected to impact companies in areas such as sales and company profits. To analyze the risks and opportunities related to climate change on the profits generated by a company, it is essential to measure using profitability ratios. Profitability measures a company’s ability to generate profit from a certain level of sales, assets, and equity capital. This study aims to analyze the profitability in the context of global climate change issues at CV. Kelapa Inti Murni. This research is qualitative with a descriptive approach. The types of data used are quantitative and qualitative. Data sources include primary and secondary data. Data collection methods used are observation, interviews, and document analysis. The data analysis method employs profitability ratios. The research findings indicate that profitability at CV. Kelapa Inti Murni is related to climate change. If there is a climate change event such as excessive heat, the company's profitability is expescted to decrease due to reduced sales or minimal profits. Overall, the company's profitability is considered quite good as it is above the industry average, except for return on equity which remains below the industry average standard.

SPEED OF ADJUSTMENT OF CAPITAL STRUCTURE IN LISTED COMPANIES ON THE INDONESIA STOCK EXCHANGE

This study aims to analyze the speed of adjustment of capital structure in companies listed on the Indonesia Stock Exchange (BEI) by considering key variables such as SoA, Distance, Profitability (RoA), Growth, and Tangibility. SoA refers to the speed at which companies adjust to their target capital structure, and the results indicate that companies in Indonesia have not yet reached an optimal capital structure target. Distance reflects the difference between the actual and target capital structure, while profitability reflects the financial performance of the company. Growth and Tangibility refer to company growth and the level of tangible assets that can be pledged as collateral. This study involved 717 companies listed on the BEI from 2020 to 2022, with 2020 as the estimation period and 2021-2022 as the research period. The One Sample t-test with a test value of 1 and multiple linear regression analysis with classical assumption testing were employed to examine the relationship between these variables and SoA. Each variable that has been used in this study shows that the speed of adjustment of capital structure in companies listed on the Indonesia Stock Exchange is not at the optimal target. Of the five hypotheses made, it turns out that only three hypotheses were accepted while the other two hypotheses were rejected.

A Parallel Monte Carlo Algorithm for the Life Cycle Asset Allocation Problem

Life cycle asset allocation is a crucial aspect of financial planning, especially for pension funds. Traditional methods often face challenges in computational efficiency and applicability to different market conditions. This study aimed to innovatively transplant an algorithm from reinforcement learning that enhances the efficiency and accuracy of life cycle asset allocation. We synergized tabular methods with Monte Carlo simulations to solve the pension problem. This algorithm was designed to correspond states in reinforcement learning to key variables in the pension model: wealth, labor income, consumption level, and proportion of risky assets. Additionally, we used cleaned and modeled survey data from Chinese consumers to validate the model’s optimal decision-making in the Chinese market. Furthermore, we optimized the algorithm using parallel computing to significantly reduce computation time. The proposed algorithm demonstrated superior efficiency compared to the traditional value iteration method. Serial execution of our algorithm took 29.88 min, while parallel execution reduced this to 1.42 min, compared to the 41.15 min required by the value iteration method. These innovations suggest significant potential for improving pension fund management strategies, particularly in the context of the Chinese market.

THE ROLE OF REGIONAL RURAL BANKS (RRBs) IN RURAL DEVELOPMENT WITH SPECIAL REFERENCE TO PRATHMA BANK, UTTAR PRADESH

Rural development is a cornerstone of India's socio-economic progress, as a significant portion of the population resides in rural areas where agriculture and small enterprises drive the economy. Regional Rural Banks (RRBs), established to bridge the credit gap in these regions, play a crucial role in promoting financial inclusion, enhancing agricultural productivity, and fostering sustainable rural development. This paper examines the multifaceted contributions of RRBs, with a specific focus on Prathma Bank in Uttar Pradesh, which has emerged as a vital institution in the rural banking landscape. The research highlights how Prathma Bank has effectively catered to the financial needs of marginalized farmers, women entrepreneurs, and small business owners through innovative lending products and microfinance initiatives. By promoting self-help groups (SHGs) and providing access to essential financial services, Prathma Bank has empowered rural communities, improved livelihoods, and stimulated local economies. Furthermore, this study analyzes the challenges faced by Prathma Bank, including high levels of non-performing assets (NPAs), limited technological infrastructure, and the need for enhanced financial literacy among rural populations. It underscores the importance of leveraging technology and expanding outreach to ensure sustainable development in rural areas. The findings suggest that while Prathma Bank has made significant strides in promoting rural development, strategic interventions and policy reforms are necessary to address operational challenges and maximize its impact. Recommendations include strengthening risk management frameworks, expanding product offerings, enhancing governance, and fostering public-private partnerships. This paper concludes that RRBs like Prathma Bank are not only pivotal in facilitating access to credit but also play an essential role in the holistic development of rural economies, making them indispensable to India's growth narrative

