Greater Profits Research Articles

A Comprehensive Study of Security and Cyber-Security Risk Management within e-Health Systems: Synthesis, Analysis and a Novel Quantified Approach

Internet of Things (IoT) applications are among the major trends of nowadays. Billions of connected devices are creating great business profits and performing a multitude of automated tasks in many daily human activities. In healthcare service delivery, IoT capabilities are difficult to overestimate, they are progressively becoming entangled and commonly coined Internet of Medical Things (IoMT). The participating nodes in IoMT networks generate, collect and exchange huge amounts of extremely private and sensitive data. Numerous security vulnerabilities arise due to the complexity and the heterogeneity of the technology. New risks, born out of IoMT systems, cannot easily be supported by existing risk management frameworks. The existing cyber-security risk assessment methods and approaches, deployed in several organizations, will not address the IoMT inherent risks properly. This study includes a comprehensive review of IoMT systems. Popular risk assessment methods are discussed and their suitability to IoMT is dealt with in detail. Based on this study, we propose a framework to enhance trust and help with decision making in e-healthcare environments given its high-risk exposure. The proposal is based on a quantified risk assessment approach. Our aim is to define a novel approach/model for improving trust and risk management in an e-health context.

Bioeconomic analysis of total replacement of corn grain with by-product from biscuit manufacture for purebred and crossbred Morada Nova lambs in feedlot system in the Brazilian semi-arid region.

The economic feasibility of replacing corn grain with by-product from biscuit manufacture (BBM) as an energy source in the diet for purebred and crossbred native lambs raised in feedlot was evaluated. Four production systems were developed based on nutritional management and genetic groups: (PS1) purebred native lambs fed a conventional diet based on corn and soybean meal; (PS2) purebred native lambs fed a diet with BBM replacing 100% of the corn; (PS3) crossbred native lambs fed a conventional diet based on corn and soybean meal; and (PS4) crossbred native lambs fed a diet with BBM replacing 100% of the corn in the diet. The extrapolation was performed for a module of 24 Morada Nova (MN) breed lambs (12 MN red (MNR) and 12 ½MNR × ½MN white lambs)) with an initial body weight of 18.8 ± 0.875 and 15.0 ± 0.838kg for MNR and crossbred, respectively. Feed, animal acquisition, and labor present the total production costs. The greatest profits were obtained in the production systems that fed the crossbred lambs with BBM. The lesser cost of BBM contributed to greater total factor productivity regardless of genetic group (1.095 vs. 1.015 for BBM and conventional feed, respectively). Systems using BBM (SP2 and SP4) showed an estimated payback of 5.44 and 3.24years, respectively, while the use of conventional feed contributed to negative economic data (PS1 and PS3) with payback period greater than 10years. The use of BBM as an energy source in the diet of crossbred sheep was economically feasible and showed better economic indices when compared to the systems using a conventional diet.

Optimization-driven uncertainty forecasting: Application to day-ahead commitment with renewable energy resources

The participation of power producers who generate electricity from renewable energy resources, e.g., wind and solar, in the electricity market has been significantly promoted by the high penetration of renewable electricity generation. In this case, the unit commitment is required to be formulated and solved to determine the optimal commitment in response to uncertainty existing in renewable electricity generation. To address this problem, a forecasting-first optimization-second approach has been practically applied in that the next-day renewable electricity generation is forecasted first using historical data, and then the unit commitment problem is solved using the forecasted renewable energy generation. However, the forecasting-first optimization-second approach has limitation that forecasting and optimization are decoupled, and thus, forecasting cannot be tuned by reflecting the effect of forecasted renewable energy generation on optimizing unit commitment. Given this context, this study proposes an optimization-driven renewable energy generation forecasting that is designed to integrate the unit commitment problem with the course of regression so that the regression can be done to minimize forecasting error while maximizing profit. Numerical experiments are conducted based on general regression models, e.g., auto-regressive and multiple linear regression models, with various parameter settings, and the results demonstrate that the proposed approach provides better renewable energy forecasting in terms of resulting unit commitment, i.e., greater profit and less penalty, without degrading forecasting accuracy significantly.

