Customization, as an important customer value strategy for corporate development, is of great significance to the improvement of customer satisfaction and the increase of firm revenue. As digital technologies such as artificial intelligence, big data, and cloud computing develop quickly, firms' customization practices and related academic research meet great opportunities and challenges. Based on this background, through systematic and comprehensive analysis of Chinese and English literatures on customization, this paper clarifies and analyses the definition and patterns of customization, the key influencing factors of customization capabilities, the performance outcomes and the corresponding theoretical mechanisms of customization strategy, and the boundary conditions of the effectiveness of customization strategy. On this basis, this paper then summaries an integrated research framework for customization literature and proposes future research directions for customization from the aspects of patterns, performance outcomes and their mechanism, influencing factors, and the new forms of customer customization in the digital environment, to provide a reference for the development of more in-depth and systematic customization theory, and to bring inspiration for understanding and guiding firms' customization practice.

Based on the dataset of branches of China's banking institutions, this paper studies the impact of inter-regional banking integration on economic synchronization between regions in China. We find that the rise of inter-regional banking integration significantly narrows the gaps of economic growth between regions and promotes the economic synchronization between regions while major four state-owned commercial banks play a primary role. After addressing the endogeneity concern by using the instrumental variable based on city commercial banks' restructuring and mergers over years, the benchmark conclusion remains robust. When employing earthquakes and COVID-19 outbreak as risk shocks, this paper finds that China's banking system, especially major four state-owned commercial banks, can significantly share the negative shocks of disasters on disaster-stricken areas' economy. This paper deepens the research on the role of the banking system in China's macro-economy, and explains the influence of the banking system on economic synchronization between regions from the perspective of risk sharing. This paper provides evidence for the financial support for the real economy and regional economic synchronization in China.

This paper takes the outbreak of the COVID-19 at the beginning of 2020 as a quasi-natural experiment to study the impact of public health emergency on corporate cash holding decisions using a difference-in-difference model. We find that firms severely affected by the epidemic have significantly increased their cash holdings compared to other firms. The increased cash holdings mainly come from the reduction of cash flow expenses from operating activities and financing activities. In the process of adjusting cash holding decisions, firms have shown strong preventive motive, holding more cash to prevent future cash flow shortages from affecting the normal production and operation, while the agency motive for cash holdings is not obvious. Heterogeneity analysis shows that management's behavior of increasing cash holdings during the epidemic period is manifested in both state-owned enterprises and non-state-owned enterprises, and is more obvious in regions with lower marketization level. Further research finds that the epidemic doesn't cause pessimism among managers, but they express concerns about the uncertainty of firms' future development. This uncertainty mood plays an important role in the process of public health emergency affecting firm cash holdings. Finally, research shows that the behavior of firms maintaining higher cash holdings can cause more positive market reaction.

Carbon emission trading scheme is an important policy tool to achieve the carbon peak and neutrality targets, and it is of great practical significance to evaluate the impact of the policy on the economy, society and the environment. This study uses the data from 30 provinces in China from 2009 to 2017 to construct the index of sustainable economic welfare, and develops the difference-in-differences model to evaluate the impact of China's carbon emission trading scheme on sustainable economic welfare. The results show that:1) The carbon emission trading scheme has significantly promoted the growth of sustainable economic welfare in the pilot areas. Compared with non-pilot areas, the sustainable economic welfare of the pilot areas has increased by 1,220 yuan per person. 2) The impact of carbon emission trading scheme on the sustainable economic welfare of the eastern pilot area is relatively the largest, which is 2,020 yuan per person. At the same time, with the increase in clean energy consumption and R&D investment in the eastern region, the carbon emission trading scheme can significantly promote the improvement of sustainable economic welfare in the eastern pilot areas. 3) The carbon emission trading scheme has a certain lag effect on sustainable economic welfare, and the lag period is about two years.

Based on the data of China's high-tech firm from 2010 to 2019, we measure the innovation strategy implemented by firm according to the relative proportion between independent innovation and technology import, and empirically test the impact of performance-vested equity incentives on firm innovation strategy. The results show that the more stringent the performance-vesting conditions are, the more firm tend to choose the technology import strategy. The study on the interaction of contractual terms of equity incentives found that the greater the intensity of equity incentives, the shorter the exercise validity and the listed firm that grant restricted stock can play a better role in promoting the technology import strategy. Further research points out that the impact of performance-vested equity incentives on firm innovation strategy is stronger in firm with high level of information asymmetry, serious agency problem and high separation of two rights. This paper expands the optimal contract theory, analyzes the internal logic of senior management choosing different innovation strategies, enriches the relevant literature on the economic consequences of performance-vested equity incentives, and also provides policy suggestions and practical enlightenment for high-tech firm to optimize equity incentives and drive independent innovation.

