Search

Environmental pollution has become an important obstacle on the path of ecological civilization construction, and it is urgent to control environmental pollution. By establishing an evolutionary game model, this thesis focuses on analyzing how paper-making enterprises choose their own emission reduction strategies under the reward and punishment mechanism. It further analyzes how social welfare changes under the reward and punishment mechanism, and finally through simulation research, this thesis analyzes the evolutionary paths of paper-making enterprises' pollution emission strategies under the reward and punishment mechanism. The results of the reward and punishment mechanism are as follows: under the static reward and punishment mechanism, the game system will repeatedly oscillate around a point. There is no stable equilibrium point at this time. However, under the dynamic reward and punishment mechanism, the game system will tend to a stable equilibrium point. The results of social welfare analysis show that high-intensity rewards will reduce the amount of pollution discharged by paper-making enterprises, thereby maximizing social welfare. On the contrary, when paper-making enterprises discharge a large amount of pollution, they will be subject to high-intensity penalties. When facing high-intensity punishments, paper-making enterprises will tend to not to discharge. So social welfare is also maximized. The simulation research results show that reasonable punishment strategies are more effective than reward ones. Based on this, the author proposes countermeasures, such as establishing a reasonable reward and punishment mechanism, reasonably determining the reward and punishment intensity for polluting enterprises. The emission reduction strategies of paper-making enterprises will be affected by the government's reward and punishment mechanism. A deep study of its internal mechanism is not only of great significance for pollution control but also of great significance for the development of a green economy. [ABSTRACT FROM AUTHOR]

This paper combines the digital twin system modeling method to conduct an in-depth study and analysis of graph-theoretic combinatorial optimization. This paper provides new ideas and approaches for optimal numerical analysis work by studying the digital twin modeling method that integrates digital modeling and graph theory combination, provides theoretical support for safe, stable, and economic operation of the system, proposes a solution for digital twin model based on big data platform, focuses on the nearest neighbor propagation (AP) and graph theory combination, solves the digital twin real-time monitoring data asynchronous, incomplete problem, and applies the algorithm to the digital twin model based on the big data platform for data preprocessing to achieve better results. This paper also presents a web-based digital twin system based on intelligent practical needs, analysis, and comparison of existing models, combined with digital twin technology, detailing the differences and connections between the various levels of numerical analysis and the implementation of this data in various fields, such as user management, equipment health management, product quality management, and workshop 3D navigation and detailed modeling of the digital twin system based on this numerical analysis to realize remote online monitoring, analysis, and management. In this paper, for the numerical analysis process, firstly, the key technologies of modeling and simulation operation control of production line based on digital twin are studied, and the rapid response manufacturing system based on a digital twin is designed and validated. Secondly, a scheduling technology framework for capacity simulation evaluation and optimization is established, and batching optimization, outsourcing decision, and rolling scheduling techniques are thus proposed to form a batching optimization algorithm based on priority rules, which realizes batching processing, outsourcing decision, and rolling scheduling of production orders to optimize equipment utilization and capacity. Finally, digital twin-based modeling is designed, and the validation results demonstrate the system's superior performance in achieving information interaction between physical and virtual production lines, optimization of numerical analysis, and display of results. [ABSTRACT FROM AUTHOR]

Current technology trends have been gradually integrated into the production of all walks of life, which play an indispensable part in promoting the intelligent development of enterprises, and have brought a greater impact on production and reformation. With the rapid development of the economy and technology, the manufacturing industry has played a very important role. For this reason, the introduction of artificial intelligence into machinery manufacturing can not only improve production efficiency but also save labor and reduce labor costs. The application of artificial intelligence in machinery manufacturing has a critical good role in promoting industrial upgrading and transformation. This time, through the application of smart algorithms in machinery manufacturing and its automation, we expect that such a technological revolution can provide a new development prospect for the development of manufacturing intelligence and automation. Taking the malfunction identification of string striking machinery as an example, this paper studies the smart identification method of mechanical malfunction based on multisensor. In the process of malfunction identification of keyboard stroke machinery, the accuracy of malfunction identification results is low due to the influence of the identification model. Moreover, a malfunction identification and analysis method for keyboard stroke machinery based on BP optimized by GA is proposed. The mechanical data of keyboard chords are acquired by sound-sensitive sensors, and the data features are extracted by wavelet packet decomposition. Based on the optimized BP, a mechanical malfunction judgment model is constructed, and various parameters in the model are calculated. The results show that the intelligent identification method proposed has exhibited strong adaptability and superiority compared with the traditional method. [ABSTRACT FROM AUTHOR]

Since 2007, knowledge graphs, an important research tool, have been applied to education and many other disciplines. This paper firstly overviews the application of knowledge graphs in education and then samples the knowledge graph applications in CSSCI- (Chinese Social Sciences Citation Index-) indexed journals in the past two years. These samples were classified and analyzed in terms of research institute, data source, visualization software, and analysis perspective. Next, the situation of knowledge graph applications in education was summarized and evaluated in detail. Furthermore, the authors discussed and assessed the normalization of knowledge graph applications in education. The results show that in the past 15 years, knowledge graphs have been widely used in education. The academia has reached a consensus on the paradigm of the research tool: examining the hotspots, topics, and trends in the related fields from the angles of keyword cooccurrence network (KCN), time zone map, clustering network, and literature/author cocitation, with the aid of CiteSpace and other visualization software and text analysis. However, there is not yet a thorough understanding of the limitations of the visualization software. The relevant research should be improved in terms of scientific level, normalization level, and quality. [ABSTRACT FROM AUTHOR]

