To investigate the diffusion degree of low-carbon technology in competitive firms and the influence of different pollution regulations, we constructed an evolutionary game model representing three environmental mechanisms: total amount control and trading, carbon tax, and subsidy, within a complex firm network. By analyzing the effects of carbon quotas, tax rates, and subsidy rates, we comprehensively assessed the performance of these mechanisms in terms of diffusion degree, firm profits, consumer surplus, environmental damage, and social welfare. The study results demonstrated distinct outcomes for each environmental mechanism. Under the subsidy mechanism, low-carbon technology exhibited the highest diffusion degree, suggesting its efficacy in promoting widespread adoption. However, it is worth noting that the higher the subsidy, the more environmental pollution it led to, which presents a trade-off between environmental benefits and financial incentives. On the other hand, the carbon tax mechanism resulted in minimal pollution, reflecting its potential as an effective tool for environmental regulation. Finally, the cap-and-trade mechanism emerged as the most favorable option, as it maximized social welfare while effectively addressing environmental concerns.
We provide the first systematic analysis of the stock return lead-lag effect among firms connected through shared analyst coverage in China’s A-share markets. We measure the shared analysts-weighted average returns of connected firms （CF） and show that CF return is a significant positive predictor of future returns of the focal firms in the following one to 12 months. The CF-based long-short portfolio earns an abnormal return of 10% to 12% per year. The effect is robust to controls for the industry and geographic momentum effects. Further evidence shows that the CF momentum spillover effect is stronger when the focal firm shares more analysts with connected firms， is covered by more non-star analysts or analysts with lower levels of education， or is held by more stress-resistant institutional investors. Our findings contribute to the cross-asset momentum literature by documenting a new， strong， and long-lasting momentum spillover effect in the Chinese stock markets.
Additive network DEA model is one kind of highly nonlinear programming problem,which is difficult to be solved directly.The existing heuristic algorithm cannot be applied to obtain the exact solution of the model,and will consumes a lot of computing resources and times in the big data environment.In order to solve these two issues,the presented study mainly does two aspects of work.Firstly,aiming at the issue of solving precision of the model,a solving method of quadratic fractional programming is proposed in this study,which decomposes the model into a finite quadratic programming,and it is proved theoretically that the presented method can be applied to obtain the exact solution of the model.Then,in view of the issue of the slow solving speed in the big data environment,this work optimized the model's constraints by reducing the number of constraints and the consumption of computing resources while the feasible region remained unchanged,so as to improve the solving speed of the model.The numerical case results show that the proposed method can effectively improve both of the calculation accuracy and speed of the additive two-stages DEA model.
To reflect the actual relationships between sequences to the greatest extent and expand the field of negative grey relational analysis,this paper establishes a bidirectional grey A-S(Area-Slope)comprehensive relational model based on proximity and similarity.Firstly,according to the positions between correlation sequences,the same or inverse area relationship is determined,and the grey relational model based on area differences is established.Secondly,considering the directionality of the sequence slope,the sign function is introduced to build a bidirectional grey relational based on the slope differences.Then,the absolute value of the correlation degree of the two models is synthesized as the correlation strength of the sequences to characterize the proximity and similarity,and the direction of the grey correlation degree based on the slope differences is determined as the relational direction of the sequences,so as to construct a comprehensive relational model,and then the properties of the model are further discussed.Finally,through the analyses of the influencing factors of agricultural development in Jiangxi Province and China's milk powder import trade,the results based on the novel model are compared with the other eight classical grey relational models'.The results show that this model has the advantages in comprehensively representing the sequence relationship,reflecting the relational direction,and improving the correlation resolution.
In the wake of epochal international developments,such as Brexit,the Sino-American trade tensions,and global health crises exemplified by the outbreak of what is referred to as New-castle pneumonia,the impetus towards regional economic integration has escalated as a strategic imperative for economies seeking resilience against multifaceted economic shocks.Concomi-tantly,there is a discernible shift characterized by the re-shoring of manufacturing,offshoring of industrial chains,and domestication of production processes.This shifting landscape necessitates rigorous investigation into the stability of regional economic systems.Leveraging an innovative framework premised on ecological nested structure theory,this study undertakes a tripartite empirical examination of production network stability within the Asia-Pacific realm through measurement,simulation,and evolutionary analyses.Our findings illuminate that the morphol-ogy of global and regional production networks conforms to a"core-periphery"topology.The evolutionary dynamics and concomitant economic ramifications of this structure find congruence with the Local World Evolutionary Network model within network science.Furthermore,we posit that nested metrics offer robust quantification of the stability of these economic systems.Notably,the generalist industrial sectors that are situated within the nested core contribute to the network's stability,whereas specialist sectors induce potential destabilization.Simulation analyses using nested metrics reveal a strong correlation between a nation(region)'s role and its position within the production network,and the nation(region)'s level of economic develop-ment and capacity for risk mitigation.Moreover,an evolutionary examination of the Regional Comprehensive Economic Partnership(RCEP)affirms that augmenting trade volumes among member states fortifies the stability of(cross-border)production networks in the Asia-Pacific re-gion,which,in turn,fosters economic growth and industrial optimization within the constituent countries(regions).
