Expensive Management Research Articles

Assessing Technical Inefficiency in Ecosystem Service Provision from an Input Perspective in the Cross Timbers region, United States.

We modeled the efficiency of ecosystem service provision-specifically timber production, carbon sequestration, and water yield-in the Cross Timbers region of the United States using stochastic frontier analysis from an input perspective. Inputs considered included natural capital and control variables such as temperature, precipitation, soil moisture, and natural disturbances, among others, that impact ecosystem service production. Inefficiency was modeled as a function of factors such as ownership, forest productivity, and natural disturbances. We utilized forest plot-level data obtained from the Forest Inventory and Analysis (FIA) program between 2008 and 2019. Our results indicated that ecosystem service production increased with higher levels of natural capital, higher temperatures, mesic soils, the presence of oaks, and damage caused by abiotic factors. We found evidence of technical inefficiency in the simultaneous provision of ecosystem services. From an input perspective, our findings revealed that, on average, 15.9% more input is used due to technical inefficiency in the Cross Timbers region. Specifically, private ownership and damage caused by abiotic factors resulted in excess input use of 16.4% and 14.3%, respectively, due to technical inefficiency. Managing the encroachment of invasive species like eastern redcedar can enhance ecosystem service production in the region, despite the high implementation costs. Collaboration among multidisciplinary extension professionals can help create comprehensive land management plans for the Cross Timbers, while landowners can also utilize cost-share programs to lower management expenses.

Advanced Personal Budget Analytics: Combining Optical Character Recognition and Natural Language Processing for Automated Budget Categorization and Insight Extraction

A budget tracking system is a tool designed to help users monitor their financial resources, categorize expenses and control their financial resources. An Intelligent Personal Budget Analysis System is designed to redefine personal finance management. IntelliFinance is a user- friendly app designed for seamless and efficient daily expense management removing the necessity for conventional paper documentation. This project inculcates the concepts of Computer Vision, Machine Learning and Data Analytics, aims to surpass traditional budget tracking by incorporating innovative features such as receipt scanning and analysis. The project is implemented using Android Studio and Firebase, incorporating advanced features such as Optical Character Recognition (OCR) to capture receipt images, extract text, and process it for further analysis. Firebase ML Kit is utilized for scanning and text recognition, while Natural Language Processing (NLP) is applied for categorizing the extracted text. The system provides a personal budget analysis that enhances the accuracy of financial tracking by offering users a comprehensive overview of their spending habits, complemented by detailed reports and visualizations. Ultimately, this project serves as a financial companion, empowering users to take control of their finances, make informed decisions, and achieve their financial goals.

Secure Blockchain Assisted Attribute-Based Keyword Search for Collaborative E-Healthcare

In the age of technological advancement, collaborative E-healthcare emerges as a transformative system eliminating traditional location and accessibility barriers in healthcare services. Here, Searchable Encryption (SE) plays a key role in enabling healthcare providers to outsource encrypted medical data and search services to third parties like cloud servers, thereby reducing storage and management expenses. This intermediary approach poses challenges of single-point failure, privacy breaches, and potentially untrustworthy results. State-of-the-art public key-based SE methods use a cloud-assisted architecture that doesn’t support reliable and practical searches with fine-grained permissions. Also, such systems require additional support to address potential privacy leakages and ensure data availability at the storage server. To address these concerns, we propose a B lockchain-assisted E fficient and S ecure K eyword S earch (BESKS) scheme to enforce fine-grained keyword search privilege control while achieving practical search complexity. Our scheme employs a ciphertext policy attribute-based keyword search mechanism where keywords are encrypted using expressive access policies to build an inverted index structure. The encrypted indexes are stored on the blockchain while encrypted medical documents are stored on InterPlanetary File System (IPFS) nodes to enhance availability and ensure the reliability and scalability of our approach. Our scheme utilizes blockchain-based smart contract for efficient, secure search operations and ensures financial fairness in fine-grained searches. Search tokens are generated based on user attributes and query keywords to facilitate private searches on-chain. To enhance the search process, our secure index enables exact match for a query keyword in constant time to ensure expensive authorization operations are performed only once. Theoretical analysis suggests that our BESKS is more efficient and secure than state-of-the-art schemes. Prototype implementation results on the Ethereum blockchain network further validate its feasibility for real-world applications, demonstrating the scheme's practical applicability in collaborative E-Healthcare systems.

