Since the 2008 financial crisis， macro-prudential management has gradually become one of the important responsibilities of major central banks around the world. Macro-prudential policies and monetary policies are “involved” each other， so central banks considering macro-prudential policies face more complicated choices in choosing the optimal monetary policies than those considering monetary policies alone. Taking China as an example， the optimal choice of monetary policy in cooperation with macro-prudential coordination is studied by establishing a dynamic stochastic general equilibrium （DSGE） model based on the characteristics of China， such as the “binary” enterprises， shadow banking， government debt， and interest rate rules considering the money supply.Not only the research results of China's optimal monetary policy are enriched， but also ideas on how to balance macro-prudential policy and monetary policy when the central bank makes decisions are provided.The results show that considering the cooperation with macro-prudential management， the interest rate rule considering the money supply factor is more helpful to maintain the short-term and long-term stability of the social economy than the interest rate rule considering only the smoothing factor when the macroeconomic economy is affected by the technological shocks of state-owned enterprises and non-state-owned enterprises. In case of financial shock， the interest rate rule that considers money supply factor has less impact on economic growth rate， government expenditure， central bank’s interest rate， employment， credit and other variables than the interest rate rule that only considers smoothing factor， but it takes longer time to achieve equilibrium. Even if macro-prudential management is not taken into account， after financial shocks， interest rate rules considering money supply factors can control macroeconomic stability more quickly， and regulate liquidity of financial market more effectively. Moreover， under technical shock and financial shock， the welfare loss caused by the interest rate rule considering the money supply factor is less than that caused by the interest rate rule only considering the smoothing factor.

The diversified allocation of asset portfolios interested many scholars and investors. Additionally， diversifying existing risk factor portfolios is a common strategy for portfolio allocation. However， diversified allocation of factor strategies may not be as advantageous when there is a high correlation between factors. Meanwhile， the Chinese commodity futures market is highly active， and its unique market environment causes different manifestations of risk factors. It is interesting to investigate the correlation between different factors in the Chinese commodity market. It focuses on whether commodity futures factors are applicable in the Chinese futures market and whether the allocation of risk factors can help investors optimize assets.The qpr quantile association model is employed to effectively capture tail dependence. Building upon the work of Li Ruosha et al.， the application of covariates is further expanded upon by integrating the mixed data model MIDAS （Mixed-Data Sampling Model） . Given the relatively short historical data available in China's financial market， the utilization of the MIDAS method becomes crucial. By amalgamating high-frequency daily data， this approach not only enriches the available data information but also enhances the model's fitting capabilities.In this paper， daily high-frequency commodity index and stock index data are used to describe the weekly tail dependence between risk factor returns and market return. Regarding the model： 1） Comparing the basic qpr model， the qpr-MIDAS model can better fit the tail dependence results； 2） the model can realize the diversification return with the allocation of investment portfolios in economic applications. The empirical results show that： 1） there is no obvious spillover relationship between risk factor combinations and market returns except during crises； 2） among all the factors， the momentum factor performs best， with high portfolio return and with low correlation with the market factor； 3） the risk spillover effect negative link with the returns of commodity indexes and stock indexes； 4） Based on our comparative analysis of commodity futures portfolios before and after the change in financial institutions’ access policies， it is determined that the relaxation of policies can help control the intensity of risk spillover. The above research results provide a theoretical reference for Chinese commodity futures investment.The contribution of this paper is that a new tail dependence measurement model qpr-MIDAS is constructed， which can more accurately capture the tail spillover effect under multi-frequency conditions， and explains the advantages of this model from both statistical and economic levels. In addition， based on the perspective of China's commodity futures market， the literature about the law of tail dependence between investment portfolios is extended.This extension serves to offer valuable insights and guidance tailored specifically for Chinese commodity futures investors， thereby enriching their understanding of market dynamics and facilitating more informed investment decisions.

The factors that influence the cross-sectional stock returns is an important aspect of asset pricing research， and numerous studies have shown that the information environment of the market can have a profound effect on asset prices. Fang & Peress（2009） studied the effect of media coverage on cross-sectional stock returns and discovered a media coverage anomaly in the U.S. stock market. They find that stocks without media coverage have higher returns compared to stocks with media coverage. Will this effect also exists in the Chinese stock market？Retail investor percentage is much higher in China's stock market. Compared with institutional investors， retail investors are more susceptible to the influence of media information. With the rapid development and wide popularity of the Internet in China， digital media has gradually replace the traditional media. The online digital media has greatly reduced the cost of information acquisition and improved the information dissemination efficiency， thus profoundly changed the information environment of China's financial market. Therefore， what is the impact of the digital information environment change on China's financial market？ Is there an Internet digital media coverage premium in China？Based on the cross-sectional stock returns from January 2008 to December 2019， the existence of online digital media coverage anomaly in China is explored and possible explanation is provided. Our internet media data includes financial news from more than 400 important internet media outlets. The result shows that： （1） there exists internet media coverage premium in China， and it still exists after controlling the size and book to market ratio factors； （2） Compared with the stocks without media coverage， the stocks with high media coverage have a lower cross-sectional return， which is significant negative； （3） Different from the U.S. market， the media coverage premium in China's stock market could not be explained by the risk compensation theory， but stems from the reversal effect after investors excess attention； （4） The media coverage premium effect of positive news is stronger than that of neutral and negative news. These findings are important for the rational investment of individual investors in China's A-share market， and provide empirical evidences for promoting the function of Internet media in information dissemination in the financial market. The results are also important for relevant policy-making and promoting the high quality development of China's stock market.

Privateplacement is the most important approach to refinance equity in China’s capital market. As a transition economy， China has many state-owned enterprises （SOEs） in the capital market； these SOEs are more likely to obtain seasoned equity offering by virtue of their natural political connections. Besides， it is common that Chinese listed companies have the controlling shareholders， hence CEOs of listed companies would like to consider more interests of major shareholders in decision-making. The volatility changes during one year before and after the private placement of Chinese listed companies is empirically examined. An inverted U-shaped volatility timing effect can be observed from empirical results， represented as the expropriation of major shareholders in Chinese listed companies. Then， the robustness tests are proceeded by using board meeting day as the benchmark day of the private placement， setting the beginning year of studying period as 2006， applying fixed-effect panel model， adopting the data during threespecial sample periods， respectively. As expected， the results of robustness tests can support our main conclusions. Furthermore， the results of heterogeneity tests show that the volatility timing effect of private placements is stronger for non-SOEs， young companies， companies with high shares proportion of controlling shareholder， and those with high ratio of intangible assets， which confirms the more severe encroachment of major shareholders in these types of listed companies. Finally， the economic consequences of the volatility timing effect for private placements in Chinese listed companies is analyzed. The empirical results prove that there is a pricing discount before the private placements， but the stock prices rise significantly after the private placements. Investment in private placement companies yields an average 37.32% arbitrage premiumafter one year， compared with investing in stock from public offerings. Therefore， our empirical findings not only enrich the theories of private placement， but also contribute to practice. The policy references are provided to improve China’s private placement market， as well as some investment guidance for investors in quantitative selection of assets and trading timings.