Under the real demand that Chinese manufacturing industry is advancing to the high end,servitization empowered by digital technology has become an important strategy for manufacturing enterprises to achieve high-quality development,which can stimulate the innova-tion vitality and create new development opportunities,enabling them to provide customers with intelligent solutions that integrate products,software and services.This study firstly collects for-eign and domestic literature that is closely related to digital technology and servitization,selects to form a sample database,and constructs a theoretical analysis framework.Secondly,on the basis of introducing the servitization and digital technology,the evolution trend of the digital servitization is revealed,and the realization approach of the empowerment is analyzed.Thirdly,based on the division of the value chain of manufacturing enterprises,this study expounds the application scenario of servitization empowered by digital technology from the perspective of front-end product innovation,middle-end hybrid product generation and back-end service inno-vation.Finally,the"double-edged sword"effect of the empowerment with potential value and risks is analyzed,the countermeasures and suggestions are put forward,and the future research directions of this topic are provided.
A tremendous amount of information is transmitted between agents in the form of digital signals in digitalization era.Under such background,how to accurately screen the true information in the information sources through signaling games is an urgent problem to be solved.However,the classical solutions to this problem are vulnerable to interference and cost a lot of resources.This paper proposes a technical route that is not only different from the classical solutions,but also different from the mainstream EWL and Li-Du-Massar quantum game frame-work.Further,by constructing a quantum superdense coding circuit,the information screening mechanism in digital signaling games is theoretically and experimentally studied.We find that the quantum circuit has obvious comparative advantages compared with the classical circuit.First,it can directly reveal the true information of the information source matrices without the design and operation of extra game rules.Second,its information screening mechanism is robust and will not be affected by random interference.Third,the corresponding information screening process does not require additional economic resources to support.The above three advantages are particularly prominent when it is necessary to screen a large amount of information.
Propose a complete framework for decomposing value added,the multiplier decompo-sition and structural decomposition methods are extended to the multi-country and multi-sector input-output model to quantitatively analyze the dual circulation evolution trend of China and the endogenous power of the domestic circulation from 2000 to 2020.Research Findings:The overall dependence of China's economic development on the domestic circulation is in a"U"shape,and the inflection point appeared in 2006.On the left side of the inflection point,the main reason for the decline of the domestic circulation is China's decreasing value-added rate;on the right side of the inflection point,the improvement of the final demand rate,the toal demand coefficient and the value-added rate become the main driving force for the domestic circulation to rise in turn.Compared with investment,consumption has always been the main factor affecting the domestic circulation change in final domestic demand.The countries relying on the external circulation have shifted from developed countries to developing countries and developed coun-tries.The dependence of the development of manufacturing industry on the domestic circulation has also increased since 2008.During this period,the increase of the toal demand coefficient of the service industry for the manufacturing industry,the upgrading of the industrial structure,and the improvement of the manufacturing value-added rate have successively occupied the main position in the cyclical rise of the manufacturing industry.The change in the domestic circula-tion of digital industry is dominated by its own final demand rate or the total demand coefficient of non-digital industry,and the dominant industries in the domestic circulation of non-digital industry are mainly themselves.
The solidarity value is a prominent value in the cooperative game with transferable utility,and plays an important role in solving the problem of benefits distribution,as it reflects both fairness and solidarity.We discuss axiomatizations of the solidarity value by the sign differential marginality axiom,together with the weakened equal average gains axiom(called sign equal average gains).Meanwhile,a case of revenue sharing in the carbon trading alliance is discussed,in order to show the mechanism of the solidarity value.We find that:1)the solidarity value can be characterized by efficiency,sign equal average gains(or average-null player property)and sign differential marginality;2)it is necessary to use the solidarity value to allocate benefits when there are a number of participants with strong development potential in the alliance.
