New urbanization construction is an essential driver for expanding domestic demand and a critical measure to facilitate internal circulation. This paper evaluates the impact of new urbanization pilot projects on the consumption levels of the rural migrant using data from the China Migrants Dynamic Survey. The study reveals that, compared to non-pilot areas, the consumption levels of rural migrants in pilot areas have significantly improved, and a series of robustness checks support this conclusion. Mechanism analysis indicates that the pilot projects have increased income, enhanced access to public services, and strengthened a sense of identity, all of which contribute to the increased consumption levels of rural migrants. The pilot projects have a more substantial effect in regions with low dialect diversity and more effectively raise the consumption levels of employed and intra-provincial migrants. Additionally, the pilot projects have boosted both daily and housing consumption of migrants, with a more pronounced effect in counties and county-level cities. The findings provide theoretical explanation and empirical evidence for establishing a long-term mechanism to expand domestic demand.

How digital platforms enable enterprises to achieve disruptive innovation is a key concern for managers in the context of the platform economy. Building on the literature on platform ecosystem and dynamic capability, we explore the effect of digital platform capabilities on disruptive innovation. Leveraging data from 209 Chinese high-tech enterprises that have either developed their digital platforms or integrated with existing ones, we find that digital platform capabilities have a significantly positive impact on disruptive innovation. We further show that structural flexibility and organizational unlearning partially mediate the relationship between digital platform capabilities and disruptive innovation. Specifically, digital platforms empower shaping structural flexibility, dismantling rigid organizational routines, and identifying emerging niche markets targeted for disruptive innovation on the one hand. On the other hand, they facilitate organizational unlearning, breaking away from existing knowledge path dependencies, and acquiring complementary knowledge required for disruptive innovation. Additionally, structural flexibility has a significant positive impact on organizational unlearning, and both factors serve as chain mediators between digital platform capabilities and disruptive innovation. This study deepens our understanding of the formation mechanisms behind disruptive innovation in high-tech enterprises within the platform economy framework. It addresses the practical question of which capabilities high-tech enterprises need to cultivate for disruptive innovation from a micro perspective. These insights provide valuable theoretical guidance for enterprises seeking to leverage digital platforms for achieving disruptive innovation in the context of ongoing digital transformation.

The digital transformation of government is a major initiative to improve the government's governance capacity in the new era, which provides a new idea to promote "tax governance by numbers". In order to explore the micro tax governance effect of government digital transformation, this paper takes the establishment of Big Data Bureau as a quasi-natural experiment, takes listed companies from 2008 to 2020 as the research samples, and uses the DID model to test the micro tax avoidance governance effect of government digital transformation based on the A-S model and information asymmetry theory. The results showed that government digital transformation can effectively inhibit corporate tax avoidance, and its inhibition is mainly generated through joint tax audits, optimization of business environment and government-enterprise cooperation and sharing. Further research shows that government service-oriented Big Data Bureaus and regions with stronger tax collection and management are more conducive to the micro tax governance effect of government digital transformation, and that the tax avoidance governance effect of digital government is more pronounced for highly digitized enterprises. This paper can extend and deepen the governance effect of government digital transformation and provide theoretical basis for the government to further promote digital transformation and create a fair tax environment.

Digital transformation is an important micro foundation of China's industrial upgrading, and the characteristics of CEO play a key role in the digital transformation of enterprises. Based on relevant data from listed companies spanning the years 2011 to 2021, this study constructs adaptive LASSO and QUBO models using machine learning to select trait variables. The goal is to grasp the main contradictions and systematically study the influence mechanism of some important CEO characteristics on digital transformation. According to the results of the machine learning model, this paper argues that the characteristics of old, female, financial experience, management experience are the main traits promoting digital transformation, and production experience is the main inhibiting trait. Mechanism study shows that age of CEO will affect his experience richness in a reversed U-shaped relationship and affect his risk tendency in a U-shaped relationship, this makes a reversed U-shaped relationship between CEO age and digital transformation. Moreover, financial experience and management experience promote digital transformation by alleviating information asymmetry and improving corporate governance, production experience increases the short-termism characteristic of the CEO, which inhibits digital transformation, gender will promote digital transformation by less risk tendency. In this paper, two machine learning models are used for variable selection, it provides a reference for solving the problem of subjective variable selection, this paper enriches the research on CEO traits and digital transformation and provides some enlightenment for the design and adjustment of company management.

Strengthening compliance management is a key measurement for Chinese central state-owned enterprises to comprehensively implement the strategic deployment of governing the country in accordance with the law. After the quasi-natural experiment of the implementation of the "Guidelines for Compliance Management of central state-owned enterprises (Trial)'', based on the empirical analysis of the panel data of China's Shanghai and Shenzhen A-share listed central enterprises and local state-owned enterprises from 2016 to 2021, studied the time difference and individual difference before and after the implementation of the guidelines by using the duel-differential model, the aim of this article is to examines the impact of the implementation of the guidelines on the ESG performance of listed state-owned enterprises. The study found that the implementation of compliance guidelines significantly improved the ESG performance of listed companies of central enterprises, and the research conclusion remained valid after the robustness test such as placebo test was adopted. Moreover, the compliance guidelines of central enterprises mainly enhance the ESG rating of enterprises through external supervision, which is complementary to the company's internal governance capabilities, especially those with stronger internal governance capacity or weaker external supervision effects. This article provides micro-evidence for Chinese central state-owned enterprises to improve corporate governance and achieve high-quality development by strengthening compliance management construction. The study provides positive inspiration for listed companies to strengthen compliance management in order to optimize ESG performance.

