The fact that most assets are not traded around the clock raises a natural decomposition of the daily return. The intraday return covers the price movement between open and close， while the overnight return covers the price movement between the previous close and current open. Previous literature documented that overnight information has a significant impact on financial activities. It can help explain the market anomalies and improve the volatility forecasting accuracy. However， there is little research investigating the effects of option pricing. In this paper， the daily log returns are decomposed into intraday and overnight components and a new model that extends the Heston-Nandi GARCH framework to a bivariate structure is proposed to describe the two return processes simultaneously. Such decomposition is different from those with high-frequency data （such as semivariance-based good-bad volatility framework） as we only require daily frequency data. Using the variance-dependent pricing kernel， a closed-form option pricing formula is derived and the pricing performance of SSE 50 ETF options is assessed. The empirical results using SSE 50 ETF options from 2015 to 2019 show that distinguishing the overnight component from daily returns can potentially reduce the pricing errors， both in-sample and out-of-sample. The results enrich the current literature on return decomposition by adding a piece of option pricing evidence and call for more research on option pricing in this new direction.

A supply chain is typically characterized by mutual benefit and risk sharing based on member coordination and the integration of material flow， fund flow， and information flow. Engaging in supply chain cooperation may have an impact on firms in both positive and negative ways. Many empirical studies explore the effects of various supply chain characteristics on a firm’s default risk； however， few of them have investigated the relationship between relationship-specific investment （RSI）， bargaining power， and a firm’s default risk. RSI could intensify the supply-chain relationship， decrease production and operation costs， and increase the profit of the whole chain. Nevertheless， bargaining power determines which party takes more profits and which party takes more risks. Firms with little bargaining power only get a small share， but even so， they must commit to RSI. In this circumstance， they will suffer a high lock-in risk of RSI and face more uncertainties in cash flow management. Accordingly， their profit margin may fall over time， capital turnover may slow down， and default risk may increase to a relatively higher level. It focuses on a supply chain with N upstream firms and M downstream customers and a structural framework is built to study the impact of a supplier firm’s RSI on its debt default risk. It first models the supply decision of upstream firms， the demand decision of downstream customers， and a supplier firms’ optimal RSI decision. It also defines an upstream firm’s bargaining power as its capacity to get the RSI-induced surplus， and a customer’s bargaining power as its capacity to force upstream firms to reduce the basic price. Then， it estimates a supplier firm’s equilibrium profit and develops a profit-flow-based structural approach to quantify its debt default risk. Finally， it makes numerical simulations in different market environments and alternative competitive scenarios and evaluates the influence of a supplier firm’s optimal RSI and the bargaining powers of both parties on its profit flow and debt default risk.The result shows a supplier firm’s optimal RSI always helps increase its profit and decrease its default risk at all price levels. With an increase in substitutability between suppliers， a supplier firm’s bargaining power decreases. Its RSI plays a limited role in increasing profit； nevertheless， it still leads to an obvious decrease in its default risk. In addition， a supplier firm’s bargaining power increases with the number of competing suppliers when substitutability between them is low. Thus， its RSI could help to increase the profit considerably and decrease the default risk significantly. However， a supplier firm’s bargaining power decreases with the number of competing suppliers when substitutability between them is high. In this case， the RSI could not improve its profit significantly， but it still helps to reduce its default risk. Furthermore， a customer’s bargaining power also changes with the substitutability between suppliers， which then affects a supplier firm’s profit flow and debt default risk.It contributes to the existing literature by investigating how a supplier firm’s RSI decision and the bargaining powers of players in a supply chain influence its default risk in alternative competitive scenarios. It is also theoretically valuable in developing a new structural approach to default risk based on the profit flows and coordination mechanisms of the supply chain. It extends the traditional structural models of default risk that only focus on the change in a firm’s asset value. It is expected that this structural approach will be used to quantitatively evaluate the impacts of other important supply chain characteristics， such as supplier/customer concentration and trade credit， on firms’ default risk.

Under the background of China putting forward the goal of carbon peak and carbon neutralization， and China’s economy turning to high-quality development， it is very necessary to scientifically evaluate the impact of total carbon control policy on China’s high-quality economic development， but both theoretical research and empirical evidence in this field are very limited.Guided by the new development concept， a comprehensive evaluation index system is established to evaluate the high-quality development index of each province from 2010 to 2019； On this basis， DIDmodel is used to study the impact of total carbon control policy on high-quality development.The results show that： （1） The national high-quality development index shows a steady upward trend from 2010 to 2019；（2） The total carbon control policy has significantly promoted the high-quality development of the pilot areas， and its role in promoting high-quality development will continue to increase in the future；（3） The total carbon control policy mainly promotes high-quality development through the transmission path of advanced industrial structure.The research conclusions of this paper provide a beneficialreferencefor China to implement the total carbon control policyunderthe background of high-quality economic development.

A behavior management based consensus method for large-scale group decision-making is proposed to address potential non-cooperative behaviors， strategic manipulation behaviors， and delegation behaviors that may occur during the consensus reaching process of large-scale group decision-making under social network environments. Firstly， the directed Louvain method in social network analysis is introduced to divide decision-makers into subgroups within overlapping communities based on the directed social network， based on which subgroup members and subgroups are weighted based on social relationships and preference similarity. Subsequently， during the process of consensus reaching， by introducing the non-cooperative behavior identification and management methods based on the uninorm operator， identification and management mechanisms are designed for strategic manipulation behaviors based on the types of behaviors and social network analysis. A social relationship based management mechanism is also proposed for delegation behaviors， after which the consensus method for large-scale group decision-making based on behavior management is completed. Finally， a numerical example， simulation experiments and comparative analysis are conducted to verify the feasibility and effectiveness of the proposed method.

The existing grey models can only predict three-parameter interval grey number sequences indirectly， and the influence of time-delay effect is seldom considered. In order to improve the prediction accuracy of grey model for three-parameter interval grey numbers， a new model considering time-delay effect is proposed. Firstly， the autoregressive time-delay terms of system characteristic are introduced into the traditional grey models. Further， a matrix autoregressive time-delay grey multivariable model （MARGM（1， N）） is proposed by taking the variables as three-dimensional column vectors and setting the parameters as matrices. The integrity of the three-parameter interval grey numbers is maintained and the relations between the boundaries are connected， so that the three-parameter interval grey number sequences can be modeled and predicted directly by MARGM（1， N）. MARGM（1， N） is used to forecast the output of China's secondary industry and tertiary industry. The results show that the models considering the time-delay effect have better fitting effect， the matrix models have higher prediction accuracy， and MARGM（1， N） has the best performance in both fitting and forecasting compared with the competition models. Overall， MARGM（1， N） is feasible and effective. In application， it is helpful for relevant departments to make correct policies to coordinate economic development.

