邻近性与创新合作：最新研究进展

自邻近性理论提出以来，邻近性在创新合作网络及其演化中的作用得到了很多学者的关注，相关研究丰富而庞杂。从邻近性因素对创新合作的影响、邻近性因素在创新合作中的相互作用以及创新合作对邻近性因素的影响等方面梳理了当前的研究进展，力图在邻近性因素与创新合作构成的复杂系统中厘清相互关系与动态作用机制。在此基础上，针对当前研究中尚未明晰和解决的问题，进一步提出了未来研究中有待持续深入的议题。     

Evolution of FDI flows in the global network: 2003–2012

As one type of international capital flow, FDI maintains its important role in globalization. This article attempts to investigate the evolution of the FDI flows from a network perspective. Based on the bilateral FDI flows data between countries from 2003 to 2012, we construct the global FDI flows network for each year and thus quantify network measures (such as flow volumes and connections); further by analysing the tendency and changes of these network measures during the past 10 years, we delineate the features and dynamics of the FDI flows in the global network. We have the following findings: (a) the flows network changes during and after the crisis, i.e. flow volume fallen down and recovered, and flow connection restructured with more diversity; (b) the global FDI flows network is getting more loosely connected; (c) individual countries vary in different patterns.     

Resource Dependence and Network Relations: A Test of Venture Capital Investment Termination in China

This study examines how venture capital (VC) firms terminate investments in an emerging economy context. We contend that due to the weak institutional environment, it is appropriate to draw on insights from power and social relation perspectives for a better understanding of the phenomenon. Specifically, we argue that a termination decision hinges on not only the dependence relationship between a VC firm and its portfolio companies, but also the social relationships among VC firms. Event history analyses of approximately 12,000 VC deals made in China between 2001 and 2012 reveal that when a VC firm has a greater number of investments in an industry, it is more likely to terminate investments on a portfolio company in that industry. Moreover, such effect on termination is moderated by the focal VC's embeddedness with its syndicate partners and collaboration opportunities with other VC firms outside the immediate access of the syndicate partners. Our study sheds light on research on VC decision making in emerging markets by integrating insights from resource dependence relationships and interorganizational network characteristics.     

A dynamic perspective: local interactions driving the spread of social networks

ABSTRACT

This study takes a micro standpoint to quantitatively verify the extent to which local interactions affect the expansion of dynamic social networks. By reviewing and synthesizing the theoretical literature in this article, we seek to establish a pragmatic analytical framework to capture the underlying functioning of local interactions. It then aims to produce findings on seven distinct marketing campaigns in which the real-world virtual communities offer intact time-series connections. In our considered cases, the firm-to-consumer interactivity plays a pivotal role in social media marketing while the customer-driven influence advances individual information transmission. The significant positive relationships demonstrate features of interactivity within subgroups including reciprocal edges and directed 3-cliques associated with the evolution of the virtual community by electronic word-of-mouth (WOM) of both firm-to-consumer and consumer-to-consumer interactions. More importantly, the attenuation of local interactions to a large extent leads to the cut-off point of the growth of the dynamic social network.     

Big data driven cycle time parallel prediction for production planning in wafer manufacturing

Cycle time forecasting (CTF) is one of the most crucial issues for production planning to keep high delivery reliability in semiconductor wafer fabrication systems (SWFS). This paper proposes a novel data-intensive cycle time (CT) prediction system with parallel computing to rapidly forecast the CT of wafer lots with large datasets. First, a density peak based radial basis function network (DP-RBFN) is designed to forecast the CT with the diverse and agglomerative CT data. Second, the network learning method based on a clustering technique is proposed to determine the density peak. Third, a parallel computing approach for network training is proposed in order to speed up the training process with large scaled CT data. Finally, an experiment with respect to SWFS is presented, which demonstrates that the proposed CTF system can not only speed up the training process of the model but also outperform the radial basis function network, the back-propagation-network and multivariate regression methodology based CTF methods in terms of the mean absolute deviation and standard deviation.     