Under global supply chain system, the global economic and political situation becomes more complex, which significantly increases the supply disruption possibility of key components such as chips. How to use local components to substitute imported components and adjust the supply chain structure to deal with the uncertainty, and how to enhance the robustness of supply chain have become an important research question. This paper captures the crucial factors of the supply chain structure adjustment and develops a game theory model compromising a cross-border supplier, a local supply, and two competing brands. Considering the possibility of supply disruption for the cross-border supplier, whether the Chinese brand has incentives to cooperate with the local supplier, and adopts a dual-sourcing strategy to ensure stable supply. The results show that, the order allocation proportion and the disruption probability of the cross-border supply can significantly affect the sourcing strategy preference of the Chinese brand. If the order allocation proportion is relatively even, the dispersion of orders induces the two upstream suppliers to decide higher wholesale prices, which increases the sourcing cost of the Chinese brand and results in the single-sourcing strategy is better. Further research finds that, other supply chain players' preferences of the Chinese brand's dual-sourcing strategy mainly depend on the cross-border disruption probability.

With the prosperity of e-commerce, online reviews have become an important information source for both the online consumers and vendors in their decision making. However, with the marvelous reviews on the e-commerce platform, it is hard for consumers and vendors to acquire valuable information to support their decision making. This paper proposes a novel topic model called help-LDA by extending the classic LDA model with considering the helpfulness of online reviews. On the one hand, the proposed help-LDA model can extract helpful topics from online reviews. On the other hand, the proposed help-LDA model can be used for online review representation with goal of predicting the helpfulness of online reviews. With the real data collected from Dianping.com, we conduct extensive experiments to compare the proposed help-LDA model and the baseline models in topic modeling and helpfulness prediction of online reviews. The experimental results demonstrate the superiority of the proposed help-LDA model over the baseline models.

This paper analyzes the theoretical mechanism of urbanization affecting high-quality economic development using an urban-rural dual general equilibrium model including environmental factors, and empirically tests the actual effect of urbanization affecting high-quality economic development through industrial structure upgrading based on panel data of cities above the prefecture level in China. The results show that urbanization has a positive role in high-quality economic development represented by pollutant emissions per unit of GDP, and industrial structure upgrading has a significant mediation effect. Urbanization of eastern cities mainly inhibits environmental pollution emissions through mediation effect of industrial structure upgrading; urbanization of central and western cities has both direct and indirect effects on environmental pollutant emissions. Urbanization of provincial capital cities and non-provincial capital cities has a partial mediating effect on environmental pollutant emissions. The promotion effect of urbanization of provincial capital cities on high-quality economic development is significantly higher than that of non-provincial capital cities. In the future, it is necessary to continue to promote new urbanization, rationally optimize industrial structure, enhance the synergy between urbanization and industrial structure, and promote high-quality economic development.

With the release of China's "dual carbon goals", individual investors' green concerns gradually cause strengthened pressure on listed companies. Using the data of investor interaction platforms of the Shanghai Stock Exchange and Shenzhen Stock Exchange, this paper constructs green concern indicators based on a sample of 2048 listed companies and empirically reveals that individual investors' green concerns can promote green innovation in terms of quantity and quality. This influence is more pronounced in non-heavily polluting industries and those with no pollution charges and fewer environmental protection subsidies, individual investors' green concerns play a supplement role in the environmental regulation policies. Improving the construction of the green financial system and guiding individual investors' green investment concept can promote listed companies' green innovation behaviors.

Do environment pollution and resultant costs of the environmental regulation help to promote corporate green innovation? This is an important issue of common concern from all sections of society. Using A-share industrial listed firms from 2014-2018, this study examines whether and how air pollution affects corporate green innovation. Our results show that air pollution significantly increases the level of corporate green innovation in near future. On average, 1% increase in air pollution in a focal city will lead to 0.75% increase in green innovation in focal firms, displaying statistic and economic significance. Further mechanism analyses reveal that local government regulation and public supervision are partial intermediary factors of the associtation between air pollution and corporate green innovation. Moreover, the positive association is found to be more pronounced in firms having higher media coverage and lower financing constraints. In addition, we find that green innovation will significantly improve corporate market value. Overall, this study can enrich the literature on the microeconomic consequences of air pollution and the determinants of corporate green innovation, and also provide theoretical support and empirical evidence for the government making policies for pollution prevention.

In the cross-national supply chain network system, upstream and downstream enterprises inevitably face tariff policies in the transaction process. At the same time, the substitution of local products will also have an impact on the tariff implementation and the decision-making of all parties. Considering product substitutability, this paper constructs a profit maximization model of multinational supply chain members affected by tariff policy under random demand, and using the complementary system, the equilibrium decision of transnational supply chain network is obtained. The results show that: 1) As the country increases the tariffs on imported products, the profits of the enterprises producing and trading substitute products will increase; 2) When the demand fluctuation of a country's imported products increases, the trading volume of the country's local products will reduce, and both manufacturers' profit and dealers' expected profit will decrease; 3) If the manufacturer improves the substitution degree of its products for imported products, the trading volume of products will increase, which will also increase the profit of the manufacturer and the expected profit of dealers dealing with it, the implementation of national tariff policy will amplify the positive impact of local products on the improvement of the substitution degree of imported products.