As China’s economy enters the stage of high-quality development， the conflicts between different groups become more complex and intense. For example， under the “3060 carbon peak and neutrality” goal， local governments have taken measures such as “power rationing”， which has caused multiple disputes in the society. Finding a balance between economic growth and reducing energy consumption has become a hot topic. The power asymmetry among decision makers （DMs） is a common problem， and the uncertainty of the power asymmetry makes it more difficult to resolve the conflict. It is of great significance to effectively resolve the power asymmetric conflicts of different degrees between DMs. To further resolve the realistic conflicts with uncertain power asymmetry between DMs， a fuzzy asymmetric power conflict analysis is proposed based on a graph model with two decision makers， a leader and a follower. Firstly， the power structure between DMs is divided into three types in conflicts. Secondly， the graph model for conflict resolution （GMCR） under fuzzy power asymmetry is constructed， which includes fuzzy improved preference of the leader and the follower， and unilateral improvement under fuzzy power for the follower. When power among DMs changes， the preferences of leader and follower also change. Further， the logical and matrix of asymmetry stabilities of the follower and leader under fuzzy power are defined. Finally， the equilibria of supply chain carbon emission reduction conflict of “carbon peak” and “carbon neutral” goals are solved using the proposed stabilities of fuzzy power asymmetry under the framework of graph model for conflict resolution. After analyzing the actual background of supply chain carbon emission reduction conflict under “3060 carbon peak and neutrality” goal， the results of the case study show that the proposed method can effectively resolve the conflict under different power structures. At the same time， the following management enlightenments are also provided： 1） Upstream manufacturer need to attract downstream manufacturer to participate in the research and development of new carbon emission reduction technologies together. 2） In order to promote the realization of carbon emission reduction targets， local governments need to introduce strict carbon emission reduction policies to guide enterprises to produce low-carbon products. And they can dynamically adjust product procurement policies according to the changes of market environment to achieve the ideal balance of conflict resolution. Different with the previous studies， not only the power asymmetry conflict is considered in this paper， but also the fuzzy power structure is taken into account， which further enriches the theoretical research of GMCR.

Considering the current situation of insufficient supervisory capacity of the established Vessel Traffic Service （VTS）， the expansion of VTS radar station location optimization is studied in this research.And a multi-objective locationoptimization problem of VTS radar station is investigated.While the attenuation of radar electromagnetic wave and obstacle occlusion are considered in the location optimization process. By expanding the number of the radar station to the built VTS system， safe navigations of voyaging vessels can be achieved and ensured.In the location optimization process， taking the obstacle occlusion and the attenuation of the radar electromagnetic wave into consideration， the radar attenuation measurement method and the obstacle occlusion judgment method are proposed in the three-dimensional space based on the spatial geometry method.Then， with the objectives of minimizing the total construction cost of VTS radar station and maximizing the coverage of the total water area， the maximum coverage model and the gradual coverage model are used to construct the mathematical model for the expansion of the radar station. And a VTS radar station project in a southern province of China is used as an example to verify the effectiveness of the proposed model and algorithm， and the results of the example are analyzed and sensitivity analysis is conducted.The results show that the proposed model and algorithm can effectively obtain the approximate optimal solution， which provides the solution program for location selection in the expansion process of VTS radar station. Meanwhile， it can provide references about method and model for the studies about radar station blind area， radar station location selection and facility location problems.

In recent years， the open platform strategy has been adopted by the incumbent ride-hailing platform in some cities in China， i.e.， passengers can select the services provided by the drivers from the new ride-hailing platform through the incumbent ride-hailing platform’s APP. It is an important research topic whether the incumbent ride-hailing platform should adopt the open platform strategy with respect to different market environments in different cities.In this paper， a transportation system with an incumbent ride-hailing platform and a new ride-hailing platform is considered， where the supplement of the incumbent ride-hailing platform’s drivers are not sufficient and the new ride-hailing platform’s drivers are sufficient. The models for maximizing profits of the incumbent platform and the new platform are constructed with regard to the competition mode （the incumbent platform does not adopt the open platform strategy or the new platform does not join the open platform） and cooperation mode （the incumbent platform adopt the open platform strategy and the new platform joins in）. Then， by solving the models， the optimal prices of the two platforms under competition mode and cooperation mode are obtained. Further， by comparing the profits of platforms under different modes， the optimal strategy of the incumbent platform and the new platform is analyzed under different market scenarios. On this basis， how several factors affect optimal prices， demands， supplies， and profits of the two platforms is examined. Finally， some numerical studies are conducted to show the impacts of passenger market size and different optimal strategies on social welfare.Several important results are shown through the theoretical analysis. First， if the one-off investment cost of the incumbent platform and that of the new platform are both low， or the incumbent platform’s potential market size is large， the profit of the incumbent platform under cooperation mode is higher than that under competition mode， then the incumbent platform should adopt the open platform strategy； On the contrary， the profit of the incumbent platform under competition mode is higher than that under cooperation mode， then the incumbent platform should not adopt the open platform strategy. Second， the decision results that maximize the platform’s profits are not always consistent with those that maximize social welfare. Thus， the government should take appropriate measures to guide platforms’ decisions.

The outbreak of emergencies has severely affected the operation of the supply chain and the business activities of enterprises. The supply chain reconfiguration strategy is studied under the risk of emergencies， and a supply chain decision model is constructed with supply and demand interruptions under emergencies. The model considers that a manufacturer needs to purchase a core component from a main supplier to meet the offline market demand； after the outbreak of emergencies， in order to deal with the supply interruption of the main supplier and the sales stagnation in the offline market， the manufacturer can put in a cost to implement the supply chain reconfiguration - start the backup purchase （i.e.， make an urgent purchase of components to a backup supplier not affected by emergencies） and carry out online sales business， in which the unit production cost of the backup supplier is higher than that of the main supplier， and it is necessary to reserve production capacity through a deposit to ensure the progress of backup procurement. The results show that under the risk of emergencies， when there is a threshold below which the online market potential is lower， the manufacturer will not reconstruct its own supply chain， otherwise， the manufacturer will reconstruct the supply chain by reserving the capacity of backup procurement to backup suppliers and opening up online sales channels for products. The threshold is a function of the risk of emergencies， the cost of backup production， and the predetermined price per unit of capacity.Moreover， the interval for manufacturers to implement supply chain restructuring is enlarged with the increase of the risk of emergencies， and then reduced with the increase of procurement cost and capacity reservation price. A priori， overbooking always occurs when a manufacturer books capacity with a backup supplier.When the manufacturer implements supply chain reconfiguration， if the risk of emergencies outbreak is small， the cost of capacity reservation is higher than the expected cost of backup procurement， that is， the backup supplier gains additional benefits through the manufacturer's capacity overbooking； otherwise， the cost of capacity reservation is lower than the expected cost of backup procurement， that is， the manufacturer will not suffer losses due to capacity overbooking.