Over the past few decades, numerous scholars have conducted research on global value chains, and the amount of literature in this field has grown rapidly to become "big data." In order to deeply analyze and explore the current research status and development trends in the field of global value chains, this article conducted a systematic and quantitative study on the global value chain. Based on the Web of Science Core Collection SCIE and SSCI databases, this article searched 8273 articles published between 2001 and 2021 with the theme of "Global Value Chain" and used visualization and bibliometric analysis methods. The research field was analyzed using VOSviewer software. Research has shown that the number of papers published in the global value chain field has been continuously increasing over time and has entered a period of rapid development since 2016. The main disciplines are economics and management. A few researchers and research institutions have a strong influence, but the cooperation between scholars and institutions is relatively weak. The United States, the United Kingdom, and China dominate the research field. The complex impact of the natural environment and public health on the global value chain, and the impact of big data and artificial intelligence on the global value chain, has become a new direction for future research. Countries should actively promote the development of the digital economy and green economy, promote the effective allocation of global value chain resources by enterprises, and adhere to the development of good bilateral political relations to reduce the uncertainty of enterprise participation in the global value chain caused by political risks. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic linkages among economic policy uncertainty (EPU), the green bond market, the carbon market, and the macroeconomy using the time-varying parameter vector autoregressive (TVP-VAR) model with monthly data spanning from January 2016 to December 2021. Additionally, it assesses the robustness and accuracy of the empirical results through the Bayesian vector autoregressive (BVAR) model. The findings indicate that EPU negatively affects the green bond market in the short term but has a positive impact in the medium and long term. Conversely, EPU has a positive impact on the carbon market in the short term but a negative impact in the medium and long term. Furthermore, the green bond market negatively influences the carbon market in both the short and medium to long term. These results suggest that emerging markets, such as the green bond and carbon markets, are influenced by EPU. The adverse impact of the green bond market on the carbon market, however, contributes to expediting China's attainment of its low-carbon objectives. Appropriate economic policies can play a vital role in accelerating the transition to a low-carbon economy. The study also reveals that the US-China trade war has expedited the development of green capital markets in China, despite its impact on the green economic transition in the country. These findings provide insights for the government and investors to formulate suitable strategies for risk mitigation. [ABSTRACT FROM AUTHOR]

Low energy consumption and green transformation of automobile product portfolio is the trend of the times. Automotive manufacturers make product portfolio decisions by setting multiple criteria such as fuel consumption, sales, and volume. It is also important to take into account the symbiotic interaction effects between automotive products. In order to achieve the above research objectives, this paper constructs the Lotka–Volterra MCGP model to make multicriteria decisions on automobile product portfolio design from the perspective of energy sustainability with BMW Brilliance is taken as an example to illustrate the process of using the multicriteria model. The empirical analysis successively measures product growth using the logistic model, analyzes the symbiotic relationship of product portfolios using the Lotka–Volterra model, and finally performs multicriteria evaluation using the MCGP model. In order to verify the reliability of the model, this paper verifies the robustness of the model from the perspectives of parameter dynamics, system boundaries, and model scalability. The results of empirical analysis and robustness analysis show that the Lotka–Volterra MCGP model proposed in this paper is applicable to the multicriteria decision-making of automobile product portfolio design from the perspective of energy sustainability. [ABSTRACT FROM AUTHOR]

Facing the dual background of risk society and the fourth scientific and technological revolution, digital emergency management (DEM) research has attracted wide attention worldwide. Based on the comparative analysis of data from Web of Science (WOS) and China National Knowledge Infrastructure (CNKI) databases, the research draws the knowledge map by CiteSpace, in order to analyse the spatiotemporal distribution, hotspots, and trends of DEM research. The following are the results: (1) DEM research shows a spiral growth, with a significant increase in the number of papers. Existing highly cited references are mainly carried out from the perspective of management or technology. (2) The complex countries' cooperation network has been formed from the USA, China, and other countries; the complexity of the institutions' cooperation network must be strengthened, and the density of the authors' cooperation network is low; DEM research has significant interdisciplinary attributes. (3) The hotspots of DEM research can be divided into three categories: means, processes, and objects, but the research emphases between international and China are different. (4) The evolution of DEM research can be divided into three stages between international and China: embryonic, development, and deepening stages, and research contents in each stage show some differences. (5) The trends of DEM research between international and China are different. The former are information technology, artificial intelligence, and machine learning, whereas the latter are emergency decision making, scenario analysis, and public health. [ABSTRACT FROM AUTHOR]

This paper aims at identifying the causal relationship between the reform of the cultural system and the upgrading of industrial structure, revealing the causal relationship between the reform of the cultural system and the upgrading of industrial structure, which is of great significance for promoting the reform of the cultural system and the upgrading of industrial structure. The impact of cultural administrative reform on industrial structure upgrading is empirically tested using panel data from 261 prefecture-level cities in China from 2001 to 2017. The double difference model and PSM-DID method are used. This includes conducting placebo tests and examining the robustness of empirical findings using other methods. The findings indicated that (1) the influence coefficient of the cultural administrative system reform on industrial structure upgrading is positive and passed the significance level test, indicating that the cultural administrative system reform significantly promoted industrial structure upgrading, and on average, it can improve the level of the urban industrial structure by 11.81 percent. (2) Theoretical analysis of the mechanism demonstrates that the innovation level acts as a link between cultural administrative system reform and industrial structure upgrading, implying that cultural administrative system reform promotes industrial structure upgrading by stimulating the innovation level of cultural enterprises. (3) The results of the heterogeneity analysis indicate that the influence of cultural administrative reform on industrial structure upgrading is highly regionally and economically differentiated. The higher the economic level of the local community, the more effective the promotion effect on industrial structure upgrading. The reform of the cultural administrative system has a greater impact on industrial structure upgrading in the eastern region than in the central and western regions. On the basis of the foregoing research findings, this paper makes some policy recommendations for releasing the overall system reform dividend based on the cultural system and promoting regional industrial structure upgrading. [ABSTRACT FROM AUTHOR]

To measure the gray relation between the core competence of research universities and its influencing factors, this paper took the same period statistical data of the five research universities directly subordinate to the Ministry of Education of China as the research samples, all these five schools were shortlisted in the "World Top 300" rankings of USNews, QS, THE, and ARWU from 2014 to 2018, and the indicator systems of the four authoritative lists were taken as the basis; 30 representative indicators affecting the core competence of research universities were selected, and the gray relation model was adopted for the research; moreover, this paper applied the information entropy method to calculate the weight of each indicator and estimate the comprehensive gray relation between the core competence of research universities and the entire factor system. This research gives the rankings of the influencing factors of the core competence of research universities, and there is a 0.8485 degree comprehensive gray relation between the influencing factors and the core competence of research universities, which has further clarified the future development direction of research universities. [ABSTRACT FROM AUTHOR]

This paper simulates the behavior mechanism of each subject in the equipment manufacturing industry-university-research (IUR) collaborative innovation system based on NetLogo, and constructs the input-output model of each subject. Secondly, the reasonable value of each parameter is determined through expert consultation, and finally 6 scenarios are selected to simulate the evolution of the IUR collaborative innovation system. The results show that different decision-making behaviors of each subject will lead to different operating states of the innovation collaborative system. When the conditions of each subject are exactly the same, the innovation system can achieve stable and continuous operation. However, if the initial conditions are different, the IUR collaborative innovation system needs an authoritative intermediary to coordinate the behavioral strategies of each subject, strengthen the willingness to cooperate, and ensure its stable operation. Reasonable reward and punishment measures are also an effective and important measure, which can mobilize the enthusiasm of all subjects for collaborative innovation. This paper is of great significance for the IUR collaborative innovation in equipment manufacturing industry. [ABSTRACT FROM AUTHOR]