Optimal Debt and Risk Balancing Behavior of Rural Households in China: Evidence from a Discrete Choice Experiment

ABSTRACT Using an in-the-field discrete choice experiment on 336 farmers from rural China, this study aims to determine whether farmers optimize debt according to the optimal capital structure models and assess whether there is evidence of risk balancing behavior among Chinese farmers when they make financing decisions under risk constraints. Results suggest that farmers will increase leverage with greater profits, reduced interest rates, reduced business risk, lower risk aversion, and increasing prudence; they will reduce credit demand with increased collateral requirements, shorter repayment terms, and reduced loan usage flexibility. We also found significant heterogeneity among farmers and substantial differences across areas.

Broiler production efficiency: An analysis using thermal infrared images

The study objective was to evaluate the efficiency of using technology focusing on the thermal comfort of broilers in two poultry houses located in the metropolitan region of Teresina, Northeast Brazil, with different technological levels. One level uses cooling control of the housing and adopts high management of good production practices (Tech 1), while the second (Tech 2) was considered to use deficient technology during production. We analyzed the birds' surface temperature and the environment using infrared surface temperature data. Data were collected at a mean distance of 1 m from the birds using an infrared camera to construct the thermograms on the targets (broilers and surroundings). Data were processed using thermograms, and Boxplot graphs were built. It was found that broilers housed on the farm with higher environmental control (Tech1) obtained a better feed conversion and had more significant weight gain and greater profitability. This indicates that the greater the investment to mitigate heat stress, the better the producer's economic performance in this activity.

Rancang Bangun E-Commerce Berbasis Web untuk UMKM Batik

In the sales process carried out by batik craftsmen who are in Trusmi village, namely still selling their batik cloth to the sorum of batik sellers, so that the craftsmen take profits from selling their batik cloth only slightly, because the batik cloth will be resold by the sorum of batik sellers. In terms of application development, the author uses the Software Development Life Cycle (SLDC) model with an approach using the waterfall method, while the stages use the waterfall method, namely communication, planning, modeling, construction, and deployment. Therefore, the author makes an application for selling batik cloth that aims to break the chain of batik cloth sales, so that craftsmen can get greater profits because they directly sell their products to consumers without going through a batik seller sorum. The final result obtained in this study is an application for selling batik cloth which is expected to help batik craftsmen in Trusmi village in selling their batik cloth directly to consumers without having to go through the center of batik sellers.
 In the sales process carried out by batik craftsmen who are in Trusmi village, namely still selling their batik cloth to the sorum of batik sellers, so that the craftsmen take profits from selling their batik cloth only slightly, because the batik cloth will be resold by the sorum of batik sellers. In terms of application development, the author uses the Software Development Life Cycle (SLDC) model with an approach using the waterfall method, while the stages use the waterfall method, namely communication, planning, modeling, construction, and deployment. Therefore, the author makes an application for selling batik cloth that aims to break the chain of batik cloth sales, so that craftsmen can get greater profits because they directly sell their products to consumers without going through a batik seller sorum. The final result obtained in this study is an application for selling batik cloth which is expected to help batik craftsmen in Trusmi village in selling their batik cloth directly to consumers without having to go through the center of batik sellers.

Impact of Reducing Synthetic Chemical Inputs on Pest and Disease Management in Commercial Onion Production Systems

Onion production is reliant on synthetic chemical inputs such as fertilizer and pesticides to ensure its profitability. In the Great Lakes region (USA), onion thrips (Thrips tabaci) and a complex of bacterial pathogens that cause bulb rot disease threaten the sustainability of onion production. The potential exists for reducing T. tabaci infestations and bulb rot disease incidence in onions by decreasing the amounts of fertilizer applied at planting and the insecticide applied to foliage during the season. In a three-year study that included 20 New York commercial onion fields, the impact of synthetic fertilizer (no fertilizer, half rate, and full rate) and insecticide use (action threshold-based application program and weekly application program) on T. tabaci populations and bulb rot disease incidence was examined. Results indicated that the amount of fertilizer applied to an onion at planting had no impact on T. tabaci population levels, bulb rot disease incidence, or onion bulb size and yield. In contrast, insecticide use had the greatest impact on reducing T. tabaci densities. Both the action threshold-based program and weekly spray program reduced T. tabaci infestation levels below the economic injury level, but the action threshold program averaged 2.3 fewer applications per season. The insecticide program had no effect on bulb rot incidence, bulb size, or yield. We conclude that synthetic fertilizer and insecticide inputs can be reduced substantially without compromising onion bulb yields, and this should lead to greater profits and a reduction of chemicals in the environment.