Optimizing Organizational Efficiency: Strategic Requirement of Modern Industrial Asset Level Management

Asset Hierarchy Management (AHM) is not just a theoretical concept but a practical tool for optimizing operations in modern businesses, particularly in sectors with intricate infrastructures such as manufacturing, utilities, and healthcare. This research paper explores the significance of AHM in standardizing and enhancing organizational efficiency. It traces AHM's evolution, delineates its benefits, and provides strategies for implementation. By emphasizing the tangible benefits of AHM, the paper aims to instill optimism in the audience about its potential impact. The paper outlines prerequisites and steps for developing a robust asset hierarchy, stressing transparent governance and integration with technology solutions like Enterprise Asset Management (EAM) software. Furthermore, it presents a detailed framework for implementing AHM in manufacturing plants, highlighting the importance of defining clear asset categories, hierarchical levels, and relationships. By adhering to best practices and leveraging advanced tools, organizations can effectively manage assets, drive operational excellence, and achieve sustainable growth.

Does Bank Monitoring Reduce Corporate Misreporting? Evidence from Foreign Bank Entry in China

We propose a model of bank monitoring and borrower financial misreporting. Using the staggered liberalization of the banking sector in China as a natural experiment, we find that, consistent with the model’s prediction, entry by more efficient foreign banks reduces corporate misreporting fraud. Fraud reduction is greatest among borrowers of foreign banks, but fraud also drops among borrowers of domestic banks, suggesting a spillover effect. As predicted by the model, fraud reduction is greatest for borrowers with higher levels of fixed assets or lower levels of current assets. Our evidence suggests that improved bank monitoring reduces financial misreporting. This paper was accepted by Tomasz Piskorski, finance. Funding: M. Li acknowledges support from the National Science Foundation of China [Project 71402078] and the Social Science Foundation of Tsinghua University [Project 2013WKZD004]. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.02414 .

Empirical Analysis of the Relationship Between Debt Level and Business Performance of List Companies in the A-share Real Estate Industry

Since China's reform and opening, the real estate industry has moved towards marketization, with rapid development with the help of market opportunities and financial leverage. However, in recent years, China has continued to promote industrial structure transformation and deleveraging, and affected by the world economy, the epidemic, and other factors, the market has continued to cool, and the past development situation is no longer applicable to the present, and the change in the real estate industry is imminent. Taking the real estate enterprises listed in Shanghai and Shenzhen A-shares as the analysis object, this paper uses the data from three consecutive years from 2019 to 2021, uses the Stata data analysis tool to conduct empirical analysis, and analyzes the relationship between the debt level and business performance of enterprises in the real estate industry in different regions through descriptive statistical analysis and multiple linear regression analysis. The results show that the results vary in different regions, and there is a significant positive correlation between the operating performance and debt level of real estate enterprises in other regions, while the north, Shanghai, and Guangzhou regions do not. The state should strengthen supervision, encourage new financing channels, promote the transformation of enterprise asset structure, optimize the level of assets and liabilities, and then reduce financial risks and ensure the benign development of the market.

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.

