With the prosperity and development of the platform economy， problems such as online counterfeit sales， false information and piracy and infringement occur frequently on the platform. The government attach great importance to the problem of platform economic governance in our country， and have introduced a number of policy documents in order to balance the two important goals of “regulation” and “development”. As for platform economic governance issues， the focus of current academic studies is mostly focused on the emphasis on the implementation of a relatively strict and strong supervision mode for platform economy， and few scholars include “development” and “norms” into the research scope of governance strategy formulation， which makes it difficult for platform economic governance strategies to achieve in-depth promotion， moderate advance and orderly implementation. It failed to effectively promote the healthy and sustainable development of Chinese platform economy. Therefore， it has become a key topic to explore the role of both regulatory norms and development promotion policies in platform economic governance， as well as effective measures to give full play to the role of both policies. In this paper， evolutionary game theory and Markov chain method are comprehensively applied. Based on the stochastic characteristics of the state evolution of the platform economic governance game system， Markov transition probability matrix under the effect of equal emphasis policy is constructed. MATLAB is used to simulate the probability change trend of the system state after n-stage iteration， and the role of equal emphasis policy on the platform economic governance is explored. Then， according to the modified strategy of emphasizing the role of the policy， the correlation analysis of key parameters with Maple is carried out， and the countermeasures are proposed by comprehensively considering the conditions affecting the play of the role. The findings are as follows： the implementation of equal emphasis policy has a positive effect on platform economic governance， but at the same time， there is a risk of increasing the probability of illegal operation of merchants. Strict supervision by the government or active review by the platform to guide merchants to operate in compliance is an effective correction strategy to give full play to the role of both policies， and the correction effect is the best when both the government and the platform fulfill their duties. Keeping the efficiency of information transfer between the government and the platform and the probability of public reporting at a high level is an important direction for deepening the application of the policy of equal importance in the future. It provides a new perspective and method of analysis for future scholars to better explore the issues of platform economic governance in this study.

The “Asian premium” phenomenon in crude oil trade is a long-term unfair treatment for the economic development of Asia-Pacific countries， and the launch of Shanghai crude oil futures is a crucial measure for China to compete for the pricing right of international crude oil market. The pricing powers and their dynamic features of China’s crude oil futures and other three developed crude oil futures are quantitatively compared from the perspective of dynamic information spillovers among global crude oil futures and Asian crude oil spot markets， using a spillover index method based on the time-varying parameter vector autoregressive （TVP-VAR） model. Meanwhile， the impacts of COVID-19 pandemic on the pricing powers of various crude oil futures are also focused on. In order to enhance the robustness of our conclusions， the asymmetric spillover behaviors of crude oil futures market in the correlation systems of positive and negative returns are further distinguished. The empirical results show that， first， the crude oil system is still dominated by WTI and Brent crude oil futures， and the pricing power of China’s crude oil futures is generally weaker than those of three developed crude oil futures. While， China’s crude oil futures becomes more crucial to Asian crude oil spot markets after the COVID-19 outbreak. Second， the price-leading role of China’s crude oil futures in Asian crude oil spot is more susceptible to the COVID-19 pandemic than those of three developed crude oil futures. Different from acting a net information receiver of other crude oil markets before the COVID-19 outbreak， China’s crude oil futures also became a net information transmitter of Asian crude oil spot markets for a short time after the outbreak. Finally， even though there are significant impacts of COVID-19 pandemic on the information spillover intensity of oil system and its asymmetric feature， the spillover directions among these crude oil markets have not changed. At the same time， the tremendous effects of the pandemic on crude oil system are gradually absorbed within five months.

Human-induced operational risk is the operational risk directly caused by employees' misbehavior. It is the type of operational risk with the highest frequency and loss intensity in commercial banks. According to the difference in the initiative of misbehavior， the human-induced operational risk can be subdivided into human error risk and internal fraud risk. The nature and impact of internal fraud risk caused by employees’willful misbehavior are more serious，such as defrauding and embezzling property， or violating laws， regulatory rules， or internal systems.Researches pointed out that the key to optimizing operational risk measurement models and improving risk management effectiveness lies in the mastery of risk drivers. Therefore， it focuses on the formation mechanism of internal fraud risk in this paper， in order to provide theoretical support and basis for operational risk management. At present， there are few studies on the formation mechanism of internal fraud risk in the banking industry， but experimental evidence and theoretical explanations have been provided from the perspectives of institutional culture and colleague behavior. In addition， numerous studies on unethical decision-making provide evidence on individual psychological characteristics. Based on integrating the above characteristic factors， the scenario characteristic factor of internal fraud is introduced， and a systematic framework of the formation mechanism of internal fraud risk among employees in the banking industry is constructed.In this research， a randomized controlled trial is used to test this theoretical framework. Taking 244 employees of a commercial bank as effective samples， a random experiment in a completely unsupervised daily environment is carried out. The participants were randomly divided into three groups according to different decision-making scenarios to intervene with scenario characteristic.On this basis， mature scale tools are used to measure the personal psychological characteristics of employees and situational characteristics in the decision-making process， and a coin toss game is used to observe theinstitutional ethical culture. In addition， the actual misbehavior data of the bank's employees before and after the experiment are obtained based on the research project in cooperation with the bank.The research shows that scenario characteristic has a significant impact on the decision-making results and decision-making process of bank employees' internal fraud： the weaker the pressure employees feel in the scenario， the stronger the fraud intention； in different moral intensity scenarios， the impact of personal psychological characteristics and organizational environmental characteristics is different. The positive impact of personal psychological characteristics is more significant in low-intensity scenarios， and the inhibitory effect of organizational environmental characteristics， especially department culture， and the same group infection of colleague misbehavior are more significant in high-intensity situations.This research further enriches the theoretical research on the formation mechanism of operational risk， especially human-induced operational risk and provides a behavioral motivation explanation for the loss distribution characteristics of "low risk and high frequency" of operational risk in banking industry. In addition， the research conclusions of this paper provide a theoretical and empirical basis for commercial banks to implement key risk indicator tools， which will help commercial banks optimize operational risk measurement models and improve dynamic control technology. Moreover， management inspiration is provided for commercial banks to optimize the dynamic prevention and control mechanism of human-induced operational risk.

