Financial Efficiency Research Articles

A study on differences in economic and social structure between education and food production

Education and food are vital commodities, yet their economic and social structures differ greatly. Food production requires private enterprise to maintain financial efficiency, while education relies on the government to maximize social efficiency. This paper examines the rationale behind disparities in the distribution of education and food production sectors through the lens of economic efficiency, accessibility and informed public decision-making. Education has positive externalities, promoting social cohesion by teaching shared values, stabilizing the functioning of society and achieving social and educational equity through the participation of an educated population in democratic processes. Private food production can maintain the ability to minimize costs and maximize product quality through market competition. In addition, private companies are better equipped to take on the significant risks associated with agribusiness. Competition and technological innovation in the food industry have made prices accessible, ensuring that essential nutrients are affordable to low-income and vulnerable groups. Public education can also have a positive impact on food production. Public education promotes the long-term development of the food industry by training relevant agricultural talents to carry out technological innovations related to food production. In addition, educated citizens are more likely to be concerned about food safety and its production process—the demand for food transparency and quality forces food producers to adhere to higher standards and innovate. Thus, rationalizing distribution and interaction between the education and food production sectors results in optimal social outcomes.

Digital financial inclusion, environment volatility and investment efficiency: demand and supply side experiences of Chinese listed renewable energy firms

Digital financial inclusion, environment volatility and investment efficiency: demand and supply side experiences of Chinese listed renewable energy firms

Quantum-Inspired AI for Optimized High-Frequency Trading

This article explores the transformative role of quantum-inspired AI in optimizing financial practices, particularly within high-frequency trading (HFT) in the financial sector. As HFT operates in an environment of rapid transactions and significant market volatility, the need for advanced optimization techniques becomes paramount. Quantum-inspired algorithms leverage principles from quantum mechanics, such as superposition and tunneling, to enhance various aspects of trading strategies. These algorithms enable rapid optimization of asset allocation, real-time trade execution, and proactive fraud detection, effectively addressing the challenges posed by traditional financial models. By facilitating simultaneous evaluation of multiple strategies and enabling real-time analysis of complex trading patterns, quantum-inspired AI significantly improves decision-making speed and accuracy. The financial implications of this advancement are profound, leading to higher profitability, improved market integrity, and enhanced trust among market participants. Ultimately, integrating quantum-inspired AI in finance represents a crucial step towards harnessing cutting-edge technology to reshape trading dynamics, paving the way for innovative strategies that can adapt to the evolving landscape of financial markets. This study underscores the potential of quantum-inspired AI to redefine operational efficiency in finance, ensuring competitiveness in an increasingly complex trading environment.

Enhancing Portfolio Decarbonization Through SensitivityVaR and Distorted Stochastic Dominance

Recent trends in portfolio management emphasize the importance of reducing carbon footprints and aligning investments with sustainable practices. This paper introduces SensitivityVaR (SensitivityVaR), an advanced distortion risk measure that combines Value-at-Risk (VaR) and Expected Shortfall (ES) with the Cornish–Fisher expansion. SensitivityVaR provides a more robust framework for managing risk, particularly under extreme market conditions. By incorporating first- and second-order distorted stochastic dominance criteria, we enhance portfolio decarbonization strategies, aligning financial objectives with environmental targets such as the Paris Agreement’s goal of a 7% annual reduction in carbon intensity from 2019 to 2050. Our empirical analysis evaluates the impact of integrating carbon intensity data—including Scope 1, Scope 2, and Scope 3 emissions—on portfolio optimization, focusing on key sectors like technology, energy, and consumer goods. The results demonstrate the effectiveness of SensitivityVaR in managing both risk and environmental impact. The methodology led to significant reductions in carbon intensity across different portfolio configurations, while preserving competitive risk-adjusted returns. By optimizing tail risks and limiting exposure to carbon-intensive assets, this approach produced more balanced and efficient portfolios that aligned with both financial and sustainability goals. These findings offer valuable insights for institutional investors and asset managers aiming to integrate climate considerations into their investment strategies without compromising financial performance.

Investigating the influence of digital transformation, budgeting and budgetary control on the financial performance of SMEs

The study delves into the challenges and opportunities SMEs face in South-West Nigeria, focusing on the transformative impacts of digitalization, big data analytics, customer experience enhancement, and stringent budgeting controls on their financial performance. The research analyzes data from 825 SMEs through Partial Least Squares Structural Equation Modelling (PLS-SEM) analyze the data. The findings indicate that digital transformation significantly boosts customer experience, big data analytics, and budgetary controls. Enhanced customer experience and effective big data utilization reciprocally improve budgetary control processes, which are crucial for financial performance. The study reveals the mediating roles of customer experience and big data analytics in the relationship between digital transformation and budgeting control, highlighting the interconnectedness of these factors. Financial efficiency also emerges as a significant moderator in the nexus between budgetary control and financial performance, underscoring its influence on economic outcomes. This research proposed initiatives such as investments in customer relationship management systems, personalized services, and streamlined communication channels to create positive customer experiences that, in turn, positively influence budgeting outcomes.

