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.

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.

Unraveling the efficacy network: A network meta-analysis of adjuvant external beam radiation therapy methods after hepatectomy

BACKGROUND Primary liver cancer is a malignant tumor with a high recurrence rate that significantly affects patient prognosis.Postoperative adjuvant external radiation therapy(RT)has been shown to effectively prevent recurrence after liver cancer resection.However,there are multiple RT techniques available,and the differ-ential effects of these techniques in preventing postoperative liver cancer re-currence require further investigation.AIM To assess the advantages and disadvantages of various adjuvant external RT methods after liver resection based on overall survival(OS)and disease-free survival(DFS)and to determine the optimal strategy.METHODS This study involved network meta-analyses and followed the PRISMA guidelines.The data of qualified studies published before July 10,2023,were collected from PubMed,Embase,the Web of Science,and the Cochrane Library.We included relevant studies on postoperative external beam RT after liver resection that had OS and DFS as the primary endpoints.The magnitudes of the effects were determined using risk ratios with 95%confidential intervals.The results were analyzed using R software and STATA software.RESULTS A total of 12 studies,including 1265 patients with hepatocellular carcinoma(HCC)after liver resection,were included in this study.There was no significant heterogeneity in the direct paired comparisons,and there were no significant differences in the inclusion or exclusion criteria,intervention measures,or outcome indicators,meeting the assumptions of heterogeneity and transitivity.OS analysis revealed that patients who underwent stereotactic body radiotherapy(SBRT)after resection had longer OS than those who underwent intensity modulated radiotherapy(IMRT)or 3-dimensional conformal RT(3D-CRT).DFS analysis revealed that patients who underwent 3D-CRT after resection had the longest DFS.Patients who underwent IMRT after resection had longer OS than those who underwent 3D-CRT and longer DFS than those who underwent SBRT.CONCLUSION HCC patients who undergo liver cancer resection must consider distinct advantages and disadvantages when choosing between SBRT and 3D-CRT.IMRT,a RT technique that is associated with longer OS than 3D-CRT and longer DFS than SBRT,may be a preferred option.

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.

Attention-based spatio-temporal graph convolutional network considering external factors for multi-step traffic flow prediction

Traffic flow prediction is an important part of the intelligent transportation system. Accurate multi-step traffic flow prediction plays an important role in improving the operational efficiency of the traffic network. Since traffic flow data has complex spatio-temporal correlation and non-linearity, existing prediction methods are mainly accomplished through a combination of a Graph Convolutional Network (GCN) and a recurrent neural network. The combination strategy has an excellent performance in traffic prediction tasks. However, multi-step prediction error accumulates with the predicted step size. Some scholars use multiple sampling sequences to achieve more accurate prediction results. But it requires high hardware conditions and multiplied training time. Considering the spatiotemporal correlation of traffic flow and influence of external factors, we propose an Attention Based Spatio-Temporal Graph Convolutional Network considering External Factors (ABSTGCN-EF) for multi-step traffic flow prediction. This model models the traffic flow as diffusion on a digraph and extracts the spatial characteristics of traffic flow through GCN. We add meaningful time-slots attention to the encoder-decoder to form an Attention Encoder Network (AEN) to handle temporal correlation. The attention vector is used as a competitive choice to draw the correlation between predicted states and historical states. We considered the impact of three external factors (daytime, weekdays, and traffic accident markers) on the traffic flow prediction tasks. Experiments on two public data sets show that it makes sense to consider external factors. The prediction performance of our ABSTGCN-EF model achieves 7.2%–8.7% higher than the state-of-the-art baselines.

Circular Formation Flight Control for Unmanned Aerial Vehicles With Directed Network and External Disturbance

This paper proposes a new distributed formation flight protocol for unmanned aerial vehicles(UAVs)to perform coordinated circular tracking around a set of circles on a target sphere.Different from the previous results limited in bidirectional networks and disturbance-free motions,this paper handles the circular formation flight control problem with both directed network and spatiotemporal disturbance with the knowledge of its upper bound.Distinguishing from the design of a common Lyapunov fiunction for bidirectional cases,we separately design the control for the circular tracking subsystem and the formation keeping subsystem with the circular tracking error as input.Then the whole control system is regarded as a cascade connection of these two subsystems,which is proved to be stable by input-tostate stability(ISS)theory.For the purpose of encountering the external disturbance,the backstepping technology is introduced to design the control inputs of each UAV pointing to North and Down along the special sphere(say,the circular tracking control algorithm)with the help of the switching function.Meanwhile,the distributed linear consensus protocol integrated with anther switching anti-interference item is developed to construct the control input of each UAV pointing to east along the special sphere(say,the formation keeping control law)for formation keeping.The validity of the proposed control law is proved both in the rigorous theory and through numerical simulations.

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.