A brand owner, which sources from an upstream supplier and sells to the downstream consumers, normally has private information about the supplier's corporate social responsibility (CSR) and has to decide whether or not to disclose such information to consumers. Consider the upstream supplier can be more responsible (h-type) or less responsible (l-type), facing different responsible violation risks, which impacts consumers' purchasing utility. The brand owner chooses whether or not to disclose its private information on the supplier type to the consumers. Under the disclosure scenario, the brand owner informs the consumers about the supplier's type. Under the non-disclosure scenarios, the brand owner signals the supplier's type to consumers through CSR efforts and the price. By comparing equilibrium outcomes under two information scenarios, it is shown that the brand owner sourcing from an h-type supplier prefers to disclose the information, but it may not necessarily invest higher CSR efforts depending on the brand owner's CSR cost coefficient and consumers' belief regarding the brand owner sourcing from the h-type supplier. Whereas, the brand owner sourcing from an l-type supplier will choose not to disclose information. This is because the brand owner can achieve higher profits from pooling and reducing the cost of investing in CSR efforts. As consumers' belief on the probability of sourcing from the h-type supplier increases, the brand owner's motivation to disclose the h-type supplier will be reduced, and it is more incentive to not disclose l-type supplier. In expectation, the brand owner has an ex-ante incentive to audit the supplier's CSR information in advance and disclose the information to consumers. Finally, this paper extends to examine the robustness of the results by considering the scenarios of myopic consumers and heterogeneous consumer valuation.

In the context of the normalization of bidirectional fluctuations in the RMB exchange rate, the bank-firm relationship, as a crucial linkage mechanism between firms and financial institutions, plays an essential role in enhancing corporate exchange rate risk management capabilities. Based on relationship banking theory and the optimal currency area theory, this study empirically investigates the impact and mechanisms of the bank-firm relationship on corporate exchange rate exposure, using a sample of A-share listed companies from 2016 to 2022. Empirical evidence shows that the bank-firm relationship significantly reduces corporate exchange rate exposure, with this result remaining robust across various endogeneity and sensitivity tests. The mechanism suggests that the bank-firm relationship mitigates exchange rate exposure by facilitating the use of foreign exchange derivatives and foreign currency debt. Further analysis indicates that increased RMB internationalization weakens firms' dependence on the bank-firm relationship for exchange rate risk management. Heterogeneity analysis reveals that ownership structure and regional marketization levels significantly influence the bank-firm relationship's effectiveness in reducing exchange rate exposure. This study advances the literature on the economic consequences of the bank-firm relationship and corporate exchange rate risk, providing both theoretical and practical insights for enhancing corporate risk management and promoting financial services in the real economy.

Recently, defaults in the global sovereign bond market have occurred successively. As the largest creditor country, China is likely to be significantly impacted by overseas debt market. However, due to the time-varying characteristics of debt risk spillover effect, the traditional linear analysis framework may not be applicable, and may even lead to significant deviations in the conclusion. In view of this, this paper adopts the newly developed nonlinear smooth-transition vector autoregression model (STVAR), to conduct research on sovereign debt risk contagion relationship in 16 countries (regions) including China's mainland and the United States. Specifically, based on commodity research bureau index, global economic policy uncertainty, CBOE implied volatility index, American excess bond premium, nominal dollar index and federal funds rate, this paper constructs asymmetric risk contagion matrix in different periods, analyzes the role of countries (regions) in debt risk contagion and the path of contagion, examines the influencing factors and mechanisms of sovereign debt risk transnational contagion. It is found that China's mainland has been the net risk importer in the sovereign debt risk contagion network for a long time, and the rising of inflation, the increase of economic policy uncertainty, the global market sentiment turns pessimistic, the boost of financial risks, the strengthening of the US dollar and the monetary policy turns hawkish will amplify the imported impact of global sovereign debt risk on China's mainland. On this basis, we put forward relevant policy suggestions to prevent imported debt risks from the perspectives of preventing debt risks at key nodes, monitoring the macroeconomic environment and controlling the transmission channels of sovereign debt risks.

To deal with the complex and ever-changing business environment, startups employ diversification techniques. As a result of these diversification techniques, entrepreneurs must put effort over many tracks. Diversification creates new tasks for corporate development, and these duties may be cooperative or competitive in nature. The impact of inter-task linkages on dynamic contract design and investor expected returns is investigated in this study. Furthermore, due to the disparities in agency structures amongst organizations, this study is separated into two cases: Multi-agent and single-agent. This study gives optimal dynamic contracts and investor expected profit equations under both agency structures using the martingale approach of continuous-time principal-agent theory, and explores the impact of varied task relationships on them. Under the multi-agent model, the entrepreneur's response function to incentives is independent of task relationships, whereas task relationships only affect the entrepreneur's response function under the single-agent model. There is a fixed ratio between the entrepreneur's multiple efforts in the single-agent model, and the ratio is governed by task linkages and cost considerations. Using the background of venture capital, this study builds a particular example of entrepreneurs who consistently exert utmost effort and discovers that conflict connections diminish expected returns while collaborative partnerships increase expected returns. When there is poor task collaboration or disagreement, investors prefer the multi-agent model. But as task collaboration improves, the single-agent approach is preferable.

This paper uses textual analysis techniques to identify anti-takeover provisions existing in the company's articles of association, and focuses on the mechanism of anti-takeover provisions on company performance from the perspective of supply chain stability. It is found that anti-takeover provisions can significantly enhance firm performance, and this positive effect is particularly significant in firms with large customers or dependent suppliers. This suggests that anti-takeover provisions contribute to maintaining supply chain stability and thus enhance firm performance. The results of the mechanism of action test show that from the perspective of customers, anti-takeover provisions can help firms obtain more orders from large customers, which in turn generates scale effects and reduces selling expenses. From the supplier's perspective, anti-takeover provisions can help the company obtain raw materials from suppliers in a timely manner, which can reduce operating costs and increase the turnover rate of raw materials. This paper expands the literature on the economic consequences of anti-takeover provisions, which is important to understand the role of anti-takeover provisions in promoting supply chain stability.

