The Outline of the 15th Five-Year Plan for National Economic and Social Development of China has, for the first time, dedicated a separate chapter to “Advancing the Digital China Initiative and Enhancing the Level of Digital and Intelligent Development”. It emphasizes the advancement of the Artificial Intelligence (AI) Plus Initiative across the board to facilitate AI empowerment in all sectors on all fronts. At the same time, it also underscores the need to remain rooted in the broad and rich Chinese culture, follow the trends of information technology, and make tangible progress in building China into a country with a strong culture. Against this background, smart industrial heritage has become an important development direction for the digital and intelligent protection and utilization of China's industrial heritage, fostering an innovative paradigm in which AI empowers the field of industrial heritage. Its core lies in achieving automated and autonomous protection of industrial heritage through digital and intelligent technologies and fostering new forms of cultural business that deeply integrate culture and technology and offer interactive experiences. This paper reviews the three stages of the evolution of digital and intelligent protection and utilization of industrial heritage, analyzes the value implications of smart industrial heritage for realizing Chinese modernization, and explores the practical paths for promoting the development of smart industrial heritage in China from the perspective of Chinese modernization. This paper finds that smart industrial heritage has undergone a triple paradigm shift:from passive protection to active management, from single-site protection to landscape construction, and from physical object preservation to digital value development. This shift has not only helped cities tap their full potential and promoted green transition across the board, but also provided strong support for fostering new drivers of economic growth. On this basis, this paper proposes practical paths, including building a multi-stakeholder collaborative governance mechanism, creating a favorable innovation culture ecosystem, and providing financial support through multiple measures. This paper provides theoretical support and practical references for the development of smart industrial heritage in China and has important theoretical and practical significance for carrying forward the industrial spirit, accelerating efforts to build China into a country with a strong culture, and contributing to Chinese modernization.

The value generation and significance evolution of industrial culture run through the entire process of human industrialization, whose core lies in the concentrated reflection of the contradictory movement between productive forces and production relations from the perspective of historical materialism at the ideological and cultural level. Based on the classical expositions of Marx and Engels as the theoretical foundation, this paper clarifies that industrial culture is a comprehensive cultural form characterized by the three-dimensional synergy and unity of the material, spiritual, and institutional dimensions. It systematically analyzes the internal driving mechanisms of its evolution from the technological, social, and cultural logics, and comprehensively sorts out the complete evolutionary context of industrial culture in the three historical stages:initial industrialization, middle and late industrialization, and post-industrialization. Industrial culture has gradually transformed from mechanical worship and efficiency supremacy to technological ethics, sustainable development, and humanistic care. This paper also deeply interprets the deep-seated contradictions, such as the excessive expansion of instrumental rationality in industrial culture development. The evolution of industrial culture is essentially a dynamic process in which instrumental rationality and value rationality move from opposition toward dialectical unity. The value realization of industrial culture relies on the coordinated support of the productive forces base, institutional environment, and cultural consciousness. The development of industrial culture presents distinct developmental trends:from production-oriented dominance to diversified significance, from Western-centrism to pluralistic symbiosis, and from physical vehicles to virtual-real integration. To promote the innovative development of industrial culture of China in the New Era, it is essential to realize the value goal as the fundamental position of people's free and well-rounded development and actively promote the in-depth integration of industrial culture with digital technology, ecological civilization, and local civilization. This is not only the inevitable outcome of the historical evolution of industrial culture but also an essential path to solving the current practical dilemmas such as the unbalanced development and inheritance disruption of contemporary industrial culture, constructing a modern industrial culture system that integrates deep historical roots, contemporary features, and Chinese characteristics, injecting spiritual momentum into the development of new industrialization, and supporting the building of a country with a strong culture.

Shared manufacturing has attracted extensive attention for its role in improving production efficiency and optimizing resource allocation. However, most existing studies inadequately address energy consumption and carbon emissions during production processes. To promote the sustained development of shared manufacturing, this paper investigates resource scheduling and optimization problems from the perspective of energy conservation and emission reduction. A multi-objective production scheduling optimization model is developed with the respective goals of minimizing costs and production time, and minimizing energy consumption and carbon emissions. To solve the model, a hybrid optimization algorithm is proposed by integrating the non-dominated sorting genetic algorithm with particle swarm optimization. Using real-world data for empirical analysis, the results show that: (1) as production utility increases, carbon emissions and energy consumption rise, with an accelerating marginal growth rate; (2) comparative analysis based on different weight settings for production cost and maximum production time indicates that a higher weight assigned to production cost is associated with greater production utility, suggesting that platform operators should place greater emphasis on cost control; (3) comparisons between the proposed hybrid genetic algorithm incorporating particle swarm optimization and other algorithms demonstrate that the hybrid approach achieves faster convergence and yields higher-quality solutions, thereby validating the applicability of the model. The findings provide a basis for advancing energy conservation and emission reduction efforts and for promoting the sustained development of shared manufacturing.

Corporate sustainable innovation is a key driving force for high-quality development and green transformation. Under the guidance of the “dual carbon” goals, the external environment has placed higher requirements on enterprises' environmental, social, and governance (ESG) responsibility fulfillment, and ESG performance has gradually become an important criterion for measuring corporate sustainable development. Using A-share listed companies from 2010 to 2024 as research samples, this paper constructs a multiple regression model to systematically examine the impact of enterprises' ESG responsibility fulfillment on their sustainable innovation capability. By introducing continuous indicators of innovation input and output, this paper characterizes enterprises' sustainable innovation capability from both input and output dimensions. A series of robustness and endogeneity tests are conducted using the instrumental variable method, Heckman two-stage model, propensity score matching (PSM), and other methods. Furthermore, this paper explores the mediating effects of digital transformation and financial flexibility, introduces the degree of industry competition to investigate its moderating effect, and finally conducts heterogeneity analysis based on enterprises' pollution attributes and regional differences. The results show that enterprises' active ESG responsibility fulfillment can significantly improve their sustainable innovation capability, and this conclusion still holds after a series of robustness and endogeneity tests. After distinguishing different dimensions of ESG, it is found that environmental, social, and governance performance all enhance enterprises' sustainable innovation capability, among which social and governance dimensions have more significant promoting effects. Mechanism analysis indicates that ESG responsibility fulfillment can strengthen sustainable innovation capability by promoting corporate digital transformation and improving financial flexibility. The moderating effect test shows that the degree of industry competition positively moderates the relationship between ESG responsibility fulfillment and sustainable innovation. Heterogeneity analysis reveals that the promoting effect of ESG responsibility fulfillment on sustainable innovation capability is more significant in non-heavy polluting enterprises and enterprises located in the eastern and central regions. From the two dimensions of corporate digital transformation and financial flexibility, this paper reveals the internal mechanism of how enterprises' ESG responsibility fulfillment affects their sustainable innovation capability, and points out the heterogeneous effects across industries and regions. It aims to provide theoretical references and managerial implications for enterprises to fulfill ESG responsibilities, enhance their sustainable innovation capability, and promote their high-quality development.

