Public Meetings and Risk Amplification: A Longitudinal Study

This article offers longitudinal data tracking people who did and did not attend a series of public meetings in an upstate New York rural community grappling with the expansion of an existing solid waste landfill and remediation of an adjacent inactive hazardous waste site. Before and after the public meetings, mailed questionnaires measured risk perceptions and perceived credibility of risk managers (here, the state government agencies and the responsible industry) conducting the meetings. Respondents at each measurement point included meeting attendees and nonattendees, with some fluctuation over time when attendees at one measurement point were nonattendees at the next and vice versa. The results from the first survey indicate that following the first two public meetings, attendees perceived greater risks from the waste sites than did nonattendees; attendees also perceived the risk managers as less credible. After the third public meeting, the results showed that attendees' risk perceptions remained steady; however, perceptions of government agency credibility significantly decreased. After the fourth public meeting, the survey found that attendees' risk perceptions were again not significantly different, whereas perceptions of government agency credibility increased significantly. The industry's credibility also increased, though only among attendees who had attended the most recent public meeting, not among attendees who had attended both the third and fourth public meetings. For nonattendees, risk perceptions and credibility ratings did not change. The discussion examines how distinctive characteristics of communication at each public meeting may have resulted in different effects and proposes hypotheses for future research.     

公共利益的概念建构评析 ——行政伦理学的视角

文章系统地梳理了美国行政学理论发展过程中的“公共利益”观念的变迁;批判了诸种功利主义和技治主义行政学理论对于“公共利益”的片面甚至错误的看法;主张将“公共利益”取向视为行政人必备的一种精神,一种职业信仰和终极向往。     

Optimization Model and Algorithm for Crew Management During Airline Irregular Operations

Airline irregular operations have long been a realm where human experience and judgement are the most important tools to utilize. Crew management during irregular operations is usually the bottleneck of the whole system-recovering process due to complicated crew schedules and restrictive crew legalities as well as the size and scope of the hub-and-spoke networks adopted by major carriers. A system-wide multi-commodity integer network flow model and a heuristic search algorithm for the above purpose are presented and discussed in this paper. The computational experiences show that the algorithm is efficient enough to solve problems of realistic size and also has the flexibility to accommodate practical business requirements.     

Analytical network process for software selection in product development: A case study

Application of software for manufacturing processes is one of the resolutions many enterprises have resorted to in the 21st century. This has been a result of increased complexity of products, globalization, rapid changes in technology and so on. The idea was that application of software especially for product development would increase the competitive advantage of industry nevertheless the irony has been that most of the investment in software has not achieved the expected results. We carry out a case study to introduce a methodology, the analytical network process as a multiattribute strategic decision making approach to help in the selection of appropriate software to suit the product development process of a particular product.     

产业集群参与者交互偏好与知识网络演化:模型与仿真

知识网络是产业集群网络演化的重要组成部分和先决条件,本文将产业集群中参与者进行交互的偏好分为任务导向型和知识导向型,建立了一个基于多智能主体的产业集群知识网络模型,利用Blanche软件实现了知识网络演化模型的仿真计算,通过仿真研究了任务导向型和知识导向型知识网络的对网络演化的不同影响.最后,本文提出了研究的局限性和下一步研究的方向.     

面向网络营销企业的营销信号选择博弈分析

如何通过营销信号来降低电子市场逆向选择风险是影响网络营销企业业绩的重要因素.本文以两家企业垄断市场为例,建立了企业信号传递博弈模型.通过对分离均衡与混同均衡存在条件的分析,讨论了信号传递成本以及不同消费者群体所占比例对企业营销信号决策的影响.分析结果有助于网络营销企业在电子市场中选择营销信号.     

基于两阶段优化算法的神经网络预测模型

采用基于两阶段优化算法(multi-stage optimization approach,MSOA)的GA人工神经网络,将训练集分为两部分,在前一训练集训练后获得的网络基础上使用后一训练集进行进一步的训练获得更为优化的网络结构.针对复杂系统建模输入节点难以确定的问题,提出将其与自组织数据挖掘算法相结合,利用GMDH算法获得神经网络的初始化节点,使用训练好的神经网络模型进行预测.将由此建立的预测模型应用于粮食价格的预测,并进一步探讨了MSOA算法的收敛性问题.结果表明基于GMDH和MSOA的神经网络组合预测模型能较大提高神经网络的全局收敛能力和收敛速度,提高预测精度.     

具有网络外部性的产品兼容性决策分析

通过Stachelberg竞争模型,本文研究了在具有网络外部性的市场中,拥有专有技术的主导厂商对其兼容技术的授权动机问题。并且得到了主导厂商在纵向兼容决策中最优厂商数量的控制的关系。     

不同模型在财务预警实证中的比较研究

研究当前国内外公司财务困境预测问题的现状,寻找一套适合于我国企业的财务状况识别指标体系;然后依据该指标体系采用不同方法建立财务状况预测模型;最后,利用样本公司实际指标数据对各个模型的短期及中期预测效果进行了比较分析与实证研究。     

Inverse Combinatorial Optimization: A Survey on Problems, Methods, and Results

Given a (combinatorial) optimization problem and a feasible solution to it, the corresponding inverse optimization problem is to find a minimal adjustment of the cost function such that the given solution becomes optimum.Several such problems have been studied in the last twelve years. After formalizing the notion of an inverse problem and its variants, we present various methods for solving them. Then we discuss the problems considered in the literature and the results that have been obtained. Finally, we formulate some open problems.