Since the central government proposed the motion of rural land transfer， the transfer of agricultural land has achieved remarkable results. However， there are still some areas where the transfer of agricultural land is in an inefficient， slow， and disorderly state. This is because there are different stakeholders in the process of farmland transfer， and whether their interest demands can be met affects the orderly transfer of farmland. Therefore， how to reasonably redistribute the interests of farmland transfer is the key to achieving the Pareto efficiency of the stakeholders.Since the interest demands of stakeholders are difficult to meet due to the imbalance in the redistribution of interests in the farmland transfer， the lack of effective pertinence of government policies has led to insufficient promotion results. As a result， the transfer of agricultural land lacks sufficient motivation， and stays an inefficient and slow situation in the long term. The SD（system dynamics） evolutionary game model of farmland transfer with the local government， the contractor， and the transferee as the tripartite players in the game is established. Based on the expected utility theory and Lyapunov's first law， the stability of the game players' strategies and the stability of the game system combination strategies are analyzed， respectively. Taking the national modern agricultural demonstration zone in Henan province as an example， the feedback regulation simulation analysis is carried out on the decision-making behavior of the tripartite game players. Data for the scenario simulations is mainly obtained from online consultation， Local Government Statistical Yearbook， Local Government Agricultural Survey Statistical Reports， Agricultural Price Survey Statistical Yearbook， Land Resource Network， China Agricultural Economic Information Network， and the academic literature. The results show that： The state of agricultural infrastructure and farmland transfer policies are the root causes of the different processes of farmland transfer in different regions， and the evolution track of game players is affected by the redistribution benefits of farmland transfer. However， ultimately the system evolves in an ideal equilibrium （promote， transfer-into， transfer-out）. The decision-making behavior of the contractor and the transferee plays a decisive role in the stability of the farmland transfer system， and the local government can effectively promote the process of farmland transfer by increasing transfer subsidies， providing technical support， and reducing transfer costs. In addition， increases in both wages from other jobs after transfer-out farmland and farmland rents are conducive to driving contractors toward the game strategy of transfer-out. For the transferee， the yield of farmland output is the main factor influencing its willingness to transfer-into. In the areas with high farmland output income， the government has little influence on the stability of the farmland transfer game system， while in the areas with low agricultural land output income， the transferee's willingness to transfer farmland is more sensitive to the government's promotion.Finally， according to the research conclusions， some management suggestions are giuen from the perspective of the government， which can provide theoretical and practical suggestions for promoting the orderly transfer of farmland and improving the agricultural modernization level in China.

Asset pricing explores the potential and latent factors that drive the prices of and returns on real and financial assets. In the big data era， asset pricing is influenced by many factors， such as high frequency market information， low frequency firm characteristic information and macroeconomic information. In this sense， typical mixed frequency data issue then arises. In addition， test assets play a critical role in the process of estimating pricing kernels. However， artificially constructing test assets to examine and optimize asset pricing models can not fully identify weaknesses in model pricing. How to efficiently capture useful pricing factors from multi-source heterogeneous information and achieve accurate asset pricing is valuable to practitioners， regulators， and academic researchers alike. To this end， the concept of mixed frequency stochastic discount factor （MF-SDF） is proposed through introducing a mixed data sampling （MIDAS） approach into the stochastic discount factor （SDF） theory. MF-SDF is used as a criterion function to construct a generative adversarial network （GAN） which solves the asset pricing issue under the mixed frequency data environment. Taken together， the proposed MIDAS-SDF-GAN model is able to handle mixed frequency data via the MIDAS approach and model the complex nonlinear pattern hidden in high-dimensional pricing factors through deep learning. It can employ the generative adversarial game mechanism to construct test assets， guiding itself to learn pricing patterns and continuously improve the pricing power in a data-driven way. All Chinese A-stock listed firms from January 2000 to December 2020 are chosen as our sample data and construct a large mixed frequency dataset containing 48 high frequency market variables， 153 low frequency firm characteristic variables and 11 low frequency macroeconomic variables. The data come from the CSMAR database. Then， the performance of the MIDAS-SDF-GAN model in asset pricing is empirically investigated. The results show that： 1） The MIDAS-SDF-GAN model is able to construct test assets in a data-driven way and guide itself to learn the pricing mechanism. It outperforms the other four competing models in both stock return prediction and investment profitability. 2） The MIDAS-SDF-GAN model is able to fully exploit information in mixed frequency data. It anchors the pricing basis through low frequency firm characteristic information and macroeconomic information， and optimizes the pricing accuracy through high frequency market information. These two types of information work together to improve the pricing effect. The study is an example of applying deep learning methods to the field of asset pricing. It is of great significance to solve the problems encountered in the process of asset pricing with the help of advanced artificial intelligence technology under the framework of financial theory.

While driving the rapid economic development， China's real estate industry is also showing a trend of rapid growth in housing prices. The long-term control mechanism to promote the stable and healthy development of the real estate market is still being explored. At the same time， after a round of rapid urbanization expansion， Chinese cities， especially large cities， have entered the era of "stock development" from "incremental development". Among them， urban renewal， as an important activity in the development of urban China， has become a hot issue of concern，and the 2019 Central Economic Work Conference also emphasized strengthening urban renewal and the improvement of existing housing. Therefore， does urban renewal play a role in restraining the rapid growth of housing prices？ More importantly， what is the mechanism of its influence？ Further， whether there are obvious differences between different cities？ What is the reason for the difference？ The answers to these questions will help us understand the role of urban renewal in regulating market economic activities. At the same time， it will also be an important decision-making reference for China to vigorously promote urban renewal and drive the direction of real estate transformation and upgrading policies in the future. As a pioneer and pathfinder of China's urban renewal and real estate market stock development， Guangdong’s “Three old regeneration” has become an important measure for urban renewal. Since 2009， when they received the pilot policy support for the “Three old regeneration”， cities in Guangdong have made certain achievements in integrating existing land resource elements， reshaping the vitality of urban functions， revitalizing existing low-efficiency land， and promoting industrial transformation and upgrading. effectiveness. It can be said that after more than ten years of policy innovation and practical exploration， the “Three old regeneration” has had an important impact on the urban renewal and real estate market of Guangdong Province.Therefore， the 2009-2019 urban panel data of Guangdong Province are used to study the impact of the “Three old regeneration” on the growth rate of urban housing prices in Guangdong Province based on the perspective of stock development.The results show that： ①the scale of the transformation of the “Three old regeneration” and the scale of old villagesregeneration has a significant negative impact on the growth rate of housing prices， indicating that the practice of the transformation of the “Three old regeneration” has restrained the excessive growth of housing prices to a certain extent； ②the transformation of the “Three old regeneration” and The inhibitory effect of the transformation of old villages on the growth rate of housing prices is spatially heterogeneous. Currently， it is more significant in non-Pearl River Delta regions than in the Pearl River Delta； ③The moderating effect shows that the higher the financial pressure on land， the less restrained the growth rate of housing prices； The higher the stock development motivation， the greater the degree of suppression of the growth rate of housing prices in cities.④ The mechanism test shows that the “Three old regeneration” has suppressed the growth of housing price growth by increasing housing supply and reducing the growth rate of local government land transfer income.Compared with the existing literature， the possible marginal contribution of this paper lies in the following two aspects. First， based on the perspective of urban stock development and China's unique urban renewal practice， the implementation effect of urban renewal is studied. Starting from the urban and regional scales， the macro effect of the “Three old regeneration” on the growth rate of housing prices in Guangdong Province is discussed. It complements other research scales on housing price regulation and expands and enriches the theoretical research on urban governance and real estate. Second， the existing research mainly focuses on case studies， and the relevant quantitative research is insufficient. Based on theoretical analysis， the impact of the “Three old regeneration” renovation practice on the growth rate of housing prices is further verified through empirical data and discusses in depth. Its moderating effect， intermediary effect， and regional heterogeneity not only help us understand the inner link between urban renewal and housing prices， but also answer the question of how to regulate the path of stable development of the real estate market to a certain extent. The government provides decision-making reference for promoting the steady development， transformation and upgrading of real estate by city-specific policies.