Industrial intelligence stands as a core lever for advancing the green transformation of China's industrial sector and elevating regional carbon productivity. To deeply dissect its impacts on carbon productivity and the underlying mechanisms, this paper constructs a three-dimensional analytical framework integrating industry, energy, and technology, drawing on panel data from 30 provincial-level regions in Chinese mainland from 2010 to 2022 (excluding Xizang). Employing a fixed-effects model, a mediation effect model, a spatial Durbin model, and a random forest model, this paper systematically analyzes the influence mechanisms, transmission pathways, spatial evolution patterns, and nonlinear characteristics of industrial intelligence on carbon productivity. The findings reveal that industrial intelligence significantly enhances regional carbon productivity and exhibits stage-specific nonlinear evolutionary characteristics; industrial structure upgrading, energy efficiency improvement, and green technological innovation are key mediating channels through which industrial intelligence empowers carbon productivity growth; the empowering effect of industrial intelligence on carbon productivity is more pronounced in underdeveloped regions; spatially, an asymmetric pattern of “local efficiency gains and neighboring region suppression” emerges, primarily driven by factor siphoning in developed regions, homogeneous industrial competition, and inter-provincial gaps in environmental regulation, resulting in significant negative competitive spillovers across provincial-level regions. Based on these results, differentiated policy recommendations are put forward, aiming to provide empirical evidence and decision-making references for narrowing regional gaps in green development and constructing a coordinated emission reduction pattern in China.

Humanistic economics profoundly reveals the inherent correlations and development laws between culture and economic growth, and offers important theoretical guidance for the integration of culture and tourism in such aspects as value stance, methodologies, and practical approaches. Building on existing studies, this paper further proposes integration and regeneration as the core concepts for analyzing the deep integration of culture and tourism. The former refers to the value penetration and systematic integration of cultural elements into economic activities, while the latter manifests as value reshaping and industrial leapfrogging achieved through business form innovation. At different stages of culture-tourism integration practices, regions guided by humanistic economic ideas break down industrial barriers among culture, sports, tourism, agriculture, and commerce via resource consolidation and factor restructuring. They fully leverage the mutual empowerment of culture and the economy, and have formed three practical models: industrial ecosystem restructuring, event and festival-driven development, and digital technology empowerment. Each model boasts distinct strengths and together forms a mutually complementary organic whole. Going forward, efforts should be further intensified to improve development pathways from multiple dimensions, including exploration of humanistic values, application of digital and intelligent technologies, creation of spatial scenarios, and establishment of collaborative governance mechanisms.

The integrated development of education, science and technology, and talents is an important foundation for promoting high-quality development. New Quality Productive Forces, driven by scientific and technological innovation, are the key to achieving high-quality development. Based on the perspective of collaborative incentives, this paper takes Liaoning Province as the research object to explore the integrated development level of education, science and technology, and talents, and its promoting effect on New Quality Productive Forces. By using the panel data from Liaoning Province from 2013 to 2023, this paper constructs an evaluation indicator system for the integrated development of education, science and technology, and talents. It employs the coupling coordination degree model to calculate the integrated development level, uses the system dynamics model to simulate the improvement paths and dynamic effects of the integrated development level under multi-dimensional collaborative incentives, and analyzes the collaborative mechanism between explicit and implicit incentives. The results show that there is a significant coupling and coordinated relationship between the systems of education, science and technology, and talents and regional New Quality Productive Forces. Collaborative incentives can produce an emergent effect of “1+1+1>3”. The activation effect of the coordination of explicit and implicit incentives can effectively cultivate new quality workers and enhance regional innovation capabilities, which is the core driving force for promoting the integrated development of education, science and technology, and talents. Although Liaoning Province has the advantages of high-quality higher education resources and a solid industrial foundation, it still needs to optimize the talent introduction and cultivation mechanisms, deepen the integration of industry, university, and research, and integrate multi-dimensional incentive policies to enhance the overall system efficiency and promote the continuous emergence of New Quality Productive Forces. This paper aims to provide theoretical references and policy implications for Liaoning Province and similar regions to promote the deep integration of education, science and technology, and talents, and optimize collaborative incentive policies.

The historic convergence of generative artificial intelligence (AI) technology and the continuous optimization of the business environment is driving the gradual realization of human-machine collaboration in government services. In this process, scenario governance has become a key factor determining whether technology can translate into service quality. Drawing on technology empowerment theory and scenario theory, this paper employs a multi-case analysis method to conduct an in-depth examination of the governance outcomes and bottlenecks in four types of scenarios during the process of optimizing the business environment: approval services, market supervision, policy support, and legal guarantees. This paper finds that generative AI technology has a significant empowering effect in government scenario governance, such as optimizing the business environment, and can effectively improve the efficiency of government governance. However, during the practical deployment of the technology, there remain numerous shortcomings, specifically manifested as insufficient adaptability to complex matters, prominent pressure on data security and privacy protection, misalignment between technology iteration and policy development, heightened risks of algorithmic bias, evident technology dependence, weak capacity to resolve complex disputes, and so on. In response to these bottlenecks, this paper proposes measures such as constructing a hierarchical and categorical precision empowerment system, improving collaborative iteration mechanisms, and strengthening risk prevention and control and ethical governance, thereby providing practical references for generative AI to empower the high-quality development of the business environment.

