Revenue forecasting, budget setting and risk

The budget-making process can be viewed as a problem of decision making under uncertainty since revenues are unknown at the time the budget is written. Revenue forecasts become information for describing the uncertainty in revenue receipts, thereby allowing the decision maker to trade off desire for a larger budget against the uncertainty in revenues. A chance constraint decision model is used to model this process. Application of the model to evaluate alternative forecasting techniques is then demonstrated for several revenue sources used in Kansas City, Missouri.     

Periodic learning about a hidden state variable

In active learning models the value function is necessarily convex in the priors. Hence, in combination with a concave objective, the decision problem need not become concave so that nonregularity problems are inherent. This paper considers an objective that unambiguously implies a quasi-convex decision problem and highlights the effect of the inherent nonregularities on active learning. A trigger policy for learning is shown to be optimal: the minimum amount of learning is optimal until uncertainty surpasses a critical value. At this trigger point the maximum amount of learning is chosen, uncertainty falls temporarily, and the cycle then repeats itself.     

混合TOPSIS方法在货位优化方案选择中的应用

货位优化方案的选择是自动化立体仓库中的重要决策。货位布局合理关系着整个库内作业的效率。根据货位布局应遵循的原则。建立了选择方案的指标体系。考虑到信息的不确定性．以区间数形式表示定性指标值,应用混合型TOPSIS方法建立了目标优选的模型。最后通过实例对方法的有效性和实用性进行了验证。     

供应链环境下库存的模糊多目标优化策略

由于供应链中产品订货提前期的不确定性以及决策者对目标偏好和产品价格的模糊性,本文讨论了多级供应链库存控制的多个不可公度的模糊多目标决策问题,采用模糊数来描述产品市场价格和目标权重的模糊性,并利用交互式多目标线形加权优化算法对模型进行了分析和求解,从而使企业和供应链在库存管理方面获得双赢。     

基于OWGA算子和CWGA算子的战时航材保障系统效能评价

战时条件下航材保障系统的影响因素众多,因此,对战时航材保障系统效能评价是一项极其复杂的系统工程。本文建立了战时航材保障系统的评判体系。针对系统评价过程中信息的不确定性,引进OWGA算子和CWGA算子,建立战时航材保障系统多属性群决策模型,从而对系统效能做出科学的评判。     

DECISION THEORY UNDER AMBIGUITY

Abstract We review recent advances in the field of decision making under uncertainty or ambiguity. We start with a presentation of the general approach to a decision problem under uncertainty, as well as the ‘standard’ Bayesian treatment and issues with this treatment. We present more general approaches (Choquet expected utility, maximin expected utility, smooth ambiguity and so forth) that have been developed in the literature under the name of models of ambiguity sensitive preferences. We draw a distinction between fully subjective models and models incorporating explicitly some information. We review definitions and characterizations of ambiguity aversion in these models. We mention the challenges posed by some of the models presented. We end with a review of part of the experimental literature and applications of these models to economic settings.     

From Hot Cakes to Cold Feet: A Contingent Perspective on the Relationship between Market Uncertainty and Status Homophily in the Formation of Alliances

In this study, we reconsider the classical positive association between the level of market uncertainty and an organization's propensity to form ties with organizations of similar status. Although prior research argues that the greater the uncertainty, the higher the level of status homophily, we suggest that this relationship is contingent upon framing that affects positive or negative valence towards uncertainty. In an up market, organizations tend to frame uncertainty as upside risk, and thus will subsequently favour explorative uncertainty‐mitigation devices; whereas, in a down market, organizations primarily frame uncertainty as downward risk, and thus will rely on more conservative uncertainty‐mitigation mechanisms. We therefore predict that a greater number of status‐heterophilous ties will be formed in an up market than in a down market. We discuss the implications of our results for status theory and more broadly for research on strategic decision making under uncertainty.     

