Assessment of Catastrophic Risk Using Bayesian Network Constructed from Domain Knowledge and Spatial Data

Prediction of natural disasters and their consequences is difficult due to the uncertainties and complexity of multiple related factors. This article explores the use of domain knowledge and spatial data to construct a Bayesian network (BN) that facilitates the integration of multiple factors and quantification of uncertainties within a consistent system for assessment of catastrophic risk. A BN is chosen due to its advantages such as merging multiple source data and domain knowledge in a consistent system, learning from the data set, inference with missing data, and support of decision making. A key advantage of our methodology is the combination of domain knowledge and learning from the data to construct a robust network. To improve the assessment, we employ spatial data analysis and data mining to extend the training data set, select risk factors, and fine‐tune the network. Another major advantage of our methodology is the integration of an optimal discretizer, informative feature selector, learners, search strategies for local topologies, and Bayesian model averaging. These techniques all contribute to a robust prediction of risk probability of natural disasters. In the flood disaster's study, our methodology achieved a better probability of detection of high risk, a better precision, and a better ROC area compared with other methods, using both cross‐validation and prediction of catastrophic risk based on historic data. Our results suggest that BN is a good alternative for risk assessment and as a decision tool in the management of catastrophic risk.     

Decision support system for the batching problems of steelmaking and continuous-casting production

This paper investigates two batching problems for steelmaking and continuous-casting (SCC) production in an integrated iron and steel enterprise. The tasks of the problems are to make the decisions as how to consolidate ordered slabs into charges, and then how to group charges into casts. The effective decisions on these batching problems can help to balance the requirements of materials in downstream production lines, improve the customer satisfaction levels, and reduce production costs (including reduction of open ordered slabs, less slabs quality upgrading, reduction of steel-grade changeovers, and reduction of inefficient utilization of tundishes lives). We first formulate the problems as integer-programming models by consider practical constraints and requirements, and then develop the two heuristic algorithms for the corresponding batching problems. By embedding above models and algorithms, we develop decision support system (DSS) software with interactive planning editor. The DSS has been tested by using practical data set collected from the steelmaking plant in Baosteel which is one of the most advanced iron and steel enterprises in China. Computational experiments demonstrate that the models and algorithms developed can generate the satisfactory solutions when they work together with the planning editor in the DSS.     

Analysis of postponement strategy by EPQ-based models with planned backorders

This paper develops economic production quantity (EPQ)-based models with planned backorders to evaluate the impact of the postponement strategy on a manufacturer in a supply chain. We derive the optimal total average costs per unit time for producing and keeping n end-products in a postponement system and a non-postponement system, respectively. By comparing the optimal total average costs of the two systems, we evaluate the impact of postponement on the manufacturer under four circumstances. Our results show that postponement strategy can give a lower total average cost under certain circumstances. We also find that the key factors in postponement decisions are the variance of the machine utilization rates and the variance of the backorder costs.     

服务业国际转移的模式选择及对策分析

本世纪初,以服务业转移为标志的新一轮全球产业转移浪潮正逐步兴起,服务业外包和服务业FDI是服务业国际转移中最重要的两种模式.通过建立发达国家服务业国际转移模式的选择模型,分析比较了发达国家在服务业国际转移过程中面临的外包模式、FDI模式和本国生产模式的成本差异,并且根据最小成本原则,确定了发达国家在不同情况下国际转移模式的不同选择.同时,分析了服务业外包和服务业FDI之间的替代关系和互补关系,据此提出承接国相应的承接对策.     

云南边疆少数民族间的"康吧"经济交往模式:理论与实证分析

"康吧"交往是纳西族与傈僳族、藏族之间一种独特而历史悠久的物质交换模式,它不符合理性选择的逻辑却能世代延续至今,同时,不同民族间的"康吧"交往又存在差异。本文借鉴西方主流理论对这种古老的交往模式进行分析,从经济学、社会学、人类学的多重理论角度出发,采用访谈、观察与定量分析相结合的研究方法,对上述现象进行了分析。研究结果表明:(1)资源依赖性、信任和互惠原则对"康吧"交往的延续至关重要;(2)货币市场和投机行为的出现导致"康吧"交往走向衰落,但情感互惠和资源互补使之至今存在;(3)自然资源条件、资源互补程度、社会历史背景和文化因素,对交往模式的差异都有重要影响作用。     

实验市场中的股权结构、信息与控制权收益

实验室环境下的决策过程研究可以较好地考察决策变量的行为基础和动态临界值.本文以中国股市中的股权结构为背景,在实验框架下考察了股权结构、信息披露和控制权收益的关系.文章先从理论上计算股东的夏普利值并以此代表股东控制权.再分不同设置变量来实验地考察控制权收益.结果表明:(1)股东控制权越平均,控制权收益越少;大股东与小股东形成"核"联盟的机会越多,其取得控制权的机会越少.(2)信息对控制权收益的影响主要体现在信息在联盟的形成和维持中的作用.(3)大股东夏普利值的高低和信息情况决定了联盟的方式.(4)控制权溢价并不一定就是控制权收益,也许只是大股东为防止自身利益被侵害而支付的成本.(5)信息不完全不一定是坏事,部分信息的隐含更能增加公司的分配效率.     

管理者过度自信与企业投资行为异化——来自我国证券市场的经验证据

本文以非金融类A股上市公司为研究样本,考察了管理者过度自信与企业投资行为的关系。研究发现,过度自信的管理者倾向于过度投资,并对融资活动产生的现金流有更高的敏感性。即当公司有充裕的融资活动现金流时,过度自信的管理者会过度投资;反之,则投资不足。本文还发现,过度投资与经营活动产生的自由现金流之间的敏感性基本上不受管理者过度自信心理特征的影响,这与其它一些研究的结论不一致。     

顾客参与一定会导致顾客满意吗——顾客自律倾向及参与方式的一致性对满意度的影响

在产品或服务的生产过程中,顾客参与行为越来越普遍。营销文献主要集中在顾客参与带来的经济影响上,对顾客参与方式、顾客心理特质基本没有涉及。本文在已有文献的基础上,通过模拟情景实验法探讨顾客参与对顾客满意的影响。研究表明,顾客参与本身并不是顾客满意的直接刺激因素,感知参与方式的一致性、自身的自律倾向和不同的服务结果都会对满意度产生不同程度的影响。     

信任、关系、控制与研发联盟绩效——基于中国制药产业的研究

本文以我国制药产业研究开发联盟为研究对象,研究了关系治理(包括信息共享、持续性预期、关系深化)、过程控制、信任对联盟绩效的影响。研究发现,持续性预期、信息共享有助于增进信任,进而提高联盟绩效;技术的不确定性越高,信任对联盟绩效的促进作用越显著;但过程控制则会降低信任与联盟绩效的正相关。     

基于IDT/TTF整合模型的企业移动服务采纳实证研究

本文基于创新扩散理论(Innovation Diffusion Theory)和技术任务匹配理论(Task-technology Fit)提出了一个分析企业对于移动服务采纳行为的综合模型。通过中国四大电信公司的客户服务部门从80个不同行业的企业收集调查数据,利用SPSS统计软件对模型量表进行了信度效度分析,并采用Graph3.0分析软件对研究模型的假设进行了检验。研究结果表明,该模型对理解、预测和解释企业对于移动服务采纳行为具有一定的实际意义。