Under the dual background of transformation and upgrading of Chinese economy and the new round of technological revolution, we select the quarterly data of Shanghai and Shenzhen A shares from 2011 to 2019 to investigate whether there is a substitution effect between labor factor and technology factor based on the micro perspective, and then provide an explanation for the labor leverage discount in China. We find that: 1) There is a significant substitution effect between the firm's labor factor and technology factor, and the degree of substitution is more obvious in the high-tech industry, state-owned firms and firms with low financing constraints; 2) The performance of this effect is different in different economic conditions: The substitution effect is stronger during the economic downturn, which indicates that the best time for firm to make technology substitution decision is economic recession; 3) Labor-technology substitution can significantly weaken the negative effect of labor leverage on stock returns. This result is still robust after replacing the labor technology-substitution variable with total factor productivity and labor productivity, which can also directly reflect the the firm's technical level. The result prove that the firm's technical level has a significant inhibitory effect on labor leverage discount, indicating that labor factor can effectively promote the positive effect of low-level labor leverage on stock returns. Related results can provide ideas for firms to take effective measures to cope with the rising labor costs and the shortage of labor supply caused by the aging population. At the same time, those results also provide empirical support for the in-depth understanding of the pricing mechanism of labor leverage in Chinese A-share market, the rational allocation of production factor, the transformation of the firm's growth mode and the optimization and upgrading of the firm's production structure.

Traditional hotel dynamic pricing research always considers improving demand forecasting methods or considers that the demand environment is known, while the demand distribution in real life is usually unknown. In this paper, we established a multi-period dynamic pricing model for hotel rooms based on Markov decision process with unknown demand distribution, and used the reinforcement learning method to propose improved algorithms based on SARSA(λ) to solve the dynamic pricing model of rooms. In order to improve the solving ability and convergence speed of the algorithm, we proposed the ε-SARSA(λ) algorithm based on the improved ε-greedy strategy and the ISA-SARSA(λ) algorithm based on the improved simulated annealing strategy. Through numerical experiments, the revenue optimization results of the four algorithms, SARSA(λ), ε-SARSA(λ), SA-SARSA(λ) and ISA-SARSA(λ), were compared. The study results verify the effectiveness of improved algorithms and show that the ISA-SARSA(λ) algorithm has the best solution performance.

In perspective of tournament theory, this paper develops a principal-agent model with standard economic theory from the objective reality of congenital differences, to analyze the evolutional mechanism of unbalanced and inadequate development, and to design the policy logic of common prosperity. The main findings include the following. Firstly, the unbalanced and inadequate development will evolve in the trend of becoming serious without any policy regulation, which plays a negative role in common prosperity. Secondly, the preferential treatment of tournament should be applied to help the weak in the congenital disadvantageous position, but not fill in the congenital differences completely. Thirdly, the distribution mechanism based on the preferential treatment should be regulated to widen the allocation gap and increase the aggregate of tournament. Finally, the combined policies of preferential treatment and regulated distribution mechanism can resolve the problem of unbalanced and insufficient development simultaneously, and thereby promote the common prosperity.

Based on the newly constructed input-output model that distinguishes firm size categories (LMS model) and the structural decomposition analysis (SDA) method, this study quantitatively calculates the employment effects and determinants across three firm size categories in China's dual circulation, from the perspectives of "aggregate", "efficiency" and "increment". Empirical results show that:1) In 2007 and 2012, the employment generated by domestic demand across all firm size categories is higher than foreign demand both in total and per unit of domestic demand. 2) In respect of firm size categories, small and micro enterprises are the critical force in stimulating the employment generated by domestic demand; Meanwhile, the employment generated by per unit of final demand (both domestic demand and foreign demand) of small and micro enterprises has a more significant role in driving the employment than large and medium sized enterprises. 3) The change of the final demand scale is the key driving force for employment growth across all firm size categories. This paper demonstrates the practical significance of actively expanding domestic demand in promoting China's employment growth under the new development pattern of "dual circulation" from a quantitative perspective, and provides scientific support for formulating reasonable and effective employment policies.

This paper focuses on the factors influencing China's economic growth since the reform period based on the rent dissipation perspective. This paper consists of the following four parts. Firstly, Analysis based on different data sets shows that the China's rapid economic growth is related to the low level of development in 1978, which puts forward the difficulties of China's economic transition today. Secondly, after the identification of the four stages of development since the reform period, we analyze the reason of China's high economic growth. The core is the market-oriented institutional change, in which process the local government plays an important role. Our regression analysis based on provincial level data agrees with our theory hypothesis. But the trend is changing in recent years, which destroys the incentive compatibility of economic growth and fiscal interest of the local government. Thirdly, we put forward the difficulties that China will face in the process of reform. Reducing the monopoly rent both in product markets and factor markets is very important to further the market-oriented reform. Finally, the difficulty of furthering China's economic reform is concludingly emphasized and policy suggestions are put forward.

