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Debt restructuring is an effective means to solve the financial difficulties of enterprises. At present, the operation methods and means of enterprises with different characteristics to participate in debt restructuring are different, and no universal debt restructuring scheme has been formed. In order to solve this problem, this paper uses the method of fuzzy set qualitative comparative analysis. This paper discusses the influence mechanism of multiple concurrent factors on enterprise debt restructuring and summarizes the selection rules of debt restructuring strategies for enterprises with different characteristics of debt. The research shows that there are five kinds of allocation for enterprises to realize debt restructuring. According to the different core conditions, enterprise debt restructuring can be divided into high-quality operation and management mode, technology leading mode, and debt-to-equity mode. The research results reveal the mechanism behind enterprise debt restructuring and provide a reference basis for the government and creditors to make corresponding decisions in the debt restructuring process. [ABSTRACT FROM AUTHOR]

This paper adopts the fuzzy set qualitative comparative analysis method to carry out an empirical analysis on Chinese latecomer enterprises and examines the key factors and realization paths that affect the technology path transformation of latecomer enterprises. This paper finds that there are configuration characteristics among the influencing factors of the technological path transformation of latecomer enterprises. The paper reveals the causal complexity mechanism of multiple factors that jointly affect technology path transformation. The key factors that affect the technological path transformation of latecomer enterprises include organizational vigilance, strategic transformation capability, network connections breadth, resource governance depth, dynamics of the technological environment, and the scale of social demand for technology. The above factors not only emphasize that latecomer enterprises should focus on new technologies rather than the market but also reveal that strategic transformation capability and resource governance depth are the keys for enterprises to achieve technology path transformation. In addition, it is pointed out that latecomer enterprises should pay attention to the "window of opportunity" brought about by the scale of social demand for technology. The transition from technology path dependence to technology path transformation of latecomer enterprises is a process in which the key factor becomes stronger. [ABSTRACT FROM AUTHOR]

Owing to the rapid expend of the global economy and the increasingly fierce competition among enterprises, scientific and modern management has been gradually adopted in the transaction processing of enterprises. Especially for the show appraisal of enterprises, the traditional appraisal has a lot of subjective influence of managers, so the traditional show appraisal methods cannot meet the need for survival and expend of enterprises. The pressure of talent demand is increasing, which makes many enterprises pay more attention to whether their own mankind resource management system supports the company's strategic spend and can win advantages in the competition of talent structure, organizational structure, and management process. Numerous foreign enterprises use mankind resource audit to achieve this goal, but at present, there is little practice in China that enterprise show evaluation is an important basic work and core content of mankind resource management and expend. Improving the effectiveness of enterprise show evaluation is of great significance to increase the core competitiveness of enterprises and promote the sustainable expend of enterprises. Therefore, this paper designs a model based on collaborative filtering algorithm to analyze the show of mankind resource management of enterprises and has achieved good results. Compared with the original algorithm, the model designed in this paper has a 65.4% improvement in algorithm, which will greatly simplify the calculation process and improve the model processing efficiency. The numerical results show that there is an inevitable linear correlation between mankind resource management and enterprise show. This index can reflect that the accuracy of the model has been enhanced by 74.3%. [ABSTRACT FROM AUTHOR]

This paper studies how the blockchain technology applies the enterprise's vertical value chain management and specifically studies how the blockchain technology is applied to the management of various transaction information involved in the enterprise's vertical value chain management. This paper first analyzes the basic needs of the enterprise vertical value chain management, analyzes the decentralization, integrity, and authenticity of relevant transaction information in management, and designs and implements enterprise value chain management solution based on the blockchain technology, including the design and implementation of organizations, consensus mechanisms, data structures, and business processes. The simulation data is used for testing, and finally, the solution is evaluated in terms of security, transparency, efficiency, and scalability. The research in this paper shows that the blockchain technology can be applied to the enterprise's vertical value chain management, which can ensure the authenticity, transparency, tamper resistance, and security of various transaction information of enterprises, thus improving the quality and reliability of the vertical value chain management of enterprises. [ABSTRACT FROM AUTHOR]

The comprehensive reasons for the cross-regional flow of enterprises in their own economy are studied in this paper. Most traditional enterprise migration research focuses on the impact of a single factor. Even the research on the influence of multiple factors often ignores the interaction of various factors. Therefore, this paper proposes and logicalises the "push and pull" mechanism of enterprise migration to address the limitations of previous research. Through bibliometric analysis and investigation, we systematically think about the factors that affect the corporate migration mechanism and improve the Push-Pull Theory. Besides, by deploying a conceptual system dynamics model, this paper explains how various factors affect enterprise migration. In addition, we discussed how to adopt systems thinking to promote the development of emerging economies. We selected and tested 6 companies that migrated in China, and the results are in line with reality. The conclusion supports the theory that systematic thinking and decision-making influence corporate behaviour. [ABSTRACT FROM AUTHOR]

The development of manufacturing industry affects the operation of Chinese economy, and it is necessary to study the possible configuration paths of servitization transformation to support sustainable development. Based on previous studies of manufacturing servitization transformation, it is extended to explore multifactor combinations which affects servitization transformation performance. This paper constructs technology-organization-environment (TOE) framework of servitization transformation performance evaluation and uses fuzzy-set Qualitative Comparative Analysis (fsQCA) method to analyze the key factors and mechanism of servitization transformation with the data of 28 Chinese manufacturing enterprises. The results reveal that the six major factors are not the necessary conditions, and single-factor cannot effectively promote servitization transformation of Chinese manufacturing enterprises. There are four configurations which can be divided into three paths to improve servitization transformation performance. Based on the results of analysis, it proposes strategies to promote the development of Chinese manufacturing enterprises, such as developing targeted servitization strategies, enhancing technology development, and improving technology applications. The findings reveal the mechanism of multiple factors behind the evolution of manufacturing servitization transformation and take useful suggestions for the high-level development of Chinese manufacturing enterprises. [ABSTRACT FROM AUTHOR]

This paper explores the influence mechanism of the marketization process and financial technology on corporate investment preference using panel data from 2013 to 2019 for China's A-share listed companies. The study finds that both the marketization process and FinTech can facilitate increased R&D innovation and foreign equity investment by companies but discourage investment in their fixed assets, and FinTech has a "U-shaped effect" on corporate R&D and innovation. At the same time, the marketization process and FinTech show different threshold effects on corporate investment preferences with government subsidies as the threshold variable. It is found that market-based processes in small-scale enterprises are better able to promote investment in innovative R&D by companies—the marketization process for large enterprises has a greater impact on outward equity investment in the heterogeneity analysis. From the perspective of the nature of property rights, it is found that the marketization process and FinTech have a greater impact on non-state enterprises. As a result, in an era of rapid FinTech development, this paper enriches the relevant research on the impact of the marketization process on corporate investment preferences, which has important practical significance for policy formulation and corporate future development. [ABSTRACT FROM AUTHOR]