Accurately predicting whether bank loans of listed companies will default is very important for the management of listed companies and investors ' investment decisions. The innovation and characteristics of this study are as follows. Firstly， JS divergence is introduced into the field of credit risk for the first time to discrete the features， which ensures the ability of the discrete feature numerical interval to discriminate the default state of enterprises. According to the proportion of default enterprises and non-default enterprises in the feature interval， the corresponding feature interval is scored by WOE， which ensures that the greater the WOE score is， the better the credit status of enterprises is. This has changed the problem of insufficient understanding data of classical models such as logical regression caused by the subjective setting of feature interval values in existing studies. Second， the least-angle regression （ Lars ） equation with L1 norm penalty term （ Lasso ） is adopted， and the minimum Bayesian information criterion （ BIC ） is taken as the goal.Features with weights not equal to 0 in the Lasso-Lars regression equation are inversely derived as the optimal feature combination， so as to ensure that the selected feature combination has the maximum default discrimination ability and the minimum redundancy degree. It makes up for the deficiency that the existing research often does not consider the redundancy of feature combination selected， which leads to the increase of model complexity. Thirdly， the optimal threshold of default discrimination of logistic regression model is deduced with the goal of maximizing G-mean， which avoids the disadvantage of inaccurate judgment of default enterprises caused by the threshold with 0.5. It is shown that 43 discrete features selected from 159 features not only have the ability to distinguish default states， but also conform to the principle of “ credit 5C ”. The feature system is scientific and reasonable. Among them， in addition to the cash ratio， corporate value multiples and sales gross margin and other financial factors that reflect corporate solvency， profitability， operational capacity and growth capacity significantly influenced corporate default， non-financial factors such as management shareholding ratio， the number of shareholders ' meetings and whether to disclose internal control evaluation reports， and external macro factors such as engel's index， per capita GDP and ultimate consumption rate remarkably affects corporate default.

In recent years， the scale of China's household debt continues to grow. At the same time， China's housing prices and real estate investment show a rapid upward trend， while the growth rate of GDP， consumption and fixed asset investment has decreased to varying degrees. This is the phenomenon of “shifting from real to fictitious”. It intends to interpret the above economic phenomenon from the perspective of housing price expectation in this paper. Based on the statistical data from 2007 to 2019， it is found that： household debt continues to increase， but the volatility is small； household debt and the main macroeconomic variables show a weak positive correlation. Then a DSGE model is built which including heterogeneous households， credit constraints and GHH utility function. Numerical simulation shows that under the impact of technology shock and weak expectation shock of housing price rising， the model can explain the cyclical characteristics of household debt， real estate market and real economy. When the wealth effect of technology shock is greater than the speculative effect of weak expected shock of house price rising， the wealth effect dominates， the total demand increases， and the household debt forms a positive co-movement with the real estate market and the real economy. If the expectation of house prices rising becomes stronger， speculative effect will dominate， and household debt， real estate market and real economy will move in reverse. Once a strong expectation of rising house prices is formed and speculative effect is dominant， household debt will restrain aggregate demand and crowd out the real economy. And then household debt， house prices and real estate investment will rise rapidly， while GDP， consumption and fixed asset investment will decline. That is to say， household debt， real estate market and real economy will move in reverse， and credit constraints will have amplification effect. The counterfactual simulation shows that the strong expectation of house price rising will lead to the problem of “shifting from real to fictitious”. And then the strong expectation of house price falling has significant “deleveraging” and tightening effect on household debt and real estate market. Therefore， the expectation of house price stable can avoid the ups and downs of the macro-economy， which is conducive to the smooth operation of the macro-economy.

As a targeted financing channel for green and low-carbon projects， green bonds have developed rapidly around the world， but there are some different specific conditions for each country. However， the existing literature lacks an assessment and analysis of green bond development at the national level. This knowledge gap obstructs understanding the development trend of China's green bonds from a global perspective. So， it is crucial to comprehensively evaluate the global green bond development level and detect the determinants behind the differences among economies.In this paper， the green bond issuance record data of 62 countries or regions from 2014 to 2020 are collected to conduct comprehensive empirical research. With the application of the principal components analysis method， a systematic assessment of the green bond development in various economies is conducted firstly； then， some national clusters are obtained through the K-means cluster algorithm， which suggests some heterogeneities and homogeneities for different economies； To detect the rationales for the global differences in the development of green bonds， multiple linear regression， and ordinal Probit model are utilized sequentially.The empirical results show that the different economies display different levels and speeds in developing green bonds. Three categories of determinants could affect the development level of green bonds in a country， namely macroeconomic fundamentals， financial system， and low-carbon transition environment. Regarding specific determinants， the intensity of targeted green bond promotion policies is the most critical driving force for the development of green bonds.Some targeted policy recommendations are provided for China， in the field of capturing the development tendency of global green bonds， optimizing the development path of green bonds， and promoting green bonds to support the carbon-neutral actions. Additionally， this paper fills the current research blank in evaluating the development of green bond， whose conclusions can effectively support further exploration of this emerging domain.

In the face of old and new versions of software， strategic consumers not only choose the best time and type of products to buy over time， but also consider the costs of using the new software due to a series of compatibility problems， which poses a huge threat to corporate profits. Therefore， aiming at the optimal decision-making problem of software enterprise under the influence of consumers' internal preference and use costs， we consider the generally popular two-period game. From the two-dimensional perspective of sales model and discrimination strategy， four dynamic game models of inter-temporal discrimination strategy and mixed discrimination strategy are constructed under the sales model or the subscription model， respectively. Then， backward induction is used to solve the game models in four different situations， and on that basis， the optimal marketing strategy combinations and implementation conditions for software company are compared and analyzed. Finally， Maple 2021 is used to verify the validity of the relevant propositions and conclusions. Through model construction and analysis， some interesting management insights are obtained. First of all， when the consumer's use costs are small， the mixed discrimination strategy is superior under the selling model， while the inter-temporal discrimination strategy is superior under the subscription model. Second， the optimal selling model under the inter-temporal discrimination strategy is related to the consumer's use costs， while the subscription model under the mixed discrimination strategy is always superior to the selling model. Finally， the effect of inter-temporal discrimination strategy on alleviating consumers' delayed purchase behavior varies across sales models. To sum up， software enterprise should adjust business strategies according to the changing circumstances and help to enhance the new marketing potential. In addition to the consumers’ internal and external factors， the degree of quality difference and the type of discrimination strategy are also the key factors to improve profitability. At the same time， there is an interaction between the discrimination strategy and the sales model. Therefore， the enterprise also needs to fully consider the decision-making order of both. In addition， in the price-setting process， enterprise should take into account operating conditions （such as the type of products and their degree of popularity， discriminatory strategies and sales models， etc.） and market conditions （such as whether consumer preferences are benign and the future development potential of the market） and other aspects of the decision-making.

