SOME MONEY GAMES

The authors consider three games which come directly to grips with important ideas in finance, are complex enough to be interesting, yet sufficiently simple to be explained and played in less than one class period. Their purpose is to help students become more involved in the art of economic model building and to impart a better understanding of the demand for money. It seems likely that these games can be used to test specific hypotheses about the learning process and human decision making under conditions of uncertainty.     

A DYNAMIC PROGRAMMING MODEL FOR OPTIMAL ALLOCATION OF DECISION TIME

Recurrent decision making by a lower-level manager can be viewed as a sequential decision process in which time and uncertainty are limiting factors. Under these conditions, the manager must determine how to best utilize his decision making time consistent with his own particular set of decision values. A dynamic programming model was devised to determine the optimal (consistent) allocation of decision time among five different types of problems for a sequence of simulated recurrent decision situations. Fifty-one lower-level managers were interviewed about their use of decision time and decision procedures. The model was validated by comparing model assumptions and results with the findings from the interviews. The model was used to determine the effects of variations in the levels of time available and uncertainty upon the optimal allocation of decision time.     

ON THE SELECTION OF CRITICAL VALUES IN SEQUENTIAL DECISION PROBLEMS

This paper explores the effect which the choice of critical values in sequential decisions has on the overall distribution of payoffs. It demonstrates in the context of a simple two-stage sequential decision model that the mean and variance of the overall distribution can be highly sensitive to the choice of critical values. Finally, it considers the problem of selecting optimal critical values when a standard meanvariance approach is used.     

Entscheidungsverhalten von Kunden in Mass Customization-Systemen

Sequential choice processes are ubiquitous in consumer decision making. In each attribute decision, consumers are often faced with different numbers of options which they must trade off in order to make the best possible choice. Thereby, complicated high variety choices at the beginning of a choice process produce a larger trade-off conflict and, thus, initially a greater mental depletion than more simple low variety choices. We examine the strength of mental depletion in sequential choices on individuals’ perceived attractiveness of the firm’s recommended default option at a target choice. We show that consumers who are confronted with difficult high variety choices early in the decision sequence followed by low variety choices initially deplete more than consumers who encounter exactly the same attribute decisions in reverse. As a result, depleted consumers are more likely to fall prey to the recommended default or some perceptually focal options close to the default anchor at target choice succeeding a sequence of decisions.     

internet网上旱地农业土壤灌溉和需水管理决策支持系统

本文通过对因特网旱地农业土壤灌溉和需水管理决策支持的设计和分析的介绍,较具体地阐明了internet技术在旱地农业土壤灌溉研究的应用,讲述了系统所提供的各种功能,深入浅出地阐明了该系统提供的决策分析模型。说明该系统是旱地水资源可持续利用的重要辅助决策工具。     

基于犹豫直觉模糊语言集均值-标准差偏好距离的多属性决策研究

在犹豫直觉模糊语言集和语言尺度函数的基础上定义了均值-标准差偏好的Hamming距离，并提出了基于犹豫直觉模糊语言集距离TOPSIS和TODIM的多属性决策方法，进一步利用这两种方法对实例问题建筑商的招标方案进行排序，并讨论了偏好参数对排序结果的灵敏度分析。为验证上述方法的有效性，与已有方法对同一实例的排序结果进行了比较分析。     

基于三维密度算子的群体DEMATEL指标权重确定方法

针对现有DEMATEL指标权重确定方法大多基于个体决策,且未考虑群体决策评价标度不一致的情况,提出一种新的基于三维密度算子的群体DEMATEL指标权重确定方法。首先,定义了不同评价标度的转换函数,以此将群体DEMATEL矩阵进行一致化处理;其次,给出一种群体DEMATEL矩阵的聚类方法,在此基础上利用三维密度算子对其进行集结;最后,依据DEMATEL方法识别出指标的中心度和原因度,并计算各指标的权重。文末通过一个应用实例验证了所提方法的可行性与有效性。实例结果表明,该方法由于能够较好解决群体决策评价标度不一致的问题,还能够充分考虑群体决策的共识度,因此可使指标权重结果更为客观合理且更为可靠。     

时序多属性决策的广义等级偏好优序法

实际中很多复杂的多属性决策问题往往需要考虑多个时间序列的决策信息,针对这类时序多属性决策问题,本文在优序法的基础上,定义了广义优序数的概念。同时提出基于理想时间权向量的方法来解决时序多属性决策中时间权重的确定问题,进而在此基础上提出时序多属性决策的广义等级偏好优序法。最后,利用文献中的数据,用本文的方法对某集团的四个铜矿企业的综合效益进行了评价,其结果表明了本文方法的可行性和有效性。本文为解决时序多属性决策问题提供了一种新的方法和思路。     

