What happened to complex product systems literature over the last two decades: progresses so far and path ahead

Complex product systems (CoPS) industries largely contribute to industrial development, economic growth and creation of national wealth in both developed and developing economies. CoPS also show a number of specific characteristics as a distinctive category of industrial products in comparison with mass-produced consumer goods. These aspects have attracted the attention of scholars to study CoPS over the last two decades, resulting in a fairly extensive body of literature on the subject. However, there is a further need to connect research findings in this area, to illustrate a macro view of the development in the field, explore common themes, and identify possible paths into the future. This study aims to contribute to these ends by: (i) exploring the quantitative aspects of the CoPS literature; (ii) illustrating topical classification of CoPS studies and their findings; and (iii) suggesting opportunities for future research through examining common trends and unresolved issues in the literature.     

“双创”时代高校创客空间的复杂适应系统分析及优化策略

“大众创业、万众创新”时代,创客空间建设已成为高校扶持大学生创业的主流模式和重要举措。基于复杂适应系统（CAS）理论,阐释了高校创客空间的开放性、非线性、自组织性和涌现性等系统特征,指出高校创客空间的演进过程包括接触和交互两个阶段,在其演进过程中,标识机制和积木机制扮演着重要角色。最后,从CAS视角提出促进高校创客空间发展和系统优化的建议。     

全球产业集群发展关联网络模型研究

投入产出表数据都以矩阵形式给出,能够描述国家或地区间经济系统中各产品部门间经济技术关联紧密程度,通过直接或间接处理后可作为复杂网络的邻接矩阵,从而形成有向加权网络。依据投入产出表直接消耗系数矩阵,构建了全球产业强关联网络（GISRN）模型,然后,以特定的产品部门为核心产品部门,构建了全球产业集群发展关联网络（GICDN）模型,最后,采用紧密中心性网络特征值,研究了汽车制造业作为核心产品部门在经济系统中的作用及地位。     

多主体建模下四类创新文化特征对创新的影响

创新文化具有自组织性和开放性,是一个知识创造和利用的复杂适应系统。基于复杂适应系统视角,将创新文化特征分为冒险开拓、创新氛围、交流共享、决策参与4类,通过构建多主体（Agent）创新文化复杂系统模型,深入探讨了4类创新文化对创新的影响机制。仿真结果表明,4类创新文化特征对创新的影响存在差异。其中,冒险开拓、创新氛围、交流共享3类创新文化均对创新存在正向促进作用,而决策参与对创新的促进作用与其它3个创新文化特征具有显著关系,且冒险开拓与交流共享等因素在协同作用下比单一因素对创新的影响更积极、更显著。     

产业集群知识转移复杂系统反馈结构分析

产业集群内知识转移过程构成一个复杂的社会经济系统,在其转移过程中存在制约和促进系统发展的反馈结构。只有准确分析其系统结构才能有效把握系统行为,为管理对策的制定提供依据。利用系统动力学反馈动态复杂性分析理论与技术,建立了有效刻画产业集群内知识转移过程复杂系统的结构模型。利用基模分析技术分析了系统中的反馈关系,进行管理对策的生成研究,实现了以系统科学方法有效分析产业集群内知识转移过程的目的。     

集群内创业网络对创业资源的影响研究

根据Timmons创业过程模型,成功的创业活动需要将创业机会、创业团队和创业资源三者作适当搭配,在取得必要的资源和组成创业团队之后,才开始创业过程。新创企业的不确定性或弱势使其难以得到外部的支持,会面临突出的资源约束问题。集群内创业网络的构建,有助于新创企业在网络中获取创业资源,提高创业绩效。研究界定了集群内创业网络及其维度、创业资源及其类型,具体分析了集群内创业网络不同维度对创业资源获取的影响,建立了集群内创业网络对获取创业资源的影响模型。     

中国融入东亚生产网络的贸易利益——基于20个工业部门净附加值的分析

本文结合中国融入东亚生产网络的现状,采用反映进口中间产品在国内的产业循环效应或产业波及效果的净附加值指标来衡量中国融入东亚生产网络后归属于中国的直接的贸易利益。基于1992-2007年期间中国20个工业部门从东亚进口的中间产品在国内产业循环后所创造的净附加值分析表明:从净附加值的绝对量来看,中国工业部门从东亚进口中间产品所创造的净附加值增长迅猛,且在从世界进口的中间产品所创造的总的净附加值中平均占了42%左右的份额,但该净附加值占中国工业部门总出口的比重总体上不高且年均增长幅度有限。细分行业的考察发现,来自东亚的中间产品创造的净附加值比重较高的部门主要是技术、资本密集型工业部门,但在大多数工业部门中这一比重增长不显著。因此,应在进一步深化中国与东亚的垂直专业化分工的基础上,通过增强本土企业的技术吸收能力和自主创新能力来提升本土企业在东亚生产网络中的分工地位,以获取更多的贸易利益。     

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.     

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.     

区域人口复合生态系统生态位评价

人类社会是一类社会-经济-自然复合生态系统,它所提供给人们的或可被人们利用的各种生态因子和各种生态关系的总体集合可以定义为区域人口复合生态系统生态位.研究在借鉴可持续发展和宜居城市等评价方法的基础之上建立了一套区域人口复合生态系统生态位评价的指标体系及评价方法.并对全国31个省、自治区、直辖市的区域人口复合生态系统生态位做出了定量评价.