Performing public welfare functions is the basic duty and obligation of state-owned enterprises （SOEs）. Pursuing economic benefits is an important guarantee for SOEs to integrate into the international market， participate in international and domestic market competition and achieve sustainable development. It is an important issue faced by the mixed ownership reform of SOEs for how to improve the operating performance of SOEs by optimizing the ownership （including equity and control rights） structure between state-owned shareholders and non-state-owned shareholders under the constraint of public welfare functions. Relevant documents， such as the Guiding Opinions on Deepening the Reform of SOEs issued by the Central Committee of China Communist Party and the State Council in 2015， proposed measures to promote the mixed ownership reform of SOEs through classification and stratification. However， these documents lack strong theoretical and practical evidence support. It is of great theoretical and practical significance to clarify the effect mechanism of public welfare functions and ownership structure on operating performance of mixed-ownership SOEs from both theoretical and empirical perspectives for ensuring the sustained， stable and healthy development of SOEs.

Based on the in-depth investigation of interest distribution and control allocation between state-owned and non-state-owned shareholders in mixed ownership SOEs， an optimization decision-making model among state-owned shareholders， non-state-owned blockholders and executives is constructed to theoretically reveal the effect mechanism of public welfare functions and ownership structure on operating performance of mixed ownership SOEs. Then， the A-share state-owned listed companies in Shanghai and Shenzhen during 2010-2018 are selected as samples， and the operating performance of SOEs is measured by the market value， and the public welfare functions of SOEs is measured by the corporate social responsibilities， and the equity structure and control structure are measured by the degree of equity integration and the proportion of the number of directors， supervisors， and senior executives appointed by non-state-owned shareholders among the top ten shareholders to the total number of directors， supervisors， and senior executives， an empirical testing on the theoretical model results is conducted. The following conclusions are obtained. The public welfare functions undertaken by SOEs will present a significantly negative effect on the operating performance. Strengthening non-state-owned blockholder’s participation in the substantive corporate governance of SOEs and increasing the degree of equity integration between state-owned shareholder and non-state-owned blockholder can remarkably improve the operating performance of SOEs. It is achievable to improve the operating performance of SOEs by optimizing the shareholder ownership structure while keeping the public welfare functions undertaken by SOEs unchanged. This study provides theoretical evidence and implementation path for Chinese SOEs， under the constraints of public welfare functions， to optimize the equity structure and control structure and further promote the mixed ownership reform.

Based on the above theoretical and empirical research results， combined with the development status of SOEs and their mixed ownership reform goals， the following policy suggestions are put forward. First， the “stronger， better and bigger state-owned capital and SOEs” should always be the fundamental goal of the mixed ownership reform of SOEs. The mixed ownership reform cannot fail to be implemented due to the need to fulfill public welfare functions， nor can the so-called “national retirement and civilian advancement” be implemented due to pursue economic benefits. Balancing public welfare and operational functions is an effective way to promote the mixed ownership reform of SOEs. Second， in the process of mixed ownership reform of SOEs， it is not only necessary to improve the equity structure of SOEs by introducing non-state-owned shareholders， which formally achieves the goal of mixed ownership reform， but also to strengthen the substantive participation of non-state-owned shareholders in corporate governance， and effectively protect the right of non-state-owned shareholders to participate in operating decision-making， which essentially promotes the mixed ownership reform of SOEs.

In recent years， many NEV （new energy vehicle） manufacturershave collaborated with battery suppliers to vigorously promote the technology of NEV product. For example， in 2017， BMW signed a $117 million battery-production contract with Contemporary Amperex Technology Ltd （CATL）， the world largest battery manufacturers. After that， the CATL has signed several development and supply contracts with NEV manufacturers （such as， Toyota， Chang an et al.）. However， the stability of collaboration is challenged by the innovation cost， opportunity behavior and conflicts interest， which lead to a low innovation effectiveness.In view of the difficulties of the manufacturers and distrust with the suppliers in NEV supply chain， the shareholding strategy is introduced into the NEV supply chain. Considering whether the shareholding strategy is introduced and who holds share in the investments， the game theory and operational research optimization methods are embraced to develop the mathematical models for different scenarios. Firstly， a game model is built in which the manufacturers and supplier do not collaborate in innovation and this model is treated as a benchmark model for comparison. Secondly， a game model is adopted in which the battery supplier holds shares of NEV manufacturer. Then， a game model is developed in which the NEV manufacturer holds shares of battery supplier. Finally， the situation of NEV manufacturer and battery supplier hold share with each other is designed.In order to draw some valuable conclusions， the models are analyzed through numerical analysis， focusing on the relationship between the shareholding strategy and decision-making and innovation activities.Our findings show that the decision of boththe NEV manufacturersandbatterysuppliers is affected by the proportion of shares. In the longitudinal shareholding strategy model， the battery endurance and vehicle quality are positively affected bythe proportion of shares. Besides， both the wholesale price of the battery and the selling price are positively affected bythe proportion of supplier’s shares，and are negatively affected bythe proportion of NEV manufacturer’s shares. Furthermore， it is found that the supplier prefers the cross-shareholding strategy since he can gain more profit than that under the other shareholding strategies. However， for the manufacturer， he chooses the cross-shareholding strategy only when his shareholding ratio is low and the supplier's shareholding ratio reaches a certain level.