To address the diverse purchasing and returning needs of customers for different shared warehouses, unreasonable distribution of shared warehouse locations, and high total logistics costs, the issues of location selection of shared warehouses are studied with multiple suppliers and integrated forward and reverse logistics. A shared warehouse location model is built that integrates forward and reverse logistics, with the goal of minimizing the total logistics cost including shared warehouse location cost, third-party transportation cost, order cost, inventory cost, and return cost. An improved genetic algorithm is designed based on the characteristics of the model, and the monarchy scheme is used instead of traditional selection and crossover operations to enhance overall search capability. Numerical examples for simulation experiments are introduced to analyze the impact of different parameters on the average running time, average cost, and minimum solution of the experiment, and the optimal location and minimum logistics cost of the shared warehouse are obtained. The experimental results have demonstrated the effectiveness of the model and the operational efficiency of the algorithm, reducing logistics costs and improving logistics efficiency.

In the era of digital intelligence, the protection of laborers' personal information is facing severe challenges. The current Personal Information Protection Law has difficulties in application in the workplace context. This paper analyzes the specific obstacles faced by the application of these rules in the labor field and explores the path to institutional improvement. This paper finds that due to the unequal status of employers and laborers, consent is easy to become a mere formality in the workplace context, and the clause of “being necessary for human resources management” is transformed into almost unlimited general authorization due to the lack of an objective definition. Facing the above problems, it is necessary to reconstruct the existing rules through legal interpretation or supplementary provisions in labor law based on the principle of preferential protection of labor law and the legal principle of personal information protection. First, it is essential to adjust the application order of the legitimacy basis, position consent as an exception, and establish a tiered notification mechanism. Second, the clause of “being necessary for human resources management” should be narrowly interpreted, with the introduction of dual procedural and substantive review standards. Finally, the burden of proof should be reallocated, and a judicial relief mechanism without adverse consequences should be established. The institutional design of the current personal information processing rules is reasonable, but there is a gap between the application effect in the workplace context and the legislative expectation. Under the premise of adhering to the existing legal framework, it is necessary to return to the core legal principle of the preferential protection of labor law and make targeted adjustments and improvements, so as to achieve a dynamic balance between the protection of laborers' rights and interests and the legitimate management needs of employers. The main innovation of this paper lies in the deep analysis of the structural barriers to the application of general personal information protection rules in the labor field from the perspective of preferential protection of labor law, and the proposal of systematic rule reconstruction, which provides references for correcting the imbalance of rights between employers and laborers and preventing the abuse of algorithms and management rights in the era of digital intelligence.

With the rapid development of big data technologies, investigative models are undergoing a profound transformation. Owing to its powerful data-processing capacity and advantages in digital analysis, big data investigation has become an important component of modern criminal governance system, serving as a crucial tool for combating intelligent and complex criminal activities. However, while this technology-driven investigative model enhances investigative efficiency, it also significantly expands the boundaries of public power, posing potential threats to personal information security. Drawing on literature analysis, comparative research, normative analysis, and other methods, this paper identifies critical challenges in the field of big data investigation in China, including an incomplete and fragmented legal framework for personal information protection, insufficient constraints on investigative authorities in the process of collecting and processing information, and inadequate remedies for individuals whose rights have been infringed. In the process of empowering judicial practice with digital technologies, a balance between power constraints and rights protection must be achieved. In big data investigation, efforts should focus on establishing a high-level, systematic legal framework for big data investigation through multi-department collaboration, developing a tiered system for the approval, processing, and oversight of personal information data, improving the administrative public interest litigation system for personal information protection, expanding avenues for citizen rights relief, etc. The innovation of this paper lies in introducing, on the basis of existing theories, new measures such as the classification and tiered system of personal data and administrative public interest litigation. These measures not only preserve the effectiveness of big data investigation, but also place stronger constraints on the exercise of public power, so as to promote the coordinated development of technological empowerment and rights protection, fully leverage the positive role of big data in crime prevention and control, and effectively curb the risk of public power abuse, ultimately achieving an organic integration of digital justice and investigative efficiency and promoting the standardized big data investigation within the framework of the rule of law.

As a “global model of institutional civilization”, intellectual property serves to underpin the missions of economic transformation, the function of innovation-driven development, and the requirement for fair competition in fostering New Quality Productive Forces in the private economy through its impacts on economic contribution, innovation guidance, market regulation, and so on. Currently, the intellectual property legal safeguards for developing New Quality Productive Forces in the private economy still face challenges and difficulties, including insufficient alignment of intellectual property frameworks with the new development philosophy, inadequate support from the intellectual property system for comprehensive innovation, and a lack of integrated development in the legal governance of intellectual property. Therefore, the intellectual property legal safeguards for advancing the development of New Quality Productive Forces in the private economy should emphasize the overarching guidance provided by the New Development Philosophy in intellectual property efforts more than ever, modernize the intellectual property system that ensures both development and security, and promote the integrated improvement of the three mechanisms of intellectual property:incentives, commercialization, and protection. These measures aim to achieve optimal synergy between the high-quality development of New Quality Productive Forces in the private economy and the high-quality advancement of intellectual property legal safeguards under multiple constraints.

With the advancement of the digital and intelligent transformation of the manufacturing industry and the implementation of the strategy to boost China′s strength in manufacturing, digital and intelligent transformation has become the key for the steel industry to enhance its competitiveness and achieve high-quality development during the 15th Five-Year Plan period. During the 14th Five-Year Plan period, China′s steel industry actively carried out innovation activities in digital and intelligent transformation and achieved positive results, such as a significant overall improvement in the digital and intelligent level of the industry, the notable effectiveness of the construction of intelligent steel factories, the deep integration of “artificial intelligence+” to enhance quality and efficiency, and leading enterprises driving the digital and intelligent transformation of the entire industrial chain. Currently, the digital and intelligent transformation of the steel industry faces problems and difficulties, including the need to further solidify the foundation of intelligent manufacturing, severe data silos, insufficient coordination in the digital and intelligent transformation of the industrial chain, and the shortage of talents with digital and intelligent expertise, etc. During the 15th Five-Year Plan period, under the combined effects of national strategic demands, the accelerated development of New Quality Productive Forces, increasing policy support for digital and intelligent transformation, the coupled development of digital and green technologies, and the excellent practical experience, China′s steel industry will build up substantial momentum for digital and intelligent transformation. Based on this analysis, countermeasures and suggestions are proposed, including consolidating the foundation of intelligent manufacturing, focusing on breaking down data barriers, advancing the digital and intelligent transformation of the entire industrial chain, and promoting the integrated development of digital and intelligent education, science and technology, and talents, so as to promote the digital and intelligent transformation of the steel industry during the 15th Five-Year Plan period.