How to promote green transformation in social life and consumption is a key issue that governments should pay attention to and solve. Academics have paid extensive attention to the green transition of production mode. However, insufficient attention has been paid to the green transition of lifestyle and relevant empirical studies on the theme of green lifestyle are rare. Based on the panel data of 30 provinces in China from 2008 to 2019, this paper examines the impact of environmental regulations on residents' green lifestyles by constructing an econometric model and systematically explores the possible mechanism of environmental regulation on the green lifestyle. It is found that environmental regulation directly affects green lifestyles and can also positively affect residents' green lifestyles by improving the level of green technology innovation at the production level. In addition, green environmental awareness positively modifies the impact of environmental regulation intensity on green lifestyles. Heterogeneity analysis and robustness analysis further enrich the reliability of the conclusions and results of this study. This paper attempts to open the "black box" in which environmental regulations guide residents to form green lifestyles and provide a reference for government policy-making and guiding residents to form green lifestyles.

Predicting the mortality risk of patients in the intensive care unit (ICU) is considered to be one of the most important clinical prediction tasks. Accurately predicting the mortality risk of ICU patients can provide information about the patient's condition and facilitate timely measures to intervene. At the same time, it contributes to the effective allocation of limited medical resources. The condition of ICU patients is unstable and requires close monitoring. A large amount of clinical data is collected, recorded and saved by relevant monitoring equipment, which provides an important reference for relevant clinical decision-making of ICU patients. This paper takes the 30-day mortality risk prediction of ICU patients as the research objective, based on the medical information mart for intensive care III database, constructs a mortality risk prediction model for ICU patients, and analyzes related influencing factors to support medical care clinical decision in practice. First extract relevant patient data and perform preprocessing, and use multiple statistics to represent time series features. The hybrid optimization algorithm SAGA based on the fusion of genetic algorithm and simulated annealing algorithm is used for feature selection of the corresponding base classifier, and finally uses the ensemble learning method to integrate the classifiers in bagging based on the idea of information fusion, and uses real data to verify the model. And based on the accuracy rate, F₁ score and AUC three evaluation indicators, the model proposed in this article is compared with the classic mortality risk prediction model and showing better performance. Finally, based on information fusion, the important factors affecting the mortality risk of ICU patients are analyzed, and the central tendency statistics are more important, which provide reference for clinical decision-making.

The monetary policy framework of the People's Bank of China (PBOC) points out that it is necessary to guide the trend of market interest rates through the policy interest rates system. However, the negotiable certificate of deposit (NCD) interest rate often deviates greatly from the medium-term lending facility (MLF) interest rate. By constructing the policy interest rates transmission model under the control of credit interest rates, this paper puts forward three influential factors of spreads between market interest rates and policy interest rates: Shadow banking, inter-bank lending market financing difficulty, and legal deposit reserve ratio. Liquidity stratification is the external embodiment of the latter two factors, while shadow banking can be divided into traditional shadow banking and bank shadow with opposite roles. In terms of economic mechanism, traditional shadow banking and loans are independent and complementary, while bank shadow is an alternative loans for regulatory arbitrage of China's commercial banks. In addition, the overall liquidity abundance of the interbank market and the monetary policy transmission efficiency caused by the liquidity gap between financial institutions can explain the impact of liquidity stratification.

Motivated by the trend of overseas/cross-regional firms returning to domestic/local and the background of COVID-19 normalization, a sourcing decision model is proposed based on the cost-signal game under the demand uncertainty and forecast inaccuracy. We explore the trade-off between the efficient cross-regional sourcing and responsive local sourcing. The results show that the sourcing decision depends on the linkage performances of cost and information. Cross-regional sourcing always brings mighty cost performance, while the local sourcing can not always give full play to information performance advantage. Because if both firms choose local sourcing, the correlation effect between forecast information will hedge signal accuracy effect. Greater demand uncertainty and more accurate cross-regional sourcing forecast are driving films to return. Interestingly, this return may benefit all the firms, and break the Prisoner's Dilemma of symmetric cross-regional sourcing. The reason is that the returning can alleviate competition by inducing a new equilibrium sourcing structure. In response, this mixed equilibrium endows firms with “follower advantage” to realize local-Pareto improvement. With the increase of demand uncertainty and forecast inaccuracy, this mixed equilibrium will turn to the symmetric local sourcing, which temporarily reaches the overall Pareto-optimum. However, it will eventually fall into the Prisoner's Dilemma of lose-lose situation. In addition, it is also found that the poor local sourcing forecast will endow firms with ''mover advantage'', which will lead to the mover becoming better while the follower becoming worse.

As an open system, the stability of the financial system is affected by many markets. It is of great significance to study the infection mechanism between financial markets, or between financial departments and the other markets to maintain the stability of the financial system. This paper uses value at risk (VaR) to measure the tail risk, and investigates the risk contagion effects among China's crude oil, gold, real estate and four financial sectors, adopting the variance decomposition spillover index framework based on TVP-VAR model. The results indicate that: 1) the total spillover index (TSI) among the analyzed assets is as high as 81.37%, suggesting that tail loss is highly infectious in the financial system. 2) crude oil and bank are the largest net transmitter and the largest net receiver of the system shocks, respectively. The real estate industry has the largest positive net spillover effect on the banking sector. 3) Market volatility (VIX) and term spread (TS) have strong explanatory ability to the total spillover index (TSI). Investors and regulators should pay full attention to the important role of stock and bond markets in systemic risk early warning.