Traditional software is permanently licensed and customizable， while SaaS services are standardized， and are generally charged at a monthly/annual fixed price subscription or according to the actual usage of each consumer. Existing research on the competition between traditional software providers and SaaS providers is mostly limited to vertical differentiation models， or given the pricing scheme of SaaS. Taking into account the vertical and horizontal differences between providers， as well as the consumer heterogeneity in the two dimensions of product usage and product preferences， the optimal pricing strategy of the SaaS provider and its impact on social welfare are examined. The competition between the traditional software provider and the SaaS provider is characterized by the Hotelling model， and the choice between subscription-based pricing scheme and pay-per-use pricing scheme is analyzed. The results are as follows. （1） When the vertical difference between the SaaS provider and the traditional software provider is relatively small and the horizontal difference is relatively large， the subscription-based pricing scheme should be adopted to extract more surplus from the locked market segment； otherwise， the pay-per-use pricing scheme should be adopted to ease competition and attract low-end consumers with low usage and large price sensitivity. （2） The higher the product customization level of the traditional provider， the more willingness of the SaaS provider to adopt the pay-per-use pricing scheme. （3） The best social welfare can be always achieved when the subscription-based pricing scheme is adopted by the SaaS provider. Therefore， if wishing the strategic choice of providers to be consistent with the goal of social welfare maximization， providers should be guided by the government agencies to diversify their products， and prevent homogeneous competition or price discrimination.

The immutability and verifiability of blockchain technology provides new ideas for solving trust problems in enterprise operation and management， but whether to adopt blockchain technology is an important decision for companies. Four competitive models are constructed， including all companies not adopting blockchain （NN）， weak brand company adopting blockchain and strong brand company not adopting （BN）， weak brand company not adopting blockchain and strong brand company adopting （NB）， all companies adopting blockchain （BB）， and the adoption strategies of blockchain technology and its impact on quality and pricing decisions in the context of competition between strong and weak brands are studied. In addition， the relevant conclusions are verified by numerical analysis methods. The results show that because the strong brand company has a higher degree of market recognition， it is difficult for the BN strategy to become an equilibrium state， and whether two competing companies adopt blockchain technology depends on many factors， among which the cost of adoption has the most significant impact. When the cost of adoption is high， the NN strategy will be the final choice. When the cost of adoption is at a moderate level， the NB strategy will be selected. As the cost of adoption is further reduced， the market will reach equilibrium under the BB strategy. Market size， market expansion ratio， quality competition intensity， and privacy concerns will affect the scope of application of different strategies. Comparing the quality and price under different adoption strategies， it is shown that compared with the NN strategy， under the BN or NB strategy， the company that do not adopt blockchain technology will reduce the quality and price， while under the BB strategy， the weak brand company will always provide higher quality products and adopt a price reduction strategy when consumers have low quality recognition ability for the strong brand company. The strong brand company choose to increase quality and price when their consumer recognition ability is low， but lower quality and price when recognition ability is high. Comparing BN， NB and BB strategies， it is found that the BB strategy does not always incentivize companies to improve quality. Only when the company adopts blockchain and competitors do not adopt it， it has an incentive effect on quality improvement， and profits will rise. Otherwise， the quality and profit level under the BB strategy will be higher. The research conclusions can provide management insights for governments to promote blockchain technology and guide companies to adopt blockchain technology.

The scenarios of unconventional emergencies are highly complex and uncertain， which means that the generation of emergency response plans must consider the needs of subsequent dynamic adjustment and the generated plans must have the characteristics of flexible adjustment. In addition， there are often multiple conflicting goals in the process of emergency response. How to balance the conflicting goals and make the generated plans more scientific and reasonable is also a problem that must be considered. There is still room for improvement and expansion in the existing researches on the above two aspects. Improvisational decision-making provides an effective mode or means for improvisational generation and dynamic adjustment of emergency response plans for unconventional emergencies， but the operable models and methods in its key links still need to be further studied. In order to improve the flexibility of the generation of emergency response plans for unconventional emergencies， an emergency response plan model is constructed based on the idea of improvisational decision-making and with emergency response activities as the core. For the sake of generating a satisfactory and feasible emergency response plan， taking emergency response activities as the programming objects， and taking resources， time and order relations of emergency response activities as constraints， a multi-objective programming model for improvisational generation of emergency response plans is established to minimize rescue time， minimize response cost and optimize the balance of resource allocation. With the help of the non-dominant ranking evolutionary algorithm with elite strategy and the optimal compromise solution selection based on the fuzzy set theory， the multi-objective programming model is solved and the plan is optimized， so that when there is a “mismatch” between the response ability of the existing plan and the current scenario at any moment， the effective emergency response plan can be obtained through the reconfiguration of emergency response activities. By systematically collecting， analyzing and summarizing relevant survey data obtained from Ministry of Emergency Management， news content， emergency preplans and references， a case study of improvisational generation of the emergency response plan of Yancheng “3.21” chemical plant explosion accident is carried out， and the scientificity and effectiveness of the proposed model and method is verified by solving the case-based problem. The results show that fine-grained representation of emergency response activities improve the flexibility and reconfigurable of emergency response plans， and provide basic active elements for the improvisational generation of emergency response plans. The further refinement of the elements of emergency response activities such as time， resource and priority ensures that the generated plans meet the requirements of time， cost and fairness for emergency response. The proposed multi-objective programming model and the corresponding solving algorithm for improvisational generation of emergency response plans not only enrich the connotation of improvisational decision-making， but also improve the operability and feasibility of the application of improvisational decision-making in the generation of emergency response plans for unconventional emergencies， and then provide some reference for the further improvement and deepening of the theories and methods of emergency decision-making.