This paper takes 286 prefecture-level Chinese cities from 2011 to 2019 as research objects. It empirically examines the influence of digital finance on green development by using the EBM model, two-way fixed effect model, and instrumental variable method. It is found that digital finance can significantly promote the green development of Chinese cities, and this conclusion is still valid after the robustness tests, such as the instrumental variable method dealing with endogeneity and two-sided winsorization. The mechanism analysis results suggest that only the breadth of digital finance can significantly promote green development in the internal mechanism of digital finance, but the effect of coverage depth and digitization degree is not significant. The external mechanism of industrial structure upgrading assumes the mediating role of digital finance in improving the level of green development. The heterogeneity analysis results show that digital finance has a stronger impact on green development in the central and western cities and small-scale cities. This paper contributes to the study of the relationship between digital finance and green development and puts forward relevant suggestions. [ABSTRACT FROM AUTHOR]

Background. Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. Methods. Through the intelligent transformation of jig, this paper proposes an intelligent washing method with cooperated deep reinforcement learning and evolutionary computation. First, it designs a fault warning method based on statistical analysis, helping to recover the normal running state of jig with manual maintenance. Then, it constructs a regulation strategy generation method with deep reinforcement learning supported by the fusion of artificial experience and historical data. Last, for the lack of monitoring data caused by poor communication quality and environment, the regulation strategy prediction method with evolutionary computation and surrogate model is proposed. Results. In practice, this method shows accurate fault warning accuracy and rapid cleaned coal ash adjustment response ability. Conclusions. This shows that the method proposed in this paper is of great significance for intelligent washing and can better cope with the special situation when the washing equipment sensing data are missing. [ABSTRACT FROM AUTHOR]

For the purpose of understanding the effect of green marketing on brand image, this paper has added mediation variable namely brand image into the research model; meanwhile, in order to better discuss about this issue in the context of green marketing, the paper considers that greenwash is an indispensable element in adjusting green marketing's effect on the brand. The paper has used the method of a questionnaire survey to distribute questionnaires on online social platforms. A total of 500 questionnaires have been distributed, and 415 valid questionnaires have been collected with an effective collection rate of 83%. In this paper, SPSS 24 and AMOS 23 are applied to verify its theoretical model and structural model. The result manifests that the design of the questionnaire is well reliable and highly effective; meanwhile, variables are significantly correlated. Besides, it concludes that the relationship between green marketing and brand trust differentiate in the following two dimensions: spontaneity and compulsion. Moreover, brand image plays an obviously intermediary role between green marketing and brand trust, which also proves that greenwash works as a significantly negative regulatory role. [ABSTRACT FROM AUTHOR]

In recent years, because the complex system discrete model has brought good results in the application of many research directions such as human management analysis, control system prediction, and animal group prediction, how to combine the complex system discrete model with the prediction of enterprise brand communication effect has become a current research hotspot. Based on this, this paper studies the application of the discrete model based on the complex system in sports club to enterprise brand communication and designs a model of the impact of professional sports club on enterprise brand communication based on the SIR model and PSO algorithm. Firstly, this paper analyzes the research status of the impact on enterprise brand communication at home and abroad and optimizes and improves the impact of professional sports clubs on enterprise brand communication and the shortcomings of big data analysis technology in the current research. The complex system discrete model can accurately analyze the enterprise brand communication and conduct big data mining analysis with known professional sports clubs to achieve accurate calculation. The results show that in the process of analyzing the impact of professional sports clubs and enterprise brand communication, the communication mode design of professional sports clubs based on SIR-PSO algorithm can not only effectively deal with various complex discrete data evaluated by club users but also analyze and evaluate the impact of professional sports clubs on enterprise brand communication. [ABSTRACT FROM AUTHOR]

With the development of digital technology, the curriculum design of art majors is also quite different from traditional courses. With the continuous development of information technology and the continuous maturity of campus network technology, teaching resources have become an important part of information resources. High-quality teaching resources play an important role in improving teaching quality and excavating educational development potential. However, traditional classroom teaching is difficult to meet people's needs. In the context of the current new normal, the way of social and economic management has changed. On the one hand, traditional course teaching resources store information in the forms of paper lesson plans, PPT courseware, discrete pictures, and video files. These forms of storage are not conducive to the distribution and sharing of resources. On the other hand, these teaching resources are scattered among the teaching teachers. As the curriculum develops, the courses taught by teachers change. Because schools lack effective means for unified management, these teaching resources are easily lost. The used method is not conducive to the accumulation of teaching resources or the continuation and development of courses. In order to present good results, these materials usually occupy a large amount of storage space. Therefore, some existing information-based teaching platforms cannot meet the demand. We use network and web technology to develop a teaching file management system, which is very necessary. This paper firstly compares the mature teaching resource management system on the market and some problems in its professional application. Secondly, the article analyzes the actual situation of teaching resource management of art design majors in China and generally describes the system development background and technology. Then, the paper analyzes the requirements of the system in detail by using the object-oriented method and gives the overall design and implementation method of the system. These methods include the use case diagram of the subsystem, the flow chart of the main module, the system architecture, and the design and application of UML. Finally, this paper designs a test case for the teaching resource management system. [ABSTRACT FROM AUTHOR]

Accurate risk assessment of international scientific and technological (S&T) cooperation is significant to international cooperation. In this paper, 5 risk dimensions with respect to the political, economic, social, cultural as well as technological of the regional comprehensive economic partnership countries (RCEP) are selected to establish a proper S&T cooperation index system for risk assessment. To calculate the weight of each index, a cross-entropy combination weighting method is proposed based on the combination weighting method of game theory. Furthermore, the standard cloud model is constructed by using the golden ratio, and the risk of S&T cooperation among the RCEP countries is analyzed by the cloud model. The results show that the combination weighting method proposed in this paper is effective, and its calculation is simpler than that of the game theory combination weighting method. Besides, compared with political, social, cultural, and technological indicators, economic indicators have a greater impact on S&T cooperation risk. Furthermore, it is also obtained from the results that the risk of S&T cooperation with China and the Philippines is at a lower to low level and medium to higher level, respectively, and the risk of S&T cooperation with other countries is all at a lower to medium level. [ABSTRACT FROM AUTHOR]