This paper constructs a series of new volatility prediction models by introducing the jump and jump intensity to the heterogeneous autoregressive (HAR) model and together considering a Markov regime switching model with a fixed transition probability matrix. To evaluate the predictability of the above prediction models on Chinese stock market volatility, popular statistical tests such as the model confidence set (MCS), out-of-sample R² test and direction-of-change test are used. The empirical results indicate that:1) compared with the benchmark, the regressions incorporate the regime switching can achieve superior forecasting performance; 2) the forecasting model with jump component, jump intensity and regime switching can outperform peers; 3) the MS-HAR-TJI model still can successfully predict the stock realized volatility during the COVID-19 and high volatility periods.

With the significant expansion of the breadth and depth of financial services for the real economy, the real sector's "be diverted out of the real economy" trend has become a structural contradiction, and the motivation and appropriateness behind the enterprise's financialization have become an urgent issue to be resolved. This paper starts from the enterprise's response to risk and uncertainty, as well as the financialization drive mechanism to pursue shareholder value, and constructs the optimization problem of the investment portfolio intending to minimize enterprise risk and maximize shareholder value, and then obtains the optimal allocation of financial assets under different objectives reflecting the relationship between enterprise risk, shareholder value and the non-linear relationship between the levels of enterprise financialization. On this basis, based on the fact that the enterprise's financialization driving mechanism reflects the characteristics of the financialization motivation, we start from the enterprise's asset allocation structure. Combined with the optimal allocation of financial assets under specific objectives, we propose the criteria for determining the enterprise's financialization motivation and the appropriate scope of the enterprise's financialization. Then, we selected the representative listed non-financial enterprises in China as a sample for empirical analysis:As for the identification of the motivation of financialization, this paper found that although the non-financial enterprise sector is still dominated by the "reservoir" motivation, the whole, the "investment substitution" motivation is more significant and cannot be ignored. There is heterogeneity among different industries and enterprises with different equity natures, among which the motivation of "investment substitution" in the wholesale and retail industry and real estate industry is significant, and the motivation of "investment substitution" in non-state-owned enterprises is significantly stronger than that in state-owned enterprises. Concerning the appropriateness of enterprise financialization, we find that the overall financialization appropriateness of the non-financial enterprise sector is low. Especially in the information technology industry and the power, gas, and water production and supply industry, the appropriateness of financialization is significantly lower than the average level, and the level of industry financialization is insufficient. In contrast, the wholesale, retail, and real estate industries have excessive financialization. The moderation of non-state-owned enterprises' financialization is significantly higher than that of state-owned enterprises, and there is also the phenomenon of excessive financialization. The conclusion of this paper provides guiding suggestions for financial investment decision-making and regulatory identification of enterprises.

Compared with point data, interval data can better grasp the internal structural characteristics of financial markets from a global perspective. However, the existing prediction research on interval data only focuses on the single prediction of error series or the preprocessing of original series, and the methods usually cannot fully extract the main features of interval stock price time series. Therefore, this paper proposes an error correction and decomposition method for forecast of interval-valued stock price time series. In view of the role of the error series in the combination forecasting model, we first use Ljung-Box test and machine learning model to test and modify the interval-valued error series generated by the original series. Then, bivariate empirical mode decomposition technique is used to decompose the corrected error series into multiple intrinsic mode functions (IMFs) and a residual. Then, a single machine learning model is used to predict each IMFs component and residual except IMF1 component. Finally, the predicted values of the original series and the error series are aggregated to reconstruct the predicted values of the interval stock price. Furthermore, on the basis of the proposed method, we build an interval-valued stock price forecasting model based on error correction and decomposition, and use real stock market data for empirical analysis. Experimental results show that the proposed method is superior to some traditional methods in prediction accuracy.

Based on the asymmetric jumps in asset prices and the rough in the asset volatility, this paper proposesthe the rough Heston model with asymmetric jump (rHeston-AEDJ) and derives the characteristic functions in the risk-neutral measure. Due to the non-Markovian and non-semimartingale of the model, it cannot be approximated using the Euler method. A hybrid simulation approach is used to approximate the rough Heston model with asymmetric jump and can solve the pricing problem of exotic options under rough volatility with poisson jump. Under the risk-neutral measure, the quasi-closed function of the Euclidean option is derived based on Fourier-SINC. The results of the empirical study show that there is a jump in the price of Shanghai Stock Exchange (SSE) 50 exchange traded fund (ETF) and the volatility Hurst index is much less than 1/2, i.e., there is roughness in the volatility. The pricing experiment of SSE 50 ETF options based on the quasi-closed function finds that the proposed rHeston-AEDJ model has good pricing accuracy both inside and outside the sample. The findings of the study are of great practical significance and application value to the pricing and accurate risk management of domestic and foreign option products.