Penerapan Konsep Ash-Shiddiq Pedagang Temporer pada Wisata Mappogau Sihanua di Kabupaten Sinjai

The dependency between a human with another human cannot be denied anymore so that it's needed a collaboration to fulfil their life based on Islam recommendation. A good Muslim is who does work that not conflict with Islamic law. Since the birth of Islam, trading has been known as a lines of fulfilling the necessities of life which is halal and recommended. The same thing happened at Tompobulu village, Bulupoddo, Sinjai where the temporary traders appeared at the certain time in a traditional party held " Mappogau Sihaua". Through this activity the trader should apply the concept of trading that has been regulated by Islam based on values and ethics that come from the basic values of religion, especially upholding the value of honesty (Ash- Shidiq) and justice, instead of taking advantages of this situation by getting the greatest profit without paying attention to the good values of trading. The temporary trader should apply Ash-Shidiq according to Islamic business ethics so that their business gets the blessing of Allah Swt. The prophet has laid down the principle of Ash- Shidiq as the basic for the implementation of justice and honesty in trading. With honesty, it is hoped that the trade of a Muslim will progress and develop.

Sustainability and profitability efficiencies: the moderating role of corporate social responsibility

AbstractTo develop a better way of assessing the sustainability efficiency (SE) and profitability efficiency (PE) of mining multinational enterprises (MNEs), the two‐stage data envelopment analysis (DEA) network model is proposed. The study shows that slack‐based models (SBM) can strengthen the previous and present measurements of the mining industry. When we assess the SE and PE of 53 mining MNEs from 2016 to 2019, the overall efficiencies of both the sustainability and profitability of mining MNEs are not higher than 70%. Such results are shown to be helpful for suggesting that global mining companies need to improve their efficiencies. This study addresses filling the research gap in the literature review about SE positively and significantly influencing PE with the moderating effect of corporate social responsibility (CSR) in mining MNEs. The result reveals that higher sustainability yields higher returns to the companies. In other words, MNEs have improved their SE to achieve a higher PE. Furthermore, the value of SE significantly influences PE regardless of whether the moderating effect, CSR, is higher or lower. The results show that a higher governance pillar score (GPS) and social pillar score (SPS) lead them to have greater profitability. However, a higher Environmental Pillar Score (EPS) tends to create a weaker relationship between SE and PE. We addressed a few interpretations of why higher EPS negatively influences profitability. Nevertheless, our study strongly recommends companies to increase their CSR score. Last, this study proves that all hypotheses are supported.

Forecast and Analysis of Stock Market Volatility Using Deep Learning Algorithms

Stock markets serve as a platform where individuals and institutional investors can come together to buy and sell shares in a public venue and ultimately impact the economy. With the advent of digital technology these markets or exchanges exist as electronic marketplaces. These markets are very volatile thus making the stock market prediction a highly challenging problem. These predictions of stock value offer great profits which serve as a huge motivation for extensive research in this area. Identifying and predicting a stock value beforehand by even a fraction of a second can result in very high profits. Similarly, a near to precise prediction can be extremely profitable in the amortized case. This attractiveness of finding a solution has motivated researchers in both industry and academia to devise techniques despite the complications due to volatility, seasonality and time dependency, economy, and other such factors. Lately, AI/ML techniques like Fuzzy Logic and Support Vector Machines (SVMs) have been used to arrive at different solutions. In this paper, we explore and develop an ensemble predictive system to forecast the market prices using deep learning algorithms. Here we consider the fractional change in stock value and the intra-day high and low values of the stock to train and employ a neural network for obtaining the trading strategy that leads to relatively superior market returns. The focus here is on the use of regression and LSTM based deep learning strategies used to predict stock values. Factors considered are open, close, low, high, and volume.

Does Dynamic Non-Linear Relationship Drive Corporate Social Responsibility Disclosure and Financial Performance?