In today's information service society， there are various channels for customers to obtain service information. On one hand， some customers can easily grasp service information and make rational decisions according to relevant service information. On the other hand， due to the influence of various factors， it is difficult for some customers to obtain service information. In order to avoid blind decision， they can use the word of mouth （WOM） information to confirm whether they can trust such service， that is， WOM information can provide more reliable guarantee for their decision making.On the basis of this phenomenon， in this paper， it aims to deal with the related following questions： Q1. When the queue information obtained is heterogeneous， how do the two types of delay-sensitive customers make their own queuing decisions， how do the decisions of non-member customers affect the member customers’ equilibrium queuing strategies？ Q2. As the market size of member customers changes， how should the service provider make the optimal pricing decision to maximize his revenue without changing service capacity？ Q3. As non-member customers collect more WOM information， how should the service provider adjust the optimal service price？To address these research questions， this paper considers a non-preemptive M/M/1 priority queuing model， which includes two types of customers， namely， member and non-member customers. The service information obtained by the two types of customers is heterogeneous， where member customers can obtain sufficient service-related information and make rational decisions， while non-member customers have no relevant service information and can only rely on WOM ways to make decisions， such as interpersonal channels or service rating websites， that is， they can obtain relevant experience information from relatives and friends who have purchased service， or use review websites to collect relevant rating information on the service value to know the service. The equilibrium strategic behavior of member customers is described and the influence of the number of ratings on the service value obtained by non-member customers on the queuing behavior of member customers is studied. Then the revenue function of service provider is constructed and the optimal service strategy of service provider is obtained.The main results show that， first， the decision-making behavior of non-member customers affects the queuing strategy of member customers as well as the optimal service pricing decision of the service provider. Therefore， it is very important to grasp the decision-making behavior of non-member customers to maximize the revenue of the service provider. Second， the smaller market size of member customers may improve the optimal pricing of service provider. In addition， when the market size of member customers is large， the number of WOM information and the market size of member customers have a weak impact on the optimal service pricing. Third， when the market size of member customers exceeds a certain value， and the service rate of member customers is greater than that of non-member customers， then the high overall rating （low overall rating） provider should decrease （increase） the service price as the number of rating on the service value received by non-member customers increases， and vice versa.

The airline network is not only an important strategic resource for airlines， but also a key national infrastructure. The choice and construction of the network model will affect the operational efficiency and quality of the civil aviation industry. A three-stage non-cooperative game model for airline network selection is constructed. If the airlinei adopts the hub-and-spoke network， the second-stage capacity game model and the third-stage quantitative game model are： {\Pi }_i=\mathrm{m}\mathrm{a}\mathrm{x}\left(E{\pi }_i-\mathrm{2}{c}_h{n}_i{K}_i\right)、{\pi }_i=\mathrm{m}\mathrm{a}\mathrm{x}{\displaystyle \sum _{y=\mathrm{1}}^{\mathrm{2}}}y{q}_{yi}\left[M_y-\left(q_{yi}+q_{yj}\right)\right]\text{?}. If the airlineiadopts the point-to-point network， the second-stage capacity game model and the third-stage quantitative game model are： {\Pi }_i=\mathrm{m}\mathrm{a}\mathrm{x}\left(E{\pi }_i-c_p{\displaystyle \sum _{y=\mathrm{1}}^{\mathrm{2}}}y{q}_{yi}\right)、{\pi }_i=\mathrm{m}\mathrm{a}\mathrm{x}{\displaystyle \sum _{y=\mathrm{1}}^{\mathrm{2}}}y{q}_{yi}\left[M_y-\left(q_{yi}+q_{yj}\right)\right]， where {\Pi }_i and {\pi }_i represent the profits of the second stage capacity game and the third stage quantity game respectively. Based on the three hypotheses in this paper， the Stackelberg dynamic game theory is used to solve the problem， and the uncertainty effect， cost effect and market scale effect of game equilibrium are discussed deeply. It is found that： firstly， market uncertainty provides great flexibility value for the hub-and-spoke network， but competition will cause a certain degree of loss to it. When the degree of uncertainty exceeds a certain limit， new entrants tend to adopt the hub-and-spoke network. Secondly， under the assumption of the symmetry of the local market， the size of the local market will not affect the equilibrium result of the network game. When the connecting market scale is large enough， even if the market has strong uncertainty， new entrants still tend to use point-to-point networks. Thirdly， the best network decision for new entrants is essentially a tradeoff between the value of flexibility and cost advantage. When the unit capacity cost is low， the new entrants tend to obtain the flexibility value， when the unit capacity cost is high， the new entrants will adopt different network strategies， and the two companies enjoy flexibility value and cost advantages respectively. In most cases， this equilibrium tends to be socially optimal. It concludes with a numerical simulation of the theoretical results and the corresponding management insights in this article.

To cater to the multi-variety and small-batch characteristics of aerospace product manufacturing， flexible allocation and scheduling of resources in production workshops based on production planning is key to maintaining efficiency and response capability. In particular， an integrated optimization problem of resource allocation and scheduling is formulated and solved to minimize production delay， manufacturing costs， and total resources across multiple scenarios with various production resources， in-workshop transportation， and resource availability. A multi-objective programming model is first formulated based on a detailed delineation of our research questions. An improved multi-objective differential evolution （IMODE） algorithm is then put forward based on Pareto optimization to solve such an NP-hard problem efficiently. Upon obtaining a high-quality set of initial chromosomes based on heuristic search， the final solution of a Pareto set is derived from fast non-dominated sorting followed by iterative optimization through a differential evolution algorithm. Based on 11 scenarios with different combinations of job numbers and due dates generated from empirical data， IMODE on average outperforms NSGA-II and MOPSO， two widely-adopted algorithms for multi-objective optimization. Furthermore， our additional analyses identify a ceiling effect of resource quantity on overdue days and manufacturing costs. When there is a large number of jobs with insufficient resources， on the one hand， increasing the number of resources can mitigate production delays and costs. On the other hand， the allocation of more resources is unable to shorten overdue days or bring down costs in the context of a small job number with adequate production resources. In sum， flexible integrated resource allocation and scheduling through IMODE enhance resource utilization and manufacturing efficiency in the face of dynamic production demands.

In order to improve market penetration and meet the differentiated needs of passengers， ridesharing enterprises explore the “dual platform” operation mode on the basis of the existing single platform. The multi-agent simulation and Hotelling model are integrated to construct a “dual platform” pricing simulation model for ridesharing enterprises. Among them， the Hotelling model is combined to analyze the impact of vehicle service quality， vehicle loyalty， and passenger price sensitivity on the “dual platform” pricing of enterprises under joint pricing strategies， and further it is compared with independent pricing and monopoly pricing strategies. At the same time， a multi-agent model considering individual dynamic behavior rules is designed using computational experiments to simulate the operating scenario of ridesharing enterprises in Repast， Explore the optimal pricing strategy. It is found that： when the service quality of new platform vehicles is low or passenger price sensitivity is low， enterprises should not implement a “dual platform” strategy； If enterprises implement the “dual platform” strategy， they should adopt a joint pricing strategy； Under the “dual platform” joint pricing strategy， vehicle service quality， vehicle loyalty， and passenger price sensitivity will all affect platform pricing behavior. It provides theoretical guidance for optimizing operational strategies of ridesharing enterprises in this article.