As an important factor in the creation and growth of new enterprises, social entrepreneurship and new enterprise performance have attracted more and more attention from scholars in recent years. This research analyzes the network relationship of new companies on the basis of existing entrepreneurial network research. This paper proposes social entrepreneurial capabilities and new company performance based on the SOM neural network algorithm to solve these problems and then establishes entrepreneurial networks, organizational learning, and new business performance models. The method of this paper is to study the SOM neural network algorithm and then establish the entrepreneurial ability and enterprise performance evaluation system. The function of these methods is to put forward the meaning and research of venture capital. It also defines the meaning and research of innovation capabilities based on innovation theory, ensuring the scientific nature of the evaluation indicators, evaluation standards, and evaluation processes of innovative enterprises. In this survey, this paper conducted a field survey in Shanxi Province, China, and analyzed the internal impact of the network of social entrepreneurship and new companies on corporate performance. The survey results show that the value of the correlation β between entrepreneurial orientation and entrepreneurial environment dynamics is 0.167 (P < 0.05). This shows that improving the entrepreneurial environment and enhancing social entrepreneurial capabilities have a positive impact on corporate performance. [ABSTRACT FROM AUTHOR]

Comprehensive performance evaluation is an important basis for improving the training effect of enterprise employees and the effective allocation of enterprise resources. Based on AHP and BP neural network theory, this paper constructs a comprehensive performance evaluation method for enterprises, AHP is used to calculate the weight of the index, and then the importance index is screened. The model proposes a conceptual model of comprehensive performance of manufacturing enterprises from the support layer, core layer, and promotion layer and constructs a manufacturing system from horizontal and vertical. The influencing factors of comprehensive performance solve the quantification problem of enterprise comprehensive performance evaluation and have obvious guiding value for the research on the integration mode and path of industrialization and industrialization of regional manufacturing enterprises. In the simulation process, the weight of each index in the evaluation system is first determined by the analytic hierarchy process; then the evaluation index membership score table is established, and fuzzy mathematics is used to calculate the expert's score, so as to solve the problem caused by the intermediate value. The uncertainty caused by the jump is finally established by the analytic hierarchy process, and the neural network is used to simulate the sample. The experimental results show that by using AHP to collect training samples for neural network evaluation, the comprehensive performance evaluation system has good fitness and achieves the best comprehensive consideration of accuracy and training time when there are 17 hidden layer neurons. The maximum relative error is 1.64%, which is much lower than the general accuracy requirement of 5%, which effectively improves the performance and calculation accuracy of the network. [ABSTRACT FROM AUTHOR]

The combination and application of big data and machine learning in the offline consumer market makes the formulation of marketing strategies more scientific. The use of machine learning can make statistics and analysis of users' consumption behavior and classify customers according to users' consumption behavior, so as to realize the personalized promotion of marketing content. In this context, this paper carries out research on enterprise digital precision marketing strategy based on big data. Starting from the actual application, this paper analyzes the current problems faced by consumption data sharing, as well as the characteristic needs of precision marketing for consumer groups, introduces homomorphic encryption technology, completes the structural design, process design, and algorithm design of the scheme in combination with the actual scenario that enterprises need to carry out precision marketing for customers based on consumption data, describes each design link in detail, and verifies the feasibility of the algorithm in the scheme. [ABSTRACT FROM AUTHOR]

Under the current trend of economic globalization and international competition, more and more production enterprises are introducing the project management model, that is, customer or order projection, and using the concept of project management to manage operations. In an enterprise, there are multiple customers at the same time, and the production line can also generate multiple orders from different customers at the same time. That is to say, multiple projects are running at the same time, resulting in continuous changes in management processes, heavy project coordination tasks, and a serious waste of corporate resources. The resources that can be used are limited. In the production business using project management, how to rationally utilize the limited business scheduling resources has become the focus of research. Aiming at the method of business management resource scheduling, this paper investigates the application of enhanced particle swarm algorithm on the cloud deep learning platform, and the mapping problem between virtual machines and physical machines. As a heuristic algorithm, particle swarm optimization is suitable for solving combinatorial optimization problems. By improving the diversity of particle hosts and setting parameters, it improves the integration speed and accuracy of the algorithm. Through the analysis of the current situation of multi-project business management, it examines the allocation of resources. In terms of business management, it has established a resource allocation model for multiple projects. The results show that the method improves the efficiency of the enterprise by 35% compared to the traditional method with a 20% reduction in personnel. A better configuration scheme is simulated by MATLAB, which verifies the scientificity and effectiveness of the method studied in this paper. [ABSTRACT FROM AUTHOR]

Focusing on the topic of dynamic capability development and digital transformation of traditional enterprises in the digital economy era, and using traditional manufacturing as an example, this paper examines how small- and medium-sized (SMS) businesses should transform and develop in the digital economy era. Furthermore, in light of the problem that existing models cannot evaluate dynamic nonlinear optimization, a diversified dynamic capability evaluation model of SMS enterprises is developed, and the model is solved using the accelerated genetic value method based on real number coding, while the parameters of the BP network are evaluated using the genetic algorithm. In this study, 100 SMS companies are chosen from a pool of 1000 companies to perform an empirical study. In the empirical study, three different scenarios were employed. The selected dataset is utilized to test BP and GA in the first scenario. In the second scenario, the BP and GA are combined to create a more robust model, which is then evaluated on the specified dataset. This research provides a novel approach that combines the PCA with the acceleration method in the third case. According to the findings of this study, the methodology suggested in this work has an overall evaluation accuracy of 95.6 percent, which is pretty good when compared to other approaches. The model training error and test error, on the other hand, are both lower than those of traditional assessment procedures, according to the data. [ABSTRACT FROM AUTHOR]

Based on the data of China's listed companies from 2007 to 2020 and the financial license of the China Banking and Insurance Regulatory Commission, this paper analyzes the influence of bank competition on enterprise innovation investment and its mechanism. It is found that bank competition can improve the enterprise innovation investment, which still holds true after endogenous treatment and robustness test. Further research demonstrates that bank competition plays a stronger role in enterprise innovation for non-state-owned enterprises and small-scale enterprises. The mechanism analysis shows that bank competition can promote enterprise innovation investment and enterprise financialization by easing financing constraints. Moreover, enterprise financialization has a crowding-out effect on enterprise innovation investment. Therefore, moderately intensifying bank competition, further improving the financial system, and deepening the financial marketization reform have profound effects on driving enterprise innovation and its high-quality development. [ABSTRACT FROM AUTHOR]

