Tool For Management Decisions Research Articles

APPLICATIONS OF NON-TRADITIONAL EARNED VALUE MANAGEMENT MODELS IN PROJECT ANALYTICS

Effective management of financial resources in projects is crucial for project success. Often, difficulties with financial resources, such as budget overruns, lead to unfavorable consequences that directly impact the successful completion of the project, the quality of the outcome, and stakeholder satisfaction. Therefore, identifying and developing tools for the effective management of financial resources, is of paramount importance. The purpose of this study is to apply non-traditional earned value management (EVM) models based on machine learning to predict project costs. To achieve the research objectives, previous literature on the topic was analyzed, a dataset of past projects was prepared, and a machine learning model was applied. The study found that non-traditional models, such as the regression algorithm AdaBoost, produced results close to the actual costs. The research indicates that the developed model could become an indispensable tool for project management and business decision-making, as it demonstrates the ability to adapt to various conditions and make accurate forecasts.

Utilising Design Thinking To Alleviate The Effects Of Covid-19 On Civil Servant Operations

The phenomenon of design thinking has a significant potential to form a synergistic interaction of individual abilities of leaders, managers and civil servants in the context of global challenges caused by the consequences of the COVID-19 pandemic. Against the backdrop of these issues, ensuring the effectiveness of key state institutions and organisations is of particular relevance, which, in turn, requires a detailed analysis of potential measures to counteract negative impacts. The aim of the study is to analyse the potential of design thinking in the context of developing and implementing a comprehensive mechanism for overcoming the effects of COVID-19 on the activities of civil servants. The article focuses on the functionality of design thinking in terms of civil servants’ basic professional and personal skills. The possibility of their allocation as separate indicators of the concept is considered. The structural elements of design thinking are outlined, and each of them is described in detail. The imperative for establishing a unified mechanism to address the pandemic’s existing and potential adverse consequences is clearly demonstrated. The peculiarities of integrating design thinking based on the Stanford concept into the work of civil servants in Ukrainian public institutions are described. It is assumed that implementing this goal will increase the efficiency of civil servants, forming an effective mechanism for mitigating the risks caused by the pandemic. The author identifies sustainable principles that can facilitate the operational and strategic management of team performance in the civil service. The priorities for further improvement of design thinking skills to improve the efficiency of public institutions are revealed. The specifics of the Stanford model as an effective tool for team development and management decision-making are investigated. The main principles of the mechanism for overcoming the destructive effects of COVID-19 through the introduction of design thinking technology, which helps improve public institutions’ efficiency and quality of work and create favourable conditions for team effectiveness, are analysed. The study’s results have practical value in the development, improvement and modernisation of the design thinking concept to minimise the impact of the adverse effects of the COVID-19 pandemic.

Deep learning infused SIRVD model for COVID-19 prediction: XGBoost-SIRVD-LSTM approach.

The global impact of the ongoing COVID-19 pandemic, while somewhat contained, remains a critical challenge that has tested the resilience of humanity. Accurate and timely prediction of COVID-19 transmission dynamics and future trends is essential for informed decision-making in public health. Deep learning and mathematical models have emerged as promising tools, yet concerns regarding accuracy persist. This research suggests a novel model for forecasting the COVID-19's future trajectory. The model combines the benefits of machine learning models and mathematical models. The SIRVD model, a mathematical based model that depicts the reach of the infection via population, serves as basis for the proposed model. A deep prediction model for COVID-19 using XGBoost-SIRVD-LSTM is presented. The suggested approach combines Susceptible-Infected-Recovered-Vaccinated-Deceased (SIRVD), and a deep learning model, which includes Long Short-Term Memory (LSTM) and other prediction models, including feature selection using XGBoost method. The model keeps track of changes in each group's membership over time. To increase the SIRVD model's accuracy, machine learning is applied. The key properties for forecasting the spread of the infection are found using a method called feature selection. Then, in order to learn from these features and create predictions, a model involving deep learning is applied. The performance of the model proposed was assessed with prediction metrics such as R 2, root mean square error (RMSE), mean absolute percentage error (MAPE), and normalized root mean square error (NRMSE). The results are also validated to those of other prediction models. The empirical results show that the suggested model outperforms similar models. Findings suggest its potential as a valuable tool for pandemic management and public health decision-making.