Banks play a crucial role in the economy.Ensuring efficient resolution of failing banks is essential to prevent systemic risks and achieve the Second Centenary Goal.We have constructed a virtual economic system using a macroeconomic agent-based model and employed computer simulations to explore three strategies for addressing troubled banks:Bail-in,purchase and assumption,and bailout.Our findings indicate that the systemic importance of failing banks is a key factor in determining the effectiveness of different resolution strategies.For banks that aren't deemed systemically important,a bailout might boost output and reduce unemployment in the immediate term.However,it can skew economic incentives,ultimately heightening economic fluctuations and undermining the stability of the financial system in the longer horizon.In contrast,allowing systemically important banks to go bankrupt not only provokes a liquidity crisis but also triggers cascading defaults and financial crisis.Thus,we advise regulatory bodies to evaluate the systemic significance of banks through a methodical and balanced approach.For banks not of systemic importance,market-driven solutions should be pursued.Meanwhile,direct interventions should be reserved for faltering banks that present systemic threats.
In the critical period when the poverty alleviation is gradually deepened and fully launched,many companies respond to the government's call to actively participate in targeted poverty alleviation.This paper discusses empirically the impact of participating in targeted poverty alleviation on companies systemic extreme tail risk using A-share listed companies in China from 2012 to 2020.The empirical findings show that,1)participating in targeted poverty alleviation can significantly mitigate the companies'exposure to the extreme tail risk spillover of the market,and can reduce effectively firms'systemic extreme tail risk;2)the impact of targeted poverty alleviation on reducing the systemic extreme tail risk has the larger sensibility in the companies with the larger size,the higher institutional shareholding ratio and the higher leverage ratio;3)the mechanism analysis shows that by participating in targeted poverty alleviation,companies delivery positive signals to the market about fulfilling social responsibility,which has positive external effects such as reducing financing constraints and increasing stock liquidity,as well as positive internal effects such as improving internal corporate governance capacity and efficiency,and all these are important reasons why targeted poverty alleviation significantly improves the immunity of companies.This paper shows that participating to targeted poverty alleviation can significantly improve the immunity to the extreme tail risk spillover of the market,and is the"immunity tool"in the risk management of firm,and therefore has the important implications to how to prevent the extreme tail risk shock of the market and can provide the valuable reference to for companies to actively participate in social responsibility activities such as targeted poverty alleviation.
Accurately describing the co-movement among industries in global stock market and the shocks of major emergencies on it are significant for international investors.We choose stock index returns of all industries in the past 30 years until 2021 as empirical data,and use the time-domain and frequency-domain Granger causal models to construct static and dynamic complex connectedness networks and calculate their co-movement indicators.We investigate the receiving and sending co-movement information level of industries,as well as their response to shocks of major emergencies,at the perspective of full-period,short-period and long-period.The empirical results show that(ⅰ)the overall co-movement for all industries at full-period is stronger than that at short-period and long-period,this means that the investors without a specific investment period face high market risk;(ⅱ)the receiving or sending co-movement information level of some industries exceeds the average at short-period or long-period but not full-period,it indicates that making decisions only according to the co-movement characteristics at full-period will make short-period and long-period investors ignore some key industries when constructing their portfolio;(ⅲ)during the European sovereign debt crisis with the lasting impact of the Subprime crisis,the overall co-movement for all industries at long-period is much stronger than that at full-period and short-period,but during the rest of the major emergencies dominated by its own influence,they are basically the same.This illustrates that during a major emergency,if there is additional impact from the previous major emergency in addition to itself,then its long-period shocks is greater than full-period and short-period shocks,while there is almost no difference between full-period,short-period and long-period shocks for independent major emergencies;(ⅳ)during the COVID-19 epidemic,the Subprime crisis and the European debt crisis,the sending and receiving co-movement information intensity of an industry at one period are different from that at other two periods,but they are basically the same during the rest of the major emergencies.It confirms that the full-period,short-period and long-period shocks on the ability to receive and send co-movement information of an industry are different for the major emergencies that seriously affect the business environment,while there is almost no difference between these three kinds of shocks for the other major emergencies.
To achieve the green logistics of"less pollution,less carbon emissions,and less en-ergy consumption",this paper investigated the co-optimization of routing and speed for a mixed fleet comprising traditional fuel vehicles and electric vehicles under a carbon trading mechanism.To minimize the total cost of fixed,energy consumption,and carbon trading,a mixed integer programming model is developed,which incorporates an actual energy consumption model based on distance,load,and speed.To solve the problem,a parallel improved variable neighborhood search algorithm with speed optimization is designed,which utilizes global destroy-repair oper-ators from the large neighborhood search and a parallel local search strategy.Benchmarks and empirical examples are used to verify the effectiveness of the algorithm and to analyze the impact of fleet composition,carbon trading mechanism,and speed optimization strategy on the distribu-tion scheme.The study can enrich the related research on vehicle routing problem and provide valuable theoretical insights for logistics enterprises to reduce costs and increase efficiency,as well as for government to guide market behavior.
