China’s High-Quality Technology Innovation:Scenario Narrative and Measurement System

The world today is undergoing disruptive,transformative shifts driven by a new wave of technological revolutions and industrial changes.In this context,a central question for China’s innovation-driven development strategy is how to effectively identify and measure high-quality technological innovations.Drawing on the stylized facts and scenario narrative of China’s technological landscape,this paper proposes a framework and measurement system for evaluating high-quality technological innovations.While China’s top-level design for technological innovation is guided by policy documents,the increasing number of enterprises applying for“high-tech enterprise”status has coincided with a decline in the quality of patent filings.In response,this paper first underscores the challenges and necessity of measuring the quality of technological innovations.Second,we introduce the high-quality technological innovation indicators and employ them to assess the quality of tech innovations at the firm level,utilizing an approach that combines analogical narrative,gene coding,text analysis,semantic logic,and a database of granted invention patents in China.Third,we examine the systematic and individual biases inherent in citation counts,a commonly used indicator,under specific contexts,and employ a granular instrumental variable approach to validate the effectiveness of the indicators.Finally,we develop a“family tree”of the indicators and explore their application scenarios through a combination of established and extended indicators.Our findings provide a theoretical foundation for evaluating China’s technological innovation quality,inform policy incentives,and offer insights for academia to apply high-quality technological innovation indicators in different contexts.

Domain-specific modeling and verification for C4ISR capability requirements

An approach was proposed to specify the C4ISR capability of domain-specific modeling language.To confine the domain modeling within a standard architecture framework,formally a C4ISR capability meta-ontology was defined according to the meta-model of DoD Architecture Framework.The meta-ontology is used for extending UML Profile so that the domain experts can model the C4ISR domains using the C4ISR capability meta-concepts to define a domain-specific modeling language.The domain models can be then checked to guarantee the consistency and completeness through converting the UML models into the Description Logic ontology and making use of inference engine Pellet to verify the ontology.

Rac GTPases:domain-specific functions in neuronal development

Understanding fundamental mechanisms governing axon outgrowth and guidance can inform the development of therapeutic strategies to restore neuronal function damaged though injury or disease. Axons navigate the extracellular environment by responding to guidance cues that bind to cell surface receptors to relay information intracellularly via Rho GTPase family members, including the Rac GTPases.

NNL:a domain-specific language for neural networks

Recent years,neural networks(NNs)have received increasing attention from both academia and industry.So far significant diversity among existing NNs as well as their hardware platforms makes NN programming a daunting task.In this paper,a domain-specific language(DSL)for NNs,neural network language(NNL)is proposed to deliver productivity of NN programming and portable performance of NN execution on different hardware platforms.The productivity and flexibility of NN programming are enabled by abstracting NNs as a directed graph of blocks.The language describes 4 representative and widely used NNs and runs them on 3 different hardware platforms(CPU,GPU and NN accelerator).Experimental results show that NNs written with the proposed language are,on average,14.5%better than the baseline implementations across these 3 platforms.Moreover,compared with the Caffe framework that specifically targets the GPU platform,the code can achieve similar performance.

Building a Productive Domain-Specific Cloud for Big Data Processing and Analytics Service

Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.

Influence of Software Modeling and Design on Domain-Specific Abstract Thinking: Student’s Perspective

Software engineering has been taught at many institutions as individual course for many years. Recently, many higher education institutions offer a BSc degree in Software Engineering. Software engineers are required, especially at the small enterprises, to play many roles, and sometimes simultaneously. Beside the technical and managerial skills, software engineers should have additional intellectual skills such as domain-specific abstract thinking. Therefore, software engineering curriculum should help the students to build and improve their skills to meet the labor market needs. This study aims to explore the perceptions of software engineering students on the influence of learning software modeling and design on their domain-specific abstract thinking. Also, we explore the role of the course project in improving their domain-specific abstract thinking. The study results have shown that, most of the surveyed students believe that learning and practicing modeling and design concepts contribute to their ability to think abstractly on specific domain. However, this finding is influenced by the students’ lack of the comprehension of some modeling and design aspects (e.g., generalization). We believe that, such aspects should be introduced to the students at early levels of software engineering curriculum, which certainly will improve their ability to think abstractly on specific domain.

Research on the Innovativeness and Characteristic of Digital Media under the Environment of Internet and Big Data

In this paper, we conduct survey and research on the innovativeness and characteristic of digital media under the environment of Internet and big data. Under the background of the era of rapid change, the current education system is more severe impact and challenge. Creative industry is the product of cultural industry development to a new stage, is the most creative cultural industry and the origin of the core part of the new economic era of creativity industry is the condition of globalization. The research indicates that the combination of the big data with digital media is necessary and needed. In the future, we will test more related combination and creativeness.

