基于微博情绪信息的股票市场预测

行为金融理论的研究表明,股票投资者在进行投资决策时,容易受到自身的因素如情绪与心理因素的影响.以行为金融理论为依据,作出基本假设:微博情绪信息反映的社会整体情绪倾向能够影响并预测股票市场整体价格走势的变化.实证过程包括抓取新浪微博数据并进行预处理,生成情绪倾向时间序列,通过格兰杰因果关系检验上证指数时间序列与情绪倾向时间序列间的相关关系,建立支持向量机模型预测股票市场价格的变化采验证假设的正确性.实验结果显示加入微博情绪信息的预测模型能够获得更高的准确率,进而证明了本文所作假设的正确性.     

基于可变区间权重的中期用电量半参数预测模型

由于数据变化规律的多样性,中期电力负荷的波动有着不同于短期、长期负荷的特点。基于电力系统复杂性的研究视角,重点讨论了中期负荷预测过程中模型的不确定性、参数的时变特性以及负荷波动的周期性规律。根据中期负荷的数据特性,建立了基于非参数修匀的半参数模型,定义了函数区间的划分粒度以及模型权重的求解方法,提出了基于可变区间权重的动态预测方法,给出了基于经验模态分解和波动能量分析的噪声序列提取、检验方法。试验研究结果表明,气候因素对用电消耗的影响最大,经济因素次之;从选取的指标来看,不同时期的影响因素对于模型的解释能力是时变的;所提方法能够对电力负荷进行精确的多粒度、多维度分析,进而掌握其局部变化规律,可有效用于电力系统中期负荷预测。     

基于浙江工业企业微观数据的国有资本带动产业升级累计效应分析

使用面板门限模型,通过国有资本比重对绩效影响系数在门限值前后的变化,分析国资带动产业升级作用的累计效果.通过设置虚拟变量区分不同行业类别,考察国资在哪些类别行业中能够起到对于整体的带动(挤进)作用或者挤出作用.实证结果显示,国资比例提高到门限值对于浙江整体企业管理水平有显著正向作用.国资在精细化工和医药等产业中的比例提升对于浙江整体经济的绩效有相比其他行业更加显著的正向作用,而这些行业不是明显的垄断行业.由此得出结论:国资在重点行业中的示范带动作用应该强化,以期累计作用结合混合所有制推进从而达到挤进民资和促进民企产业升级.     

网络群体事件政府治理的演化博弈分析

利用演化博弈模型预测舆论的发展趋势,对政府应对网络群体事件采取的治理模式进行了研究.在一般化复制动态模型基础上建立网络群体事件舆论的传播方程,将地方政府部门与弱势群体的策略互动和行为演化融入到传染病传播模型中,用以模拟舆论的扩散和收敛过程.结果表明:在网络群体事件初期,如果弱势群体通过抗争获得政府补偿的概率不断增大,将造成事态的扩大.此时,地方政府应控制信息的交流程度与初始抗争人数,减缓舆论的扩散;在网络群体事件舆论大范围扩散阶段,上级政府介入并采取惩罚措施,及时披露信息,促使网络舆论的收敛平息,实现社会福利最大化.     

Assessing the Performance of a Classification‐Based Vulnerability Analysis Model

In this article, a classification model based on the majority rule sorting (MR‐Sort) method is employed to evaluate the vulnerability of safety‐critical systems with respect to malevolent intentional acts. The model is built on the basis of a (limited‐size) set of data representing (a priori known) vulnerability classification examples. The empirical construction of the classification model introduces a source of uncertainty into the vulnerability analysis process: a quantitative assessment of the performance of the classification model (in terms of accuracy and confidence in the assignments) is thus in order. Three different app oaches are here considered to this aim: (i) a model–retrieval‐based approach, (ii) the bootstrap method, and (iii) the leave‐one‐out cross‐validation technique. The analyses are presented with reference to an exemplificative case study involving the vulnerability assessment of nuclear power plants.     