Individual behavior analysis and induction is an important aspect of organization management. The behavior analysis and evaluation method oriented to management requirements can provide strong data-based support to the development of individual and organization.In this paper， the management needs of incentive and punishment are integrated into the evaluation process based on the analysis of behavior characteristics， and a contextualized evaluation method for different reward and punishment needs is proposed. Firstly， the behavior characteristics of the alternatives are identified by the combination analysis of the comprehensive development level and competition degree of the indicators. Based on this， all the indicators are divided into four groups： advantage indicators， comparative advantage indicators， disadvantage indicators， and comparative disadvantage indicators. Secondly， three types of evaluation situations are defined based on the common demands of reward and punishment such as “reward excellence”，“punish weakness” and “reward and punishment equal emphasis”. Based on the rules of reward and punishment in different situations， the determination method of indicator weights is discussed to induce the development behavior of the alternatives through weight design. Lastly， the proposed methods are applied to evaluate the comprehensive development of 14 cities in Liaoning province. The effectiveness of the proposed method is verified by the correlation analysis between the ranking results and that of the corresponding indicators. And the characteristics of the proposed method are illustrated by comparing with the existing methods.The results indicate that the effect of “punish weakness” is obvious， so it is suggested that this kind of strategy should be preferred in applications. However， if the decision-makers expect to form a good evaluation atmosphere， they can adopt the strategy of “reward and punishment equal emphasis” in practice. The “reward excellence” strategy alone is generally not recommended to avoid situations that lead to “malformation” development.The research work in this paper can provide theoretical and methodological support for the incentive management of individuals in organizations and systems. The use of reward and punishment strategies can highlight the differences between individuals， so the proposed methods have a good application prospect in differential performance management problems. In addition， this method can lay a foundation for in-depth analysis and management of individual development behavior by classifying and identifying individual advantages and disadvantages. Therefore， the methods also have certain application prospects in individual behavior induction management and development planning.The main contributions of the research reflect on the following three aspects　（1） The behavior characteristics of the alternatives are analyzed in the evaluation process， and a contextualized evaluation model oriented to behavior guidance is proposed； （2） The classification and identification of indicators makes the alternatives’ judgment of their own advantages and disadvantages more clear； （3） The proposed methods implement rewards and punishments to the indicators level， which makes the effect of reward and punishment more obvious， and the induction of development behavior of the alternatives more direct.

It focuses on design features of mobile live streaming commerce platform from the perspective of IT affordance in this study， based on the Kano model of dummy variable regression to conduct quality classification of design features. With the quality types of design features， the “performance-satisfaction” function expressions are established， to depict the nonlinear and asymmetric relationships between performance of design feature and customer satisfaction. Further， the matter-element model is used to propose a satisfaction evaluation method for mobile live streaming commerce platform considering different quality classification of design features， and the feasibility and effectiveness of the proposed method are verified by the instance of Taobao Live platform. The results show that the 13 design features extracted belonged to four different Kano quality categories， with the highest user satisfaction with transaction methods and the lowest with commerce cues； the quality categories of design features and user satisfaction differed among users of different genders and years of live shopping. It can guide the quality assessment and improvement of mobile live streaming commerce platforms in this study， as well as support users' purchase decisions and enhance their experience through optimized design.

There are double uncertainty of product service system demand and supply in product service supply chain. In view of the uncertainty of product service system demand and supply in the product service supply chain composed of a single integrated service provider， a single subcontractor and a single supplier， the decision model of the product service supply chain network in the decentralized decision-making state and the coordinated state are constructed respectively， and their decision-making behaviors are analyzed. The research shows that： in the decentralized decision-making state， each member enterprise makes decisions based on the maximization of its own benefits， which cannot reduce the influence of demand and supply uncertainty， the overall optimization of the product service supply chain cannot be achieved. In the coordinated state， the coordination model between the integrated service provider and the subcontractor based on revenue sharing contract can reduce the influence of demand uncertainty， but because the supply uncertainty faced has not been improved， their optimal expected revenue could not be realized. The coordination model between subcontractor and the supplier based on punishment strategy can reduce the influence of supply uncertainty. Combining the punishment strategy and the revenue sharing contract， the coordination model of the product service supply chain based on the punishment-revenue sharing joint contract is constructed， and the coordination result not only reduces the uncertainty of supply， but also weakens the influence of demand uncertainty， and the Pareto improvement of the overall revenue of the product service supply chain and the revenue of each member enterprise are realized. Finally， the validity of the conclusion is verified through numerical simulation.

With the gradual enhancement of customer service awareness， the demand for services has become diversified， and personalized value-added services have become an important means for manufacturing and retail enterprises to gain competitiveness considering customer value. Value-added services facilitate the use of products by customers， and have a greater impact on customer value. Therefore， in dual-channel supply chains， both offline retailers and e-commerce platforms are keen to enhance customer value to achieve the purpose of expanding its own channel market demand by providing value-added services. It is very important for members of dual-channel supply chains to formulate reasonable value-added service strategies in the era of customer value as the core.Considering customer value and value-added services of offline retailers and e-commerce platforms， in order to explore the optimal cooperative value-added service strategy choice problem of a dual-channel supply chain， four cooperative value-added service scenarios of the manufacturer， offline retailer and e-commerce platform are established in this paper： non-cooperation strategy，manufacturers only cooperate with offline retailers， manufacturers only cooperate with e-commerce platforms and manufacturers cooperate with offline retailers and e-commerce platforms at the same time. With the help of game theory， comparison and numerical analysis methods， the optimal decisions and different members’ profits under different scenarios are compared and analyzed. The results show that： the optimal strategies of channel members are not consistent. Manufacturers who cooperate with offline retailers and e-commerce platforms in value-added services can enhance dual-channel customer value. This is the manufacturer’s optimal strategy. Non-cooperative value-added services is the manufacturer’s worst strategy， manufacturers only cooperate with e-commerce platforms （offline retailers） for value-added services. These are the best strategies for e-commerce platforms （offline retailers）， and the worst strategies for offline retailers （e-commerce platforms）， the sub-optimal strategies for manufacturers. The customer value of the e-commerce channel may not decrease with the increase in the marginal profit of the manufacturer’s e-commerce channel. The customer value of the offline channel may not decrease with the increase in the offline retailer’s marginal profit. These depend on the relative sensitivity of customers’ perception of gains and losses.