Callfor Papersfor Special Issue Innovative Pharmaceutical Research Facilitated by Ai

Al is revolutionizing the current paradigm of pharmaceutical research,addressing the challenges encountered at all stages of the process.Al driven drug discovery is based on biomedical big data and new algorithms to identify drug targets,screen and optimize active compounds,analyze drug properties,and facilitate drug production and quality control.On this basis,we are organize this special issue entitled“Innovative Pharmaceutical Research Driven by Al”,to collect Research articles,Review papers,and Short communications,facilitating pharmaceutical research.

Addressing inclusion,innovation,and sustainability challenges through the lens of economic geography:Introducing the hierarchical regional innovation system

The world is facing dramatic challenges related to environmental sustainability at an accelerating pace.In this context,the field of economic geography(EG)has been playing an important role in understanding both the socioeconomic and technological dimensions of these challenges,as it deals with a variety of complementary notions and perspectives.Departing from this lens,our aim is to explore a conceptual framework that can help us to understand environmental changes relating to multi-dimensional territorial development,notably in eco-nomic contexts where inequality is high,and stratification based on hierarchies regulate social and economic life.Based on the territory concept,we propose the original notion of a hierarchical regional innovation system(HRIS)that emphasises the pervasive role of hierarchies(powers)in regional innovation systems and illustrate its value with evidence and case studies from extant literature on sustainability transitions.The HRIS can help us understand and promote development paths considering the contribution of inclusive eco-innovations(another original conceptual amalgam).Through some empirical cases from other studies in low-carbon transitions,we show the application of the HRIS(and inclusive eco-innovation)framework.In conclusion,we provide incen-tives to explore new regional innovation systems,alongside the HRIS,adapted to different regions worldwide and centred on the inclusiveness of people and places.

Research on Innovation-Driven Expansion of Regional OFDI: New Evidence From a Business Environment Perspective

This paper investigates the impact of provincial innovation-driven efficiency on the expansion of regional Outward Foreign Direct Investment(OFDI)flows within the context of China’s economy during the period 2011 to 2020 by measuring the innovation-driven efficiency and business environment index using the DEA-Malmquist index and the combined CRITIC weighting method from the new perspective of business environment improvement.The findings reveal that:(a)There is an inverted U-shaped relationship between provincial innovation-driven efficiency and regional OFDI flows.This increase in innovation-driven efficiency can promote OFDI expansion of the region by improving its business environment.(b)The improvement of the business environments plays a significant intermediary and synergistic role in OFDI expansion driven by improved innovation efficiency.(c)The study of regional heterogeneity suggests that the central region enjoys the longest window period in terms of innovation-driven OFDI expansion,followed by the eastern region while the western region has the shortest window period.The improvement of the business environment in the western region is more effective in driving regional OFDI expansion.This conclusion remained true after the robustness test.In conclusion,this paper offers a few policy recommendations that can help Chinese capital of various kinds go global more effectively.

Improving innovation and entrepreneurship education in higher institutions: the impact of "Mass Entrepreneurship and Innovation" education on undergraduates' entrepreneurial intentions

The exploration of the way"mass entrepreneurship and innovation"(MEI)education influences students'aspirations to become entrepreneurs has grown into an important area of analysis in studies related to higher education.This research intends to examine the consequences of MEI education on students'tendency towards entrepreneurship,and to put forward methods for augmenting the teaching of innovation and entrepreneurship in private higher educational establishments.To achieve this objective,questionnaires and semi-structured interviews were employed in the study,which involved a total of 197 students and five education experts.The statistical analysis of the questionnaire data revealed that MEI education was positively related to students'entrepreneurial intentions,and that both entrepreneurial experience and family entrepreneurial background played moderating roles in this relationship.The interview findings indicated that private universities could enhance educational reforms by designing talent training programs,developing diversified curricula,and developing more professional entrepreneurial platforms to encourage students'entrepreneurial intentions.This study offers fresh insights for improving and perfecting the mechanism of innovation and entrepreneurship education in private universities.

How does network intermediary affect collaborative innovation?Evidence from Chinese listed companies