Optimization of Cascade‐Resilient Electrical Infrastructures and its Validation by Power Flow Modeling

Large‐scale outages on real‐world critical infrastructures, although infrequent, are increasingly disastrous to our society. In this article, we are primarily concerned with power transmission networks and we consider the problem of allocation of generation to distributors by rewiring links under the objectives of maximizing network resilience to cascading failure and minimizing investment costs. The combinatorial multiobjective optimization is carried out by a nondominated sorting binary differential evolution (NSBDE) algorithm. For each generators–distributors connection pattern considered in the NSBDE search, a computationally cheap, topological model of failure cascading in a complex network (named the Motter‐Lai [ML] model) is used to simulate and quantify network resilience to cascading failures initiated by targeted attacks. The results on the 400 kV French power transmission network case study show that the proposed method allows us to identify optimal patterns of generators–distributors connection that improve cascading resilience at an acceptable cost. To verify the realistic character of the results obtained by the NSBDE with the embedded ML topological model, a more realistic but also more computationally expensive model of cascading failures is adopted, based on optimal power flow (namely, the ORNL‐Pserc‐Alaska) model). The consistent results between the two models provide impetus for the use of topological, complex network theory models for analysis and optimization of large infrastructures against cascading failure with the advantages of simplicity, scalability, and low computational cost.     

Transformational leadership and optimal functioning at work: On the mediating role of employees' perceived job characteristics and motivation

This study aimed to deepen our understanding of the motivational mechanisms involved in the relationship between transformational leadership (TFL) and employee functioning. Drawing on the TFL literature, the job demands–resources model and self-determination theory, we propose an integrative model that relates TFL to employee psychological health (burnout and psychological distress), attitudes (occupational commitment and turnover intention) and performance (professional efficacy, self-reported individual and objective organizational performance) through two explanatory mechanisms: perceived job characteristics (job demands and resources) and employee motivation (autonomous and controlled). This research was conducted in two occupational settings (nurses and school principals), using a distinct variable operationalization for each. Results of both studies provide support for the hypothesized model, suggesting that TFL relates to optimal job functioning (psychological health, job attitudes and performance) by contributing to favourable perceptions of job characteristics (more resources and less demands) and high-quality work motivation (more autonomous motivation and less controlled motivation) in employees. Theoretical contributions and managerial implications as well as directions for future research are presented.     

The Inherent Politics of Managing the Quality of Urban Green Spaces

Although the term ‘quality’ has a universal positive connotation and typically is framed by a focus on improvements, its application includes as well as excludes the access, values and world views of particular actors and interests. In this article, we highlight the relevance and implications of such ‘inherent politics’ through a case study of a widespread approach to operationalizing quality in urban green space management. We conclude that adoption of any quality model has both limiting and enabling implications for public participation and decision-making and that a critical stance is needed within both research and practice for the development of quality models that connect to values of broader societal relevance.     

考虑服务约束的第三方仓库收益与设计优化模型

第三方仓库作为服务提供商, 主要以期望收益最大化为目标, 但是必须满足一定的顾客服务标准。针对高需求环境, 考虑顾客服务水平约束, 提出了一个基于排队论的随机设计优化模型以使仓库的期望收益最大化。采用动态优化算法对模型求解, 选取实例进行了数值实验。结果显示, 模型的优化设计显著地提高了高需求环境下该第三方仓库的期望收益。在此基础上, 找到了服务约束的可行范围和有效范围, 为决策者制定服务标准提供了依据。     

存在主次委托人条件下的委托-代理问题:理论模型和实验研究

在传统委托-代理理论基础上, 根据主次委托人在委托-代理关系中的不同作用, 建立存在主次委托人条件下的委托-代理模型, 并利用实验数据对模型结果进行实验检验。研究结果表明, 当代理人为次委托人付出的努力水平对主委托人存在外部性时, 主委托人支付给代理人的最优激励性报酬和代理人为主委托人付出的最优努力水平都将高于单一委托人条件下的情况;当代理人为次委托人付出的努力水平对主委托人存在正(负)外部性时, 主委托人获得的预期收益将大于(小于)其在单一委托人条件下获得的预期收益;代理人在存在主次委托人条件下获得的预期总收益将高于其在单一委托人条件下获得的预期总收益。论文基于主次委托人在委托-代理关系中的不同地位拓展和深化了传统委托-代理理论。