Variable and Invariable,Explore the Value-Creation Techniques of Management Accounting by Benchmarking the Financial Management of Large Enterprises

With the development of information technology such as ChatGPT,artificial intelligence,5G,and so on,technological innovation brings about a qualitative change in the economic business.This change is embodied in breakthroughs in the field of science and technology and the iterative upgrading process of products.The traditional business model undoubtedly fails to adapt to the management needs of modern enterprises,while traditional financial practices and knowledge reserves cannot meet these needs.Faced with sudden technological changes and the emergence of financial sharing,financial robots,etc.,there is an urgent need for financial practitioners to transform from traditional financial accounting to value-creating management accounting.In the future,financial professionals with the ability to embrace uncertainty,adapt to environmental changes,and find breakthroughs in uncertain environments will be the most sought-after by enterprises.This paper aims to benchmark the excellent financial management models of large enterprises and conduct thematic research on financial management in large enterprises.It seeks to explore,in the era of big data management accounting,the road and art of creating value in enterprises.The objective is to provide references for colleagues in the financial field and to explore effective ways to generate value for enterprise management ideas,thus serving as a reference point in the financial transformation journey.

Research on the Optimization of Enterprise Financial Management under the Financial Sharing Model

With the advancement of globalization and information technology,the financial sharing mode has gradually emerged as a crucial means for enterprises to optimize their financial management.Particularly within the context of economic globalization,informatization,and digital transformation,enterprises find themselves navigating a rapidly evolving market environment by intensifying competition.To enhance efficiency and competitiveness,many enterprises have embraced the financial sharing model to streamline financial management processes,curtail costs,and bolster the execution of corporate strategies.This article aims to dissect the definition and essence of the financial sharing model and its significance in the realm of enterprise financial management.Drawing upon this analysis and aligning with the needs of enterprise financial management,the article proposes ideas for optimizing management practices,aspiring to foster reform and innovation in enterprise financial management while enhancing its level of financial management and ability to respond to financial risks.This contribution seeks to provide valuable insights for practitioners in the field.

Artificial Intelligence for Maximizing Agricultural Input Use Efficiency: Exploring Nutrient, Water and Weed Management Strategies

Agriculture plays a crucial role in the economy,and there is an increasing global emphasis on automating agri-cultural processes.With the tremendous increase in population,the demand for food and employment has also increased significantly.Agricultural methods traditionally used to meet these requirements are no longer ade-quate,requiring solutions to issues such as excessive herbicide use and the use of chemical fertilizers.Integration of technologies such as the Internet of Things,wireless communication,machine learning,artificial intelligence(AI),and deep learning shows promise in addressing these challenges.However,there is a lack of comprehensive documentation on the application and potential of AI in improving agricultural input efficiency.To address this gap,a desk research approach was used by utilizing peer-reviewed electronic databases like PubMed,Scopus,Goo-gle Scholar,Web of Science,and Science Direct for relevant articles.Out of 327 initially identified articles,180 were deemed pertinent,focusing primarily on AI’s potential in enhancing yield through better management of nutrients,water,and weeds.Taking into account researchfindings worldwide,we found that AI technologies could assist farmers by providing recommendations on the optimal nutrients to enhance soil quality and deter-mine the best time for irrigation or herbicide application.The present status of AI-driven automation in agricul-ture holds significant promise for optimizing agricultural input utilization and reducing resource waste,particularly in the context of three pillars of crop management,i.e.,nutrient,irrigation,and weed management.