In the big data environment, the factors affecting the operation of small- and medium-sized enterprises are becoming more and more complex. In order to more accurately measure the financial crisis of small- and medium-sized enterprises, from the perspective of multisource information fusion, based on the traditional financial data reflecting the private information of enterprises, the public information data for measuring the macroeconomic and market environment are integrated and analyzed. Considering the multidimensional heterogeneity of multisource information data, BPNN, SVM, KNN, LOG, and MDA are introduced to build models, and ensemble learning is used to integrate the results of different early warning models to reduce the risk of inconsistent results from different models. The empirical results show that the early warning model integrating multisource information can improve the early warning accuracy. The research results show that the financial crisis early warning of small- and medium-sized enterprises should not only pay attention to financial indicators but also pay attention to the impact of corporate governance, industry, and the overall economic environment of the country; the accuracy of the model in this paper is significantly higher than that of the other models in terms of the accuracy of financial crisis early warning. It shows that the model in this paper can better predict the real financial status of small- and medium-sized enterprises. [ABSTRACT FROM AUTHOR]

Strengthening the construction of intellectual property rights of SM-TE (small and medium-sized scientific and technological enterprises) in China is an important measure to speed up the development of SM-TE, and improve their scientific and technological innovation ability and market competitiveness. In this paper, a patent recommendation algorithm based on deep semantic similarity is proposed to solve the problem of low calculation accuracy of similarity matrix among users in sparse interaction matrix. The algorithm trains the patent corpus, and obtains the Doc2vec DL (Deep Learning) model, and then constructs the semantic similarity matrix among patents through the DL model. On this basis, to further improve the modeling ability of semantic expression and feature extraction, this paper optimizes CNN (Convolutional Neural Network) model, using a variety of pretrained word vector models, multi-layer classifiers, etc., to improve the model accuracy and generate feature vectors of different dimensions. The results show that the accuracy, recall rate and F1 value of the proposed algorithm are better than those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The experiment shows that this paper can guide Chinese enterprises to establish and improve the risk warning system of independent intellectual property rights, thus reducing the losses of enterprises. [ABSTRACT FROM AUTHOR]

Innovation in products or services is crucial for industrial manufacturing businesses in countries that prioritize exports. A plethora of advancements based on the internet of things (IoT) applications has been made possible by the falling prices of processing power, communication, and electrical components. Only a small number of industrial manufacturing enterprise-specific IoT applications have been effective yet. The present literature does not fully explain this scenario, which is very necessary for taking the advantage of IoT in manufacturing enterprises. In order to adapt to the change in digital market demand and enhance the market competitiveness of manufacturing enterprises, this paper aims to study the digital transformation path of manufacturing enterprises based on the internet of things (IoT) and data encryption technology. A digital transformation service system is built for manufacturing enterprises based on the IoT and data encryption technology to help manufacturing enterprises fully understand their own digital degree, provide effective suggestions for the digital transformation, and introduce the overall architecture and functional structure of the service system in detail. A distributed intelligent recommendation method is proposed that is based on personalized customization and recommends transformation schemes for businesses in order to better direct users' product customization and decision-making and allow the users to accurately describe their own needs, improve customization efficiency, introduce intelligent recommendation methods, and strengthen the basis of collaborative filtering methods based on items. The simulation result demonstrates that the service system proposed in this study performed really well in terms of both accuracy and time consumption. It is anticipated that the suggested approach will successfully raise the digital maturity of manufacturing companies and will help them in increasing their ability to compete in the current market. [ABSTRACT FROM AUTHOR]

Preferential access to scarce resources can bring competitive advantages and better performance to enterprises. However, the existing literature has a relatively single research path on the influencing factors of enterprise resource access, which has lack of sufficient research from the perspective of multidimensional environment. In particular, as an important factor affecting enterprises' access to external resources, few studies have given empirical results on the impact of political factors such as government structure on enterprise resource access. Preferential access to scarce resources can bring competitive advantages and better performance to enterprises. However, the existing literature has a relatively single research path on the influencing factors of enterprise resource access, which lacks sufficient research from the perspective of multidimensional environment. In particular, as an important factor affecting enterprises' access to external resources, few studies have given empirical results on the impact of political factors such as government structure on enterprise resource access. Through the discussion of multidimensional environmental factors, this paper can provide theoretical reference for the reform of government institutions and the establishment of good political relations between enterprises and the government. Focusing on the multidimensional environment of government structure, political relations, and enterprise resource acquisition, this paper takes 129 enterprises in Central China as samples and uses the structural equation model to empirically verify the relationship between the formalization of government structure, liaison mechanism, decentralization, and enterprise resource acquisition, especially the easing effect of political relations. The results show that the formalization of government structure is promoting enterprises to obtain policy resources and financial resources; the liaison mechanism helps enterprises to obtain financial resources and market resources; decentralization has a significant positive impact on enterprises' access to policy resources and market resources; and political connection magnifies the positive effect of government structure on enterprise resource acquisition, but there are differences in different dimensions. [ABSTRACT FROM AUTHOR]

With the rapid development of multimedia technology today, digital technology research has penetrated into various fields. Based on the integration of industry and finance, management accounting breaks the barriers of business and financial communication, makes business and financial processes penetrate each other, reduces financial levels, improves work efficiency, and helps enterprises create value and improve their core competitiveness. In recent years, with the continuous emergence of new technologies such as big data, cloud computing, and blockchain, how to rely on multimedia technology to effectively realize the platform model of management accounting aiming at "integration of industry and finance" is a difficult problem faced by enterprise management. Combined with the characteristics of multimedia technology, this paper embeds the neural network algorithm in the design of the model and matches the optimization and processing of management accounting in decision-making under the guidance of fuzzy theory. Business decision-making is the core of all the work of enterprise management. The formulation of its decision-making scheme involves all business fields of the enterprise. The implementation of the decision-making scheme directly affects the business performance of the enterprise. The correctness of the decision-making scheme is directly related to the success or failure of the enterprise. Extracting and utilizing the huge financial data generated during the daily management of the enterprise's financial department, a multimedia technology-based enterprise management accounting analysis model is designed and implemented. [ABSTRACT FROM AUTHOR]

With the rapid development of software industry, software enterprises have many problems in risk management, and enterprises are facing a huge crisis. In order to detect the risk of software enterprise, a risk detection model based on BP neural network is proposed in this paper. Firstly, risk analysis and modeling are carried out for the software life cycle process of the enterprise. Then, BP neural network is combined with common software risk items to realize supervised deep learning based on label information in data set. Using the advantage of neural network in automatic selection of original data features, the relationship between these risk items is extracted. Meanwhile, the network model in this paper learns the complex relational rules of the input risk features, to classify the risks. Finally, the proposed combined prediction model is compared with other prediction models. The experimental results show that the risk prediction effect of the proposed algorithm is better, to avoid the loss caused by the risk of software enterprises. [ABSTRACT FROM AUTHOR]