In order to investigate the issue of food and energy security in China， a cross-market “food-energy-finance” three-sector system is constructed to study the risk contagion within the system and outside the system， by using DAG， CoVaR， network topology and other methods. Research shows that the risk sources of domestic food and energy have changed from the original international dominance to a “Dual Circulation” dual-wheel drive since the end of 2019. And the risk contagion center within the food-energy-financial system has changed from the international crude oil market to the international agricultural product market and the domestic financial market with the development of the epidemic， so does the intensity and direction. Among many external shocks， the monetary policy of quantitative easing in the United States and the fluctuation of international commodities are the main external factors affecting the security of China’s food-energy-financial system. In accordance with the conclusions， this paper obtained provides a new basis for index selection in risk warning to forecast China’s food and energy security.

A common problem in the production and management of enterprises，especially retail enterprises， how to make reasonable purchasing and production plans to achieve the business objectives of enterprises， is studied in this paper. In addition to production，sales，inventory and other activities，paying dividends to shareholders and accepting capital injection from shareholders are also essential links of enterprises. It is of practical significance to formulate purchasing and production strategies with the goal of maximizing shareholders’ interests.On the basis of previous relevant studies，it is considered that enterprises operate a class of products，similar to the multi-cycle newsboy model. An enterprise controls the purchase or production and capital flow，adopts the barrier dividend strategy to pay dividends to shareholders at the end of each cycle，or accepts capital injection from shareholders when the amount of cash held is insufficient to pay the optimal production cost in the next period. In addition，it is assumed that the unit production cost of any period，the unit selling price of the previous period and the quantity demanded obey a joint distribution. In this paper，a discrete time Markov decision model is proposed to maximize the future cumulative expected discounted returns of shareholders，the aim is to find the optimal production strategy and the corresponding optimal value function. Under the condition that the assessment period is limited，the iterative relation satisfied by the optimal value function is given by the formula of total expectation. When the assessment period is unlimited，the Bellman equation satisfied by the value function is given，and the optimal value function is proved to be the only solution by the contraction mapping principle.Finally，a numerical example is given according to the method provided in this paper，and the results mainly provide the following information： 1） When the duration of the assessment period is limited，the optimal production strategy of each period which is far away from the expiration time basically remains unchanged. When other conditions remain unchanged，the optimal production of each period shows a monotonous trend with the increase of the initial inventory. When the inventory reaches a certain value，the production is 0，indicating that the inventory should be sold first and no reproduction is needed. 2） When the duration of the assessment period is unlimited，the value function of a finite assessment period with sufficient length can approximate the optimal value function of the infinite case. The length of the finite assessment period can be calculated when the error is given. 3） No matter the assessment period is finite or infinite，the value of the optimal value function is affected by the dividend barrier，and the decision maker can adjust the dividend barrier appropriately to achieve the optimal state.A decision method for enterprises is provided，and the research on enter prise decision making is enriched.

The problem of battery electric bus （BEB） charging scheduling is investigated in this study. The problem stems from the large-scale popularization and application of BEBs in especially Chinese urban areas， which bring unprecedented challenges to the current bus operation scheme. It is a very necessary and urgent task to accordingly solve the corresponding scheduling optimization problems emerged due to the application of BEBs. The charging scheduling of BEBs is taken as the research perspective， which aims to provide an efficient and minimum cost charging schedule to meet the electric power demand of BEBs in their daily operations. The BEB battery damage cost is described by analyzing the optimal fluctuation range of the battery state of charge （SoC）. The feature of peak-valley electricity price in the time horizon of a full day is furtker depicted. It is mainly observed that in the BEB charging activities， one battery actually needs not to be charged to 100%of SoC， while a minimum percent of SoC after charging is required so as to satisfy the power demand in the next day operation. Therefore， the amount of SoC being charged， which is called the task completion degree in this work， during one BEB charging activity becomes a critical variable in the considered problem. It differs from the classical scheduling problem in which tasks have to be fulfilled to 100% to be satisfied. It is assumed that all the BEB chargers in the charging field are identical in this work. Based on the above analysis and assumption， the considered problem is formulated as the identical parallel machine scheduling problem with controllable task completion degree. A mixed integer linear programming （MILP） model is established with the objective of minimizing the total operation cost， which consists of the cost of power consumed and the BEB battery damage cost. For small-scale instances of the considered problem， exact solutions can be obtained by solving the MILP model via commercial solvers such as CPLEX. For solving large-scale instances， an immune optimization algorithm based on random key coding and a greedy heuristic algorithm based on the idea of avoiding peaks and filling valleys are developed. The correctness of the MILP model is verified by solving small-scale instances in the numerical experiments. The effectiveness of the proposed algorithms is revealed by a case study based on a real public transport network in Shanghai and experimental results for large-scale instances. Numerical results show that the optimal charging scheduling scheme can save about 7.08% of operation costs for bus companies. Moreover， the random key immune algorithm proposed in this work has the potential to be applied in large-scale BEB charging scenarios.

In this paper， the problem， what are the characteristics of a blinding agreement for forming a stable grand coalition， is studied Based on a situation of small Non-Truck Operating Common Carriers cooperating by shipment consolidation， after considering the complicated scenarios such as transport capacity， freight spot market price， penalty of waste capacity， etc.， a cooperative game model is formulated under the typical time policy. Different from other research， the designed characteristic function is a piecewise function whose non-differential point changes as the difference of formed coalition. The departure strategies under the typical time-based policy will be further refined to the four consolidation strategies. The research shows that Full-loaded transportation is not always optimal， and under-loaded transportation may be optimal. The impacts of key parameters such as the freight spot market price and the penalty of waste capacity on decision-making are further explored， which shows when no other parameters are considered， then strategy I and strategy III are directly related to the penalty of waste capacity. The feasible range of the penalty of waste capacity is also discussed. With the increase of the transport spot price on decision-making. The trajectory of the final decision is changed from Strategy IV to Strategy II to Strategy III. The game is not necessarily subadditive， and the formation of the grand coalition is also more complicated. Finally， from the perspective of myopic and farsightedness， the stability of the grand coalition is studied.