Current state and influencing factors in airbag management among emergency department nurses:A multicenter study

BACKGROUND The emergency department(ED)plays a critical role in establishing artificial airways and implementing mechanical ventilation.Managing airbags in the ED presents a prime opportunity to mitigate the risk of ventilator-associated pneumonia.Nonetheless,existing research has largely overlooked the understanding,beliefs,and practical dimensions of airway airbag management among ED nurses,with a predominant focus on intensive care unit nurses.AIM To investigate the current status of ED nurses'knowledge,beliefs,and practical behaviors in airway airbag management and their influencing factors.METHODS A survey was conducted from July 10th to August 10th,2023,using convenience sampling on 520 ED nurses from 15 tertiary hospitals and 5 sary hospitals in Shanghai.Pathway analysis was utilized to analyze the influencing factors.RESULTS The scores for ED nurses'airway airbag management knowledge were 60.26±23.00,belief was 88.65±13.36,and behavior was 75.10±19.84.The main influencing factors of airbag management knowledge included participation in specialized nurse or mechanical ventilation training,department,and work experience in the department.Influencing factors of airbag management belief comprised knowledge,department,and participation in specialized nurse or mechanical ventilation training.Primary influencing factors of airbag management behavior included knowledge,belief,department,participation in specialized nurse or mechanical ventilation training,and professional title.The belief in airbag management among ED nurses acted as a partial mediator between knowledge and behavior,with a total effect value of 0.513,and an indirect effect of 0.085,constituting 16.6%of the total effect.CONCLUSION ED nurses exhibit a positive attitude toward airbag management with relatively standardized practices,yet there remains room for improvement in their knowledge levels.Nursing managers should implement interventions tailored to the characteristics of ED nurses'airbag management knowledge,beliefs,and practices to enhance their airbag management proficiency.

Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

Management of lateral pelvic lymph nodes in rectal cancer:Is it time to reach an Agreement?

In this editorial,we proceed to comment on the article by Chua et al,addressing the management of metastatic lateral pelvic lymph nodes(mLLN)in stage II/III rectal cancer patients below the peritoneal reflection.The treatment of this nodal area sparks significant controversy due to the strategic differences followed by Eastern and Western physicians,albeit with a higher degree of convergence in recent years.The dissection of lateral pelvic lymph nodes without neoadjuvant therapy is a standard practice in Eastern countries.In contrast,in the West,preference leans towards opting for neoadjuvant therapy with chemoradiotherapy or radiotherapy,that would cover the treatment of this area without the need to add the dissection of these nodes to the total mesorectal excision.In the presence of high-risk nodal characteristics for mLLN related to radiological imaging and lack of response to neoadjuvant therapy,the risk of lateral local recurrence increases,suggesting the appropriate selection of strategies to reduce the risk of recurrence in each patient profile.Despite the heterogeneous and retrospective nature of studies addressing this area,an international consensus is necessary to approach this clinical scenario uniformly.

Design and Implementation of Library Seating Management System

The library seating management system is an important part of the library’s modern services. The system is based on the Spring and Spring Boot framework, and the system realizes a series of functions such as real-time query, reservation, and cancellation of seat resources, providing users with great convenience. With a simple operation, users can know the availability of seats in the library in real time and reserve them according to their needs. At the same time, the system also provides rich management functions, enabling administrators to easily configure and manage seat resources. The addition, deletion, modification and review of users, the generation of seats, the viewing of user usage records, and the addition or deletion of points for users’ usage can also be carried out. This not only improves the management efficiency, but also provides more scientific and accurate data support for the management of the library. The system not only optimizes the user experience, but also promotes the scientific management and efficient utilization of library resources, and provides strong support for the modern services of the library.

Intelligent Decision-Making in Warehouse Management: How AI Automation Improves Inventory Tracking, Order Fulfillment, and Logistics Efficiency Compared to Drone Technology

This paper analyzes how artificial intelligence (AI) automation can improve warehouse management compared to emerging technologies like drone usage. Specifically, we evaluate AI’s impact on crucial warehouse functions—inventory tracking, order fulfillment, and logistics efficiency. Our findings indicate AI automation enables real-time inventory visibility, optimized picking routes, and dynamic delivery scheduling, which drones cannot match. AI better leverages data insights for intelligent decision-making across warehouse operations, supporting improved productivity and lower operating costs.