Selecting the right partner is a key factor for the successful construction of the strategic alliance of prefabricated construction enterprises in China. Based on the summarization of domestic and foreign studies, combined with the characteristics of the strategic alliance of prefabricated construction enterprises, the paper has constructed an evaluation indicator system of the partner selection of the strategic alliance of prefabricated construction enterprises in China. The paper also has conducted an empirical study on the evaluation model of partner selection of the strategic alliance of prefabricated construction enterprises in China by using the method Entropy Weight-TOPSIS. The research results show that the five most influential second-level indicators are commercial housing sales capability, property management capability, commitment of capital, commitment of talents, and product innovation capability. The model constructed in the paper can comprehensively evaluate and select the strategic alliance partners of prefabricated construction enterprises in China. [ABSTRACT FROM AUTHOR]

In this paper, we proposed an advanced business intelligence framework for firms in a post-pandemic phase to increase their performance and productivity. The proposed framework utilizes some of the most significant tools in this era, such as social media and big data analysis for business intelligence systems. In addition, we survey the most outstanding related papers to this study. Open challenges based on this framework are described as well, and a proposed methodology to minimize these challenges is given. Finally, the conclusion and further research points that are worth studying are discussed. [ABSTRACT FROM AUTHOR]

In order to improve the monitoring effect of corporate human resource efficiency under the smart city management model, this paper establishes an evaluation model for the human resource management model between different growth stages of the organization, different organizations in different industries, and different organizations in the same industry. The proposed human resource management model is based on the deduction result of human resource planning and design, work system design and employee system design, and the dynamic matching of the three. Moreover, this paper uses the three-factor vector evaluation model to modify the management efficiency of the human resource model and designs the corresponding intelligent enterprise human resource efficiency monitoring model. In addition, this paper analyzes the system functions and designs experiments to test the model in this paper. Through experimental testing, it can be seen that the enterprise human resource efficiency monitoring system under the smart city management mode proposed in this paper has good practical results. [ABSTRACT FROM AUTHOR]

The primary motive of each and every organization or company is to sustain, strengthen, upgrade, and improve its position and standard in the highly dynamic, constantly changeable, aggressive, and competitive environment. There is a very urgent requirement to develop a framework for green and sustainable vendor selection in the organizations. The main aim of this research is to explore, identify, examine, and evaluate the important, applicable, green, and sustainable vendor selection attributes and to analyze and determine their interactions or relationships in the area of green and sustainable vendor selection. A total of ten important attributes have been determined through review reports and by the assessments of the group of professionals belonging to various organizations. A questionnaire has been prepared for these ten attributes and feedback was maintained from the judgments of the group of professionals in dairy industries. In this paper, a multicriteria decision-making technique namely interpretive structural modeling is implemented to look over the interactions and connections among various attributes and to put forward a constructional representation or digraph. Matriced Impacts Croise's Multiplication Appliqúe and Classment inspection is used to identify which attributes are autonomous, dependent, independent, influencing or not influencing, and importance of one criterion over another according to their driving and dependence powers. It is analyzed numerically from this model that the cost attribute is a very remarkable attribute as it exists in the bottom or sixth level and the attributes economic growth, financial capacity, and research ability are at first or topmost level of this model. The interpretive structural modeling hierarchy constructional representation and Matriced Impacts Croise's Multiplication Appliqúe and Classment inspection will support the company's owner or decision maker for attaining a best decision. [ABSTRACT FROM AUTHOR]

This paper studies the complexity analysis in production between competition and R&D for a traditional energy vehicles enterprise and a new energy vehicles enterprise under the introduction of corporate average fuel consumption credits and new energy vehicle credits mandate. From the internal perspective of market complexity evolution, this paper analyzes the internal mechanism of market competition fluctuation and discusses the influence of different corresponding speeds of enterprises on market stability through the nonlinear dynamics' theory. The research results show that the adjustment coefficient of R&D investment and the price coefficient of credit transactions are the key factors affecting the competitive strategies of the two companies. The difference between these two factors will even change the relative R&D investment intensity, relative profitability, and market stability of the two companies in a balanced state. In addition, the numerical analysis showed that the time-delay feedback control method could control the unstable behavior of the dynamic system efficiently and quickly and make the market quickly recover a stable and orderly state, which provided a scientific basis for decision makers to effectively solve the market instability. [ABSTRACT FROM AUTHOR]

With the rapid development of Internet technology, artificial intelligence and soft computing are gradually applied in various fields. Through active transformation, many companies use artificial intelligence, software computing, and other technologies to develop sales channels, improve corporate performance, and obtain greater benefits. However, some traditional enterprises have been gradually eliminated by the market because they have not rapidly transformed and improved their intelligence. Urban intelligence is the trend of urban economic development, and the degree of intelligence in a city is closely related to the number and scale of intelligent enterprises. In the context of artificial intelligence and soft computing, this paper expounds the relationship between enterprise performance and the degree of urban intelligence and analyzes the key factors affecting enterprise performance and the impact of enterprise performance on the degree of urban intelligence. The results show that Internet technologies such as artificial intelligence and soft computing can improve the performance of enterprises, thereby improving the level of intelligence in cities. [ABSTRACT FROM AUTHOR]

The logistics service chain is a specialized service chain produced along with the continuous update and development of the logistics industry. It is an inevitable direction choice that is naturally formed when the degree of logistics specialization continues to increase. This paper aims to study how to analyze and study the logistics service supply chain model based on artificial intelligence and big data analysis, and describe the data mining algorithm. This paper puts forward the problem of logistics service supply chain, which is based on big data analysis, and then elaborates around its related concepts and algorithms, and conducts case design and analysis on supplier selection. The experimental results show that the customer satisfaction of supplier C has reached 86%, the accuracy rate of supplier D's logistics operations is as high as 90%, and the logistics transportation cost of supplier B is only 0.38 yuan/ton ∗ km. In the end, the three of them were selected as company Z's transportation suppliers. [ABSTRACT FROM AUTHOR]