How hot cognition can lead us astray: The effect of anger on strategic decision making

Anger is one of the most frequently experienced emotions. However, the extant research on the impact of anger has predominantly focused on its effect on decision making in simple decision tasks. Strategic decision making differs significantly from such tasks, as it is characterized by complexity, ambiguity, and a high information load. To better understand the impact of emotions on strategic decision making, we investigate the effect of anger on decision quality and decision speed. To do so, we carry out a strategy field experiment with 52 executives in which we use participants’ psychophysiological skin conductance response. In line with psychological research on non-strategic decisions, we find that anger negatively influences decision quality in strategic decision making. However, in contrast to predictions made by research on non-strategic decisions, we find no increase in decision speed among angry participants. We thus extend extant theory by suggesting that anger impacts the quality of strategic decisions but does not affect important process characteristics such as decision speed.     

考虑决策者损失规避的异质信息多属性变权决策方法

现实中存在大量异质信息（或数据）和需要考虑权重随属性值变化的多属性决策问题。针对这类异质信息多属性决策问题，本文提出了一种基于前景理论的变权综合求解方法。首先，构建了异质信息的统一距离计算公式，进而计算各个决策方案的相对贴近度；然后，提出基于不同类型效用函数的变权向量构造方法；其次，以初始权重为参考点，计算变权向量相对于参考点的益损决策矩阵，进而计算考虑决策者权重损失和收益的风险态度的各个决策方案的前景综合值，据此确定方案优劣排序和最优方案。通过数值例子的计算分析说明，文中所提决策模型与方法具有较好的有效性和合理性，可为解决复杂情景的决策问题提供理论依据与方法支持。     

Intelligence gathering for decision making

Empirical studies of decision making seldom consider the intelligence gathering activities required for decision making. In an attempt to fill this void, this study set out to identify and assess some of the key steps in gathering intelligence, considering the difficulty of the decision and available resources. The study found performance gapping and premising to be crucial activities and explored how each is carried out. A variety of premising and gapping tactics were uncovered, with some having better success than others. These tactics were found to influence the search approach selected to uncover alternatives and the success of the resulting decision. The best results were noted when search efforts are guided by needs documented with a quantitative performance gap; and when formal search or negotiation is used to identify alternatives. These findings hold for decisions that have high and low difficulty and for those with high and low resource support. The implications of these findings for decision makers and decision making are discussed.     

基于交叉效率DEA与群体共识的区间乘性语言偏好关系群决策

针对区间乘性语言偏好关系群决策问题，提出了一种基于交叉效率DEA和群体共识的群决策方法。首先，提出乘性语言偏好关系导出函数的定义，并构建产出导向的DEA模型，证明了一致性乘性语言偏好关系的DEA效率得分与排序向量之间存在比例关系。在此基础上，建立基于理想值的交叉效率DEA模型，提出乘性语言偏好关系的通用排序方法。同时，基于群体共识建立目标规划模型来计算各语言偏好关系的权重系数。最后，利用Monte Carlo随机模拟的方法对群体语言偏好空间进行统计分析，得到群决策期望排序向量及其可信度。算例分析表明本文方法能够有效的避免信息损失，具有较强的适用性和较高的可信度。     

A Conjugate Class of Utility Functions for Sequential Decision Problems

The use of the conjugacy property for members of the exponential family of distributions is commonplace within Bayesian statistical analysis, allowing for tractable and simple solutions to problems of inference. However, despite a shared motivation, there has been little previous development of a similar property for using utility functions within a Bayesian decision analysis. As such, this article explores a class of utility functions that appear to be reasonable for modeling the preferences of a decisionmaker in many real‐life situations, but that also permit a tractable and simple analysis within sequential decision problems.     

基于一致性度量的概率模糊语言多属性群决策方法

人们通常习惯用语言术语来表达他们的偏好，因此概率型语言术语集（Probabilistic Linguistic Term Set，PLTS）在决策过程中有着十分重要的作用。目前PLTS的研究刚刚起步，有关PLTS的相关研究没有关注到一致性度量的问题，对于PLTS的多属性群决策方法有待进一步研究。首先，给出了一种新的PLTS的集结方法，并且在已有的PLTS可能度公式的基础上，构建了PLTS的相似度量方法，在此基础上，进一步提出了基于PLTS一致性度量的多属性群决策方法。该方法在各决策者权重未知的情况下，考虑到各决策者之间的一致性。首先，定义PLTS的一致性度量公式，确定决策者权重；并根据PLTS的集结方法，集结各决策者的评价信息；最后，利用可能度公式对PLTS进行排序。通过案例分析验证了该方法的可行性和优越性。     

Corporate Strategy Formulation and Taxation: Evidence from UK Firms*

This paper considers the relationship between corporate strategy formulation and taxation. Drawing on prior literature we briefly review the important influence that international taxation has on an array of corporate strategy decisions. We then consider issues in strategy formulation and taxation planning in order to develop an understanding of when and how taxation factors impinge on strategic decision‐making. We draw out the apparent paradox between the nature of strategic decision‐making and financial decision‐making and look for areas of reconciliation. In order to shed light on some of these issues we present findings from the qualitative analysis of a set of personal interviews undertaken with senior tax practitioners in seven UK‐based multinational enterprises and then consider quantitative responses from the tax practitioners working in 145 UK firms.     