In recent years， frequent large-scale natural disasters （such as floods， typhoons， earthquakes） and public emergencies （such as COVID-19 epidemic） have brought increasing challenges to China’s relief materials reserve system. In order to enlarge the supply capacity of relief materials in “urgent” time period and reduce the excessive waste resulted by expiration of the relief materials in “ordinary” time period， a new joint reserve model based on a delegated reserve contract with option is proposed between a government and an agent enterprise. In the model， the stochastic programming method and game theory is used and the two factors of reserve cost and relief satisfaction value are simultaneously considered. Moreover， the maximization of the government’s relief satisfaction value and the agent enterprise’s profit is the decision-making objective， and the government’s subsidy and the agent enterprise’s flexible quantity of the relief materials are the decision-making variables. As a result， the optimal subsidy strategy of the government and the optimal flexible reserve strategy of the agent enterprise are provided， respectively. The main results show that： （1） Only when the probability of the government purchasing the flexible materials of the agent enterprise is big enough， or it is in a moderate range and the unit subsidy is greater than a certain threshold， the agent enterprise will reserve flexible materials and the quantity of flexible materials is positively correlated with the unit subsidy； （2） When the agent enterprise reserves flexible materials， as the minimum quantity of relief materials with option increases， the agent enterprise’s expected profit increases first and then decreases， and the optimal flexible quantity of relief materials decreases， as well as the optimal unit subsidy level and the government’s expected relief satisfaction value； （3） The optimal unit subsidy and flexible quantity of relief materials are positively correlated with the difference of the relief satisfaction values between the relief materials with option and temporarily purchased materials. Finally， a numerical example is given to further illustrate the impact of relevant factors on the optimal strategies， and the corresponding management insights are provided.

Bullwhip effect refers to the phenomenon of demand variation and gradual amplification in the supply chain， which will bring high costs to supply chain enterprises. Therefore， alleviating the bullwhip effect has always been one of the core tasks of supply chain management， but the existing methods still cannot completely eliminate bullwhip effect. Introducing artificial intelligence methods into the supply chain to create a smart supply chain is one of the main methods for supply chain management in the information age， and it is also the main source of ideas to study the bullwhip effect. To explore new ways to alleviate the bullwhip effect， a four-level supply chain consisting of a retailer， a wholesaler， a distributor and a manufacturer is constructed， the deep reinforcement learning technology in artificial intelligence is introduced into supply chain management， and a human-machine collaborative intelligent decision-making robot is designed， used to improve the decision-making of distributors in the supply chain. The results of the smart experiment show that the indicators such as “variance ratio， average cost and service level” of each node in the supply chain have been comprehensively improved， which means that the bullwhip effect has been greatly alleviated. A new perspective and approach for studying the bullwhip effect in supply chain management is provided， and supply chain management is endowed with the value of intelligent decision-making.

With the rapid development of urbanization in China and the formation of urban agglomeration scale， the problem of urban traffic congestion brought about by the increase in the number of motor vehicles is becoming more and more serious year by year. A large body of literature suggests that road traffic congestion is the main cause of increased carbon emissions and high air pollution in cities. Therefore， to achieve the "double carbon" goal， it is not only necessary to give play to the energy saving and pollution reduction effect of the transportation industry， but also to pay attention to the treatment of alleviating traffic congestion.In order to alleviate urban road traffic congestion， first of all， from the theoretical level， the local static congestion caused by the assumption of “homogeneity” of bus lines is described as the mismatch between supply and demand in economics， and on the basis of the assumption of “heterogeneity” of bus routes， the hub and spoke network design is introduced into the optimization problem of urban bus routes. Secondly， the article takes the survey data related to residents' bus travel in Tongzhou District as a sample， verifies that the travel distance of residents coincides with the simulated electronic cloud and the distribution of two-order Weibull， and incorporates factors such as travel time value， safety factor， and comfort factor into the total cost function required by residents to take public transportation， so as to construct the advantageous travel distance function of residents taking different levels of bus lines as a standard. Finally， the demand for buses at different levels is defined as the product of the average travel distance of the corresponding bus lines and their traffic volume， and the supply of bus lines at different levels is defined as the product of the total traffic volume of the bus system and the proportion of passengers of the bus lines at this level， and on this basis， an hub and spoke multi-level bus line configuration model is constructed to test the mismatch between the bus travel needs of residents in Tongzhou District and the transportation capacity provided by the urban bus system.The results of the study show that the bus demand for the axis and auxiliary lines in Tongzhou District is much greater than the bus supply of the corresponding grade lines， and there is a mismatch between supply and demand； the demand for branch buses is smaller than the bus supply of this level， and there is a mismatch between oversupply and demand. The corresponding countermeasures are propased for the above problems， dynamically the mismatch is adjusted between supply and demand of different levels of bus lines， resources are reconfigured， a balance is achieved between supply and demand， and the local static congestion problem of urban public transportation is alleviated， in order to provide a scientific theoretical basis for the transportation sector to promote the realization of carbon neutrality goals， reduce pollution and reduce emissions， and alleviate traffic congestion.

Existing traffic demand management strategies， such as road pricing， parking restrictions， and tradable credits scheme， mostly focus on using punishment mechanisms to keep travelers away from certain transportation modes or time periods. However， due to the issues such as traveler aversion， inequity of charges and market settings， these measures are difficult to implement. The incentive-based traffic demand management （IBTDM） strategy adjusts the temporal-spatial distribution of travel demand through incentives， which is highly feasible in solving the potential problems such as traveler aversion and inequity of charges. Therefore， it is necessary to analyze how to formulate IBTDM strategy reasonably so that the government can effectively adjust the temporal-spatial distribution of travel demand.A differentiated incentive strategy to encourage green travel behaviors is analyzed by considering the scope of incentive objectives and different levels of incentives in a multi-mode transportation system. Given a one-to-one multi-modal transportation network， in which commuters can get to their destination by driving regular vehicles solely， sharing vehicles with others or taking bus mode， the effect of the strategy is analyzed based on the bottleneck model in scenarios where the ride-sharing services are provided by two suppliers with different incentive budgets.The results show that the proposed strategy can effectively guide commuters to the preferred travel mode through different parameter settings for the strategy. When there is no incentive budget limit， increasing the coefficient difference or incentive amount can reduce the number of vehicles traveling on roads and travel costs while the number of bus commuters shows different trends. When minimizing the travel cost with emission reduction constraint， the feasible range of the incentive amount and difference coefficient narrows， and is inversely proportional to the fixed budget value. Additionally， although there is no budget， the road congestion queue can be eliminated， and the temporal-spatial distribution of the travel demand can be adjusted by combining with a dynamic bottleneck toll.Through the implementation of differentiated incentive strategy that encourage green travel behavior， commuters can be reasonably guided towards designated transportation modes and effectively alleviate urban road congestion. A theoretical reference is provided for selecting incentive objectives and determining the incentive amounts in IBTDM strategy in a multi-modal travel scenario and help deepen the understanding of policies for multi-modal traffic demand management based on incentive mechanisms.