Accounting and Healthcare Waste Management: Strategies to Improve Financial Efficiency and Reduce Environmental Impact

Healthcare waste management represents both a financial and environmental challenge for healthcare institutions. This article discusses accounting and financial management strategies that can be implemented to optimize operational costs related to healthcare waste disposal, while minimizing environmental impact. A theoretical framework based on financial and environmental sustainability is proposed, integrating environmental accounting policies and waste management methodologies. The results demonstrate that adequate financial planning and the implementation of treatment technologies can significantly reduce costs and improve efficiency in healthcare waste management. The findings highlight the need for more robust management policies and greater investment in sustainable treatment technologies.

Overview of Financial Efficiency in India’s Power Sector

Power is an important tool for economic growth of the country. Power is vital for every form of human activity-domestic, agricultural and industrial infrastructure, such as telecommunication and transport. The demand for electricity in India is enormous and is growing steadily. This growth has been slower than a country’s economic growth. The big challenge of the power industry is to balance the demand and supply of electricity. Financial management involves planning, organizing, directing, and controlling the financial activities of an organization. Its primary goal is to maximize shareholder wealth and ensure the efficient use of resources. Financial efficiency refers to how effectively an organization utilizes its resources to generate revenue or profits. It involves minimizing costs and maximizing output or outcomes relative to inputs. The financial efficiency of India's power sector is a critical aspect of its energy infrastructure, impacting both economic growth and sustainability. The main needs of the study are the source and use of funds of the company and how to evaluate the financial performance of the company. The objective of this study is to critically evaluate and assess the financial performance of Southern Power Distribution Company of Andhra Pradesh State Limited, Tirupati.

Building the Foundation of Indonesia’s Digital Economy: Encourging the Adoption of Bitcoin and Blockchain Technology to Increase Financial Inclusion and Efficiency

This research aims to promote the adoption of bitcoin and blockchain technology to enhance financial inclusion and efficiency in Indonesia. A mixed-method approach was used, involving qualitative interviews with experts and users of blockchain and bitcoin, as well as quantitative surveys distributed to students and the general public. Findings suggest that these technologies can improve efficiency in the financial sector by reducing costs and improving accessibility, especially for people without access to traditional banking services. However, the successful implementation of blockchain and bitcoin requires proper education on their use. Theoretical implications highlight the role of blockchain in advancing digital financial inclusion, while practical implications point to the need for government regulations and strategies for financial institutions. This research offers insights into supporting digital economic transformation and improving the efficiency of financial services in Indonesia.

Factors Affecting the Sustainability of Corporates in Polluting Sectors

Corporate sustainability performance is gaining ever greater importance. The negative impact of climate change is manifested through heavy air, water and soil pollution. Polluting sectors, as the major players, are characterized by large amounts of emissions, waste and consumption of resources, and therefore have a larger negative impact on the environment. Companies operating in polluting sectors are recognized globally as the main sources of greenhouse gas emissions; thus, their performance is widely debated. Despite their character, such companies strive for higher profitability, better financial performance and operational efficiency. However, higher financial resources create the potential for innovation investments in companies. It is widely accepted that research and experimental development (R&D) expenditures enable new business ideas, models, products, services, and processes. However, while pursuing sustainability targets, financial results could be directed towards sustainability performance. The purpose of this paper is to analyze how the financial and innovation results of companies in polluting sectors interact with sustainability performance scores. For it, we have identified three essential pillars of sustainability: environmental, governance, and social. Using ordinary least squares (OLS) regressions, models were developed for each pillar of sustainability, including corporate financial performance indicators and R&D expenditures. The obtained results provide the insights that a company operating in polluting sector size and turnover significantly interacts with all pillars of sustainability. However, we also found that the corporate debt ratio, earnings ratio, and current liquidity have a significant relation only with environmental and social sustainability indicators.

