With the emergence of technology business schools as a new organizational phenomenon in universities and innovation ecosystems, their development has shifted from justifying organizational legitimacy to establishing differentiated positioning and sustainable capabilities. Based on literature analysis, functional comparison, and conceptual analysis, this study proposes a typology of technology business schools according to their primary innovation missions and organizational objects. Three types are identified: technology commercialization-oriented, industrial innovation organization-oriented, and technology enterprise development-oriented technology business schools. The study further develops a “mission–resource–capability” framework to explain how different types of technology business schools achieve organizational fit. It argues that technology commercialization-oriented schools focus on organizing the transition of scientific and technological achievements into industrial applications; industrial innovation organization-oriented schools aim to enhance coordination among innovation actors; and technology enterprise development-oriented schools support the growth and management of technology-based firms. The effectiveness of technology business schools depends not on adopting a unified model, but on aligning their missions with available resources and building organizational capabilities for resource integration, cross-boundary collaboration, and knowledge accumulation. This study provides a conceptual framework for understanding the evolution of technology business schools and offers implications for universities and innovation organizations seeking new approaches to integrating knowledge creation with value realization.

The technological leap of generative artificial intelligence presupposes the exponential expansion of computing power. Driven by capital logic, computing resources are rapidly concentrating among a few technology giants and developed economies, forming a structural monopoly. Marx’s theory of technological alienation provides an analytical lens: when computing power transforms from a human-serving resource into a power lever for extracting excess profits and externalizing environmental costs, technological alienation reappears in digital form. This monopoly gives rise to three ethical dilemmas: the de-subjectification of technological development, the structural entrenchment of social inequality through the computing power gap, and the disruption of the material exchange relationship between humans and nature. To resolve these dilemmas, computing power must be recognized as a public good, and an ethical governance framework must be built along three dimensions—power deconstruction, equitable distribution, and ecological constraint—so that the allocation of computing resources shifts from capital dominated to public governance, truly serving the all-round development of human beings.

Amid the global transition to low-carbon energy, hydrogen has emerged as a critical focus for green economic development. This paper proposes a digital risk management framework for the entire hydrogen supply chain, leveraging large-scale modeling algorithms. Drawing on the China Hydrogen Energy Development Report (2025), the study analyzes four segments in Foshan: production, storage and transportation, refueling, and applications. It identifies key challenges, including data fragmentation, delayed risk warnings, and insufficient cross-regional coordination. To address these issues, a three-tier system is proposed, comprising data resources, model computation, and implementation layers. The framework incorporates measures such as low-carbon production processes, continuous safety monitoring, intelligent deployment of 176 refueling stations, and 21 demonstration scenarios. The findings provide valuable guidance for advancing Foshan’s zero-carbon industrial development.

This paper takes the whole process collaboration of AI enabled industrial chain as the core, sorts out the key elements of collaborative operation, establishes the whole process collaboration architecture, analyzes the implementation effect combined with empirical data, and proposes a systematic implementation mechanism. The research aims to break the collaborative barriers in all links of the industrial chain, build an intelligent, dynamic and efficient collaborative operation system, and provide theoretical support and practical reference for industrial digitalization and intelligent transformation.

To meet the requirements for green and energy-efficient construction of highways, digital twin technology can establish a virtual-real mapping system encompassing physical engineering, construction processes, environmental energy consumption, and management decision-making. This enables real-time perception of construction status, dynamic analysis of resource consumption, optimized scheduling of equipment operation, and process control of carbon emissions. Focusing on highway infrastructure construction scenarios, this research analyzes the application value of digital twins in organizing energy-efficient construction, optimizing material utilization, coordinating mechanical equipment, providing early warnings for quality and safety, and bridging with operation and maintenance. Furthermore, it proposes development pathways for platform construction, data standards, technology integration, demonstration promotion, and industrial synergy, thereby providing support for green highway construction and the upgrading of smart transportation infrastructure.

Digital-intelligent technologies are profoundly transforming the construction and management paradigm of ultra-high voltage power transmission and transformation projects. From the perspective of industrialization, this paper elucidates the theoretical connotations and logical connections among digital-intelligent technology, lean construction and quality traceability, analyzes their industrialization value, identifies bottlenecks such as inconsistent standards, data silos, talent shortage and unclear input-output expectations, and proposes promotion strategies from four dimensions to provide reference for the digital-intelligent transformation and high-quality development of the power industry.