Sequential and Simultaneous Decision Making for Optimizing Health Care Resource Flexibilities

Health care administrators commonly employ two types of resource flexibilities (demand upgrades and staffing flexibility) to efficiently coordinate two critical internal resources, nursing staff and beds, and an external resource (contract nurses) to satisfy stochastic patient demand. Under demand upgrades, when beds are unavailable for patients in a less acute unit, patients are upgraded to a more acute unit if space is available in that unit. Under staffing flexibility, nurses cross‐trained to work in more than one unit are used in addition to dedicated and contract nurses. Resource decisions (beds and staffing) can be made at a single point in time (simultaneous decision making) or at different points in time (sequential decision making). In this article, we address the following questions: for each flexibility configuration, under sequential and simultaneous decision making, what is the optimal resource level required to meet stochastic demand at minimum cost? Is one type of flexibility (e.g., demand upgrades) better than the other type of flexibility (e.g., staffing flexibility)? We use two‐stage stochastic programming to find optimal resource levels for two nonhomogeneous hospital units that face stochastic demand following a continuous, general distribution. We conduct a full‐factorial numerical experiment and find that the benefit of using staffing flexibility on average is greater than the benefit of using demand upgrades. However, the two types of flexibilities have a positive interaction effect and they complement each other. The type of flexibility and decision timing has an independent effect on system performance (capacity and staffing costs). The benefits of cross‐training can be largely realized even if beds and staffing levels have been determined prior to the establishment of a cross‐training initiative.     

Budgets for integrating decentralized investment and production planning

Planning for an economic enterprise can be dichotomized into short-run production planning and longer-run investment planning. Usually these problems are treated as if they were separate, if not independent. This paper briefly reviews the separate approaches to optimal production decision making and investment planning, ‘fusing’ these models in order to consider the two issues simultaneously. The resulting ‘fused’ model is used to illustrate several difficulties which result from an intuitive synthesis of the independent solutions of the production problem and the investment problem. An integrated model is presented representing a centralized simultaneous solution for decision variables from the two functional fields. The paper compares and contrasts the synthesis of separate functional models to the decomposition of a simultaneous model of those functional areas. A result of this comparison is a theoretical justification for operating budgets and revenue targets as organizational mechanisms for achieving coordinated plans among decentralized planning units. Further, the set of conditions are identified under which the two approaches to simultaneous decision making are equivalent.     

Multiobjective investment planning under uncertainty

In this paper we consider the relevance of various planning methods and decision criteria to multiobjective investment planning under uncertainty. Assuming that a natural reaction to uncertainty is to operate so as to leave open as many good options as possible (as opposed to maximizing subjective expected utility) we argue that the planning process should concentrate on analyzing the effects of the initial decision, and that for this exercise the classical methods of mixed integer programming are inappropriate. We demonstrate how the technique of dynamic programming can be extended to take account of multiple objectives and use dynamic programming as a framework in which we analyze the robustness of an initial decision in the face of various types of uncertainty. In so doing we also analyze the risks involved in both the planning and decision making functions.     

A Sequential Selection Problem*

In this study we formulate a sequential selection problem. In a setting where a choice sequence among candidates is established for filling a job position, the analysis explicitly takes into account the benefits from the hiring, the risk of rejection of the job offer, and the costs due to delays in filling the position. The proposed solution, which is both intuitive and simple, is able to capture analytically the decision process. We also illustrate the versatility of the analysis by considering several other relevant sequential selection settings.     

A DECISION THEORETIC APPROACH TO PRICING

The problem of price determination and revision is considered as a case of decision making under uncertainty in which profit is to be maximized. Typically price is a simple function of cost which in turn determines the quantity which will be demanded. This paper proposes that maximum profits could be realized in the long run, if a quantity corresponding to the lowest cost per unit of product under the attendant circumstances was fixed and a price established at which demand would exactly equal the fixed quantity. It further suggests a theoretical approach to the determination of this price based on decision theory. The decision theoretic approach considers the set of possible price levels at which demand will equal the fixed quantity of product as the state of nature. The set of acts consist of the establishment of the product price at each of the possible levels. After an initial price is established, empirical information can then be utilized according to some optimal decision rule for subsequent price revisions.