Supply chain disruptions caused by unexpected events lead to economic loss risks for supply chain node companies. Based on the demand-side risk of the supply chain, this paper portrays three scenarios: No business interruption insurance, separate retailer insurance and manufacturer-retailer joint insurance, and considers the endogenous problem of insurance rates to incorporate insurance companies into the supply chain system. The study investigates the risk transfer effect of business interruption insurance on insured subjects, the mechanism of business interruption insurance influencing the decision making of supply chain participants and the value realization process of business interruption insurance under different insurance decision scenarios. The study finds that: The joint insurance strategy of manufacturers and retailers has the best risk transfer effect in the supply chain and the strongest value-added effect of business interruption insurance; the insurance company has the boundary of insurance rate decision, and the insurance company can only maximize its own profit by setting the appropriate insurance rate level to achieve a win-win situation for manufacturers, retailers and insurance companies; the impact of retailers' overconfident behavior on supply chain participants' profit enhancement and value addition of business interruption insurance is closely related to the insurance strategy.

With the development of informatization and networking and the acceleration of urbanization, the breadth and depth of the impact of disasters have been deepened. While as an effective measure and essential guarantee in response for disaster, the inter-government coordination still has a lot of problems to address, such as unclear division of rights and responsibilities, blocked resource sharing, and unreasonable interest coordination. Based on these problems, this study proposes an emergency response strategy model considering information sharing and resource sharing according to evolutionary game theory, and analyzes the external factors (e.g., disaster characteristics, regional location) and internal factors (e.g., cooperation efficiency, rescue efficiency, interest coordination, etc.) that affect inter-government coordination from a micro perspective, as well as guiding effect of the construction of the vertical government information sharing platform on horizontal inter-government emergency coordination, so as to analyses and compare the strategy selection and evolutionary path of governments. The following results and policy suggestions can be obtained through the numerical analysis of case of the Guangdong-Hong Kong-Macao Greater Bay Area: 1) The information sharing platform promotes the efficiency of horizontal inter-governmental communication and coordination to some extent. 2) External factors have a significant impact on horizontal inter-governmental coordination. Besides, horizonal governments determine the coordination amount of relief supplies with overall consideration. 3) The form of interest distribution affects the horizontal inter-governmental coordination. Both sides need to comprehensively consider the disaster situation, relief benefits, costs and other factors to allocate supplies and benefits so that increase the possibility of collaboration. 4) The traceability of information sharing platforms can provide more reasonable incentives, subsidies and punishments for vertical governments, which promotes the horizontal inter-government division of power and responsibility and prevent from causing the failure of emergency management. It is suggested that the horizontal government should design an emergency plan and cooperation evaluation mechanism in the disaster preparation stage, formulate an appropriate benefit distribution mechanism based on internal and external factors, and conduct regular drills to improve the efficiency of cooperation. The vertical government should actively promote the construction of information sharing platform, use blockchain and other information technology to improve the sharing process and supervision system, and set up reasonable punishment and incentive mechanism, so as to promote the efficient response of disaster emergency under inter-government coordination.

Energy storage for new energy vehicles (NEVs) is of great significance for power grid load shifting, ensuring power supply security, and promoting clean electricity consumption. The competitive charging demand function during the peak power period and the off-peak power period is first proposed, and then an energy storage game model including grid companies, charging companies and NEV users is established. Furthermore, the influence of key factors such as peak and valley electricity prices, charging service fees, energy storage participation, and peak power grid operating costs on energy storage decisions is further investigated. Finally, the incentive efficiency of three kinds of NEV energy storage policies including valley power subsidy policy under power price regulation, peak power taxation policy under power price regulation and marketization of power price is also comprehensively examined. The results demonstrate that: 1) The NEV energy storage will not change the charging service fee and the total power consumption of the system during the peak and valley periods, but it can effectively increase the charging amount and the benefits of all parties during the valley power period at night; 2) NEV users will obtain most of the NEV energy storage benefits, and the peak-to-valley price difference and peak power grid operating costs are the key factors driving all parties to participate in NEV energy storage; 3) the valley power subsidy policy is better than the peak electricity tax policy, and when the peak electricity price is high, continuing the electricity price regulatory policy will have a better incentive effect than the marketization of electricity prices. This study will be beneficial to improve China's NEV energy storage operation and incentive policies.

With the development of power exchange technology, China's new energy vehicle industry proposes battery as a service under the separation of vehicle and battery, which allows consumers to rent batteries on demand. Against this background, this paper constructs a Stackelberg model composed of the new energy vehicle manufacturer and the battery supplier. Two battery service models are considered: Not providing battery rental service (N) and providing battery rental service (B). The results show that, when the body price is relatively high (low), the new energy vehicle manufacturer should choose (not) to provide the battery rental service, but it is harmful (beneficial) to the battery supplier. Therefore, when the body price is moderate, the battery rental service can achieve a win-win outcome for the new energy vehicle manufacturer and the battery supplier. Meanwhile, we reveal the impact of the battery rental service on the decision of the new energy vehicle supply chain and analyze the impact of the battery life level and the body expectancy life on the win-win outcome's realization conditions. We also provide useful managerial implications for both the new energy vehicle supply chain and the overall industry.

