Compatibility and competition in airlines demand side network effects

Network effects arising in air transport markets are usually viewed as resulting from the implications of joint production on the cost side. In this paper, we focus on network effects originating on the demand side. We consider a network that links three cities involving two direct and one indirect connection. Two carriers, with asymmetric traffic rights on this network compete sequentially: at the first stage, they choose their departure times; at the second, they set prices. We show that in order to compensate its network disadvantage the ‘weak’ carrier chooses its departure time as close as possible to its competitor's. This is in contrast to the usual maximum differentiation principle. The network effect intensifies price competition. Depending on the size of the market and on consumers valuation of waiting time, various subgame perfect equilibrium configurations are exhibited.     

基于复杂网络理论的科技创新联盟运行机制研究

复杂网络理论已应用到许多领域,科技创新联盟也是为了现在更多企业、高校等诸多资源的科技创新合作而搭建的合作平台。利用复杂网络理论、加强科技创新联盟运行机制的研究,有利于优化科技创新联盟建设、推动科技创新人才培养、科技创新的发展和企业自主创新水平的提高。     

基于FA-SOM神经网络的农业技术水平省际差异研究

采用5大方面的13个指标,构建出区域农业技术水平综合评价体系,引入FA-SOM神经网络模型,对中国农业技术水平进行聚类分析。根据聚类的结果,把农业技术水平分为5个类型,并从总体特征、局域特征两个层面探讨了中国农业技术水平的空间格局及其内部差异。     

资本市场系统风险评估模型及其实证应用

本文在提出更全面和更具操作性的系统风险定义基础上,借鉴综合评价法及神经网络等方法,构建了一套适用于系统风险状态评估的模型体系。进而运用此模型对我国资本市场2001年第一季度至2009年第一季度的系统风险状态进行了实证研究,并在综合分析基础上指出我国资本市场建设若能得到持续、稳步推进,则2009年市场将有望维持在较低的系统风险状态。     

全球生产网络下产业发展中的政府角色——新加坡信息产业发展经验及对中国的借鉴

全球生产网络的存在使产业发展跨越国界,它以跨国公司为主体,给参与国家的工业化发展带来机遇。摆在当前各国政府面前的问题是,是利用市场力量推动全球网络下产业的发展,还是积极发挥政府在产业中的促进作用？文章回顾了有关政府介入经济发展的理论,并以新加坡信息产业为例,说明了发展中国家政府应在产业发展中起主导作用;在此基础上分析了对中国政府以及中国信息产业发展的借鉴。     

结合Landsat 8和GF 1数据的冬小麦种植空间分布提取

[目的]为探讨多源中等分辨率数据在冬小麦种植时空分布上的应用。[方法]利用2017年冬小麦关键生育期的Landsat8 OLI(抽穗期)和时间序列的GF-1 WFV(2016—2017生育期)数据,在分析各个行政分区的地表覆盖状况、作物结构和地块破碎度差别的基础上,将行政区划分为3种类型不同的提取单元并建立了适合于各自分区的提取模型:(1)利用关键生育期的OLI数据,采用监督分类—神经网络方法提取结构单一、地块齐整的怀远县种植区;(2)基于WFV数据构建五河县及城区种植区的冬小麦全生育期NDVI时间序列曲线,根据NDVI的时间特征构建冬小麦提取的决策树分类模型提取结构较复杂、混合像元明显的五河县及城区种植区;(3)在对关键生育期OLI-NDVI数据合理分割的基础上,采用最大似然的面向对象分类法获取种植密集、地块破碎的固镇县种植区。[结果]提取结果采用混淆矩阵和当年度统计数据相结合的方法进行精度评价,结果表明:(1)怀远县提取出的冬小麦提取总体精度为97.91%,五河县及城区提取出的精度为97.62%,固镇县的精度为97.42%;(2)全区域冬小麦提取的总体精度为86.82%,Kappa系数为0.84。与当年度统计数据对比的结果表明:2017年蚌埠市的准确提取面积精度可达97.91%,提取面积数据小于蚌埠市统计年鉴提供的统计数据,与调查的实际种植地块基本一致。[结论]采用不同方法提取不同空间分布特征的冬小麦种植面积具有较好的精度,该方法可以为市域冬小麦面积提取提供技术参考。     

