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

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

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

Climate change profoundly affects the survival and development of mankind, and provides a major opportunity for the transformation of economic development mode and the promotion of urbanization. Based on the panel data of 284 prefecture-level cities in China from 2003 to 2018, we systematically investigated the effects of climate change on urban green development, its mechanism and regional differences. We found that climate change may make greater differences in economic green growth between the north and south in China. Relative to the base weather bin (6℃~12℃), rising temperature significantly reduced urban green total factor productivity, and the effects would be more obvious for southern cities; conversely, falling temperature would promote urban green development and the positive effects of falling temperature is mainly reflected in northern cities. The mechanism test shows that the expansion of urban construction area will not aggravate the negative impact of high temperature, but improving the green coverage can significantly reduce the inhibitory effect of high temperature on urban green development. The positive effect of low temperature in winter on urban green development will decrease with the increase of energy consumption. In addition, the effects of climate change on urban green development will continue to deepen in the medium and long term, especially based on the forecasting of high fossil energy consumption development path, the green growth of southern cities will be more impacted. Our research provides new evidence for assessing the economic impact of climate change at the urban scale, and also provides useful policy inspiration for responding to climate change and promoting urban green development.

1. School of Finance, Shanghai Lixin University of Accounting and Finance, Shanghai 201209, China; 2. School of Economics, Shanghai University of Finance and Economics, Shanghai 200433, China

The research on the nonlinear dynamic evolution of Cournot duopoly game and its equilibrium state in the economic system has been paid much attention by the academic circles, while the multiple constraints of credit have become the key to the stable development of modern enterprises, and have an important impact on the game behavior and stability of enterprises. In view of this, this article considers the multiple constraints on credit such as downstream enterprises' credit default, bank loan willingness and bank credit risk appetites, to build the upstream duopolies output decision dynamic Cournot duopoly model under the multiple credit constraints. Combining the nonlinear dynamic theory and Cournot game, the influence of multiple credit constraints on the equilibrium stability of two upstream duopolies' dynamic output game and the evolution characteristics of Cournot-Nash equilibrium are analyzed systematically. Through theoretical derivation and simulation research, it is found that:1) The increase of downstream enterprises' credit default, bank loan willingness and the gap between bank credit risk appetites has a stabilizing effect on the Cournot-Nash equilibrium of output decision, and the degree of influence of the three decreases in turn; 2) The increase of the gap between bank credit risk appetites will result in the oligopoly under the chaotic state; 3) The increase of fluctuation frequency of downstream enterprises' credit default and bank loan willingness can restrain chaotic behavior, but it is not conducive to the stability of Cournot-Nash equilibrium.

With the development of the digital economy, coupon cooperation through e-commerce platforms and their merchants has become increasingly popular. This not only brings complexity to the operational decisions of e-commerce platforms and their merchants but also poses challenges for regulators and researchers to analyze its economic consequences. This paper constructs a theoretical model to study the optimal strategy and economic benefits of e-commerce platforms and their merchants when issuing coupons cooperatively. We further compare the above results with the traditional coupon strategy and examine the interaction between coupon strategies and advertising promotion strategies. We found that:1) settled merchants would be more willing to participate in the cooperative issuance of coupons with i) the decrease in the platform commissions, ii) the cost of merchants when participating in the cooperative issuance of coupons and iii) the expansion of the market scale of merchants' platform sales channels; 2) the merchants' incentive to participate in coupon cooperation increases with e-commerce platform's spending on marketing; 3) there exists a complementarity between participating in the cooperative issuance of coupons and advertising investment; 4) when settled merchants can rely more on advertising and marketing to increase demand, cooperative issuance of coupons will increase the actual price paid by consumers and hence hurt consumer welfare. This article provides a new perspective on understanding the economic benefits of emerging cooperative issuance of coupons.

