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.

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.

Drivers for Inter-city Innovation Networks Across Chinese Cities:Modelling Physical Versus Intangible Effects

Cross-region innovation is widely recognized as an important source of the long-term regional innovation capacity.In the recent past,a growing number of studies has investigated the network structure and mechanisms of cross-region innovation collaboration in various contexts.However,existing research mainly focuses on physical effects,such as geographical distance and high-speed railway connections.These studies ignore the intangible drivers in a changing environment,the more digitalized economy and the increasingly solidified innovation network structure.Thus,the focus of this study is on estimating determinants of innovation networks,especially on intangible drivers,which have been largely neglected so far.Using city-level data of Chinese patents(excluding Hong Kong,Macao,and Taiwan Province of China),we trace innovation networks across Chinese cities over a long period of time.By integrating a measure on Information and Communications Technology(ICT)development gap and network structural effects into the general proximity framework,this paper explores the changing mechanisms of Chinese innovation networks from a new perspective.The results show that the structure of cross-region innovation networks has changed in China.As mechanisms behind this development,the results confirm the increasingly important role of intangible drivers in Chinese inter-city innovation collaboration when controlling for effects of physical proximity,such as geographical distance.Since digitalization and coordinated development are the mainstream trends in China and other developing countries,these countries'inter-city innovation collaboration patterns will witness dramatic changes under the influence of intangible drivers.

AI-Powered Innovations in High-Tech Research and Development: From Theory to Practice

This comparative review explores the dynamic and evolving landscape of artificial intelligence(AI)-powered innovations within high-tech research and development(R&D).It delves into both theoreticalmodels and practical applications across a broad range of industries,including biotechnology,automotive,aerospace,and telecom-munications.By examining critical advancements in AI algorithms,machine learning,deep learning models,simulations,and predictive analytics,the review underscores the transformative role AI has played in advancing theoretical research and shaping cutting-edge technologies.The review integrates both qualitative and quantitative data derived from academic studies,industry reports,and real-world case studies to showcase the tangible impacts of AI on product innovation,process optimization,and strategic decision-making.Notably,it discusses the challenges of integrating AI within complex industrial systems,such as ethical concerns,technical limitations,and the need for regulatory oversight.The findings reveal a mixed landscape where AI has significantly accelerated R&D processes,reduced costs,and enabled more precise simulations and predictions,but also highlighted gaps in knowledge transfer,skills adaptation,and cross-industry standardization.By bridging the gap between AI theory and practice,the review offers insights into the effectiveness,successes,and obstacles faced by organizations as they implement AI-driven solutions.Concluding with a forward-looking perspective,the review identifies emerging trends,future challenges,and promising opportunities inAI-poweredR&D,such as the rise of autonomous systems,AI-driven drug discovery,and sustainable energy solutions.It offers a holistic understanding of how AI is shaping the future of technological innovation and provides actionable insights for researchers,engineers,and policymakers involved in high-tech Research and Development(R&D).

Evolution Characteristics of Government-Industry-University Cooperative Innovation Network of Electronic Information Industry in Liaoning Province, China

It is important to optimize the cooperative innovation network for the improvement of economic competence and innovative power. Based on the patent information services platform, we obtain invention patent data for the electronic information industry in Liaoning from 1985 to 2015. This paper analyzes the cooperative innovation network structure, its spatiotemporal evolution and the triple helix relationship of government-industry-university(GIU) by using the social network analysis method and the triple helix theory as well as UCINet, ArcGIS and NetDraw. The empirical results show that: 1) the number of the subjects of the electronic information industry GIU cooperative innovation network in Liaoning demonstrates a gradual increase from 1985 to 2015, with the same trend in concentration. In terms of its subject and its centrality, the universities have a higher position, and the industries have a lower position,while the status of the government is still unclear. 2) The cooperative innovation network presents a core-periphery structure, and the polarization effect of innovation subjects tends to be obvious. There is certain distance-decay regularity in the cooperative innovation network, and a strong geographical proximity to cooperative innovation. 3) The compactness shows a downward trend as a whole. In terms of the extent of participation, the industries are better than the government but worse than the universities. This means that the cooperative innovation network of GIU in the electronic information industry in Liaoning is in the initial stage of formation.

