Economic Benefits Of Enterprises Research Articles

Research on the Carbon Reduction Technology Path of the Iron and Steel Industry Based on a Multi-Objective Genetic Algorithm

This paper establishes a multi-objective optimization model based on an improved NSGA-II algorithm, aiming to study the carbon reduction technology path of specific enterprises in the steel industry under the background of China’s dual-carbon goal and fill the research gap in the carbon reduction technology path of steel enterprises, which has certain guiding significance for the realization of China’s dual-carbon goal and the low-carbon development of steel enterprises. Firstly, through the analysis of the list of extreme energy efficiency technologies in the steel industry and the main process flow of steel industry production, the multi-objective optimization model is constructed from the two objective dimensions of maximum CO2 emission reduction and maximum enterprise economic benefit. Then the improved NSGA-II algorithm is used to solve the model. And the empirical analysis of a Hebei iron and steel enterprise, based on the technology application of enterprises before the release of the technology list, the technology path of enterprises to reduce carbon is predicted. The actual application data of the enterprise is used for verification and analysis, and suggestions on the technical path for the future low-carbon development of the enterprise are provided. The experimental results show that: (1) The optimal solution set of Pareto is consistent with the practical application of enterprises, and the constructed model is accurate and efficient, which can be used for the research of carbon reduction technology path. (2) When introducing technology, enterprises can give priority to the solution of common set technology based on their own needs.

Retracted: Data Envelopment Analysis Algorithm of Enterprise Economic Benefits Based on Leapfrog Algorithm

Retracted: Data Envelopment Analysis Algorithm of Enterprise Economic Benefits Based on Leapfrog Algorithm

Retracted: Exploring Evaluation of Enterprise Economic Benefits Using Big Data.

[This retracts the article DOI: 10.1155/2022/1103561.].

Research on Optimization of Enterprise Logistics Management Mode based on Cost Control

The competition among enterprises is fierce, not only in performance, price and quality, but also in high-quality customer service. The rationality of logistics system determines the reliability of services and products provided by enterprises, and the level of customer service directly affects the level of logistics costs. Reasonable planning of enterprise cost can reduce enterprise's resource energy consumption to a certain extent, thus improving enterprise's economic benefits. By analyzing the influencing factors of enterprise logistics cost and the principles of logistics cost control, this paper puts forward an enterprise logistics management model based on cost control in order to make logistics cost control serve the enterprise logistics cost strategy.

Analysis of the Impact of Job Burnout on Quality and Economic Benefits of Enterprises

Job burnout is a crucial cause of the decline in product (work) quality and operating efficiency, which may lead to increased costs, reduced revenues, and a decline in the quality and economic performance of business enterprises. Based on a systematic review of the extant literature, this paper examines several conceptual issues of job burnout (i.e., connotation, classification, and consequences), explores its influencing factors and possible intervention measures, and analyzes the impact of job burnout on operating quality and economic benefits from the perspective of quality cost management. We contend that the negative impact of job burnout on "improvement of quality and operating efficiency" cannot be overlooked. It is of great practical significance to prevent the occurrence of job burnout and minimize its adverse effect on the quality and economic benefits of an enterprise. Some countermeasures to avoid or alleviate job burnout are proposed, from the perspectives of legislative and institutional settings and new technology applications.

Analysis and research on the economic benefits of employee labor in enterprises in the context of the Internet

Abstract Analyzing the economic benefits of enterprise employees is better for protecting the rights and interests of enterprise employees. In this paper, based on the K-means clustering algorithm in the context of the Internet, the K-means clustering algorithm is optimized by the entropy weight method, and a K-means clustering model for exploring the analysis of the economic benefits of enterprise employees’ labor is proposed. For the model of this paper, the classification accuracy of the model is verified by employing controlled experiments, and two types of evaluation indexes for the labor economic efficiency of enterprise employees are analyzed and mined, namely labor employment and work environment and wage compensation and training and learning, using enterprise T as an example. Regarding labor and work environment indicators, 74.52% of the evaluations were above C grade. From the data of the indicators of salary and compensation and training and learning, the percentage of C grades or above is 89.41%. In the background of the Internet, the K-means algorithm model to analyze the relationship between the economic benefits of enterprise employee labor can help enterprises understand the current problems of employee labor and improve the happiness of employee labor, thus promoting the increase of enterprise economic benefits.