The role of the sustainable competitive advantage of enterprises is becoming increasingly prominent. Taking TMT behavior integration, enterprise sustainable competitive advantage, absorptive capacity, and critical reflection as independent, dependent, intermediary, and regulatory variables, respectively, and 223 enterprises as an empirical research sample, through theoretical analysis and empirical research, this paper reveals the influence of TMT behavior integration on sustainable competitive advantage of enterprises and intermediary role of absorptive capacity and the regulatory role of critical reflection. The empirical results show that the behavior integration of top management team can promote the sustainable competitive advantage of enterprises. The potential absorptive capacity plays a partial intermediary role between TMT behavior integration and enterprise financial performance and a complete intermediary role between TMT behavior integration and enterprise strategic performance. Realistic absorptive capacity can partially mediate the behavioral integration of TMT and the sustainable competitive advantage of enterprises. Critical reflection plays a positive regulatory role between TMT behavior integration and enterprise strategic performance. The research shows that in order to improve enterprises sustainable competitive advantage, enterprises should take the following measures: ① Enterprise executives must attach importance to TMT behavior integration. ② Enterprise executives should focus on critical thinking. ③ Enterprise executives should take cultivation of absorptive capacity seriously and give full play to the intermediary effect of absorptive capacity. Research model provides a new path to build sustainable competitive advantage, and can be applied to enhance enterprises sustainable competitive advantage from the perspective of TMT behavioral integration. [ABSTRACT FROM AUTHOR]

With the rise and gradual development of the Internet, today's era has been transformed into the information age. The network transaction mode has involved all levels. At the same time, a new business model is gradually emerging, that is, e-commerce enterprises. Compared with the traditional business model, e-commerce enterprises are more information technology, networking, and convenience. In the current cross-border e-commerce enterprise development model, e-commerce enterprise performance evaluation and application have always been a key concern. Based on the lag of performance calculation and analysis of cross-border e-commerce enterprises, this paper carries out experimental analysis by combining the in-depth learning model. The results of the experiment are as follows: (1) it analyzes the growth situation of overseas Internet sales enterprises, determines the research direction of the experiment, puts forward the construction principles of the performance index system of overseas Internet sales enterprises, and constructs the performance evaluation system of overseas Internet sales enterprises according to the principles, to ensure the reliability of data and effectiveness of performance accounting. (2) On the basis of retaining the traditional performance calculation and evaluation mode of cross-border e-commerce enterprises, the in-depth learning mode is integrated into the performance evaluation process of overseas Internet sales enterprises. Using the in-depth learning mathematical algorithm combined with the enterprise performance calculation algorithm of cross-border e-commerce enterprises can not only ensure the effectiveness of performance calculation but also classify more quickly, facilitate the later use, and reduce the pressure on business enterprise enterprises. [ABSTRACT FROM AUTHOR]

Enterprises conduct performance management through performance management systems, which can greatly improve work efficiency and quality. The win-win of human resources and time resources has been realized, making the assessment fair and objective. At present, the application of performance management to digitalization is becoming more and more intense. This paper proposes to use the optimization of the simulated annealing algorithm to help the research of the enterprise performance management system. It is helpful to analyze and solve some negative factors brought by the current traditional enterprise performance management system, so that the employees of the enterprise have higher satisfaction in the performance, and the enterprise can have more far-reaching development goals. In the subsequent survey of employee satisfaction with the enterprise performance management system, the results show that after the implementation of performance management reform, the recognition of performance management by enterprise managers and employees has increased significantly. Among the returned questionnaires, 3360 people expressed great satisfaction, and the proportion increased from 32.69% to 63.62%, almost doubling. A total of 4259 people expressed great satisfaction and satisfaction, the proportion increased from 70.08% to 87.35%. A total of 1021 people expressed dissatisfaction and very dissatisfaction, the proportion dropped from 29.92% to 12.65%. Therefore, this survey result shows that the visual analysis of the digital enterprise performance management system and its application in the operation of the enterprise is very important. [ABSTRACT FROM AUTHOR]

The Business Model Canvas (BMC) is a strategic model for developing business organizations' roadmap toward achieving their goals. While several organizations utilize the Business Model Canvas (BMC) to establish and operate their businesses well, the utilization of BMC seems to be limited in the local market of Saudi Arabia, especially when businesses utilize electronic business channels. This paper aims to explore the status of the utilization of BMC among Saudi SMEs, as a critical sector. The paper highlights the awareness and practice of BMC's nine factors before and during the operation of e-commerce stores by Saudi SMEs. Then, it aims to explore the significance of practicing those factors in increasing the satisfaction level of running businesses. In this paper, a quantitative survey was distributed conveniently to 200 SMEs in the two largest Saudi cities, which are Riyadh (the capital) and Jeddah (the country's main seaport), resulting in 63 valid participations from different industries. After operating e-commerce stores, most SMEs gained more knowledge of five BMC factors: key partners, value propositions, customer relationships, customer segments, and cost structures. Meanwhile, they found some issues in the other four factors: key activities, key resources, channels, and revenue streams. The proposed method exposes the variety of results and indicates a lack of understanding of BMC by the examined e-commerce SME samples, as they depend on traditional methods of identifying the elements of each of the BMC factors. [ABSTRACT FROM AUTHOR]

Since the introduction of a low-carbon economy, corporate performance is no longer limited to the evaluation of internal economic benefits but has become the performance of corporate sustainable development, adding environmental and social factors. Now, the whole world is paying attention to low consumption and low emission. As the main economic pillar of society, the enterprise undertakes the biggest low-carbon task. In order to develop the economy in the longer term and meet the needs of society, enterprises must combine green innovation to evaluate the performance of sustainable development. However, because the previous model's analysis of performance will produce distortion effects, the data error is also relatively large. Therefore, in order to solve these problems and make performance analysis more realistic, this paper deeply discusses the issue of green innovation and enterprise sustainable development performance. Using the method of the SBM-DEA model, it analyzes the performance comparison of enterprises without and with the expected output and conducts a comparison experiment. The result shows that in 2017, the efficiency of company A without unexpected output was 0.6943. The efficiency with undesired output is 0.6643. In 2018, the efficiency of the enterprise without undesired output is 1, and the efficiency with undesired output is 1. After applying the model, it is obvious that the efficiency of computing performance has been greatly improved. Therefore, in order to better study the sustainable development performance of enterprises, the SBM-DEA model should be focused on. [ABSTRACT FROM AUTHOR]