Towards an open pipeline for the detection of critical infrastructure from satellite imagery—a case study on electrical substations in The Netherlands

Abstract Critical infrastructure (CI) are at risk of failure due to the increased frequency and magnitude of climate extremes related to climate change. It is thus essential to include them in a risk management framework to identify risk hotspots, develop risk management policies and support adaptation strategies to enhance their resilience. However, the lack of information on the exposure of CI to natural hazards prevents their incorporation in large-scale risk assessments. This study sets out to improve the representation of CI for risk assessment studies by building a neural network model to detect CI assets from optical remote sensing imagery. We present a pipeline that extracts CI from OpenStreetMap (OSM), processes the imagery and assets’ masks, and trains a Mask R-CNN model that allows for instance segmentation of CI at the asset level. This study provides an overview of the pipeline and tests it with the detection of electrical substations assets in the Netherlands. Several experiments are presented for different under-sampling percentages of the majority class (25 %, 50 % and 100 %) and hyperparameters settings (batch size and learning rate). The highest scoring experiment achieved an Average Precision at an Intersection over Union of 50 % of 30.93 and a tile F-score of 89.88 %. This allows us to confirm the feasibility of the method and invite disaster risk researchers to use this pipeline for other infrastructure types. We conclude by exploring the different avenues to improve the pipeline by addressing the class imbalance, Transfer Learning and Explainable Artificial Intelligence.

What drives solar energy adoption in developing countries? Evidence from household surveys across countries

This study investigates household solar energy uptake in developing countries by combining household surveys for 11 countries with area-level data. We use data from World Bank surveys for countries in Africa, Asia, and Central America. Our probit regressions use up to 36,653 household observations and cover actual uptake rather than intentions. The main result shows that households further from capital cities are less likely to have solar home systems. Furthermore, there are strong links between assets and solar uptake across solar types such as solar home systems, solar lighting systems, and solar lanterns. This is an important finding given the small number of prior studies that use actual uptake data for developing countries and the mixed results from prior literature. We do not find evidence that households in sunnier areas are more likely to have solar home systems across countries. This study motivates policymakers to consider greater support for households far from capital cities, in sunnier regions, and with low levels of assets.

Technology transfer as a tool for managing the regional innovation economy

Relevance. The Russian economy is moving to a new innovative level of development, and actively implemented projects in the field of digital transformation form the basis for creating a long-term and secure information and telecommunications infrastructure capable of providing high-speed transmission, processing and storage of large amounts of data, which will be available to a wide range of enterprises.The purpose of the study is to identify the role of technology transfer in the management of the regional innovation economy and current trends.Objectives: to study the indicators of Internet use by the population for ordering goods and services in urban and rural areas; to assess the dynamics of gross value added of the ICT sector and GDP; to assess the demand of economic and social sectors for digital technologies; to propose ways to solve these problems of digitalization of Russian enterprises.Methodology. The methods of system analysis, deduction and induction, analysis and synthesis are used.Results. Russian enterprises are experiencing significant difficulties in the process of technology transfer to the digital space due to the lack of deep readiness to accept and use open innovations, as well as due to restrictions on the free exchange of intellectual property results and insufficient level of asset sharing. These factors can slow down the pace of technology transfer of enterprises and create obstacles to their competitiveness in today's digital business environment. It is necessary to actively develop technology transfer mechanisms that promote the exchange of knowledge and resources in order to increase efficiency to the new challenges of the digital economy.Conclusions. Economic measures of technology transfer, including bans on access to foreign digital products and services, have not only negative consequences. Currently, consumers in Russia who are accustomed to using digital solutions from foreign manufacturers are faced with the need to switch to domestic analogues of technology as a result of the restrictions imposed.

Unaffordable, untrustworthy, or unnecessary? Reasons for foregoing building, home contents, and comprehensive car insurance in disaster‐prone Australia

AbstractIn Australia, building, home contents, and comprehensive car insurance facilitate the accumulation of assets associated with rational, responsible citizenship while promising protection in case of events such as fire, flooding, car accident, or theft. Yet many Australians lack these insurance products, risking exposure to devastating financial losses when disaster strikes. This article compares the findings of online surveys of insured and uninsured Australians and explores the factors driving some to forego insurance coverage. Our findings show that inability to afford premiums is a major driver of noninsurance in Australia, particularly for people with low levels of disposable income and assets, or those living in areas affected by rising disaster risk. Yet the decision to forego insurance is also influenced by attitudes to financial matters. Australians who forego insurance have lower levels of trust in insurance and are less likely to consider themselves under a social obligation to be insured. However, contrary to portrayals of the uninsured as risk‐takers, the decision to forego coverage does not appear to be driven by lesser risk aversion among uninsured Australians relative to those who do purchase building, home contents, and comprehensive car insurance policies.