Best Value Investing Strategy: Analysis of Graham, Greenblatt, and Piotroski Methods for Smart Investment Decisions

This study aims to analyze the value investment portfolio strategy based on prominent investors Benjamin Graham, Joel Greenblatt and Joseph Piotroski. The three portfolio models are built according to the methodology developed by each author, using the last five years of financial accounting data and through stocks listed on the Kompas 100 Index listed on the Indonesia Stock Exchange for the 2022 period. This study uses a three-factor model from the Fama and French method which is an extension of the Capital Asset Pricing Model methodology by adding Small Minus Big and High Minus Low. The regression results show that all three strategies produce positive and statistically significant coefficients in the three-factor model setting. After backtesting the three portfolios, Graham's portfolio has a higher return compared to the other two portfolios. The managerial implications of this study include the implementation of strategies based on strengthening financial fundamentals and operational efficiency to increase the company's attractiveness in the eyes of value-investing investors.

Streamlining budgeting and forecasting across multi-cloud environments with dynamic financial models

This review paper explores the complexities of financial management in multi-cloud environments, emphasizing the need for streamlined budgeting and forecasting processes. It begins by addressing the challenges inherent in managing finances across multiple cloud platforms, such as integration difficulties, data silos, and cost management issues. The paper then provides an overview of dynamic financial models, detailing their components and benefits in overcoming these challenges. It highlights the role of automation, real-time data utilization, and predictive analytics in enhancing financial accuracy and efficiency. Furthermore, the paper discusses the importance of collaborative platforms in fostering stakeholder communication and coordination. Finally, strategic planning, best practices for multi-cloud financial management, and emerging trends and prospects are outlined. The review underscores the significance of aligning financial models with organizational goals and leveraging advanced technologies to achieve optimal financial outcomes in multi-cloud settings. Keywords: Multi-Cloud Financial Management, Budgeting and Forecasting, Dynamic Financial Models, Automation in Finance, Predictive Analytics.

Leveraging Data Analytics for Financial Stability: A Blueprint for Sustaining SMEs in Economically Distressed Regions of the U.S.

Purpose: Our research explores how data analytics can empower small- and medium-sized enterprises (SMEs) in economically distressed regions of the U.S. by improving financial decision-making, operational efficiency, and risk mitigation. The study aims to provide a blueprint for leveraging data-driven insights to ensure long-term financial stability and economic growth in underserved areas, particularly in the Midwest and Southern states. Methodology: The study employs a case-study approach to analyze the real-world applications of data analytics platforms in SMEs within economically distressed regions. It uses statistical analysis to compare the performance of businesses that have adopted data analytics tools with those relying on traditional methods. The methodology also includes the collection of data from various sources such as financial performance records, customer analytics, and predictive models. Findings: The research demonstrates that SMEs using data analytics experience significant improvements in financial performance. For instance, predictive analytics increased financial forecasting accuracy by 25%, and real-time business intelligence tools reduced operational costs by 15%. Businesses using customer analytics tools saw a 20% rise in customer retention and a 15% increase in revenue. The study shows that data-driven strategies can improve overall financial stability by 30% and enable SMEs to proactively mitigate risks in volatile markets. Unique Contribution to Theory, Policy, and Practice: The study contributes to the emerging body of literature on the transformative potential of data analytics in financially distressed regions, providing new insights into how real-time and predictive analytics can enhance financial decision-making in SMEs’ practices within the economically distressed regions. The study provides a practical blueprint for SMEs to adopt data analytics tools, demonstrating their impact on financial stability, operational efficiency, and long-term growth. It offers actionable recommendations for business leaders in distressed regions to integrate analytics equitably into their decision-making processes.

Unlocking the potential of FinTech: A pathway to sustainable resource management in the EU

The rapid growth of the ecological footprint within the European Union (EU) has indicated a strong need for new and innovative approaches to sustainably managing natural resources. To this end, this study delves into how to harness the power of financial technology (FinTech) by infusing the principles of circular economy and technological innovation to address the growing ecological footprint. This study aims to explore the intricate interplay of natural resources, circular economy, and technological innovation on the effect of ecological footprint, particularly focusing on FinTech as a moderator in these relationships. The common correlated effects mean group (CCGMG) estimator addresses panel data's heterogeneity and cross-sectional dependence, which is essential for understanding the complex nature of ecological footprint issues. The evidence from 27 EU countries spanning 2013 to 2021 suggests that while more natural resources are used, the ecological footprint will increase, but improving circular economy practices and technological innovation will massively reduce this increase. Specifically, a 1% increase in natural resources leads to a corresponding 0.079% rise in ecological footprint, while a 1% increase in the circular economy and technological innovation reduces ecological footprint by 0.328% and 0.326%, respectively. Furthermore, FinTech stands out as a pivotal moderating force in amplifying the positive effects of circular economy and technological innovation towards ecological sustainability. Notably, it cushions the negative impacts of natural resource use and reinforces the power of sustainable practices on the footprint-reducing effect. From that angle, several targeted policy recommendations are proposed to harness FinTech's capabilities of resources and waste management, optimizing financial capital allocation, and enhancing financing efficiency. The study provides valuable insights and practical recommendations for promoting green initiatives within the EU and globally, aligning with the overall objectives of environmental sustainability and economic resilience.