In order to better manage the supplier's inventory and formulate a reasonable distribution plan, based on the existing research, taking the two-level supply chain system composed of one supplier and multiple retailers as the research object and VMI mode as the background, this paper studies the inventory path optimization problem with the goal of minimizing the total cost in the planning period. Taking the retailer's inventory capacity and vehicle capacity constraints as constraints, this method constructs a mixed integer programming model with random demand in multiple cycles and the goal of minimizing the total cost in the planning period. When building the model, the distribution cost is refined. In addition to identifying shipping-related start-up costs and travel costs, processing costs are associated with additional delivery time, which is close to reality. In the algorithm design, the genetic algorithm is combined with the C–W algorithm, a similar hybrid genetic algorithm is used to solve the model, and the sample model is used for estimation; that is, the expected value of the random sample is taken, which is used as the target value for each chromosome. In addition, when optimizing roads, the C–W algorithm is used to divide vehicle capacity according to truck capacity as much as possible, thereby reducing the number of vehicles used and saving the overall total cost of preparation time for certain projects. Facts have proved that the optimized and improved inventory path is more conducive to help enterprises reduce logistics costs and provide theoretical support for enterprise management decisions. [ABSTRACT FROM AUTHOR]

With the accelerated pace of e-commerce, online supply chain finance (SCF) led by logistics enterprises (LE) has attracted increasing attention. On the basis of introducing the related concepts of online SCF dominated by LE, this paper constructs the performance evaluation index system of LE by integrating the balanced scorecard model. Then, we use the analytic hierarchy process (AHP) to evaluate the performance of LE and take company A as an example to calculate the total score of performance in the past seven years. Finally, according to the research results, we give some suggestions to optimize the performance of LE. The research results are conducive to promoting the online SCF model in reality. [ABSTRACT FROM AUTHOR]

Under the background of the new power system, the proportion of new energy power generation enterprises in the power market is gradually increasing. With the further expansion of China's power trading scale, the increasingly fierce market competition, and the instability of new energy output, the credit problems of new energy power generation enterprises in the trading process cannot be ignored. Therefore, improving and perfecting the credit system of new energy power generation enterprises is necessary for building a modern market system. Firstly, the credit indexes of new energy power generation enterprises are constructed from the three dimensions of performance ability, performance behavior, and performance willingness. Then, a credit index evaluation model of new energy power generation enterprises is proposed based on the fuzzy best-worst and improved matter-element extension method. Finally, an empirical study is carried out. The analysis results show that scheduling discipline compliance, historical credit, and participation rate of the market-oriented transaction have a more significant impact on the recognition of new energy power generation enterprises. They should focus on market transactions. The model proposed in this paper can effectively deal with the ambiguity of indexes in the credit evaluation of new energy power companies. Through comparison with other models, the effectiveness of the model proposed in this paper in the credit evaluation of power companies is further verified. Construction provides method support. [ABSTRACT FROM AUTHOR]

The cooperative management strategy plays an important role in the development direction of enterprises. However, there are still many problems in the cooperation management strategy, the long-term development strategy is lacking in the management, which seriously hindered the development of enterprises. Knowledge transfer is an important research field and practice field of knowledge management, the qualitative analysis of knowledge transfer can be applied to the analysis of enterprise cooperation management strategy, which can solve the problems of enterprise management strategy analysis more effectively. In this paper, an enterprise cooperation management strategy analysis system based on the knowledge transfer model is built, in which the EAI algorithm is applied to the analysis of enterprise cooperation management strategy. Finally, the performance of the system is tested in many ways, the results show that the EAI algorithm can not only reduce the computational complexity but also can reduce the degradation phenomenon of the original evolutionary algorithm. The system can withstand the access of a large number of users at the same time, which can meet the needs of users. [ABSTRACT FROM AUTHOR]

Machine learning belongs to the science of artificial intelligence, so its main exploration goal is artificial intelligence, mainly to accumulate experience and improve the relevant performance of the algorithm. ML is a complex discipline that learns and improves skills primarily through imitation. Unstructured text data refer to unstructured data in the form of text. Financial accounting is a basic work of an enterprise, mainly to provide decision-making reference information for enterprise managers to ensure the normal operation of the enterprise. Financial accounting is a management activity that monitors the business and provides relevant information to the relevant authorities. This paper aims to study the advanced artificial intelligence model of financial accounting transformation based on machine learning and enterprise unstructured text data, expecting to use machine learning and unstructured text technology to upgrade the management of financial accounting and improve its analysis level. In this paper, an improved KMP algorithm is proposed for the keyword matching problem of unstructured data. Then, the data crawling technology of unstructured text is studied. It mainly uses the crawler technology based on the Python language and obtains a large amount of information on the Internet by formulating appropriate regular expressions. The algorithm is used to mine the data set and generate frequent itemsets. The association rules mining algorithm is proposed and implemented, and the association rules with practical reference value are obtained. The test leads in this document indicate that the return on assets of the enterprise is −11.2%, the net interest rate on equity is −44.5%, and the business profit rate is −12.1%. This shows that the profitability of the company has been declining in recent years, and there is even the risk of bankruptcy. [ABSTRACT FROM AUTHOR]

New media is a scientific and technological product under the background of the new era, and now new media technology has been widely used in all aspects of social development, and it has spawned the arrival of the new media era. In the new media environment, the survival and development environment faced by enterprises have undergone earth-shaking changes; if you still follow the traditional marketing methods, it will not only reduce the effectiveness of marketing but also because of the deviation from the development requirements of the times be eliminated, bringing threats to the survival and development of enterprises. The development of new media, represented by the Internet and mobile phones, has brought great changes to various industries in the world including tourism. The market size of the travel network is expanding, and online sales are soaring. At the same time, all kinds of tourism organizations often have blind optimism in the construction of tourism networks and lack of reasonable application means, so that tourism network marketing is far from exerting its potential in reality; on the one hand, it cannot provide transaction services that satisfy both supply and demand; on the other hand, it also affects the economic benefits of tourism organizations. Compared with the rapid development of the tourism media industry, the theoretical research related to the actual situation lags significantly. Although the number of related studies at home and abroad is increasing, most of them stay at the level of explanation and introduction, and the analysis of the tourism industry chain is not enough. The breadth and depth of the study are sorely lacking. The future letter needs to summarize the successes and failures of the development of the tourism media industry from a theoretical height and carry out theoretical improvement to guide practice, and it also needs to strengthen forward-looking research, summarize the laws and models, and put forward practical implementation plans to improve the overall development level of the tourism and media industry. Aiming at the problem of new media marketing strategy in shopping tourism scenic spots, this paper applies descriptive research, questionnaire survey, statistical processing, mathematical model, and other research methods to analyze the characteristics of new media such as prominence of personalization, increased audience selectivity, and diversified forms of expression presented by new media compared with traditional media, as well as the differences between the two in terms of communication status, dominant state, and audience state. 4I Marketing theory is applied to new media marketing, the changes in the marketing environment and marketing needs under the background of new media, and the extensive impact of these changes on the marketing mix strategy; the basic strategies and expected effects of new media marketing of tourism enterprises are studied from the aspects of product, price, channel, and promotion; the IPA model is constructed, and the empirical analysis of the shopping tourist attractions of Changshu Garment City in China is carried out. Through the research of this paper, in theory, the understanding of new media marketing is enriched, and in fact, it provides guidance for optimizing the new media marketing strategy of tourist attractions. [ABSTRACT FROM AUTHOR]