Research on Digital Transformation of Human Resources in Enterprise Management

Affected by COVID-19 and political factors, enterprises around the world are facing many problems, such as an unstable market environment, stagnant productivity growth, and overcapacity. At the same time, the development and innovation of digital technology indicate the inevitability of digital transformation and point out a new direction for the development of enterprises. This paper studies the digital transformation of human resources in enterprise management. It is found that digitalization still has a lot of room for progress in human resources. During the implementation, the digitalization of human resources still faces many difficulties, such as the lack of strategic planning, the lack of systematic training of digital skills, the failure to cultivate relevant talents, and the failure to combine performance with digitalization. As a result, the scope of transformation is narrow, the efficiency of transformation is low, and the goal of transformation cannot be achieved. This requires the digitization and modernization of the basic elements of human resources, the digitization of talent ability, and the data visualization of the performance management system. Only in this way can digital technology be used to continuously empower the enterprise's human resource management, which is conducive to the enterprise's sustainable competitiveness and thus improve the enterprise's economic benefits.

Incentive Mechanism Analysis of Environmental Governance Using Multitask Principal–Agent Model

In view of the principal–agent relationship between local government and pollution enterprise in environmental governance, this paper established a multitask principal–agent model, gave the optimal contract form of local government incentive to enterprises, examined the influencing factors of the optimal incentive contract, and focused on analyzing the influences of institutional factors, enterprise types and enterprise attributes on the optimal incentive contract. The results show that the optimal incentive contract is affected by the influence coefficient of enterprise economic benefits on local government revenue, the environmental index weight in government performance systems, the types of enterprise, the risk preference of enterprise, the variance in economic benefits, the variance in pollution emission reduction, the ability of economic benefits, the direct cost of emission reduction and the economic cost (income) of emission reduction. In order to realize the coordinated development of economy and environment, the establishment and adjustment of optimal incentive contract should be established or adjusted according to the institutional factors, different types of enterprise, and the enterprise characteristics. Local governments should divide enterprises into traditional enterprises and green innovative enterprises in the process of management. The policy formulation of the local government should be based on the characteristics of the system and cooperate with the national strategy. Local governments should actively collect and master the attribute information of the enterprises, including risk preference, profit model, pollution control technology and ability, management experience and level, production mode and green innovation ability. Local governments should combine the types of enterprises, the characteristics of institutions and the attributes of enterprises, and adjust various policies and measures more flexibly.

Automobile Component Recognition Based on Deep Learning Network with Coarse-Fine-Grained Feature Fusion

With the development of artificial intelligence, machine vision technology based on deep learning is an effective way to improve production efficiency. Because of the rapid update of the automobile manufacturing industry and the large variety of products, the learning time and the number of learning samples of the deep learning model are limited, which brings great difficulties to the recognition of components. Therefore, considering the economic benefits of enterprises, this paper proposes an intelligent component recognition method appropriate for small datasets, aiming to explore an automatic system for component recognition suitable for industrial manufacturing environments. The method completes the generation of the dataset through the system architecture with the potential for automation and the image cropping method based on feature detection and then designs a deep learning network based on coarse-fine-grained feature fusion to generate an intelligent recognition model of components. Finally, the designed network achieves an accuracy of 95.11%, and compared with the traditional classical network on multiple datasets, the designed network has better performance. Thus, the proposed method can improve the production flexibility of the automobile manufacturing industry and improve equipment intelligence.

The analysis of enterprise economic benefit evaluation model based on network marketing

The comprehensive evaluation of enterprise economic benefits is the core content of enterprise diagnosis and has been the focus of domestic and foreign enterprise management circles. In thorough statistical evaluation, establishing a set of scientific and economic benefit index systems and evaluation methods is of great significance. This paper briefly introduces the design principles of the economic benefit evaluation index, analyzes the shortcomings and improvement measures of the current enterprise economic benefit evaluation system in China, and puts forward the indexes that should be added on the basis of the current index system. At the same time, the main methods for comprehensive evaluation of enterprise economic benefits are also proposed.

Analysis on the digital transformation index system of enterprise’s low carbon business performance based on AHP-DEA

