多重知识网络嵌入性对团队创新绩效的“双刃剑”效应——失败学习的中介作用

基于网络嵌入理论和经验学习理论，遵循“资源―行为―绩效”框架，从团队视角探讨多重知识网络嵌入性对创新绩效的影响机制。采用PROCESS宏程序和MEDCURVE宏程序分析技术，对多时点收集的277套创新型团队领导―成员配对数据进行分析，研究发现多重知识网络嵌入性转化为团队创新绩效的4条路径：①内部和外部知识网络嵌入性均对团队创新绩效存在倒U型影响；②利用式失败学习在内部知识网络嵌入性与团队创新绩效的正向关系中具有显著中介作用，在外部知识网络嵌入性与团队创新绩效的倒U型关系中具有显著中介作用；③探索式失败学习在两个维度的知识网络嵌入性与团队创新绩效的倒U型关系中具有显著中介作用；④两个维度的知识网络嵌入性顺次通过利用式失败学习、探索式失败学习对团队创新绩效发挥间接作用，利用式失败学习和探索式失败学习在其中起链式中介作用。     

国防产业联盟协同创新网络政府治理：基于语义挖掘技术的策略向度研究

国防产业联盟发展的关键在于科学管理协同创新网络。政策注意力聚焦点反映政府治理创新网络的策略向度，不同政府层级间的注意力分布结构差异表明该策略向度的偏向性。通过人工构建主题词袋，计算主题词TF-IDF权值及余弦相似度，对中央和地方共96份政策文件、1 926份新闻文章进行规模化语义分析，整体评估政府治理国防产业联盟协同创新网络的策略适应性，并测量其在实施与宣传过程中的偏向性。结果发现，网络拓展是首要策略选择，网络管理方式为引导而非参与，关系耦合度低，网络愿景策略运用有限。地方政府在实施过程中出现了策略偏异和策略调整；政策宣传更接近地方政府的策略向度。     

The impact of customer experience on consumer purchase intention in cross-border E-commerce——Taking network structural embeddedness as mediator variable

This study investigates the mediator effect of network structural embeddedness between customer experience and consumer purchase intention in the context of cross-border e-commerce. 321 copies of online questionnaires unfold cross-border online shopping experience. The structural equation model is built to analyze the mediator effect of network structural embeddedness. Network density, Network centrality separately plays a mediating role between website ease of use, website relationship service and consumer purchase intention. In contrast, both of them play a mediating role between customer cost and consumer purchase intention. The research suggests developing the relationship between consumers and e-commerce websites for cross-border e-commerce platforms from a network standpoint, but not only marketing.     

网络双重嵌入与大学生新创企业绩效：双元创业学习的中介与自我效能的调节作用

基于创业网络理论、创业学习理论和创业成长理论，构建创业网络双重嵌入、双元创业学习、自我效能以及大学生新创企业绩效内在逻辑关系模型。基于168份大学生新创企业样本数据，应用结构方程模型进行实证研究。结果表明，相比网络关系嵌入，网络结构嵌入对大学生新创企业绩效的正向影响更为显著；相比网络结构嵌入，网络关系嵌入对大学生创业学习的影响更为显著；大学生创业学习在网络结构和网络关系嵌入影响大学生新创企业绩效中均发挥部分中介作用，且对网络关系作用传导更明显；自我效能正向调节网络结构嵌入和关系嵌入对大学生新创企业绩效的影响。     

Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.     

双元联盟网络如何影响突破式创新——技术能力与网络惯例的调节作用

不同类型联盟网络涉及不同程度的知识共享和知识泄露风险，并有可能对突破式创新产生差异化影响。选取合肥、南京和苏州253个企业为样本，探究企业探索性联盟网络和开发性联盟网络分别对突破式创新的直接效应，以及技术能力和网络惯例等内外部情境变量对两种关系的调节效应。结果发现：探索性联盟网络对突破式创新具有倒U型效应；开发性联盟网络对突破式创新不具有曲线效应，仅是正向线性关系；内外部不同情境变量对探索性、开发性联盟网络具有不同调节效应。其中，技术能力仅对探索性联盟网络与突破式创新间关系具有显著正向调节作用；网络惯例对开发性联盟网络与突破式创新间关系具有显著正向调节作用。研究结论对组建企业联盟和推动企业技术创新发展具有一定指导意义。     