Personality in Asian elephants (Elephas maximus): Temporal stability and methods of assessment

Personality is the essence of individuality in animals, affecting individual behaviours, perceptions and lived experiences. Being able to reliably assess personality in animals holds the key to understanding individual differences, and application of this knowledge is paramount in the provision of individual-level management of animals to optimise welfare. A key aspect of the definition of animal personality is ‘consistency over time’. Yet, despite the range of studies assessing elephant personality, there is a lack of consistency within methodologies and personality is usually assessed at a single point in time. Here, we examine personality data from adult members of the Asian elephant (Elephas maximus) herd at Chester Zoo at five separate time points, across a ten-year period (2013−2023). Data were analysed in terms of the instruments used to measure personality (differences in questions/items across assessments, presentation of the personality assessments, raters), and changes over time in elephant personality assessment scores. Select personality traits were consistent over multiple time points. Inter-rater reliability across personality adjectives is highest when keepers are involved in scale development, reinforcing the importance of collaboration between scientists and animal caregivers in building tools for evidence-based management decisions over the lifetime of animals.

A geospatial web service for small pelagic fish spatial distribution modeling and mapping with remote sensing

Small pelagic fish are an essential resource for coastal countries worldwide and their assessment and monitoring are a key part of successful fisheries management. Advances in marine satellite remote sensing can contribute to the creation of methodologies for continual small pelagic fish spatial distribution monitoring that can act as supplementary tools for fisheries management decision making, enhancing traditional field practices. In this work a comprehensive Geospatial Web Service (GWS) is proposed that utilizes Sentinel-3 data to publish Spatial Distribution Modeling (SDM) maps for anchovy (Engraulis encrasiculous) and sardine (Sardina pilchardus). The proposed GWS is developed through the sole use of open-source programming languages and software and provides fishery management related data through various parameters: A) Sea Surface Temperature (SST) and Chlorophyll-a Concentration (CHL), B) mesoscale oceanic fronts and C) the SDM maps for the target species. The SDM results are produced through a Random Forest algorithm and utilized oceanographic parameters relevant to the ecological needs of the target species (CHL, SST, oceanic fronts and bathymetry). All data are processed and gap-free through a spatiotemporal DINEOF interpolation, allowing the continuous provision of information independently of the weather conditions. Furthermore, the service integrates auxiliary information, such as weather and sea state forecasts, that aim to contribute to maritime safety for effective decision-making. The resulting GWS offers an easy to use and interactive tool that bridges the gap between the scientific community and the decision makers. The utilization of satellite remote sensing enhances the scalability of the proposed service for future improvements and continuous monitoring.

Performance Management Decision-Making Model: Case Study on Foreign Language Learning Curriculums

Foreign language learning courses can be regarded as a service operation system, and a complete foreign language learning course performance evaluation model can help improve the effectiveness of student learning. The performance evaluation matrix (PEM) is an excellent tool for evaluation and resource management decision making, and the administrator uses the satisfaction and the importance indices to establish evaluation coordinate points based on the rules of statistical testing. The coordinate points of all service items are plotted into the PEM to grasp the full picture and to make decisions on what to improve or to consider resource transfers so as to elevate the overall satisfaction of the entire service. However, plotting all the coordinate points on the PEM can only be performed by programming, which will lead to limitations in practice. Therefore, instead of the above evaluation rules, this article uses the confidence intervals of decision-making indicators to form a validity evaluation table, to decide which teaching service items should be improved, maintained, or transferred to improve the satisfaction of the entire service system. This form of performance evaluation can be completed using any commonly used word-processing software, so it is easy to apply and promote. Finally, this article provides an applied example to illustrate the proposed method.