ESG integration strategy with a multivariate normal distribution

Purpose: The paper aims to present a new framework for ESG integration strategies in portfolio optimization problems. The optimization in the new structure focuses on the portfolio level, and the procedure is not focused on utility functions or on preliminary weights applied to the asset level. It applies the resampling technique, and all the portfolios are optimal portfolios in the mean-variance space. It uses a filtering process where only optimal portfolios with lower ESG risks are considered. Therefore, this technique works only with optimized portfolios, avoids concentration bias, and considers estimation errors in the expected returns and in the covariance matrix. Design/methodology/approach: The sample mean returns and covariance matrices generated by a multivariate normal distribution are applied in mean-variance optimization to generate several portfolios in the efficient frontiers. An ESG filtering process is used to select portfolios with lower ESG risks from a sample of 42 companies listed on the Brazilian stock exchange with returns from the period of 2018/01/01 to 2024/04/22.Findings: Integration strategy costs may be lower than the best-in-class strategy costs and may be similar to the costs of a negative screening strategy. Social implications: The paper presents a framework that considers social, environmental, and governance factors in the portfolio optimization process.Originality: The main contribution of this paper is to present a new framework that combines resampling of returns’ mean and covariance based on a multivariate normal distribution with an ESG portfolio filtering process.

Does organizational ambidexterity mediate the relationship between intellectual capital and financial performance

PurposeThis paper aims to examine the relationship between different dimensions of intellectual capital and industrial companies' financial performance. In addition, this paper aims to examine the role of organisational ambidexterity in mediating this relationship.Design/methodology/approachThis paper adopted a quantitative method using a previously validated questionnaire. The questionnaire copies have been distributed to accountants and accounting managers in the context of industrial companies.FindingsFindings indicate that there is a positive correlation between all dimensions of intellectual capital and organisational ambidexterity. Furthermore, the connection between intellectual capital dimensions and financial performance is notably positive when it comes to relational capital. Additionally, it was established that the various dimensions of capital and financial performance are interconnected through the intermediary influence of organisational ambidexterity.Originality/valueThis paper provides important contributions to managers, policymakers and stakeholders. Jordanian industrial companies must improve the quality of their work by enhancing levels of intellectual capital and organisational ambidexterity that leads to improving the financial performance of companies. Additionally, managers should identify and capitalise on the benefits of other intangible assets and understand more about how to increase the use level of other intangible assets.

A STUDY OF FINANCIAL SUSTAINABILITY IN INDIAN BANKING INDUSTRY

Financial sustainability has become a catch line in the modern financial systems. This has become a matter of concern in all economies worldwide. Financial sustainability ensures stable and resilient financial health. This comprehensive approach supports the banking sector in generating more revenue, and its strategic planning system is conducive to reducing the level of non-performing assets by managing costs. This allows the financial system to achieve its strategic goals by effectively managing borrowing and credit. Strategic investment decisions help evade financial strain and mitigate probable financial pitfalls. This makes the system more viable and resilient, allowing banks to achieve long-term goals in a zestful environment of financial threats and opportunities. The concept of financial sustainability is a new term in the Indian banking system. Banks are trying their best to adopt and implement it, but are still lagging. To date, only a few banks have incorporated them successfully. Financial sustainability offers many benefits to banks in the form of high productivity, effective management of interest rate fluctuations, controlled non-performing assets, cost reduction, better customer satisfaction, and risk control. Indian banks have acknowledged the significance of financial sustainability and are now committed to achieving it. Banking regulators must incorporate and implement the goal of financial sustainability in the Indian banking system on a priority basis. This study highlights the need to adopt the goal of financial sustainability in the Indian banking industry. Further, the strategies made by the RBI in this direction have been analyzed along with the challenges that banks face during the implementation of these strategies in the real world.