Commercial practice shows that core component suppliers with patents usually use two ways to calculate patent licensing fees. The first is based on the percentage of the product's sales price. The other is based on the percentage of the wholesale price of core components. The argument about patent licensing strategy is mainly since the patentee wants to get more benefits through patent licensing， while the licensee wants to use the patent with less return. Therefore， when enterprises are in a monopoly position in their respective markets， suppliers tend to choose licenses based on product price， while manufacturers prefer licenses based on component price. Although the supplier with several standard patents is in a leading position in technology， it will not become a complete monopolist in its market. For example， Qualcomm faces potential competitors such as HiSilicon and Samsung. In addition， with the development of global economic integration， competition no longer occurs between enterprises but between supply chains. Therefore， it is necessary to integrate the elements of the competitive supply chain into the licensing decision of enterprises， and such research is still lacking. Thus， it aims to study the supplier's optimal patent licensing strategy selection in the presence of chain-to-chain competition. In this paper， for two competitive supply chains composed of one supplier and one proprietary manufacturer， the optimal patent licensing strategy selection and its influence are studied. As a patent holder， the supplier can license the patent to the manufacturer with the percentage of the selling price of the manufacturer's products （product-based strategy） or the percentage of the wholesale price of components （component-based strategy）. Two competing manufacturers produce and sell homogeneous products， but their production costs are heterogeneous. After licenses， manufacturers can use patents to reduce production costs.The research shows that， firstly， the licensing strategy preference of supply chain participants depends on factors such as product competition， production cost difference， and unit patent licensing fee. Secondly， for suppliers， the supplier facing the downstream high-efficiency manufacturer always tends to implement a product-based licensing strategy， but the component-based licensing strategy may become optimal for the supplier facing the downstream low-efficiency manufacturer. Thirdly， the low-efficiency manufacturer is always willing to accept the component-based licensing strategy. However， under the condition that competition is mild， the cost advantage is high enough， and the unit licensing fee is low enough， the high-efficiency manufacturer may adopt the product-based strategy. Hence， under certain circumstances， one specific strategy combination （i.e.， the supplier facing an inefficient downstream manufacturer implementing the component-based strategy， along with the supplier facing an efficient downstream manufacturer implementing the product-based strategy） can be the equilibrium strategy that both suppliers are willing to implement， and both manufacturers are willing to accept. It enriches the theory of competitive supply chain management and patent licensing in this paper， and it provides a reference for enterprises to effectively manage the operation practice of patent licensing in the vertical supply chain channel.

Motivated by the industry practice that two famous Chinese clothing companies respond differently in production quantities as debts increase， how debts affect the pricing and production decisions of a firm with limited liability is investigated. Specifically， the firm simultaneously determines its selling price and production quantity to maximize the expected benefit， which is defined as the positive part of profits minus debts. By comparing the optimal pricing and production decisions under profit maximization and those under benefit maximization， it is found that debts indeed influence the joint decisions. With a low unit production cost， product price increases but production quantity decreases as debts increase. However， with a high unit production cost， both product price and production quantity increase as debts increase. It is further numerically shown that the results hold when demands follow a normal distribution. Our findings provide guidelines for firms with debts and limited liability to set their optimal price and production quantity.

In recent years， with the rapid development of the platform economy in the world， the platform supply chain has begun to receive sufficient research attention. In the uncertain market environment， the information asymmetry of the supplier's product/service/content quality in the platform supply chain often leads to moral hazard problems， and the incentive contract can reduce this risk. Motivated by this problem， suppliers’ continuation value is introduced as a state variable to measure the overall performance of the supplier， the platform’s profit distribution mechanism is designed to incentive two competing suppliers’ effort， and the optimal dynamic incentive contract model is constructed based on the continuous-time principal-agent theory and stochastic process. By transforming the dynamic incentive contract problem into a stochastic optimal control problem， the Hamilton-Jacobi-Bellman equation （HJB） satisfying the platform utility value function is obtained， and further the existence and uniqueness of its concave solution are proved. Finally， numerical solutions are provided to explain the effects of the competition on the platform supply chain decision-making under different market volatility. The results suggest that： （1） In a highly uncertain market environment， the platform can give suppliers appropriate subsidies to incentivize suppliers to improve their efforts. （2） When the cost coefficient of effort is very large， the platform shares a part of the cost of suppliers to incentivize suppliers to improve product quality and achieve a win-win situation. （3）The platform can reduce the risk premium it pays to the suppliers through competition between suppliers， thereby increasing the platform’s profit.

With the rise of live streaming and the boom in online shopping， many manufacturers have opened up live streaming distribution as a new marketing channel. Such live streaming leads to intense competition with the manufacturer’s official online store. However， consumers may be interested in the product and also purchase it in the official online store due to the spillover effect of the live streaming. Therefore， it is important to investigate how the spillover and competition effects of the live streaming channel impact the manufacturer’s pricing strategy. In practice， the contract between manufacturers and live-stream carriers is generally classified into two different types： resale model and commission model. Thus， it is also worth investigating the contract selection for the manufacturer.Based on the above background， this paper establishes a supply chain system consisting of the manufacturer and the live-stream carrier. A game-theoretic research approach is applied to examine the interaction between the manufacturer and the live-stream carrier. First， the manufacturer will decide to introduce the live streaming business with a live-stream carrier by selecting two types of sales contracts： （1） resale contracts （2） commission contracts. Second， the live-stream carrier will decide its subsidy price， and the manufacturer will decide the selling price of its products in its official online store. Finally， consumers generate purchase behavior in different channels based on price competition between channels. The innovations of this article are： First， it is one of the few to consider the channel competition between the online store and live-streaming distribution for this article. Second， the spillover effect in the live streaming is explained， which extends the interaction knowledge between spillover effect and sales contract selection. Third， the discount coupon of the live carrier and the impact of sales contracts on its profitability discussed， which further reveals the sustainable development of the live streaming supply chain.Some interesting results are obtained by comparing the equilibrium results in terms of the optimal product price， subsidy， and profit. First， the results show that there always exists Pareto gains for the entire supply chain. Specifically， when the commission rate is moderate， if the competition degree between two channels is low， the manufacturer and the live-stream carrier are willing to adopt the commission contract. If the competition degree is high， both parties are willing to choose the resale contract. However， enhancing the spillover effect will expand the “win-win” region of two parties. Second， the extended situation is considered where the manufacturer offers a mixed live-streaming contract. The extended situation shows that under certain circumstances， both parties still willing to choose the commission contract， which proves the robust of this study. Interestingly， the preference of the two parties for the mixed contract may cause the other party to become worse. The numerical simulation is also given to further prove our results and strategic guidance is provided for manufacturers， live-stream carrier， and relevant practitioners on management to achieve more profits. For example， it is proposed that the profit of the entire supply chain can be improved by reducing the negative impact of subsidies. It is also advocated that those laws and regulations related to live streaming should be perfected and formulated.