ANALISIS ARUS KAS UNTUK PENGAMBILAN KEPUTUSAN PADA CV ELSA MANDIRI ABADI

The cash flow report is a very important part of a company which describes the amount of cash receipts and expenditures. The cash flow report consists of operating activities, investment activities, and financing activities. To maintain the continuity of the company, a cash flow is very necessary and the company can read the cash flow calculations for decision making. The research aims to find out whether information on cash flow from operating activities is a step in making company management decisions. The research was carried out at CV Elsa Mandiri Abadi, located on Jalan Setia Budi, Klegen Madiun. The type of research is descriptive qualitative. The results of the research are the adequacy of the company's operating cash flow to meet all its needs is quite good. The results of the overall ratio calculation are an analysis of the ratio of operating cash flow to current debt, the ratio of operating cash flow to total debt, the interest coverage ratio the ratio of cash flow to net profit, and the quality ratio. sales for 3 periods in the company that cash flow can be used as a management decision-making tool because the results are positive. Management decision-making includes: 1) Consider purchasing fixed assets; 2) Fixed assets that are not useful should be sold to be realized as cash; and 3) Companies need to reduce expenditure items and make efficiencies to increase profit margins

Creation of a complex multivariate integrated model of the oil interfield transport system

Background. In conditions of variability of external and internal factors that directly affect the loading of the existing hydrocarbon transport system, the risks arise associated with the productive capacity of the existing infrastructure and noncompliance with the requirements for the quality of delivered oil. Objective. To create a tool allowing to assess the degree of loading of existing infrastructure facilities and indicators of the commercial quality of oil at commercial delivery sites in the near and long term, the availability of which is essential for risk minimization. Materials and methods. An integrated model in combination with automation tools is an effective tool for making strategic decisions in order to develop the assets of a subsurface user company. Results. By the example of transport infrastructure, the paper describes an approach to using the gathering system model, which jointly with automation algorithms allows solving a number of strategic tasks of oil and gas producers, such as performing multivariate hydraulic calculations and monitoring oil quality in order to verify compliance with the requirements. Conclusions. An integrated model in combination with the developed automation tools is an auxiliary tool for management decision-making. The tool helps to significantly reduce the labor costs for performing calculations and primary processing of the results. The implemented approaches can be used for hydraulic calculations and monitoring of limitations of transportation networks of similar configuration.

ABOUT THE GEOGENIC FLUOR ELEMENT AND DENTAL FLUOROSIS IN THE STATE OF BAHIA, BRAZIL

The findings between the relationships between the geological/geochemical environment and the health of populations, based on the effect of the chemical element fluor of geogenic origin present in the groundwater of several locations in the State of Bahia, Brazil present numbers that indicate values of the order of 0.4 mg/L F, as a risk to populations, 0.4 to 0.8 mg/L F as a protective factor and >0.8 mg/L F as a myth prone to dental fluorosis. Analyses of water for human consumption, in particular fluor concentrations, represent an important planning and decision-making tool for managers and municipal bodies regarding water fluoridation and the presence of natural fluoride. The results presented can promote prevention strategies for a series of diseases, including dental fluorosis and highlight, in a striking way, the importance of geogenic materials and the health of populations.

Risk of cardiovascular death in patients with hepatocellular carcinoma based on the Fine-Gray model.