Prediction of Rolling Load in Hot Strip Mill byInnovations Feedback Neural Networks

Because the structure of the classical mathematical model of rolling load is simple, even with the self-adapting technology, it is difficult to accommodate the increasing dimensional accuracy. Motivated by this fact, an Innovations Feedback Neural Networks （IFNN） was presented based on the idea of Kalman prediction. The neural networks used the Back Propagation （BP） algorithm and applied it to the prediction of rolling load in hot strip mill. The theoretical results and the off-line simulation show that the prediction capability of IFNN is better than that of normal BP networks, namely, for the prediction of the rolling load in hot strip mill, the prediction precision of IFNN is higher than that of normal BP networks. Finally, a relative complete rolling load prediction system was developed on Windows 2003/XP platform using the OOP programming method and the SQL server2000 database. With this sys- tem, the rolling load of a 1700 strip mill was calculated, and the prediction results obtained correspond well with the field data. It shows that IFNN is valid for rolling load prediction.

Evolution Characteristics of Government-Industry-University-Research Cooperative Innovation Network for China＇s Agriculture and Influ- encing Factors： Illustrated According to Agricultural Patent Case

Under the special background of China, the cooperative innovation between different government-industry-university-research institutes plays an increasingly important role in the agricultural field. However, the existing literature has paid little attention to it. Considering the cooperation patents, published in the agriculture field stemming from the Full-text Database of China Patents as the study object, the spatial and institutional attribute of the authors as the data source, and by combining the social network and spatial econometrics analysis, this paper analyzes the structure evolution characteristics of cooperative innovation networks of agricultural government-industry-university-research institute in the city level of China in 1985–2014, based on the triple helix theory, with the influence factors discussed. This shows that, 1) since 1985, China's agricultural innovation level has been substantially increased, but the development degree of the cooperative innovation network is low, and the patent cooperation mainly relies on authors in the same unit; 2) enterprises play a leading role in the agricultural cooperative innovation. The effect of the government and hybrid organizations driven by the government is not obvious; 3) the cooperative innovation in the province and city dominates, and a multi-pole pattern has been formed. The cooperative innovation network structure evolves from a single helix empty core and double helix multi core to a double helix hierarchical network; 4) the city's science, education funding and personnel investment are key factors determining the agricultural cooperative innovation, while the agricultural development of the city presents slight negative impacts on it. The spatial mismatch of supply and demand is present in the technical cooperative innovation of China's agriculture. Therefore, the science enhancement and education investment to big agricultural provinces should be promptly implemented.

Effects of Network Closure on Cooperative Innovation: Evidence from Dongying's Petroleum Equipment Industry in China

There are two opposing viewpoints on which kind of network configuration provides a more competitive advantage, namely,network closure or structural holes, with the latter occupying the dominant position in the literature. Using social network analysis and negative binomial regression methods, we graph the co-patent network of Dongying's petroleum equipment industry in China and explore its impact on enterprise innovation. The analysis is based on 17 face-to-face interviews, 31 enterprise questionnaires, and 354 co-patent records from the China State Intellectual Property Office identifying cooperative innovation for the years 1988–2013. We find that this network is closed, controlled by state-owned enterprises, and its closure has positive effects on enterprise innovation performance. This may be related to China's unique industrial development history, state system and policies, regional culture and circumstances, and enterprise characteristics. Therefore, for some industries in specific regions, the advantages usually attributed to structural holes and open innovation may not necessarily apply.

Software Defined Optical Networks and Its Innovation Environment

Software defined optical networks （SDONs） integrate software defined technology with optical communication networks and represent the promising development trend of future optical networks. The key technologies for SDONs include software-defined optical transmission, switching, and networking. The main features include control and transport separation, hard-ware universalization, protocol standardization, controllable optical network, and flexible optical network applications. This paper introduces software defined optical networks and its innovation environment, in terms of network architecture, protocol extension solution, experiment platform and typical applications. Batch testing has been conducted to evaluate the performance of this SDON testbed. The results show that the SDON testbed has good scalability in different sizes. Meanwhile, we notice that controller output bandwidth has great influence on lightpath setup delay.