With the development of social network technology， trust relationships among experts bring new opportunities and challenges to the consensus research of group decision making. Due to the inherent risk of trust， experts may be blindly trusted or lack due trust in decision-making process， which will cause risk issues affecting decision and make it more difficult to reach a scientific and reliable consensus. Therefore， based on experts’ behavior mining， the trust risk in social network group decision making is linked with the scientificity and reliability of the decision result， and a consensus model is proposed for social network group decision making considering experts’ trust risk behaviors mining and dynamic management to reduce the decision risk， improve the credibility of decision result and consensus efficiency. Firstly， based on social network and experts’ credibility， the trust risk behaviors mining， measurement and dynamic management mechanism is designed. Secondly， the information aggregation driven by the comprehensive influence of experts， consensus measure and feedback adjustment mechanism are constructed. Finally， the maximum/minimum thresholds of experts’ risk index and the threshold of group risk level are obtained by Monte Carlo simulation， the rationality and validity of the proposed model are demonstrated， and it is applied to the cooperative research between automobile enterprises and laser display technology companies to assist actual decision-making and enrich the consensus research of social network group decision making.

The operation of self-produced content of an online video platform is studied， who engages in a three-stage game with an embedded ads sponsor， involving decisions of embedded ads price， embedded ads quantity， consumer subscription fee， and pre-roll ads quantity. The game is analyzed and compared under two different pricing modes of the embedded ads， i.e.， CPT （cost per time） and CPM （cost per mille）. The results show that when the revenue rate of the embedded ads sponsor is below certain thresholds， the platform under both CPT and CPM only places pre-roll ads； otherwise， the platform will place both embedded ads and pre-roll ads under CPT， while only places embedded ads under CPM. Comparisons show that CPT and CPM are equivalent when the revenue rate of the embedded ads sponsor is low； otherwise， the CPM mode leads to higher price and quantity of embedded ads， lower subscription fee and pre-roll ads quantity， and higher platform profit and consumer utilities. The embedded ads sponsor prefers CPM when its revenue rate is moderate and prefers CPT when its revenue rate is high.

Conducting targeted mass screening and allocating limited pharmaceutical resources accurately and timely to in different regions is of great importance for epidemic control， especially in a sudden large-scale epidemic outbreak involving asymptomatic patients. Based on the practice of emergency management in COVID-19， a new problem， namely， joint multi-period mass screening and pharmaceutical resource allocation in the epidemic outbreak， is proposed. It is a sensing and control problem of spatial-temporal dynamic network with uncertain transmission parameters， non-stationary transmission dynamics， and partially observable system state. To solve this problem， a data-driven optimization approach using the data of periodically diagnosed cases for the decision-making process is proposed， which combines stochastic programming and rolling-horizon optimization methods. By learning the new arrival data， the uncertain parameter space is continuously reduced and can be expressed as an empirical probability. Then， the epidemic detection and pharmaceutical resource allocation problems are formulated as stochastic dynamic programming problems， which are solved by the rolling horizon optimization method. Finally， an environment interaction simulator is established to verify the superiority of the proposed data-driven decision-making approach over the existing practical decision-making method， and the effectiveness of resource allocation strategies under different resource-level constraints as well as decision-making preferences are discussed. The main findings of our study that can offer policy insights for public sectors include the following four folds. First， implementing large-scale mass screening at the early stage of the epidemic outbreak plays a great role in improving the efficiency of epidemic control and reducing the total number of infections. Second， given an intervention budget， increasing the mass screening scale has a larger marginal effect on improving the efficiency of epidemic control than increasing the amount of pharmaceutical resources. Third， when the intervention resources are sufficient， a more exclusive decision-making preference can help reduce the total infection， while a more inclusive decision-making preference can improve the economic efficiency of resource utilization. Fourth， when intervention resources are in shortage， making decisions moderately with a slightly tilting to some severely infected areas can achieve a good performance in both humanitarian and economic efficiency. An online decision-making framework and optimization approach are provided for resource allocation of public health management departments in epidemic outbreaks. By introducing the corresponding mechanism model and data， the proposed approach can provide epidemic mass screening and pharmaceutical resource allocation decision support for other large-scale epidemic outbreaks （such as H1N1， and Ebola）.

The evaluator's emotional behavior belongs to recessive behavior， such as the degree of worship and love of the evaluated object， which is difficult to quantify. Even the emotional behavior data obtained through a questionnaire survey may be difficult to distinguish between true and false. Aiming at the problem that it is difficult to quantify intangible emotional behaviors in the field of non-self-participatory group evaluation， an objective filtering method for group evaluators’ emotional behavioral data is proposed using the idea of probability.Firstly， in the case of insufficient or unavailable data in the early stage， it is almost impossible to realize and convince the absolute recognition of the existence or nonexistence of intangible emotions. Therefore， the emotional behavior probabilities of the evaluators are calculated based on the absolute， relative， and variation dimensions， so as to filter the data. Secondly， there are relatively many subjective factors involved in emotional behavior data filtering， which will make it challenging to obtain the evaluator's true value in the method verification process. Thus， the random simulation algorithm is used to generate the virtual real value of the evaluators， and the emotional behavior of the group evaluators is inversely verified and analyzed. The trend of the verification parameters in different situations is counted to demonstrate the reliability and effectiveness of this method. Finally， an example of performance appraisal is given to solve the above research content and explain its feasibility.The main innovation and application value of this study are reflected in the following aspects　（1） The original data that cannot determine the existence or nonexistence of emotional relationships is directly converted into the form of emotional probability. And the comprehensive probabilities of the evaluator's possible emotional behavior from multiple dimensions are analyzed to achieve emotional filtering of the original data. （2） Considering that the real value of the evaluation is difficult to obtain， the random simulation method is used to generate the virtual real value of the evaluators to improve the effectiveness and feasibility of the reverse simulation analysis. （3） This method is an objective optimization method， which is easy to operate and does not need other subjective data intervention. It can be used to quickly solve such problems， guide the evaluation makers to design a more scientific evaluation process， and obtain more accurate evaluation conclusions.