Smart fire protection technology is at a critical window period for transitioning from laboratory innovation to industrial large-scale application; however, its industrialization path still lacks systematic research. Taking fire prevention supervision in high-rise buildings as the entry point, this paper systematically analyzes the technology transfer and transformation path of smart fire protection technology from the perspective of the entire industrialization chain, providing a path reference for the industrialization and transformation of scientific and technological achievements in the fire protection field and related public safety fields.

Focusing on Nanyang’s“333”emerging industrial clusters, this paper combines field surveys, data excavation and AI modeling to analyze local intelligent transformation hurdles. The findings aid Nanyang’s new quality productivity growth and sub-central urban construction, while offering practical references for analogous regions to advance industry-AI integration.

The market-oriented allocation of data elements provides an institutional foundation for realizing the value of medical data. As a new type of infrastructure that facilitates compliant data circulation, the trusted data space is becoming a key carrier for the industrialization of medical data. Based on the national policy background of market-oriented allocation of data elements, this paper systematically reviews the construction logic and operational mechanisms of medical trusted data spaces, deeply analyzes the key obstacles faced in the process of industrialization landing, including insufficient technical standardization, unclear data ownership definition, immature commercialization models, and shortage of interdisciplinary talent. It further proposes industrialization promotion strategies from the aspects of scenario-driven development, standard construction, ownership regulation, business model innovation, and talent cultivation, with a view to providing theoretical and practical references for the industrialization development of medical trusted data spaces.

Smart highway vehicle–road coordination is shifting from demonstration-based validation toward industrial operation, yet its commercialization remains constrained by inadequate pilot-scale testing, unclear data authorization, weak interface coordination, insufficient traceability in acceptance procedures, and incomplete revenue realization mechanisms. Drawing on cases such as the vehicle–road–cloud integration pilot program, the Beijing High-Level Automated Driving Demonstration Area, and the Wuxi Internet of Vehicles Pilot Zone, this study proposes a data governance pathway that connects research outcomes, project delivery, and continuous services through scenario screening, engineering scale-up, service packaging, compliance acceptance, and operational review.

Using a sample of Chinese A-share listed manufacturing firms over 2017–2025, this study empirically examines the performance effects of digital transformation, the mediating mechanism of innovation, and the enabling role of digitalization in manufacturing industrial development, with attention to sector-specific characteristics. The results show that digital transformation significantly improves firm operating performance, with innovation serving as a partial mediator. At the industrial level, firm-level digitalization generates technology spillovers and supply-chain synergy effects, contributing to overall efficiency gains and structural optimization of the manufacturing sector. By integrating both micro-level firm behavior and macro-level industrial dynamics, this paper enriches the empirical evidence on manufacturing digitalization and offers practical implications for firm upgrading, policy formulation on industrial digitalization, and high-quality development of the manufacturing industry.

The digital transformation of the exhibition industry is shifting from the application of isolated tools toward full-process, scenario-based, and platform-oriented transformation. The development of the technology factor market provides resource allocation mechanisms and institutional support for this process. Focusing on the impact of technology factor market development on the digital transformation of the exhibition industry, this paper examines the relationship between the two from three dimensions: the current situation, operational logic, and implementation pathways. The study aims to provide a theoretical reference for enhancing the digital service capacity of the exhibition industry, improving the industrial collaboration system, and promoting high-quality development.

The construction of digital twin cities has become an important direction for the development of smart cities and plays a key role in promoting the transformation of urban governance models. From the perspective of collaborative governance, taking the CIM platform of Shenzhen City as a case, this paper analyzes the cross departmental collaborative mechanism in the construction of digital twin cities, deeply reveals the constraints of deep-seated obstacles on the effect of collaborative governance, and proposes countermeasures to optimize the collaborative governance path of digital twin cities and improve the modernization level of urban governance.

The low-altitude economy is a critical arena for cultivating new quality productive forces. This paper, contextualized within Zhaoqing’s development reality, synthesizes its existing foundations and strategic plans. It analyzes core construction aspects—spatial carriers and technology platforms—and proposes pathways to optimize collaborative governance, strengthen factor guarantees, expand distinctive scenarios, and improve risk prevention, thereby offering practical references for Zhaoqing to establish itself as a distinctive low-altitude economy hub in the Greater Bay Area.

