Dynamical clustering of exchange rates

We use techniques from network science to study correlations in the foreign exchange (FX) market during the period 1991–2008. We consider an FX market network in which each node represents an exchange rate and each weighted edge represents a time-dependent correlation between the rates. To provide insights into the clustering of the exchange-rate time series, we investigate dynamic communities in the network. We show that there is a relationship between an exchange rate's functional role within the market and its position within its community and use a node-centric community analysis to track the temporal dynamics of such roles. This reveals which exchange rates dominate the market at particular times and also identifies exchange rates that experienced significant changes in market role. We also use the community dynamics to uncover major structural changes that occurred in the FX market. Our techniques are general and will be similarly useful for investigating correlations in other markets.     

Co-innovation in networks of resources — A case study in the Chinese exhibition industry

This work explores how network partners collaborate to innovate and innovate to collaborate and thereby achieve value. The innovation processes analyzed are within an IJV in the Chinese exhibition industry. The findings highlight that the IJV's development of a successful trade show resulted from effective co-innovation by partners which enabled the exploitation of opportunities in an industry characterized by rapid growth and continuing structural change. Partner co-innovation enabled evolving strategic and operational capabilities which has led to continued and growing market success. This co-innovation involved the targeted co-mingling of partner resources which creates value that motivated continued cooperation. The effectiveness of the partners' activities is evidenced by the growing size and prestige of their large-scale trade show as well as the expansion of the IJV into other endeavors. The paper concludes by considering the way these innovative processes can be applied in other contexts.     

Inter-firm learning and knowledge-sharing in multinational networks: An outsourced organization's perspective

This research provides insights into how learning and knowledge are exchanged multinationally between customer firms and their outsourced suppliers who provide non-core, yet essential, services. The paper seeks to understand: (1) how information is exchanged in these networks; (2) how cumulative knowledge adds value in these networks; and (3) how boundary-spanners assist in the dissemination of knowledge and learning within the network. Based on a pharmaceutical industry case, the results suggest that: (a) multinational firms operate more effectively and interact by sharing knowledge with outsourced firms which reflect the customers' structure and fit; (b) networked firms benefit from interactions through economies of scope, but knowledge is not necessarily shared equally among partners; (c) learning and knowledge-sharing interactions are tightly coupled at the product development stage; and (d) outsourced firms interact with external boundary-spanners as needed. The research provides insights for managers of multinational organizations and managers of firms from where essential services are outsourced.     

Communication channels,innovation tasks and NPD project outcomes in innovation-driven horizontal networks

Inter-organizational collaborations and horizontal networks are increasingly playing a pivotal role in innovations and new product development among firms. In this study, we investigate the link between the innovation task analyzability and the richness of communications channels used in network arrangements and the link between task analyzability and ties and project development time. We investigated the links based on the data collected from 372 respondents representing ninety three different innovation-driven horizontal networks. The results of structural equation modeling reveal a negative link from task analyzability to communication channel richness and a positive link from communication channel richness to ties. Communication channel richness was found to partially mediate the influence that task analyzability has on both NPD project outcomes of ties and development time. The implications of our results for theory and practice are discussed.     

Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks

We present a hierarchical architecture based on recurrent neural networks for predicting disaggregated inflation components of the Consumer Price Index (CPI). While the majority of existing research is focused on predicting headline inflation, many economic and financial institutions are interested in its partial disaggregated components. To this end, we developed the novel Hierarchical Recurrent Neural Network (HRNN) model, which utilizes information from higher levels in the CPI hierarchy to improve predictions at the more volatile lower levels. Based on a large dataset from the US CPI-U index, our evaluations indicate that the HRNN model significantly outperforms a vast array of well-known inflation prediction baselines. Our methodology and results provide additional forecasting measures and possibilities to policy and market makers on sectoral and component-specific price changes.     

创业团队成员信任对社会网络与企业创新能力关系的影响

本文通过对吉林省112家有效样本企业进行调查,将社会网络细分为内部社会网络和外部社会网络,在创业团队的定义下检验了社会网络与信任对新创企业创新能力的影响。研究结果表明,内外部社会网络都会对企业创新能力产生积极影响,而团队成员之间的信任则作为调节变量影响两者之间的关系。创业团队成员之间的信任越高,越有利于知识、信息的传播与交流,内部社会网络对企业创新能力的积极影响越大;但却易产生"非我发明症"现象,导致外部社会网络对企业创新能力的积极影响越小。     

预案分析的贝叶斯网络方法

在对预案进行评估分析和执行过程中常会涉及不确定性问题,传统的预案编制工具关键路径法(Critical Path Method,CPM)不具备处理不确定性问题的能力。本文推荐的贝叶斯网络法(Bayesian Networks)因其处理分析不确定性问题的能力已经被广泛应用于一系列的决策支持应用,但对预案评估分析的应用是新颖的。本文介绍了用贝叶斯网络法分析传统关键路径法编制的预案。     

知识网络中的社会资本及其作用

知识网络的绩效,在一定程度上取决于网络伙伴间社会资本与信任关系的形成。社会资本在知识网络中起着不可忽视的重要作用,其积极作用主要有:促进组织间交互学习;减少交易费用;促进风险分担;形成知识网络的竞争优势,进而增强网络成员的竞争优势;有利于解决知识网络中产生的"囚徒困境"等问题。而其消极作用主要有:易帮派化;易冒进;易产生锁定。     

The Governance of Networks and Economic Power: The Nature and Impact of Subcontracting Relationships

Abstract.  Current debate on networking focuses on network structures and firm strategies. In this perspective, theoretical analysis has been concerned with allocative issues. This essay proposes a different interpretation. Starting from the existing theoretical framework, we emphasise the nature and the implications of different types of networks with respect to socio‐economic development from a distributional point of view. Within this context, we develop the analysis of subcontracting starting from the concept of economic power. We then provide an analysis of governance in production by considering the attitudes and the nature of the actors involved. The externalisation of activities by large transnationals, which characterises current corporate restructuring, is often related to the search for greater flexibility, but also for greater power over governments, labour, and subcontractors. Differently, networks based on the mutual dependence of actors, which are not necessarily built around a large firm, could – under particular conditions – reach large production scales or more complex scopes without breaking the links with territorial systems, thus including local objectives in the strategic decision‐making process. Our conclusion is that the impact of subcontracting networks varies enormously. This is crucial to an understanding of future trends and possibilities. Not least, firms and public policy agencies need to understand the implications of different forms of subcontracting network and how those forms actually differ in practice.