The aim of this paper is to generate an empirical estimation of the relationship between Corporate Social Responsibility Disclosure and Financial Performance by exploring the possibility of the existence of a non-linear relationship driving these two variables. Using a strongly balanced panel data with 2580 observations from 215 African listed firms over 12 years (2005-2016), the study investigated the short-run impact of CSRD through the Arellano-Bover /Blundell-Bond technique and the long-run effect via the Delta Method based on non-linear combinations of parameters estimated. The results indicate that in the short run, CSRD affects positively ROA while a negative significant relationship between the three-lagged measure of CSRD and ROA is also revealed. The results present the insignificance of the impact of CSRD on the other firm performances variables namely ROE, ROS. In the long run, CSRD is positively linked to all of the responses variables except ROE. Thus, the findings show that CSR practices do not generate benefit immediately. CSR effort positively affects firm financial performance in the following years after implementing it. Therefore, Managers should be aware that social practices should constitute an integrant part of overall firm strategy in order to achieve great profit.

An automated cryptocurrency trading system based on the detection of unusual price movements with a Time-Series Clustering-Based approach

The cryptocurrency market, which has a rapidly growing market size, attracts the increasing attention of individual and institutional investors. While this highly volatile market offers great profit opportunities to investors, it also brings risks due to its sensitivity to speculative news and the unpredictable behaviour of major investors that can cause unsual price movements. In this paper, we argue that rapid and high price fluctuations or unusual patterns that occur in this way may negatively affect the functionality of technical signals that constitute a basis for feature extraction in a machine learning (ML)-based trading system and this may cause the generalization of the model to deteriorate. To address this problem, we propose an end-to-end ML-based trading system including a time series outlier detection module that detects the periods in which unusual price formations are observed. The training of the classification algorithms for the price direction prediction task was performed on the remaining data. We present the results related to the accuracy of the classification models as well as the simulation results obtained using the proposed system for real time trading on the historical data. The findings showed that the outlier detection step significantly increases return on investment for the machine learning-based trading strategies. Besides, the results showed that during the highly volatile periods the trading system becomes more profitable compared to the baseline model and buy&hold strategy.

Inventory Modeling: A Five Step Approach

Inventory is the array of finished goods, spares, raw materials, and other substances required in the production of the finished goods and it is a major asset to a typical manufacturing company. When utilized properly, it can yield great profits for an organization and when not managed in an optimized way, it can incur big losses. There are various methods for inventory control, some of them being JIT (just in time inventory), cross-docking, and cycle counting. But these methods never yielded dividends to companies in getting control over their inventories. Therefore the need for proper inventory models to help maintain optimal stock keeping in mind the specific constraints of each company/organization is essential, say the least. This paper presents a generic version of an inventory model for raw materials, finished goods, and spares in a stock-keeping unit (SKU) where the overall stock is considered as a dependent variable and it is expressed as a function of various parameters or independent variables such as seasonality, demand and lead times ( to name a few). The model allows the prediction of inventory levels of raw materials, finished goods, and spare parts of the machinery with a very high degree of accuracy and can subject the predictive model to various sensitivity and scenario analyses thus being able to gauge the opportunities and risks involved. As a result, there will be all-around improvements in vendor performance, procurement of raw material, handling the finished goods, and spare stocks resulting in an optimized environment in the inventory.

The heterogeneous treatment effect of low-carbon city pilot policy on stock return: A generalized random forests approach

To achieve sustainable development, China has launched the low-carbon city pilot (LCCP) program in 2010. However, the impact of this policy on firm performance has not been well investigated. By the cutting-edge generalized random forests (GRF) method, this paper takes LCCP as a quasi-natural experiment and analyzes its heterogeneous treatment effect on the stock return of Chinese firms. It is found that LCCP has a significantly negative effect on stock return and the market reacts in advance. The effect is heterogeneous and nonlinearly decided by firm features. Specifically, firms with lower financial leverage, greater profitability and longer listing years suffer more decrease in stock return. Best linear predictor test suggests that the GRF method provides satisfying estimate of the true heterogeneous treatment effect.