The pricing methods of charging by usage and charging by stage is examined for SaaS service providers. Three pricing discrimination strategies are considered to analyze their impact on the pricing methods of these providers. The objective is to determine which pricing methods and strategies SaaS service providers should adopt in different scenarios to maximize profits. The optimal profit of the two billing methods is investigated under three different price discrimination strategies. Additionally， it analyzes the influence of five factors on the profits of SaaS service providers. Furthermore， the research identifies the recommended price discrimination strategies for SaaS service providers using both charging by stage and charging by usage.The findings indicate that when the usage is high and transaction costs are high， SaaS service providers can generate greater profits by employing the stage-based charging method. In cases where the usage rate and transaction costs reach an equilibrium state， both pricing methods yield similar profits. However， when usage is low and transaction costs are low， SaaS service providers can maximize their earnings by implementing per-usage billing. For SaaS providers using the stage charging method， the choice of price discrimination strategy depends on the discount rate of the second phase. A behavior-based price discrimination strategy is most effective when the discount rate is high， while an inter-period price discrimination strategy works best when the discount rate is low. Conversely， when the charge-by-usage method is utilized， the intertemporal price discrimination strategy proves to be the most beneficial. These research findings have important management implications. Enterprises should carefully consider the usage and transaction costs associated with SaaS services when determining their pricing strategies. These insights help explain the varying pricing strategies employed by different types of SaaS service providers. For instance， Wistia， a video hosting platform， adopts an intertemporal price discrimination strategy based on usage pricing due to limited video uploads by users. On the other hand， Salesforce， a CRM service provider， utilizes an inter-period price discrimination strategy under the stage charging method， given its high user usage and transaction costs.

In order to gain competitive advantage in the fierce market environment， retailers often adopt markdown strategy to attract consumers to buy. In fact， it is the frequent price cuts by retailers that lead to the emergence of strategic consumers， posing severe challenges to their pricing decision-making. Unlike myopic consumers who only focus on current purchase utility， strategic consumers can fully obtain product price information and future price trends， and will choose the optimal purchase behavior by comparing the utility levels obtained by purchasing products in the current and future periods.The existence of strategic customers brings severe challenges to enterprises' pricing decisions. Consumers can choose to buy products at lower prices by delaying their purchases. Considering the influence of consumer's strategic behavior， a continuous time consumer purchase decision-making model is constructed， the optimal decision-making of retailer's two-stage pricing and markdown timing is analyzed， and further the retailer's markdown timing is analyzed under the situation of inventory surplus and inventory shortage.It is indicated that there is an inverted U-shaped relationship between retailer's profit and two-stage product pricing， and there is a unique price combination to maximize the retailer's profit. The increase of price in the regular period will stimulate consumers to choose to wait for purchase， and the increase of price in the markdown period will weaken consumers' patience for waiting to buy. In different situations， retailers can choose to postpone or advance the timing of markdown to achieve Pareto improvement. Considering the two scenarios of inventory surplus and inventory shortage， retailers can balance inventory by dynamically adjusting the markdown timing and meet the demand of all potential consumers under the condition of bearing a certain cost， which can solve the matching problem of product supply and demand， even achieve zero inventory or meet the needs of all potential consumers.Based on the above analyses， it is proposed that retailers need to fully grasp the behavioral laws of strategic consumers and set prices according to the needs of strategic consumers. Retailers can expand market demand by adopting markdown strategy， while training consumers to be more and more patient， it is necessary to take into account the inventory situation and determine the optimal markdown timing and two-period price. It can provide some meaningful reference for relevant studies and firms in practice.

The rating of new retail ecology network security is a key problem in nowadays cybersecurity management. However， the existingnetwork security rating investigated on general network security. New retail ecology network security is not studied， especially paying little attention to issues such as the non-compensation of information among factors and the stability of rating methods， the stability for variable weight decision methods for rating network security situation. Based on the description of the fuzzy rating problem， the membership functions of interval type， upper bound type， and lower bound type are constructed， and the membership functions of four cases are given. A method of determining index weights based on cross-entropy and entropy theory is proposed. A compromised variable weight analysis method is systematically studied. A compromised variable weight function construction method based on utility function is proposed. Furthermore， the absolute risk aversion coefficient is used to analyze the effect of variable weight decision-making， and the relevant properties are proved. Accordingly， a fuzzy comprehensive evaluation model of compromised variable weight is proposed， and the binary semantic method is further used to identify grades reasonably and distinguish the ranking of the same grade. The stability analysis of cybersecurity situation grade assessment mixed variable weight synthesis model is studied through using mathematical theory， and the analytical solutions of index weight ranges are given when the grades’ results of the cybersecurity situation grade assessment mixed variable weight method are stable. This method can overcome the shortcomings of the maximum membership rating method and compensation index rating problems.

In the closed-loop supply chain， considering smart recycling and corporate goodwill. Third-party recyclers use smart recycling cabinets to recycle used products. The recovery rate affected by various factors such as recycling effort and time. The impact of the three scenarios of no marketing strategy，coupons valid on the day of issuance and coupons valid on the next day of issuance on the environmental and economic benefits is studied， and a comparative analysis is made. The dynamic recovery rate is characterized by Ito process， and the influence of different cooperation strategies on supply chain members is analyzed. Research shows： The issuance of coupons that take effect the next day has the most significant increase in the recovery rate， recovery effort level， and profit of closed-loop supply chain members， and the volatility is more obvious than other situations， mainly because the uncertainty of the number of repurchases increases the volatility. The greater the impact of manufacturer's recycling costs on the recycling rate of waste products， the more it can incentivize recycling and improve the recycling efforts and profits of third-party recyclers. The more sensitive the reputation of a third-party recycler to the discount factor， the more it can improve its recycling efforts and retailers’ profits.

Online display advertising is developing rapidly， and the cost-per-click （CPC） contract is an important form of contract for online display advertising. Based on reality， the impression supply is usually uncertain when making advertising delivery decisions， and its probability distribution is difficult to accurately know， and only partial distribution information is known. Using the distributionally robust optimization framework， an uncertain set characterized by known information is constructed， and the optimal advertising strategy in the worst case. Then a distributionally robust chance-constrained formulation is established and a solution algorithm is given， and some numerical experiments are carried out. The results of the numerical experiments show that the designed advertising optimization model and the corresponding solution algorithm have good performance.