With the deep integration of the digital economy and the green, low-carbon transition,Data elements have become a core new production factor driving the green transformation of the manufacturing sector.Guangxi has leveraged its strategic location and resource advantages to establish a distinctive manufacturing system.However, the sector faces several transformation challenges, including a relatively low industrial level, high energy consumption, and insufficient integration of digitalization and green initiatives.This paper selects time series data from Guangxi for the period 2010–2024.Constructing an econometric model to empirically examine the impact of data elements on the green development of the manufacturing sector。Empirical results show that，Data elements exert a significant, robust, and positive enabling effect on the green total factor productivity of Guangxi's manufacturing sector.Proposed countermeasures and recommendations。This can serve as a reference for the manufacturing sector in Guangxi and other underdeveloped regions in western China to achieve digital-green integration and transition toward a green and low-carbon economy.

In the first year of the 15th Five-Year Plan in 2026, the National Data Bureau designated 2026 as the Year of Data Element Value Release. The Draft of the State-owned Assets Law first included data assets as parts of state-owned assets. Guangzhou’s government data accounts for 80% of the city’s total, but the assetization rate is less than 15%. This article examines the current assetization situation, analyzes challenges related to rights, governance, market and technology, and proposes solutions from systems, markets, technologies and directories, to assist Guangzhou as a benchmark for smart cities.

Heilongjiang Province boasts abundant ice and snow resources, and its digital economy is advancing steadily, providing favorable conditions for the integrated development of the two. In recent years, continuous improvements in regional innovation capacity, the expanding scale of the ice and snow industry, and the accelerated construction of a modern industrial system have laid a solid foundation for digital technologies to empower the ice and snow industry in all respects. However, in practice, the integration of technology and industry remains superficial, digital applications are fragmented, the overall level of the industry is not high, infrastructure is unevenly distributed, and the supply of interdisciplinary talent is insufficient. The root causes are directly related to a reliance on traditional development paths, an industrial structure biased toward traditional sectors, inadequate factor support, and insufficient regional coordination. Based on the actual development of Heilongjiang, it is essential to adhere to innovation-driven development, shore up infrastructure weaknesses, extend the industrial chain, deepen opening up to Russia, strengthen factor support, and ensure green development. A systematic development path should be constructed for the digital economy to empower the ice and snow industry, thereby promoting the high-quality development of this industry through digitalization and contributing to the comprehensive revitalization of Heilongjiang.

The article focuses on the transformation of scientific and technological achievements into industrial applications in Heilongjiang Province’s green industries. It integrates electricity marketing records, industry labels, 96-point daily load curves, and green energy consumption data into a unified analytical framework, establishing an identification chain of “policy guidance–technology transfer–technology commercialization–application validation market diffusion.” The results show that 96-point load data can reflect enterprise production organization, equipment operation, pilot-line ramp-up, and seasonal load variations, providing data support for green industrial chain monitoring, achievement commercialization evaluation, and market-oriented services.

Quantum measurement, which has achieved order-of-magnitude leaps in precision, sensitivity and other key indicators, possesses both strategic security and economic value, representing an important direction for cultivating new quality productive forces. Chengdu has established a solid foundation in terms of policy system, industrial carriers and innovation ecosystem, leveraging its first-mover advantages in quantum time-frequency measurement and core quantum sensing devices. However, it still faces shortcomings including insufficient transformation of scientific and technological achievements, shortage of composite talents, and limited application scenarios. It is recommended that Chengdu focus on differentiated development of advantageous tracks such as quantum time-frequency measurement, build an integrated ecosystem of “government-industry-academia-research application-finance”,strengthen talent cultivation and introduction, open up application scenarios, enhance regional coordination and standardization construction, and establish Chengdu as a core quantum measurement innovation source for national strategic hinterland.

Digitalization serves as the core driving force for advancing high-quality development of rural economy. From four dimensions including industry, production factors, market and governance, this paper analyzes the internal mechanism of digitalization empowering rural economic development, and sorts out practical achievements such as improved rural digital infrastructure, booming new business forms, increased farmers’ income and upgraded rural governance. Meanwhile, it summarizes restrictive problems existing in the development process, including inadequate infrastructure, shortage of digital talents, immature industrial formats and imperfect governance systems. Furthermore, it prospects development trends covering expansion of rural digital industries, urban-rural digital integration, formation of green digital development and modernization of digital governance, so as to provide references for rural construction and the improvement of quality and efficiency of rural economy.