The Application of Fintech (Financial Technology) and Risk Management

This paper provides a comprehensive overview of the impact and applications of financial technology (Fintech) across various sectors such as payment and clearing, lending, wealth management, insurance, and risk management. It highlights the transformative potential of Fintech in enhancing financial efficiency, inclusiveness, and risk management through the utilization of modern technologies like big data, artificial intelligence, and blockchain. The paper delves into specific examples such as online payment systems, peer-to-peer lending platforms, robo-advisory services, and blockchain technology. Furthermore, it discusses the challenges and risks associated with Fintech, including regulatory issues, security concerns, and the need for effective risk management practices. The abstract emphasizes the importance of responsible risk management in ensuring financial stability and preventing systemic risks in the Fintech sector. Overall, the abstract provides a comprehensive understanding of the role of Fintech in shaping the future of the financial industry and emphasizes the need for effective regulation, risk management, and technological innovation to harness its full potential while mitigating associated risks.

Innovative competences in public administration: The path to sustainable development, financial efficiency and strengthening of national security

The article claims that modern transformation processes in the system of international relations have led to the emergence of a new set of security problems threats, challenges, and risks of a non-traditional series, differing from traditional, military-strategic threats in the parameters of their impact on modern states and their transboundary nature. Hybrid dangers have an increasing impact on societal domains. To further their political, ideological, or commercial goals, hybrid actors take advantage of the weaknesses found in intricately interconnected communities. Research makes an attempt to outline innovative competencies of public administration in the domains of national security and sustainable development within this complex environment.

Analisis Kinerja Keuangan Bank BUMN dan Bank Swasta Indonesia: Studi Komparatif

Purpose: This study assesses and compares the financial performance of state-owned and private banks in Indonesia from 2019 to 2021. This study focuses on evaluating key financial indicators to monitor the financial structure and efficiency of banking institutions continuously amid increasing competition in the banking sector. Methodology: This study utilizes several financial ratios and applies independent sample t-tests to analyze the financial performance of state-owned and private banks. The key ratios analyzed include (Equity to Total Assets Ratio), ECTAR (Equity to Customer Assets Ratio), IMAEAR (interest margin to average earnings assets ratio), LLCR (Loan Loss Coverage Ratio), DTCR (Debt to Capital Ratio), LDR (Loan to Deposit Ratio), and CAR (Capital Adequacy Ratio). Results: State-owned banks are financially weaker than private banks. Furthermore, there is no significant difference in the average financial performance of state-owned and private banks when measured using EATAR and ECTAR ratios. However, clear differences are observed between these two banking groups in terms of the IMAEAR, LLCR, DTCR, LDR, and CAR ratios. Limitations: This study is limited to the analysis of financial performance from 2019 to 2021, which may not fully capture long-term trends or the impact of external economic conditions, such as global financial crises or regulatory changes. Additionally, this study focuses only on a specific set of financial ratios. Contribution: This study contributes to the body of knowledge by providing a comparative analysis of the financial performance of state-owned and private Indonesian banks. It offers valuable insights for banking institutions, regulators, and investors on how financial performance differs across banking groups, highlighting areas where state-owned banks may need to improve their financial strength.

Innovative competences in public administration: The key to sustainable development, increasing financial efficiency and ensuring national security

The definition and analysis of innovation in this article focus on how it may be interpreted as a dramatic shift in public administration that results in new goods, new technology, new procedures, and the introduction of new ideals. Novel paradigms, novel approaches to management, and novel kinds of innovation characterize modern public management models. A paradigm shift and the emergence of a new public management model built on innovative competences are discussed when innovation in public administration results in new operational approaches. The research is carried out within the paradigm of ‘hybridity’ as a key characteristic of today world and, accordingly, challenges for public administration. Ecosystem model, implying innovative competence in public administration, based on the pillars of hybrid- thinking and foresight paradigm, is suggested as the most corresponding to realities of today.