Risk analysis and maintenance decision making of natural gas pipelines with external corrosion based on Bayesian network

Buried natural gas pipelines are vulnerable to external corrosion because they are encased in a soil environment for a long time.Identifying the causes of external corrosion and taking specific maintenance measures is essential.In this work,a risk analysis and maintenance decision-making model for natural gas pipelines with external corrosion is proposed based on a Bayesian network.A fault tree model is first employed to identify the causes of external corrosion.The Bayesian network for risk analysis is determined accordingly.The maintenance strategies are then inserted into the Bayesian network to show a reduction of the risk.The costs of maintenance strategies and the reduced risk after maintenance are combined in an optimization function to build a decision-making model.Because of the limitations of historical data,some of the parameters in the Bayesian network are obtained from a probabilistic estimation model,which combines expert experience and fuzzy set theory.Finally,a case study is carried out to verify the feasibility of the maintenance decision model.This indicates that the method proposed in this work can be used to provide effective maintenance schemes for different pipeline external corrosion scenarios and to reduce the possible losses caused by external corrosion.

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.

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.

The Mechanism Behind Urban Population Growth and Shrinkage from the Perspective of Urban Network Externalities

Urban shrinkage is a global phenomenon,and it will coexist with urban growth for many years.At the same time,the network connection between cities continuously improved due to the construction of the transportation and information networks.However,the relationship between urban network externalities and urban population growth/shrinkage remains unclear.Therefore,based on high-speed railway(HSR)flow data,a spatial econometric model is used to explore the mechanism behind urban population growth and shrinkage from the perspective of network externalities in China.The results indicate that:1)the urban network experiences a certain clubbing effect.Growing cities that are strongly connected are concentrated along China’s main railway lines and the southeastern coastal areas,while shrinking cities that are weakly connected are distributed at the periphery of the network.2)Moreover,the network externality disregards spatial distance and together with the agglomeration externality influences the growth and shrinking of cities.3)Urban economic development still promotes the development of Chinese cities.However,the improvement of the urban economy has a negative cross-regional spillover effect on neighboring cities due to urban competition.4)Lastly,Local spillovers of urban network externalities are positive,while cross-regional ones are negative.Consequently,the government needs to promote the construction of multi-dimensional network connections between cities to promote cities’sustainable development.This study reveals the relationship between urban network externalities and urban development,enriches the theories of network externalities and urban growth/shrinkage,and provides a reference for regional coordinated development.

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.

The Risk Evaluation of Enterprise Technological Innovation Network Based on Extenics

Growing competition has prompted enterprises to choose construct Technological Innovation Network to promote innovation, however the innovation network is a risky innovation system, how to carry out a comprehensive risk assessment of the innovation network is particularly important. This paper focused on the technological innovation network risk analysis, used extenics to define which risk levels should these various risk factors in technological innovation network belongs to. And used Shanghai Caohejing hi tech park to do the empirical research, comfirmed risk factors which have the larger influence on technological innovation network.Enterprises can face them as the main objects of enterprise risk managemenL in order to improve the success rate of the innovation of the enterprise technological innovation network.

The Risk Evaluation of Enterprise Technological Innovation Network Based on Extenics

Growing competition has prompted enterprises to choose construct Technological Innovation Network to promote innovation, however the innovation network is a risky innovation system, how to carry out a comprehensive risk assessment of the innovation network is particularly important. This paper focused on the technological innovation network risk analysis, used extenics to define which risk levels should these various risk factors in technological innovation network belongs to. And used Shanghai Caohejing hi tech park to do the empirical research, comfirmed risk factors which have the larger influence on technological innovation network.Enterprises can face them as the main objects of enterprise risk management, in order to improve the success rate of the innovation of the enterprise technological innovation network.

EFFECTS OF COLLABORATION NETWORKS ON TECHNOLOGY INNOVATION IN THE SOLAR PHOTOVOLTAIC(PV)SECTOR:A CASE STUDY OF CHINA

Efficient use of energy is an essential aspect of green building development.In order to achieve a more energy efficient society,innovation of solar photovoltaic(PV)technologies is a necessity.Collaboration between innovators is regarded as important for innovation;however,the existing literature has made few attempts to investigate how a collaboration network can affect technology innovation in the context of the solar PV sector.This study aims to fill this research gap.In this study,innovation activities are categorized as exploratory innovation and exploitative innovation.A conceptual framework and a series of hypotheses are proposed from the perspectives of network structure(including direct ties,indirect ties,and network efficiency)and network composition(such as geographical proximity,institutional proximity,and technological proximity).The empirical results show that in the solar PV sector of China,collaboration networks with different kinds of structure and composition can imply diverse effects on exploratory innovation and exploitative innovation.Followed with the derived results,it can be concluded that network collaboration is not always beneficial for PV technology innovation.The research findings could convey useful information to both practitioners and policy-makers to adopt appropriate strategies for promoting effective innovation collaboration.