Out of the trap: Conversion funnel business model, customer switching costs, and industry profitability

AbstractResearch SummaryAcross many industries, firms employ a conversion funnel business model to attract customers with basic and affordable products, generate lock‐in, and then sell them more advanced and expensive products. We argue that this business model, coupled with high customer switching costs, results in a market outcome characterized by aggressive pricing and reduced profits. A sudden reduction in customer switching costs disrupts the conversion funnel and can eventually increase industrywide prices and profitability, an outcome that contradicts conventional wisdom in strategy research. We develop a stylized model to formalize our ideas and provide supportive evidence using a difference‐in‐differences methodology with staggered treatment for a large, global sample of mobile telecommunications operators.Managerial SummaryIndustry changes that lower customer frictions can surprisingly be beneficial for companies. Building on the telecommunications industry, we document how a reduction in customer switching costs following mobile number portability increases the profitability of mobile operators. We explain this finding based on a change in companies' business model. When switching costs are high, companies adopt a funnel business model designed to convert customers from basic to advanced products. While advantageous for a single company, when strategic interactions are accounted for, the diffusion of this business model has a depressive effect on average market prices and profitability. A reduction in customer switching costs breaks the funnel and decouples product pricing decisions that, counterintuitively, can lead to higher industrywide prices and greater profitability.

Yield and profitability responses of cowpea to cropping systems and sowing seasons in Vitória da Conquista, Bahia State, Brazil

Cowpea (Vigna unguiculata) crops produce a poor yield in northeastern Brazil compared to the other regions. The goal of this study was to assess the effects of irrigated cropping systems and sowing seasons on cowpea yield and profitability in Vitória da Conquista, Bahia, Brazil. Field studies were performed in four experiments during the rainy and dry seasons during 2016/2017 and 2017/2018, which denoted harvests 1, 2, 3, and 4, respectively. A randomized block design was used for each experiment with four replicates and the following treatments for cropping systems: (1) manual weeding; (2) liming and manual weeding; (3) liming and phosphorus (P) fertilization at sowing, nitrogen (N) and potassium (K) topdressing fertilization, and chemical weed control; (4) liming and P fertilization at sowing, K topdressing fertilization, rhizobia inoculation, and chemical weed control; (5) liming and P fertilization at sowing, N and K topdressing fertilization, rhizobia inoculation, and chemical weed control; and (6) seed pretreatment with cobalt (Co) and molybdenum (Mo), liming and P fertilization at sowing, N and K topdressing fertilization, rhizobia inoculation, and chemical weed control. The technology added to cropping systems increased the number of pods per plant, pod length, seeds per pod, and 100-seed weight, irrespective of the rainy or dry sowing season. Economic analysis, in turn, showed that the technology decreased the total operating cost despite increasing the cost of mechanical operations, inputs, and materials because of the replacement of manual weeding by chemical weed control. However, these costs were not influenced by the sowing seasons. We concluded that technologically enhanced cropping systems, especially systems 4 and 6, improved grain yield and provided greater profitability, which translated into improved economic benefits for farmers. Conversely, the sowing season influenced profitability, which was higher for dry season harvests, when there was less product offered and prices became higher.

Pemasaran Ayam Broiler di Kabupaten Lombok Utara terhadap nilai Tambah

Broiler chickens are superior breeds of chicken produced by crosses from chicken nations that have high productivity, especially in chicken meat production. Until now broiler chickens have been known to the Indonesian people with various advantages. Broiler chicken farms have a relatively short maintenance time and harvest time which is considered fast among other meat-producing livestock commodities. This indicates that the availability of broiler chicken meat supply tends to be continuous. In addition, many consumers tend to prioritize the consumption of broiler meat to fulfill their animal protein needs, so that many business people are interested in pursuing broiler farming because of their rapid capital turnover. In value added analysis there are three supporting components, namely: 1) Conversion factor, showing the amount of output produced from one unit of input, 2) Factor coefficient of labor, indicating the amount of labor needed to process one input unit, and 3) Product value , shows the output value per input unit. The average output value of the sale of broiler chickens obtained by large cutter traders is Rp. 28,500 per head, for small cutter traders Rp. 33,650 per head while at retailers Rp. 33,650 per output value is obtained. from the multiplication of the output price variable (selling price) with the conversion factor. The price of output for large cutter traders is smaller because the sale of products to small cutter traders and retailers. The added value of broiler chicken marketing obtained by large cutter traders is Rp.7,909.23 per head (27.75%) and small cutter traders get Rp.10,195.45 (30.30%) per head, while retailers get value added Rp.3,940.52 (11.71%) per head. Overall, small cutter traders get greater profits than large cutter traders and retailers, this is because small cutter traders buy live chicken raw materials to large cutter traders and sell them in the form of carcasses and non carcasses to end consumers. The average marketing margin obtained by large cutter traders is Rp 10,000 per head, while for small cutter traders Rp 10,500 per head, and retailers Rp.5,150 per head.