This paper proposes an improved whale optimization algorithm with chaotic mapping and adaptive iteration strategy (CMAIS-WOA). This algorithm addresses the issues of the WOA algorithm that is prone to local optimal solutions with low stability. CMAIS-WOA utilizes chaotic mapping to enhance the diversity and coverage of the initial population. Also, it adaptively adjusts the weight values based on the current distribution of whale populations and the fitness of search agents. In addition, CMAIS-WOA uses an improved nonlinear convergence factor to adjust the breadth-first and depth-first search during the optimization process. The performance of the proposed CMAIS-WOA is evaluated by using 13 classical benchmark functions and IEEE CEC2014 test suite. The experimental results show that CMAIS-WOA effectively improves the stability of the optimal solution and helps the algorithm to approach the global optimal solution. The method proposed in this paper contributes to the field of optimization which solves problems more powerfully and efficiently. [ABSTRACT FROM AUTHOR]

Under the background of the rapid development of digital economy, this paper empirically analyzes the impact of digital transformation on enterprise innovation and selects the panel data of China's Shanghai and Shenzhen A-share listed companies from 2013 to 2021 as the research objective is to study the impact of digital transformation on enterprise innovation from theoretical and empirical perspectives. First, we find that digital transformation accelerates enterprise innovation, a conclusion that has been validated through robustness testing. Second, digital transformation impacts enterprise innovation by enhancing productivity and information transparency. Third, financing constraints and financial redundancy play distinct regulatory roles in the process. Fourth, heterogeneity analysis finds that the role of digital transformation in promoting enterprise innovation has different effects in state-owned and non-state-owned enterprises, high-tech and non-high-tech enterprises, and enterprises with different life cycles. Finally, the functional analysis suggests that further investigation is needed to determine whether digital transformation can significantly promote the sustainable development of enterprises through innovation while also recognizing that this function may have a lag effect. Overall, this study contributes to a deeper understanding of digital transformation and innovation-driven practices and encourages more significant integration of the real and digital economies. [ABSTRACT FROM AUTHOR]

It is important in image restoration to remove noise while preserving sharp edges and fine details such as blurred thin edges and low-contrast fine feature. The Perona–Malik (P-M) model is a well-known anisotropic diffusion denoising model, which can effectively remove noise while preserving edges. However, its diffusion coefficient only associates with the gradient of each pixel but not with the local region information; thus, the P-M model is not able to effectively preserve the important details of image. To address this problem, this paper proposes an anisotropic diffusion denoising model based on local entropy. The diffusion coefficient of the new model not only depends on the gradient of image but also on the local region information described by local entropy. On this basis, a coupled anisotropic diffusion scheme is proposed for detail-and edge-preserving smoothing. Experimental results show that the proposed model not only can effectively remove noise while preserving the boundaries better but also can maintain important details in an image very well. [ABSTRACT FROM AUTHOR]

In the operation of service-sharing platforms, online review information is crucial to attracting consumers. Considering consumers' preference for online review information, this paper discusses the pricing policy selection for a service-sharing platform providing vertically differentiated services in sharing economy, which is worth studying. In this paper, a platform service supply chain composed of a high-quality service provider, a low-quality service provider, and a service-sharing platform is considered. For the two pricing policies of a platform: service provider pricing and platform pricing, the profit-maximizing models are constructed, and the optimal high-quality and the low-quality service prices are obtained. This paper also analyzes the effects of online review information on the profits of service providers, platform profits, consumer surplus, and social welfare under the two policies. The results show that under the platform pricing policy, the platform can gain more profits, while the surplus of consumers and service providers may decrease. When the online review information exceeds a threshold, the high-quality service provider profit under the service provider pricing policy is larger than that under the platform pricing policy. Under the platform pricing policy, the low-quality service provider can earn more profit. We also find that the low-quality service provider is more motivated to encourage consumers to provide online reviews regardless of the pricing policy. [ABSTRACT FROM AUTHOR]

As an important component of modern service industry, tourism is regarded as a "green" driver to regional economic growth and industrial upgrading. Applying the "quasi-natural experiment" advocated by the "The Belt and Road" initiative, this paper, based on the method of DID, assessed the influence of this initiative on regional tourism development by analyzing panel data collected from 286 prefecture-level cities in China over the period of 2007–2018. It is found that the "The Belt and Road" initiative has stimulated market dynamics and promoted tourism development in the regions along the route and has significantly improved indicators such as per capita domestic and inbound tourism revenue and per capita domestic and inbound tourist receipt. Also, the degree of contribution of domestic tourists to the tourism economy of the regions where the policy has been implemented is stronger than that of inbound tourists. In sum, the results of this paper not only confirm that the "The Belt and Road" initiative has significantly contributed to the high-quality tourism development of Chinese provinces along the routes but also provide important policy enlightenment for the upgrading of regional tourism industry and regional economic balance. [ABSTRACT FROM AUTHOR]

The China Securities Regulatory Commission (CSRC) proposed the green channel policy for poverty alleviation Initial Public Offerings (IPOs), aiming to help poverty-stricken areas reduce poverty and increase income, but it has an impact on the business performance of the companies involved. This paper uses data from public annual reports of listed companies to construct a policy intervention group and a control group and comparatively analyzes the degree of annual performance downturn of newly listed companies in A-share from 2016 to 2017 through a counterfactual method, and the results show that the "IPO green channel" policy for poverty alleviation has an obvious negative effect on listed enterprises in poverty-stricken counties. The results show that enterprises listed via the green channel have more significant performance downturn than those listed normally during the same period. This paper suggests that the distortion of the market issuance system causes the declining of the quality of IPO firms. Finally, this paper suggests that regulators should cooperate with local governments actively to ensure the smooth implementation of the government's poverty alleviation efforts while balancing market equity and efficiency. The SFC should take more consideration of institutional compatibility for policy output in financial poverty alleviation to avoid institutional alienation and distortion of corporate behavior. [ABSTRACT FROM AUTHOR]