This paper considers a supply chain consisting of one upstream firm (UF) and one downstream firm (DF), which are linked by backward shareholding, in the sense that the DF owns equity shares in the UF. The UF is jointly owned by the DF and other shareholders, and each shareholder has both the control right and the dividend right of the UF. In the setting of joint control, all shareholders have rights to participate in the decision-making of the UF, and establish the decision-making objective for the UF by balancing their different interests. The paper explores the impacts of equity shares held by the DF in the UF, on the supply chain operations, by investigating operating decisions (e.g., pricing decision) of the two firms in the upstream Stackelberg supply chain and the downstream Stackelberg supply chain, respectively. The results show that:In the upstream Stackelberg supply chain, the UF provides the product at the price of the cost, and the supply chain achieves coordination, if and only if the percentage of equity shares held by the DF reaches 50%; in the downstream Stackelberg supply chain, the UF may provide the product at the price of the cost even if the percentage of equity shares held by the DF is lower than 50%, and the supply chain achieves coordination only if the percentage of equity shares held by the DF reaches 50%.

This research studies the game relationship between platform's logistics strategy and retailer's demand forecast information sharing strategy in e-commerce platform selling mode. In the e-commerce platform selling system, which is consisted of a retailer and an e-commerce platform. The retailer owns the private demand forecast information and the e-commerce platform could determine logistics mode (the retailer operating, e-platform operating and third party operating logistics modes), are assumed. The information sharing models under three logistics modes are built. The incomplete information static game and Bayesian Nash equilibrium solution of e-commerce platform logistics strategy and retailer demand information sharing strategy are studied. The results show that, when the logistics cost coefficient is high, the pure strategic Nash equilibrium is e-commerce platform chooses the retailer operating logistics mode, and retailer conceals demand forecast information; when the logistics cost coefficient is low, the pure strategic Nash equilibrium is e-commerce platform chooses e-commerce platform operating logistics mode, and retailer shares demand forecast information.

For ultra-high-dimensional censored data, feature screening can be performed to remove noise in big data, and classical statistic analysis can be applied after that. This paper proposes a robust partial correlation coefficient for feature screening, and introduces an inverse probability weighting method to deal with censoring. Based on that, a new joint feature screening method is developed. By incorporating the information of the entire conditional distribution of the failure time, our method can depict the relationship between the response and covariates comprehensively. Compared with the traditional Pearson partial correlation coefficient, this measurement is robust to outliers, heavy-tailed distribution and heteroscedasticity. Moreover, the joint feature screening method proposed based on this metric eliminates the interference caused by the correlation between the covariates through the projection effect, so as to reduce the false negative errors, false positive errors and tackle the problem of collinearity of covariates. We establish the sure screening property of our method and give the details of the iterative algorithm. The competence of our method is further confirmed through comprehensive simulation studies and a real data example.

Modelling the US West Texas Intermediate (WTI) crude oil spot price structure has received an increasing attention in recent years. However, most of the existing literatures focus on classical econometric methods and point-valued counterfactual analysis, which may suffer from informational loss. This paper proposes a novel interval-based counterfactual analysis to explore the impact of crude oil fluctuation events that appeared on WTI crude oil spot prices in 2011. The interval-based models can be used to simultaneously estimate hypothetical values of level and volatility of WTI price that are not affected by the event. These counterfactual estimations are based on the cross-sectional correlations between WTI and other 10 international crude oil spot markets. Our findings reveal that both the level and volatility of WTI price were lowered by the oversupply of crude oil production caused by shale oil boom, and this effect did not disappear until the end of 2014. The results can provide an important reference for the government, industry practitioners and individual investors.

Accurate forecasting of crude oil prices has always been the focus of government management decision makers, investment entities and academics. However, due to the interaction of various risk factors such as monetary policy and geopolitics, crude oil price exhibit more complex nonlinear characteristics, making crude oil price forecasting an unprecedented challenge. Our paper conducts an empirical study on INE and WTI crude oil futures markets through a crude oil price forecasting model (PVMD-QSBT-ECS) conducted based on data decomposition, reinforcement learning integration strategy and error correction technology. Firstly, the crude oil futures price series are decomposed by variational mode decomposition (VMD) using particle swarm optimization (PSO) via adaptive weights; Secondly, the Q-learning (QL) algorithm is utilized to determine the optimal weight combination of stacked bidirectional long short-term memory (SBiLSTM), bidirectional gated recurrent unit (BiGRU) and temporal convolutional network (TCN) to build an integrated prediction model, and then the dynamic error correction is applied to the prediction outcomes. Finally, the modified Diebold and Mariano (M-DM) test was utilized to further evaluate the forecasting performance of PVMD-QSBT-ECS. The empirical results indicate that the PVMD-QSBT-ECS model proposed in this paper not only has lower prediction error than other comparative models, but also exhibits superior performance in both emerging and developed markets, and also has obvious advantages in forecasting at different step sizes.