Purpose:This study aims to explore how network intermediaries influence collaborative innovation performance within inter-organizational technological collaboration networks.Design/methodology/approach:This study employs a mixed-method approach,combining quantitative social network analysis with regression techniques to investigate the role of network intermediaries in collaborative innovation performance.Using a patent dataset of Chinese industrial enterprises,the research constructs the collaboration networks and analyzes their structural positions,particularly focusing on their role as intermediaries,characterized by betweenness centrality.Negative binomial regression analysis is employed to assess how these network characteristics shape innovation outcomes.Findings:The study reveals that firms in intermediary positions enhance collaborative innovation performance,but this effect is nuanced.A key finding is that network clustering negatively moderates the intermediary-innovation relationship.Highly clustered networks,while fostering local collaboration,may limit the innovation potential of intermediaries.On the other hand,relationship strength,measured by collaboration intensity and trust among firms,positively moderates the intermediary-innovation link.Research limitations:This study has several limitations that present opportunities for further research.The reliance on quantitative social network analysis may overlook the complexity of intermediaries’roles,and future studies could benefit from incorporating qualitative methods to better understand cultural and institutional factors.Additionally,cross-country comparisons are needed to assess the consistency of these dynamics in different contexts.Practical implications:The study offers practical insights for firms and policymakers.Organizations should strategically position themselves as network intermediaries to access diverse information and resources,thereby improving innovation performance.Building strong trust helps using network intermediary advantages.For firms in highly clustered networks,it is important to seek external partners to avoid limiting their exposure to new ideas and technologies.This research emphasizes the need to balance network diversity with relationship strength for sustained innovation.Originality/value:This research contributes to the literature by offering new insights into the role of network intermediaries,presenting a comprehensive framework for understanding the interaction between network dynamics and firm innovation.

The Future of Environmental Engineering Technology:A Disruptive Innovation Perspective

Scientific and technological revolutions and industrial transformations have accelerated the rate of innovation in environmental engineering technologies.However,few researchers have evaluated the current status and future trends of technologies.This paper summarizes the current research status in eight major subfields of environmental engineering—water treatment,air pollution control,soil/solid waste management,environmental biotechnology,environmental engineering equipment,emerging contaminants,synergistic reduction of pollution and carbon emissions,and environmental risk and intelligent management—based on bibliometric analysis and future trends in greenization,low carbonization,and intelligentization.Disruptive technologies are further identified based on discontinuous transformation,and ten such technologies are proposed,covering general and specific fields,technical links,and value sources.Additionally,the background and key innovations in disruptive technologies are elucidated in detail.This study not only provides a scientific basis for strategic decision-making,planning,and implementation in the environmental engineering field but also offers methodological guidance for the research and determination of breakthrough technologies in other areas.

Current Status and Future Suggestions for Innovative Drug Research and Development in China

In recent years,with the policy reform of new drug review and approval,China has ushered in a surge of innovative drug development.Based on the Pharnexcloud database and the Pharmcube database,we analyzed the innovative drugs approved for marketing and entered clinical trials in China,sorted out the major research and development(R&D)institutions and enterprises,the distribution of innovative drug target types,and the primary therapeutic areas of the approved innovative drugs,and compared with the global innovative drug R&D landscape.Since 2020,China's innovative drug development has shown a rapid growth trend,with intense competition among biopharmaceutical companies,and the emergence of a number of leading biopharmaceutical enterprises.Popular targets for clinical-stage and approved drugs include protein tyrosine kinase,epidermal growth factor receptor,vascular endothelial growth factor receptor,and others.Oncological diseases are the most active domain for new drug R&D in China,followed by infectious diseases and neurological diseases.Suggestions for future development are proposed to increase policy support,enhance R&D innovation investment,optimize pipeline layout,strengthen international cooperation,and focus on innovative targets.This review provides a reference for pharmaceutical R&D enterprises,scientific researchers,and government administrators.

Innovation and Firm Co-ownership Network in China’s Electric Vehicle Industry

Firms are embedded in complex networks,where diverse ideas combine and generate new ideas.Shareholders of firms are of-ten seen as critical external resources that have significant influence on firm innovation.The current literature tends to focus on the rela-tionship between firms and their shareholders,while paying less attention to the connections between firms with the same shareholders.This article identifies two types of network spillover effects,intra-city network effect and inter-city network effect,by visualizing the co-ownership networks in China’s electric vehicle(EV)industry.We find that firms with the same shareholders,which are defined as co-owned EV firms,are more innovative than non-co-owned ones.Furthermore,there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders.While corporate shareholders help exploiting local tacit knowledge,financial institutions are more active in bridging inter-city connections.The conclusion is confirmed at both firm and city levels.This paper theor-izes the firm co-ownership network as a new form of institutional proximity and tested the result empirically.For policy consideration,we have emphasized the importance of building formal or informal inter-firm network,and the government should further enhance the knowledge flow channel by institutional construction.

The Mediating Effect of Digital Transformation on the Link Between Executive Overconfidence and Corporate Green Innovation

Green technological innovation is crucial for the manufacturing industry’s green transformation and sustainable development.This study examines the impact of executive overconfidence on corporate green innovation,focusing on the internal drivers of corporate innovation and using a sample of Shanghai and Shenzhen A-share listed manufacturing companies from 2013 to 2020.We further examine the mediating role of digital transformation and the moderating role of external attention.The findings indicate that executive overconfidence promotes corporate green technological innovation.Overconfident executives enhance green innovation by accelerating digital transformation.Moreover,external attention from analysts and media positively moderates the relationship between executive overconfidence and corporate green innovation.Heterogeneity analysis reveals that the positive impact of executive overconfidence on green innovation is more significant in non-state-owned enterprises,high-tech firms,and enterprises with lower pollution levels.