Effect Of Funding Structure And Liquidity On The Financial Performance Of The Sugar Industry In Kenya

The main aim of this study was to determine the effect of funding structure on the financial performance of the sugar industry in Kenya. The relationship between funding structure and financial performance is crucial within Kenya's sugar industry, as it directly impacts resource allocation, expense management, and overall profitability. Inadequate financial management can result in liquidity challenges, affecting the sector's competitiveness and sustainability. Conversely, a well-balanced funding structure, incorporating both debt and equity, has the potential to strengthen financial stability. Stockholder, Trade-offs, and Pecking order guided the study. The study employed a correlational research design. The study's target population consisted of 16 sugar companies operational in Kenya. Purposive sampling was used to select 9 sugar companies. A total of 324 secondary data points from 2014 to 2022 were collected, including the cost of equity, debt, retained earnings, and economic value added, derived from financial statements and cash flows. The results showed a significant positive relationship between funding structure and Economic value added (coeff=0.863126, p=0.000<0.005). This reveals that Companies that maintain an appropriate funding structure are more likely to achieve higher Economic Value Added (EVA) over the long run. Given the positive long-term correlation between funding structure and EVA, it can be inferred that Kenyan sugar companies should prioritize maintaining a balanced funding structure to improve financial performance. The study concludes that funding structure has a significant relationship with economic value added

Financial Management Analysis in Early Marriage Families in Galis District, Pamekasan

Early marriage is a marriage that occurs at the age of under 19 years for both men and women. Financial management is one of the skills that must be possessed to manage the economy, especially the family economy. This study aims to describe and explain financial management in early marriage families in Galis Pamekasan District. The method used in this study is a descriptive qualitative method. The data used in this study uses primary data, namely direct observation and interviews with informants, as well as secondary data, namely from previous articles, and other literature sources. The results of this study obtained that financial management in early marriage families is more centered on the wife, meaning that the wife has more rights to manage finances more deeply than the husband. This is because the management of income, expenses, future planning, and debt management is more managed by the wife. Keywords : Early Marriage, Family, Financial Management

Tax incentives and environmental performance: The pay-as-you-throw policy in Emilia-Romagna, Italy

This study investigates the impact of implementing the pay-as-you-throw policy as a fiscal incentive mechanism for municipal waste management across municipalities in the Emilia-Romagna region, Italy. Utilizing panel data from 2010 to 2022 and employing a synthetic control with staggered treatment adoption, we evaluate the policy's effects on environmental and local public finance performances. Our findings reveal that treated municipalities witness an average 10% increase in separate waste collection alongside a parallel reduction in municipal waste production since the policy outset, equating to approximately 60 kg per capita annually. Furthermore, our analysis indicates that the policy enables local governments to reduce current energy and environmental expenditures by roughly €130 per capita annually in our optimal model. Notably, results hold robust across three recently developed estimators using difference-in-differences with staggered treatment adoption over time. The policy proves overall effectiveness in promoting circularity within municipal waste management systems, leading to better environmental performances, and decreased environmental management expenses. These implications underscore the potential value for local governments to adopt similar strategies where not yet envisaged.

Efficiency of Inventory in Thai Hospitals: Comparing Traditional and Vendor-Managed Inventory Systems