Logo design is related to the image of a company, unit, product, etc. A good logo can leave a deep impression on people and intuitively understand the content of the product. With the increasing emphasis on intellectual property protection, the design of logos should also pay more attention to the protection of property rights. It can be said that the logo of some big brands is enough to represent the enterprise itself; for example, seeing the red cross as a hospital. This paper aims to propose a logo design process and method under the background of intellectual property big data, so as to make the logo design more procedural and efficient, and to better focus on the protection of property rights. By introducing the relevant knowledge of logo design and trademark registration, it is indicated that trademark search can be used as an auxiliary tool for logo design. Combined with digital media and big data technology, a logo image recognition and classification method is designed so that the trademark registration and screening stage can avoid the infringement design to the greatest extent, so as to put forward the design process and method to improve the innovation ability of logo design. According to the research, the classification accuracy rate of the algorithm proposed in this paper is 91.5%, and the recognition rate of various defects is also above 95%. In addition, in design practice, the stability of design proposals should be monitored through multiple search methods using trademark search tools. If a high similarity is found in the search results, the design direction should be adjusted in time until the final design scheme is determined. [ABSTRACT FROM AUTHOR]

The research on emergency response systems usually only considers the role of professional rescuers in emergency rescue or the activities taken by the victims in the process of self-rescue, and the joint research of the victims and rescuers in the same environment is relatively few. Multiagent modeling technology is a promising tool for simulating natural disaster emergency response systems. Based on the background of the earthquake rescue operation, this paper studies the related contents of the cooperative emergency response system of disaster victims and rescuers by using the modeling and simulation method of the multiagent. On the premise of making full use of the victims' ability to obtain information and move, it is proposed that the rescuers and the victims move together to the cluster point to complete the treatment to reduce the time wasted by the rescuers moving among the victims. This paper simulates different degrees of disaster through many experiments and simulates the influence of the relative speed of victims and rescuers by changing the moving speed of victims. It can be found that when there are many disaster victims, the collective rescue operation can reduce the overall emergency response time; when the movement speed of the victims is lower than that of the rescuers, the effect of the clustered rescue is similar to that of the victims waiting for rescue. When the movement speed of the victims is similar to that of the rescuers, the clustered emergency response is better than that of the victims waiting. [ABSTRACT FROM AUTHOR]

Job insecurity reflects the desire and expectation of organizational managers for employees' exhibition of innovative behavior. Ubiquitous and inevitable, it has gradually become a concern psychological problem for job survival and stability. As a key driver of innovation, employee innovation depends heavily on knowledge workers, who are best able to spot problems and identify and capture opportunities. Based upon the transactional theory of stress and coping (TTSC), this paper discusses the influencing mechanism of knowledge workers' job insecurity and innovative behavior in enterprises, emphatically analyzes the mediating effects of two coping strategies, i.e., proactive work behavior and working withdrawal behavior, and verifies the moderating effect of organizational climate for innovation. With the data from 665 questionnaires of enterprise knowledge workers, this paper shows that job insecurity can influence knowledge workers' innovative behavior either positively through proactive work behavior or negatively through working withdrawal behavior, thus forming a dual-channel effect model of influencing their innovative behavior, and that organizational climate for innovation has a moderating effect on the relationship between job insecurity and proactive work behavior/working withdrawal behavior. The organizational innovation climate played a moderating role between job insecurity and proactive work behavior and work withdrawal behavior and detected the value of the boundary where the organizational innovation climate played a mediating role. [ABSTRACT FROM AUTHOR]

In 2019, the Chinese government has put forward comprehensive plan for reducing social insurance premium rate, which will affect the measurement of the pension security level. In order to evaluate the pension level, this paper uses CHIPs data from 1988 to 2018 to calculate "empirical" pension replacement rate by "empirical" method based on different wage calibers. The result shows that the pension replacement rate and income replacement rate of urban employees have gradually declined in the past 30 years. The pension level of nonprivate employees is lower than that of insured employees, and that of insured employees is lower than that of full-scale employees. The pension level of male, high-income groups, the older generation, organs, and institutions is much higher than that of female, low-income groups, the younger generation, and enterprises relatively. Compared with other countries, the pension replacement rate of urban employees in China is not low, but the income replacement rate is relatively low. This paper makes an in-depth analysis of the actual pension level under the new policy. As a result, it is necessary to vigorously develop multilevel and multipillar pension system such as enterprise annuity, occupational annuity, and commercial pension insurance, so as to improve the pension level of urban employees. [ABSTRACT FROM AUTHOR]

In the current complex global economic background, international capital flows are becoming more frequent. Based on this, this paper takes international portfolio investment as the research object and empirically tests the causal relationship and control channel between international portfolio flows and macrofinancial risk in emerging economies. It selects the panel data of emerging economies from 2001 to 2020, constructs macrofinancial risk indicators by using contingent claim analysis and the entropy-based TOPSIS method, tests the effect of international portfolio flows on macrofinancial risk by using the panel distributed lag regression model, and explores the management effect of foreign exchange reserves and capital controls on the risk effect by using the panel threshold regression model. The results show that long-term international portfolio flows help reduce macrofinancial risk, but short-term capital flows appear to increase macrofinancial risk. In addition, both foreign exchange reserves and capital controls effectively reduce the risk effect of portfolio flows. However, when considering different types of portfolios, we find that foreign exchange reserves do not effectively control the risk effect of equity securities flows, while stricter capital controls do. This paper argues that emerging economies should be more open to international long-term portfolio flows, focus on the monitoring of short-term portfolio capital flows and equity securities flows, and coordinate the use of foreign exchange reserves and capital control instruments to manage the risk effects of portfolio flows. This paper verifies the risk effect of international portfolio investment flows through empirical analysis, tests the effectiveness of foreign exchange reserves and capital controls, and provides a decision-making reference for emerging economies to timely identify, effectively manage, and prevent the risk effect of international capital flows. [ABSTRACT FROM AUTHOR]

Although the port industry is very important in the Korean economy, there are few literature studies that shed light on the macroeconomic implications of the business cycles in this industry. This paper examines the roles played by foreign economic factors in the business cycle in the Korean port industry. Specifically, it aims to estimate the impulse response of the seaborne freight volume in the port industry due to the shocks of the foreign economy and analyze the contributions of each shock considered on the variation in the freight volume. The structural FAVAR (SFAVAR) model was employed to extract the unobserved foreign economic factors. This paper estimates the four foreign economic factors and the parameters of the model using the one-step Bayesian Gibbs sampling method. The findings of this study show that foreign economic activity statistically affects the freight volume of the Korean ports. Specifically, the shocks to the foreign real economic activity increased freight transportation for nearly one year. Following the world inflation shocks, the freight transportation was enhanced. However, this impact disappeared after a year. Similarly, the rise in global liquidity was shown to encourage transportation activity; nevertheless, this activity declined after five quarters. Moreover, the increase in the world interest rates exerted a negative effect on the volume of transportation. Furthermore, the variance decomposition analysis shows that 49.2% of the variation in the transportation volume could be attributed to foreign economic activity. This analysis can contribute to drawing useful implications in establishing the port industry policy in response to the change in the economic environment such as the foreign economy. [ABSTRACT FROM AUTHOR]