During the 15th Five-Year Plan period (2026—2030), the digital and intelligent transformation of China′s automotive industry has entered a critical phase:moving from isolated applications to the restructuring of the entire industrial chain, underpinned by the scale advantages, supply chain completeness, and established electrification foundation of the industry. Based on policy text analysis and international comparative research, this paper systematically examines the achievements, challenges, and institutional supply conditions of the digital and intelligent transformation of China′s automotive industry. The challenges hindering the digital and intelligent transformation of China′s automotive industry are fourfold. First, insufficient provision of public goods, such as standards and interfaces, constrains cross-entity collaboration efficiency. Second, imperfect data property rights and revenue distribution mechanisms limit the market-oriented allocation of data as a factor of production. Third, weak transformation capabilities of small and medium-sized parts suppliers cause a synergy bottleneck in the supply chain. Fourth, spillover effects of international rules shift market access from constraints through border-based measures to process-based governance, significantly increasing fixed compliance costs. Taking the collaborative models of the European Union′s Catena-X, Germany′s International Data Spaces, and Japan′s automotive software platform as examples, this paper mainly analyzes their institutional mechanisms in areas such as the supply of standards as public goods, data sovereignty protection, chain leader leadership, and organizational embeddedness, as well as the implications for the digital and intelligent transformation of China′s automotive industry. Accordingly, this paper proposes that during the 15th Five-Year Plan period, policy instruments for the digital and intelligent transformation of China′s automotive industry should shift from project-based subsidies to institutional supply. Specifically, national unified standards and the provision of public infrastructure should be leveraged to reduce institutional frictions in cross-entity collaboration; systems for rights confirmation, authorization, revenue distribution, trusted circulation, and compliance auditing should be established to improve the allocation efficiency of data factors; chain leader leadership should be harnessed to drive the synchronous digital and intelligent transformation of small and medium-sized enterprises; and institutionalized capacity building for overseas expansion should be strengthened.

The 15th Five-Year Plan period is a crucial stage for laying a solid foundation and making all-round efforts for China to basically achieve socialist modernization. The petrochemical industry is an important pillar of the national economy, and its digital, intelligent, and green transformation directly determines the quality of progress in new industrialization and the modernization of the industrial system. At present, amid profound shifts in the global industrial competition landscape and intensifying resource and environmental constraints, the petrochemical industry is confronted with severe challenges, including prominent structural contradictions, stringent safety production requirements, and rising security risks in industrial and supply chains. Against this macro backdrop, an in-depth exploration of the inherent logic, practical dilemmas, and evolutionary paths of the digital and intelligent transformation in the petrochemical industry carries important academic value and practical significance for formulating medium and long-term development plans for the sector. Theoretical analysis shows that the digital and intelligent transformation can systematically reshape conventional petrochemical production models through mechanisms such as value chain upgrading, green and safe governance, and multi-dimensional innovation-driven development. Leveraging big data, artificial intelligence, and industrial Internet of Things technologies, the petrochemical industry can achieve precise allocation of resource factors, improve production efficiency while effectively alleviating resource and environmental pressures, and establish a digital security defense system that integrates early warning and response. Since the 14th Five-Year Plan period, the petrochemical industry has achieved remarkable progress in the breadth, depth, and effectiveness of the digital and intelligent transformation. Nevertheless, deep-seated problems remain, such as bottlenecks in core technologies in key fields, shortages of cross-industry talents, inadequate adaptation of digital and intelligent technologies to industry-specific demands, and insufficient internal impetus for enterprise transformation. To meet the more urgent transformation and upgrading tasks during the 15th Five-Year Plan period, targeted and effective policy support should be further strengthened. Joint research on core technologies in key fields should be intensified to break through underlying technical bottlenecks constraining industrial development. The cultivation of cross-industry talents integrating petrochemical expertise and digital intelligence capabilities should be accelerated to build a talent development system suited to digital transformation. The integrated application of “operational technology (OT)+information technology (IT)” and “data+mechanism” should be deepened to enable digital technologies to penetrate the basic processes of petrochemical production. Internal impetus for enterprises′ digital and intelligent transformation should be stimulated to achieve a shift from “passive transformation” to “active reform”.

The digital and intelligent transformation is not only an inevitable choice for building a strong shipbuilding industry in China, but also a systematic project that fundamentally reshapes the ship manufacturing system through deep integration of intelligent technologies such as artificial intelligence, with data serving as a crucial driver. This paper conducts an analysis of the practical foundation, challenges, advancement pathways, and strategic choices for the digital and intelligent transformation of China′s shipbuilding industry during the 15th Five-Year Plan period, based on a literature review, policy analysis, typical case studies, and field research. Currently, China′s shipbuilding industry has successfully established a systematic model for advancing digital and intelligent transformation, characterized by data as the foundation, intelligent technologies as the core, independently developed products as the hallmark, and open ecosystems as the backbone. However, it still faces challenges, including insufficient self-reliance in core technologies, barriers to data factor circulation, digitalization gaps in the industrial chain, and lagging support for standards and talents. The digital and intelligent transformation of China′s shipbuilding industry possesses such advantages as a comprehensive industrial system, a solid policy framework, and the driving role of leading enterprises, while also embracing major historical opportunities, including explosive demand for green and intelligent new ship types, the maturity of enabling digital technology clusters, and strategic impetus from national policies fostering New Quality Productive Forces. During the 15th Five-Year Plan period, coordinated measures should focus on achieving self-reliance in core software and hardware and data standardization, promoting the transformation of business models toward full life-cycle services and networked collaboration, building an industrial new ecosystem characterized by the integration of large, medium, and small enterprises and cross-sector integration, and simultaneously improving the systematic support of standards, regulations, and interdisciplinary talent cultivation. This paper can provide a theoretical basis and decision-making references for relevant departments to formulate the 15th Five-Year Plan for the high-quality development of the shipbuilding industry, serve as action guidelines for the digital and intelligent transformation of shipbuilding enterprises, and offer reference models for the digital and intelligent transformation of other equipment manufacturing industries.