The lack of charging infrastructure has severely limited the large-scale promotion of electric vehicles in China, and how to design an effective incentive policy to promote investment in charging infrastructure is an urgent problem to be solved. By constructing a tripartite game model, this paper investigates the effects of two types of EV charging infrastructure subsidy policies in the presence of consumer range anxiety and discusses the choice of the optimal government policy for promoting electric vehicles. The results of the study show that: 1) Compared with the charging infrastructure subsidy policy, the charging service fee subsidy policy not only has a good effect on the promotion of EVs but also improves social welfare. Therefore, the optimal charging infrastructure subsidy policy for the government is the charging service fee subsidy.2) As consumers' range anxiety increases, the optimal charging service fee subsidy rate tends to decrease and then increase. As the externality coefficient of charging infrastructure increases, the optimal charging service fee subsidy rate should continue to increase. 3) The effect of the combination of charging infrastructure subsidy and charging service fee subsidy on the promotion of EVs is not better than that of the single charging service fee subsidy policy. 4) Under the circumstances of changes in charging infrastructure construction and operation, the existence of government budget constraints, the existence of competition from fuel vehicles, and changes in the type of consumer travel demand, the conclusions of the base model are still robust, and the charging service fee subsidy policy is still the optimal choice for the government. The results of this paper have important implications for the promotion of electric vehicles and the achievement of the "double carbon" goal of the transport sector.

Effective incentives are crucial to driving the reclaimed water market. Aiming at the reclaimed water use system composed of local governments, manufacturers, and industrial enterprises, a three-stage dynamic game model was constructed considering water rights trading and tiered subsidy to analyze the impact of the government incentive model (S mode) and dual government and market incentive model (SP mode) on the system optimal decision. The results showed that: 1) Tiered subsidies can increase the total demand for reclaimed water, manufacturer profits, and government benefits, and the water rights trading price can positively moderate this incentive effect of the subsidy policy. There is an optimal boundary between the two measures; whether the government implements subsidy policies depends on the water rights trading price limit. 2) Whether the enterprise receives high-level subsidies determines the impact of tiered subsidies on reclaimed water use decisions of individual industrial enterprises. And there is a threshold effect of the residual transfer ratio of water rights on promoting individual enterprises' reclaimed water use by the water rights trading price. 3) The government's preference for economic benefits has a better pull on demand for reclaimed water than its preference for resource and environmental benefits.

The annual schedules generation for military construction planning is to develop the annual construction schedule for the next year based on the actual situation and feedback in the current year. Based on deep reinforcement learning and multi-objective optimization theory, this paper proposes a dynamic multi-objective optimization algorithm improved by the Deep SubQ-Network. It is used to assist in the generation of annual schedules for military construction planning. First, from the process of implementing military construction planning and generating annual schedules, we analyze the dynamic characteristics of the problem; then, the mathematical model of iterative multi-objective optimization of annual construction schedules for projects is constructed, and the objective function is described in recursive form. Based on a typical deep reinforcement learning algorithm framework, we innovatively propose a SubQ network, which makes it possible to solve multi-objective optimization problems using deep reinforcement learning. We design an iterative optimization algorithm, that can gradually generate annual construction plans for each year; the illustrative part is based on simulated data and set up comparison experiments with other optimization methods to verify the feasibility and advantages of the model and algorithm in this paper.

Taking naval battles as an example, due to the swift movement and constraints posed by distance and obstructions, radar and satellite systems face challenges in swiftly and accurately capturing the motion patterns of maritime targets, thereby impacting combat precision and response speed. To address this, a collaborative mission planning approach involving unmanned aerial vehicles (UAVs) and unmanned vessels is proposed. Initially, integrating motion data acquired by UAVs, a method for tracking and predicting maritime target trajectories is devised to accurately ascertain the real-time positions and forecast the subsequent motion states of dynamic targets. Subsequently, upon acquiring target information, a task planning model for multi-objective weapon-target allocation in naval unmanned vessel operations is established. Finally, considering the influence of mutation operators on weapon-target allocation, a deep Q-learning network-based artificial bee colony algorithm is proposed for resolution. Simulation results demonstrate that the proposed method accurately locates dynamic maritime targets, enhances tracking precision, and exhibits significant advantages in solving multi-objective optimization problems and scalability.

This paper proposes a novel reliability solving algorithm for non-network reliability block diagram (RBD) with complex logical relationships, such as series, parallel, voting, and plus structure, as well as shared components. Motivated by the water flow in a pipe system, we call it water flow algorithm. Initially, some virtual nodes are introduced into the classic RBDs, and a new encoding scheme is designed to store RBD structure. Subsequently, three types of algorithms are designed, namely the node inflow and outflow probability computing, the search for branching nodes, and the reliability solving of systems with shared components. These algorithms constitute the water flow algorithm and enable the accurate solving of complex system reliability within approximate polynomial time. Some numerical examples and a real-world fleet task reliability evaluation case study indicate that in certain application scenarios, this method demonstrates advantages over traditional techniques such as binary decision diagrams (BDD) and Monte Carlo simulation in terms of efficiency, accuracy, and applicability.

Multi-view learning is an emerging artificial intelligence algorithm that focuses on utilizing data with multiple sets of different feature representations for machine learning. However, a major challenge faced by multi-view learning models is their high computational complexity. To improve the computational efficiency of multi-view learning models, this paper introduces the concept of "pseudo Lagrange multiplier" and analyzes the advanced properties of the multi-view twin hyper-sphere support vector machine (MvTHSVM) model. By combining the variational inequality to estimate the neighborhood of the hyper-sphere center and the value range of the radius, a safe screening rule for MvTHSVM (SSR-MvTHSVM) is proposed. This method can identify and remove redundant dual variables in advance, thereby effectively reducing the data size and training cost. Additionally, the obtained SSR-MvTHSVM has the property of "safety", which ensures that the removed dual variables are indeed redundant, resulting in a solution that is exactly consistent with MvTHSVM. The numerical experimental results on three artificial multi-view datasets and thirteen UCI datasets validate the effectiveness of the proposed SSR-MvTHSVM.