社会资本视角下棚户区改造PPP项目风险分析

为了降低棚改PPP项目中的风险,提高社会资本参与棚改PPP项目的积极性,以社会资本方为研究视角。通过文献回顾和案例分析,总结社会资本参与棚改PPP项目面临的主要问题,筛选出社会资本参与棚改PPP项目面临的17个主要风险因素;运用DEMATEL法分析各风险因素的重要程度及相互影响关系,确定政府信用风险、相关法律法规不健全风险、市场收益不足风险、规划设计风险为关键风险因素;针对关键风险因素提出社会资本方防范措施,即多举措并举、细化合同条款、合理界定棚改PPP项目使用者付费范围、选择实力强的设计院是防范社会资本的有力措施。研究结果为分析棚改PPP项目风险提供了新思路,有助于提高社会资本参与棚改项目的积极性,所提对策对社会资本合理规避棚改PPP项目关键风险具有重要的借鉴意义。     

Race and the Production of Extreme Land Abandonment in the American Rust Belt

Extreme land abandonment is one of the most visible expressions of urban decline. Conventional theory emphasizes housing lifecycle processes, municipal fiscal challenges and deindustrialization to explain its prevalence. Empirically however, these factors are not strongly associated with the most extreme instances of land abandonment in the American Rust Belt. Race, by contrast, is strongly associated with these patterns, yet there is little mention of it in conventional theory. This article draws on group threat theory to explain how the construction of Blackness as a threat to white property, power and political influence, has propelled the production of extreme land abandonment. The constructed threat has translated into a sustained suppression of demand and capital for overwhelmingly black neighborhoods. These forces operate both independently and as an accelerant for other abandonment drivers.     

The problem of employees' network centrality and supervisors' error in performance appraisal: A multilevel theory

This article reveals an unexplored paradox for HR managers: the centrality of an employee in the social network benefits performance but hampers performance appraisal because it affects supervisors' rating errors. Central employees can be erroneously rated high on performance even when they are not high performers because supervisors tend to overappraise their performance. A distinction is made between rating precision, which depends on supervisors' uncertainty regarding employees' performance, and rating accuracy, which depends on supervisors' bias in favor of employees. Employee centrality is posited to be beneficial to precision but deleterious to accuracy because it regulates the diffusion of positive information, status, and power, all of which distort supervisors' capacity and motivation to accurately appraise performance. It is then argued that rating errors caused by network centrality affect aggregate perceptions of justice in organizations. When employees are highly connected to each other in a dense network, organizations have a strong and positive justice climate. Yet when some employees are more central than others in a centralized network, organizations have a negative and weak justice climate. The article contributes to the literature because it identifies an unexplored dark side of network centrality and offers recommendations for HR managers to cope with its deleterious consequences and for scholars to study them.     

The Urban–Rural Gap of Chinese Household Finance

Using data from a large household survey, we investigate the size of China’s urban–rural gap in ownership of bank deposits, risky financial assets, and credit cards. We further examine the factors underlying the gap using decomposition analysis. Compared to their urban counterparts, rural Chinese are much less likely to own a variety of financial products. Both demand-side barriers and supply-side barriers to financial inclusion exist in China. More, we use instrumental variable analysis to address the endogeneity of the local supply of financial service. Above all, our study indicates that a large financial services vacuum in rural areas needs to be filled.     

Trade networks and economic fluctuations in Asian countries

The paper presents a new methodology, based on tensor decomposition, to map dynamic trade networks and to assess its strength in forecasting economic fluctuations at different periods of time in Asia. Using the monthly merchandise import and export data across 33 Asian economies, together with the US, EU and UK, we detect the community structure of the evolving network and we identify clusters and central nodes inside each of them. Our findings show that data are well represented by two communities, in which People's Republic of China and Japan play the major role. We then analyze the synchronisation between GDP growth and trade. Furthermore we apply our model to the prediction of economic fluctuations. Our findings show that the model leads to an increase in predictive accuracy, as higher order interactions between countries are taken into account.