The low-altitude economy epitomizes New Quality Productive Forces and serves as a key component of strategic emerging industries, increasingly functioning as a new engine of economic growth. Its safe and sound development relies heavily on the construction of low-altitude infrastructure. In recent years, boosted by policy guidance and market demand, China has made tangible progress in developing low-altitude infrastructure, characterized by the coordinated advancement of physical and digital infrastructure. Through pilot and demonstration programs, some regions have pioneered initial models of commercial operation and multi-scenario application. This paper systematically reviews the current situation of low-altitude infrastructure development, conducts an in-depth analysis of its core challenges, and innovatively proposes a three-dimensional collaborative classification framework based on function, hierarchy, and object, deepening the understanding of the institutional architecture of low-altitude infrastructure and more comprehensively clarifying its core connotations and operational logic. This paper reveals that, despite initial achievements, China′s low-altitude infrastructure construction remains constrained by multiple factors, including inadequate top-level design, inconsistent standard systems, insufficient regional coordination, ambiguous division of roles between the government and the market, and the incompatibility between conventional airspace management and low-altitude economy development. Based on an in-depth analysis of the problems, this paper proposes a series of countermeasures: improving laws, regulations, and strategic planning; establishing an integrated standard system; adopting differentiated regional development strategies; optimizing government-market coordination mechanisms; and reforming and innovating airspace management. These efforts aim to provide theoretical support for strengthening the “aerial foundation” of the low-altitude economy, unlocking its trillion-yuan market potential, and promoting its large-scale development nationwide. This paper recommends that future priorities be directed toward advancing intelligent upgrades, fostering multi-scenario integration, and optimizing dynamic operations, while leveraging international experience to chart a path for the high-quality development of China′s low-altitude economy.

The low-altitude economy epitomizes New Quality Productive Forces and constitutes a prioritized strategic emerging industry in China, demonstrating immense growth potential in advancing high-quality economic development. However, a significant structural tension exists between its productive attribute of cross-regional mobility and the traditional boundaries of territorial administrative jurisdiction. From the macro perspective of building a unified national market, this paper establishes an analytical framework interconnecting administrative logic, transaction costs, and market fragmentation, and deeply analyzes current developmental challenges facing the low-altitude economy, including the fragmentation of airspace regulations, the disparities in regulatory systems and deficiencies in the rule of law, the technological isolation and insufficient provision of infrastructure, and the implicit barriers to factor mobility. This paper finds that local protectionism, rooted in the logic of territorial resource allocation, significantly inflates institutional transaction costs for market entities and obstructs the network externalities and economies of scale effects within the industry. This model not only results in severe efficiency losses, but also triggers asset impairment pressure and industrial involution due to inconsistent standards. Furthermore, the large-scale development of the low-altitude economy relies heavily on unified rules and the free flow of factors, whereas the ambiguous definition of property rights and the divergence in regulatory systems within the current management regime have become core obstacles restricting its high-quality development. The fundamental solution to this dilemma lies in promoting a transition of the governance paradigm from territorial fragmentation to collaborative governance. This paper proposes a collaborative governance framework encompassing vertical restructuring of powers and responsibilities, horizontal integrated regional development, and multifaceted market-based checks and balances. By correcting institutional distortions and restoring market mechanisms, it provides theoretical support and implementation pathways for breaking market fragmentation and building a unified national market for the low-altitude economy characterized by unified rules and orderly competition.

The Fourth Plenary Session of the 20th Central Committee of the Communist Party of China has coordinated the deployment of industrial clusters in the low-altitude economy as a strategic emerging field and the construction of a nationally integrated computing power network, establishing the strategic positioning of the low-altitude economy as a typical representative of New Quality Productive Forces. However, its industrial practice remains constrained by structural limitations such as physical space congestion, rigid operational marginal costs, and lagging safety governance. This paper regards computing infrastructure as a key driver determining industrial production boundaries and resource allocation efficiency, systematically examining its empowerment mechanisms and implementation pathways. Computing infrastructure fundamentally transforms the growth logic of the low-altitude economy through digital capital deepening and institutional reshaping effects. It drives a leap in research and development paradigms from physical trial-and-error to virtual iteration, promotes the transformation of resource allocation from static directives to dynamic game equilibrium, and reshapes agile governance models based on algorithmic contracts. In response to existing practical constraints, including supply-demand mismatches in spatial layout, efficiency bottlenecks of the storage-computation separation architecture, and asymmetric dependency within the industrial chain, this paper further proposes pathways such as constructing a gradient spatial layout for computing power, advancing the development of integrated communication-sensing-computing networks, and improving mechanisms for data assetization and patient capital incentives. These proposals aim to provide theoretical support and policy references for the high-quality development of the low-altitude economy.

The cultivation of elite engineers is currently a focal point of postgraduate education reform. Synergy theory, serving as an important theoretical support for promoting the efficient linkage of system elements, provides key insights into addressing the practical challenges in cultivating outstanding engineers in local universities. This paper, based on the core tenets and logical pathways of synergy theory, analyzes the practical dilemmas in the cultivation of engineering postgraduates at local universities. Taking Shenyang University of Technology as an example, it focuses on discussing how the university, guided by synergy theory, centers on five dimensions of enrollment model, cultivation program, cultivation mode, supervisor team, and classified evaluation, through goal synergy, resource synergy, process synergy, project synergy, and evaluation synergy, to forms a deeply integrated, whole-process cultivation system characterized by joint participation, joint management, sharing, and joint research between the university and enterprises, which solidly advancing the reform of elite engineers cultivation and achieving significant breakthroughs in educational practices. The systematic solution proposed in this paper can offer references for local universities to improve the categorized system of postgraduate education and optimize the cultivation path of elite engineers based on synergy theory.