The present paper aims to propose a new hybrid multi-criteria decision-making (MCDM) framework with spherical fuzzy numbers (SFNs). We extend two recently developed algorithms such as level-based weight assessment (LBWA) and MULTIMOOSRAL in spherical fuzzy (SF) domain. We present a case study on six MSME units belonging to engineering cluster for examining their leanness. MSMEs form the backbone of the socioeconomic growth and therefore garner attention of the policy makers. Lean manufacturing (LM) has been a key enabler for the last three decades which help the organizations to achieve business growth. We consider the criteria like leadership, supplier focus, customer focus, process management, waste, culture, human resource focus, technology use and communication, and awareness to compare leanness of the MSMEs using expert opinions. We find that committed leadership, waste reduction, and customer value are given more weightage by the experts for achieving leanness in SMEs. Furthermore, the results show that medium and small units with focused product line score high in terms of leanness. We validate the results obtained by our proposed method by comparing with the same derived by using another widely used approach such as Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). We carry out sensitivity analysis for examining the stability in the solution with the changes in the given condition such as variations in the criteria weights. Our results using SF-LBWA-MULTIMOOSRAL show reasonable accuracy and stability. [ABSTRACT FROM AUTHOR]

With the advent of the crossborder e-commerce (CE) boom, more and more traditional enterprises have transformed into the field of crossborder e-commerce. It has become a new outlet for enterprises in the international trade environment, and at the same time, it has some problems in the utilization of resources and the maximization of benefits. In response to this problem, it is very important to optimize the export operation model of crossborder e-commerce enterprises (CEE). With the development of intelligent algorithms, research on the application of intelligent algorithms to the economic field has gradually been carried out. Its characteristics and advantages are of great significance to the optimization of CEE export operation mode. The purpose of this paper is to study the CEE export operation mode and optimization strategy based on data mining algorithm (DMA). Through the analysis and research of DMA, it can be applied to the optimization of CEE export operation mode to cope with the world trade in the new environment. This paper explains the basic theory of DMA and CEE export operation mode. Its effect is experimentally analyzed, and the relevant theoretical formulas are used to explain. The results show that the comprehensive trade quality index of the CEE export operation mode integrating DMA is higher, and the adaptability is stronger. Compared with the traditional operating model, the difference between the two indices is 3.175 index points. It has guiding significance in terms of CEE export operation mode and optimization strategy. [ABSTRACT FROM AUTHOR]

Innovation is the driving force behind enterprise development. Improving the quality of the internal control of enterprises and increasing the intensity of R&D investment are important ways to enhance the level of scientific and technological innovation. Based on the data of Shanghai and Shenzhen A-share listed companies from 2010 to 2019, in this paper, we empirically examine the correlation between the quality of internal control and the intensity of R&D investment by using the level of corporate cash holdings as an intermediary variable. We find that high internal control quality can improve cash-holding level and that improving cash-holding level will increase R&D investment intensity. That is, cash-holding level has a mediating effect between internal control quality and R&D investment intensity, while internal control quality can have a direct or indirect positive effect on R&D investment. Accordingly, this study has important theoretical significance and practical value for enterprises that seek to promote R&D innovation and improve their internal control. [ABSTRACT FROM AUTHOR]

Crowdfunding, as an emerging phenomenon of enterprise after entrepreneurship financing, has maintained rapid and sustained growth in recent years. For crowdfunding environmental protection enterprises, one of the main challenges in financing is to reduce the uncertainty of public investors about the quality, management level, and products or services of crowdfunding projects. After reading the text of crowdfunding projects, the public investors have a subjective impression of the crowdfunding environmental protection projects, which determines the public investors' judgment on the risks and prospects of environmental protection projects and the willingness to invest. Therefore, the texts of crowdfunding projects are very important. In this paper, the data of 130 crowdfunding environmental protection projects on the Modian website are selected, and the ordinal logistic regression model is used. This paper explores the influence of language style in the description text and brand name in the title text on crowdfunding performance. [ABSTRACT FROM AUTHOR]

Currently, the global consumer market is moving toward digitalization, and cross-border e-commerce enterprises are no exception and have to make adjustments in their operational strategies. Digitalization brings complexity, dynamism, and fragmentation in sales channels, media environment, and consumer behavior, requiring cross-border e-commerce enterprises to react more quickly and timely, and the need for intelligent operations is becoming more and more urgent. In this paper, through the problem of predicting the e-commerce user behavior process, the model usually needs to focus on both long-term preferences and short-term preferences of e-commerce users in the current behavior sequence; otherwise, the behavior prediction will be much less effective. Specifically, through a comprehensive analysis of typical cases, the strategies and problems in the intelligent operation process of China's cross-border e-commerce enterprises at the present stage are discussed, and corresponding suggestions are put forward, so as to promote the rapid development of China's cross-border e-commerce enterprises. [ABSTRACT FROM AUTHOR]

Cluster analysis is one of the most commonly used data analysis methods, and K-means is among the most popular and widely used clustering algorithms in recent years. Because of its performance in clustering huge amounts of enterprise data, the K-means algorithm is one of the most commonly used clustering methods in enterprises. Furthermore, in the context of the new era, enterprises are under growing pressure from both domestic and international sources, particularly market competition pressure. Moreover, the traditional K-means dispersed clustering algorithm has several issues when it comes to clustering big data in enterprises, such as instable clustering findings, poor clustering results, and low execution effectiveness. Based on the premise of the clustering algorithm in enterprises, this paper constructs an improved K-means clustering algorithm of the enterprise management system. It enables businesses to quickly address deficiencies, improve information in all areas, supplement adequate resources, and promote growth. The proposed algorithm uses the sample density, the distance between the clusters, and the cluster compact density, and defines the product of the three as different weight densities and the maximum difference as the initial cluster center to solve the problem. It finds the point of sampling with weight density, randomness, and low quality of early cluster center selection. The experimental results show that my planned algorithm has higher execution efficiency, accurateness, a lower error rate, and good stability. [ABSTRACT FROM AUTHOR]