再造成本不确定性对再造投资的效应分析

本文在一定假设条件下,对进行产品制造和再造混合生产的垄断制造商建立两期模型,研究再造成本的不确定性对制造商再造投资和最优决策的影响效应。研究表明,在某些条件下,再造成本不确定性对再造投资具有一定促进作用。制造商可以根据自身条件,适当选择再造投资,文章也为其再造投资决策提供了依据。     

Residential mobility and job changes under uncertainty

This paper empirically investigates households' residential mobility and job change decisions under uncertainty. We allow households' degree of risk aversion to be a confounding factor in the joint decision of residential mobility and job changes. Using panel data to estimate a random effects multinomial probit model of households' joint decision of residential and job mobility, our empirical results show that risk aversion discourages a household from making any changes. Moreover, when compared to single changes in either job or residential locations, risk aversion is more discouraging for joint changes to more central residential locations and less discouraging for joint changes to more distant residential locations. These effects are statistically significant, albeit small in magnitude. Our empirical results demonstrate the uncertainty does play a role in households' job and residential mobility decisions.     

Rechtszekerheid bij onzekerheid

Legal security under uncertainty
There are two sources of losses in decision making: collective judgment and uncertainty. The situation can be summarized as follows:
Minimization of losses can be achieved by using optimal decision rules. The effect of this method differs in the three cases treated. The analogies and differences of the three cases are discussed in this paper.
Lezing gehouden op de Statistische Dag 1969.     

Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

Due to mounting environmental and social challenges, supplier selection has become one of the most critical tasks of project-oriented organizations. Because supplier selection can affect the long-term success and profitability of the organizations and their projects, directly, embracing sustainability can add value in the equation. Considering sustainability measures can positively guide project managers in making better decisions for the projects in the long term. Therefore, the current study attempts to provide a conceptual model for selecting the best supplier based on a sustainability framework in megaprojects. Meanwhile, decision-making methods can be employed as a proper tool to find the best supplier. Ordinal priority approach (OPA) is a recent development in multiple criteria decision making (MCDM), while it has many benefits compared with other methods like analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). However, this method cannot consider multiple ranks during the decision-making process, and using an uncertainty approach feels strongly. Grey systems theory (GST) can consider uncertainties with no need for large sample or proposing membership function. Hence, the current study employed the GST to consider multiple ranks for criteria and alternatives in the OPA method. This is the first time that a sustainable supplier selection framework has been presented for megaprojects with the aid of the Grey OPA (OPA-G) method. Finally, a case study has been examined to evaluate the performance of the proposed approach. The results show that the proposed approach can be used in real-world situations and it has acceptable performance under uncertainty conditions.     

Quantifying uncertainty in applying importance-performance analysis

In a traditional importance-performance analysis (IPA), the information of uncertainty for importance and performance does not normally take into account from the survey but does commonly exist in practice. To further consider the uncertainty for each item from the survey results, the IPA under uncertainty method is proposed in this study. The traditional IPA possesses the ease of calculation and can be further viewed as a special case of the proposed IPA under uncertainty method, which is more complicated for computation but provides much more information for a decision maker to judge the strengths and weaknesses effectively by considering sampling, instrument effects, measurement conditions, sample effects, computational effects, random effects, etc. Finally, a brief case is illustrated to show how the proposed IPA under uncertainty method works and what the differences are between the traditional IPA and proposed methods.     

The assessment of the expected value of information in the binary decision model

The expected value of information represents the maximum amount the decision maker should spend on inquiry before making a decision. This amount depends upon the accuracy of the information. In many cases of inquiry, prior objective knowledge of the accuracy is not available. This paper presents and compares two methods of subjectively assessing the value of imperfect information in the binary decision model. In the first method, the decision maker provides a likelihood function for the inquiry and hence the probabilities of error. The second method is the preposterior approach, in which the decision maker provides the prior distribution for the posterior probability.     

Empirical labor search: A survey

This paper surveys the existing empirical research that uses search theory to empirically analyze labor supply questions in a structural framework, using data on individual labor market transitions and durations, wages, and individual characteristics. The starting points of the literature are the Mincerian earnings function, Heckman's classic selection model, and dynamic optimization theory. We develop a general framework for the labor market where the search for a job involves dynamic decision making under uncertainty. It can be specialized to be in agreement with most published research using labor search models. We discuss estimation, policy evaluation with the estimated model, equilibrium model versions, and the decomposition of wage variation into factors due to heterogeneity of various model determinants as well as search frictions themselves. We summarize the main empirical conclusions.     