In the New Era of artificial intelligence (AI) technology empowering education, this paper focuses on the mechanism innovation of enhancing the effectiveness of postgraduate training through AI technology from the perspective of the integration of industry, academia, and research. In response to the three structural contradictions of current technological detachment, data silos, and lagging evaluation, based on the four-dimensional theoretical framework of technology empowerment, management coordination, human-machine collaboration, and ecological evolution, a progressive closed-loop model of “tool breakthrough→resource coordination→evaluation innovation→system reconstruction” is constructed. Through a mixed research method, an empirical analysis is conducted on postgraduate training through the integration of industry, academia, and research at four typical enterprises, and shows that the inherent law of industry-academia-research collaboration is driven by the tripartite synergy of technological integration as the foundation, resource coordination as the wings, and institutional alignment as the axis, together propelling a leap in the effectiveness of capability transformation. The results indicate that the four-dimensional model systematically resolves the problems of delayed training responsiveness and inefficient innovation transformation through a tripartite mechanism of “technology embedding-resource connectivity-institutional guarantee”, providing a replicable new paradigm for postgraduate education in the AI era.

The miniaturization of smart factories is an important path for small and medium-sized enterprises to achieve intelligent manufacturing. Using a literature review method, this paper systematically retrieves related literature on micro smart factories from databases such as CNKI, Web of Science, and Scopus. Combining studies on micro factories and smart factories, this paper defines a micro smart factory and analyzes the constituent elements of a micro smart factory from three aspects: conceptual subjects, technical foundations, and development goals. It is believed that micro smart factories have characteristics of subject specificity, technical similarity, subject applicability, and functional fundamentality compared to traditional smart factories. This paper also clarifies conceptual differences among micro factories, smart factories, intelligent manufacturing, and micro smart factories. Additionally, based on application scenarios of micro smart factories, it constructs a research framework following the logic of “influencing factors-development barriers-implementation paths-goals and outcomes”. This paper finds that influencing factors of micro smart factories involve three aspects: technological, organizational, and environmental levels. Development barriers include financial, technological, talent, and management obstacles. Building micro smart factories requires solving issues in five areas: finance, technology, talent, cognition, and management support. The goals and outcomes of micro smart factories differ at both micro and macro levels. Finally, this paper proposes future development directions for micro smart factories from four dimensions: construction and practice, theoretical framework, benefits and governance, and growth changes and boundary effects, providing references for theoretical research on micro smart factories and the future development of intelligent manufacturing in China.

With the rapid development of the market economy, mergers and acquisitions (M&As) and restructuring have become the main commercial activities in the securities market. To explore the impact and mechanism of M&A and restructuring inquiry letters on corporate ESG performance, based on the theoretical analysis, all A-share listed companies that underwent M&As and restructuring from 2015 to 2021 are selected as the research objects, and regression tests are conducted under strict control of time and individual fixed effects, further expansion analysis is conducted on the economic consequences and characteristics related to M&A and restructuring inquiry letters, and the heterogeneity of the impact of M&A and restructuring inquiry letters on corporate ESG performance under different levels of financing pressure is explored. Research has found that M&A and restructuring inquiry letters can significantly improve the ESG performance of the surveyed companies through a dual path of increasing analyst attention and alleviating information asymmetry issues. Further analysis reveals that the impact of receiving letters on a company's ESG rating is short-term, with an improvement in the quality of ESG information disclosure after receiving letters, and the mechanism of action is similar to that of ESG performance. At the same time, changes in the effectiveness of M&A and restructuring inquiry letters are revealed, and it is found that their impact on ESG performance significantly decreases after 2019. Heterogeneity analysis shows that this promoting effect is more significant in non-state-owned enterprises and enterprises with higher levels of financing constraints. This paper verifies the optimization effect of M&A and restructuring inquiry letters on corporate ESG performance, there is heterogeneity in the regulatory effects on companies under different financing pressures, indicating that the ability of companies to withstand potential risks in their financing activities weakens the promotion effect of M&A and restructuring inquiry letters on ESG performance.

Urban transportation is one of the key sectors contributing to urban carbon emissions. Investigating efficient carbon reduction paths is of significant importance for promoting the high-quality development and green, low-carbon transformation of the transportation sector. Beijing, a city with a dense population and frequent economic activities, has considerable energy consumption and carbon emissions in its transportation sector. The Chinese government has pledged to peak carbon emissions by 2030 and achieve carbon neutrality by 2060. Therefore, studying the relationship between transportation carbon emissions and economic growth in Beijing, as well as exploring effective carbon reduction measures, is crucial for achieving these goals. This paper takes Beijing as a case study and employs a “top-down” approach to calculate the annual carbon dioxide emissions from its transportation sector. It analyzes the decoupling status between transportation carbon emissions and economic growth and constructs a system dynamics model for urban transportation carbon emissions. The model considers multiple subsystems, including the population and economy subsystem, the transportation subsystem, the energy and carbon emissions subsystem, and the private car cost subsystem. By simulating and forecasting the trends in carbon dioxide emissions from urban transportation in Beijing, the study investigates the changes in emissions under various carbon reduction strategies. The study calculates and analyzes the carbon emissions from Beijing's transportation sector, revealing an increasing trend in recent years. It also shows that the decoupling status between transportation carbon emissions and economic growth is characterized by either an expanding or weak decoupling, failing to achieve the ideal state of strong decoupling. Based on this, the study develops a system dynamics model for urban transportation carbon emissions and simulates the emission trend variations under different scenarios. The results indicate that adjusting the vehicle energy structure, controlling private transportation demand, and improving energy efficiency are effective measures for reducing transportation carbon emissions. Promoting new energy vehicles, implementing stringent traffic restriction policies, and enhancing energy-saving technologies can significantly reduce transportation carbon emissions. This paper not only examines the ecological benefits of implementing carbon reduction measures from a policy perspective but also assesses their economic benefits, thereby enriching the evaluation framework of transportation carbon reduction policies. Furthermore, the study considers the cost changes for consumers resulting from policy implementation, comprehensively evaluating the implementation effects and guiding role of the policy from both the ecological and economic benefits. The findings offer valuable guidance for government departments in selecting efficient and rational carbon reduction policies, which will help promote high-quality economic development and high-level protection of the ecological environment. Additionally, the research provides insights for low-carbon transportation development in other regions and holds significant theoretical and practical values for achieving the green and low-carbon transformation of the transportation sector.