The external environment the market facing is becoming increasingly complex， and unexpected events occur frequently， which makes the price change at any time and makes the marginal profit fluctuate. In this ever-changing environment，if manufacturers and retailers cooperate in advertising，there will be some delay in advertising andprice competition among manufacturers. At this time， how to make decisions among members of the supply chain has become an urgent problem to be solved.In this paper， the influence of advertising delay degree on the optimal decision-making of supply chain members is studied based on marginal profit fluctuation and price competition among manufacturers.The concrete research ideas are as follows. Firstly， under the background of non-competition， the differential equation of brand goodwill and the profit equation of marginal profit fluctuation considering the effect of advertising delay are built. By applying differential game，the optimal wholesale price， optimal retail price， optimal advertising investment， optimal advertising sharing rate， brand goodwill and profit are found out. Secondly， the corresponding differential equations are constructed to obtain the optimal wholesale price， optimal retail price， optimal advertising investment， optimal advertising sharing rate， brand goodwill andprofit under the background of price competition among manufacturers. Finally， the influence of delay time on the optimal path of each decision parameter is verified by an example simulation and the comparison between the results obtained under the condition of competition among manufacturers with those obtained of non-competition is made. And based on above information， it can be conduded that the optimal retail price， optimal wholesale price， brand goodwill and profit are positively related tothe delay degree of national advertising and alsotothe delay degree of local advertising. The optimal advertising investment of manufacturersis only positively correlated with the delay degree of national advertising， while the optimal advertising investment of retailersis only positively correlated with the delay degree of local advertising. Meanwhile， the optimal sharing rate is aconstant， which has nothing to do with advertising investment and advertising delay. When manufacturers compete in price， the optimal wholesale price， the advertising input of manufacturers and retailers are alllow. The retail price of manufacturers incompetition is slightly lower than that innon-competition，but there is little difference. Price competition among manufacturers will damage the profits of manufacturers， but it will help retailers togethigher profits.In this study， it aims to explore the internal operation and evolution law of the dynamic optimization of the delayed cooperative advertising supply chain under the condition of marginal profit fluctuation， enrich the supply chain management theory， and provide scientific basis for the decision-making behavior of the supply chain and its members under the condition of price competition among manufacturers.

The heterogeneity of bilateral network is a key factor to be considered in the operation and management of network platform. The additional investment and pricing strategy of a two-sided online platform with monopoly position considering two-sided network effects are studied， and the factors are found out that affect the additional investment， membership fee pricing and advertising fee pricing of the platform. The results show that when the additional investment coefficient is greater than a certain threshold， the platform should invest at the highest level， otherwise the additional investment should be reduced； When the marginal additional investment cost is in a certain range， the platform should invest at the highest level， otherwise， it should reduce the additional investment； When the negative network effect of consumers and advertisers increases， the platform shall reduce the additional investment and reduce the membership fee； when the positive network effect of advertisers on consumers increases， the platform shall increase the additional investment， reduce the membership fee and advertising fee； when the internal network effect between consumers increases， the platform shall increase the additional investment， membership fee and advertising fee.

With the internet penetration into daily life and the development of consumers’ online consumption habits， fresh produce e-commerce has seen explosive growth. However， with the increasing growth of fresh e-commerce， Numerous actual cases show that the corporate social responsibility （CSR） of fresh produce firms is woefully insufficient. For example，the “Dingdong” platform was investigated by the Haidian District Market Supervision Bureau due to sellingseconds at best quality prices andunauthorized “repacking” for labeling.“Miss fresh” was frequently complained by consumers for selling expired food.To deal with the reality，the Food Safety Law of the People’s Republic of China， updated in 2021， states that food businesses must be responsible for customers and practice social responsibility.As a result， several leading Fresh businesses， such as Freshippo， J.D. Fresh， and Dilifresh， have been impelled to incorporate CSR in their supply chains. However， it is still unclear what are the effects of CSR practice on fresh supply chain members， and how can CSR be shared among supply chain members to improve supply chain performance.To answer the research questions posed above， a two-stage supply chain with a fresh produce supplier and an e-tailer is explored in which each supply chain member considers CSR in addition to profit.Stackelberg game is constructed for the following four strategies： The fresh produce supplier practices CSR alone and supply chain members jointly practice CSR are discussed separately under wholesale price contract and revenue-sharing contract. The four models are formulated and some equilibrium results are gotten. Then the effects of CSR levels on optimal decisions， profits， and consumer surplus are investigated. Finally， the optimal decisions， profits， and consumer surplus of the four models are compared and analyzed. The conclusions are also verified through numerical examples.It is shown that CSR behaviors can always improve the freshness of fresh produce， reduce retail price， stimulate demand， and improve consumer surplus and social welfare. It is also shown that the fresh supplier practices CSR can reduce its profit but increase the profit of the e-tailer， while the e-tailer practices CSR can improve its and the supplier’s profits under certain conditions. It is further shown that the supply chain members jointly practicing CSR has a more significant stimulating effect on demand than the fresh supplier practices CSR alone.Finally， the supplier and the e-tailer jointly practice CSR under a revenue-sharing contract， which can both improve the level of freshness-keeping effort and achieve Pareto improvement of supply chain members’ profits under certain conditions， but at this time the fresh suppliers should not pursue high revenue sharing blindly.