Supply chain finance (SCF), as a systematic financial service for all member enterprises in the supply chain, focuses on solving the financing problems of small and medium-sized enterprises (SMEs). However, for a long time, the asymmetric information of relevant participants leads to frequent risks, and the risk assessment technology is relatively backward, which makes it difficult to effectively promote the service model. Therefore, the assessment of SCF risk has become a hot issue in the industry and academic circles. In this paper, the related documents of SCF risk assessment are taken as the research object, and knowledge is extracted from 152 Chinese documents and 61 English documents by using knowledge graph technology, and then visual analysis is carried out. On the one hand, the current research status of SCF risk assessment is explored, and it is found that the existing research has one-sided research perspective, single research object, small research data sample, and insufficient research model performance and interpretability. On the other hand, looking ahead to the research trends in SCF risk assessment, the main issues include the following to be explored in depth:1) How to collect structured, semi-structured and unstructured data from multiple sources, integrate them effectively, and share private data securely? 2) How to mine the SCF risk association knowledge from the massive data generated by Internet economic activities and extract risk features from it, to establish a high-dimensional and fine-grained SCF risk assessment index system? 3) How to use deep learning methods to improve the overall performance of SCF risk assessment models and ensure the interpretability of the models by resolving the importance and marginal effects of risk features?

Using the social network analysis method, for the first time, this paper builds an exponential random graph model to identify and interpret the formation mechanism of China's carbon emission spatial association networks based on the investigation of the structural characteristics of the networks from 1998 to 2016. The results show that China's carbon emission spatial association networks can be divided into four major plates with different responsibilities and present an evident regional club distribution characteristic. Each plate experienced a recombination process to varying degrees during our sample period. In detail, provinces belonging to the net spillover plate decreased, while provinces belonging to the main benefit and net benefit plates all increased. Meanwhile, although provinces belonging to the broker plate changed, its total number remains unchanged. Moreover, the "carbon emission refuge" effect between regions weakened. Regions tend to participate in the spatial association "activities" of carbon emissions in the forms of "reciprocity" or "clusters," and the spatial association of carbon emissions has the phenomena of "feudal economy" and gradient fault. A high degree of openness, a clean and low-carbon energy structure, and improved energy efficiency are conducive to promoting more carbon emission reception relationships between regions. As energy structure upgrades, the spatial association pattern of carbon emissions has gradient flow trends from west to east and from north to south. The complementarity of inter-regional economic development modes in openness, economic agglomeration, industrial structure, and energy efficiency leads to forming the carbon emission spatial association networks. Thus, the strengthening of regional division and cooperation and close regional trade ties causes the network to present the feature of a "carbon" fate match across a thousand miles drawn by a thread. Therefore, accelerating the implementation of cooperation emission reduction policies, such as regional integration and carbon trading market, will effectively promote the realization of regional collaborative low-carbon transformation development.

Based on the data of corporate bond issuers in Chinese market, this study applies oversampling techniques including Wasserstein generative adversarial networks (WGAN) and SMOTE to the imbalanced sample to improve the performance of bond default prediction. To explore the effect of oversampling techniques on classification models, the predictive outputs with difference imbalanced ratios are reported in the experimental results. It finds that the classification performance is significantly improved with the application of oversampling techniques, and the improvement is further enhanced when the sample distribution becomes more balanced. Compared to the classical SMOTE technique, both AUC and F1 score can be improved by WGAN. Overall, the experimental results demonstrate that the predictive performance of bond default models can be effectively boosted by generating artificial minority samples based on WGAN combined with the application of machine learning algorithms, which provides new insights into the bond default risk prediction of imbalanced samples.

Financial technology (FinTech) is critical in empowering banks' reform and innovation, especially in risk management activities. This study uses textual mining methodology to collect and identify the FinTech patent applications at the city level and creatively establishes the local FinTech development index. With the annual data of 148 commercial banks from 2013—2018 in China, this paper quantitively examines whether and how local development of FinTech affects financial institutions' risk management capacity. The main findings show that the FinTech development can significantly reduce the banks' risk, and more significantly in medium-sized banks. This paper employs the amount of news on FinTech related keywords in the Baidu searching engine at the city level as the instrumental variable to alleviate the endogeneity problem and finds robust results. The empirical findings also remain robust after using other alternative measurement on main variables and controlling spatial spillover effects. The mechanism analysis verifies that local FinTech development can significantly reduce the information asymmetry, promote business expansion, and strengthen the banks' risk management ability, thus contributing to the reduction of banks' risk. Moreover, the local regulatory authority efforts and the citizens' awareness of credit consciousness will increase the power of FinTech in risk management. Under the circumstance of the emerging FinTech and its pervasive adoption in commercial banks, profoundly understanding whether and how the FinTech development affects bank risk management will prevent and dissolve the financial risks and contribute to the high-quality development in the financial industry.