As crucial market entities in the socialist market economy, state-owned enterprises have always been the core force driving China′s high-quality economic development. In the new era, amid profound shifts in the international political landscape and strategic requirements of the domestic goal of common prosperity, redefining the functional positioning of state-owned enterprises not only shapes their reform trajectory but also serves as a crucial proposition for understanding the institutional strengths of the socialist market economy with Chinese characteristics. Based on the extended analytical framework of “Attributes-Strategic Missions-Functions” for state-owned enterprises based on five types of market failures, this paper systematically explains the strategic mission and functional positioning of state-owned enterprises in the new era. From the perspective of making up for market failures, the traditional market failure theory mainly focuses on three types of issues: first, issues universal in market economies such as monopolies, externalities, and public goods shortages; second, the trap of comparative advantage in developing economies formed due to path dependence; third, imperfect market institutions and administrative barriers peculiar to transitional economies. With the development of the times, the scope of market failure has been further extended to two new types of challenges: fourth, disruptions to the international division of labor under the influence of international politics in the trend of anti-globalization, and fifth, market mechanisms′ inadequacy in achieving common prosperity. This paper argues that the strategic mission and functional positioning of state-owned enterprises are rooted in the coordinated practice of their triple attributes: the economic attribute, with efficiency improvement and strategic breakthrough as the core, can make up for the traditional three types of market failures and drive high-quality economic development; the political attribute, which carries the mission of ensuring national security and enhancing global competitiveness, can make up for the fourth type of market failure and cope with the challenges of anti-globalization; the social attribute, which aims to promote fairness and sharing, can make up for the fifth type of market failures and strive to achieve common prosperity. State-owned enterprises are not only key actors in addressing market failures but also the pioneers of national strategies. The coordinated practice of their three attributes is not only a unique advantage of China′s economic system but also a vivid illustration of “an efficient market+an effective government” in the changing situation of global governance. The Inclusive Green Development Survey finds that the realization of the functions of state-owned enterprises in addressing the five types of market failures has been highly recognized by society.

Developing New Quality Productive Forces is an inherent requirement and an important focus for promoting high-quality development in China. It is an important decision and deployment made by the Central Committee of the Communist Party of China to pursue a strategy of national rejuvenation amid global changes of a magnitude not seen in a century. This paper summarizes the importance of New Quality Productive Forces to the strategy of boosting China's strength in manufacturing, the ways in which New Quality Productive Forces drive new industrialization, the path to achieving new industrialization and high-quality industrial development, and the future direction of high-quality industrial development in China. In order to achieve high-quality industrial development in China, China need to build a new industrialization system through developing New Quality Productive Forces under the guidance of Manufacturing Powerhouse Strategy, and integrate the core requirements of high-quality industrial development throughout the construction process. Firstly, through developing New Quality Productive Forces, industrial transformation should be continuously promoted, and the structure of the manufacturing industry should be optimized; technological innovation should be driven, and the core competitiveness of the manufacturing industry should be enhanced; the green economy should be promoted, and the quality of development should be improved, thereby empowering Manufacturing Powerhouse Strategy. On this basis, through developing New Quality Productive Forces, the resilience of the industrial chain should be enhanced, breakthroughs should be made in some core technologies in key fields to ensure sustained industrial development, industrial clusters and leading enterprises should be cultivated, and the international competitiveness of “Made in China” should be enhanced, so as to promote the construction of China's new industrialization system. At the same time, New Quality Productive Forces can also integrate the requirements of high-quality industrial development into the construction of new industrialization by leading quality, efficiency, and driving force transformation. Among them, quality transformation mainly includes scientific and technological innovation and development mode transformation led by New Quality Productive Forces, efficiency transformation mainly includes industrial transformation and upgrading led by New Quality Productive Forces, and driving force transformation mainly includes system and mechanism innovation and talent training innovation led by New Quality Productive Forces. In the future, driven by the three major transformation paths, China's industrial system will continue to progress towards high-end, digital, service-oriented, green, inclusive, and international directions. This paper analyzes the internal logic and practical laws of promoting high-quality industrial development in China through New Quality Productive Forces, and provide references for China to further perfect relevant policies in the future.

Since entering a new stage of development, a new round of scientific and technological revolution and industrial transformation represented by artificial intelligence, big data, blockchain, and cloud computing has driven the rapid development of China's digital economy. The digital economy consists of digital industrialization and industrial digitalization. The digitalization of industries constitutes a crucial part of industrial digitalization, and it applies digital technologies to industrial production, management, and services, playing an important role in optimizing resource allocation and improving resource utilization. It involves intelligent manufacturing, digital design, data collection and analysis, supply chain digitalization, cloud and edge computing, virtual reality and augmented reality, cybersecurity, and digital twins. This paper systematically examines the current status and challenges of the digital development of industries, laying the foundation for further leveraging the driving role of the digital economy to promote high-end, intelligent, and green industrial development and to build a modern industrial system. China actively guides, encourages, supports, and ensures the digital development of industries such as intelligent manufacturing and the industrial internet through incentive measures like special projects, industry standards, and demonstration pilots. This paper utilizes the CSMAR (China Stock Market & Accounting Research Database) to analyze the digital development of industries in China. The study finds that the level of intelligent manufacturing has significantly improved, the industrial internet is flourishing, the innovative development of “5G+industrial internet” is accelerating, and the initiative of “providing inclusive cloud services to empower big data application and intellectualized reconstruction” is being promoted. Since the 18th National Congress of the Communist Party of China, the digital transformation of Chinese industrial enterprises has shown an accelerating trend, particularly in the eastern regions and the manufacturing sector. Although the digital transformation in the central and western regions and some traditional industries started later, recent years have seen strong growth momentum, indicating potential for catching up. Despite the significant achievements in the digital transformation of industrial enterprises in China, challenges remain, including the imperative need for breakthroughs in key technology areas, the necessity to enhance the digitalization level of industries, regional development imbalances, and a shortage of high-end talent. Thus, to promote high-quality development of the real economy and facilitate the digital and intelligent development of industries, it is essential not only to accelerate the digital and intelligent transformation of traditional industries but also to innovate and develop core industries of the digital economy, cultivate emerging and future industries, optimize the development environment for industrial digital intelligence, strengthen digital security guarantees, and vigorously cultivate specialized digital talents.