With the increasing willingness of consumers to shop online， a growing number of retail platforms not only serve as service providers to operate an agency channel， but also sell competing store brands through their own platforms. At the same time， many manufacturers who used to sell national brands through the retail platform have also established direct online channel to sell the products. As a result， there is not only brand competition between the manufacturer and the retail platform but also selling channel competition between the direct online channel and the platform’s online channel. Therefore， two strategies of the retail platform are considered： introducing store brand and non-introducing store brand. Given the platform’s strategy， the manufacturer has three channel strategies： selling products through the retail platform， selling products through the online direct channel， and selling products through the dual channels. Combining with consumers’ willingness to pay for different selling channels and brands， two-stage game models are constructed in different strategy scenarios. The games are solved by backward induction and equilibrium selling prices and profits are obtained. The optimal strategies of both players can be identifiedby comparing and analyzing these equilibrium outcomes.The results suggest that when the unit purchasing cost of the store brand is low， the platform has an incentive to introduce thebrand and can obtain higher revenues by charging commission feesfrom manufacturer and selling store brand products. However， a higher commission rate may hurt its profit. Even if the online platform introduces the competing store brand， themanufacturer sells national brand product through the platform only， and the selling price and market demand of the national brand are both higher. However， when there is no store brand on the platformand the channel establishment cost is low， the manufacturer sells national brands through dual channels. Nevertheless， it is worth noting that the manufacturer’s profit will be worseas the price difference between the dual channels increases. Furthermore， compared with the case where the platform firstly decides brand strategy， the case where the manufacturer firstly decides channel strategy results in a prisoner’s dilemma， whereas the higher preference of store brand can achieve the profit improvement of both players.

With the rapid economic growth， growing demand for high-tech products and decreasing service life of products， E-waste is surging. Due to its environmental pollution and the valuable resources contained， E-waste has become a focus. However， a very small percentage of used electronic products are recycled. One of the important reasons for this problem is the lack of economic and efficient recycling logistics mode. The existing E-waste recycling logistics mode ignores the collaboration between stakeholders， resulting in high cost and low recovery rate. Thus， a horizontal logistics cooperation is considered in which multiple enterprises collaboratively solve their logistics optimisation problem through the platform.In this study， this problem is modelled as an integer programming which minimizes vehicle routing costs and fixed costs for sub-alliances， named the multi-owner collaborative recycling vehicle routing problem model with time windows. Based on the model， the optimal results of routes planning can be solved. The total cost of each sub-alliance can also be quantified. Then， Shapley value method is used to allocate the total cost of the alliance. The recovery rate quantization function model in collaborative recycling logistics mode is constructed based on customer satisfaction and enterprise recovery efficiency.Through numerical experiments， the benefits of collaborative recycling are demonstrated and the influencing factors of cost saving and recovery rate are further discussed. The following conclusions are drawn： the cost of multi-owner collaborative recycling can reduced by 30%-40%. Compared with individual recycling， collaborative recovery rate can increase by more than 20%， and compared with traditional recovery， the recovery rate can even increase by more than 60%.Thus， the significant cost reduction and recovery rate improvement can be verified. In addition， the consideration of time windows can obtain higher recovery rate and collaboration shows to be particularly attractive for enterprises with more dispersed demand orders because of higher cost reduction.Collaborative recycling logistics mode proposed is an important supplement to the existing recycling mode， and its path optimization and cost allocation have wide application value in practical recycling. There are important reference value and practical significance for enterprises to choose collaborative recycling mechanism and relevant cost allocation.

To enhance consumers’ shopping experience， a growing number of retailers who own both offline and online channels are introducing buy-online-and-pickup-in-store （BOPS） channels. Meanwhile， the platform will deliver coupons for retailers' BOPS and online channels to promote consumption. Based on the practice， this raises the following two interesting questions： What is the platform’s coupon delivery strategy when the retailer builds BOPS and online channels？ What is the impact of the platform’s coupon delivery strategy on retailers and consumers？ To answer these questions， considering a supply chain with an e-commerce platform， and a retailer who can implement omni-channel strategy by entering the platform， two models are built to study whether the platform should deliver coupons to both the BOPS and online channels.Our main results suggest that　（i） The platform chooses to deliver small denomination coupons when search cost is small.（ii） The platform’s couponing strategy is not always beneficial to the retailer and consumers. Specifically， only when both the channel preference and the search cost are not moderately large， delivering coupons can increase the retailer’s profit. Furthermore， only when the search cost is moderate or large， the platform can increase consumer surplus by delivering coupons. （iii） If the channel preference is small and the search cost is moderate， the platform will deliver coupons to achieve a “win-win-win” situation in which the platform， retailer， and consumers become better-off. Finally， a numerical example is used to analyze the situation where the cost of sales in physical stores is large. It is observed that consumers’ preference for the BOPS and online channels plays a key role in determining the coupon strategy for the platform. In fact， when the channel preference is high， the platform is likely to deliver coupons.

Under the carbon cap-and-trade mechanism， in a two-echelon supply chain comprised of a capital-sufficient supplier and a capital-constrained manufacturer with yield uncertainty， when there exists two financing mode the bank lending credit and trade credit， the decision-making of carbon emission reduction and price of supply chain is studied that the supplier and the manufacturer all have fairness concerns. The equilibrium strategy of the members and the financing decision of the manufacturer are achieved by Stackelberg game model. The impacts of fairness concerns and yield uncertainty etc. on the equilibrium decisions，the members’ profit and system-wide profit of supply chain are also analyzed. The results show that： （1） When the interest rate of trade credit is not less than that of bank lending credit， the manufacturer should choose trade credit as financing policy. If the interest rate of bank lending credit is larger than that of trade credit， the choice of the manufacturer’s financing policy depends on the initial working capital. （2） The carbon emission reduction， order quantity， profit of supplier and the whole supply chain are negatively correlated with fairness concern of both manufacturer and supplier. The wholesale price is positively correlated with supplier’s fairness concerns while negatively correlated with manufacturer’s fairness concerns， and the manufacturer’s profit is positively correlated with its own fairness concern while negatively correlated with supplier’s fairness concerns. （3） The yield uncertainty has a negative impact on carbon emission reduction， order quantity and the system-wide profit and members’ profits of the whole supply chain， and has nothing to do with the supplier’s wholesale price. The consumers’ low-carbon preference is positively correlated with manufacturer’s order quantity and carbon emission reduction， system-wide profit and member’s profit of supply chain， and has no influence on the supplier’s wholesale price； The carbon trade price is negatively correlated with the wholesale price， and the impacts of carbon trade price on the optimal decisions of manufacturer， system-wide profit and member’s profit of supply chain is related to the value range of price. Finally， some numerical examples are used to verify the theoretical results.