As an important international public good,global cooperation on epidemic pre-vention and control not only faces the trade-off between major infectious diseases control and economic-social development,but also to participate in international cooperation mechanisms on major infectious diseases:Is it good interaction that leads to Pareto optimality,or prisoner's dilemma of tit-for-tat?The paper use the theory of sequential reciprocity to analyze the internal mechanism,major obstacles,and the necessary and sufficient conditions for win-win cooperation in the prevention and control of major infectious diseases.The innovative view of this paper is to demonstrate the optimal strategy of China's selective participation and provision of inter-national public goods based on the principle of matching capability and responsibility,that is,to select"exchange gifts",or"tit for tat",or"discretionary choice"depending on the specific situation.Beware of the"Kindleberger trap"of insufficient international public supply and the"great power responsibility trap"because of the"good for evil"strategy under the the traditional Oriental culture of"Shu Tao".
In an automated warehouse,a module refers to an independent unit capable of performing a defined task that consists of a group of interlinked equipment.For example,com-mon storage modules include four-way shuttle storage and retrieval system,autonomous shuttle storage and retrieval systems and puzzle-based storage system.Lift is the main equipment for connecting different functional modules.Due to the high transfer frequency between modules,as well as the constraints of lift capacity and budget,lift has become a bottleneck of warehouse operation efficiency.In view of lift scheduling problem in transfer operation,we present a mixed integer-programing model and a constraint programming model with the goal of minimizing the total completion time,and develop an interval insertion greedy algorithm to solve the problem.Numerical experiments show that for small-scale instances,the mixed integer-programing model and the constraint programming model can provide the optimum solution,and IIG can obtain near-optimum solution efficiently;for medium-to large-scale problems,constraint programming model and IIG can obtain high-quality solutions in a short time.Moreover,compared with the adaptive large neighborhood search algorithm and the Lin-Kernighan-Helsgaun algorithm,the IIG can obtain better solutions more quickly in various scale instances.Compared with first-come,first-served rule commonly used by enterprises,the IIG can reduce completion time by more than 25％for different instance scales.In terms of system configuration,the smaller the difference between the number of layers of left and right module shelves,the bigger average hourly throughput of the lift.The influence of shelf depth on throughput is not significant,but the average pallet completion time rises with increasing depth.The empty shelf layer number of 3 or 4 can be a good balance for system efficiency and cargo space utilization.
The rapid development of industry-themed ETFs has brought investors diversified industry asset allocation opportunities.However,the critical question is how investors can al-locate rational and practical industry assets to obtain long-term healthy development dividends from high-quality enterprises in the industry.The CSI 300 primary industry index is taken as the research sample from 14 January 2005 to 15 July 2022.This paper uses the adaptive boosting(AdaBoost)algorithm to generate investor views and establishes the optimal allocation strategy of industry assets through the Black-Litterman(BL)model.The numerical example results show that the BL model based on the AdaBoost ensemble algorithm(BL_AdaBoost)can obtain better investment performance than the market portfolio,equal weight portfolio,and MV model.In addition,we further examine the performance of BL_AdaBoost in different periods.The results show that BL_AdaBoost can resist risks to a certain extent during the shock of extreme risk events and the overall continuous downturn of the stock market,thereby reducing the loss of the investment portfolio.During regular stock market volatility periods,BL_AdaBoost can achieve higher returns than other portfolios.
Grey prediction model is an effective technique to solve small sample and uncertain information system.However,with the improvement of data collection technology and methods,more and more data can be collected.The limited sample adaptability limits the application of grey model in different fields.To solve this problem,this paper proposes a dynamic part accu-mulated generating operation(DPAGO)based on data-driven technology.Then,we carry out grey modeling under different frequencies(annually frequency,quarterly frequency and monthly frequency),and construct dynamic part accumulation discrete grey model(DPDGM(1,1))and discrete seasonal model(DPDGSM(1,1)).In order to verify the prediction performance of the new model in a large sample scenario,two new models is applied to forecast three types of cases with different frequencies,sample lengths and development trends,namely annually GDP,quar-terly power generation,and monthly raw coal production.And the accuracy is compared with a series of comparison models.The results show that two new models have a good modeling effect for larger samples,whose simulation and prediction accuracy are better than other models,including ARIMA,SARIMA(SARIMA-GARCH),SVR,BPNN,Holt-Winters,DGM(1,1)and DGSM(1,1).It provides a new forecasting method and modeling idea for grey theory on larger sample system.