Information security is the foundation for the high-quality development of the software supply chain. In the software supply chain， information security risks are inherited， and the input of upstream and downstream information security jointly determines the degree of software operation security. Information security risks in any link will directly or indirectly affect the security of end software users. Due to the complexity of information security， neither software vendors nor users can observe each other's efforts in information security. When a safety accident occurs， the responsibility for the accident cannot be clearly defined， thus generating bilateral moral hazard. The supply chain studied in this paper consists of software suppliers and users. By constructing an ideal control model under centralized decision-making （without moral hazard） and an information security vulnerability loss sharing model under decentralized decision-making （bilateral moral hazard）， a reasonable software supply chain information security responsibility coordination contract is designed and the numerical simulation of the model is carried out.The research results show that the ratio of vulnerability loss sharing between software suppliers and users is related to the cost coefficient of the other party， not its own cost coefficient. The level of cooperative R&D determined by the synergy coefficient and cost coefficient has not changed， and when both parties in the software supply chain have certain negotiating power， under the condition of bilateral moral hazard， there is an optimal loophole loss sharing contract and the optimal benefit ratio of both parties is equal to the ratio of their respective negotiating factors. When both parties in the software supply chain share information security risks， they can change the linear distribution ratio according to their respective cost structures to seek the optimal sharing of vulnerability loss costs for both parties. At last， based on the perspective of information security management， relevant management implications are given for software suppliers and its users.

The dual-channel marketing model integrating online and offline has become the best choice for fresh agricultural product suppliers. In practice， less capital becomes a huge challenge for supplier development. Some retailers within the supply chain offer financing services to suppliers. Therefore， some key questions must be considered： Which financing method should a supplier choose taking into account channel competition and fresh-keeping efforts？How the operational decisions of suppliers and retailers are changing？In response to these problems， a dual-channel supply chain consisting of a supplier with limited funds and a retailer is constructed. The supplier sells fresh agricultural products through two channels online direct sales and traditional distribution. In the distribution channel， suppliers wholesale fresh products to retailers， who then sell them to end consumers. In the online direct sales channel， suppliers retail products directly to consumers through online platforms and ease channel competition by sharing part of the direct sales profits with retailers.In order to obtain the optimal financing strategy， the equilibrium decision and optimal profit under two different financing strategies is obtained by constructing the Stackelberg game model. The analysis results show that： when the retailer's interest rate and the bank's interest rate meet certain conditions， choosing the internal financing model will make the supplier and the retailer a win-win； The transit time of fresh produce will only change the supplier's preservation decision， and will not affect the financing strategy； when the direct sales channel revenue sharing ratio is high， suppliers are encouraged to choose internal financing， but retailers are reluctant to provide financing services； consumers' preference for distribution channels will only affect retailers' financing strategies； Compared with the external financing model， under the internal financing model， the equilibrium decision-making of the supplier and the retailer decreases； capital constraints will reduce the supplier's income， on the contrary， it will have a favorable impact on the retailer. The research results of this paper have important management significance for fresh dual-channel supply chain enterprises.

Competitive enterprises are the microfoundation of high-quality economic development. A good business environment is an important guarantee for the high-quality development of enterprises， and high-quality development of enterprises requires high-quality asset structure allocation. However， many enterprises in China have asset structure mismatch problems， which not only limit the growth and development of enterprises themselves， but also may have a negative impact on the whole economic system. Based on this， listed companies in China's Shanghai and Shenzhen markets from 2010 to 2020 are taken as the research sample， and principal component analysis and entropy weight method are used to construct evaluation indexes for high-quality development of enterprises from the five dimensions of financial performance， market competition， technological innovation， social responsibility， and institutional innovation. Based on the five dimensions of investment and financing service environment， market innovation environment， government governance environment， human consumption environment， public service environment， etc.， use entropy weight TOPSIS model to measure the comprehensive evaluation index of business environment. It explores the impact of asset structure allocation bias， i.e.， asset structure mismatch， on the high-quality development of enterprises， and the moderating role of the business environment on the relationship between asset structure mismatch and high-quality development of enterprises.

It is found that， first， asset structure mismatch significantly reduces the high-quality development of firms， and the inhibitory effect of asset structure mismatch on the high-quality development of firms in the central and western regions is more pronounced than that of firms in the eastern regions， and the conclusion is still robust after a series of endogeneity treatments and robustness tests. This may be due to the fact that the economic development in the eastern region of China is faster， the performance， innovation ability and core competitiveness of enterprises are more stable compared with those in the central and western regions， and the infrastructure and cutting-edge technologies in the eastern region are more mature. The central and western regions， on the other hand， have a lower level of economic development， unstable enterprise development and backward industrial development. Second， the moderating effect shows that in the eastern region， the business environment plays a significant positive moderating role between the asset structure mismatch and the high-quality development of enterprises， while the moderating role in the central and western regions is not significant. This may be due to the fact that different regions have different levels of development， differences in entrepreneurial preferences and choices， and different government measures on optimizing the business environment. Therefore， there are differences in the effects of business environment. Third， the heterogeneity study shows that asset structure mismatch significantly reduces the high quality development of firms based on different life cycles. This may be due to the fact that regardless of the life cycle stage of an enterprise， asset structure mismatch leads to lower efficiency of capital utilization， which results in higher financial risks for the enterprise， and thus affects the sound operation and long-term development of the enterprise. The positive moderating effect of the business environment on non-state-owned enterprises is more pronounced than that of state-owned enterprises. This may be due to the differences in government intervention， political affiliation， administrative efficiency， rule of law environment， market access， and entrepreneurial activity allocation， etc. The positive regulatory effect of business environment on non-state-owned enterprises is more obvious than that of state-owned enterprises. In the manufacturing sector， business environment plays a significant positive moderating role， while in the non-manufacturing sector， the moderating role is not significant. This may be because the future development of the manufacturing industry relies on technological innovation， product quality and intelligent manufacturing， etc.， while the business environment helps to reduce transaction costs， stimulate enterprise creativity and market vitality， which is the key measure for the manufacturing industry to improve quality and efficiency and realize high-quality development.

In summary， the findings of the study provide empirical evidence for an in-depth understanding of the impact of asset structure mismatch on the high-quality development of enterprises， optimizing the asset structure of enterprises， optimizing the business environment， and enhancing the level of high-quality development of enterprises. For enterprises， it is important to comprehensively synergize the enterprise development strategy with the high-quality development strategy of the industrial chain， and strengthen the synergy between the asset investment strategy and the enterprise development strategy. Effectively plan the medium- and long-term asset structure allocation of enterprises， focus on the core business of industries， strengthen the asset structure allocation of emerging industries and future industries， and strengthen the integrated layout and investment guidance of asset structure allocation in key industries. For the government， strengthen regional cooperation and synergistic development as well as reform and innovation of diversified business environment. Formulate clear industrial policies and investment guidelines to guide enterprises to optimize their asset structure and avoid ineffective investment and overcapacity. Encourage enterprises to increase technological innovation and R&D investment， enhance core competitiveness， promote industrial transformation and upgrading， and promote high-quality development of enterprises.