Significant changes of the allocation of resources have arisen under sharing economy environment： the platform enterprise now matches the member enterprises to the projects’ demands instead of the contractor arranging its own resources. Based on this fact， the resource-constrained Max-NPV multi-project scheduling optimization problem is studied. First， the problem is identified and formulated into a nonlinear integer programming model after abstracting the characteristics of the sharing economy. Then for the NP-hard problem， a simulated annealing algorithm is developed to generate multi-project baseline schedules and corresponding matching schemes. Ultimately， an instance is used to illustrate the problem and a sensitivity analysis of key parameters is conducted. The conclusions are as follows： The total NPV of projects grows with the increase of member enterprises numbers， project deadlines and pay ratio and drops with that of the discount rate. Besides， the increasing number of member enterprises and the extension of project deadlines have a diminishing marginal effect on the NPV， and augment of one will make NPV less sensitive to the other. The quantitative decision support is provided for multi-project scheduling and member enterprises resource allocating under sharing economy environment.

With the development of the Internet， advertisers are spending more and more on online advertising； however the effect is not always satisfactory. In order to improve the effect of online advertising and expand market demand， an increasing number of advertising agencies （agency） have started providing marketing services directly for advertisers while selling online advertising media（media） advertising resources.There are two common modes of cooperation between media and agency： premium mode and rebate mode. Under the premium mode， the media offers the advertising resources to theagency at a pre-specified wholesale price， and the agency is free to set the sales price in the marketplace. Under the rebate mode， the price for the advertising resources is determined by the media instead of the agency.The complementary relationship between advertising resources and marketing services makes the choice of service chain cooperation mode more difficult. Because under the premium mode， the agency has the incentive to cut the price of advertising resources to promote the sales of marketing services in order to maximize her own profit. Meanwhile， channel power structure is also an important factor to consider when choosing the optimal cooperation mode. The channel leader has the priority of choosing a more beneficial cooperation mode.Therefore， when downstream agency provides complementary services at the same time， the mode of cooperation between media and agency under different power structures has become problematic for the online marketing service supply chain.In the paper， an online marketing service supply chain comprising of one media and oneagency is considered. The media distributes advertising resources through the agency. Besides advertising resources， the agency also sells marketing services. The advertising resources and marketing services are complementary， which means the demand of each good is influenced not only by its own price but also by the price of the other.Game-theoretic models are developed to study the corporate behavior under different power structures （media Stackelberg and agency Stackelberg） and different cooperation modes （premium mode and rebate mode）.Through comparing equilibrium decisions and profits in diverse scenarios， the optimal cooperation modes for the service supply chain are obtained. Then the influence of the rebaterate and the degree of complement is analyzed.Findings reveal that， the cooperation mode selection is influenced by power structure， rebate rate and complementary degree. Under media Stackelberg structure， it is optimal for the media to choose premium mode when the rebate rate is high or the rebate rate is low but complementary degree is high， otherwise it is better for her to select rebate mode. Under agency Stackelberg structure， the situation is almost the opposite. For the overall channel， however， it is shown that the performance is always better under the rebate mode than under the premium mode regardless of channel power. Under the premium mode， power structure only affects the wholesale price， but under rebate mode it affects the sale price of both advertising resources and marketing services. Under the rebate mode， with the increase of rebate rate， the price of advertising resources will increase while the price of marketing services will decrease. Furthermore， power structure has a significant effect on the profits of channel members；they always get higher profits when they play a dominant role under the same cooperation mode.Our research also has management implications for the service supply chain decision-making. One prominent finding is that the degree of complementarity can critically affect cooperation mode choice. So it is necessary for the media and the agency to consider when making pricing decision and choosing cooperation mode.Moreover，maintaining competitive advantage and taking the initiative in the game can also benefit the channel members. The media and the agency should adjust pricing decisions flexibly according to different power structures.

Carbon pricing is one of the key measures for China to reach a carbon peak in 2030 and achieve carbon neutrality in 2060. However， price regulations relating to electricity， natural gas， and refined oil products in China may affect the cost-effectiveness of carbon pricing policies. Therefore， China’s existing energy pricing mechanism is introduced into a computable general equilibrium model， and the comprehensive effects of orderly deregulation of multiple energy prices on China’s marginal abatement cost （MAC） is explored. On this basis， the total abatement costs and cost-saving effects under different scenarios for China to achieve Nationally Determined Contribution target and phased target of carbon neutrality are evaluated. The results indicate that， first， China’s MAC is most sensitive to the deregulation of refined oil prices. Whether it is to liberalize refined oil prices for non-key oil-using sectors in the preliminary reform or to liberalize refined oil prices for key oil-using sectors in the in-depth reform， China’s MAC will demonstrate an obvious downward trend and the cost-saving effects to achieve the given abatement target will be the most significant. Second， the deregulation of electricity prices for households and agriculture sector will also reduce China’s MAC and total abatement costs to some extent. Third， although China’s MAC is insensitive to deregulate gas prices for non-households or households， it will also lead to a slight decline in MAC and total abatement costs. Finally， combined with the current mainstream carbon trading policies in China， the following suggestions are given： First， the overall roadmap for China’s energy market price reform may give priority to deregulating natural gas prices for non-household sectors and refined oil prices for non-key oil-using sectors. If the part of refined oil price is liberalized first， the total emission quota in the carbon market can obviously be reduced. If the natural gas price for non-household sectors is liberalized first， the corresponding abatement policies do not need to be adjusted. Second， in the long-run， the energy market price reform will eventually deregulate electricity， natural gas， and refined oil prices in all sectors. In this phase， if we fully liberalize refined oil prices first， it can continue to significantly reduce the total emission quota. If we fully deregulate electricity prices or natural gas prices first， the total emission quota can be both moderately reduced. Third， from an industry perspective， it would be appropriate for the oil refining industry to consider reducing oil refining capacity or transforming and upgrading， and for the power and natural gas industries to consider controlling the scale of new installed capacity or moderately reducing capacity.