Economical planning of fuel cell vehicle-to-grid integrated green buildings with a new hybrid optimization algorithm

Popularity of fuel cell electric vehicles (FCVs) is an important criterion for solving the global problem of reducing CO2 emissions. However, the overall cost of FCVs and hydrogen fuel production is relatively high, so FCV promotion is slow. Considering that FCVs have near-zero CO2 emissions and high endurance, which is suitable for vehicle-to-grid (V2G) systems, this study aims to analyze the economic potential of the fuel cell vehicle-to-grid (FCV2G) systems to promote FCVs to the highest level. For this purpose, a large-scale green building was first selected as the research target and an agent to provide V2G services for the power grid. Then, Monte Carlo method was used to simulate the vehicle visiting time. A discharge model was also developed. Considering CO2 emission price and self-elasticity coefficient of discharge price, an overall economic optimization model was presented. Then, the hybrid algorithm of competitive swarm optimization (CSO) and imperialist competitive algorithm (ICA) was applied to optimize the model, which not only led to definite results and reduced standard deviation, but also eliminated the weakness of the CSO, i.e., convergence speed and poor performance in some benchmark functions. The simulation results indicated the proposed algorithm had faster convergence and more accuracy in finding the optimal solution than other optimization algorithms. Moreover, the overall economic profit improved in the presence of FCVs. Finally, sensitivity analysis was performed on six parameters, including daily electricity price, battery cost, fuel cell cost, CO2 emission price, power grid carbon emission, and hydrogen cost. The results showed FCV2G system had high development potential as well as great economic profit increasing over time.

Cost-Benefit Analysis of the Implementation of an Integrated Production Software in the Raw Materials Sector of A Pharmaceutical Industry

The pharmaceutical industry currently has computer systems that seek to optimize processes and allow the maximum performance of its resources through the use of computer tools. The objective of the work was to determine the costs and benefits of two different software in management of raw materials for the pharmaceutical industry. Methods: observational, descriptive, cross-sectional, study that compared ONDANET and SAP software in positive and negative costs inferred in the implementation of the tools and the benefits in terms of the profitability of the management of raw materials for the elaboration of pharmaceutical products. Results: it has been observed by using direct costs and benefits that the benefit-cost ratio of the SAP software implementation yielded a result of 15.37, whereas the ONDANET software presented a cost-benefit ratio of 0.05, which could have been demonstrated Conclusion: A widely favorable cost-benefit ratio was found for SAP Software compared to the previously used ONDANET Software, indicating that the new software used is profitable. It is desirable to periodically carry out this type of analysis to guarantee not only that the Pharmaceutical Industry has a greater profitability, without also being able to provide its products with continuity and at affordable prices for the population.

Key areas of staffing at the enterprises of the North-West region

The human capital of an enterprise is the main resource of every organization, the quality and efficiency of which largely depend on the results of the company's activities and its competitiveness. Labor resources set in motion the material elements of production, create a product, value and surplus product in the form of profit. By investing in staff and creating comfortable conditions for the professional growth of employees, a business entity can count on a greater profit than investing only in solving production tasks. Which is consistent with the objectives of the Regional Staffing Standard and ensures interdepartmental cooperation in the regions on staffing issues of the regional economy, improving the efficiency of these processes, developing human resources for the long term, attracting and retaining human resources, training and retraining of highly qualified personnel in accordance with the international standards and market requirements, allows you to monitor the effectiveness of the implementation of regional personnel policy, systematize modern management practices, mechanisms and tools for staffing. At the same time, it is necessary to have a clear and objective situational picture of the causes of the current conjuncture in the staffing sector. What causes the need to analyze the prerequisites for the directions of development, the motives for the increase in the turnover of human resources, etc. The article analyzes the main reasons for the dismissal of employees of industrial enterprises of the North-Western District, highlights the opportunities provided by the enterprise for the development of human resources.