Target Enterprise Research Articles

Monitoring high-carbon industry enterprise emission in carbon market: A multi-trusted approach using externally available big data

Carbon markets are widely recognized as effective strategies for regulating carbon emissions from the enterprises of the high-carbon industry. Accurate monitoring of emissions in these enterprises is crucial for ensuring fair and trusted carbon trading. However, traditional monitoring methods have encountered various challenges including poor accuracy, low frequency, significant hysteresis and weak credibility. Addressing these concerns, this paper introduces a novel, multi-trusted, high-frequency monitoring approach for the measurement of both direct and indirect carbon emissions of enterprises, utilizing externally available multi-source big data, vertical federated long short-term memory network with a self-attention mechanism (VF-LSTMSA) and additive homomorphic encryption. The efficacy of this model is thoroughly assessed via case studies on six hourly datasets from the power and steel sectors. Our principal findings include: (1) In the current scenario, the proposed VF-LSTMSA model demonstrates superior federated efficiency, improving with the inclusion of more federated participants. (2) The VF-LSTMSA model surpasses other prevalent AI models, achieving a Mean Absolute Percentage Error (MAPE) of less than 9% across power and steel datasets. (3) The advanced high-frequency carbon emission monitoring method exhibits errors of +0.28%, +1.29%, and −0.41% in the current scenario monitoring task, suggesting that the model effectively leverages multi-source externally available big data to precisely monitor the target enterprise's carbon emissions while safeguarding multi-party data security. These findings suggest that the proposed monitoring method can accurately track corporate hourly carbon emissions, significantly improving the carbon trading and verification processes for enterprises

Case Study of Enterprise Value Assessment

Along with the gradual advancement of the deepening reform of our country's socialist market economy and the further optimization of resource allocation, the restructuring, investment, acquisition and merger of enterprises are becoming increasingly frequent economic activities. The evaluation of the value of the target enterprise is one of the important links. This paper takes the small household appliance industry as the starting point, takes the small B Electric Appliance Co., Ltd. as an example, and uses the discounted free cash flow model in the income method to estimate its market value. It can reflect that this method is conducive to providing detailed and solid basis for value assessment relatively comprehensively from the aspects of enterprise profitability, profit quality, future profit sustainability, expected rate of return of the industry in which it is located, and time cost of funds, etc., and is widely used in the capital financial market and market information disclosure requirements.

An Analysis of the Causes and Effects of the Out-of-Control Merger and Acquisition of Subsidiaries—A Case Study of the Great Wall of Culture Company

The phenomenon of out-of-control of subsidiaries after mergers and acquisitions is becoming more and more prominent. Effective control of subsidiaries is the most important issue that needs to be paid attention to. How to reasonably and effectively control subsidiaries has become the focus of theoretical and practical research. Taking the acquisition of Jade Education by Great Wall of Culture as an example, this paper analyzes the causes of losing control after the acquisition and analyzes the impact of losing control subsidiaries on the enterprise by means of event research and financial index analysis. The study found that the main reasons for the out-of-control of subsidiaries are unreasonable performance commitment, excessive decentralization caused by cross-border mergers and acquisitions, and out-of-control caused by blind mergers and acquisitions. Moreover, the out-of-control subsidiaries are no longer included in the scope of consolidated statements, which has a significant impact on the operating conditions of enterprises. In order to prevent the subsidiaries from losing control, it is suggested to carefully select the target for merger and acquisition, conduct due diligence on the target enterprise before merger and acquisition, reasonably delegate decision-making power and enrich and improve the performance commitment agreement.

Valuation of Biomedical Engineering Industry Under Epidemic: Evidence from Andon Health Company Limited

Contemporarily, under the ravages of the epidemic, nucleic acid testing has become one of the most critical preventive means, hence many nucleic acid testing companies develop rapidly in recent years. In the United States, antigen test kits have been the primary means for the past few years. Meanwhile, in the context of China’s gradual liberalization in the future, the test kit will also have a significant market space. This paper selects Andon Health Company Limited as an investigation target to discuss the valuation of the biomedical engineering industry during the epidemic. Based on the industry attributes and the circumstance of the epidemic, this paper concluded that the valuation of Andon Health is not suitable for some traditional value evaluation methods and models. According to the analysis, the valuation method based on the forecast of future cash flow is more suitable for the valuation of biomedical enterprises. Based on to the DCF valuation method, the value of Andon Health in 2022 is predicted to be 11.2 billion CNY. In this case, the current stock market price of the target enterprise is overvalued because of the biomedical enterprises’ characteristics. These results guide further exploration for valuing similar biomedical enterprises.