Disasters can easily damage the functionality of urban transportation infrastructure and even create the risk of systemic paralysis， thereby compromising its important role in urban operation. Therefore， it is necessary to study how to improve the post-disaster resilience governance. Existing research mainly focus on the single-agent decision-making of the government or operating companies， and limited consideration has been placed on the public （e.g.， their participation， cooperation and bargaining）. The disaster factors and public participation are incorporated into the decision making of transportation infrastructure’s post-disaster resilience governance， a dynamic game model is constructed for government and operating companies， and the effects of such a resilience governance structure and improvement strategies is discussed under different resource constraints. It is found that： （1） public scrutiny and government incentives are conducive to improving resilience， but in the case of a high disaster level， the effect of government incentives is reduced； and （2） government incentive policies and the operating company’s resilience governance plans should be adjusted according to resource constraints， namely， when resource constraints are too strict， incentives may fail. The interactive influence of multi-agent decision-making behavior and its impact on the post-disaster resilience level is revealed in the context of transportation infrastructure， and thus a robust decision-making underpinning for transportation infrastructure’ post-disaster resilience governance is provided.

Choosing an appropriate recycling model is the key to achieving standardized recycling of waste power batteries. According to the recycling technical route of waste power battery： recycling- echelon utilization- material recycling， a Stackelberg game model with the main recycler of a new energy vehicle（NEV） manufacturer， a power battery（PB） manufacturer and a third-party recycling enterprise respectively is constructed to solve the optimal decision and optimal profit of this three recycling models. Besides， the effect of recycled material revenue on the choice of recycling model and the carbon emission of the closed-loop supply chain system is discussed.The results show that from supply chain perspective， as recycled material revenue is below a certain threshold， when NEV manufacturer becomes the recycler is the optimal recycling model， otherwise， when PB manufacturer becomes the recycler is the optimal recycling model. Meanwhile， different recycled material revenue will lead to inconsistent choices of recycling models among supply chain members， so that coordination of supply chain profit is required to achieve a long term and consistent optimal recycling model. Moreover， when the carbon emission efficiency of power battery recycling technology is high， the optimal recycling model corresponds with the lowest carbon emission， otherwise， the optimal recycling model will cause carbon emission burden.The findings of this paper provide a reference for power battery closed-loop supply chain to select the optimal recycling model and it can also assist the government to formulate subsidy policies for the material recycling chain.

In the process of diagnosis and treatment service for different types of diverse patients， how to achieve rapid intelligent diagnosis according to the patient’s condition is a new challenge and frontier problem in medical services. Based on this， the complicated and varied diagnosis information and diagnosis process of patients are analyzed， then an intelligent diagnosis and treatment decision method that considering the multi-source behavior fusion information generated by patients is proposed in this paper. In the proposed intelligent diagnosis decision method， the attribute diversity of different types of patient diagnosis and treatment information is considered， and a distance measurement method considering different types of attribute features is defined. Then， on the basis， a rough set attribute weight determination algorithm based on similarity measure is used to calculate the weight of each attribute. Further， the similarity measurement and consistency test of attributes are combined to compare and analyze the information of target patients and historical patients. According to the similarity value obtained by quantitative calculation in the reasoning process， the most similar case to the target patients can be obtained， which can help doctor give accurate treatment plans. Finally， the validity and feasibility of the proposed method are verified by UCI heart disease data from Cleveland data set.

A supply system is studied in which the government， core suppliers and node suppliers jointly reserve emergency supplies.On the basis of establishing the principal-agent relationship between government and enterprise， two forms of cost sharing contract are proposed： （1） Reserve cost sharing contract， which is a kind of classical cost sharing mechanism， that is， the dominant core supplier in the supply chain unilaterally shares part of the reserve cost of the node supplier； （2） Bilateral cost-sharing contract with revenue sharing， that is， core suppliers share fixed proportion of reserve revenue and reward and punishment revenue with node suppliers， and at the same time， two suppliers share certain proportion of reserve cost for each other， forming a two-way subsidy mechanism.By means of differential game， the optimal decision-making strategy of government and enterprise is deduced. Finally， combined with numerical simulation， the differential effects of purchase price and other parameters on equilibrium strategy and Fed inventory under two contract forms are investigated， and some management implications are obtained. The results show that：（1） Compared with the classical CS contract with unilateral compensation mechanism as the core， RS&BS contract enables the government to have a larger range of executable purchase price by introducing revenue sharing and bilateral compensation mechanism；（2） The cooperation form of suppliers will also reverse the government's pricing strategy. Under THE RS&BS contract， the sharing strategy of the core supplier only depends on the revenue distribution within the supplier， while under the CS contract， its sharing strategy is restricted by the external purchase price.（3） CS contract and RS&BS contract have their own best application scenarios. The CS contract can increase the quantity and reserve efficiency of the Fed's inventory. RS&BS contracts are more helpful in keeping inventories at a stable and safe level.

Emergency materials allocation is the prerequisite guarantee for local governments to cope with major public health emergencies. Due to the escalating pressure of epidemic prevention and control and material allocation， decision-makers face the problem of choosing and changing the mode of material allocation. Materials allocation within the territory and the coordination of materials allocation in internal and external provinces and cities are the two main modes to solve the above problems. In this paper， based on the disease transmission rate and the prevention and control level of public health emergencies， the differential game model of dynamic on-demand supply is constructed for two modes of internal allocation and coordinated internal and external allocation. When the demand for fixed materials exceeds the critical value， coordinating internal and external allocation is more advantageous. When the demand for fixed materials is less than the critical value or the cost of external provincial and municipal assistance is greater than the critical value， the internal allocation mode is advantageous. Local governments in disaster areas choose the most appropriate material allocation mode according to specific situations， such as the demand for fixed materials in disaster areas， the proportion of materials allocated within the territory， and the critical point of external provincial and municipal assistance costs. Finally， combined with the case study of material allocation in Wuhan and Xi 'an， a cross-comparison analysis of single factor and double factor is conducted to analyze the total effectiveness of the two deployment modes to provide decision support for the overall allocation and rapid response of materials in significant public health emergencies.