Western national computing hubs prioritize cross-regional computing allocation, causing weak local industrial empowerment,poor compute-green power coordination and insufficient local digital capacity.Taking Qingyang hub as a case, this paper builds a four-layer two-way closed-loop framework under energy, fiscal and digital constraints, summarizes three core integration bottlenecks, and proposes sixdimensional improvement strategies

The aero-engine is a core field of the national strategic emerging industries. Taking the fuel atomization and injection technology of aero-engines as the entry point, this paper systematically analyzes the full-chain transformation process of such technologies from basic research, applied research, concept validation, engineering validation to industrial application. It reveals the key bottlenecks and core challenges at each stage, and proposes systematic pathway optimization suggestions for technology transformation from the dimensions of university enterprise collaboration mechanisms, construction of concept validation platforms, technology readiness level management, and industrial ecosystem building.

In recent years, to promote the transformation of scientific and technological achievements, many local governments have issued policies driving technological innovation, deepening the transformation of research achievements, fostering the development of scientific and technological service industry, and strengthening the capacity-building of technology manager team. These policies explicitly support universities and research institutions in establishing achievement databases and resource service platforms. Against this backdrop, and considering the realistic problems currently faced by universities, such as difficulties in sharing technological achievements and promoting technology, as well as barriers in supply and demand information, it is urgent to build digital service platform with scientific researchers at the core. This platform should be capable of comprehensively gathering, efficiently sharing, and intelligently displaying innovative resources of universities. This paper focuses on the construction of a digital service platform for the transformation of Scientific and technological achievements under the background of artificial intelligence. Starting from the current situation and necessity of construction, the paper elaborates on the platform’s functional modules, system architecture, and service characteristics of the platform, in order to provide pathways to enhance the efficiency and service capabilities of scientific and technological achievements transformation, and promote the transformation of scientific and technological achievements in universities finally.

Against the backdrop of fostering new quality productive forces and advancing industrial transformation and upgrading, optimizing university scientific and technological achievement transformation platforms based on enterprises’ actual technical demands is an effective way to break barriers hindering the integration of innovation chains and industrial chains. From the perspective of enterprise demand traction, this paper adopts policy text analysis and case studies to investigate the construction effects and collaborative operation logic of university achievement transformation platforms in Henan. The study finds that Henan has established a “1+4+N” platform network and a four-dimensional collaborative system via policy arrangements, and stimulated industry-university research vitality through university-enterprise cooperation. However, the platforms are confronted with unbalanced regional development, supply-demand mismatch, insufficient supporting resources and inefficient coordination mechanisms. Accordingly, optimization strategies are proposed involving differentiated platform construction, closed loop services, financial empowerment and intelligent governance. The research results support the improvement of Henan’s innovation ecosystem and provide references for similar platforms in central and western China.

The essence of industrial upgrading lies in the fundamental shift from a factor-driven model to an innovation-driven model, and its success depends on the efficiency of transforming technological achievements into real productive forces. This study closely focuses on the new demands of industrial upgrading for the transformation of technological achievements, constructing specific optimization paths from five dimensions: demand-driven pull, pilot verification platforms, capital injection tools, data matching systems, and delivery model innovation. It aims to provide optimization strategies for the transformation of technological achievements in the context of industrial upgrading.

To promote in-depth collaboration between universities and enterprises in Henan Province, foster the integration of industry, academia, research, and application, and enhance the rate of scientific and technological achievement transformation, this study takes universities in Henan Province as the research subject to explore the influencing factors, models, and innovative strategies for the transfer and transformation of university scientific and technological achievements. The findings reveal that the maturity and value of scientific and technological achievements, are the primary factors affecting the transfer and transformation of university scientific and technological achievements. Currently, the main models for the transformation of university scientific and technological achievements in Henan Province include market transformation, technology transfer, and the “industry-academia-research” model. To address this, innovative approaches are proposed, including improving management mechanisms, upgrading traditional models, establishing service platforms, and policy support. The study demonstrates that by advancing the innovation of university scientific and technological achievement transfer and transformation models through multiple dimensions, multidisciplinary cross-disciplinary development can be promoted, better serving regional economic growth.