Increasing labor income share is the core essence of optimizing the income distribution pattern and achieving common prosperity. This paper examines the impact of local fiscal pressure on the labor income share of enterprises using difference-in-difference method with a quasi-natural experiment of the nation-wide abolition of agriculture tax in 2005. We find that local fiscal pressure significantly reduces the share of labor income of enterprises. Moreover, we find that the negative relationship is more pronounced in small and medium-sized enterprises, regions with lower financial development, regions with lower fiscal self-sufficiency, and firms in labor-intensive industries. Further mechanism analysis shows that fiscal pressure leads local governments to raise tax and non-tax enforcement, increase debt raising, and thus intensify firms' financing constraints. Financing constraints firms cut human capital investment to smooth out fixed asset investment, which in turn leads to a decrease in firms' labor income share. This study not only enriches the research on local fiscal pressure and labor income share of enterprises, but also provides empirical evidence and policy implications on how to improve the primary distribution structure and achieve common prosperity.

China is currently undergoing a dynamic process of evolution in the government-business relationship, with a transition from old to new forms. A new type of government-business relationship that emphasizes "cordiality" and "cleanliness" has become the fundamental approach for governments at all levels to improve this relationship. Examining whether such a relationship can better promote entrepreneurial spirit and drive regional innovation and entrepreneurship is of great significance. This study employs national industrial and commercial enterprise registration data and the China cordial and clean government-business relationship index to construct an annual observation sample of Chinese cities at or above the prefecture level from 2016 to 2019, empirically testing the impact of cordial and clean government-business relationships on regional entrepreneurship levels and its mechanism. The findings are as follows: First, a higher degree of cordial and clean government-business relationships leads to greater improvement in regional entrepreneurship levels. On average, a 10-point increase in the cordial and clean government-business relationship index corresponds to a 2.35% increase in the number of entrepreneurial enterprises in the city, with significant economic implications. Second, cordial and clean government-business relationships play a "cost-saving effect" and "income incentive effect" in empowering regional entrepreneurship and optimizing its structure. Third, the positive impact of cordial and clean government-business relationships on regional entrepreneurship levels is stronger in non-eastern regions, small-scale, and lower-level cities, indicating a "supporting the weak" effect. Fourth, the promoting effect of cordial and clean government-business relationships on regional entrepreneurship levels is stronger when their institutionalization in the region is higher and official media propaganda is stronger. Fifth, this study finds that cordial and clean government-business relationships can significantly improve the entrepreneurial probability of micro individuals, particularly in opportunity-based entrepreneurship, with a stronger empowering effect. In conclusion, the research findings not only enrich the literature on government-business relationships and regional entrepreneurship but also provide timely decision-making support for the current reform practice of building a new type of cordial and clean government-business relationship system in China.

By constructing a two-stage model of dynamic R&D investment of enterprises under own capital investment (OC), independent venture capital (IVC) financing, and corporate venture capital (CVC) financing, this study explores the influence of different financing modes on the dynamic R&D investment decision made by enterprises. The results show that, IVC financing always promotes R&D investment of enterprises in the second stage. It can also promote the R&D investment of enterprises in the first stage when the success probability of R&D projects is higher than a certain threshold. CVC financing can promote R&D investment of enterprises in the first stage when the success probability of R&D project is higher than a certain threshold and the strategic synergy of the R&D project for the CVC parent company is greater than the risk-free project. Compared with IVC, CVC can better promote the R&D investment of enterprises in the first stage, but if the result of the R&D project in the first stage is low quality, IVC can better promote the R&D investment of enterprise in the second stage.

This paper empirically examines the relationship between customer enterprises' ESG rating and supplier enterprises' green innovation, using all A-share listed companies from 2009 to 2022 as the research samples. The empirical results show that customer enterprises' ESG rating can positively influence supplier enterprises' green innovation; customer enterprises reduce the amount of funds absorbed from supplier enterprises, encourage supplier enterprises to increase innovation investment, and improve the managers' green cognition of supplier enterprises are the three mechanisms of promoting supplier enterprises' green innovation through customer enterprises' ESG rating; supplier enterprises' market power will negatively moderate the positive relationship between customer enterprises' ESG rating and supplier enterprises' green innovation. Heterogeneity analysis shows that the positive influence of customer enterprises' ESG rating on supplier enterprises' green innovation is more significant both when customer enterprises are under greater legitimacy pressure or have more substantive ESG practices, and when supplier enterprises lack credibility or face stricter environmental regulations. Further research shows that customer enterprises' ESG rating is more effective in promoting supplier enterprises' green innovation when the uncertainty of ESG rating results is low, and that supplier enterprises' green innovation contributes not only to supplier enterprises' own ESG rating but also to supplier enterprises' total factor productivity. This paper highlights the spillover effects of ESG rating pressure from the perspective of supplier enterprises, and provides empirical evidence and management enlightenments for effectively promoting enterprise green innovation.

