Inference in hybrid Bayesian networks using dynamic discretization

We consider approximate inference in hybrid Bayesian Networks (BNs) and present a new iterative algorithm that efficiently combines dynamic discretization with robust propagation algorithms on junction trees. Our approach offers a significant extension to Bayesian Network theory and practice by offering a flexible way of modeling continuous nodes in BNs conditioned on complex configurations of evidence and intermixed with discrete nodes as both parents and children of continuous nodes. Our algorithm is implemented in a commercial Bayesian Network software package, AgenaRisk, which allows model construction and testing to be carried out easily. The results from the empirical trials clearly show how our software can deal effectively with different type of hybrid models containing elements of expert judgment as well as statistical inference. In particular, we show how the rapid convergence of the algorithm towards zones of high probability density, make robust inference analysis possible even in situations where, due to the lack of information in both prior and data, robust sampling becomes unfeasible.     

Configuration of flexibility strategies under supply uncertainty

In this paper, we study a buyer׳s configuration of flexibility strategies under supply uncertainty. His main supplier׳s production process is uncertain, and he can either choose pricing flexibility (setting prices depending on the available supply) or operational flexibility (requesting a contingent order from a backup supplier). As the buyer may or may not find a suitable contingent supplier ex post, we study two scenarios that the backup supplier׳s supply is infinite, and that this supply is random. We also include the factor that the main supplier may determine the wholesale price. We demonstrate that the adoption of flexibility strategies is controlled by threshold policies in different scenarios whether the main supplier determines the wholesale price or not. We also investigate how the buyer׳s attribute (finding a suitable contingent supplier) affects the configuration of flexibility strategies.     

新兴产业政策决策过程中的不确定性管理研究——基于物联网产业的宏观政策决策过程的案例

采用纵贯研究、内容分析、深度访谈相结合的定性研究方法,以推动我国物联网产业发展的3个宏观政策决策过程为研究对象,旨在讨论政企互动是如何帮助政府进行不确定性管理的.研究结论表明:新兴产业的宏观政策决策是由数个存在递进关系的渐进式阶段组成,而每个渐进式事项的解决依赖于众多在政企互动中形成的微观政策工具的实施.政企互动帮助政策决策者通过4种机制(信息获取、行动协调、企业行动承诺和政府政策承诺)实现了对因信息缺乏以及对产业行动者资源依赖所造成的不确定性的管理.     

不确定条件下个性化产品提货时间损失规避行为模型

研究在不确定条件下,决策者风险规避行为对决策的影响,利用前景理论对决策者的风险规避行为进行建模,分析风险规避决策者的决策值与完全理性决策者的决策最优值的偏差。并以个性化产品销售企业最佳提货时间设置为例,通过建模和分析发现：当货物提前到达的边际损失大于延时到达的边际损失时,决策者越是进行风险规避,他设置的提货时间就越比风险中立者设置的最优提货时间小;当货物提前到达的边际损失和延时到达的边际损失相等时,不管决策者如何进行风险规避,他设置的提货时间都和风险中立者设置的最优提货时间相等;当货物提前到达的边际损失小于延时到达的边际损失时,决策者越是进行风险规避,他设置的提货时间就越比风险中立者设置的最优提货时间大。     

The price of risk with incomplete knowledge on the utility function*

When a risk is exchanged, the exact value for the minimum price (positive or negative) that the purchaser (investor, or insurer) is willing to pay is given by the certainty equivalent wealth level, which in turn depends on his specific utility function. When this utility function is unknown, then only a sufficient condition on the price can ever be found. This paper provides methods for calculating such a sufficient condition, when only limited information on the utility function is known.     

Insurer ambiguity and market failure

A series of studies investigate the decision processes of actuaries, underwriters, and reinsurers in setting premiums for ambiguous and uncertain risks. Survey data on prices reveal that all three types of these insurance decision makers are risk averse and ambiguity averse. In addition, groups appear to be influenced in their premium-setting decisions by specific reference points such as expected loss and the concern with insolvency. This behavior is consistent with a growing analytical and empirical literature in economics and decision processes that investigates the role that uncertainty plays on managerial choices. Improved risk-assessment procedures and government involvement in providing protection against catastrophic losses may induce insurers to reduce premiums and broaden available coverage.This article is part of a larger effort supported by the National Science Foundation on The Role of Insurance, Compensation, Regulation, and Protective Behavior in Decision Making about Risk and Misfortune. We greatly appreciate the many helpful comments and suggestions by our colleagues on the project: Jon Baron, Colin Camerer, Neil Doherty, Jack Hershey, Eric Johnson, and Paul Kleindorfer. Support from NSF Grant #SES8809299 is gratefully acknowledged.     

Decision problems under uncertainty based on entropy functionals

This essay intends to define the role of entropy, in particular, the role of the maximum entropy criterion with respect to decision analysis and information economics. By considering the average opportunity loss interpretation, the basic hypothesis for Shannon's derivation can be derived from properties of decision problems. Using the representation Bayes Boundary it is possible to show that selecting a single probability from a set by the Maximum Entropy Criterion corresponds to a minimax criterion for decision-making. Since problems of randomly accessing and storing information as well as communicating information can often be stated in terms of coding problems, this result might be used to develop strategies for minimizing retrieval time or communication costs.     

基于两阶段风险的定制类信息系统开发项目绩效模型构建与实证研究

开发阶段绩效风险和实施阶段绩效风险是信息系统开发项目中两个重要的中介变量,它们调节了项目内在不确定性和管理实践对项目绩效的影响.在项目不同阶段,绩效风险的主要影响因素是不同的.在开发阶段,主要影响因素是项目计划和控制、内部整合和用户参与;在实施阶段,主要影响因素是用户参与和高层支持.另外,用户参与直接地正向影响产品绩效,但对过程绩效没有直接影响.过程绩效对产品绩效也没有显著的正向影响.     

Robustness of Risk Maps and Survey Networks to Knowledge Gaps About a New Invasive Pest

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk‐ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.     

Parents' perceptions of their children in a context of shared political uncertainty

The study describes the differences and similarities between parents’ feelings and their perception of their children’s feelings in a politically uncertain situation. The study focuses on Israeli families living in Judaea and Samaria (the West Bank) during two periods: the Intifada and the post‐Oslo Agreements years during the first phase of the peace process with the Palestinians. The research combines qualitative and quantitative methods. The results show that most of the feelings evoked by the uncertainty are negative emotions, such as fear, anger, hate, the desire for revenge, and avoidance. These emotions are experienced by parents and, according to the parents’ perceptions, by their children as well. In addition to the correlation between parents’ own experiences and their appraisal of their children’s, the children were perceived as having more negative feelings than the parents. Systemic analysis of the results indicates that the children are often a channel for expression of their parents’ emotions. Based on this finding, suggestions are made regarding intervention with children that takes family processes into account. Some direction for applying the findings of this specific study in other contexts of shared political uncertainty, such as Northern Ireland, are suggested.