Urban critical infrastructure networks (CIN) are closely related. It is of great practical significance to systematically analyze the vulnerability of associated urban CIN failure. However, the vulnerability association analysis of CIN is faced with the dilemma of knowledge gap caused by the information differences between responsible organizations. Considering the knowledge interaction and sharing across organizations, this paper proposes an ontology configuration method for vulnerability association analysis of urban CIN. The core of ontology configuration is to transmit the disaster scenario information of related organizations through scenario ontology mapping with feature-level set pair analysis, so as to drive the updating and improvement of the organization's scenario description. For the mapped disaster scenarios, rule-based reasoning is used to activate ‘association ontology' and identify associated CIN failures. According to the time difference and scenario difference, ‘evaluation ontology' is reused to generate vulnerability association results. The use case results show that the proposed method is helpful to transfer key knowledge from different organizations through timely and effective organizational communication, which further improves its systematicness and timeliness of CIN vulnerability association analysis. At the same time, this method can reduce the semantic barriers of cross organizational knowledge and promote the effective integration of knowledge.

The group consensus reaching process induced by the empirical threshold can be significantly influenced by non-cooperative behavior, reducing the consistency and robustness of decision results. Concentrating on the three core contents of the consensus reaching process:Interaction network structure, consensus driving element, and preference interaction model, we propose the adaptive group consensus model based on the BA-BSO interaction mechanism. Considering the imbalance of interaction relations, the BA free scale interaction network is developed to control the interaction opportunities of non-cooperators adaptively and dynamically. Then, the individual interaction utility function, satisfying supermodular game condition, is designed to induce the spontaneous emergence of group consensus, which consists of proximity degree and consensus cost. Through the interaction process, we propose the BSO algorithm-based preference interaction model to reflect the individual interaction preference and avoid the excessive influence of non-cooperators. Moreover, the optimal alternative selecting rule is proposed based on the "Majority Principle", enhancing the consistency of group decision results. Finally, the effectiveness and efficiency of the proposed consensus model are illustrated by numerical example analysis and comparative analysis part.

The rapid development of information technology has profoundly changed the way of communication among employees and various online channels have begun to emerge. In order to explore how to use a variety of online and offline channels to promote the diffusion of creative idea, this paper regards the complex system composed of employees communicating the creative idea through multiple channels in an enterprise as a group of multiplex networks. A multi-channel diffusion model of creative idea with consideration of the interaction between any two channels for diffusion and choice overland from the perspective of multiplex network. Threshold conditions for persistent diffusion of a creative idea through online and offline channels are given based on the dynamic analysis of model. The diffusion process in the multiplex networks composed of multiple channels is numerically simulated. Research shows that companies should not blindly build new online communication platforms for employees. It is easy to waste time and psychological resources in the process of choosing channels and hinder the spread of creative idea when there are too many kinds of available channels. If employees communicate only through online channels and ignore offline channel, it will also reduce diffusion efficiency. Only when employees share ideas through offline channels as much as possible, the efficiency of idea diffusion will be maximized and the scope of diffusion will be widest. The research can provide decisions for companies to rationally use online and offline channels to promote creative idea diffusion.

Autonomous vehicles are expected to generate significant impact on travel behavior and modal split in transportation system. This study investigates the influence of combined strategy of tradable credit scheme (TCS) and public transit fare on commuters' travel mode choice (such as the conditions for various portfolios of travel modes, the penetration rate for shared autonomous vehicles (SAVs), and the credit price), and the number of commuters transferring among different travel modes and the total travel cost. The results show that the equilibrium credit price can be uniquely determined after the combination strategy is introduced. When a certain condition is met, the number of commuters for regular vehicles and the total number of vehicles on highway decrease significantly by switching to the modes of SAV or public transit, and the effect increases with the public transit fare and the amount of charged credit. Finally, the optimal solution of the total travel cost appears in the region including all three travel modes, where the amount of charged credit equals a certain value and the public transit fare achieves its maximal value in the feasible region. This paper is helpful in quantifying the impact of the new technology and providing the theoretical reference for traffic management departments to develop effective management strategies.