In the context of economic globalization and rapid development of science and technology, technological progress has become one of the most important way for enterprises to seek survival and development. This paper studies the supply chain reconfiguration strategy under the background of technological progress, and constructs two models. Before technological advancement, a high-tech supplier provides two manufacturers with components, and then one of the manufacturers invested in technology upgrades, and has its own supplier of components. The study found that after technological advancement, both manufacturers will lower their product prices, and high-tech suppliers will also lower the prices of their components. And the stronger the substitution between competing products, the greater the price reduction. Technological progress can reduce the impact of product substitution on pricing. The profits of high-tech suppliers and manufacturers that have not made technological advancements will reduce, but the profits of technologically advanced suppliers and the overall profit of the entire supply chain will only increase when the technological input is controlled within a reasonable range. In addition, technological progress will increase the consumer surplus, and the larger the market size, the smaller the unit cost of components, the more lavish this increase will be. Finally, we expand the model to situations with technical upgrade failures and supplier brand effects, and obtain similar results, verifying the robustness of the model.

This paper investigates the impact of economic sanctions on the value added and global value chain position of the target countries, based on cross-country input-output tables and economic sanctions data from 1990——2018. The findings of this paper show that economic sanctions reduce the value chain participation and domestic value added of the target countries, moving them up the value chain and transforming them into resource-exporting countries. Longer duration and larger scale sanctions more significantly reduce the domestic value added of the target country. The impact of sanctions on value added is transmitted according to foreign value added, indirect value added, and domestic value added. In addition, the basic empirical results of this paper remain robust after using the instrumental variables approach and considering the conditions set by the difference in difference method and industry heterogeneity.

Product diversity and shortened life cycles increase the uncertainty of consumers' online purchases, and online reviews have an increasingly significant impact on consumer purchases and the operation of e-commerce platform. Considering a monopolistic market consisting of an e-commerce platform and a manufacturer, we investigate the optimal self-operated channel strategy of e-commerce platform and its influence on system equilibrium. Based on this, the e-commerce platform's self-operated channel strategy, the value of online reviews, and their impact on consumer welfare are analyzed. The results of this paper show that, when online reviews have a positive effect or online reviews have a negative effect and their effectiveness level is high, the e-commerce platform are motivated to introduce self-operated channel. Moreover, if the level of channel competition is large enough, online reviews can also increase the motivation of the e-commerce platform to introduce self-operated channel. However, when e-commerce platform introduce self-operated channel, the optimal pricing strategy changes depending on the level of online review effectiveness and its accuracy, and self-operated channel are also beneficial to the manufacturer, while online reviews are not good for the manufacturer. Further, online reviews will affect consumers' choice of purchasing channels, which may damage the welfare of consumers who choose to purchase products through self-operated channel. Finally, the original model is expanded to analyze the choice of e-commerce platform's self-operated channel strategy and the effect of self-operated channel in the case of variable product online reviews.

Based on the daily trading data of Chinese A-share listed companies from 1997 to 2018, this paper establishes a prediction model for the probability of price crashes of individual stocks in the Chinese stock market. Combined with the event study method, the ability of the prediction model to identify individual stock crashes is tested. The result shows that the model has the ability to identify individual stocks with stock price crashes in the future, meanwhile the model has an excellent ability to predict the critical point of stock crashes. Based on the prediction model, this paper studies the role of corporate characteristic variables in crash risk contagion in China's stock market. Beginning with the prediction of individual stock crash risk, this paper combines individual stock crash risk and risk contagion. It has made contributions to related research.

A new problem of economic development today is how to effectively promote a double cycle between China and internationality. In this study, a framework of currency internationalization, exchange rate risk and of cross-border settlement was built based on "an equilibrium model of open economy of two markets". We would like to impel the interactions of this double cycle through RMB internationalization, which improving import and export trade of China and the Belt and Road Initiative countries. Theoretical analysis in this paper reveals that degree of currency internationalization has a great important effect on import and export trade, while exchange rate, exchange rate volatility and cross-border settlement are responsible for the effect. In addition, the solid evidences of import and export trade of China and the Belt and Road Initiative countries indeed show RMB internationalization make a great difference to the import and export trade, which is corresponding with the theoretical analysis very well. Unlike traditional literatures, our results indicate RMB internationalization can increase import and export trade by the peer effect of RMB settlement, rather than by increasing in exchange rate or decreasing in exchange rate risk, and the peer effect is result from the increasing of RMB cross-border settlement. This research can provide some suggestions for steadily promoting the RMB internationalization and accelerating the economic development of the double cycle.

The rapid development of information technology has brought complex and diverse network security problems. Now, more and more small and medium-sized enterprises, who have weak security foundation, begin to try a new security investment model combining risk management services and cyber security insurance. However, either over-investment or under-investment could result in losses of efficiency in cyber security risk management, and even unacceptable insecurity. Therefore, this paper discusses the small and medium-sized enterprises' local optimal solutions and global optimal solutions to their multi-player games from the perspective of heterogeneity, and tries to optimize their decision-making model in cyber security investment. On one hand, the result shows that there exists optimal solution for the risk-averse enterprises to achieve optimal and stable equilibrium under non-cooperation circumstance. On the other hand, under cooperation circumstance, although the overall utility of the market would increase, each single enterprise has the motivation to break the equilibrium of cooperation because of the prisoner's dilemma. There exists no stable equilibrium. Further, this paper studies the effects of insurance deductible and cyber security expense on the wealth utilities of uncooperative enterprises when taking the additional premium into consideration. It is proved that a reasonable level of insurance deductible could increase the enterprises' wealth utilities.

