Development and transformation of collaborative networks in events

This study examines the mechanisms by which and the reasons that leaders of non-profit organizations transform interorganizational collaborative networks through event attendance. Drawing from a two-wave survey, this study examines the interorganizational networks of 30 individuals who participated in both waves, along with the reported activities of 121 individuals who participated in the second wave of the survey. This mixed methods study found that events transformed participants’ weak ties into strong ties and promoted development of collaborative networks. Further, the study found that participants’ motivations for attending the event and following up with contacts afterward focused on sharing resources and deepening connections. Implications for understanding how events promote formation and transformation of collaborative networks are discussed.     

矿井通风三维可视化系统及优化

系统建立了三维仿真框架,建立了三维空间属性模型和非空间属性模型,分别对空间数据和非空间数据进行储存和管理。并建立了Hardy-Cross迭代模型和离散反馈型神经网络模型优化通风网络模型。并以C#语言来实现系统的功能。     

浅谈选煤厂建设投资估算影响因素及改进措施

本文对选煤厂建设工程投资估算中影响准确性的因素进行了分析,并结合BP神经网络理论基于Matlab软件对选煤厂带式输送机及栈桥单位工程进行了数值模拟,通过对比数值模拟结果与概算指标估算结果,详细阐述了可以提高选煤厂建设工程投资估算准确性的几点建议。     

Macro-Networks: An application to euro area financial accounts

This paper develops a financial network, designated the “Macro-Network”, that depicts the connections between the main financial and non-financial sectors of the economy in the various financial instruments of the euro area. The Macro-Network comprises of linkages across financial and non-financial sectors in each country. These country-level sector networks are then connected by the cross-border links between the individual banking sectors. Using the Macro-Network to simulate financial shocks, we find that the propagation effects depend on the underlying network structure, which evolves over time. After the financial crisis, bilateral linkages contracted sharply, reflecting the surge in counterparty risk and the de-leveraging processes. Nonetheless, our analysis suggests that even after this process, vulnerabilities remained in the euro area financial system, while a more diversified portfolio of cross-border exposures might mitigate the shock effects. We identify sectors which are most relevant for the propagation of financial shocks in the Macro-Network.     

Neighborhood quality and labor market outcomes: Evidence from quasi-random neighborhood assignment of immigrants

Settlement in a socially deprived neighborhood may hamper individual labor market outcomes because of lack of employed or highly skilled contacts. I investigate this hypothesis by exploiting a unique natural experiment that occurred between 1986 and 1998 when refugee immigrants to Denmark were assigned to municipalities quasi-randomly, which successfully addresses the methodological problem of endogenous neighborhood selection. I show that individuals sort into neighborhoods. Taking account of location sorting, living in a socially deprived neighborhood does not affect labor market outcomes of refugee men. Their labor market outcomes are also not affected by the overall employment rate and the overall average skill level in the neighborhood. However, an increase in the average skill level of non-Western immigrant men living in the neighborhood raises their employment probability, while an increase in the employment rate of co-national men living in the neighborhood raises their real annual earnings. This provides quasi-experimental evidence that residence-based job information networks are ethnically stratified.     

Systemic risk and dynamics of contagion: a duplex inter-bank network

This paper constructs a duplex banking network formed by credit relationships and information interaction via the banks’ balance sheet to model the structure of systemic risk and investigate the dynamic mechanism of contagion in terms of default and liquidity infection along with the factors that affect the extent of the contagion. We systematically explain the role that duplex banking networks play in different aspects of risk contagion. Through theoretical analysis and simulations, we conclude that asymmetric information interaction would increase the inflexibility of the system, which leads to liquidity shortage and possibly the collapse of the whole market. The weakness of systemic risk in the interior of the complex banking system can be characterized by the partial discount factor using illiquid assets in the information network. By improving the connectedness of the information network of the duplex networks, the spread of contagion can be partially slowed.     

模糊层次分析法优化BP神经网络的交通冲突预测模型

本文通过全面剖析影响交通冲突的原因,以交通流量、道路几何设计和道路环境三方面的因素建立指标层次结构体系。提出基于模糊层次分析(FAHP)法优化BP神经网络(BPNN)的预测模型,应用于交通冲突预测。     

The indirect effects of foreign direct investment on trade: A network perspective

The relationship between international trade and foreign direct investment (FDI) is one of the main features of globalisation. In this paper, we investigate the effects of FDI on trade from a network perspective, since FDI takes not only direct but also indirect channels from origin to destination countries because of firms’ incentive to reduce tax burden, to minimise coordination costs and to break barriers to market entry. We use a unique data set of international corporate control as a measure of stock FDI to construct a corporate control network (CCN), where the nodes are the countries and the edges are the corporate control relationships. Network measures, as the shortest path length and the communicability, are then computed on the CCN to capture the indirect channel of FDI. Empirically, we find that corporate control has a positive effect on trade both directly and indirectly. The result is robust with different specifications and estimation strategies. Hence, our paper provides strong empirical evidence of the indirect effects of FDI on trade. Moreover, we identify a number of interplaying factors such as regional trade agreements and the region of Asia. We also find that the indirect effects are more pronounced for the manufacturing sector than for primary sectors such as oil extraction and agriculture.     

基于PCA-BP-GA的BOT项目风险预测研究

由于BOT项目本身的长期性和复杂性,所以在BOT项目实施前需要准确科学的预测出所面临的风险大小。针对BOT项目风险影响因素众多的问题,先利用主成分分析法进行降维,然后利用遗传算法找出BP神经网络的最优全值阈值,建立了PCAGA-BP BOT项目风险预测模型。同时将以往的BOT项目数据作为学习样本,对BOT项目风险进行预测,并利用某地污水厂的例子进行验证,说明此模型对实际工程的科学指导性。