Developing institutional repositories network:Taking IR Grid at Chinese Academy of Sciences as an example

This paper introduces the current practice of building a network of institutional repositories(IRs) at Chinese Academy of Sciences(CAS), which is named CAS IR Grid.National Science Library(NSL) of CAS plays a leading role in the construction, promotion and implementation of CAS IR Grid. It aims to promote each institute of CAS to build IR of its own, and finally form the IR network of CAS institutes. NSL's experience is introduced in coordinating and supporting institutes' building of their respective IRs and promoting IR services by adopting collaborative and progressive development strategies. Achievements made during the development of CAS IR Grid are described and challenges for its future development are discussed. The authors aim to provide best practices for developing a network of institutional repositories in research institute settings, which can serve as a practical reference to other institutions engaged in the similar task.

A Review on Determinants Affecting Commercialization of Academic Institution Final Year Projects

Final year project is an important training and assessment component incorporated in many courses of academic institution.The ability to translate ideas,research,and creativity into actual products,services,or businesses shows how successful and impactful people or institutions can be in the wider economy.However,in most of the cases,the outcomes of the final year project usually remain as academic discussion without maximizing their potential to be converted into a commercialized product or services.In this review,theory and applications are discussed to understand how entrepreneurial skills and networking abilities,components of individuals’human capital can impact the commercialisation of final year projects.Furthermore,determinants affecting commercialization of final year projects will also be explored namely:entrepreneurial skills,networking ability,access to resources,institutional support as well as creativity and innovation.

Optimized Artificial Neural Network Techniques to Improve Cybersecurity of Higher Education Institution

Education acts as an important part of economic growth and improvement in human welfare.The educational sectors have transformed a lot in recent days,and Information and Communication Technology(ICT)is an effective part of the education field.Almost every action in university and college,right from the process fromcounselling to admissions and fee deposits has been automated.Attendance records,quiz,evaluation,mark,and grade submissions involved the utilization of the ICT.Therefore,security is essential to accomplish cybersecurity in higher security institutions(HEIs).In this view,this study develops an Automated Outlier Detection for CyberSecurity in Higher Education Institutions(AOD-CSHEI)technique.The AOD-CSHEI technique intends to determine the presence of intrusions or attacks in the HEIs.The AOD-CSHEI technique initially performs data pre-processing in two stages namely data conversion and class labelling.In addition,the Adaptive Synthetic(ADASYN)technique is exploited for the removal of outliers in the data.Besides,the sparrow search algorithm(SSA)with deep neural network(DNN)model is used for the classification of data into the existence or absence of intrusions in the HEIs network.Finally,the SSA is utilized to effectually adjust the hyper parameters of the DNN approach.In order to showcase the enhanced performance of the AOD-CSHEI technique,a set of simulations take place on three benchmark datasets and the results reported the enhanced efficiency of the AOD-CSHEI technique over its compared methods with higher accuracy of 0.9997.

A Study of Methods to Identify Industry-University-Research Institution Cooperation Partners based on Innovation Chain Theory

Purpose： This study aims at identifying potential industry-university-research collaboration（IURC） partners effectively and analyzes the conditions and dynamics in the IURC process based on innovation chain theory.Design/methodology/approach： The method utilizes multisource data, combining bibliometric and econometrics analyses to capture the core network of the existing collaboration networks and institution competitiveness in the innovation chain. Furthermore, a new identification method is constructed that takes into account the law of scientific research cooperation and economic factors.Findings： Empirical analysis of the genetic engineering vaccine field shows that through the distribution characteristics of creative technologies from different institutions, the analysis based on the innovation chain can identify the more complementary capacities among organizations.Research limitations： In this study, the overall approach is shaped by the theoretical concept of an innovation chain, a linear innovation model with specific types or stages of innovation activities in each phase of the chain, and may, thus, overlook important feedback mechanisms in the innovation process.Practical implications： Industry-university-research institution collaborations are extremely important in promoting the dissemination of innovative knowledge, enhancing the quality of innovation products, and facilitating the transformation of scientific achievements.Originality/value： Compared to previous studies, this study emulates the real conditions of IURC. Thus, the rule of technological innovation can be better revealed, the potential partners of IURC can be identified more readily, and the conclusion has more value.