The inequality between economic trade benefits and carbon emission costs among cities not only reveals the inherent interaction of cities' carbon decoupling processes among but also reflects the heterogeneity of their industrial division and economic structure. Existing carbon-decoupling index models insufficiently consider the impact of intercity carbon inequality, thereby leading to the ambiguity in the development trend of industrial carbon emissions with the urban carbon decoupling progress. Therefore, this study combines input-output analysis framework and complex network methods to construct a novel carbon decoupling index model considering carbon inequality relationships. Subsequently, this study empirically analyzes the grouped development patterns of carbon emissions in various industries under China's urban carbon decoupling process in 2012, 2015, and 2017, with a focus on 309 cities. The results indicate that the distribution of carbon inequality between Chinese cities exhibits a clear demand-side concentration feature. In recent years, the carbon decoupling benefits obtained by major Chinese cities through carbon inequality have continuously increased, becoming a crucial factor in achieving low-carbon development in their production activities. With the advancement of carbon decoupling, the interdependence of city-level industrial carbon emissions demonstrates a "U"-shaped development trend, initially decoupling and then recoupling. This study contributes to enhancing the understanding of the impact of cross-regional economic environmental connections on urban carbon decoupling development. It can help city managers at different development stages formulate differentiated policy combinations to achieve stable economic development and multi-industry collaborative emissions reduction.

The pollution control strategy of enterprise is not only affected by perceived pressures, but also closely related to enterprise's own resources that can be allocated. Therefore, from the perspective of configuration, this paper analyzes what kind of pressure perception and social capital combination can promote enterprises to adopt high-level environmental pollution control strategies from the perspective of configuration. The results showed that: 1) The effective pollution control mode of enterprises can be mainly divided into three categories: Pollution control path led by government supervision and social relations, the pollution control path driven by social relations led by capital, and the pollution control path driven by social relations led by R&D. 2) "Government pressure" and "R&D platform participation" are important factors that promote enterprises to adopt high-level pollution control. The group of high-politically embedded enterprises, small-sized enterprises, and enterprises in the industrial undertaking zone has a configuration with "government pressure" as the core condition, while the group of low-politically embedded enterprises, large-sized enterprises, and enterprises in the industrial relocation zone has a configuration with "R&D platform participation" as the core condition; 3) Good social relations among entrepreneurs are the basic guarantee for all kinds of enterprises to achieve high-level pollution control. In Chinese manufacturing business environment, fully mobilizing the role of entrepreneurs' social relations is conducive to promoting the high-level pollution control process of various enterprises. The results of this study are helpful to clarify the driving path and mechanism of high-level pollution control behavior of manufacturing enterprises, provide a theoretical basis for enterprises to achieve the phenomenon of "different paths to the same end" of high-level pollution control, and provide scientific guidance for fighting the tough battle of pollution prevention.

The environmental benefits of transportation have always been a focus of environmental economics. However, due to data availability and endogeneity issues, there is limited research on the impact of urban rail transit on ambient air quality at a national level. This study innovatively matches data on subway segments in 39 Chinese cities with a high-resolution daily PM_2.5 dataset, and employs a multi-period difference-in-differences approach to empirically analyze the causal relationship between the opening of new subway segments and local air pollution. The study finds that the opening of new subway segments significantly improves ambient air quality, leading to a reduction of approximately 2.37µg/m³ in PM_2.5 concentration within a 500-meter radius. Moreover, this pollution reduction effect is more pronounced on weekdays in cities with high per capita GDP, heavy air pollution levels, and large-scale coal-fired power plants, or on the initial subway section of a certain line, as well as in the initial segments of certain subway lines. This impact may be attributed to the diversion of public transportation passenger flows from surface transportation, resulting in a decrease in vehicular traffic on the surface. Furthermore, the study identifies network effects of subway openings, as the opening of new segments improves air quality around existing subway segments, and the degree of improvement is higher for existing segments that have closer connections to the newly opened segments. The estimation of health benefits indicates that the opening of subway segments reduces premature deaths caused by PM_2.5, bringing about an estimated economic value of approximately 11.4 to 28.5 billion yuan in terms of improved health for the population covered by the subway. The findings of this study provide theoretical and empirical evidence to better understand the causal relationship between subway construction and air quality, and offer insights for the scientific planning and development of urban rail transit, contributing to urban environmental governance and sustainable development.

Under the dual-carbon goal, it is a foundation for achieving low-carbon transition of supply and demand about how demand promotes enterprises' green production and the cost transfer of green production inhibits consumption. we nest the consumption value into the utility function of consumers, and then develop enterprises' green production decision-making models where the boundary conditions of low-carbon production are identified and the inhibitory mechanisms of cost transfer on consumption are examined. The results show that: Consumption value drives demand structure and enterprise production towards low-carbon, which can be strengthen by the dual-carbon goal; the relationship between carbon price and investment revenue plays a key role in enterprises' production paths, and there is a threshold value for investment revenue; if the revenue exceeds the threshold, carbon price stimulates enterprises to invest in emission reduction, but it has a negative impact on output, and its impact degree will be weakened with the implementation of carbon-abating goals, forming an inverted U-shaped trend; the cost transfer leads to demand structure to be low-carbon upgrade.

Grey market is formed in the arbitrage opportunity brought by the price difference of the same type of merchandise in different regions, which widely exists in the marketing cycle of brand products. At the same time, brand manufacturers strategically choose the release time of products in different channels to alleviate channel conflicts. For example, compared with the synchronization strategy (release of products in both high- and low-price market, simultaneously), the postponement strategy (release of products in high- and low-priced markets, successively) is one of the most common marketing strategies. Based on it, this paper considers a production and marketing system consisting of two manufacturers, one third-party speculator and customers. Aiming at the channel selection strategy of the powerful manufacturer in the grey market environment, the channel model decision models of the powerful manufacturer with synchronous strategy and postponement strategy are constructed respectively. By comparing and analyzing the influence of the grey market and the channel models on the decision-making of the powerful manufacturer. The results show that: 1) When the third-party participates in speculation in the grey market, it is the best channel strategy for the powerful manufacturer to adopt postponement strategy; 2) the pricing strategy of the powerful manufacturer depends on the channel model selection strategy; 3) the involvement of the third-party speculators in the grey market is closely related to the transfer costs, consumers' valuation of products and the degree of substitution of products in different markets. In addition, we also analyzes the influence of the different channel strategies of the powerful manufacturer on the low-price market product pricing of the general manufacturer.