Exploring Regional Innovation Growth Through A Network Approach:A Case Study of the Yangtze River Delta Region,China

As the leading urban agglomeration in China,the Yangtze River Delta(YRD)is experiencing a factor-driven to innovationdriven transition.However,the dynamics of regional innovation growth are not yet fully understood.This paper combines the complex network methodology with spatial econometrics to disentangle the contributions of innovation endowments,innovation network flows,and innovation network positions to regional innovation growth,as well as their spatial spillover effects.The primary findings suggest that regional innovation growth results from the networked agglomeration economies,which is shaped by the interactions between agglomeration factors and network factors.Specifically,agglomeration factors play a fundamental role in regional innovation growth.In contrast,network factors,such as the network flows and network positions,may contribute to new path creation by promoting access to external innovation resources.Additionally,the institutional factors show multiplexity in fostering regional innovation patterns.Such findings indicate that the YRD region should shift the innovation growth pattern from competitive involution to mutually beneficial cooperation to reduce regional disparities.In this regard,the institutional capacity of organizing network flows and fostering reciprocal inter-city partnerships has become increasingly critical for promoting sustainable innovation and regional development.

Entrepreneurship corporate social responsibility and flexible innovation networks： On the interaction between TNCs＇ R＆D activities and local development

Entrepreneurship corporate social responsibility is concerned with obligations that should be undertaken by an enterprise or ＂enterprise citizen＂ to the society including interrelationship between enterprise and some related interest dependents. And it is a sense of value, discipline and respect to the people, community and environment-related policies of the enterprise. Obviously, the core of the notion refers to a commitment of the enterprise in order to improve living standard of related interest counterparts. Nowadays, entrepreneurship corporate social responsibility has been not only an ethical call, but also an institutional constraint. The consensus is that in operation process an enterprise should take into account of its economic, social and ethical effects on consumers, staffs, shareholders, communities, local governments and environment and make a better prospect to them. Based on this point of view, by field work and questionnaire method, this paper discusses specifically the interaction between TNCs＇ R＆D activities and local development of the Pudong New Area, a China＇s largest special economic zone in Shanghai to explore dynamics of the TNCs＇ R＆D activities, growth of the local economy and their roles in promoting flexible innovation networks for sustainable futures. This involves： a. notion of the entrepreneurship corporate social responsibility; b. current state and trend of TNCs＇ R＆D activities; c. mode and linkage tightness between TNCs＇ R＆D activities and the local economy; d. main problems of the TNCs＇ R＆D activities in Pudong; e. the context of flexible innovation networks; and f. manner and ways in creation of flexible innovation networks.

Entrepreneurial Orientation and Innovation Ecosystems in the Industrial Sector, Central Region, Kampala, Uganda: A Review

This review explores entrepreneurial orientation and innovation ecosystems in the industrial sector of the Central Region, Kampala, Uganda, through an analysis of ten scholarly articles. The study contextualizes the research within the regional landscape and establishes a theoretical framework through a focused literature review. Key findings highlight the intersection of entrepreneurial activities and innovation dynamics, emphasizing the region’s unique contributions to the broader field. Discussions on discrepancies and unexplored territories within the articles offer insights into limitations and research gaps. The manuscript concludes by identifying future research avenues, providing a roadmap for ongoing inquiry into the entrepreneurial and innovative dimensions of the Central Region’s industrial sector. This synthesis underscores the importance of cultivating an entrepreneurial mindset and collaborative innovation strategies for sustainable industrial development in the region.

The Study on the Evolutional Mechanics of Technological Innovation Network

Based on the statistical mechanics and technology innovation network, this paper analyzed network evolutional mechanics, and constituted its evolutional model.

Scheme of Railway 5G Integrated Innovation Test Platform

An inevitable trend has already taken shape for the application of the 5th Generation Mobile Communication Technology(5G)in the railway sector.The application scenarios and business types of the railway sector are complex and diverse,so it is indispensable to test and verify the railway 5G before actual deployment.The design and creation of the railway 5G integrated innovation test platform provides engineering design,test and verification conditions for the networking,coverage and business development of 5G public networks and 5G-R in railway scenarios.This paper introduces the design of the overall architecture for the integrated railway 5G innovation test platform according to the railway network requirements,application scenarios and intelligent development trend;respectively elaborates on the design of the 5G-R core network,bearer network and wireless access along loop tracks,in combination with the characteristics of railway scenarios and the requirements of railway dispatching,operation and safety;raises further solutions on the network deployment and coverage schemes of 5G public networks so as to meet the application requirements of 5G public networks.The study results show that the integrated railway 5G innovation test platform scheme contains co-existence of 5G public and private networks,combines the indoor and outdoor scenarios,as well as takes into account of the dynamic and static tests so as to meet the environmental requirements for the integrated railway 5G test and application of all network functions,for which it can provide comprehensive technical support for railway 5G technology research and development,standard formulation,testing,etc.