Bagged neural networks for forecasting Polish (low) inflation

Accurate inflation forecasts lie at the heart of effective monetary policy. This paper utilizes a thick modelling approach in order to investigate the quality of the out-of-sample short-term headline inflation forecasts generated by a combination of bagged single hidden-layer feed-forward artificial neural networks. The model’s accuracy rises during the period of consistently falling and persistently low inflation in the emerging economy of Poland, and it statistically outperforms some of the popular benchmarks more frequently, especially at longer horizons. However, dispensing with data preprocessing and bootstrap aggregation compromises its forecasting ability severely. Combining linear and non-linear univariate and multivariate approaches with diverse underlying model assumptions delivers further gains in predictive accuracy and statistically outperforms a panel of benchmarks in a number of cases. While the vague interpretability of the model poses a considerable hurdle for policy makers, its inclusion in the forecasting toolbox should increase the accuracy of the ensemble of models, especially in periods of structural change.     

企业衍生效应对创新网络演化的作用机理研究

由创新网络和企业衍生概念入手，将衍生效应分解为知识溢出、集群创新文化和竞争关系3个维度，将集群创新网络分解为 “质”、“量”两个维度，以北京、大连、济南、天津高技术产业集群的衍生企业为对象，实证研究企业衍生效应对集群创新网络的影响。结果显示，企业衍生效应对集群创新网络演化存在正向促进作用。其中，知识溢出、集群创新文化与创新网络的“质”维度存在显著正相关关系，知识溢出、集群创新文化和适度竞争关系与创新网络的“量”维度存在显著正相关关系。     

Herding in Open-end Funds: Evidence from China

This paper aims to detect the herding of Chinese open-end fund managers and examine the role that structural features of their industry play in their herding. The herding behaviour is investigated by employing the cross-sectional absolute deviation (CSAD) model, drawing on the Chinese open-end fund market for the 2007–2020 period. Our findings suggest that the presence of herding has been confirmed in all other types of funds except for income funds, with their herding being mainly driven by non-fundamental factors. Most types of funds show more pronounced herding when the market is rising and the fund flow is positive. Up markets foster positive fund flows, which promote herding to a certain extent. The structural characteristics of fund networks of common asset holdings produce an impact on the fund herding. Herding is observed in the network with larger centrality index and the disassortative network. Moreover, we also find that herding in most types of funds is more pronounced under conditions of high volatility and high economic policy uncertainty, and the fund herding tends to grow inversely with fund-size.     

Green infrastructure planning: Unveiling meaningful spaces through Foursquare users’ preferences

The design of efficient Green Infrastructure —GI— systems is a key issue to achieve sustainable development city planning goals in the twenty-first century. This study’s main contribution is the identification of potential GI elements to better align the environmental, social and economic perspectives in the GI design by including information about the use, activities, preferences and presence of people. To achieve this, user generated content from Location Based Social Network —LBSN— Foursquare is used as a complementary data source. This involved the construction of an interdisciplinary correlation framework, between the Landscape Ecology principles and the GI elements, that included the classification of Foursquare data into grouping types. The classification considered the potential role of Foursquare venues in the GI network. Valencia City in Spain served as an illustrative case study to test the validity of the proposed method. The results suggest that Foursquare can provide a valuable insight on user perceptions of potential GI elements. Moreover, the findings indicate that user generated content from LBSNs like Foursquare can serve as a complementary tool for analysing the dynamics of urban outdoor spaces to assess GI network, thereby facilitating more effective urban planning and contributing to the social sustainability of the city.