基于K-S检验与距离相关分析的网络借贷信用评价指标体系构建

网络借贷作为一种新型互联网金融模式,提升了金融资源使用效率,缓解了小企业融资难的困局。构建合理的网络借贷信用评价指标体系,从而对网络借贷的潜在风险及时甄别与预防,对互联网金融健康持续发展意义重大。本文根据K-S检验与距离相关分析相结合,筛选对借款客户违约状态甄别能力强的指标,建立了网络借贷信用评价指标体系,通过P2P网络借贷(peer to peer lending,个人对个人借贷)平台LendingClub交易数据进行实证研究,结果表明:不仅借款金额、借款利率等借款标的特征对借贷者违约具有显著相关性,借款者年龄等个人特征、借款者年收入等财务特征以及借款者违约次数等信用特征均对借贷者违约风险产生显著影响。投资者在出借资金时,往往青睐于已婚、年龄适中、具有一定工作经历、历史违约次数较少的借款人。因此,风险监管部门应构建网络借贷违约风险评估模型,对P2P平台进行风险监测,同时建立关键信息共享机制,融合多源数据,明确审查范围,实现P2P网络借贷行业健康有序发展。     

Systemic financial risk early warning of financial market in China using Attention-LSTM model

We propose an Attention-LSTM neural network model to study the systemic risk early warning of China. Based on text mining, the network public opinion index is constructed and used as a training set to be incorporated into the early warning model to test the early warning effect. The results show that: (i) the network public opinion is the non-linear Granger causality of systemic risk. (ii) The Attention-LSTM neural network has strong generalization ability. Early warning effects have been significantly improved. (iii) Compared with the BP neural network model, the SVR model and the ARIMA model, the LSTM neural network early warning model has a higher accuracy rate, and its average prediction accuracy for systemic risk indicators has been improved over short, medium and long terms. When the attention mechanism is included in the LSTM, the Attention-LSTM neural network model is even more accurate in all the cases.     

中国金融系统风险溢出效应研究——基于溢出指数和波动溢出网络

文章基于溢出指数和波动溢出网络方法，从静态和动态分别度量我国金融系统不同子市场间的风险联动水平及变动趋势。研究结果表明，我国金融系统风险溢出效应整体水平较高，各市场间联动性较强；市场内部滞后效应大于市场之间溢出效应，两两有向溢出效应具有强不对称性；作为我国金融系统的风险中心，货币市场始终处于风险溢出方，但在金融危机时期，其对外风险溢出效应相对减弱，而大宗商品市场、资本市场、房地产市场等其余市场的风险溢出效应相对增强。值得注意的是，当前我国金融系统整体风险溢出水平较高，市场间风险相关性较强，需要进一步加强系统性风险的监测与防范。     

Balancing risk with virtual private networking during a pandemic

When the pandemic struck and teaching went online worldwide, universities had to make pressing decisions that balanced cybersecurity against other factors, including health and safety, usability, and cost. One such challenge Indiana University (IU) faced was how to accommodate the secure telecommunications needs of 130,000 faculty, staff, and students who would now be teaching, learning, doing research, and working from home. Some universities reflexively promoted virtual private network (VPN) use for all activities. Such an approach would have been unsustainable at IU, however, owing both to the licenses and resources needed for the sheer number of users and to the high-throughput applications on which they rely. Perhaps even worse, it would have increased the chances that the VPN would be unavailable during a critical incident or other situation in which secure communications must be guaranteed. Instead, IU launched an awareness campaign demonstrating exactly when VPN use is and isn’t needed. In addition, network staff employed a VPN feature called split tunneling to reduce the load. This article discusses the advantages and disadvantages of this approach and how IU made the decision to balance both sides of the risk equation to ensure the continued advancement of its mission throughout the pandemic.