The Impact of Intangible Assets on Capital Structure in Asia

Past studies find evidence that the level of intangible assets is positively related to corporate borrowing in the United States. This paper explores the relationship between intangible assets and capital structure for Asian countries. We identify a positive relationship between intangible asset investment and debt levels throughout Asia. Unlike in the United States, this positive relationship appears to be significant for non-Goodwill and Goodwill intangible assets. Further, we find that the magnitude of this relationship is significantly greater for developed Asian countries than for developing ones. We explore explanations for this difference related to firm size, firm age, cash flow volatility, and a firm’s likelihood to default on its debt.

A demographic analysis of developmental assets, misconduct behaviours, and depression among New Zealand youth in mentoring relationships

ABSTRACT Mentoring is often utilised to support youth who have low levels of protective assets. This study explored 300 NZ youth (16-18 years old) who were involved in mentoring relationships to better understand how developmental assets influence depressive symptoms and misconduct behaviours. Results suggest that most participants possessed low to fair levels of internal (77.3%) and external (72.6%) assets with high levels of major depressive symptoms (40.7%) and moderate to high levels of misconduct behaviours (29.4%). There were demographic differences in developmental assets (e.g. Pacific youth reported higher assets and non-student participants reported lower assets than others), depressive symptoms (e.g. higher ranks for females than males) and misconduct behaviours (e.g. higher misconduct behaviours among Māori youth, non-student and full-time employed participants). Importantly, lower levels of external assets (β = – .90, S.E = .20, p = <.001; 95% CI [−1.30, – .50]) and internal assets (β = – .76, S.E = 29 .28, p = <.001; 95% CI [−1.31, – .20]) predicted depressive symptoms and low levels of external assets significantly contribute to youth misconduct behaviours (β = – .40, S.E = .08, p = 31 < .001; 95% CI [-.56, – .23]). These findings suggest strategies, programmes and policies to improve developmental assets which may decrease emotional and behavioural distress among youth.

Prevalence and associated factors of caesarean section among mothers who gave birth across Eastern Africa countries: Systematic review and meta-analysis study

BackgroundCaesarean section (CS) rate increased dramatically worldwide, exceeding the World Health Organization's benchmark (10–15 %) in many countries. This rate varies in different regions of the continent. Using various study designs, researchers from across East African countries investigated the prevalence of caesarean section and the factor associated with it but no study shows a pooled prevalence of caesarean section in the Eastern African region. Therefore, this review aimed to systematically summarize and estimate the pooled prevalence of caesarean section and its associated factors in Eastern Africa, 2023. MethodsPubMed, Web of Science, EMBASE, Scopus and CINAHL were rigorously searched to find relevant studies. All identified observational studies reporting the prevalence of CS and its associated factors in East Africa published till August 2023 were considered. Heterogeneity across the studies was evaluated using the I2 test. Publication bias was assessed by funnel plot and Egger's regression test. Finally, a random effect meta-analysis model was computed to estimate the pooled prevalence of CS and qualitative analysis was employed for associated factors. The study protocol was registered in PROSPERO. ResultsThis review was assessed using twenty-six eligible studies from a total of 2223 articles with a total of 600,431 participants. In this meta-analysis, the pooled prevalence of caesarean section in Eastern Africa was 24.0 % (95%CI: 22–27 %). The highest pooled prevalence of caesarean section was in Ethiopia, 28.30 % (95%CI; 21.3–35.2 %), and the lowest was seen in Uganda, 11.9 % (95%CI; 7.9–15.9 %). Urban residency, having high level of wealth asset, education level college and above, advanced maternal age, big birth weight, history of previous caesarean section, private institution delivery, multiple pregnancies, pregnancy-induced hypertension, antepartum haemorrhage and fetal malpresentation were linked with a greater likelihood of having CS. Conclusionsand recommendation: The overall pooled prevalence of CS in Eastern Africa was high compared to the WHO proposed recommended range. Therefore, the finding implies that each East African countries Ministry of Health and health care professionals shall be given particular emphasis made on strengthening antenatal care services and ensure more women have access to skilled healthcare professionals during childbirth. This can help in providing appropriate interventions, support to women and reducing the need for emergency and unnecessary CSs. The result of this research are a baseline data for future researchers to conduct further studies to better understand the reasons behind the high rates and identify potential interventions and solutions specific to the African context.PROSPERO protocol number: CRD42023440131.