The study of wisdom of crowds shows that the group judgment formed by aggregating individual judgments is more accurate than the individual judgments. In order to improve the aggregation quality and eliminate the systematic bias in individual judgment and heuristic process, this paper concretely constructs a variety of aggregation models based on extreme ideas. Two indicators, accuracy and superiority, were set up to quantitatively evaluate the wisdom of crowds validity of aggregation. The data of individual probability estimation were obtained through the probability judgment experiment on Master of Business Administration. Based on the data of individual probability estimation, Several sequential strategies and regional strategies of individual probability aggregation are compared, and the extreme function selection and parameter optimization are completed. The results show that:1) If only the probability estimates within intervals [0, 0.45] and [0.55, 1] are polarized, the local extreme strategy performs better than the global extreme strategy. 2) Average-then-calibrate strategy is better than calibrate-then-average strategy; 3) In the average-then-calibrate strategy, the anti-S-type polarizing function proposed in this paper can outperform the classical polarizing function. 4) The performance of extreme calibration aggregation is better than that of traditional arithmetic average method. This paper proposes a better strategy of aggregating individual probability estimates, which can significantly improve the wisdom of the crowds validity under the same individual valuation conditions.

Study on variation diagnosis of hydrological series can provide basis and reference for various water conservancy and civil engineering planning and management decisions. It is difficult to detect the sudden change of dynamic structure of hydrological series. This paper presents a new method for detecting the variation of a hydrological sequence based on matrix-based Renyi's alpha order entropy. First, the matrix-based Renyi's alpha order entropy is introduced to describe dynamic structure of the hydrologic sequence. Second, a sequence of moving cut matrix-based Renyi's alpha order entropy is constructed by the moving window technique; it is used to describe the evolution of dynamic structure of hydrological system. Finally, Pettitt test is applied to detect the change point and the level of significance of the moving cut sequence. Taking runoff and sediment sequences in Weihe River, Taohe River, Kuye River and Xiliugou River as examples, researches on detection of change point are performed, and the results of Shannon entropy, Mann Kendell and moving T test are also included for comparison. The results indicate that no mutation occurred in the runoff sequences at Xianyang Station, Zhuangtou Station and Red Li interval, while all the annual runoff sequences changed at Zhangjiashan Station, Huaxian Station, Wenjiachuan Station and Longtouguai Station. Moreover, all the probabilities of mutation are greater than 90%. There are change points in the 1980s for the annual sediment discharge sequences at Xianyang Station, Zhangjiashan Station and Zhuangtou Station, while the change points at other stations are in the late 1990s. All the probabilities of the mutation are greater than 95%. Compared with some researches, the results generated by the matrix-based Renyi's alpha order entropy are basically consistent with the actual situations, while those generated by the other methods are quite different from the actual situations.

The change of trade cost in services affects the cross-border flow of service elements, and under the division of global value chains, it can influence the production cost and final product price of each country through the input-output linkages and then affect the welfare of consumers. Based on WIOD database, this paper firstly calculates the level of China's trade cost in services from 2000 to 2014. On this basis, using global input-output price model and consumer welfare model, this paper examines the impact of the change of China's trade cost in services on consumer welfare in different countries from the perspective of equivalent variance and compensating variance. The results show that China's trade cost in services showed a downward trend from 2000 to 2014, with the most obvious decline in air transportation and financial services. The price effect of the change of China's trade cost in services on manufacturing industry is higher than that of service and agriculture, and the effect on knowledge-intensive manufacturing industry is the highest, followed by capital-intensive and labor-intensive manufacturing industries. The analysis of consumer welfare shows that the change of China's trade cost in services has improved consumer welfare of all countries, and it has brought more obvious welfare improvement to the United States, Japan, South Korea and Germany besides itself and the rest of the world. In terms of detailed service sector, distribution, postal transportation and finance and commerce services have the largest welfare effect among all services industry. Furthermore, international comparison shows that the welfare improvement to the rest of the world brought by the change of China's trade cost in services was about 3.3 times as much as that by the Unites States from 2000 to 2014, and China shows greater positive externality and provides more universal benefit to the world than the United States, Japan and the European Union. This paper can provide policy reference for further promoting the service trade openness and strengthening mutual cooperation among countries with the consensus of the community with a shared future for mankind.