Electronic big data is evolving from standalone data resource management toward an industrialization stage encompassing technology transfer and the commercialization of scientific and technological achievements. Taking the industrialization chain of electronic big data as the research object, this paper analyzes mechanisms related to policy-driven scientific and technological innovation, technology transfer organization, technology commercialization and validation, and industrial application. The study finds that the industrial value of electronic big data extends beyond data aggregation and statistical analysis. Rather, it lies in transforming laboratory research outcomes into products for electronic information manufacturing, smart terminals, supply chain management, and other fields through trusted data provision, model engineering, and the accumulation of industry-specific knowledge.

Industry-university-research collaborative innovation serves as a core driving force for boosting high-quality regional economic development. Nevertheless, two prevalent practical bottlenecks remain widespread: difficulties in the industrialization of university scientific research achievements and poor connection between enterprises’ technical demands and academic resources. Taking the practice of industry-university-research collaborative innovation in Tai’an City as the research subject, this paper focuses on the bottlenecks restricting the transformation of scientific and technological achievements from local universities stationed in Tai’an. It sorts out the current status of local collaborative development, explores the internal root causes of existing problems, and constructs an integrated implementation path for coordinated development covering universities, industrial parks and local industries. This study proposes to reshape the logic of cooperation guided by industrial demands, build hubs for the transformation of scientific and technological achievements relying on industrial parks, and stimulate the innovative vitality of talents through institutional reform, so as to form a closed-loop collaborative innovation ecosystem characterized by “enterprises putting forward demands, universities conducting research and development, industrial parks providing support, and markets conducting effect verification”.

The effectiveness of turning technological achievements into real-world results doesn’t just rely on R&D investment; it also depends on how well different steps like identification, evaluation, pricing, and financing work together. Right now, AI is upgrading from a helpful tool to a key infrastructure in the tech service industry. By lowering information costs, accurately profiling results, and optimizing supply-demand matching, it’s helping achievements move from being “just presentable” to “tradeable, fundable, and industrializable.” Its real power lies in building a collaborative system of “data foundation, scenario validation, professional services, and governance,” rather than replacing experts. To make this happen, we need to speed up setting standards for achievement data, open up proof of-concept and pilot scenarios, improve AI-assisted evaluation and accountability mechanisms, and nurture multi skilled service providers to truly boost the impact and industrial contribution of these achievements.

To improve commercialization efficiency and reduce ownership disputes, this study examines delayed IP planning, insufficient protection scope and weak value assessment from patent search, achievement ledger, ownership confirmation and pre-contract management. It proposes a “one database, two maps, three lists and five nodes” mechanism that embeds R&D screening, achievement identification, ownership division and commercialization agreements into the whole R&D process, thereby improving marketability. IP management should be advanced during project initiation, R&D, pilot testing, filing and commercialization negotiation.

The intellectual property system serves as a core institutional supply that stimulates innovation and empowers industrial upgrading. From the perspective of the Hunan Intellectual Property (Ningxiang) Comprehensive Service Center, this paper focuses on the crucial aspect of patent pre-examination, analyzing its institutional value in shortening the authorization cycle, guiding high-quality innovation, and serving key industries. In combination with the practices in Ningxiang Economic Development Zone, this paper proposes optimization paths such as expanding the coverage of filing entities, implementing a batch pre-examination model, strengthening patent navigation services, and enhancing talent cultivation. The aim is to provide a reference for the park to make good use of the intellectual property system and achieve high-quality development.

Currently, China is advancing from a “patent powerhouse” to a “patent superpower,” shifting its patent strategy from quantity-driven growth to quality enhancement. This paper explores the importance and strategies for improving patent quality and reasonably defining claim scope within the context of building an intellectual property superpower. Research indicates that overly broad claim scope leads to difficulties in obtaining patents and unstable rights, while overly narrow scope weakens patent protection. To enhance patent quality, coordinated efforts are required at both the application and examination stages: During application, strengthen publicity and guidance, standardize application procedures, and leverage patent pre-examination services. During examination, rigorously control grant quality, enhance examination capabilities, and improve the reasoning behind rejections. Systematic quality improvement will foster high value patents and support the implementation of innovation-driven development strategies.