Optimization Management of Industrial Organizations Based on Performance Indicators

This paper proposes an intelligent management system (IMS) to help managers in their delicate and tedious task of exploiting the plethora of data (indicators) contained in management dashboards. This system is based on intelligent agents, ontologies and data mining. It is implemented by PASSI (Process for Agent Societies Specification and Implementation) methods for agent design and implementation, the Methodology for Knowledge Modeling and Hot-Winters for data prediction. Intelligent agents not only track indicators but also store the knowledge of managers within the company. Ontologies are used to manage the representation and presentation aspects of knowledge. Data mining makes it possible to: make the most of all available data;model the industrial process of data selection, exploration and modeling;and transform behaviors into predictive indicators. An instance of the IMS named SYGISS, currently in operation within a large brewery organization, allows us to observe very interesting results: the extraction of indicators is done in less than 5 minutes whereas manual extraction used to take 14 days;the generation of dashboards is instantaneous whereas it used to take 12 hours;the interpretation of indicators is instantaneous whereas it used to take a day;forecasts are possible and are done in less than 5 minutes whereas they did not exist with the old management. These important contributions help to optimize the management of this organization.

Leadership and Top Management Influence on Total Quality Management Implementation in the Ghanaian Construction Industry

This study aims to determine the key and underlying Leadership and Top Management (LTM) factors that have a significant impact on sustaining the implementation of Total Quality Management (TQM) within the construction industry in Ghana. The research methodology employed in this study was a quantitative technique. Questionnaires were distributed to 641 participants within construction industry in Ghana. Questionnaires retrieved for the analysis were 536. Three steps approached were used for the data analysis. These include Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) analysis. After conducting the EFA and CFA, SEM was also used to analyze the construct validity. The SEM analysis helps to determine four key indicator variables for the leadership and top management construct. These include Leadership/Top Management approach to employees’ management, Leadership/Top Management understanding of TQM, Leadership/Top Management empowerment of employees to resolve quality issues, and Leadership/Top Management endorsement of TQM. All the four indicator variables were found to be good of fit and closely associated with the dependent variable. The study adds to the body of knowledge by using EFA, CFA and SEM techniques to establish key leadership and top management factors affecting TQM implementation in Ghana’s construction industry. The findings in general suggested that leadership and top Management factors identified have a direct positive impact on sustaining TQM implementation in the Ghanaian construction industry. Consequently, the leadership and top management factors identified in this study can help improve TQM in the Ghanaian construction industry.

Optimizing Resource Management for IoT Devices in Constrained Environments

Embedded computing device implementation on the Internet of Things (IoT) requires careful assessment of their intrinsic resource limitations. These constraints are not limited to memory and processing capabilities but extend to the network interfaces, particularly due to the low-power radio standards that these devices typically employ. The IPv6 protocol is shown to be a strong option for guaranteeing interoperability in the IoT, mostly because of its large address space, the range of current IP-based protocols, and its intrinsic versatility. Considering these benefits, we investigate if current IP-based network management protocols can be implemented on devices with limited resources. We investigate the resource needs in particular for implementing Network Configuration Protocol (NETCONF) and Simple Network Management Protocol (SNMP) on an 8-bit AVR-based device. Our investigation reveals the specific memory and processing demands of these protocols, providing valuable insights into their practicality and efficiency in constrained IoT environments. This study underscores the potential and challenges of leveraging IPv6-based network management protocols to enhance the functionality and interoperability of IoT devices while operating within stringent resource limitations.

