真我型领导与员工创造力:中介性调节机制

有关领导与创造力关系的研究更多关注领导效能的作用,很少探讨真我型领导通过何种机制对创造力产生影响.从自我决定理论视角构建真我型领导影响员工创造力的内在作用机制模型,并以两家民营企业集团中的532名员工及其89名主管为对象,借助中介性调节作用模型及相关技术,验证工作激情和权力距离在真我型领导与员工创造力关系中的中介和调节作用.研究结果表明:1)真我型领导对工作激情和员工创造力均有显著的正向影响;2)工作激情能完全中介真我型领导和员工创造力间关系;3)员工的权力距离感越高,真我型领导对工作激情的正向作用越强,对员工创造力的促进作用也更显著.     

基于非参数回归的遗漏变量检验

基于非参数回归提出了同时适用于横截面和时间序列数据的遗漏变量检验统计量.与现有文献相比,该统计量不仅避免了模型设定偏误问题,而且具有更高的局部检验功效,能够识别出速度更快的收敛到原假设的局部备择假设.该文选择单一带宽估计条件联合期望和条件边际期望,允许二者的非参数估计误差共同决定统计量的渐近分布,不仅改善了统计量的有限样本性质,而且避免了选择多个带宽和计算多个偏差项产生的繁杂工作.蒙特卡洛模拟结果表明该统计量具有良好的有限样本性质以及比Ait-Sahalia等更高的检验功效.实证分析采用该统计量捕获了F统计量无法识别的产出缺口与通胀之间关系,验证了非线性“产出一通胀”型菲利普斯曲线在中国的适用性.     

基于相似日聚类和贝叶斯神经网络的光伏发电功率预测研究

光伏发电功率的预测是光伏发电规划和运行的基础,因而受到越来越多的重视。文中提出了FCM相似日聚类与智能算法相结合的光伏阵列功率短期预测模型。该方法的思路是首先通过分析影响光伏阵列输出功率的主要因素,对历史数据与预测日气象环境进行模糊分类,并筛选出相似度高的子集作为样本,以提高预测样本的质量;然后通过神经网络映射出特征空间与光伏功率之间的复杂关系,并用贝叶斯理论对神经网络参数进行优化,提高网络的泛化能力。为检验该方法的有效性和精确性,将所提出方法与常用BP神经网络模型对同一仿真算例进行预测,预测结果表明本文提出的预测模型效果更佳。     

自动化立体仓库中的储位分配及存取路径优化

储位分配和存取作业路径优化是仓储管理中的两个重要决策问题。本文研究如何在自动化立体仓库中对这两个问题进行同时决策。提出了一个混合整数规划模型对该问题进行优化建模,设计开发了一个基于有向连接图的两阶段优化算法对问题求初始解,并利用禁忌搜索算法对所求得的解进行改进。算法第一阶段解决储位分配问题,在此基础上第二阶段利用Hungarian算法对堆垛机的存取作业路径优化问题进行求解。最后利用实例对算法效率和精度进行分析评价,计算结果验证了算法的有效性。     

Catch-up as a Survival Strategy in the Solar Power Industry

We evaluate the strategies of the emerging market firms in the context of nascent industries. We use the Indian solar power industry as the empirical setting, against the backdrop of the evolution of the global industry, While in traditional industries emerging market firms learn from advanced economy multinational enterprises (MNEs) and slowly upgrade their capabilities, in the intensely competitive environment of nascent innovative industries, emerging market firms are exposed to global competition in their home market right from the early years. This shortens their catch-up clock. As a result, their long-term survival depends on their ability to catch-up fast, both in output and innovation capabilities. In the solar power industry, we find that innovations stem, in the main, from advanced economy firms. Further, Chinese firms are beginning to move from cost-based imitation to innovation. In contrast, with a few key exceptions, most firms in the Indian solar industry remain locked within a narrow niche of downstream site-based installation. Their operations are opportunistic, short term, and without specific catch-up goals, a scenario that does not bode well for the industry's future in India.     