Study of energy scheduling and optimal cost management of a new structure CCHP system: A case study supplying energy for a chemical enterprise in Jiangsu Province

A new structure combined cooling, heating and power (CCHP) system integrating green power applying a control strategy based on a improved whale optimization algorithm is proposed in this paper. This paper fully considers the high energy demand and a large amount of waste heat in chemical enterprises. By absorbing chemical waste heating (mainly from chemical wastewater), coupling wind and photovoltaic equipment, adding cooling, heating, and electricity storage equipment, combined with an energy scheduling strategy, and an efficient CCHP energy system for the target enterprise is realized. The improved whale optimization algorithm is used to optimize cost management. The results show that after the optimization scheduling with the improved whale optimization algorithm, the CCHP system meets the energy demand with higher efficiency at a lower cost. In winter and summer, heat pump recycling chemical wastewater provides 15.4%–57.9% and 11.5%–62.9% of the heating load of the heating network. Meanwhile, the lithium bromide refrigerator in the cooling-net equipment provides an average cooling load of 6.25–58.4% and 7.01–16.64%.​ Finally, the improved whale optimization algorithm reduces the total cost by 2.4 % and 2.17 %.

Application of Price Competition Model Based on Computational Neural Network in Risk Prediction of Transnational Investment.

Aiming at the scenario where edge devices rely on cloud servers for collaborative computing, this paper proposes an efficient edge-cloud collaborative reasoning method. In order to meet the application's specific requirements for delay or accuracy, an optimal division point selection algorithm is proposed. A kind of multichannel supply chain price game model is constructed, and nonlinear dynamics theory is introduced into the research of the multichannel supply chain market. According to the actual competition situation, the different business strategies of retailers are considered in the modeling, which makes the model closer to the actual competition situation. Taking the retailer's profit as an indicator, the influence of the chaos phenomenon on the market performance is analyzed. Compared with the previous studies, this thesis uses nonlinear theory to better reveal the operating laws of the economic system. This paper selects company A in the financial industry to acquire company B in Sweden. It is concluded that company B is currently facing financial difficulties, but its brand and technical advantages are far superior to company A. The indirect financial risk index of company B, that is, the investment environment, is analyzed, and the final investment environment score of the country where company B is located is 90 points, which is an excellent grade by scoring the investment environment of the target enterprise. Combining the investment environment score and the alarm situation prediction score, it is concluded that the postmerger financial risk warning level of company A is in serious alarm.

The Application of Price-Sales Ratio Method in S Company's Merger and Acquisition of F Company

Accurately assessing the value of the target enterprise is an important factor for the success of enterprise mergers and acquisitions. As one of the important methods of enterprise valuation, the price-to-sales ratio method adopts the operating income indicator, and uses the valuation model to obtain the market value of comparable companies and the multiple of this indicator, and then obtains the value of the target enterprise, which can reflect the business prospects of the enterprise and is widely used by the capital market. generally accepted. Based on this, this paper deeply analyzes the basic principle, applicable environment and application process of the price-to-sales ratio method and its valuation model, and applies it to the target company's valuation when S company acquires F company, and uses the price-to-sales ratio method for mergers and acquisitions. Companies that conduct valuations set an example to help them ultimately realize value appreciation.

A Path-Based Feature Selection Algorithm for Enterprise Credit Risk Evaluation.

In recent years, there has been increasing interest in exploring diversified features to measure small and medium-sized enterprises (SMEs) credit risk. Path-based features, revealing logical connections between SMEs, are widely adopted as informative feature kinds for causal inference in credit risk evaluation. Since there may exist thousands of feature paths to the target enterprise, to evaluate its credit risk, how to select the most informative path-based features becomes a challenging problem. To solve the problem, in this paper, we propose a novel method of feature selection, considering both similarity and importance on features' structured semantics as the factors of informativeness. With this, the proposed method can effectively rank both conventional and path-based features together. Furthermore, to improve the efficiency of the method, a heuristic algorithm is proposed to fast search for the candidate features. Through extensive experiments, we show our method performs competitively with other state-of-the-art selection methods.