Assessment of Municipal Solid Waste Management in the Farmgate Area of Dhaka North City Corporation

This investigation is focused on conducting a thorough analysis of Municipal Solid Waste Management (MSWM). MSWM encompasses a range of interdisciplinary measures that govern the various stages involved in managing unwanted or non-utilizable solid materials, commonly known as rubbish, trash, junk, refuse, and garbage. These stages include generation, storage, collection, recycling, transportation, handling, disposal, and monitoring. The waste materials mentioned in this context exhibit a wide range of items, such as organic waste from food and vegetables, paper, plastic, polyethylene, iron, tin cans, deceased animals, byproducts from demolition activities, manure, and various other discarded materials. This study aims to provide insights into the possibilities of enhancing solid waste management in the Farmgate area of Dhaka North City Corporation (DNCC). To accomplish this objective, the research examines the conventional waste management methods employed in this area. It conducts extensive field surveys, collecting valuable data through interviews with local residents and key individuals involved in waste management, such as waste collectors, dealers, intermediate dealers, recyclers, and shopkeepers. The results indicate that significant amounts of distinct waste categories are produced daily. These include food and vegetable waste, which amount to 52.1 tons/day;polythene and plastic, which total 4.5 tons/day;metal and tin-can waste, which amounts to 1.4 tons/day;and paper waste, which totals 5.9 tons/day. This study highlights the significance of promoting environmental consciousness to effectively shape the attitudes of urban residents toward waste disposal and management. It emphasizes the need for collaboration between authorities and researchers to improve the current waste management system.

Development of a Framework for Equipment Health Management in the Mining Industries in Zambia

The Zambian mining industry is crucial to the national economy but struggles with inconsistent equipment maintenance practices. This study developed an Equipment Maintenance Management Framework (EMMF) tailored to the industry’s needs. Using surveys, interviews, and on-site visits at eight major mining companies, we identified significant variations in maintenance strategies, CMMS usage, and reliability engineering. The EMMF prioritizes predictive maintenance, efficient CMMS implementation, ongoing training, and robust reliability engineering to shift from reactive to proactive maintenance. We recommend adopting continuous improvement practices and data-driven decision-making based on performance metrics, with a phased EMMF implementation aligning maintenance with strategic business objectives. This framework is poised to enhance operational efficiency, equipment reliability, and safety, fostering sustainable growth in the Zambian mining sector.

Development and Application of Integrated Indicators for Assessing Healthcare Waste Management Systems in Kenyan Hospitals

Healthcare waste management (HCWM) is an important aspect of healthcare delivery globally because of its hazardous and infectious components that have potential for adverse health and environmental impacts. The paper introduces a set of indicators for assessing HCWM systems in hospitals. These indicators are: HCWM policies and standard operating procedures, management and oversight, logistics and budget support, training and occupational health and safety, and treatment, disposal and waste treatment equipment housing. By plotting a mark on a continuum which is defined as good and poor on the extremes and is connected with all other marks in a spoke arrangement, it’s possible to describe a baseline for HCWM in any specific hospital. This baseline can be used to improve awareness of the actors and policy-makers, compare the same hospital at a different point in time, to compare observations by different evaluators and to track improvements. Results suggest that in Kenya, the application of such indicators is useful for evaluating which priorities should be addressed to improve outcomes in HCWM systems. Systematic sampling technique was used to identify and collect data by use of observational checklist, interviews, visual verification and review of documents and a HCWM assessment tool. The objective is to suggest an integrated management tool as a method to identify prevailing problems with a HCWM system. The method can be replicated in other contexts worldwide, with a focus on the developing world. The integrated indicators focus on management of HCW and not its potential impact on human health and environment, an area recognized to be critical for future research.

Analysis of Hospital Budget Management Control Based on Smart Hospital

Hospitals are crucial healthcare facilities where patients seek treatment,and effective budget management within hospitals significantly impacts their operational efficiency and financial performance.In the age of information technology and advanced healthcare solutions,the emergence of smart hospitals represents a new trend in the medical industry’s evolution.Leveraging modern information technology can enhance the development of hospital IT systems and drive budget management toward greater intelligence.This paper begins by analyzing the influence of smart hospitals on hospital budget control.It then examines the current state of budget management control within smart hospitals.Finally,it proposes several strategies for budget management control in smart hospitals,aiming to provide guidance for relevant stakeholders.