This paper considers an agricultural supply chain consisting of a downstream company and a farmer in the presence of the latter having the adulteration behavior of agricultural raw-material products, in which the downstream company promises to purchase all the effective agricultural raw-material products of the farmer with a procurement price, and the latter determines the amount of brand and counterfeit agricultural raw-material products. Then, we develop a stylized model under the settings with non-blockchain-based (traditional technology-based) traceability and blockchain-based traceability. Our results show that under the blockchain-based traceability, the downstream company can restrain the farmer' enthusiasm to produce the counterfeit raw-material products via the procurement price. In addition, under some mild conditions, the blockchain-based traceability has significantly impact on inducing the farmer to produce less counterfeit raw-material products, and makes the farmer produce more brand raw-material products. However, it is interesting to show that blind pursuit of curbing adulteration by the farmer does not necessarily bring more profits to all the parties. Further, we find that under some cases, choosing the blockchain-based traceability can reach a "win-win" situation for the two parties. Moreover, the blockchain-based traceability does not always cause the company to offer a higher retail price of the final agricultural products, and consequently, consumer surplus is not always improved.

Identifying key nodes in emergency logistics networks contributes to the deployment of maintenance measures, ensuring the stability of emergency logistics networks. We introduce a cooperative game theory approach to identify key nodes in the emergency logistics networks. By defining the feasible coalition and coalition utility in the emergency logistics network, a single-valued solution in the emergency logistics network is proposed based on the Shapley value, which is used as the measurement method of node centrality in the emergency logistics network. Firstly, it is proved that the centrality of nodes calculated by this single-valued solution is mutually independent among different independent emergency logistics networks, which reduces the computational complexity. Secondly, the feasible component efficiency and road fairness are defined, and it is proved that this solution is the unique single-valued solution satisfying the two axioms mentioned above. Finally, the rationality and robustness are illustrated by numerical examples. Taking the single-valued solution as the measurement method of node centrality in an emergency logistics network can not only fully consider the topological characteristics of the network, but also take into account the non-network characteristics of nodes, which provides strong theoretical support for the optimization and stability maintenance of emergency logistics networks.

Since innovations rely on the combination and recombination of knowledge elements that are caused by organizational collaborations, innovations are dual embedded in the interdepend networks constructed by knowledge networks and collaboration networks. Accordingly, it has significant implications for maintaining the continuous operation of interdepend networks and preventing the neck problem of innovation by unveiling the destruction of combinatorial relationships of knowledge elements within knowledge networks and the cascade effects of organizational cooperative ties in collaboration networks caused by the failure of knowledge elements based on technical sanction. On the basis of constructing the three-dimensional properties structure ofof the knowledge element, we divide the failure strategies of the knowledge element into six categories. By using the data of the new generation of information technologies industry of China from 2000-2021, we comprehensively reveal the impact of knowledge elements failure on interdepend networks in accordance with the change of resilience of structure and function. Furthermore, drawing on the mechanism of knowledge replacement, we develop the stability strategies of network resilience and explore the ways to guarantee the operation of interdepend networks via the strategies practice simulation. We find that: 1) In the knowledge networks, different knowledge elements were combined following the existing innovation logic. Although knowledge elements were connected as scattered clusters, their contents emerged with the tendency of diversity. Knowledge elements that are characterized by relatively medium expertise but high relativeness can create serious neck problems of innovation. 2) In the collaboration networks, organizations had embedded their multiple knowledge elements into the knowledge networks, the cooperation of organizations was related to several knowledge elements and could not directly break by the failure of one knowledge element. 3) The strategies of the initial calculated-based and recalculated-based obtained similar effects. 4) Three essential ways can maintain the stability of interdepend networks. Including comprehensively combining the knowledge elements with medium-degree, adequately capturing the knowledge combinatorial opportunities that were provided by knowledge elements with medium in-degree, and continuously developing knowledge elements with fundamentality and high relativeness.

Trust relationship is the main tool to determine the importance of subject in group comprehensive evaluation. However, in the existing research, trust relationship mostly depends on emotional factors and is regarded as static and fixed. This can easily lead to the "trust risk" problem. How to avoid this problem and improve the reliability of trust relationship has become one of the important research contents in group evaluation. To solve this problem, this paper first constructs a trust relationship network based on Page Rank. A dynamic trust relationship measurement method is proposed, which considers affective trust and cognitive trust comprehensively, and realizes the dynamic calculation of the interaction process of trust relationship with groups. Further, a group consensus reaching method based on dynamic trust relationship is proposed to improve the efficiency of consensus reaching. On this basis, a group evaluation method considering the dynamic trust relationship of evaluation subjects is constructed. Finally, the validity and reliability of the method are demonstrated by an example of the selection of major investment projects.