盛名难副: 明星 CEO 与负面信息隐藏

以 2009 年 ～ 2016 年间 A 股上市公司为研究样本,采用双重差分法研究明星 CEO 成名后负面信息的披露策略． 以 CEO 是否登上媒体发布的榜单作为明星 CEO 的代理变量,研究结果表明: 明星 CEO 上榜将显著增加隐藏负面信息的可能性,验证了“名声俘获假说”; 明星CEO上榜后发生财务重述的概率显著增加,而一旦退出榜单其隐藏负面信息的可能性则显著降低,验证了名声的负面效应． 机制检验表明明星 CEO 通过管理层权力抑制负面信息披露． 另 外,上榜前盈余质量较低、代理问题较严重的公司,其明星 CEO 隐藏负面信息的可能性更高．文章丰富了 CEO 个人特质对信息披露行为的影响及其经济后果的研究,对于资本市场的健康发展具有一定的启示意义．     

Feminist power and its implications on Uganda’s malaria communication campaign

This paper examines power and its manifestation in Uganda’s “Stop Malaria Campaign.” It specifically questions the apparent radical feminism, which is conceptualized as a quest for power, and how such excesses drive implementation of the campaign. The paper explains data collected through focus group discussions and key informant interviews using feminist communication theory as informed by the critical ideas of feminism and power. These three ideas help to put into perspective: domination of the campaign by one gender, interpretation of the campaign’s objectives to suit that one gender, and communication methods used in the campaign. Analysis of the above three processes shows that men are the weaker gender in the malaria prevention drive, an idea that has clashed with the existing male chauvinism on which several families still thrive in Africa. A view that radical feminism should be seen as an organized form of power that needs to be checked if Uganda’s malaria communication campaign is to be implemented successfully is herein proposed, along with some solutions to the challenges.     

Spatial Risk Analysis of Power Systems Resilience During Extreme Events

The increased frequency of extreme events in recent years highlights the emerging need for the development of methods that could contribute to the mitigation of the impact of such events on critical infrastructures, as well as boost their resilience against them. This article proposes an online spatial risk analysis capable of providing an indication of the evolving risk of power systems regions subject to extreme events. A Severity Risk Index (SRI) with the support of real‐time monitoring assesses the impact of the extreme events on the power system resilience, with application to the effect of windstorms on transmission networks. The index considers the spatial and temporal evolution of the extreme event, system operating conditions, and the degraded system performance during the event. SRI is based on probabilistic risk by condensing the probability and impact of possible failure scenarios while the event is spatially moving across a power system. Due to the large number of possible failures during an extreme event, a scenario generation and reduction algorithm is applied in order to reduce the computation time. SRI provides the operator with a probabilistic assessment that could lead to effective resilience‐based decisions for risk mitigation. The IEEE 24‐bus Reliability Test System has been used to demonstrate the effectiveness of the proposed online risk analysis, which was embedded in a sequential Monte Carlo simulation for capturing the spatiotemporal effects of extreme events and evaluating the effectiveness of the proposed method.     

Agent‐Based Recovery Model for Seismic Resilience Evaluation of Electrified Communities

In this article, an agent‐based framework to quantify the seismic resilience of an electric power supply system (EPSS) and the community it serves is presented. Within the framework, the loss and restoration of the EPSS power generation and delivery capacity and of the power demand from the served community are used to assess the electric power deficit during the damage absorption and recovery processes. Damage to the components of the EPSS and of the community‐built environment is evaluated using the seismic fragility functions. The restoration of the community electric power demand is evaluated using the seismic recovery functions. However, the postearthquake EPSS recovery process is modeled using an agent‐based model with two agents, the EPSS Operator and the Community Administrator. The resilience of the EPSS–community system is quantified using direct, EPSS‐related, societal, and community‐related indicators. Parametric studies are carried out to quantify the influence of different seismic hazard scenarios, agent characteristics, and power dispatch strategies on the EPSS–community seismic resilience. The use of the agent‐based modeling framework enabled a rational formulation of the postearthquake recovery phase and highlighted the interaction between the EPSS and the community in the recovery process not quantified in resilience models developed to date. Furthermore, it shows that the resilience of different community sectors can be enhanced by different power dispatch strategies. The proposed agent‐based EPSS–community system resilience quantification framework can be used to develop better community and infrastructure system risk governance policies.     

Bad News Has Wings: Dread Risk Mediates Social Amplification in Risk Communication

Social diffusion of information amplifies risk through processes of birth, death, and distortion of message content. Dread risk—involving uncontrollable, fatal, involuntary, and catastrophic outcomes (e.g., terrorist attacks and nuclear accidents)—may be particularly susceptible to amplification because of the psychological biases inherent in dread risk avoidance. To test this, initially balanced information about high or low dread topics was given to a set of individuals who then communicated this information through diffusion chains, each person passing a message to the next. A subset of these chains were also reexposed to the original information. We measured prior knowledge, perceived risk before and after transmission, and, at each link, number of positive and negative statements. Results showed that the more a message was transmitted the more negative statements it contained. This was highest for the high dread topic. Increased perceived risk and production of negative messages was closely related to the amount of negative information that was received, with domain knowledge mitigating this effect. Reexposure to the initial information was ineffectual in reducing bias, demonstrating the enhanced danger of socially transmitted information.