Climate change and environmental pollution are major problems in energy and environment management around the world. To relieve these two problems for “double carbon” target， it is important to develop renewable energy. However， certain characteristics of renewable energy （e.g.， uncertainty and high cost） have limited its further development. Renewable electricity standard （RES） has been widely adopted inmany countries to further develop the renewable energy. In this paper， a data-driven approach is provided to allocate a renewables quota among the regional power industries of China in order to achieve a goal for renewable energy consumption. Specifically， each regional power industry’s historical production data is used to build its own technology， which is used to show the changes of new productions with different renewables quotas. Then， based on each regional power industry’s production technology， a maximum total electricity generation model is proposed to allocate the renewables quota among regional power industries. With maximizing total electricity generation as the primary goal， the proposed model also is able to minimize the total carbon emission as a secondary goal approach. Through empirical research， the following management suggestions are provided for the development of renewable energy： （1） In order to solve the energy supply and demand contradiction between high production and low consumption， it is necessary to accelerate the development of trans-provincial and trans-regional renewable energy transmission technology and improve transmission capacity （2） In the economically developed eastern region， the way to fulfill the responsibility weight of renewable power should be inclined to other ways except production （such as purchasing green certificates， purchasing renewable power， etc.）. （3） In coordination with the planning of renewable energy power quota system and emission reduction targets.

Nowadays， employee turnover is an important issue in organizations. Predicting employee turnover in advance using big data can provide a scientific basis for making decisions of employment and retention， which will enhance the foresight and wisdom of human resource management. The key problem of reported employee turnover prediction models is the lack of business driving force， which is manifested in that they can only answer to the human resource manager whether an employee has the turnover intention， but cannot further indicate why he or she will leave and how to retain it in a targeted manner. Therefore， focusing on this problem， a portrait-based employee turnover prediction model named PCC is proposed， integrating PCA （Principal Component Analysis）， CLARA （Clustering Large Application）， and CART （Classification and Regression Tree）. Finally， the PCC model is experimented on an open-source employee turnover dataset with 14，999 samples from Kaggle. Theoretical and experimental studies show that the PCC model can provide theoretical reference for employee turnover prediction， turnover portrait description and accurate retention strategy design. Besides， it can be used to predict the turnover intention of individual employee and monitor the turnover distribution of all employees. Furthermore， it can provide data support for employee retention and talent reserve from both micro and macro levels. In summary， the PCC model is a feasible， effective and intelligent system for human resource management.

High-quality scientific research is the cornerstone of socio-economic development and scientific and technological progress. However， universities attach great importance to the acquisition of projects and the publication of papers， high evaluation standards， and high competition， which have led to the phenomenon of teachers tending to short-term and low-quality scientific research. In the context of the urgent need to improve the quality of research， how to improve the institutional design of universities to encourage teachers to carry out in-depth and high-quality scientific research has become the research problem.Based on the process of teachers' scientific research， a two-stage scientific research quality model including the reward and punishment mechanism of faculties' performance appraisal and the patent examination mechanism has been constructed. The concept of faculty research quality effort level is added to the model； two performance appraisal mechanisms are considered. Guided by the improvement of scientific research quality， game theory and numerical simulation analysis are used to explore the optimal reward and punishment mechanism and patent examination mechanism， and the influence mechanism of faculties' scientific research quality effort level is analyzed.The data for the simulation analysis is based on a real research project case， and some data are assumed on this basis.The applicable conditions of different assessment， reward and punishment schemes are analyzed， and the countermeasures and suggestions for quality management of scientific research are put forward.These findings provide theoretical contributions for universities to improve faculties' research quality improvement mechanisms in terms of performance assessment and patent review.The main conclusions are as follows： 1）If the income of patent transformation obtained by teachers is enough to exceed the cost of patent transformation， the university will not need to carry out patent examination again； 2）For the research projects with low yield or low success rate of patent transformation， there may be teachers applying for patent awards only， and universities should formulate reasonable patent award and review mechanism； 3）In the context of high returns from patent transformation， the optimal teacher performance assessment period is at the end of the research period. Improving the assessment rewards and the academic value of teachers' research achievements can effectively improve the level of teachers' optimal research quality and efforts； 4） A lenient assessment and reward program is more applicable. Under the policy of a high percentage of proceeds from the conversion of patents earned by faculty and the academic environment that places more emphasis on reflecting the value of teachers or research teams， universities should adopt a lenient assessment and reward and punishment scheme； Under the policy of a high percentage of proceeds from the conversion of patents earned by school and the academic environment that places more emphasis on highlighting the value of universities， universities should adopt a strict assessment and reward and punishment scheme.

In recent years， under the guidance of enterprises' “going global” strategy and the “Belt and Road” Initiative， the scale of Chinese enterprises' foreign direct investment （OFDI） has been growing year by year. However， in the face of the complex international investment environment， Chinese enterprises are still facing huge potential risks in the process of “going global”. Due to the lack of investment experience and in-depth investigation of the host country market， many enterprises often fail to acquire， invest in limited， or even end up in failure. Therefore， under the theoretical framework of heterogeneous enterprise， exploring the relationship between firm risk level and investment location choice can help enterprises actively cope with the opportunities and challenges of globalization， and point out the direction for further improving OFDI quality and optimizing investment structure.The existing literature on the location choice of China's OFDI is rich， but most of the empirical analysis is based on the flow or stock data of China's OFDI at the macro level， while relatively few literatures examine the impact of heterogeneity characteristics on OFDI location choice at the firm level. On ROA and enterprise of foreign direct investment research， scholars usually is the host country factors influence on enterprise foreign direct investment risk， and ROA as proxy variable of enterprise risk level， but there is no literature to investigate the factors from the perspective of business risk level heterogeneity influence on our country enterprise of foreign direct investment location choice. In view of the current turbulent and risk-prone international economic environment， the enterprise risk level is defined based on the uncertainty of future capital inflow， and this index is introduced into the extended enterprise heterogeneity OFDI location choice model， focusing on how the internal risk characteristics of OFDI enterprises affect their international expansion decisions. It may be innovative in the perspective of topic selection and research content.Specifically， under the framework of heterogeneous enterprise theory， a theoretical model of the influence of firm risk level on the location choice of OFDI is constructed， and the influencing mechanism of firm risk level， host country market size， natural resources， strategic assets， institutional quality and other factors on OFDI decision-making is revealled. On this basis， the enterprise micro data set is constructed by matching the List of Overseas Investment Enterprises （institutions） of the Ministry of Commerce of China and the data of A-share listed enterprises， and the conditional Logit model is used for empirical test. The results show that the relationship between the enterprise risk level and the entry threshold of the host country determines the OFDI decision of the enterprise. The deterioration of the market environment of the host country will increase the entry threshold and weaken the investment tendency of the enterprise， but the low risk level of the enterprise can improve its investment probability. On the whole， Chinese enterprises tend to invest in host countries with larger market size， abundant natural resources， close geographical distance， convenience of access and higher institutional quality. Low enterprise risk level weakens the negative influence of host country factors such as market size， geographical distance and institutional quality on location decision， but strengthens the influence of access convenience of host country. However， the high risk level strengthens the negative impact of host country factors except entry convenience， making enterprises more inclined to countries with lower entry barriers.