The stock market is a real and continuously evolving extremely complex dynamic system. This paper analyzes the change of stock market efficiency from the perspective of dynamic evolution, and the recursive graph method is used to obtain the dynamic characteristics of stock price time series. For the sharp rise and fall of stock prices, this paper uses the heuristic segmentation algorithm of nonlinear time series mutation detection to study the detection of market dynamics characteristics before the stock market crash. Based on the above research results, this paper studies the dynamic evolution of financial markets and the construction of a complex network of dynamic characteristics between financial markets. The simulation results show that there are typical characteristics of small world network in stock market complex network, the stock market complex network shows stronger synchronization ability, and the transmission range of information between the stock markets in the complex network is significantly expanded. [ABSTRACT FROM AUTHOR]

This paper uses data mining technology to mathematically model the training movements of tennis players, establish a three-dimensional data information database of athletes utilizing depth imaging, analyze the data with data mining algorithms, and derive the results after comparative evaluation and analysis with a database of movement characteristics of tennis dribblers. This paper uses video observation and mathematical modeling to construct a tennis player training action evaluation model, which provides a reference basis for tennis players to improve and enhance their tactical level; it can also provide a reference for the development of sports training special theory of tennis projects and enrich the tactical diagnosis method of tennis matches. To improve the accuracy of 3D human pose estimation, this paper adopts a 3D skeleton point extraction method based on RGBD images; for the action alignment problem, this paper uses a dynamic time warping (DTW) algorithm; for the similarity measure, this paper gives a Pearson correlation coefficient method based on the joint point features of human parts. This paper aims to conduct a systematic theoretical analysis of tennis players' training movements based on theories and methods such as system science theory and social network analysis. On this basis, the characteristics of tennis training technology development are analyzed from a combination of qualitative and quantitative perspectives, while the development of tennis player training is explored based on tracking observations of tennis player movement training, and finally, the attack and service characteristics of tennis training are analyzed to better provide some reference for the sustainable development of tennis. [ABSTRACT FROM AUTHOR]

Coal-resource-based cities, as one of the important types of typical resource-based cities in China, have strong characteristics of instability, sensitivity, and fragility, exhibiting a series of vulnerability features of the human-land system. Previous studies have lacked a deeper investigation into the vulnerability of such cities from the perspective of coupling feedback mechanisms among various elements or subsystems. This paper adopts Bohle et al.'s "Dual Structure Model" of vulnerability to establish an indicator system for vulnerability warning in coal-resource-based cities. Using Fushun City as a sample, a dynamic simulation model of vulnerability in coal-resource-based cities is constructed based on system dynamics for warning simulation calculations, analyzing the evolution trend of vulnerability in Fushun City from 2010 to 2022. The results show the following: (1) from 2010 to 2022, the urban vulnerability of Fushun City transitioned from a medium warning level to a relatively safe level, showing a trend of annual reduction and improvement, undergoing three development stages of significant reduction, fluctuation stabilization, and slight rebound. (2) Due to the causal relationships among various elements within the vulnerability subsystems of Fushun City, differences exist in the contribution levels of vulnerability subsystems during the period 2010–2022, under the combined effects of sensitivity and adaptability factors. The contribution rate of the natural subsystem was the highest from 2010 to 2014, while, from 2016 to 2019, urban vulnerability began to shift towards an economically and socially dominant type. Influenced by the pandemic, Fushun City's overall vulnerability has shown an upward trend since 2020 compared to the previous stage. Finally, specific policy suggestions are proposed for Fushun City to cope with vulnerability changes based on the analysis results, providing a theoretical basis for achieving sustainable development in such coal-resource-based cities. [ABSTRACT FROM AUTHOR]

Nowadays, construction industries are using flyash as a potential alternative for cement. Due to its improved mechanical properties, ecofriendly nature, and low cost, geopolymer technology makes use of flyash as a promising future binder material. In this paper, 7 factors such as liquid-to-flyash ratio, silicate-to-hydroxide ratio, curing temperature, curing period, concentration of NaOH (molarity), rest period prior to curing, and dosage of superplasticizer that influence the compressive strength and temperature drop are screened using the Plackett–Burman method for optimization. Here, compressive strength and temperature drop are taken as the main indices of response to analyze the parameters. The significant variables determined from the Plackett–Burman design are further considered for the process of optimization using the response surface methodology. From the analysis, the optimum values of 0.4071 liquid-to-flyash ratio, 2.5 silicate-to-hydroxide ratio, and 6 hours curing period give maximum compressive strength and temperature drop of 28.87 MPa and 5.3°C under the optimized medium in the validation experiment which varies by only 3.93% and 1.85% from the observed value of 27.20 MPa and 5.4°C. [ABSTRACT FROM AUTHOR]

In this paper, a fractional model in the Caputo sense is used to characterize the dynamics of HPV with cervical cancer. Generalized mean value theorem has been used to examine whether the infection model has a unique positive solution. The model has two equilibrium points: the disease-free point and the endemic point. The examination of the system's local and global stability is provided in terms of the basic reproductive number R p ° . The global stability analysis has been carried out using an appropriate Lyapunov function and the LaSalle invariant principle. The results demonstrate that in the infection model, if R p ° < 1 , then the solution converges to the disease-free equilibrium, which is both locally and globally asymptotically stable. Whilst R p ° > 1 , the endemic equilibrium is considered to exist. Simulations are implemented via a finite difference method with Grünwald-Letnikov discretization approach for Caputo derivative operator to define how changes in parameters impact the dynamic behavior of the system using Matlab. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic behavior of a particular category of discrete predator-prey system that feature both fear effect and refuge, using both analytical and numerical methods. The critical coefficients and properties of bifurcating periodic solutions for Flip and Hopf bifurcations are computed using the center manifold theorem and bifurcation theory. Additionally, numerical simulations are employed to illustrate the bifurcation phenomenon and chaos characteristics. The results demonstrate that period-doubling and Hopf bifurcations are two typical routes to generate chaos, as evidenced by the calculation of the maximum Lyapunov exponents near the critical bifurcation points. Finally, a feedback control method is suggested, utilizing feedback of system states and perturbation of feedback parameters, to efficiently manage the bifurcations and chaotic attractors of the discrete predator-prey model. [ABSTRACT FROM AUTHOR]