Threefold Optimized Forecasting of Electricity Consumption in Higher Education Institutions

Energy management benefits both consumers and utility companiesalike. Utility companies remain interested in identifying and reducing energywaste and theft, whereas consumers’ interest remain in lowering their energyexpenses. A large supply-demand gap of over 6 GW exists in Pakistan asreported in 2018. Reducing this gap from the supply side is an expensiveand complex task. However, efficient energy management and distributionon demand side has potential to reduce this gap economically. Electricityload forecasting models are increasingly used by energy managers in takingreal-time tactical decisions to ensure efficient use of resources. Advancementin Machine-learning (ML) technology has enabled accurate forecasting ofelectricity consumption. However, the impact of computation cost affordedby these ML models is often ignored in favour of accuracy. This studyconsiders both accuracy and computation cost as concurrently significantfactors because together they shape the technology environment as well ascreate economic impact. Thus, a three-fold optimized load forecasting modelis proposed which includes (1) application specific parameters selection, (2)impact of different dataset granularities and (3) implementation of specificdata preparation. It deploys and compares the widely used back-propagationArtificial Neural Network (ANN) and Random Forest (RF) models for theprediction of electricity consumption of buildings within a university. In addition to the temporal and historical power consumption date as input parameters, the study also embeds weather data as well as university operationalcalendars resulting in improved performance. The outcomes are indicativethat the granularity i.e. the scale of details in data, and set of reduced and fullinput parameters impact performance accuracies differently for ANN and RFmodels. Experimental results show that overall RF model performed betterboth in terms of accuracy as well as computational time for a 1-min, 15-minand 1-h dataset granularities with the mean absolute percentage error (MAPE)of 2.42, 3.70 and 4.62 in 11.1 s, 1.14 s and 0.3 s respectively, thus well suitedfor a real-time energy monitoring application.

A comparative study on institutional collaboration characteristics in EM and LIS in China

Purpose： This study analyzes the current status of institutional cooperation in economics and management （EM） and library and information science （LIS） in China.Design/methodology/approach： Based on the Chinese Social Science Citation Index （CSSCI） database, we constructed institutional collaboration networks in EM and LIS, and analyzed the collaboration characteristics through social network analysis.Findings： In the development and evolution of the collaboration network of institutions in humanities and social sciences, EM is always at the center. It has extensive cooperation relationships with other fields. The position of LIS has also become centralized, and its interdisciplinary cooperation has increased. For both EM and LIS, we observed ＂small-world＂ and ＂scale-free＂ networks, indicating full communication and mature development in both disciplines. Based on a comparison of two institutions in the two fields, we confirmed the comprehensive development in EM and the extensive information exchange in LIS.Research limitations： We collected data only from humanities and social sciences, but did not consider the connection between EM and natural sciences, or between LIS and natural sciences. In addition, the paper lacks analysis of institutional collaboration at the micro level.Practical implications： The paper provides insights into the institutional cooperation characteristics in EM and LIS in China.Originality/value： The paper offers a new perspective on the characteristics of institutional collaboration in China.

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.

Unequal Development and Territorial Competitiveness of Network Economy

The territorial consideration is enclosed in the development of network economy and e-Business, and there is no departure of the cultivation of e-Business from the establishment of territorial competitiveness. The traditional theory of the territorial competitiveness has come across a serious impact from the Internet. So the development of Intemet infrastructures and institutional environment would be something new to the theory of territorial competitiveness in the Internet era.

Challenges of the Performance Standards of the International Finance Corporation in Financing the African Integrated High-Speed Railway Network and the Way Forward: The Case of Standard Gauge Railway in Tanzania

Financing of the African Integrated High-Speed Railway Network (AIHSRN) through Standard Gauge Railway (SGR) Projects is very expensive. As a result, most of the African countries seek financial supports from the International Financial Institutions (IFIs). However, conditions provided by the IFIs through the Performance Standards (PS) of the International Financial Corporation (IFC) increase cost of the projects and thus, it becomes a burden to most of the African countries. This study aimed to explore the causes of IFC-PS through the SGR Projects that escalate costs and how to address them. The Tanzania SGR Lot 1 Project that covered 205 km from Dar es Salaam to Morogoro was selected as a case study. The methods used for data collection involved literature review, focus group discussions and interviews. The results and findings show a gap between the IFC-PS and the National Laws and Regulations that escalates costs of the projects if funds from the IFIs were to be secured. To bridge the gap, it is recommended that the African countries should engage into negotiations with the IFIs to agree to waive IFC-PS conditions that escalate costs provided they are adequately covered in the national laws and regulations;engagement of locally established national and regional financial institutions;and the responsible government institutions in the African countries should sit together for assessment and review of the IFC-PS against the national laws and regulations.