Hepatocellular carcinoma (HCC) is one of the most common types of cancers worldwide, ranking fifth among men and seventh among women, resulting in more than 7 million deaths annually. With the development of medical technology, the 5-year survival rate of HCC patients can be increased to 70%. However, HCC patients are often at increased risk of cardiovascular disease (CVD) death due to exposure to potentially cardiotoxic treatments compared with non-HCC patients. Moreover, CVD and cancer have become major disease burdens worldwide. Thus, further research is needed to lessen the risk of CVD death in HCC patient survivors. To determine the independent risk factors for CVD death in HCC patients and predict cardiovascular mortality (CVM) in HCC patients. This study was conducted on the basis of the Surveillance, Epidemiology, and End Results database and included HCC patients with a diagnosis period from 2010 to 2015. The independent risk factors were identified using the Fine-Gray model. A nomograph was constructed to predict the CVM in HCC patients. The nomograph performance was measured using Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and area under the ROC curve (AUC) value. Moreover, the net benefit was estimated via decision curve analysis (DCA). The study included 21545 HCC patients, of whom 619 died of CVD. Age (< 60) [1.981 (1.573-2.496), P < 0.001], marital status (married) [unmarried: 1.370 (1.076-1.745), P = 0.011], alpha fetoprotein (normal) [0.778 (0.640-0.946), P = 0.012], tumor size (≤ 2 cm) [(2, 5] cm: 1.420 (1.060-1.903), P = 0.019; > 5 cm: 2.090 (1.543-2.830), P < 0.001], surgery (no) [0.376 (0.297-0.476), P < 0.001], and chemotherapy(none/unknown) [0.578 (0.472-0.709), P < 0.001] were independent risk factors for CVD death in HCC patients. The discrimination and calibration of the nomograph were better. The C-index values for the training and validation sets were 0.736 and 0.665, respectively. The AUC values of the ROC curves at 2, 4, and 6 years were 0.702, 0.725, 0.740 in the training set and 0.697, 0.710, 0.744 in the validation set, respectively. The calibration curves showed that the predicted probabilities of the CVM prediction model in the training set vs the validation set were largely consistent with the actual probabilities. DCA demonstrated that the prediction model has a high net benefit. Risk factors for CVD death in HCC patients were investigated for the first time. The nomograph served as an important reference tool for relevant clinical management decisions.

Lean Accounting: A Decision-Making Tool

Lean accounting is a management decision-making tool available to companies involving streamlining a company’s competitive internal management strategy to minimize waste, such as excess inventory, to maximize profits. This exploration of lean accounting processes looks at how companies can maximize continuous improvement using reporting and accounting methods. Barriers to lean accounting implementation are identified together with means for their resolution. The basic understanding of lean accounting is it targets waste and non-value-adding activities especially those that do not benefit the internal or external stakeholder in the manufacturing or service setting. Lean accounting offers specific styled reports, performance measures.

U.S. cereal rye winter cover crop growth database

Winter cover crop performance metrics (i.e., vegetative biomass quantity and quality) affect ecosystem services provisions, but they vary widely due to differences in agronomic practices, soil properties, and climate. Cereal rye (Secale cereale) is the most common winter cover crop in the United States due to its winter hardiness, low seed cost, and high biomass production. We compiled data on cereal rye winter cover crop performance metrics, agronomic practices, and soil properties across the eastern half of the United States. The dataset includes a total of 5,695 cereal rye biomass observations across 208 site-years between 2001–2022 and encompasses a wide range of agronomic, soils, and climate conditions. Cereal rye biomass values had a mean of 3,428 kg ha−1, a median of 2,458 kg ha−1, and a standard deviation of 3,163 kg ha−1. The data can be used for empirical analyses, to calibrate, validate, and evaluate process-based models, and to develop decision support tools for management and policy decisions.