Based on the customs trade database from 2000--2015, this paper identifies Chinese firms' tendency to export competitive strategies and examines the impact of internal and external product networks on firms' changing competitive strategies and their mechanisms. It is found that firms generally adopt cost-competitive strategies to participate in exports, but firms can reduce their cost-competitive tendencies by converging on internal and external networks. And when both convergence levels reach a high level, firms can shift from cost-based competence to quality-based competence. The mechanism analysis shows that higher product quality differentiation and greater market demand will weaken firms' cost competitive tendency; proximity to external product networks weakens cost competitive tendency mainly through the channel of strengthening product quality differentiation, and proximity to internal product networks improves quality competitive tendency mainly through the channel of strengthening export market demand. The heterogeneity analysis shows that this network effect is more effective for new entrants and domestic firms but is weakened by policy support, as the impact of information flow will be limited by the fluency of knowledge extraction, transfer and diffusion. The findings of the study not only reveal the feasibility of enterprises using information flow of product networks to enhance export competitiveness, but also suggest more diversified thinking on the optimization of industrial policy implementation.

Enhancing total factor productivity is a key initiative to promote high-quality economic development and build a strong socialist modern state comprehensively. We examine the impact of convertible bonds on firm's total factor productivity and the corresponding mechanism based on a multi-period difference-in-differences model. We find that convertible bonds can significantly increase firm's total factor productivity. The mechanism tests show that convertible bonds can improve total factor productivity by alleviating financing constraints and optimizing resource allocation. The heterogeneity tests show that debt-like convertible bonds have a more significant impact on total factor productivity. Moreover, the contribution of convertible bonds to total factor productivity is more significant in firms with higher external monitoring and regions with lower financial development. Our paper adds empirical evidence on the economic consequences of convertible bonds from the Chinese capital market and complements the research framework in the field of financial development and economic growth, which has important implications for promoting innovation in financial instruments and high-quality economic development in China.

Fund performance is the core question of fund research. Using the commission paid to all brokerage firms, this paper maps brokerage networks of mutual funds and shows a positive relation between network centrality and risk-adjusted performance. Central funds pick better stocks, and their trades become better predictors for abnormal stock returns around subsequent earnings announcements. When differentiating funds' valuation-motivated and liquidity-motivated trades on single trade level, this paper finds that central funds outperform peripheral funds at anticipation of earnings surprises only for valuation-motivated trades. The centrality premium is more pronounced for small fund company, non-crisis period and funds with low liquidity demand. The results indicate that brokerage network centrality premium is due to the private information provided by the brokers. This paper signifies the importance of business network to China's capital market and casts insights into understanding of information transfer mechanisms and the economic effects of business networks in China's capital market, as well as fund investors.

It is of great theoretical and practical significance to accurately model and forecast the volatility of financial assets in the complex and changeable financial market environment. Therefore, based on a variety of volatility decomposition methods, and embedded with the Markov regime-switching approach, this study reconstructs multiple new heterogeneous autoregressive realized volatility models, and further takes Shanghai Stock Exchange 50ETF as the research object to compare the prediction accuracy of each model. The main empirical results are as follows. First, the model confidence set (MCS) test shows that the newly constructed model (MS-PHAR) combined with Markov regime-switching and quantile array volatility has the best predictive performance and various robustness checks confirm the above conclusion. Second, during the periods of high and low volatility, before and after the COVID-19 epidemic, and considering the leverage effect, the newly constructed MS-PHAR model still has a good performance.

Based on the realistic background of "guiding financial services to serve the real economy", this paper constructs an evolutionary game model to describe the game evolution process of investment and financing behavior between financial institutions and real enterprises, and studies the mechanism that affects the dynamic evolution path. The analysis shows that both parties tend to make decisions that promote business cooperation in the stable state. In addition, using agent-based modeling approach, this paper transforms the evolutionary game behavior of the two sides into a resource allocation problem of investment and financing funds, which includes geographical factors. By simulating the optimization process of real enterprises and financial institutions, it analyzes the influence of various factors on the proportion decision of investment and financing. It is found that by means of cost control, income distribution and government subsidies, financial institutions can be promoted to serve real enterprises in the way of indirect financing. In addition, this paper also finds that capital market financing costs, corporate profitability and geographical factors have a significant impact on decisions of two parties. Finally, this paper compares and combines the results of the two models and puts forward some suggestions.