Background: Traditional procurement and price negotiation methods in public hospitals in Thailand involve group purchasing agreements and bulk orders, posing challenges to improving inventory management efficiency. The vendor-managed inventory (VMI) model is a promising alternative for enhancing hospital performance, especially during crises. This study aimed to assess the potential cost savings in implementing VMI in a large general hospital in Thailand. Methods: A simulation modeling approach was used to compare the current inventory system with three VMI models: VMI1, focused on improving inventory turnover rate (ITR); VMI2, emphasized frequent replenishment with a 1-month supply; and VMI3, eliminated safety stock. Results: The results demonstrated significant cost savings, with potential reductions in total inventory management expenses. Specifically, VMI1 improved ITR from 6.31 to 7.76, reducing average inventory by 36% and cutting management costs by 40%. VMI2, with an ITR of 12.80, reduced inventory by 44% and saved 47% in management costs, while VMI3 achieved a 70% reduction in inventory and a 69% saving in management costs. Conclusions: This study highlights the VMI’s transformative potential in hospital inventory management, demonstrating significant cost savings. However, in the public sector, the feasibility of procurement regulations requires further exploration.

Comparing cost‐effectiveness of radio and drone telemetry with playback surveys for assessing translocation outcomes

Abstract Post‐release monitoring is critical for assessing translocation outcomes. Yet the quality of information gained from monitoring can vary greatly, and perceived monitoring costs often results in reduced monitoring effort. Selecting cost‐effective monitoring strategies that provide high quality data are therefore important for assessing translocation outcomes and making informed management decisions. To compare how monitoring strategy affects information gained, we monitored a toutouwai/North Island robin (Petroica longipes) reintroduction in Aotearoa New Zealand, based on monitoring objectives of determining survival, site fidelity and whether the extent of management was large enough to protect dispersing individuals. We compared how these objectives were met through four monitoring strategies: (1) comprehensive surveys with ground radio telemetry and playback; (2) aerial drone telemetry; (3) dedicated playback by trained surveyors and (4) opportunistic playback by predator control contractors. We undertook a viewshed analysis to determine search coverage of each strategy and compared detection rates, efficiency and cost. Comprehensive ground telemetry and playback, while costly, covered the largest area and provided the most accurate data on dispersal, survival and the translocation outcome. In comparison, opportunistic playback monitoring detected substantially fewer individuals, giving a false impression of low site fidelity and survival and a failed translocation. Although drone telemetry had considerable site‐specific limitations, which limited its effectiveness during our study, it was the most cost‐effective with a high detection rate and low search effort. Synthesis and applications: Our study shows the value of intensive monitoring in facilitating management decisions for wildlife translocations. Comprehensive telemetry and playback, while costly, were invaluable for gaining high quality information on the translocation outcome. Without suitable monitoring, reintroduction outcomes can be difficult to assess and potentially result in unnecessary, ineffective or overly expensive management actions. We recommend that monitoring intensity and methodology should reflect the site, species and level of uncertainty regarding the translocation outcome. Prioritising monitoring can help reduce long‐term costs, increase quality of information gained and allow for more informed management decisions that can improve subsequent translocation outcomes.

Effects of genetic and environmental trends from 1970 to 2020 on farm efficiency estimated with a whole farm modeling system

The objectives of this study were to evaluate associations of genetic, cow management and nutrition, inbreeding, and crop yields from 1970 to 2020 with measures of production and economic efficiency according to a whole farm model, and to evaluate effects of genetic change in individual traits on economic efficiency in comparison to expectations from economic selection indexes. Genetic and phenotypic performance metrics for Holsteins from 1970 and 2020 were retrieved and input into the Integrated Farm System Model (IFSM) for a 7000 cow TX herd and a 50 cow PA grazing herd. Crop yields estimates from 1970 and 2020 were retrieved and farm hectarage was altered so that forage and energy concentrate requirements were met through farm production; likewise, scenarios evaluating effects of atmospheric CO2 fertilization (CO2F) on crop yield were evaluated by altering farm hectarage. For single traits that could be dynamically modeled by IFSM, performance shifts and resulting change in product prices or management expenses were added to 1970 base models. Economic efficiency was evaluated as the per cow return to management and unpaid factors as compared with 1970 base models. As averaged across state scenarios, gains in economic efficiency were +$945 and -$76 for additive genetic and inbreeding effects, respectively, for a total gain from genetic change of +$869. Genetic gain in fat yield (+$549) and protein yield (+$524) were responsible for most of the genetic gain, whereas milk yield (-$128) and increased cow BW (-$129) depressed economic efficiency. Genetic change in productive life had a smaller effect (+$44) than predicted unless heifers were purchased and at double the default value. Gains due to cow management and nutrition increased efficiency by +$666 and crop yield increased efficiency by +$711, of which +$371 was attributed to CO2F across scenarios. Whole farm dry matter efficiencies derived as the ratio of fat and protein corrected milk yield to dry matter intake increased from 0.82 (PA) and 0.97 (TX) in 1970 to 1.20 in 2020 and could be higher if farms reduce the size of their replacement herd by producing beef calves. The landmass required in 2020 was 63% and 78% of the 1970 requirement for TX and PA, respectively. Changes in cow genetic merit, management and nutrition, and crop yields have all increased the economic and environmental sustainability of milk production, and systems such as IFSM could be a useful tool to help inform economic selection indices.