МЕТОДИ ДЛЯ НАПРАЦЮВАННЯ, АНАЛІЗУ ТА ПРОГНОЗУВАННЯ ВАРІАНТІВ УПРАВЛІНСЬКИХ РІШЕНЬ В ПРОЦЕСІ ЇХ ПРИЙНЯТТЯ

Methods for managerial decision-making in the process of decision-making are considered. Management decisionmaking tools are studied in the field of management and analysis. They include methods, models and approaches that help managers make informed decisions. Decision-making in any organization is a key task. It begins with determining the type of activity and strategic issues, without which the existence of the enterprise becomes impossible. Managers are guided by decision-making to minimize possible risks and achieve strategic goals. To make optimal decisions, it is necessary to carefully analyze all existing risks and optimize the decision-making process. To achieve successful solutions to these problems, it is necessary to conduct a comprehensive analysis of management decision-making methods. It is noted that the effectiveness of a decision depends on the decision-making methods. Since the stages of development and adoption of a management decision form a full cycle of the management decision-making process. At the same time, the composition and content of the stages depends on the specific management problem. The effectiveness of a managerial decision is determined by the methods used in the process of its adoption and implementation at an enterprise. The stages of development and adoption of a managerial decision from the point of view of different scientific schools are considered. The basic requirements for a managerial decision in the process of management activity are characterized, namely, realism, specificity, informativeness, and consistency. The peculiarities of applying these terms in relation to management decisions made at an enterprise are analyzed. A review of existing technologies for developing and making management decisions in the enterprise management system is carried out. The range of research methods for substantiating the adoption, development and implementation of a management decision is grouped into classes. The article also discusses the variety of decision-making methods, from those based on the intuition and experience of managers to formalized methods that use mathematical tools. This work is important for understanding and improving the decision-making process in various areas of management.

Development of web‐based hydrograph analysis tool considering seasonality and flow condition

AbstractBaseflow was proven to be the most unpredictable component of streamflow through various research. However, the recent method for estimating baseflow is due to the development of theoretical and computational techniques. This paper attempted to develop a fully automated baseflow separation system based on a recursive digital filter with an optimization algorithm for the single separation. Most of the previous baseflow separation methods use a single set of a parameter and BFImax (the maximum value of baseflow index), which can underestimate or overestimate the baseflow; however, the system developed in this study estimates multiple optimized a parameters using seasonality and flow conditions and uses them for BFImax calculation and baseflow separation. This system derived baseflow results in better understanding of watershed and streamflow tendency characteristics. This study developed a Web‐based Hydrograph Analysis Tool 2020 with a user‐friendly interface and new separation method regarding the seasonality and flow conditions with a fully automated python module to optimize a parameters and BFImax. The application to the two area show diverse parameter sets and different baseflow according to seasonality and flow conditions representing the flow characteristics. This study could be a fundamental tool for detailed watershed management decisions regarding water security in the dry season or environmental water for aquatic ecosystems.

Creation of financial business models in beef cattle breeding: structure and stages

The goal is to develop an algorithm for financial modeling of business processes in beef cattle breeding. Methods – general scientific and empirical. The logical method was used to determine the structure of the study and identify cause-and-effect relationships. The collected material is systematized, summarized and analyzed taking into account the technological features of the industry, modern market conditions, regulatory requirements, financing criteria and government measures to support agricultural producers in the republic. Methods of synthesis, comparison, comparison, and mathematical calculations were also used. Results - the authors proposed financial business model that promotes flexibility in planning production program for keeping and raising livestock for meat. The advantages of financial model in cattle breeding for meat productivity are substantiated as an effective tool for information support, planning, analysis and management decision-making, consisting in the fact that the content of each component of the mathematical financial model allows you to study their components and collect information necessary for financial and economic calculations. The composition of the elements for constructing a financial strategy for breeding beef cattle has been determined, including initial data, analytical calculations, and resulting parameters. A step-by-step algorithm for financial business planning has been created, from initial parameters and assumptions to the calculation of technological and economic efficiency indicators. Conclusions - based on financial modeling of business processes, farmers will have the opportunity to preliminarily assess profitability, find savings reserves, and predict costs for intensive beef cattle farming. A comprehensive business analysis with a financial model and assessment of the market situation is necessary in order to obtain a loan, attract investment and prepare an investment project.