Application of PDCA Cycle in Hand Hygiene Management of Psychiatric Medical Staff

Objective:To study the application effect of the plan-do-check-act(PDCA)cycle management in the hand hygiene management of psychiatric medical staff.Methods:One hundred and twenty medical staff from a psychiatric hospital from May 2023 to December 2023 were selected and divided into two groups.The control group(May 2023 to August 2023)applied the conventional management model,and the observation group(September 2023 to December 2023)applied the PDCA cycle management.The hand hygiene compliance,hand hygiene knowledge,and hygiene qualifications were compared,including the amount of hand sanitizer used.Results:The proportion of medical staff’s hand hygiene compliance and hand hygiene knowledge mastery scores in the observation group were higher than those in the control group(P<0.05);the hand hygiene passing rate in the observation group was higher than that of the control group(P<0.05);the daily amount of hand sanitizer per patient bed and the amount of hand sanitizer used was higher than that of the control group(P<0.05).Conclusion:The PDCA cycle management model for psychiatric medical staff promoted the improvement of hand hygiene compliance and increased their hand hygiene qualifications.It is suitable for further popularization and application in future clinical practice.

Analysis of the Current Situation of Cost Management and Control of Highway Construction Projects

The highway engineering process is complex,coupled with a relatively long construction period,hence requires increased coordination between participating units to prevent economic disputes and efficiency losses.The main body of the construction project needs to strengthen the management and control of funds.In this regard,this paper analyzes the importance of cost management in highway projects by clarifying and analyzing the current cost management status quo problems and causes.The highway engineering cost control strategy and implementation methods are summarized to provide references for improving the quality of highway engineering.

Digital Transformation of Enterprise Human Resource Management Enabled by Big Data

With the continuous development of big data technology,the digital transformation of enterprise human resource management has become a development trend.Human resources is one of the most important resources of enterprises,which is crucial to the competitiveness of enterprises.Enterprises need to attract,retain,and motivate excellent employees,thereby enhancing the innovation ability of enterprises and improving competitiveness and market share in the market.To maintain advantages in the fierce market competition,enterprises need to adopt more scientific and effective human resource management methods to enhance organizational efficiency and competitiveness.At the same time,this paper analyzes the dilemma faced by enterprise human resource management,points out the new characteristics of enterprise human resource management enabled by big data,and puts forward feasible suggestions for enterprise digital transformation.

Exploration of Human Resource Management in Enterprise Business Management

Human resource management is an integral part of enterprise operation and management,contributing to the avoidance of financial risks,alleviation of performance problems,promotion of organizational development,enhancement of operational efficiency,and fostering sustainable enterprise development.Enterprise management should prioritize attention to human resource management by establishing an independent human resource management department and strategically planning human resource management tasks.This involves building an information management platform,developing a professional human resource management model to mitigate market risks,actively recruiting human resource management talents to form a competent team,and enhancing the human resource management and supervision system.These measures are essential for comprehensively improving the level of enterprise operation and management.

Enhancing Enterprise Efficiency through Cross-Domain Supply Chain Linkage Management

In recent years,with the complexity and variability of international finance,debt,and geopolitical risks,the growth rate of domestic economic operations has slowed down.More enterprise groups are facing the transformation and upgrading from domestic leadership to internationalization,achieving revenue growth of nearly 10 billion yuan per year against the trend.The severe and complex internal and external environment has brought many challenges to the supply chain for enterprises.This article focuses on the goal of an“enterprise supply chain system focusing on value creation,strengthening system linkage,and improving overall chain efficiency,”aiming to find solutions to problems such as strong demand variability,frequent emergency needs,coexistence of project shortages and inventory surplus,long material turnover cycles,and high organizational complexity.By searching for key activities in the entire business chain of demand,design,production,service,and finance,implementing source planning,process control,system linkage,analysis and summary,and team collaboration,we have achieved more scientific demand forecasting,more accurate planning,more effective procurement cost reduction,more stable production performance supply,more convenient inventory sharing services,and more efficient integration of business and financial policies.