Analysis Of Financial Performance Of Muhammadiyah Aisyiyah Hospital In Jakarta Before And After The Covid-19 Pandemic

This study aims to analyze differences in the financial performance of the Muhammadiyah-Aisyiyah Hospital (RSMA) in Jakarta before and after the COVID-19 pandemic. Data was obtained from financial reports (2017Q1-2022Q4) which were analyzed using the ANOVA difference test. Based on the analysis and discussion, it was found that there was a significant difference in financial performance in the financial ratios of TATO and PBT, while the difference in DAR was not significant before and after the COVID-19 pandemic in the RSIJ Group. Apart from that, it was found that financial performance was better after the COVID-19 pandemic.This research provides practical insights for hospital managers and stakeholders in designing more effective policies for financial management during and after the pandemic. The increase in the Debt to Assets Ratio in several hospitals shows the need for better debt management strategies, while the decrease in the Total Assets Turnover Ratio emphasizes the importance of increasing the efficiency of assets use. The increase in Profit Before Tax in several hospitals indicates opportunities to increase profitability through appropriate management despite existing challenges. To improve the financial performance of Muhammadiyah private hospitals in DKI Jakarta, it is recommended to improve asset management to make it more effective, diversify income sources to reduce financial risks, improve revenue and operational expense management strategies, and invest in advanced health technology.

The Role of Housewives in the Management of Household Finances

The aim of study focuses on evaluating the role of the housewives, regarding the terms such as: financial management, knowledge and use of financial products, financial planning, forecasting and savings as well, level of debt. Female workers from the “Duxom” Corporate participated in the study, which are located in the different headquarters in the State of Mexico, Progreso, Tabasco, Sinaloa, Sonora, Guadalajara, Veracruz, and Baja California. Of the total number of employees, a non-probabilistic sample was applied by self-determination, in order to obtain the greatest number of cases in the time established for the field study, which was two months. To obtain the data we used a scale, which integrates questions from the participants' profile, and 27 items related to financial management (9 items); knowledge and use of financial products (4 items); financial planning at home (4 items), foresight and savings (3 items), debt level (7 items). With the results, a four-factor model is validated, where we can see that women like to have items to impress people, and it gives them pleasure to buy luxury items. They agree to be guarantors for other people, they make extreme decisions in investments and something very risky, they make purchases even when they cannot pay them, since they prefer to have debts than to let their children go without gifts on important dates. They like to buy online because the internet makes everything easier for them. They recognize the importance of families setting financial goals to identify priorities. Finally, they consider that having a written financial plan is essential for successful financial management of income, savings and expenses, which translates into family success.

Approaches to improving revenue and expense management in Uzbekistan's public sector

This paper explores the methods used for recognizing and recording revenues and expenses in public sector entities in Uzbekistan. It delves into the current difficulties faced and contrasts these practices with global norms, suggesting a detailed plan to improve financial governance. The proposed measures involve the implementation of contemporary accounting frameworks, the use of advanced technology, the revision of existing rules, and the promotion of global partnerships.