气候风险与系统性风险传染——来自中国上市金融机构的经验证据

本文基于2011—2021年中国51家上市金融机构的微观数据,构建了金融机构间系统性风险传染网络,并从微观层面实证研究了气候风险对金融机构间系统性风险传染的影响及传导路径。研究发现,气候风险事件下金融机构间的网络关联度更紧密,彼此间的系统性风险传染水平显著提升。气候风险主要通过加大投资者恐慌情绪提升金融机构间的系统性风险传染水平。相较于大型金融机构,气候风险冲击下中小型金融机构的系统性风险输出与风险输入水平更高;经济政策不确定性的提高会进一步加剧气候风险对金融机构的负面冲击;《巴黎协定》的提出会缓解气候物理风险对金融机构间系统性风险传染的负面影响,但在一定程度上会加剧气候转型风险对金融机构间系统性风险传染的负面影响。本文为防范气候相关金融风险与维护金融体系的稳定提供了政策启示和决策参考。

中国油气管网运行关键技术及展望

管道是连接油气产业链上下游的关键纽带,是现代能源体系和现代综合交通体系的重要组成部分。在油气体制深化改革和“碳达峰、碳中和”战略目标下,油气管道正朝着大型化、网络化、多元化的方向发展,为大规模复杂管网的运行管理带来了新的机遇和挑战。基于我国油气管网发展现状,聚焦系统分析、仿真优化、运行监测和新型管道输送4个关键领域,剖析了油气管网运行相关研究的发展动态以及面临的难点,包括管网系统可靠性和韧性评估技术、管网运行仿真和调运优化技术、管道本体监测与修复技术以及氢气、甲醇、液氨、LNG管道输送技术等。针对“全国一张网”新阶段和“多能源互补”新动向,总结了数字孪生、智能调控、智能预警、多网融合等前瞻性技术攻关方向,旨在推动我国油气管网安全、高效、绿色转型。最后,提出展望:现阶段,需要立足我国能源资源禀赋,加快适应新形势下的管网运营模式,发挥油气管网在“全国一张网”发展新阶段下的能源大动脉作用;未来,需要稳步推进多元介质的管网灵活输送,挖掘油气管网在综合立体交通和综合能源系统中的发展潜力。

基于时频波动溢出网络的中国金融机构关联性

金融机构关联性是系统性风险的主要来源,厘清时频域下金融机构关联性特征有助于防范与化解系统性风险.本文基于30家A股上市金融机构在2011年~2020年期间的高频交易数据,构建时频波动溢出网络研究中国金融机构关联性.通过引入网络密度与全局效率两个系统层面指标和入度、出度与相对影响值三个机构层面指标,以测度时频域下静态与动态关联性.研究发现:中国金融机构间的关联性主要为20天~60天的中长期关联性;在极端事件期间,往往表现为长期关联性增强和短期关联性减弱;银行部门倾向于接收偏短期的波动关联性并发出偏短期波动关联性,而证券和保险部门倾向于接收偏长期的波动关联性并发出偏短期的波动关联性.

政策网络的性质与功能:介于市场与科层之间

从科层和市场的功能性类比和延伸讨论的角度对政策网络性质进行重新认识和思考,与从政策网络的各种要素属性的角度来理解网络的属性高度一致,理解一个事物性质的时候有很多维度。显然,和作为一种组织形态具有功能性或从行动者关系角度来定义政策网络的功能不同,从政策网络自身具有的理论和实践功能性研究拓展了讨论的空间。

移民网络、制度距离与中国企业OFDI效率

提高企业对外直接投资(OFDI)效率是中国推进高水平对外开放的重要路径之一。基于2003—2021年中国A股上市公司数据,实证分析了移民网络对中国企业OFDI效率的影响及其机制。研究发现,移民网络显著提升了中国企业OFDI效率,且通过降低交易成本、提高合同执行效率、弥合文化距离促进了企业OFDI效率提升。异质性分析结果表明,移民网络对中国企业OFDI效率的提升作用仅显著存在于非国有企业、绿地投资企业以及向非接壤国家直接投资的企业中,且在向发展中国家直接投资的企业中更显著。进一步研究发现,制度距离在移民网络与中国企业OFDI效率的关系中发挥了调节作用,制度距离缩小,会强化移民网络对企业OFDI效率的提升作用。因此,政府应加强移民网络建设,加大对OFDI企业的政策支持力度,缩小双边制度距离,企业则应充分利用移民网络降低OFDI风险及不确定性,进而促进中国企业提升OFDI效率。