FINANCIAL MANAGEMENT OF ASSET-LIABILITY RATIO OF SMALL- AND MEDIUM-SIZED ENTERPRISES IN DYNAMIC NONLINEAR SYSTEM

The purposes of this paper are to optimize the financial management methods of small- and medium-sized enterprises (SEMs) and deeply explore asset-liability ratio’s relevant theories. A medium-sized manufacturing enterprise’s financial conditions and the influencing factors of enterprise’s asset-liability ratio are researched by a dynamic model with two-way effects and the enterprises’ dynamic nonlinear simulation model. Meanwhile, capital injection’s impacts on asset-liability ratio are explored. The results show that different industries’ enterprise asset-liability ratios vary. The real estate enterprises’ asset-liability ratio is 61.35%, the highest, and the cultural communication industry is the lowest, 35.62%. Meanwhile, the asset-liability ratios of energy industry, manufacturing industry, and the wholesale and retail industry are also relatively high. The larger the enterprise’s scale, the higher its asset-liability ratio, long-term liability ratio, current liability ratio, and loan financing. The proposed simulation software performs satisfactorily in its application. The simulation system’s analysis shows that the target enterprise’s asset-liability ratio is gradually increasing, and its return on equity and capital turnover rate is decreasing, reaching the critical bankruptcy point in the 36th month. With a 20 million CNY capital injection, its asset-liability ratio decreases significantly, and return on equity increases steadily. In the 49th month, it resumes normal operations. The results provide a useful reference for subsequent research on enterprises’ asset-liability ratios and SMEs’ financial management.

Analysis of Financial Statement and Prewarning of Audit Risks Based on Artificial Neural Network

The marketization of social capital has resulted in frequent audit failures, and financial statement frauds. One of the key steps of auditing is the identification of material misstatement risk of financial statement. However, there is no unified analysis framework or quantitative method for identifying this risk. Therefore, this paper aims to analyze financial statement and prewarn audit risks in an accurate manner. Firstly, the items of financial statement were analyzed in three aspects of the target enterprise: balance statement, income statement, and cash flow statement. Next, the authors probed deep into the core indices of the post audit risk verification and evaluation of the business process, constructed a scientific evaluation index system for audit risks of financial statement, and quantified the 89 tertiary indices, 21 secondary indices, and 3 primary indices. After that, an audit risk prediction model for financial statement was established based on neural network. Experimental results show the effectiveness of the proposed model for audit risk prewarning, and applicable to other tasks of financial auditing.

A New Way to Evaluate Products with Reviews: A Case Study of A Hair Dryer on Amazon Platform

The era of big data is coming. How to make effective use of users’ feedback information data is the key to success in various online industries. In order to help target enterprise enter the market, we build a comprehensive rating evaluation model that can evaluate the sales status, future development and contain comprehensive indicators. We firstly study the one-dimensional index. We adopt the method of correlation analysis to find the ripple effect of star rating. Then we use SPSS to draw scatter plots to analysis correlation between specific quality description and star rating level. We found through the research that “star rating”, “comment validity”, “positive and negative indicator in comments” and “member effect” are all informative for target enterprise to track, and will determine the market development of the product to a certain extent. We take advantage of the machine learning to turn the information in the text into quantifiable metrics and get polarity and subjectivity. Use NLTK for sentiment analysis of each comment to get negative, positive, neutral and compound value. Then use AHP to assign weight to the indicators wisely. With the comprehensive rating evaluation model that we build, we calculate the comprehensive rating value of all products in this industry and take the median as the benchmark value, then the products with the comprehensive rating value higher than the benchmark value can be regarded as successful products. We provide an accurate assessment. In order to effectively evaluate and predict the future sales trend of new products after their launch and effectively measure the increase and decrease of product market reputation, we establish a time-based measurement and prediction model based on Grey model theory. We can use the model to make comprehensive evaluation and effective prediction of the target company’s products. After inspection, our model can be effectively applied to different sales fields, which has great practical significance.

МОДЕЛІ ІНФОРМАЦІЙНОЇ ПІДТРИМКИ ПОВНИХ ЛАНЦЮГІВ ПОСТАЧАННЯ

The article proposes an approach to solving economic and social problems, which consists in the development of methodological foundations for the construction of logistics processes. The object of the research is the information support processes for complete supply chains. The purpose of the work is to increase the efficiency of the functioning of complete supply chains by creating information technology for the management of material flows within the supply chain. The research method is a systematic approach. The typical object here is the complete supply chain (CSC) of goods, it is a complex socio-economic system that consists of a large number of raw material suppliers, target enterprise (processing and packaging), warehouse terminals, distributors, customs brokers, 3PL and 4PL suppliers, retailers ... The interaction between CSC participants is a collection of continuous material, financial and information flows and services, from sources of raw materials to the final consumer. The value of the study for solving economic and social problems lies in the development of methodological foundations for the construction of logistics processes. Predictive assumptions for the development of the research object - using the proposed approaches and methods of informatization, it is possible to increase the efficiency of CSC functioning, simplify organizational management structures and create better conditions for awareness. KEY WORDS: SYSTEM APPROACH, FULL SUPPLY CHAIN, DYNAMIC SYSTEM.