Digital Inclusive Finance and the Shadow Banking of Non-Financial Enterprises

In consideration of the macro background of guarding against diverting out of the real economy and the rapid development of digital inclusive finance, this study selects the A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2011 to 2019 as samples to empirically investigate the impact of digital finance on the shadow banking of non-financial enterprises. The research finds that digital finance suppresses the expansion of shadow banking business scale in non-financial enterprises. Further examination reveals that the impact of digital finance development on the shadow banking of non-financial enterprises is mainly achieved through alleviating financing constraints and reducing financing costs. Heterogeneity tests indicate that the inhibitory effect of digital finance on non-financial enterprise shadow banking is more pronounced in companies with smaller scales, poorer information disclosure quality, and higher management expense ratios. Additionally, this inhibitory effect is primarily generated by the depth of digital finance development. This study provides empirical evidence and decision-making references to clarify the inhibition of shadow banking by digital finance and guide the development of digital finance.

Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system.

Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health. Therefore, this study examined patients who underwent breast cancer surgery, analyzed hospitalization costs and structure, and explored the impact of China Healthcare Security Diagnosis Related Groups (CHS-DRG) management on patient costs. It aimed to provide medical institutions with ways to reduce costs, optimize cost structures, reduce patient burden, and improve service efficiency. To study the CHS-DRG payment system's impact on breast cancer surgery costs. Using the CHS-DRG (version 1.1) grouping criteria, 4073 patients, who underwent the radical resection of breast malignant tumors from January to December 2023, were included in the JA29 group; 1028 patients were part of the CHS-DRG payment system, unlike the rest. Through an independent sample t-test, the length of hospital stay as well as total hospitalization, medicine and consumables, medical, nursing, medical technology, and management expenses were compared. Pearson's correlation coefficient was used to test the cost correlation. In terms of hospitalization expenses, patients in the CHS-DRG payment group had lower medical, nursing, and management expenses than those in the diagnosis-related group (DRG) non-payment group. For patients in the DRG payment group, the factors affecting the total hospitalization cost, in descending order of relevance, were medicine and consumable costs, consumable costs, medicine costs, medical costs, medical technology costs, management costs, nursing costs, and length of hospital stay. For patients in the DRG non-payment group, the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses, consumable expenses, medical technology expenses, the cost of medicines, medical expenses, nursing expenses, length of hospital stay, and management expenses. The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs, medical consumable costs, and the length of hospital stay while ensuring medical safety.

Dividend Policy and its Impact on Price: Empirical Insights from Nepalese Life Insurance Companies

This study aims to evaluate the correlation and examine the impact of the explanatory factors, specifically EPS, DPS, PE ratio, management expenses to premium collected, capital to total assets, efficiency ratio, age of firm, and profitability on market price per share. Out of 14 life insurance companies operating in Nepal, 9 companies had been chosen for the study. The ordinary least square (OLS) method is used to examine the effect of predictor variables on MPS. The findings indicate that EPS, DPS, and PE ratios exhibit positive and significant correlations with and influence on share price (MPS). Moreover, this study identifies a detrimental correlation between profitability and MPS. The management expenses, in relation to the premium collected and capital to total assets, exert a detrimental and statistically significant influence on MPS. This study provides evidence in favor of the dividend relevancy theory, as it demonstrates that the dividend per share (DPS), earnings per share (EPS), and price-to-earnings (PE) ratios have a statistically significant and positive influence on the share price, as assessed by the market price per share (MPS). Nevertheless, this analysis challenges the dividend irrelevancy argument by highlighting that a company's market value is determined by its operational income rather than its capital structure or dividend payout policy. Therefore, this research supports the dividend relevancy theory. The findings of this study can be advantageous for investors seeking to enhance their returns and augment their wealth through investments in lucrative areas.