An Expert System to Detect Political Arabic Articles Orientation Using CatBoost Classifier Boosted by Multi-Level Features

The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.

A Review on Mobile and Sensor Networks Innovations in Intelligent Transportation Systems

Rapid developments of mobile technologies, data acquisition and big data analytics, and their integration with critical application domains such as transportation systems have the potential to produce more efficient, real-time, intelligent and safe transportation infrastructure. To increase the quality of transportation services, wireless sensor networks, mobile phones, crowd sourcing, RFID and Bluetooth technologies are being used. We surveyed innovations that were transformed from ideas in research labs into commercial systems in practical use. In this paper, we present some innovative mobile technologies, services and platforms that are being used in modern transportation applications including traffic data acquisition, traffic management and control, route optimizations, infrastructure redesign, road safety and enhancing user experience.

An Evaluating Model for Enterprise's Innovation Capability Based on BP Neural Network

To meet the challenge of knowledge-based economy in the 21st century,scientifically evaluating the innovation capability is important to strengthen the international competence and acquire long-term competitive advantage for Chinese enterprises.In the article,based on the description of concept and structure of enterprise's innovation capability,the evaluation index system of innovation capability is established according to Analytic Hierarchy Process(AHP).In succession,evaluation model based on Back Propagation(BP) neural network is put forward,which provides some theoretic guidance to scientifically evaluating the innovation capability of Chinese enterprises.

Construction Approaches of Enterprise Innovation Network from the Perspective of Social Network

As an important means for enterprises to promote technological progress,product development and service level,innovation has an absolute role in enhancing enterprises'innovation strength and market strength.In the context of frequent and rapid product replacement and shortened technological innovation cycle in modern society,through the embedding of social networks,forming platforms for higher education institutions,governments,capital markets,research institutions and intermediary links to promote the integration of innovation and capital development and make the most of every resource has become an important way.From the perspective of social network,the methods and necessary approaches for the establishment of enterprise innovation network are studied in this article.

Structure, Evolution and Hot Spots of Cooperation Innovation Knowledge Network

Based on the statistics analysis of cooperation innovation articles, the paper analyses the distributing characteristics of cooperation innovation research papers. The distribution, structure and evolution of cooperation innovation research are studied through the social network and co-word method, combined with the information visualization technology. This study is based on the papers in the SSCI database during 2000-2014. The analysis and statistics of papers reveal distribution characteristics of the subject, time, institutions, countries and areas. The statistics shows that the research perspective of cooperation innovation from business and economics. The time distribution presents that research of cooperation innovation attracts enormous attention and the research achievement is increasing. From the distribution of organizations, countries and areas, North America and Europe countries maintain the leading position in this research field. But institutions and universities of China and other Asian countries or areas are witnessed their outstanding achievements in cooperation innovation research. Combining the co-word network analysis method, the paper studies the structure and content of cooperation innovation knowledge network in five stages and makes the net spectrum, visually showing the hot spots at various periods. The top highly cited papers in all five stages are reviewed simultaneously;their research hot spots and evolution process are concluded. The study shows 11 subjects including strategic alliances, social networks, R&D cooperation, R&D, technology transfer, alliances, knowledge management, social capital, entrepreneurship, trust, biotechnology are always the central issues in last 15 years. The focus of research is from the relationship between alliance and technology innovation to networking and knowledge innovation and then to open innovation.

Innovation in Chinese Agribusinesses： Internal Resources and External Networks

The existing literature on innovation concentrates mostly on large industrial firms and high-technology industries, whereas, little attention has been given to agribusiness. Empirical evidence regarding the driving forces behind innovation in agribusinesses in developing countries, China in particular is scarce. This paper helps fill that void. It develops a framework in which innovation results from synergies between internal resources and external networks. This paper applies and tests the framework using 2003-2005 data from a panel survey of 32 leading agribusiness firms in Shandong Province, China. The empirical results indicate the importance of internal resources, external networks and the synergies between them. We find that R＆D expenditures and the number of technical employees are internal resources that are both important to product innovation. Surprisingly, management quality is negatively related to the possession of a unique technology and new products as a proportion of all products. It is possible that management quality is associated with more formalization and rigidity in decision-making, hindering creativity and lengthening the new product development cycle. In order to develop innovative products, our results suggest that investing in R＆D and hiring more technical staff may be more effective approaches than spending on managerial talent.