The uncertainty of the products’ real quality in online shopping makes the issue of product return in online shopping increasingly complex， and more and more products are sold in multiple stages. Considering the influence of early comments on the subsequent stage of product sales and returns， it is necessary to study the joint decision of online sellers' pricing and ordering in the case of flawless returns. Online sellers sell their products in the daily sales stage and promotion stage， online sellers plan to adopt comment improvement strategies to beautify the product comments so as to improve the consumer's initial value perception in the next stage. Consumers decide whether to buy a product according to the initial value perception， and make favorable comments， negative comments， or return processing according to the perceived differences.Based on the initial value perception of consumers before purchasing products and the perception differences after purchasing， a joint probability density function model of consumers' initial value perception and perceived differences is constructed. Combined with the different behavioral characteristics of consumers in the daily sales stage and promotion stage， the purchase probability，positive（negative） comment probability and returns probability of consumers in the daily sales stage are given.At the same time， the sensitivity of consumers to positive and negative comments is integrated into the model construction， considering the impact of consumer comments in the previous stage on consumers' initial value perception of products in the next stage， the purchase probability and return probability of products in the promotion stage are obtained. The newsboy model is used to build two-stage expected profit models under different comment improvement strategies for online sellers to determine product prices， price discount rates and order quantities. Then， the influence of comment improvement strategy on sellers' optimal decision and profit under stochastic demand is studied by numerical analysis. The results show that： the increase in the effort level of praise encouragement will increase the sales price and discount rate， the increase of the cashback amount of positive comments will reduce the optimal pricing slightly， and the commodity discount will increase first and then decrease. The improvement strategy will make the discount rate tend to be stable under different parameter values. The optimal order quantity in the promotion stage is positively correlated with the effort level of praise encouragement， while the optimal order quantity may increase or decrease with the cashback amount.The pricing and ordering decision of a seller who sells products in two stages under different comment improvement strategies is studied.Considering the uncertainty of product demand， the influence mechanism of comment improvement strategy and consumer return on the optimal decision is analyzed， which provides a new perspective for the study of comment improvement strategy and returns.

In recent years， with the improvement of living standards， consumers are increasingly requiring the quality of fresh agricultural products. Fresh agricultural products have the characteristics of short shelf life and easy corruption. At present， the supply chain management system of fresh agricultural products is not perfect， and the freshness-keeping consciousness and cooperation consciousness of each member are weak. Therefore， it is necessary to improve the freshness of agricultural products， reduce the quantity loss of products and increase the profit of the supply chain. It is necessary not only to invest in freshness-keeping efforts， but also to design reasonable and effective contracts to ensure the cooperation between supply chain members. In order to solve the above problems， the coordination and optimization strategy of a two-echelon fresh agricultural product supply chain are researched in this paper.Firstly， aimed at reducing the loss of quality and quantity of fresh agricultural products， the freshness-keeping effort is introduced to characterize the retailer’s freshness keeping work. The expected profit models of retailers and manufacturers under decentralized decision-making and centralized decision-making are constructed respectively， and the optimal decision-making problem of retailers is studied. It is concluded that the profit maximization of supply chain members cannot be realized under decentralized decision-making. Therefore， the option contract is introduced to coordinate the supply chain. Further， in order to encourage the manufacturer to accept the contract， a profit distribution contract is designed to realize the benefit sharing of both parties. Finally， the conclusions of the model are verified by numerical simulation， and the effects of the freshness-keeping effort， option price and exercise price on supply chain decision-making and coordination are analyzed.The results show that under different situations， the freshness-keeping effort has a critical value. When less than the critical value， the retailer's profit is proportional to the freshness-keeping effort. When more than the critical value， the retailer's profit is inversely proportional to the freshness-keeping effort. Under the option contract， compared with the decentralized decision-making， the retailer's optimal order quantity is increased， the optimal price is decreased， the retailer's profit is increased， the manufacturer's profit is decreased and the total profit is increased. Compared with the centralized decision-making， the retailer's optimal total order quantity， the optimal price and the total supply chain profit are increased. When the option price satisfies certain conditions， the total profit of the supply chain under the option contract is equal to the total profit under the centralized decision-making， then the perfect coordination of the supply chain is achieved.From the practical perspective， the combination of option and fresh agricultural products supply chain could better meet the needs of agricultural modernization and risk management. Option contract could better fill in gaps in other contracts， so that the manufacturer and the retailer cooperate more closely， which has practical guiding significance for the risk control of fresh product supply chain.

The rapid development of e-business（EB for short） requires EB companies to respond to consumer requirements quickly， in order to improve their efficiency of customer services， more and more EB companies have deployed distributeddistribution center systems. A main problem with using this system is that improper commodity warehouse allocation may result in a large number of orders being divided into multiple sub-orders， which not only causes inconvenience to customers， but also increases more operating costs to companies. Addressing to this problem， a commodity warehouse allocation model aimed at minimizing the total number of split orders is proposed. The model is based on a hypergraph representation of historic orders， where each vertex corresponds to a distinct goods appearing in the orders， and each hyperedge describes a co-occurrence relation of goods in a same orders. The spectrum decomposition on the Laplace matrix of the hypergraph is performed to obtain the embedding representations of the goods， then a constrained clustering algorithm is proposed and is applied to the above embeddings to generate the allocation results. The comprehensive simulations is conducted to evaluate the proposed model， where LDA （Latent Dirichlet Allocation） with variant parameter settings is used to simulate different ordering behaviors， and the proposed model as well as some other comparison models is applied to generate the allocation results from the data.All experimental results show the superior of our model.

A comparative analysis of different behavioural pricing strategies is conducted for green product supply chains （GPSCs）. It is assumed that there are two types of consumers with different preferences for green products in the market. A two-stage game model of GPSCs and non-GPSCs under three pricing strategies is constructed and the impact of different pricing strategies on GPSCs is compared. It is found that behaviour-based pricing （BBP） can promote the improvement of the level of greenness and that the growth rate of the level of greenness is the fastest under the strategy with retailer BBP. Under each BBP strategy， the pricing strategy for green products in different sales stages is affected by factors such as the rate of consumers with no difference in preferences， the cost coefficient of the level of greenness， and the sensitivity coefficient of the level of greenness. BBP is beneficial for improving the profit growth rate of green product retailers with a decrease in the rate of consumers with no difference in preferences.