Two-sided and Heterogeneous Effects of Environmental Regulation on the Technological Innovation Efficiency of Iron and Steel Enterprises in China

In this study,the relationship between environmental regulations and technological innovation efficiencyis empirically examined via panel data from 33 iron and steel enterprises(ISs)in China between 2015 and 2021.The results show that the average“innovation compensation effect”of environmental regulations on the technological innovation efficiency of ISs exceeds the average“compliance cost effect”,thus resulting in a clearly positivenet effect.Both the two-sided effects and the net effects vary across different years,geographical regions,andtypes of property rights.As the quantile of technological innovation efficiency increases,the positive influence ofenvironmental regulations tends to increase.Furthermore,the strengthening of financing constraints and firmcompetitiveness enhances the positive impact of environmental regulations on the technological innovation efficiency of ISs.Additionally,a double-threshold effect of environmental regulations on the technological innovationefficiency of ISs is revealed in this study.The realisation of the Porter hypothesis occurs when financing constraintsand firm competitiveness fall within specific threshold intervals.This research not only deepens our understandingof the relationship between environmental regulations and the technological innovation efficiency of ISs but alsoprovides valuable policy insights for optimising environmental regulations to facilitate targeted improvements in thelevel of technological innovation efficiency.

Innovative Practice of Intelligent Business Models in the Field of Communication

As a service format to meet spiritual needs, fashion culture industry is often synchronized in its creation, production, dissemination, display and consumption. In order to explore how artificial intelligence provides technical means, platforms, channels and space for intelligent formats in the field of communication, and how to provide intelligent services for cultural creation, communication, display and consumption. This paper discusses the application and innovation of artificial intelligence in all aspects of communication field, analyzes the problems and puts forward corresponding countermeasures and suggestions.

Fast-to-Clinic, Fast-to-Market in Biotech Innovation: Optimizing Chemistry Manufacturing & Controls (CMC) Excellence for Clinical and Commercial Success

In the emerging world of biotech innovation, the fast-to-clinic/market strategy has emerged as a critical “mantra” for biotech, investors, and CDMOs. This approach addresses the escalating costs and complexities of research and development by streamlining the path from concept to clinical trials and, ultimately, to market. The article delves into the intricacies of implementing a fast-to-clinic/market strategy, underlining the empowering role of strategic decision-making in preclinical and commercial stages. The plan advocates for a phase-appropriate approach, where the development decision is tailored to each phase of the product’s lifecycle. This ensures that resources are allocated efficiently, risks are managed effectively, and the product can move through the development pipeline accelerated without compromising quality or regulatory compliance. The article also discusses the role of CDMOs in facilitating rapid product development and the essential factors biotech companies must consider when selecting a partner for outsourcing. These factors include the CDMO’s expertise in navigating regulatory landscapes, technological capabilities, and ability to scale processes efficiently. Moreover, the article stresses the importance of agility and flexibility in the fast-to-clinic/market approach. Biotech companies are encouraged to adopt adaptable strategies that respond to the fast-evolving regulatory and market landscapes.

Surgeon Perspectives on Anastomotic Leaks and FluidAI’s StreamTM Platform: Integrating Qualitative Insights for Technological Innovation

Purpose: This article investigates the critical importance of integrating surgeons’ direct input into the development of innovative technologies that address gaps in surgical care, including those aimed at reducing anastomotic leaks (AL), a major complication in gastrointestinal surgery. While traditional quantitative research methods are prevalent, they often overlook the invaluable insights of the surgeons who manage these complications firsthand. Subjects and Methods: This study employs a qualitative approach, utilizing semi-structured interviews with 40 surgeons from various specialties, including general, bariatric, colorectal, trauma, hepato-biliary, and thoracic surgery. The interviews were designed to probe the needs of surgeons, challenges currently faced, and gaps in clinical practice, research, and technology for detection and/or management of AL. The data were analyzed using thematic analysis, which revealed significant gaps in current technologies for early detection and prevention of leaks. Results: Surgeons expressed strong interest in FluidAI’s Stream™ Platform, a non-invasive medical device designed to monitor postoperative drainage fluid in real-time, providing continuous data on AL risk. The ability of this platform to offer early prediction through pH and electrical conductivity analysis was particularly appealing to participants, who emphasized the importance of timely interventions in improving patient outcomes. The study’s findings highlight not only the clinical challenges but also the emotional toll that AL takes on surgeons, underlining the need for innovations that are both data-driven and humanistic. Conclusion: By centering surgeons’ perspectives, this research advocates for a human-centered approach to technological advancement, ensuring that new tools are both clinically effective and aligned with the real-world needs of surgical practitioners.