A quantitative safety regulation compliance level evaluation method

In recent years, much more and stricter regulations have been put into effect to guide and coordinate the work safety in China. To comply with the requirements of safety regulations is the imperative responsibility for enterprises. However, one of the challenges faced by both enterprises and authorities is that currently there is no systematic methodology for safety regulation compliance evaluation. To address this problem, a quantitative safety compliance level evaluation method has been proposed. Firstly, a regulation list which the target enterprise needs to fulfil is identified as a basis. Secondly, the indexes of evaluation system, including first and second-tier indexes, are established according to safety management elements or enterprise organization structures. Thirdly, the articles of regulations matching each index are picked out, and the comprehensive requirements representing each index are summarized. Finally, an improved Delphi method is used to determine the weights of indexes. Grounding on that, a quantitative safety regulation compliance evaluation index system can be established. In order to facilitate the evaluation process, a web-based software has also been developed. It integrates the safety regulation database which can help reviewers to get regulation support when needed. It also supports conducting one compliance evaluation project by several reviewers simultaneously to shorten the evaluation time. An application case study of this method in an oil & gas company is also discussed. The application of this method demonstrates that it is a scientific and practical way to conduct safety compliance evaluations for both enterprises and employed third-party organizations.

Multi-attribute decision making of target enterprises in mergers and acquisitions

In this paper a new decision-making method was proposed by relying on the powerful fuzzy information expression ability of Vague set and the practicability of TOPSIS method and grey correlation method on the aspect of multi-attribute decision-making problems. Such new decision-making method based on the integrated TOPSIS method and grey correlation method of Vague set meets not only the decision-making requirements on the accuracy depicted by uncertain fuzzy information and the flexibility of disposal, but also meets the requirements of making comprehensive evaluation on the goodness and badness of decision-making scheme; it represents synchronously the dual-benchmark characteristics of position and shape similarity, and thereby provides a new thinking for the multi-attribute decision-making problems. Lastly, the paper took the selection of target enterprise under merger and acquisition as the analysis basis to describe the effectiveness and feasibility of the decision-making method.

Research on Performance and Valuation of Enterprises Placarded by Others Based on the Improved Panel Vector Auto-Regression Model

In recent years, enterprises, which were placarded, have become a heated issue in the secondary market in China. However, there still lack researches about the performance and valuation of those enterprises which were placarded. Therefore, it seems that it is lack of persuasion to use the word “barbarians” to define the enterprises which carry out placard. For the reasons above, this paper makes the use of the improved PVAR model to give an empirical analysis on the performance and valuation of the enterprises placarded, based on the samples between 2011 and 2015. First, this paper divides the whole samples into two subsample groups by the dummy variable, according to the certain point of time whether the enterprise has been placarded. After that, it build two PVAR models combining the performance indicators and the valuation indicators. The results show that the sensitivity of the target enterprise’s performance is not as good as its valuation. Second, the two subsample groups are analyzed by the impulse response function. It explains that placard creates an incentive effect for the target enterprise in the short term. Third, by using the variance decomposition, this paper achieves a conclusion that placard reduces the dependence of the target enterprise on the aspects of its valuation, profitability, size and risk. Therefore, placard is a good signal for those target enterprises on the whole, which brings a nice momentum for the enterprises on the valuation, profitability, size and risk in the short term. In the long run, the enterprises will adjust to a stable state based on the short-term changes. From this point of view, “barbarians at the gate” bring the motivation rather than chaos.

Analysis on infertility status and influencing factors of female workers among reproductive age in China's nine industries

Objective: To investigate the infertility rate and influencing factors of female workers in China's nine industries. Methods: Using multi-stage sampling method, from January to November in 2016. A cross-sectional survey was conducted on the infertility of 33 685 female workers in the nine industries including medical and health, petrochemical, metallurgy, railway, machinery manufacturing and electronics,a questionnaire survey. First, three provincial capitals were randomly selected in seven regions. And then we consulted and communicated with the hospital of the provincial city's occupational disease prevention and treatment, marking and coding the target enterprise within its jurisdiction, In these enterprises, we randomly selected five companies. Finally, all women workers who meet the inclusion criteria were surveyed in those enterprises which were drawn. Use the"female workers reproductive health questionnaire" to collect female workers demographic status, occupational status and reproductive status and other data. The single factor analysis of infertility was performed by chi-square test. Multivariate analysis of infertility was carried out by logistic regression model. Results: The age of female workers in the nine industries was (35.98±7.98) years. The infertility rate for one year of female workers in typical industry was 24.81% (8 358/33 685), the infertility rate for two years being13.47% (4 537/33 685), the infertility rate for two years being 10.78% (3 632/33 685). Compared to the east China region, the infertility rate was the highest in the south region (OR=1.90, 95%CI: 1.66-2.17). Compared to non-working women, the infertility rate was the highest among railroad (OR=1.68, 95%CI: 1.43-1.98) and financial industries (OR=1.64, 95%CI: 1.38-1.95). Occupational exposure to heavy metals (OR=1.15, 95%CI:1.04-1.27) and occupational exposure to hazardous physical factors (OR=1.09, 95%CI:1.01-1.17) were infertility risk factors. Conclusion: The infertility rate of female workers in the nineindustries was high. And the region, industry, occupational exposure to heavy metals and occupational exposure to hazardous physical factors, were independent risk factors for infertility.