基于区间型不确定多属性决策的地下储气库设计方案优选

地下储气库的设计方案涉及因素多,必须对方案从整体上进行综合评价,建立正确的决策模型,从而客观合理确定优选方案。结合地下储气库设计方案优选的多属性、不确定性和群决策等特征,运用层次分析法赋予指标权重,并构建了地下储气库设计方案优选的区间型不确定多属性决策模型。实例表明,该方法切实可行,操作简便,为地下储气库设计方案优选提供了新的思路。     

The Manager’s Notepad: Working Memory,Exploration, and Performance

This study builds upon March and Simon’s proposition that individual‐level differences must be considered when explaining decision‐making performance. We extend their discussion on the importance of decision‐makers’ attention to explain heterogeneous patterns of exploration and exploitation within the same uncertain environment. We develop a model of decision‐making under uncertainty in which ‘working memory’ – i.e., the ability to hold multiple elements in mind to actively process them – explains the emergence of heterogeneity in exploration‐exploitation choice patterns. We validated the model in a laboratory study and two replications involving 171 individuals. Our findings show that differences in working memory allow us to identify individuals who are more likely to choose exploration over exploitation appropriately, and thus achieve higher performance. We discuss the implications for management theories, and re‐propose the work of March and Simon as a unifying framework that still can be used to generate and test managerially relevant hypotheses.     

Quantum models for decision making and opinion dynamics the role of the Lie algebras

Quantum decision models provide a theoretical framework to study decision making and opinion dynamics. The role of Lie algebras is fundamental in these models to get the opinion dynamics without violating the uncertainty principle. A particular case is developed to show the potentiality of our method.     

Two-stage optimal control problems and optimality conditions

When an optimal investment decision is studied for a firm whose capital goods are subject to a delivery lag, a control problem with a time-delay argument in the objective function emerges. Such a problem under a set of simple assumptions is shown to be reducible to a two-stage optimal control problem. The significance of this is that familiar tools from standard optimal control theory are applicable to the resulting two-stage problem. Necessary conditions are presented for a general two-stage problem with an adjustable switching time. Some specific results are also obtained for several special cases.     

Decision analysis using targets instead of utility functions

A common precept of decision analysis under uncertainty is the choice of an action which maximizes the expected value of a utility function. Savage's (1954) axioms for subjective expected utility provide a normative foundation for this principle of choice. This paper shows that the same set of axioms implies that one should select an action which maximizes the probability of meeting an uncertain target. This suggests a new perspective and an alternate target-based language for decision analysis. We explore the implications and the advantages of this target-based approach for both individual and group decision-making.     

Bracing for demand shocks: An experimental investigation

We investigate inventory ordering decisions when decision makers anticipated a demand shock. Decision makers anticipating an event have been shown to brace for an uncertain negative outcome by overestimating the likelihood of that event. Decision makers faced with a spike in demand may incur increased holding costs because they may brace, exhibiting a judgment bias, and consequently a decision bias by over-ordering inventory. Three studies span conditions of uncertainty regarding the timing and magnitude of a demand shock: Employing three between-subjects experiments, Study 1 investigates behavior when decision makers were faced with uncertainty in timing and in magnitude of demand at the most elemental level, manipulating holding and stock out costs. The three experimental tasks feature uncertainty about the magnitude of demand (Experiment 1.1), uncertainty about the timing of demand (Experiment 1.2), and uncertainty about both the magnitude and timing of demand (Experiment 1.3). Study 2 uses a dynamic, multi-period replenishment task and a between-subjects manipulation regarding the uncertainty of timing and magnitude of a demand shock. Study 3 also employs a multi-period decision environment, but compares behavior under a demand shock condition with that in a condition featuring only random variability. The collective results from the three studies identify a bias toward over-ordering in response to a demand shock, relative to the optimal orders. The between-subjects manipulations in Study 2 points toward a possible remedy as we found that providing information concerning the timing and magnitude of a shock ameliorated the bias. The primary revelation was that decision makers had more difficulty dealing with uncertain timing than with uncertain magnitude of demand. One implication is that it is particularly critical for retailers to carefully plan and manage how they share information with upstream supply chain partners regarding when they plan to introduce store-level promotions.