With the development of e-commerce and the growing awareness of consumer traceability， it is common for suppliers to encroach on the market and improve product traceability to increase their profits. In addition market demand is uncertain，the retailer can obtain a signal and predict demand. Retailers can influence the above two operational strategies of suppliers through information sharing strategies. The impact of supplier encroachment on retailers is also more complex when considering product traceability.The following research questions are addressed. Faced with the threat of suppliers' potential market encroachment and traceability investment strategy， should retailers share demand forecast information with upstream suppliers， or under what circumstances should they share demand forecast information？ How will retailers' information sharing strategies affect suppliers' channel selection and traceability investment strategies？Aims to explore the interaction between the strategies of supply chain members， a two-echelon supply chain composed of a supplier and a retailer is considered as the research object， and the influence between retailer's demand forecast information sharing strategy， supplier’s market encroachment and product traceability investment strategy under uncertain demand information are analyzed. In the first stage， retailers decide whether to share the demand forecast information with suppliers before obtaining the demand forecast information. In the second stage， the supplier decides the level of product traceability and whether to encroach on the market. In the third stage， retailers obtain the demand information and follow the agreement in the first stage to share or not share the demand information. In the fourth stage， the supplier decides the wholesale price of the product. Finally， if the supplier encroaches on the market， the supplier and the retailer determine the quantity of their own sales channels at the same time， else only the retailer determines the number of distribution channels. There are four decision-making scenarios based on whether the retailer shares demand information and whether the supplier encroaches on the market， by comparing the equilibrium strategies and results under these scenarios.Some key findings are proposed. The supplier’s encroachment strategy is affected by the operating cost of direct channel and the retailer’s information sharing strategy， while the retailer’s information sharing strategy depends on the product traceability cost and the degree of competition between channels. In addition， the supplier’s encroachment strategy does not always impair the retailer’s revenue. When the product traceability cost and the degree of competition between channels meet certain conditions， the supplier's encroachment can increase the retailer's revenue， and as the accuracy of demand forecasting improves， retailer prefers supplier to encroach on the market， but the possibility of sharing information first decreases and then increases.

In recent years， E-commerce has continued to develop rapidly， and online shopping has become one of the most important shopping choices for consumers. However， with the rapid growth of E-commerce market and the expansion of the sales scale of E-commerce platform （such as JD.com， Amazon）， the problem of product returns is becoming more and more serious. Relevant studies show that the average return rate of E-commerce is as high as 22%. To address the above issues， a supply chain consists of one E-commerce platform and one manufacturer with product returns， the E-commerce platform marketing strategy selection and its influence are investigated.According to the consumers' uncertainty about whether the product meets their needs and the possible return behavior， the consumer utility function and the product demand function are established. Two supply chain game models are constructed in the presence of consumer return behavior， which are E-commerce platform provide marketing services and manufacturer provide marketing services. With the solutions， the optimal profit of supply chain and the equilibrium pricing， marketing effort， demands， are derived under different scenarios profits for each supply chain participant. On this basis， the optimal marketing strategy of the e-commerce platform and the optimal contract design of the manufacturer， and the impact of the choice of marketing strategy on supply chain equilibrium， consumer purchasing behavior， and consumer welfare are analyzed.The results show that， given a supply chain consisting of one E-commerce platform and one manufacture， the E-commerce platform is always motivated to provide marketing service， but at the same time， the E-commerce platform also need to adjust the level of marketing effort based on product return rate and residual value of returned product. Compared with the situation where the manufacturer provides marketing service， the marketing service provided by the E-commerce platform will not change the wholesale price， resulting in an increase in the number of product returns. Further， the effect of consumer return behavior on supply chain equilibrium is discussed. It is found that in the face of consumer return behavior， the E-commerce platform will increase the level of marketing effort as the residual value of returned products increase. The impact of consumer return cost on marketing effort depends on the residual value of returned product. In terms of optimal pricing， consumer returns may prompt the E-commerce platform to implement high-price strategy， which is always detrimental to the E-commerce platform， and may improve the manufacturer’s profit level and consumer welfare. Moreover， the product return rate will not be affected by the marketing service of the E-commerce platform， but will only affect the profit of the cooperation between the E-commerce platform and the manufacturer， as well as the loss of consumer welfare.Finally， the original model is further expanded from the manufacturer bearing the loss of product return， and the impact of the manufacturer bearing the return loss on the supply chain equilibrium is analyzed. It is found that， when the manufacturer bears the loss of product returns， the level of optimal marketing effort and the profit of each enterprise will change. In this case， the manufacturer can accurately know the residual value of the returned product， and there is no information asymmetry between the manufacturer and the E-commerce platform， so the manufacturer will be motivated to take the initiative to bear the loss of return. In addition， depending on the residual value of the returned product， the manufacturer will strategically increase or decrease the level of marketing efforts， but not necessarily to the benefit of the e-commerce platform.In summary， the problem of consumer return along with the rapid development of e-commerce， reasonable pricing， marketing and other decisions can not only alleviate the adverse impact of consumer returns on the supply chain， but also improve consumer welfare and reduce unnecessary losses. The theoretical analysis results obtained in this paper can provide a theoretical basis for the practice of E-commerce operation management.

Accurate prediction of carbon emissions trading prices is the basis for stabilizing the sustainable development of the carbon financial market. When analyzing carbon emission price forecasts， existing studies often use a single modeling approach to construct forecasting models， ignoring the characteristics of changes in carbon emission prices in different dimensions. Based on the coherent and year-on-year evolution characteristics of time series， these two traditional “unit processing” modeling ideas are defined as vertical processing and horizontal processing for the first time. At the same time， these two “unit processing” modes are combined into a “dual processing” mode through the idea of integration. Then an ensemble learning model is built based on the using of Empirical Mode Decomposition （EMD）， eXtreme Gradient Boosting （XGBoost）， Extreme learning machine （ELM）， Fractional Accumulation Order Seasonal Grey Model （FSGM）， Random Forest （RF） and their combinations Model. Then， 6 domestic and foreign carbon trading markets are selected as research objects， and Shenzhen Carbon Exchange is taken as an example to conduct special analysis. To verify the effectiveness of the proposed model， the prediction results of this model are further compared with Holt Winters （HW）， Support Vector Machine （SVM）， Long Short-Term Memory Network （LSTM）， FSGM， RF and EDM-XGB-ELM. The research results show that the prediction model proposed in this paper has better prediction performance than the benchmark model， and this modeling paradigm based on dual processing level also has good application prospects in other fields.