In this paper, the limit cycles and local bifurcation of critical periods for a class of switching Z 2 equivariant quartic system with two symmetric singularities are investigated. First, through the computation of Lyapunov constants, the conditions of the two singularities to become the centers are determined. Then, we prove that there are at most 18 limit cycles with a distribution pattern of 9-9 around the two symmetric singular points of the system. Numerical simulation is conducted to validate the obtained results. Furthermore, by calculating the period constants, we determine the conditions for the critical point to be a weak center of finite order. Finally, the number of local critical periods that bifurcate from the equilibrium point under the center conditions is discussed. This study presents the first example of a quartic switching smooth system with 18 limit cycles and 4 local critical periods bifurcating from two symmetric singular points. [ABSTRACT FROM AUTHOR]

Presently, most of the existing rumor detection methods focus on learning and integrating various features for detection, but due to the complexity of the language, these models often rarely consider the relationship between the parts of speech. For the first time, this paper integrated a knowledge graphs and graph attention networks to solve this problem through attention mechanisms. A knowledge graphs can be the most effective and intuitive expression of relationships between entities, providing problem analysis from the perspective of "relationships". This paper used knowledge graphs to enhance topics and learn the text features by using self-attention. Furthermore, this paper defined a common dependent tree structure, and then the ordinary dependency trees were reshaped to make it generate a motif-dependent tree. A graph attention network was adopted to collect feature representations derived from the corresponding syntax-dependent tree production. The attention mechanism was an allocation mechanism of weight parameters that could help the model capture important information. Rumors were then detected accordingly by using the attention mechanism to combine text representations learned from self-attention and graph representations learned from the graph attention network. Finally, numerous experiments were performed on the standard dataset Twitter, and the proposed model here had achieved a 7.7% improved accuracy rate compared with the benchmark model. [ABSTRACT FROM AUTHOR]

Based on the actor network theory, this paper collects 20 representative corporate public opinion data through microblogs, uses the qualitative comparative analysis method to analyze these typical cases from the configuration perspective, identifies the elements and condition combination paths of corporate online public opinion hotness generation from four dimensions: enterprises, netizens, media, and government, and explores the generation mechanism of corporate network public opinion hotness. The results show three modes with high hotness of corporate network public opinion generation, which are internal and external linkage, internal leading, and external restriction. The public opinion hotness generation modes of consumers' rights and interests and managers' problems are different. Therefore, different measures should be taken to reduce the hotness of negative public opinion for different causes of corporate public opinion. Based on this, this paper puts forward some guidance suggestions, including strengthening the identification and contact with opinion leaders, strengthening the cooperation with the government and authoritative media, and strengthening the feedback response level of corporate network public opinion. This study helps to prevent and resolve public opinion crisis and provides reference for corporate public opinion governance. [ABSTRACT FROM AUTHOR]

The "innovation-driven" development approach plays a crucial role in transforming and developing current China's national economy. Many innovation-driven mergers and acquisitions (M&As) emerge in the M&As activities of firms, and the acquiring firm's business strategy of conducting innovation-driven M&As has drawn significant attention. To study the impact of business strategy on innovation-driven M&As, this paper adopts the probit model to conduct logistic regression analysis on the 223 M&As data samples, exploring which business strategy is inclined to perform innovation-driven M&As. The results show that prospective firms are more likely to conduct innovation-driven M&As. Besides, the firms that conduct prospective business strategies are more likely to have a higher innovation level than firms operating defensive business strategies. The innovation level plays the role of a mediator variable in the model of business strategies influencing innovation-driven M&As. This paper analyzes the innovation-driven motivation from the perspective of business strategy, enriching the research of M&A and offering a method to predict the possibility of innovation-driven M&A by measuring business strategy. [ABSTRACT FROM AUTHOR]

In the digital economy era, knowledge platforms have both the functions of knowledge collaboration and social media. At the same time, how to promote knowledge collaboration through platform empowerment is getting more and more attention. Since there are few types of research on how to realize the micromechanism of platform empowerment, the purpose of this paper is to take knowledge platforms as an example to study the conceptual system of platform affordances based on the social-technical perspective. Through the theoretical integration of technological empowerment and authorization empowerment, this paper provides new perspectives and future themes for explaining the platform empowerment mechanism of knowledge collaboration. As for the method, the deductive research approach is adopted in this paper. First, through the critical literature review, the gaps in platform empowerment research have been identified. Second, from the analysis of the characteristics of knowledge platforms such as Wukong Q&A and Zhihu, the relationship between platform affordances, platform organizational characteristics, and customer needs has been explored. In the final, according to knowledge platform characteristics, the conceptual system of platform affordances has been deduced. The result shows that through integrating organizational theory, knowledge management theory, and platform ecological viewpoints, the main components of the affordances of knowledge platforms have been summarized. In addition, the relevance of those components to the functions, interfaces and rules of the platform system has been illustrated, and the corresponding relationship between the affordances of the platform and the main components of authorization empowerment has been established. With regard to the implication of this study, it establishes the theoretical connection between technological empowerment and authorization empowerment and provides a more intuitive and operable method for platform empowerment of knowledge collaboration through the perspective of social-technical interaction. This paper emphasizes that starting from the mission of the platform, the stickiness of the platform can be enhanced by building platform affordances. In addition, extensive development ideas that purely pursue Internet traffic and capital need to be avoided, which is conducive to the high-quality development of knowledge platforms and the digital economy. Furthermore, this paper calls for more research on the affordances and empowerment mechanism of the platform to provide theoretical guidance for the highly unified practice of platform organizational characteristics, platform system characteristics, and target customer needs, so as to develop a more active and meaningful platform knowledge management field. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has received much attention in the domain of railway traffic planning and management (TPM) from academia and industries. While many promising applications have been reported, there remains a lack of detailed review of the many AI models/algorithms and their uses and adaptations in rail TPM. To fill this gap, this systematic literature review conducts, reports, and synthesizes the state-of-the-art of AI applied in railway TPM from four perspectives, i.e., the intersection between AI research fields (e.g., expert systems, data mining, and adversarial search) and rail TPM, the intersection between AI techniques (e.g., evolutionary computing and machine learning) and rail TPM, the intersection between AI applications (e.g., operations research, scheduling, and planning) and rail TPM, and the intersection between AI related disciplines (e.g., big data analytics and digital twins) and rail TPM. The study evaluates 95 research papers published during 1970–2022. Accordingly, a comprehensive synthesis of each intersection between AI and rail TPM is presented, and the practical roadmap for application of AI in rail TPM is proposed. Furthermore, the study identifies the research gaps and areas that need more investigation. The contribution helps researchers and practitioners to get a better understanding of the status quo of research stream, research development trends, and challenges for further related study. [ABSTRACT FROM AUTHOR]