Using a large sample of 437345 inventors, this paper constructs a directional flow network of inventors, and investigates the influence and mechanism of the inventor mobility network on firm innovation. We find that the different directions of inventor mobility network have different impacts on firm innovation. The inventor inflow network has a significant positive impact on firm innovation, while the outflow network exerts a negative impact. The mechanism investigation shows that inventor mobility network affects firm innovation through knowledge spillover and cooperative R&D. Moreover, such positive effect of inventor flow network is stronger in two situations. One is that inventors have higher innovation performance and come from competitive firms; the other is that the firms are non-SOEs or executives are inventor CEOs. This article highlights the impacts of the directional flow network of inventors on firm innovation, and reveals the underlying mechanism. It is also of important significance for firms to break through the technical distance and regional boundary of knowledge spillover and improve innovation performance to maintain long-term competitive advantages.

The high-quality development of enterprises is the micro foundation for the high-quality development of China's economy, and high-quality development of enterprises requires high-quality asset structure allocation. Based on the data of A-share listed companies from 2010 to 2020, this paper studies the impact of corporate asset structure mismatch on the high-quality development of enterprises, and tests the mediation effect of technological innovation and financing constraints between them. Research has found that asset structure mismatch significantly hinders the high-quality development of enterprises. In terms of mechanism, technological innovation has played a significant part of the mediation effect, and asset structure mismatch has hindered the high-quality development of enterprises by weakening their technological innovation capabilities; Financing constraints have a masking effect, and asset structure mismatch further hinders the high-quality development of enterprises by exacerbating financing constraints. The above conclusions are still valid after the robustness test. Further research shows that, except for accounts receivable, asset mismatches of various types are generally not conducive to high-quality development of enterprises, and the impact of asset structure mismatches on different dimensions of high-quality development of enterprises varies. Moreover, the negative impact of asset structure mismatch on the high-quality development of enterprises is significant in state-owned and non-state-owned enterprises, large-scale and small-scale enterprises, enterprises in the eastern and central western regions, and enterprises with low R&D intensity, but not significant in enterprises with high R&D intensity. The research conclusion can provide reference for effectively alleviating asset structure mismatch, optimizing strategic deployment, enhancing technological innovation level, improving financing constraints, and promoting high-quality development of enterprises.

By matching the unbalanced panel data of over 2.9 million enterprises in Chinese Industrial Enterprise Database from 2000 to 2013 with county-level air pollution data, regression discontinuity design is used to examine the effect of air pollution on firm's total factor productivity from theoretical logic and empirical evidences. The results show that air pollution significantly reduces firm's total factor productivity. Every 10 μg/m³ increase in PM_2.5 results in a 0.23% decrease in firm's total factor productivity. Non-state-owned enterprises and labor-intensive enterprises are more sensitive to air pollution. Larger scale and higher environmental enforcement intensity cities where enterprises are located are easier to mitigate the effects of air pollution. Air pollution suppresses total factor productivity by increasing inventory, reducing factor productivity, increasing financing constraints, reducing R&D investment and increasing employee turnover. Our paper not only enriches the relevant theories of air pollution and total factor productivity, but also provides new practical ideas for firm's sustainable developments.

In order to promote the green transformation of supply chain enterprises, it is of great significance to study the coexistence strategic of enterprise carbon emission reduction and the income distribution of the alliance under the dual carbon background. Considering the influence of alliance structure on profit distribution, this paper takes the three-level green supply chain with restricted alliances as the research object, and adopts the biform games method to analyze the problem of strategy choice and profit distribution involved in the carbon emission reduction decision of the supply chain. First, describes the biform games problem of supply chain carbon emission reduction decision-making. Secondly, construct a biform games model of supply chain carbon emission reduction decision based on A-T solution, and prove the existence conditions and properties of the solution for this model. Finally, the validity and practicability of the proposed method are indicated by a numerical example, and the profit distribution of A-T solutions and Shapley values in the cooperative game stage is compared.