Do News Reports and Google Searches Impact Bitcoin Prices? An Analysis of Granger Causality

Objective: to analyze the Granger causality relationship between the number of Bitcoin news articles, the number of Google searches related to the term "Bitcoin," and the price of the cryptocurrency. The study aims to understand how these variables influence each other using an econometric time series model. Theoretical framework: the paper is based on studies on financial market efficiency, cryptocurrencies, and Granger causality theory. It reviews research that explores the impact of media information and online searches on the price of financial assets, such as Bitcoin, while also discussing Bitcoin’s role as both a speculative asset and a transactional currency. Method: the construction of a time series with weekly data, from 2015 to 2018, covering Bitcoin price, the number of news articles, and Google searches. The Vector Autoregressive (VAR) model was used to conduct the Granger causality test and verify if there are causal relationships between these variables. Results and Discussion: the findings indicate a triple causality relationship among the studied variables. Bitcoin's price influences both the number of news articles and Google searches, and in turn, the articles and searches also influence Bitcoin's price. This suggests that increased interest and media coverage of Bitcoin drive its demand and price. Research implications: the research suggests that Bitcoin's price behavior is influenced not only by traditional economic factors but also by media information and the volume of online searches. This highlights the importance of informational factors in the cryptocurrency market and the influence of digital media on asset pricing. Originality/value: the study proposes integrating data from news articles and Google searches with Bitcoin price behavior, applying Granger causality analysis. Its contribution lies in demonstrating the importance of media in the dissemination and pricing of cryptocurrencies, providing a new perspective for the literature on digital assets and speculative behavior.

Impact of digital transformation on financial stability in emerging markets: evidence from Ethiopia

This insightful study delves into the intricate relationship between key digital finance adoption indicators and the stability of the banking sector in Ethiopia, an emerging economy undergoing rapid digitalization. Covering annual data from 1991 to 2022 and utilizing an autoregressive distributed lag (ARDL) approach alongside Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) techniques, the researchers uncover thought-provoking findings that challenge conventional wisdom. Contrary to expectations of a positive long-term association, the analysis reveals a statistically significant negative relationship between both internet usage and mobile phone subscriptions and Ethiopia's banking system's financial stability. This robust result, validated through rigorous robustness checks, suggests that the breakneck pace of digital transformation may outpace the development of robust regulatory frameworks and risk management practices, ultimately undermining the overall stability of the financial sector. Interestingly, the short-term analysis presents a more nuanced picture, with mobile phone subscriptions exhibiting a stabilizing effect in the immediate aftermath. This intriguing dichotomy highlights the complex and evolving dynamics at play, where the challenges of integrating digital finance with the traditional banking infrastructure and the persistence of informal financial activities potentially offset the benefits of enhanced financial inclusion and transaction efficiency. These thought-provoking findings carry crucial implications for policymakers and industry stakeholders navigating the digital revolution. Policy implications emphasize the need for robust regulatory frameworks, enhanced cyber security measures, and improved financial literacy. The findings underscore the importance of a nuanced approach to digital finance in emerging economies, advocating for continuous adaptation of policies to address the evolving landscape of financial technology. Continued inquiry can better guide policies that foster digital transformation while safeguarding stability, especially in rapidly developing regions like sub-Saharan Africa.Graphical

Implementing data-driven financial management systems in SMEs: A case review approach

The adoption of data-driven financial management systems has become increasingly vital for the growth and sustainability of small and medium-sized enterprises (SMEs). This review explores the implementation of such systems through a case review approach, analyzing their impact on financial decision-making, operational efficiency, and overall business performance. SMEs often face challenges in managing their financial processes due to limited resources, inefficient manual methods, and a lack of real-time data insights. Data-driven financial systems, leveraging automation, artificial intelligence (AI), and analytics, offer a solution by streamlining these processes, enhancing accuracy, and improving decision-making. The review examines three SMEs from different sectors manufacturing, retail, and services that have implemented data-driven financial systems. Through qualitative interviews, financial data analysis, and performance assessments before and after system implementation, the research identifies key improvements in cash flow management, profitability, and financial reporting. Each case highlights how automation and real-time data access have led to more strategic financial decisions, reduced costs, and operational efficiency. The findings suggest that data-driven financial systems not only increase financial transparency but also provide a competitive advantage by enabling SMEs to make informed decisions quickly. However, the review also identifies barriers to implementation, such as technical expertise, costs, and employee training, emphasizing the need for tailored solutions based on company size and sector. The review concludes by discussing future trends in financial technology adoption among SMEs and offers recommendations for facilitating successful integration. This research contributes to the understanding of how data-driven financial management can drive sustainable growth in SMEs. Keywords: Data-Driven, Financial Management, SMEs, Review.