In view of the problem that the existing large group emergency decision-making (LGEDM) methods under the fuzzy preference environment do not fully consider the decision-making efficiency insufficient, this paper proposes a LGEDM method based on DEA cross efficiency and redundant information identification. Firstly, an output-oriented DEA model and a neutral DEA cross-efficiency evaluation model are constructed to solve the ranking weights of completely additive consistent fuzzy preference relation (FPR) and FPR without completely additive consistency respectively. Secondly, a group square compatibility model based on compatibility measure is constructed to measure the rationality and importance of large group preference information according to FPR and its ranking weights. Furthermore, redundant information identification is realized by screening the zero-value component in the optimal solution of the model. Thirdly, a LGEDM method is developed by integrating DEA cross-efficiency and redundant information identification. Finally, the case study and comparative analysis show that the proposed LGEDM method can effectively improve the decision-making efficiency.

The firm-sponsored online innovation community is an online platform through which firms cooperate with users to develop new products by value co-creation. It is a typical IT-driven business open innovation model. We propose a theoretical framework that the impact of feedback on users' follow-on innovation contribution in the firm-sponsored online innovation community based on social cognition theory, Yale attitude change theory and situational regulatory focus theory. Moreover, we build panel data model and test our theoretical hypotheses empirically using the grounded dataset in the MIUI community of Xiaomi. Our findings indicate that there is a significant positive relationship between positive feedback and users' innovation contribution, while there is also a significant correlation between negative feedback and users' innovation contribution. Considering different feedback sources, there are significant differences in the impact of feedback on users' innovation contribution. The results show that compared with peer feedback, expert feedback has a stronger impact on users' continuous innovation contribution. Further, we investigate the moderating effect of new product development phase on the relationship between feedback and users' innovation contribution. Compared with the idea generation stage, the negative feedback of experts in the testing and release stage has a positive impact on users' innovation contribution. Our findings contribute user innovation, new product development and open innovation literature in the context of online innovation community, and have some potential implications for product innovation practice in the emerging platform economy era.

Based on the consumers' perception gap between actual delivery time and promised delivery time, the problem of influence of government and consumer incentives on pricing and delivery channel selection of remanufacturing closed-loop supply chain is studied. In this paper, Stackelberg game theory is used to construct 6 decentralized decision-making models of supply chain for 6 combination scenarios of three incentive modes:No incentive, the government incentive, the consumer incentive, and two delivery channels:The manufacturer responsible for delivery and the retailer responsible for delivery. Then the analytical formulas of optimal wholesale price, optimal sales price, optimal actual delivery time, optimal recovery rate and optimal profits are obtained. By comparing the optimal values under different models and using numerical calculations, it is found that the government and consumer incentives can improve the recovery rate, the delivery time is shortened. When the retailer delivers goods, the recovery rate is larger and the delivery time is shorter. In addition, when the consumer incentive exit, the selling price and wholesale price will increase. According to the profit maximization, whether the goods are delivered by the retailer or the manufacturer depends on the strength of the consumer's incentive.

Based on the situation that promoting the effective development of hierarchical healthcare services takes hospital association as the carrier, this paper studies contractual schemes of cooperation between the government and medical institutions to coordinate the implementation of the referral service as well as the influence mechanism of the operations of hospital association service. By developing a four-stage game-theoretic queueing model, this paper analyzes the dynamic interaction relationships among patients, multiple community hospitals and tertiary hospitals in hospital association, and government, and then present all participants' equilibrium decisions in terms of patient referral rate, multiple community hospitals' capacity planning, and government subsidy price and each community hospital's profit-sharing price to a tertiary hospital. Our findings of studies indicate that whether the government coordinates community hospitals that receive patients to share the benefits with the tertiary hospital that sends patients depends on the size of member community hospitals and the cost of expanding the service capacity of community hospitals. Only when the size of community hospitals do not exceed a certain scale or their service capacity cost is not higher than a threshold or the subsidy budget is relatively shorter, the case that the government coordinates community hospitals to share their revenue is more conducive to the operation of hospital association referral service. Numerical experiments show that for the larger market demand, the size of community hospitals in the hospital association is the smaller or the service capacity cost is the lower, the government should coordinate community hospitals to share a higher revenue rate and provides a lower subsidy price to improve the patient referral rate, so as to improve the performance of each participant and reduce the waiting time. This paper proposes the contracts mechanisms for coordinating the effective operations of hospital association referral service, which provides theoretical decision support for the government to establish a scientific hierarchical healthcare delivery system. At the same time, this paper has a high application reference value to improve the overall efficiency of healthcare services.