With the advancement of society and economy, the market competition among various businesses has become increasingly fierce. Nowadays, if businesses want to grow in the face of adversity, they must move forward boldly and make use of abundant human resources to fuel their growth. Human resource management is becoming increasingly important. As a result, this paper develops an enterprise human resource quality assessment system based on the WICS leadership model. The differences between the WICS model and the traditional management model are first compared in this paper. The requirements of the WICS model in human resource management are then described. Furthermore, this paper proposes a human resource evaluation algorithm that combines data-driven and WICS models to address the current human resource cost evaluation algorithm's low accuracy and poor effect. The simulation results show that the proposed algorithm can reflect changing human resource cost characteristics, improve human resource cost evaluation results, and obtain better results than other human resource cost evaluation models and has a wide range of applications. [ABSTRACT FROM AUTHOR]

Human resource planning is to predict and analyze the quantity, quality, and structure of human resources in different historical periods, different social environments, and different development stages, so as to meet the needs of human resources enterprises to implement strategies. It ensures that the supply of human resources within the enterprise can not only meet the needs of the enterprise, but also reduce unnecessary business costs without redundancy. It enables the supply and demand of human resources in daily business operations to achieve and maintain the work balance after dynamic resource management. Human resource planning in an enterprise not only helps to improve the utilization of human resources within the enterprise. And it is an important standard for human resource management such as recruitment, promotion, and training. This paper establishes an intelligent scheduling model of enterprise human resources based on inverse relationship. The experimental results show that before the causal analysis, the business performance measurement items are tested and the sphere test is carried out. The value is 0.86, greater than 0.85, indicating that the group data are suitable for exploratory factor analysis. At the same time, the significance of the spherical test result is 0.00, which is lower than 0.01, and the null hypothesis that the correlation coefficient matrix is a unit matrix is rejected. It shows that the data are correlated and are suitable for analyzing exploratory reasons. [ABSTRACT FROM AUTHOR]

At present, the number of enterprises in financial crisis in China is rising sharply, and the ability of enterprises to resist risks is generally weak. Therefore, it is necessary to establish a corporate financial crisis early warning system, to detect the signs of corporate financial crisis before it arrives and to inform managers in advance, so that effective measures can be taken as soon as possible to eliminate hidden dangers. This paper selects the two-year data of 40 companies from 2017 to 2019 as training samples and the data of 20 companies as prediction samples. After testing, 12 index variables that can reflect the financial problems of energy companies are finally selected as the basis for modeling. Then, we use Logistic and BP neural network modeling, respectively, to study and compare the data from 2017 to 2019 to predict the financial risk in the following year. The results show that the BP neural network model in the two models is better than the Logistic model in terms of fitting degree or prediction accuracy for enterprise financial early warning. Therefore, the BP neural network model has a better effect and is more suitable for the practical application of enterprises in China. [ABSTRACT FROM AUTHOR]

Cloud computing has played a strong role in promoting the accounting informatization of small and medium-sized enterprises, which is helpful to accelerate the construction of accounting informatization. In order to improve the accounting informatization construction effect of small and medium-sized enterprises, this paper proposes an improved ISCA accounting informatization model based on cloud computing and proposes a semisupervised clustering method of accounting information based on the minimum prototype cluster to classify accounting information. Moreover, this paper uses labeled samples to measure the compactness and purity of clusters and guide the splitting of clusters and constructs a corresponding intelligent model structure. The research shows that the improved ISCA model proposed in this paper has a very obvious effect on the improvement of application of accounting informatization in small- and medium-sized enterprises in the cloud computing environment. [ABSTRACT FROM AUTHOR]

In order to improve the cost control effect of the supply chain of intelligent manufacturing enterprises, this paper improves the IQC algorithm. In order to overcome the problem of multitype data processing in the supply chain, this paper describes the high-frequency NCS as a delta arithmetic system with input time-varying delay, high-frequency constraints, and actuator saturation. Moreover, through a double closed-loop feedback configuration, this paper combines the loop structure of the supply chain to analyze the stability of the actuator saturated high-frequency NCS and combines the experiments to verify the reliability of the improved algorithm. In addition, on the basis of the improved algorithm, this paper constructs an intelligent supply chain cost control system, evaluates its functional modules, sets up the system architecture, and analyzes the performance of the system in combination with experimental research. The experimental research results show that the supply chain cost control method of intelligent manufacturing enterprises based on the improved IQC algorithm proposed in this paper has good results and meets the operational needs of intelligent manufacturing enterprises. [ABSTRACT FROM AUTHOR]

Sustained and stable external financing, affected by the financial environment, is a necessary condition to support the green technological innovation of enterprises. This paper focuses on the impact of bettering the financial environment of digital finance on enterprise green technological innovation, as well as the mediating role of financing costs and financial flexibility in this process. Using China's data on manufacturing enterprises listed in Shanghai and Shenzhen from 2011 to 2018, the hypotheses are tested. The result suggests the following: (a) digital finance effectively promotes enterprises to carry out green technological innovation, specifically, the coverage and depth of digital finance can promote enterprises' green technological innovation, but the degree of digitization has no significant impact; (b) digital finance improves the financial environment by making up the shortage of traditional financial system through reducing financing problems such as "financing difficulty," "matching difficulty," and "supervision difficulty," which make effective contributions to enterprise green technological innovation; (c) financing costs negatively mediate the relationship between digital finance and enterprise green technological innovation, while financial flexibility positively mediates the relationship. Overall, our findings shed light on the role digital finance plays in shaping corporate environmental behavior—and ultimately innovation in sustainability—in financing constraint setting. [ABSTRACT FROM AUTHOR]

This paper provides an in-depth study and analysis of data transmission in key aspects of the enterprise using internet of things (IoT) technology. IoT technology can provide an effective solution to the integration of enterprise resources and efficiency improvement. If it can be properly introduced into the enterprise, it not only can effectively integrate the enterprise resources in the management but also can significantly improve the efficiency and thus further reduce its operating cost. This paper explores the management application strategy of IoT in the key aspects of digital transmission in enterprises. It can also increase productivity to address labour shortages. Most importantly, because of the internet of things technology, many emerging industries have been derived. In order to achieve this research objective, firstly, based on the in-depth study of the problems of digital transmission of key aspects of the enterprise, this paper evaluates and summarizes the supply chain, safety, efficiency, and quality problems that often occur in the past operation and management of the case enterprise and analyses the main reasons for the formation of the problems and then recognizes the necessity and feasibility of introducing IoT technology and management; secondly, based on the kernel of IoT and industrial IoT technology combined with the main modules of enterprise operation management, using the 5S field management method, we try to build a three-dimensional all-round electrical equipment enterprise IoT management application scheme design system; and finally according to the planning and design rules and management process, we focus on implementing digital transmission network application projects from the enterprise level combining key links of technology and management. This paper studies not only technical innovation but also a revolution in management. The research in this paper will provide a more feasible technical and management design scheme for the application of IoT in enterprises for industry reference. [ABSTRACT FROM AUTHOR]