Improving MSME Accounting Financial Recording Skills Based on Android Applications

Purpose: This community service project aimed to enhance the financial recording skills of Micro, Small, and Medium Enterprises (MSMEs) in Desa Kapita through hands-on training with Android-based accounting applications. Research Design and Methodology: The project employed a mixed-methods approach, including pre-and post-training evaluations via questionnaires, interviews, and practical exercises. Involving 25 SME owners in Desa Kapita, Kecamatan Bangkala, and Kabupaten Jeneponto, the training focused on the Wave application for transaction recording, expense management, and financial report generation. The program featured interactive workshops, simulated business scenarios, and follow-up mentoring. Findings and Discussion: Post-training evaluations revealed significant improvements in financial recording skills. 80% of participants developed a solid understanding of basic accounting concepts, and 85% effectively utilized the Wave application for managing finances. The training enhanced the accuracy and efficiency of transaction recording and financial report generation, leading to improved financial oversight and business decision-making. Implications: The findings indicate that targeted training can effectively close the digital literacy gap among SME owners, promoting the use of modern financial tools. Future efforts should incorporate regular mentoring and the creation of local support networks to maintain and broaden the benefits of digital financial management solutions for MSMEs.

An Analysis of Factors Influencing Public Management Expenses by Housing Type

An Analysis of Factors Influencing Public Management Expenses by Housing Type

Effects of tree and shrub species on soil quality, sediment detachment capacity caused by rills and surface slope stability in forest lands of Northern Iran

A root system is an important factor to increase soil resistance to detachment of soil particles. However, due to the large number of species, there is a need for studying the impacts of native plant species on soil quality and soil erodibility. This investigation did flume experiments at various soil slopes (9.2%, 18.1%, 25.1%, and 32.5%) and different water flow rates (0.56, 0.67, 0.74, 0.81, and 0.94 L/(m·s)), to evaluate sediment detachment capacity caused by rills (Dc) and rill erodibility (Kr) as well as the soil quality of hillslopes with three common species including Carpinus betulus (as a natural tree species), Alnus glutinosa (as a planted tree species) and Mespilus germanica (as a shrub species) in forestland of northern Iran. The variability of Dc has been associated with soil properties and root characteristics of Carpinus betulus. Dc was significantly lower (average, −45%) for soils under Carpinus betulus compared to soils with the two other plant species (p < 0.01). This was due to the higher values of soil properties including medium weight diameter of soil aggregates (MWD), organic carbon (OC), total nitrogen (TN), total phosphorous (TP), potassium (K), calcium (Ca), magnesium (Mg) as well as to the more extended root system, as confirmed by the negative correlations between Dc and the studied variables. Kr also was different among the studied soils and plant species. The root system of Carpinus betulus also played a useful role for increasing soil resistance to rill erosion yielding a safety factor (1.61) in the studied forest ecosystem. Overall, the current study supports a broader use of native species (such as Carpinus betulus) in areas exposed to surface erosion and instability, as an effective eco-engineering conservation technique and an alternative technology instead of utilizing artificial and expensive management practices.

A Transcendental LASSO Function for Combining Machine Learning and Statistical Model Forecasts

The aim of the study is the development of methodology for accurate estimation of electric vehicle demand; which is paramount regarding various aspects of the firms decision-making such as optimal price, production level, and corresponding amounts of capital and labor; as well as supply chain, inventory control, capital financing, and operational expenses management. The forecasting methods utilized include statistical techniques (autoregressive integrated moving average [ARIMA], and polynomial regression), machine learning (nonlinear autoregressive neural network [NAR]), deep learning (long short-term memory [LSTM]), hybrid and combination forecasting. With regard to the latter method, our study experiments with four different combining model approaches, including the introduction of an original, novel combining method with the employment of a transcendental LASSO function, which is used to form combinations of forecasts generated by the NAR, ARIMA, and polynomial regression models. The LASSO-based combining model proved superior to all other models, for the majority of forecast error statistics; where the root mean square error (RMSE) and mean absolute percentage error (MAPE) values are 4.5% and 8% respectively lower than the average level of the component model forecasts. The major implications of our empirical findings are that greater accuracy in demand forecasting can be achieved with a combining model approach, rather than reliance on any particular, singular model. Furthermore, given its superior performance, the employment of the studys LASSO-based combining model to forecast electric vehicle demand may lead to optimal firm decision-making over a range of organizational facets, which is predicated on accurate demand function estimation.

Strategies for enhancing revenue and expense management in Uzbekistan's public sector

Strategies for enhancing revenue and expense management in Uzbekistan's public sector