武汉都市圈协同创新时空特征、影响因素及对策研究

将2014—2021年分为四个时间段,构建武汉都市圈协同创新网络及影响因素模型;基于社会网络分析方法,研究武汉都市圈协同创新网络时空特征;采用QAP回归分析,探讨创新主体、经济水平、技术邻近性、地理邻近性、研发机构对武汉都市圈协同创新的影响。研究表明:武汉都市圈城市间协同创新主要表现为以武汉为中心的星型结构,其协同创新网络可分为三个梯队;创新主体、经济水平、技术邻近、研发机构对武汉都市圈协同创新网络具有显著正向影响,地理邻近仅在早期表现出正向作用。

董事网络能促进企业数字化转型吗?——基于独立董事网络中心度的考查

本文基于镶嵌理论和声誉理论,以2007—2020年沪深A股上市公司为样本,研究独立董事所处网络中心度对所任职企业数字化转型的影响。研究发现,独立董事所处的网络中心度越高,企业数字化转型的程度越大,说明董事网络显著促进了企业数字化转型。经稳健性检验后,该结论仍然成立。机制检验表明,独立董事网络中心度通过降低代理成本、缓解融资约束推动企业数字化转型进程。进一步研究发现,对于制度环境较差地区的企业、信息透明度较高的企业以及民营企业,独立董事网络中心度对企业数字化转型的推动作用更显著。研究结论对于如何推动数字经济与实体企业深度融合,实现企业高质量发展有重要的参考价值。

高等职业院校网络财务报销模式探析

文章对高等职业院校的网络财务报销模式应用进行研究,主要目的是了解当前高职院校网络财务报销的实施情况,针对传统报销模式下“报销慢、报销难”的情况,根据院校情况提出切实可行的网络财务报销模式,以此提升高等职业院校财务报销工作效率,有效强化院校财务报销质量,进一步提升高等职业院校报销财务风险防范能力,有助于促进各项科研教学工作良性发展,为搭建现代化的高职院校网络财务报销模式提供有价值的参考借鉴。

基于VOSviewer的测评机构市场竞争特征分析模型的构建

网络安全等级保护在网络安全保障、网络强国建设方面发挥着至关重要的作用。随着资质管理从审核推荐模式向服务认证模式的转变,网络安全等级保护测评机构的资质管理得到网络安全界越来越多的关注。在分析网络安全等级保护测评机构投标项目信息的基础上,应用VOSviewer知识图谱软件构建一种市场竞争特征分析模型,为等级测评行业的高质量发展提供参考借鉴。首先对采集数据进行清洗以及基于相似度去重;然后采用机器学习算法对项目信息进行“关键词”(项目类型、项目所属行业)的抽取和标注;最后将项目信息进行RefWorks格式转换并导入VOSviewer,可视化呈现测评机构的竞争关系和市场特征。

自贸区制度创新网络联动的空间溢出效应——以长三角地区为例

以长三角的上海自贸区和浙江自贸区为例,采用2008—2019年包括其所在城市及周边47个地级市的面板数据,首先采用空间社会网络分析方法筛选处理组与控制组,然后分别构建政策综合视角下的异质性双重差分模型(Heterogeneous DID)和政策空间分割视角下的三重差分模型(DDD),深入考察评估“双自贸区之间的制度创新空间联动”对区域经济发展的溢出叠加效应。研究发现:不仅自贸区各自的制度创新对周边区域经济发展具有显著的异质性溢出效应,而且自贸区之间的“制度创新联动”更是对中间区域的经济发展具有时空两个维度上的序贯“溢出叠加效应”;而且,定量评估还表明,中间区域受到的这种“溢出叠加效应”要远大于单一自贸区对周边地区的单纯溢出效应。进一步的异质性分析更表明:自贸区对省会城市、内陆城市、地理临近城市和大型城市经济的溢出效应更加显著。

风险投资机构二元关系的演变及其退出效应研究

基于中国风投市场2004—2018年的投资事件数据和2004—2021年的退出数据,构建风险投资机构成对的数据集,研究风险投资二元关系演变的影响因素,进而探讨其对退出的影响。研究发现,风投机构间的匹配度、网络位置、历史联合投资行为对其二元关系产生显著的正面影响,而风投机构的间接合作伙伴会对此有显著的负面影响。进一步分析发现,风投机构匹配度越高、网络位置越中心、历史联合投资行为越多,其退出的可能性越小。研究结论对风险投资机构如何选择合作伙伴有一定的借鉴意义。