Industrial green development represents a concrete practice prominent embodiment of the concept of green development in the industrial field, is an inevitable choice to address the ecological and environmental challenges posed by the rapid industrialization of large countries. From the theoretical perspective, the green transformation of industrial enterprises is mainly affected by the market mechanism, government regulation and opening up. The market mainly exerts an impact on the green transformation of enterprises through signal mechanisms such as the price or environmental preferences of market players. Government regulation, on the one hand, will increase the cost of enterprises complying with environmental protection regulations, and on the other hand, it may also promote technological innovation of enterprises to realize green transformation while improving their own competitiveness. Opening up to the outside world may enable enterprises to transfer the burden of environmental protection or improve the availability of green and low-carbon technologies, and then have a dual impact on their green transformation. From the practical level, since the 1970s, China's industrial green transformation has generally gone through four stages:end-of-pipe treatment of industrial pollution, equal emphasis on industrial pollution prevention and control, the launch of new industrialization and high-quality industrial development, and has made outstanding achievements. At the present stage, the country still faces challenges in eliminating the structural obstacles of industrial green development in the short term, the increasing pressure of energy conservation and carbon reduction in the industrial sector, and the overall weak capacity of green manufacturing and services. On the new journey of the new era, accelerating industrial green development requires promoting stock reform through incremental development, further leveraging the positive role of the carbon market in facilitating energy conservation and carbon reduction, and better utilizing fiscal, tax, and financial policies to optimize structure, promote R&D, and support transformation. Furthermore, it necessitates accelerating technological application and innovation and enhancing the technological impetus for industrial green transformation through digital-green integration.

This paper explores the connotations, current status, and challenges of inclusive industrial development. In particular, it analyzes the progress and bottlenecks in China's industrial sector in terms of promoting social equity, equal employment opportunities, regional coordinated development, and support for the growth of small and medium-sized enterprises (SMEs), and searches for solutions to promote inclusive industrial development, foster social equity, improve the quality of employment, and advance the growth of SMEs. Taking into account the actual situation of China's industrial development, this paper analyze inclusive industrial development in four key areas:industrial employment, wage and compensation, the level of inter-regional industrial development, and the development of private SMEs. The specific methodology is the combination of qualitative and quantitative analyses. From a qualitative perspective, this study explains the significance and value of inclusive industrial development through theoretical connotations. By further integrating relevant data and conducting quantitative analysis, it analyzes the current status and challenges of inclusive industrial development in China and discusses in depth the achievements and problems of employment, wages, regional development, and the growth of private SMEs. Overall, inclusive industrial development has achieved certain results in promoting employment and supporting the development of private SMEs. Specifically, there has been a significant improvement in generating employment opportunities and expanding the developing space of these SMEs. However, inclusive industrial development still faces many challenges in terms of wage and compensation and inter-regional industrial development gaps. In terms of wage levels, despite the improvement in overall industrial income, imbalances in the distribution of income still exist, with wage growth lagging for low-income groups in particular. In terms of inter-regional industrial development, the gaps between the eastern and the western regions, and between cities and villages remain large, resulting in the fruits of economic development not effectively benefiting all people. Further analysis reveals that the deep-rooted difficulties and challenges facing inclusive industrial development are primarily reflected in three areas: the uneven regional industrial development, the difficulty in transforming the industrial structure, and the insufficient innovation capacity of private SMEs. In particular, some traditional industries still rely on low-cost, low-technology production methods, leading to a slow process of industrial upgrading and making it difficult to meet the demand for high-quality development in the New Era. At the same time, private SMEs have made relatively insufficient investments in technological innovation and management upgrading, and their innovation capacity and market competitiveness are weak, which also limits their overall performance in the industrial system. In order to further promote inclusive industrial development, this paper puts forward a series of policy recommendations. Firstly, resource allocation should be optimized to promote high-quality and full employment, and the rational flow and allocation of various types of labor resources should be promoted through a combination of policy guidance and market mechanisms. Secondly, to strengthen regional coordinated development, especially by improving new mechanisms for regional development to promote industrial development in the western regions and small and medium-sized cities, and to narrow the regional gap. Lastly, to enhance technological innovation capacity, support private SMEs increase their investment in research and development and scientific and technological innovation, and promote the transformation and upgrading of the industrial structure to achieve inclusive industrial development.

Promoting the deep transformation and upgrading of traditional industries is an important part of the high-quality development of China's economy and society in the new period, and it is a major event concerning the building of China's modern industrial system. In the context of major changes unseen in a century in the world, the development of traditional industries is facing new opportunities and challenges. This paper aims to re-examine and explore the paths and countermeasures for the deep transformation and upgrading of China's traditional industries. This paper conducts a retrospective statistical analysis of the changing status of traditional industries in China's national economy, based on available data from three key dimensions:main business revenue, total profit, and number of employees. It aims to reveal the current development status of traditional industries in China, identify existing challenges through on-site investigations and literature reviews, outline the primary development paths for traditional industries in the new period and new stage, and finally provide corresponding policy recommendations. During the study period, traditional industries, predominantly labor-intensive and capital-intensive sectors, exhibit moderate profitability with slowing growth. Key indicators such as their share of GDP and contribution to economic growth show a declining trend. Nevertheless, traditional industries continue to play a crucial role in China's national economy, accounting for about 50％—60％ of the manufacturing sector in terms of scale, revenue, and employment, thereby providing essential support for national economic development. The conclusions drawn from this paper are as follows:traditional industries, as the pillar and basic components of China's national economy, are the main driver of China's economic growth, the main arena for solving the employment problem, and an important foothold for developing New Quality Productive Forces and promoting high-quality economic growth. Advancing the transformation and upgrading of traditional industries is not only of significant importance but also imperative. In the areas of application of innovation, digital and intelligent transformation, green development, industrial transfer, and talent cultivation, mindset should be shifted and innovation should be implemented in institutions, organizations, and mechanisms, so as to provide enhanced policy support, foster a more conducive environment, and offer stronger backing for the deep transformation, upgrading, and high-quality development of traditional industries.