In the context of the"double carbon"target,promoting the green and low-carbon transformation of economic and social development is a major systemic project.Developing re-newable energy and improving energy efficiency will help to build a more efficient green energy system.Analyzing the effect of energy transformation has important reference value for formulat-ing a reasonable carbon emission policy and achieving medium and long-term emission reduction targets.This study takes this as a starting point.Firstly,static panel and dynamic panel system generalized method of moments(GMM)are used to estimate the impact of energy transforma-tion,renewable energy efficiency and non-renewable energy efficiency on major macroeconomic variables.Secondly,the intermediate production sector is subdivided into renewable energy pro-duction sector and non-renewable energy production sector.The dynamic stochastic general equilibrium(DSGE)model is constructed to analyze the short-term impact of energy transfor-mation impact,renewable energy efficiency impact and non-renewable energy efficiency impact on major macroeconomic variables.The analysis shows that:1)energy transformation promotes the transfer of resources between sectors,the output of renewable energy production sector will increase,while the output of non-renewable energy production sector and carbon emissions will decrease;2)The improvement of two kinds of energy efficiency will produce economic expansion effect,but it will also produce energy rebound effect and increase carbon emissions;3)At the end of the simulation period,the implementation of the carbon emission intensity policy will promote the growth effect of three shocks on output,but will also hinder the emission reduction effect and aggravate the rebound effect in the process of energy transformation.The implementation of the carbon tax policy will inhibit the rebound effect of two types of energy efficiency shocks on carbon emissions.In the process of energy transformation,we should rely on a reasonable carbon emission policy and formulate medium and long-term emission reduction targets.This study has important reference value for China to analyze the effect of energy transformation.
For recycling competition and profit allocation of closed-loop supply chain with two channels to collect used products,a continuous noncooperative-cooperative biform game model is established under the deposit return to manufacturer implemented by the government.Firstly,in the noncooperative game part,retailer and recycler compete to collect used products,and forms competitive situation.Secondly,manufacturer,retailer and recycler cooperate to opti-mize the sales price of the used products,the wholesale and retail price of new products,that is,determine the characteristic function of coalitions in cooperative game part under the given competitive situation.Shapley value is used to obtain players'allocated profits.Finally,taking the allocated profits of retailer and recycler as the payment function,the optimal used products'collection rate of retailer and recycler are solved.The non-cooperative cooperative biform game model established in this paper combines the non-cooperative game with the cooperative game,which can simultaneously solve the problem of dual channel recycling and pricing strategy opti-mization,and profit distribution,and provide a theoretical basis for the government and supply chain members to make production,sales,and recovery decisions.Our results show that,1)The government's implementation of deposit refund system for manufacturers can promote cooper-ation between the manufacturer and retailer,and increase retailer's enthusiasm for collect used products,but it has no obvious incentive effect on recyclers.An appropriate increase of unit deposits is conducive to improving social welfare,but excessive deposits are not conducive to the stability of the recovery market.2)The fierce competition among recycling channels damages supply chain profits,consumer surplus,and social welfare.Recyclers should choose appropriate ways to moderately reduce market competition.3)Used products have the high cost advantage and can achieve a win-win situation of profit and environmental performance.Production and recycling companies should actively seek measures to improve the usable value of remanufactured products.
服务贸易成本变动影响服务要素的跨境流动,在全球价值链分工下可经由投入产出关联影响各国生产成本与最终产品价格,进而对消费者的福利产生影响.本文基于WIOD数据库首先计算了 2000-2014年中国对外服务贸易成本,在此基础上利用全球投入产出价格模型和消费者福利模型,从等价性变化和补偿性变化两个角度考察了中国服务贸易成本变动对各国消费者福利的影响.结果表明,中国对外服务贸易成本在2000-2014年呈下降趋势,航空运输和金融服务业降幅最为明显;中国服务贸易成本变动给制造业带来的价格效应高于服务业和农业,其中知识密集型制造业最高,资本密集型次之,劳动密集型最低;消费者福利分析显示,中国服务贸易成本变动对各国消费者福利均有改进作用,且除自身和世界其他地区外给美国、日本、韩国、德国带来的福利改进最为明显;细分服务业来看,分销、邮政运输和金融商务的对外贸易成本变动的福利效应最高.进一步,国际比较显示,2000-2014年中国服务贸易成本变动给世界其他经济体带来的消费者总福利改进是美国的约3.3倍,与美日欧等经济体相比正外部性更强,引致的福利增进更具普惠性.本文可为深入推进服务业对外开放和以人类命运共同体共识加强各国合作提供政策参考.