Development of a quantitative microbiological spoilage risk assessment (QMSRA) model for cooked ham sliced at retail

A quantitative microbiological spoilage risk assessment model (QMSRA) for cooked ham sliced at retail was developed based on a stochastic growth model for lactic acid bacteria (LAB), which are considered as the specific spoilage organisms (SSO), and a “spoilage-response” relationship characterizing the variability in consumer's perception of spoilage. In a simulation involving 10,000 cooked ham purchases, the QMSRA model predicted a median of zero spoilage events for up to 4.5 days of storage. After storage times of 5 and 6 days, the model predicted 1,790 and 8,570 spoilage events, respectively. A sensitivity analysis showed that domestic storage temperature was the most significant factor affecting LAB concentration in cooked ham, followed by the LAB contamination level at slicing. A scenario analysis was performed testing better temperature control of consumer's refrigerators, better hygiene conditions during slicing and a combination of the two strategies. Among the tested scenarios, a 2 log reduction in the LAB contamination at slicing combined with a 2 °C decrease in domestic storage temperature resulted in zero risk of spoilage for up to 12 days of storage. The QMSRA model developed in the present study can be a useful tool for quality management decisions.

Development of the @Antidotos_bot chatbot tool for poisoning management

ObjectiveTo describe the development of the Antidotos_bot chatbot tool, which is used to facilitate the search for information in the Antidote Administration Guide and to perform useful calculations in the use of antidotes. MethodIn January 2019, we proposed developing a freely accessible chatbot on Telegram® using Xenioo®. Software development defined the way it interacts with users and incorporated calculation functionalities. Internal validation was conducted and it was presented as Antidotos_bot in June 2019. ResultsAntidotos_bot included information in Spanish on 49 antidotes and 57 poisonings. Three types of calculations were provided and two treatment algorithms could be consulted. Consultation was possible through 332 questions. Internal validation needed five sets of training over 2 months. By July 2020, it had 415 users. The most frequently consulted antidotes were glucagon, penicillin G, protamine, n-acetylcysteine and flumazenyl. Regarding monthly activity, there was an average of 29 calculations and an average of three new users and three queries per user. ConclusionsAntidotos_bot is a poisoning management decision-making tool that provides up-to-date information in a user-friendly manner. It could contribute to improving the quality and safety of care in emergency situations.

A novel shared decision-making (SDM) tool for anticoagulation management in atrial fibrillation: protocol for a prospective, cluster randomized controlled trial

BackgroundAtrial fibrillation (AF) is a common arrhythmia that requires anticoagulation therapy to prevent stroke. However, there is still a significant under-/over-treatment in stroke prevention for patients with AF. The adherence and the risk of bleeding associated with oral anticoagulation therapy (OACs) are major concerns. Shared decision-making (SDM) is an approach that involves patients and healthcare providers in making decisions about treatment options. This study aims to assess the effectiveness of a novel SDM tool for anticoagulation management in AF.MethodsThe study will be a prospective, cluster randomized controlled trial involving 440 patients with AF in 8 community health service centers (clusters) in Shanghai, China. The SDM group will receive anticoagulation management through the novel SDM tool, while the control group will receive standard care. The follow-up period will be at least 2 years. The primary outcome will be any bleeding event, while secondary outcomes include the accordance of stroke prophylaxis for AF according to the current guidelines, time in therapeutic range (TTR), the occurrences of major bleeding and thrombosis events, and patient knowledge, adherence, and satisfaction.DiscussionThis study will provide evidence of the effectiveness of shared decision-making in improving the appropriateness of OAC use in Chinese AF patients. The findings may inform the development of guidelines and policies for the management of AF and anticoagulation therapy in China and other countries.Trial registrationChiCTR ChiCTR2200062123. Registered on 23 July 2022.

S1656 Development of a Shared Decision-Making Tool for Obesity Management

S1656 Development of a Shared Decision-Making Tool for Obesity Management

Selection of effective tools for organizing passenger transportation in the Leningrad region

The article considers problems and possible ways to solve them in the current system of organizing passenger transportation by public transport in the Leningrad Region. Existing models of transport services in today’s difficult conditions of dynamic changes in passenger traffic, increasing the cost of fuel and lubricants and spare parts do not allow the carrier to ensure timely updates of rolling stock and force them to look for ways to reduce material costs to the detriment of the quality of passenger service on routes. The system of organization of passenger transportation in the Leningrad region is complex and multi-level, so its effective management is impossible without science-based tools for management decisions. Keywords: passenger transportation, transport model, quality of passenger service, transportation costs, multi-criteria model