With the arrival of the low carbon era, enterprises, as the main body of the market economy, must take the road of low carbon operation whether to fulfill their social responsibilities or to seek enterprise development. However, Chinese enterprises started late to understand the low-carbon economy. So far, except for a few state-owned enterprises, some leading private enterprises and foreign-funded enterprises, they have made remarkable achievements in low-carbon emission reduction. Most enterprises in China have not realized the importance of low carbon emission reduction. In order to step out of the “high carbon” era and coordinate economic development and environmental protection, China must solve the problem of low-carbon transformation of small and medium-sized manufacturing enterprises. How to measure the degree of low carbon transformation, and how the government objectively evaluates the degree of low carbon economic development of enterprises, with a view to formulating corresponding standard incentives and punishment measures for them. It is urgent to establish a sound, reasonable and feasible low carbon operation management indicator system, and comprehensively evaluate the information related to low carbon operation of SMEs through reasonable selection of indicators. According to the connotation of low-carbon enterprises, the economic benefits of enterprises are closely combined with environmental benefits. A set of low carbon operation performance evaluation index system including economy, technology and environment has been constructed. The AHP index weight is calculated by establishing the AHP model and the Data Envelopment Analysis (DEA) index weight is calculated by establishing the DEA model. On this basis, the grey relational evaluation model based on AHP-DEA is established. Then the paper evaluates the performance of representative enterprises’ low carbon operation. Propose corresponding improvement suggestions for the problems reflected in the low carbon operation performance ranking of enterprises and the scoring of various indicators. The research results show that the algorithm has high efficiency and the accuracy of model evaluation is 95.51%. To a certain extent, this study makes up for the research results of the impact of digital transformation on corporate strategic performance, and also provides ideas for the research of corporate financial performance evaluation.

Day-Ahead Intelligent Energy Management Strategy for Manufacturing Load Participating in Demand Response

Flexible resources such as adjustable load widely participate in interaction with power grid, which can effectively promote renewable energy consumption. In previous studies, researchers generally focused on industrial and household users, but usually ignored the manufacturing load. Therefore, in this paper, an day-ahead intelligent energy management strategy for manufacturing load is proposed. Firstly, we analyze the power demand behavior of manufacturing load in detail, and describe the energy flow and material flow of manufacturing load through state task network (STN) method and mixed integer linear programming model. Then, the conditional deep convolution generative adversarial networks (C-DCGAN) algorithm is used to describe the uncertainty of new energy and construct a set of scheduling scenarios. Finally, case study shows that the proposed method can effectively improve the regional renewable energy consumption level and economic benefits of enterprises.

Research of the fiscal and tax policies of High - tech industry in Northeast China

In recent years, the high-tech industry has become an important driving force for economic development, and it has become an important subject to study the fiscal and tax policies suitable for the development of local high-tech industry. This paper constructs a fixed-effects linear regression model with unbalanced panel data by selecting data related to high-tech industries listed in China in three northeastern provinces to empirically test the effects of fiscal subsidies and tax incentives on innovation inputs, outputs and economic benefits of enterprises. The result show that fiscal policies mainly motivate the development of high-tech industry R&D and innovation output, and the tax policies motivate the development of hightech industry R&D and economic benefit. The fiscal and tax policies have different effect to different enterprises, private enterprises will develop better than state-owned enterprises. To motivate the development of high-tech industry, government should formulate fiscal and tax programs according to the effects of fiscal and tax policies in different stages of the industrial chain, determine the leading methods, adjust the content of the existing fiscal and tax policies according to the characteristics of enterprises. The innovation point of this paper is to analyze the relationship between innovation R&D input, innovation output and revenue and fiscal policy related to high-tech industry from the perspective of complete industrial chain, and systematically compare the effect of existing fiscal policy and tax policy in three northeastern provinces, which provide a reference for future research related to the development of regional high-tech industry.

Corporate Social Responsibility, Advertising Competition and Consumer Welfare: A Research on the Model of Oligopoly Competition Theory

The paper constructs an oligopoly competition model to explore the strategic choice of corporate social responsibility and advertising investment, which means to analyze the trade-off theoretically between advertising investment and the weight of social responsibility. The study found that, with the improvement of social responsibility performance, the dominant strategy of enterprises will evolve from advertising competition to production competition caused by social responsibility. Under certain restrictions, corporate social responsibility will promote advertising competition. Research shows that enterprises should pay attention to the benefits brought by advertising competition while paying attention to social responsibility and the government should also take reasonable control measures, otherwise social welfare and economic benefits of enterprises will be inhibited.

Research on the strategy of improving enterprise economic benefit in enterprise management

Research on the strategy of improving enterprise economic benefit in enterprise management

Strategic choice of electronic banking development under the financial and economic development

In recent years, with the rapid development of information technology, financial enterprises in order to fast, convenient, safe, efficient, improve enterprise economic benefits, by using information technology to carry out the electronic banking industry, from the initial telephone banking, gradually evolved into today's online banking, WAP banking and mobile banking. In the process of continuous development and improvement of electronic online banking business, personal financial industry is gradually in the important position of development, and even becomes the premise of benign development between Chinese banks. This paper mainly analyzes the development status and strategic choice of Chinese electronic bank.