Improving Financial Service Delivery to Communities through Micro-finance Institutions in Uganda; the case of Pride Micro-finance Limited (PML)

This study examined the design of a target Enterprise Architecture (EA) that can enable Micro-finance Institutions (MFIs) in Uganda improve financial service delivery to communities through use of Information and Communication Technologies (ICTs). Pride Micro-finance Limited (PML) was investigated with specific focus on their mission and goals, business processes, information/data, applications, actors, and technological infrastructure. Data was collected from two branches of PML using questionnaires, observation and document reviews. This data was analysed qualitatively and the results of the analysis indicated that PML faces a number of challenges in financial service delivery; like inability to reach out to its customers in a cost effective manner, inefficient ways of processing customer information, and data/information security risks. Based on findings from this study, a target EA capable of enabling PML reach out to its customers in a more sustainable, efficient, and effective manner was designed and recommendations for its implementation made. Key words · Enterprise architecture · Information and communication technologies · Financial service delivery

Suggestions on the Order of Support for Digital Contents Companies in Jeju

Purpose - The digital contents for tourism is one of the major industry in Jeju. The industrial bases of digital contents are established, but it needs to more support project because the companies in Jeju don’t have enough profits. So, this study has a purpose for analyzing the situation of industry ecosystem in Jeju, and for finding some support policy for rising incomes and employment growth of Jeju digital contents companies. Research design, data, and methodology - This study assessed the situation of the digital contents industry in Jeju, referring to the localindustry promotion roadmap of Jeju. In addition, this studyanalyzed the enterprise needs for two step process based on the analysis for a core target enterprise group : the first step is an analysis for its industry sector, and the second step is the demand survey of the supporting project for digital contents industry. In first step, this study analysis the target enterprise group divided by three fields, the character & animation field, the digital contents & game field, the visual arts & design field. In second step, the survey on digital contents enterprises’ demands is focused on current support policies. Results - Based on these results, following principal can be established. First of all, the group of enterprise with an independent foundation and a high research capacity needs a project to promote new market for selling representative goods. And the group of enterprise with a high rate of growth and a high intention for new goods needs a supporting project to do product planning for pull level the company up. In addition, to the success of this supporting project, it needs to do support in order of making prototype/ advancing products/ certification/ marketing. Conclusions - Even though Jeju Island has a great natural and cultural heritage, Jeju contents industrials has a small gain because of small size and diseconomies of scale.So, it needs to more support project for the digital contents companies. The support policies for the digital contents companies in Jeju must different with levels of companies’goods and technologies. To provide a differentiated support for the company is contribute to the development of industry and ecosystem of the digital contents in Jeju.

A Study of Financial Acquisition Risk Identification and Prevention

In this paper, the financial risk of Ping An Insurance (Group) Company of China, Ltd. acquisition of Shanghai Jahwa United Co., Ltd is divided into the target enterprise risk assessment risk, financing risk and uncertainty of future earnings according to M & A links. The study finds that the target enterprise value assessment under market approach is close to the transaction price; the financing risk can be divided into long-term risk and short-term risk; Uncertainty of future earnings arises from the volatility of the stock price caused by the uncertainty of the target enterprise. To reduce these three risks, this study suggests that M & A companies adopt a variety of methods to comprehensively assess the value of the target enterprise, rationally design the financing plan and pay close attention to the target business operation.

Study on the Withdrawal Way of Silk Road Fund under the Belt and Road Initiative Based on Game Theory Model

The Silk Road Fund is an important financial support of The Belt and Road Initiative, it has a strict investment operation process to realize the capital appreciation, so the withdrawal is crucial. This paper models the utility game and find the game mechanism between Silk Road Fund and target enterprise. And then we put forward some referential suggestions such as choosing suitable withdraw opportunity, perfecting talent team and information transmission mechanism,strengthening cooperation with local government, making effective use of gambling agreement and actively exploring new exit mode.