Various companies that once focused on online sales channels have considered expanding offline channels. In particular, their possible channel development strategies include no offline, direct, or indirect offline channels. By constructing a Stackelberg model, we study the offline channel development strategy of a supplier who only sells online through an e-commerce platform. As a result, we obtain the supplier's optimal offline channel development strategy and corresponding pricing decisions by comprehensively considering different online sales modes, consumer preferences about different channels, and sales costs in different channels. The findings show that the supplier should always extend the offline channel. In addition, the supplier's existing online sales mode vigorously influences his offline development strategy. Specifically, the supplier's optimal strategy is always developing the offline direct channel if the existing online sales model is direct sales. Alternatively, if the existing online model is indirect sales, his offline development strategy depends on the sales costs of different channels. When the sales cost of the online channel is higher, or the online and offline channel sales costs are both lower, the supplier's optimal strategy is offline direct sales. However, when the sales cost of the online channel is low, and the sales cost of the offline channel is high, the supplier's optimal strategy is offline indirect sales.

This paper constructs a two-level supply chain that composed of a manufacturer and a retailer, and explores encroachment and advertising decision-makings under the partial integration of supply chain—partial forward integration (PFI) and partial backward integration (PBI). It is found that: When only the retailer invests in advertising, in the case of PFI, manufacturer encroachment will lead to the retailer reducing advertising intensity, and manufacturer encroachment is not always the optimal strategy. When the channel competition is fierce, the manufacturer's interests will be harmed due to the encroachment, and the retailer's profits will always be damaged, thus resulting in win-lose and lose-lose results; while in the case of PBI, manufacturer encroachment will lead the retailer reducing advertising when the share holding is small and the channel competition is large, otherwise it will promote the advertising. Moreover, the impact of manufacturer encroachment on the profits of the members in the supply chain also depends on the share holding proportion and the channel competitive intensity, and there will be three results: Win-win, win-lose and lose-lose. Further, when considering that both the manufacturer and the retailer invest in advertising, no matter under the PFI or PBI, the retailer's advertising decision is consistent with that of only considering retailer advertising, but the manufacturer's advertising intensity and profit in the encroachment are always greater than that of the non-encroachment. In this situation, encroachment is a dominant strategy for the manufacturer, and leads to win-win and win -lose results.

As an important organization for resource allocation and benefit coordination in the era of platform economy, platform ecosystem has become the hot discussion of current research. However, most current studies have focused on platform competition and platform governance strategies, neglecting the strategies of complementors when entering the platform. In this paper, we incorporate three types of complementors' platform entry strategies, i.e., the multihoming strategy, the functional design strategy, and the multiple identity strategy, empirically testing the influences of the reputation on these three strategies based on the resource dependence theory. Furthermore, we reveal the moderating effect of competition intensity between complementors and platforms on the relationship between reputation and platform entry strategies. Evidence from APPs and platform applets shows that complementors with higher reputation tend to adopt the multihoming or the multiple identity strategy, and they tend to maintain fewer functions into the platform. In addition, the competition intensity between complementors and platforms strengthens the relationship between reputation and platform entry strategies. This study sheds new light on the behavioral strategies of complementors in the platform ecosystem, expands the application contexts of reputation theory, and provides a new perspective on the competition and cooperation relationship of platform ecosystem, giving practical guidance for complementors to choose the appropriate platform entry strategy.

In online retail markets, uncertainty about the quality of emerging products and firms' dynamic pricing lead to the possibility that consumers may engage in strategic waiting and delay the purchase of products. When considering the endogenous time preferences, consumers choose their own purchasing strategy (myopic or strategic), while spending an additional sunk cost of time and effort (called strategic cost) if choosing to be strategic. Based on consumer utility theory, we develop a two-period game-theoretic model, where the firm and consumers simultaneously learn and update perceived quality from online reviews in the second period. We study consumers' purchasing strategies when they have endogenous time preferences, and the impact of such consumers on the firm's pricing strategy. The results suggest that the perceived quality and strategic cost affect consumers' purchasing strategies and lead the firm to implement different dynamic pricing strategy depending on consumers' purchasing strategies. An increase in strategic cost may either increase the firm's profit, consumer surplus and social welfare, or increase the firm's profit at the expense of consumer surplus and social welfare. In addition, an increase in the accuracy of review information does not always benefit the firm. When both the strategic cost and perceived quality are at a high level, more accurate review information may even hurt both the firm's profit and consumer surplus. Also, consumers do not always benefit from strategic waiting behavior compared with the case where all consumers stay myopic.