Cross-efficiency analysis is an important extension of data envelopment analysis, which evaluates decision-making units by integrating both self-evaluation efficiency and peer-evaluation efficiency. Existing Cross-efficiency analysis methods mostly focus on obtaining efficiency results, without considering the relationship between self-evaluation and peer-evaluation efficiencies or the level of acceptance of peer-evaluation efficiency by decision-making units. This paper focuses on the cross-evaluation process and introduces social network analysis to construct a trust network between self-evaluation and peer-evaluation efficiencies, treating the cross-evaluation process as a group decision-making process within the evaluation system. Based on this, a cross-evaluation method based on consensus and trust relationships is proposed. First, the interval cross efficiency matrix is calculated using both benevolent and aggressive strategy. Then, the bidirectional trust network between decision-making units is constructed using social network analysis, which directly associates self-evaluation and peer-evaluation efficiencies. Second, based on the trust network, two indicators, namely recognition consistency and representativeness level, are proposed to assign corresponding weights to decision-making units. Third, a weighted cross-evaluation maximization model is established, and a consensus analysis is performed on the peer-evaluation efficiency values of each decision-making unit to obtain the final cross efficiency value that reflects the consistency and acceptance of peer-evaluation efficiency by decision-making units. Finally, a case study is used to demonstrate the feasibility and practicality of the proposed method.

In recent years, the emergence of customized buses has provided convenient services for commuters. However, changes in road conditions, attributed to factors such as traffic congestion, bad weather, and car accidents, have increased passenger travel time and significantly impacted the punctuality of bus operations, diminishing the appeal of customized bus services. This study addresses a new commuting customized bus network design problem. It takes into account uncertain road conditions, passenger separation, and the presence of heterogeneous vehicle models. We first formulate it into a multi-objective robust optimization model based on the minimum-maximum regret criterion. This model optimizes the selection of heterogeneous vehicle models, fleet routes, travel times, and passenger assignments with the aim of minimizing both passenger travel costs and bus system operating costs. Then, to effectively solve the model, we propose a multi-objective hybrid adaptive large neighborhood search algorithm. This algorithm incorporates problem-specific characteristics, introduces a passenger separation destruction operator based on these characteristics, and integrates a crossover operator to enhance the algorithm's optimization capability. Results of extensive numerical experimental results indicate that: i) The consideration of passenger separation and heterogeneous vehicles leads to improved vehicle resource utilization efficiency. Considering passenger separation results in an average time savings of 2.44% and a reduction of 11.46% in operating costs. Similarly, the inclusion of heterogeneous vehicle models yields an average time savings of 1.74% and a decrease in operating cost by 24.95%. ii) Compared with the traditional large neighborhood search algorithm and NSGA-II, our proposed algorithm consistently produces higher-quality Pareto solutions. iii) when compared to solutions obtained under deterministic road conditions, the solutions obtained in the presence of uncertainty in road conditions achieve an average reduction of 1.42% in passenger travel cost and a decrease of 18.24% in operating cost. This confirms the necessity of conducting robust commuting customized bus network design research under uncertain road conditions.

Automated guided vehicles (AGVs) are a key factor in determining the operational efficiency of automated container terminals. AGVs often face travel time uncertainties due to congestion, conflicts, weather, and other factors, resulting in quay and yard crane delays that reduce operational efficiency. In this paper, we introduce a distributionally robust method based on Wasserstein distance using historical travel data. We construct a data-driven model to manage the risk of waiting at quay cranes and yard cranes and to determine the task allocation scheme for AGVs with minimal operating costs. To solve the model, we first use conditional value-at-risk to approximate the distributionally robust chance constraints. Its closed-form solution is obtained by duality theory and analytic transformation, which are then transformed into a practical form. Secondly, exact branch-and-cut algorithms, along with heuristic algorithms and corresponding acceleration strategies, are designed for problems of varying sizes in automated container terminals. Experimental results demonstrate that the distributionally robust optimization method effectively captures the uncertainties in AGV travel times. Compared to the sample average approximation, the model and solution proposed in this paper can reduce the risk of waiting at quay cranes and yard cranes by 60%, significantly enhancing the robustness of the allocation scheme.

Shaping command system is an important measure to improve quality and efficiency of organizing test and training activities. The scientific design, reasonable construction and effective use of the command information system are the key to support the construction of the test and training command system. Based on the organization and command capacity needs of different types and different styles of test and training tasks, taking the combat command system of the US carrier strike group as the research object, centering on the construction problem of the marine test and training system, the description method based on unified architecture frame is adopted to design the architecture of the marine test and training command information system. Elaborate on system design content, ideas and technical approach from multiple perspectives such as capability classification, business activities, resource structure and service function. At the same time, combined with the tactical application characteristics of typical combat scenarios, based on the principle of digital and physical methods combination and equivalent function simulation, research the power grouping method of the marine test and training activities and mission support mode of the command information system. The relevant achievements can provide reference and inspiration for the research on the construction and application problem of military information systems in the field of test and training.

In this study, the impact of renewable energy technological innovation (RETI) on city-level energy transition and its mechanisms are investigated in 279 Chinese cities from 2005 to 2019. The results show that, on the whole, RETI has significantly contributed to city-level energy transition, but the real contribution was made after 2011, and the contribution to the energy transition was significantly stronger in cities located in the Southwest region than in other cities. In addition, RETI has a significant contribution to the energy transition in cities with a relative abundance of renewable energy and a relative scarcity of fossil energy, but the opposite is true for cities with a relative scarcity of renewable energy and a relative abundance of fossil energy. These findings hold after circumventing sample selection bias, endogeneity, and special sample interventions. Further studies found that reducing energy costs, increasing the economic penetration of renewable energy, and reducing pollution emissions are the key channels through which RETI drives city-level energy transition. This study is the first to reveal the mechanism of RETI on energy transition at the city level, which helps to promote the implementation of national and provincial energy development strategies to the city level, and provides strong support to promote city-level energy transition with high quality.