In the bidding stage of PPP projects， some investors who lack sufficient strength and are unable to promote project efficiency improvement deceive the government through disguised means in order to obtain project franchise rights. This opportunistic behavior is called adverse selection. Once adverse selection by investors occurs， it can damage project performance and social benefits， and in severe cases， lead to the phenomenon of “bad money drives out good money” in the PPP project market. This will greatly hinder the sustainable development of the PPP model. It is necessary for the government to address the issue of adverse selection.Therefore， a signaling game model between government and investors is constructed. And the separation equilibrium conditions that reveal the investor's true capabilities are calculated. The results show that there is the optimal range of profit rate to satisfy the separation equilibrium conditions. Investors will choose to quote truthfully if and only if the profit rate set by the government is within the optimal range. In addition， considering the scenario that investors’ competition， the strategy of investors is compared in different scenario. The results show that competition among investors has no absolute positive or negative influence on the formation of separation equilibrium conditions. Only when the government's reputation loss is small enough， the competition between investors with different abilities will be conducive to the formation of separation equilibrium. Otherwise， the existence of competition with different abilities reduces the upper limit of the profit rate given by the government， which is not conducive to the formation of separation equilibrium in the market.Finally， this paper uses actual data from the Bazhong to Wanyuan Expressway in Sichuan Province as a case study to verify the effectiveness of the conclusions drawn. The research of this paper can provide theoretical basis and decision-making reference for the mechanism design of the government to correctly identify investor capability information in the bidding stage.

In recent years， with the continuous improvement of economic and social development level， China has become the world's largest manufacturing base and consumer of home appliances. With the continuous expansion of China's household appliance market， the problem of waste household appliance recycling has become increasingly prominent. Under the dual carbon goals of “carbon peaking” and “carbon neutrality”， it is an important way to encourage production enterprises to implement the recycling target responsibility system， which can help home appliance companies achieve the dual carbon goals. At the same time， the implementation of trade-in strategy can make a good connection between the sales end and the recycling end， so providing trade-in service is an important way for manufacturing enterprises to achieve the recycling goal. However， in the context of the recycling target responsibility system， on the one hand， the decisions of new product production and old product recycling in the supply chain will be greatly affected when the collection target is constrained； on the other hand， the decision problem of trade-in strategy in the supply chain is changed from who should carry out the trade-in strategy to how should the manufacturer carry out the trade-in strategy. Based on this， the optimal decisions of closed-loop supply chain under the recycling target responsibility system and the manufacturer's trade-in strategy selection are studied in this paper.First， a closed-loop supply chain consisting of a manufacturer， a retailer and a recycler is considered in the paper. Then， based on the recycling constraints imposed on the manufacturer by the target recovery rate， the following three scenarios are explored： the manufacturer implements the trade-in service， the manufacturer outsources the trade-in service to the retailer， and the manufacturer outsources the recycling of the used product in the trade-in service to the recycler. In order to meet the actual situation， the model of wholesale price of new products and transfer price of old products is adopted when the manufacturer outsources the trade-in service to the retailer， and the commission model is adopted when the manufacturer outsources the recycling of old products in the trade-in service to the recycler. Third， three constrained Stackelberg game models are constructed， and the game equilibrium solutions of these models are obtained by backward recursion method and KKT conditions. Finally， the game equilibrium solution and the profit of supply chain members under different models are compared and analyzed， and the feasibility and robustness of the model are verified by numerical simulation.The research conclusions obtained are as follows　First， when the recycling target responsibility system is implemented and the value of the target recycling rate is greater than a certain threshold， the profits of the manufacturer， retailer and supply chain all show a rapid decline in the three trade-in models. That is， even if the fixed costs involved in recycling old products are negligible， recycling target responsibility system is always bad for the supply chain and its members. Therefore， it is necessary for the government to reduce taxes or provide subsidies to encourage enterprises to achieve the recycling target. Secondly， for new customers， if there is no target responsibility system for recycling or the target recovery rate is small， it is most advantageous for manufacturers to outsource trade-in to recyclers； otherwise， it is most advantageous for manufacturers to implement trade-in. For existing customers， it is always in the best interest of the manufacturer to implement a trade-in， and it is always the worst for the manufacturer to outsource the trade-in to a recycler. Finally， from the perspective of supply chain performance， when there is a recycling target responsibility system， the optimal trade-in strategy is for manufacturers to implement trade-in. When the manufacturer is reluctant to implement a trade-in strategy due to the large fixed investment cost， the retailer can bear part of the cost for the manufacturer to benefit all supply chain members. The research conclusion of this paper can provide management suggestions for manufacturing enterprises affected by the recycling target responsibility system to achieve the recycling target and improve corporate profits.

Under the multi-agent network cooperative innovation mode of cross-domain and cross-border， the embedded risk is accompanied by the whole process of technological innovation network evolution， which restricts the stable operation of innovation network. The patent cooperation data of China ' s new energy automobile industry from 2009 to 2020 are used to construct the industrial technological innovation network， and the evolution of technological innovation network is divided into three stages based on patent statistics and industrial key policies. Starting from the two embedding dimensions of structure and relationship， and further considering the cascading failure process of relationship embedding， the changes of innovation network structure and function under embedded risk are simulated and analyzed. It is found that the structural embeddedness of large group enterprises and enterprises in monopolistic resource industries is easy to cause embedded risks， which have strong destructive effects on the network structure of industrial technological innovation. The network structure evolves rapidly from integration to fragmentation， and the evolution speed gradually accelerates with the highlighting of the network ' score-periphery ' structure. The structural embedding behavior of enterprises in the industrial chain has a promoting effect on the stability of innovation network， and gradually increases with the emergence of network ' periphery-multi-core ' structure； the relational embeddedness behavior of innovation subjects helps the evolution of innovation network structure from simple looseness to loose coupling， and strengthening the governance of weak relations in the network can promote the stability of industrial technology innovation network.

The transformation of the energy economic system is the key to carbon neutrality， and the contradiction between the requirement of carbon neutrality for economic transformation and its requirement of energy system transformation is an urgent issue that needs to be addressed at present.A computable general equilibrium （CGE） model is developed to analysisthe impacts of different low-carbon policies on China's energy consumption and power generation structure in the long run. In order to characterize the energy system in China， the model in this study is enriched by endogenous technology improvement of renewable energy and substitution of different power generation technologies based on a Logistic model. The results show that while the carbon pricing and renewable energy subsidy policies have different advantages in realizing decarbonization of energy system and short-term optimization of energy structure，the combination of the two policies has lower macroeconomic costs and more significant effect on carbon emission mitigation than a single policy. The results indicate that it is difficult to achieve carbon neutrality only by the decarbonization of the energy system， and the difficulty in achieving carbon neutrality in the later period of 2020-2060 will mainly exist in the basic industrial sectors and the transportation sector.