Due to the existing inverse data envelopment analysis (DEA) methods fail to address the problem of the optimization of resource allocation in the two-stage production structure containing undesirable outputs, this study proposes a new inverse DEA method with undesirable output within the two-stage production structure for analyzing the optimization of environment resource allocation. Then, a new inverse DEA method with frontier changes and undesirable output in two-stage production structure is further developed by relaxing the constraint of unchanged production frontier, which can be used to analyze the optimization of environment resource allocation in two-stage production structure for the future. These two proposed methods open the 'black box' of the complex internal structure in two-stage production structure and provide more comprehensive and accurate information, which are useful tools for resource allocation and formulation and planning of development goals. Finally, an empirical study relating to China's industrial two-stage system is given to verify the rationality and effectiveness of the methods in this study.

Establishing research and development relationships with other firms have been an investable trend for firms to gain competitive advantages. However, risk propagation leads to the high failure rate of R&D network. To analyze how indirect relationships influence on risk propagation in research and development (R&D) network, this paper proposes two methods to measure the indirect relationships from two dimensions of firms and risks. Based on this, the R&D network risk propagation model is built from three aspects, which are the definition of risk load, the definition of risk capacity, and how risk occurred firms trigger other firms to occur risk. Then, the mechanism of risk propagation is analyzed by numerical simulations based on empirical and simulated R&D networks. The research results show that the indirect strength of firms has a negative impact on the robustness of R&D network under risk propagation, but it has a positive impact on the range and speed of risk propagation. However, with the increasing of the number of indirect paths between firms, the effect on the robustness of R&D network, the propagation range and the speed of risk propagation will show a diminishing marginal effect. Thus, firms should also pay more attention to risk status of these indirect cooperation firms with common partners. When considering risk loss interactions, and firms take account the additional losses caused by risk interactions into risk capacity, which will improve the robustness of R&D network. It is essential for firms to add the additional loss caused by risk interactions in risk prevention measures. The difference effect of three attack strategies on the robustness of R&D network under risk propagation will gradually disappear with the increase of the number of indirect path lengths between firms, which indicates that firms in any position in a particular network could have a great impact on the robustness of the network.

In multi-item logistics systems, loading and transportation of heterogeneous items can often cause damaged items, management difficulties, etc. For such an application scenario, this paper proposes a binary quadratic program for the bin packing problem with heterogeneous items. Based on Dantzig-Wolfe decomposition, a branch-and-price algorithm and a variable neighborhood search are designed. Compared with two traditional bin packing schemes, the superiority of the new bin packing scheme with heterogeneous items is verified by experiments. The new scheme takes both economy and flexibility into account. Both two proposed algorithms show competent performance on 180 randomized numerical instances. The average gap of variable neighborhood search is 1.8% and the average computing time is 1.06 seconds; those of the branch-and-price is 0.30% and 815.40 seconds respectively, which outperforms the commercial solver Gurobi. Finally, this paper, through introducing "the tolerance to heterogeneity", provides a trade-off solution between bin-minimizing objective and penalty-minimizing objective for a decision maker. Compared with the existing solution method, our trade-off solution is more elaborate and reasonable, providing a scientific decision support for enterprises.

Based on dynamic parameter identification, a recursive discrete grey model was constructed to address the limitations of grey prediction algorithms in characterizing dynamic system characteristics. Its feasibility and practicality were verified in practical problems. By introducing a memory factor parameter and reconstructing the cost function for model structure parameter optimization using recursive least squares method, the derivation process and related properties of the model were provided. Furthermore, the time response formula for model predictions was presented using dynamic structure parameters and optimized iteration base values, and a heuristic algorithm was employed to solve the non-linear optimization problem of model hyperparameter estimation. The new model was applied to three numerical examples: Failure test data for the C919 aircraft power supply system, wear and erosion of artillery barrels, and the lifespan prediction of aviation lithium batteries. Experimental results demonstrate that the new model has good predictive performance and application value. Compared to existing models, the new model can better describe system dynamics and effectively improve modeling accuracy.

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 renewable 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 formulating 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 transformation, renewable energy efficiency and non-renewable energy efficiency on major macroeconomic variables. Secondly, the intermediate production sector is subdivided into renewable energy production sector and non-renewable energy production sector. The dynamic stochastic general equilibrium (DSGE) model is constructed to analyze the short-term impact of energy transformation 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.