金融风险计量中人工神经网络的应用

通过简要介绍金融风险计量方法的演进,阐述人工神经网络作为新技术如何具体应用到金融风险计量中以及可行的遗传算法对人工神经网络的优化,论述了人工神经网络目前的应用现状,提出要运用其函数逼近、最优化处理功能于金融风险计量。     

互联网+背景下乌鲁木齐网约车的发展研究

网约车的出现使人们日常出行变得更加方便、快捷,但对传统的出租车行业产生了深远的影响。在“互联网+”背景下,如何使网约车在今后获得真正的可持续发展是当今社会普遍关注的热点之一。从网约车在我国的兴起与发展入手,以乌鲁木齐市为例,对乌鲁木齐市网约车发展过程中面临的主要问题,即自身网络平台、司机端、乘客端与传统出租行业的竞争以及相关监管部门等方面进行深入分析,并在完善平台系统、加强司机培训、引导市民认知、加快促进网约车和传统出租车融合发展及完善网约车服务运营管理五个方面提出合理性建议。     

团队跨边界活动对团队有效性的影响作用研究

通过文献综述,得出了团队跨边界活动对团队有效性有着倒U型的影响作用这一结论。同时,在团队学习理论和社会网络理论的基础上,对上述作用的内部机制进行研究探索,并从团队和个体两个层面分析相关的影响因素。最后,从企业管理实践的角度出发,基于研究结果提出几点思考和意见。     

A two‐step system for direct bank telemarketing outcome classification

A two‐step system is presented to improve prediction of telemarketing outcomes and to help the marketing management team effectively manage customer relationships in the banking industry. In the first step, several neural networks are trained with different categories of information to make initial predictions. In the second step, all initial predictions are combined by a single neural network to make a final prediction. Particle swarm optimization is employed to optimize the initial weights of each neural network in the ensemble system. Empirical results indicate that the two‐step system presented performs better than all its individual components. In addition, the two‐step system outperforms a baseline one where all categories of marketing information are used to train a single neural network. As a neural networks ensemble model, the proposed two‐step system is robust to noisy and nonlinear data, easy to interpret, suitable for large and heterogeneous marketing databases, fast and easy to implement.     

Data-mining,GIS and multicriteria analysis in a comprehensive method for bicycle network planning and design

In many Brazilian cities, the most common procedure for planning cycling networks is using aggregated population data in census tracts, which may not take into account the true origin and destination of trips. It may also not identify potential users of a particular mode of transport. This is particularly important considering that implementing cycling infrastructures should be based on the assumption that they are able to meet the users' needs. Therefore, the aim of this study is to develop and adopt an objective method to design and compare cycling networks based on data-mining of disaggregated origin-destination data, GIS resources, and multicriteria analysis techniques. The method follows three steps: 1) identifying potential users based on real user profiles, 2) designing proposed cycling networks and 3) a comparison between the networks proposed in this study and those developed by the municipality selected as a case study, considering real and potential users, as well as cost and benefit criteria. As a positive outcome, using disaggregated data allows for a reasonable estimate of the number of people served by the networks, a detailed analysis of their proximity to the infrastructure, as well as identifying potential users. Comparing cycling networks considering cost and benefit criteria shows that the chosen criteria were effective. It was also determined that the cycling network of the studied city poorly serves bicycle transport users, if compared to the proposed networks. These findings indicate that appropriate methods for planning cycling networks are still needed.     

Predictive spatial network analysis for high-resolution transport modeling,applied to cyclist flows,mode choice,and targeting investment

Betweenness is a measure long used in spatial network analysis (SpNA) to predict flows of pedestrians and vehicles, and more recently in public health research. We improve on this approach with a methodology for combining multiple betweenness computations using cross-validated ridge regression to create wide-scale, high-resolution transport models. This enables computationally efficient calibration of distance decay, agglomeration effects, and multiple trip purposes. Together with minimization of the Geoffrey E. Havers (GEH) statistic commonly used to evaluate transport models, this bridges a gap between SpNA and mainstream transport modeling practice. The methodology is demonstrated using models of bicycle transport, where the higher resolution of the SpNA models compared to mainstream (four-step) models is of particular use. Additional models are developed incorporating heterogeneous user preferences (cyclist aversion to motor traffic). Based on network shape and flow data alone the best model gives reasonable correlation against cyclist flows on individual links, weighted to optimize GEH (r² = 0.78, GEH = 1.9). As SpNA models use a single step rather than four, and can be based on flow data alone rather than demographics and surveys, the cost of calibration is lower, ensuring suitability for small-scale infrastructure projects as well as large-scale studies.     

复杂网络视角下中国新能源汽车产业的技术创新网络及其优化策略

基于复杂网络视角,构建了中国新能源汽车产业的技术创新网络模型,并运用社会网络分析方法分析其网络特征和网络中知识和信息的流动情况。结果显示:中国新能源汽车产业的技术创新网络具有复杂网络特征,整体网络密度较低,存在派系结构,网络中知识和信息的流动存在失真现象。最后,从合作广度、合作深度和合作效率三个方面提出该产业技术创新网络的优化策略。     

合作网络范式下集团财务资源配置：属性、系统框架与协作机制

随着企业集团由科层范式向网络范式转变,实现集团网络内的协同效应是提升集团财务资源配置效率、核心竞争力和实现集团目标的关键所在.首先,结合集团合作网络本质属性,在协同理论和企业资源理论基础上,对集团财务资源进行重新界定,将协同能力视为集团异质性整合资源;其次,将影响集团财务资源配置内部影响因素分为三个层面五个维度,论证集团战略与财务资源配置的互动关系;最后,构建集团财务配置的系统框架,并通过三个层面子系统的协作机制整合优化集团财务资源,以实现企业集团整体价值的提升.     

随机需求下横向并购供应链网络整合优化策略研究

本文从系统优化视角,针对增设集散中心的横向并购供应链网络整合策略,利用变分不等式建立了随机需求下的整合优化模型。以市场链为主线,以供应链网络均衡理论为基 础,构建了以横向并购供应链网络活动总成本最小为目标的数学模型,通过转换成变分不等式采用改进的欧拉算法进行模型求解。通过数值算例进一步说明了模型的适用性和灵活性,得出了增设集散中心的并购整合策略能够降低供应链网络的平均运营成本的结论,通过对比不同市场紧密程度下产生的供应链网络平均成本协同效应,发现随着市场紧密程度的增加其协同效应更明显,为横向并购供应链网络整合优化提供理论依据与方法。     

Cost and learning efficiency drivers in Australian schools: a two-stage network DEA approach

This article explore performance issues in Australian public schools, using a two-stage DEA network model, which accounts simultaneously for both cost and learning efficiency levels. In the cost efficiency stage, different types of expenses and investments are employed to support a given number of students, teachers and administrative staff. In the learning efficiency stage, these groups of individuals help to produce important outputs related to performance in student tests and school rankings. Results indicate that Australian public schools are heterogeneous. Policy implications are also discussed.