Predictive analysis of the psychological state of charismatic leaders on employees' work attitudes based on artificial intelligence affective computing.

With the progress of social production, the competition for talents among enterprises is fierce, and the market often lacks capable leaders, which leads to the lack of management of enterprise employees and cannot bring more economic benefits to enterprises. Traditional leaders make subordinate employees work actively and achieve the common goal of the enterprise by exerting their own leadership characteristics and observing their subordinates, but they cannot take care of the psychological state of each employee, resulting in the employee's work efficiency is not very high. In recent years, charismatic leadership has become an important economic leader in the new era, and the theoretical spirit of charismatic leadership can well guide employees to work actively. Artificial intelligence affective computing can well identify the psychological state of the subject, and the combination of artificial intelligence affective computing and charismatic leadership can achieve effective management of employees through the predictive analysis of employees' psychological state. This paper compares the psychological state prediction analysis of employees' work attitudes between charismatic leaders based on artificial intelligence affective computing and traditional leaders through experiments. The results show that: charismatic leaders based on artificial intelligence affective computing predictive analytics can improve sensitivity to employee needs, resulting in an 8.2% increase in employee trust in leadership, a 4.4% increase in employee commitment to achieving organizational goals, and a 19.3% increase in employee job satisfaction. The psychological state prediction analysis of charismatic leaders based on artificial intelligence affective computing on employees' work attitudes can improve the work efficiency of employees and the economic benefits of enterprises.

Application of hybrid kernel function in economic benefit analysis and evaluation of enterprises

Abstract The economic benefit of enterprises is an effective index to measure the economic activities, which forms the basis and starting point. Therefore, in this paper, the traditional analysis methods of enterprise in terms of economic benefits are compared and based on its evaluation principles, the advantages, theory and realisation process of the kernel function in enterprise economic benefits analysis are analysed. Then, different kernel functions are selected to analyse the total output value, product sales rate, sales revenue, total profit and total profits after taxes of five enterprises, and their economic benefits are evaluated by the cumulative contribution rate of principal components. Finally, the mixed kernel function based on the combination of polynomial kernel function and Gaussian kernel function is used to optimise the analysis effect, which is meant to help enterprise leaders make more scientific decisions and lay a foundation for the sound development of enterprises.

Application of hybrid kernel function in economic benefit analysis and evaluation of enterprises

Abstract The economic benefit of enterprises is an effective index to measure the economic activities, which forms the basis and starting point. Therefore, in this paper, the traditional analysis methods of enterprise in terms of economic benefits are compared and based on its evaluation principles, the advantages, theory and realisation process of the kernel function in enterprise economic benefits analysis are analysed. Then, different kernel functions are selected to analyse the total output value, product sales rate, sales revenue, total profit and total profits after taxes of five enterprises, and their economic benefits are evaluated by the cumulative contribution rate of principal components. Finally, the mixed kernel function based on the combination of polynomial kernel function and Gaussian kernel function is used to optimise the analysis effect, which is meant to help enterprise leaders make more scientific decisions and lay a foundation for the sound development of enterprises.

Exploring Evaluation of Enterprise Economic Benefits Using Big Data.

The purpose is to improve Chinese enterprises' economic benefit evaluation system based on big data and promote sustainable enterprise production. This paper studies the power supply enterprises-oriented Evaluation Index System (EIS) under the big data environment. Firstly, it expounds on the construction theory of the enterprise economic benefit model. Secondly, the comprehensive Grey Model (GM) based on improved weight and the power consumption prediction model based on Least Mean Square (LMS) neural network (NN) algorithm are introduced. Finally, the comprehensive GM model based on improved weight is used to evaluate the economic benefits of power supply enterprises. The power consumption prediction model based on the LMS-NN algorithm is used to predict the sustainable development of power supply enterprises. The results show that the profitability and solvency of joint-stock power companies are about 90 and 100, respectively, and the social contribution of state-owned power supply enterprises is the strongest. Lastly, it is predicted that the region will have 134.8 billion kWh of electricity and about 137.2 billion kWh of power consumption in 2020. The growth model and trend are consistent, but there are some errors in the specific power consumption data. Therefore, the audit method based on big data has a good evaluation effect on the economic benefits of enterprises. For example, the profits of private and joint-stock power supply enterprises are relatively high. In contrast, state-owned power supply enterprises have outstanding social contribution ability. The big data method is used to predict the power consumption in some areas, and the predicted value is consistent with the actual value. This study provides a reference for the follow-up economic benefit evaluation and sustainable development of enterprises.