Edge networking brings computation and data storage as close to the point of request as possible. Various intelligent devices are connected to the edge nodes where traffic packets flow. Traffic classification tasks are thought to be a keystone for network management; researchers can analyze packets captured to understand the traffic as it hits their network. However, the existing traffic classification framework needs to conduct a unified analysis, which leads to the huge bandwidth resources required in the process of transferring all captured packet files to train a global classifier. In this paper, a semisupervised graph neural network traffic classifier is proposed for cloud-edge architecture so that cloud servers and edge nodes could cooperate to perform the traffic classification tasks in order to deliver low latency and save bandwidth on the edge nodes. To preserve the structural information and interrelationships conveyed in packets within a session, we transform traffic sessions into graphs. We segment the frequently combined consecutive packets into granules, which are later transformed into the nodes in graphs. Edges could extract the adjacency of the granules in the sessions; the edge node side then selects the highly representative samples and sends them to the cloud server; the server side uses graph neural networks to perform semisupervised classification tasks on the selected training set. Our method has been trained and tested on several datasets, such as the VPN-nonVPN dataset, and the experimental results show good performance on accuracy, recall, and F-score. [ABSTRACT FROM AUTHOR]

Poverty reduction is an important driving force for the global realization of the United Nations 2030 Sustainable Development Goals and the building of a global community with a shared future for mankind. This paper takes the Belt and Road Initiative (BRI) as a quasi-natural experiment. Based on the panel data of 134 countries in the world from 2000 to 2018, this paper uses the difference-in-difference (DID) model to examine the impact of the BRI on poverty reduction in countries along the route and to study its internal mechanism from the dual perspectives of trade openness and investment openness. The results show that (1) the BRI can significantly reduce the incidence of poverty with the impact coefficient stable at −0.26, and the empirical conclusion has passed the parallel test, placebo test, and instrumental variable test; (2) the mediating effect test model shows that the BRI can achieve poverty reduction through the dual openness of trade and investment, and the intermediary effect of trade openness is greater than investment openness; and (3) from the perspective of heterogeneity analysis, geographically, the BRI has a slightly higher role in promoting poverty reduction in landlocked countries than in coastal countries. In terms of economic location, the effect of poverty reduction has a certain "pro-poverty" characteristic, that is, the BRI promotes poverty reduction in low- and middle-income countries far more than other types of income countries. Therefore, we believe that the continuous deepening of the BRI high-quality construction and the strengthening of cooperation among countries along the route will play a key role in promoting the international cycle of trade, investment, and other factors, as well as the cause of poverty reduction in the region and the world. [ABSTRACT FROM AUTHOR]

Innovation in the business model (BM) may be irreversible and therefore entails more significant risk and ambiguity compared to product, service, or process innovation. This paper focused on exploring the role of organizational learning in mediating the relationship between business model design and innovation performance using hierarchical hybridized linear regression analysis (HHLRA). Furthermore, this paper shows that organizational learning is based on variables that mediate the relationship between training and performance and improve performance through its positive effect on organizational learning. Furthermore, the study examines the multi-dimensional and contingent progressive impact on the corporate performance of organizational training through innovative conjunctive roles. However, this study determines that both organizational learning capabilities (OLC) and organization innovativeness (OI) have a positive effect on organizational performance (OP). Besides, organizational innovativeness mediates the relationship between OLC and OI. Finally, the findings suggest that managers should improve organizational learning capabilities and improve innovation performance to enhance positive entrepreneurial orientation performance connections. [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]

When the government decides to use the public-private partnership (PPP) in projects, such as infrastructure construction, selecting a private-sector partner that meets the project's needs is one of the key factors for successful implementation, but this is ignored in existing research. On this basis, this paper proposes a GRA-VIKOR method based on the combined weight of the improved CRITIC-entropy weight method (EWM). The traditional CRITIC method is improved by combining it with EWM. The combined weights are measured, which reduces the limitations of the single weight. Considering the inherent correlation of evaluation indicators, the VIKOR method is combined with the grey relational analysis (GRA), which makes the results of the selection assessment more reasonable. This paper carries out a case study of the first inland navigation PPP project in China. Through preliminary tracking studies, it tests the effectiveness of the proposed method, the superiority of which is demonstrated by comparing the evaluation results with those of the traditional GRA methods, VIKOR, and TOPSIS. [ABSTRACT FROM AUTHOR]

In order to promote the citizenship of China's rural floating population and improve the level of new urbanization, as an important source of property income for rural floating population, the transfer of agricultural land or not has an important impact on whether they choose to return to their hometowns or settle in cities. Based on data from the 2017 China Migrants Dynamic Survey (CMDS), this paper explores the mechanism of the impact of agricultural land transfer on the urban settlement intention of rural floating population by constructing a structural equation modeling and bootstrap test. The results show that agricultural land transfer has a significant positive impact on the urban settlement intention of rural floating population, with occupational prestige and identity recognition playing a part in mediating the effect. Actively promoting the identification and orderly transfer of agricultural land rights, improving the quality of urban employment for rural floating population by strengthening vocational skills training, and accelerating the equalization of urban public services to enhance the identity recognition of rural floating population are important in promoting the orderly and effective integration of rural floating population into cities and their genuine citizenship. [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]

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 context of digital economy, the international trade mode has undergone profound changes, so digital transformation has become the key to the sustainable development of foreign trade enterprises. In this paper, by collecting the data of 27 foreign trade enterprises listed in Shanghai and Shenzhen A shares from 2010 to 2020 and adopting the method of full text identification of enterprise comprehensive financial reports to quantify the intensity of enterprise digital transformation, the influence of digital transformation of foreign trade enterprises on the main business performance and the effect of two mediating variables of internal control and innovation ability of enterprises were studied. The result shows that the digital transformation of foreign trade enterprises has a significant role in promoting their main business performance. From the mechanism of action, digital transformation promotes the overall improvement of the main business performance of enterprises by improving the internal management of enterprises and enhancing the mediating role of enterprise innovation ability. Finally, from the perspectives of government and enterprises, some suggestions were put forward for foreign trade enterprises to choose the development path of digital transformation. [ABSTRACT FROM AUTHOR]