CONSISTENT RANKINGS BASED ON TOTAL AND DIFFERENTIAL AMOUNTS UNDER UNCERTAINTY*

Rankings of decision alternatives based on total and on differential monetary amounts may in general be inconsistent under uncertainty. In the following cases, either approach is valid and hence yields consistent rankings: (i) with expected values, provided that the differential amounts have been coherently determined and are constant within states (but may differ across states); (ii) with exponential utility functions if the shared and differential amounts are statistically independent; or (iii) in a market valuation context, assuming diversification and implicit separate market values for differential and shared amounts.     

An environmental decision model for dynamic planning

In the complex, rapidly changing environment facing the modern business enterprise, it has become increasingly difficult to make meaningful predictions concerning future activities. As such, it is especially important for the decision maker to seek means of gathering and evaluating information. Due to the immense amounts of subjective data, the need arises for the development of valid techniques for identifying and quantifying relevant information.Writers in the area of organization theory have emphasized the importance of the relationship between and organization and processes occurring within its environment to the extent that these environmental processes and their impact are considered vital to the ultimate survival of the firm. The Graphical Evaluation and Review Technique (GERT) is an analytical process upon which simulation models can be developed to examine the effect of more sophisticated information processing. The GERT technique serves as an input to decision making and for purposes of analysis will be studied under conditions of the disturbed reactive environment.The essential method upon which this study is based is the development of a model designed to capture the characteristics of the environment. The model in turn is tested under various conditions and changing sets of information to arrive at some idea of the possible implications for decision making under a situation affected by more and different information usage.     

Column generation with free replicability in DEA

The evaluation of efficiency scores in data envelopment analysis is based on the construction of artificial decision making units subject to some assumptions, usually requiring convexity of the production possibility set. This demands divisibility in input and output, which is not always possible. The so-called free replicability model, proposed by Henry Tulkens, permits input and output to enter in only discrete amounts. The model is of a mixed integer programming type, for which the number of variables, here corresponding to the decision making units, may be critical in order to reach an optimal solution.     

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。     

Optimal Sourcing and Lead‐Time Reduction under Evolutionary Demand Risk

We develop a real‐options model for optimizing production and sourcing choices under evolutionary supply‐chain risk. We model lead time as an endogenous decision and calculate the cost differential required to compensate for the risk exposure coming from lead time. The shape of the resulting cost‐differential frontier reveals the term structure of supply‐chain risk premiums and provides guidance as to the potential value of lead‐time reduction. Under constant demand volatility, the break‐even cost differential increases in volatility and lead time at a decreasing rate, making incremental lead‐time reduction less valuable than full lead‐time reduction. Stochastic demand volatility increases the relative value of incremental lead‐time reduction. When demand has a heavy right tail, the value of lead‐time reduction depends on how extreme values of demand are incorporated into the forecasting process. The cost‐differential frontier is invariant to discount rates, making the cost of capital irrelevant for choosing between lead times. We demonstrate the managerial implications of the model by applying it first to the classic Sport‐Obermeyer case and then to a supplier‐selection problem faced by a global manufacturer.     

共识条件下最小最大妥协的直觉模糊数集结方法研究

直觉模糊集（IFS）理论是描述广泛模糊事物的重要工具。为减小决策过程中个体偏好值与群体偏好值的差异，协调个体与群体间矛盾，提升决策结果的执行效率，本文提出最小化最大妥协度（Minimize maximum compromise）的决策准则。给出直觉模糊环境下的，个体偏好值的集结算法及决策方法，并分别考虑了有无共识条件、有无决策主体权重的三类决策情景。最后给出算例，验证本文方法的有效性，结果表明，相较于I-IFOWG算子，本文方法能够有效降低群体决策中个体的妥协程度。     

在BOT模式下收费道路定价和投资的博弈决策模型

本文主要研究在两地之间已有一条免费道路的情况下,私营财团在BOT模式下再建造一条平行的收费道路,从而进行选择道路收费价格和道路建设投资的决策问题。通过对交通BOT项目中私营财团和出行者之间的博弈分析,本文建立了道路收费价格的决策模型和道路建设投资的决策模型,对博弈的纳什均衡解的性质进行了讨论,得到了一些非常重要的结论,这对交通BOT项目实践中有着重要的指导意义。     

Decision-making Autonomy in UK International Equity Joint Ventures

This paper investigates approaches to decision making in international joint ventures (IJVs) from the perspectives of the transactions cost and resource‐based theories of the firm. In particular, the concept of autonomy in decision‐making in a sample of UK‐European equity joint ventures is examined. The study adopts a multi‐method personal interview and self‐administered questionnaire approach to examine managerial perceptions of decision‐making and autonomy in the parent firms and the joint venture. The findings show that there are differences in the perception of autonomy between each of the parent firms, and between the parent firms and the IJV management. When we unpack the nature of autonomy in detail, it is found that IJV managers have greater degrees of operational autonomy than strategic autonomy and that decision making by IJV managers takes place within the context of constraints set within the IJV's business plan. This confirms the transaction cost theory which posits that key internal markets (for management, technology and capital) will be under parent control and also supports the resource based view that key capabilities are protected under the business plan established by the parent firms. The influence on IJV autonomy of the moderating variables IJV performance and IJV duration are also examined.     

一种新的基于双前沿面的交叉效率方法及其应用

本文将双前沿面效率评价的思想引入到传统交叉效率模型中，同时，针对双前沿面交叉效率方法中仁慈型和激进型交叉效率策略无法抉择，以及这两种交叉效率策略的应用范围有限的不足，提出了一种新的基于双前沿面的交叉效率方法。该方法的基本思想是选取一个理想决策单元和负理想决策单元，使用被评价决策单元的权重来计算理想决策单元和负理想决策单元的效率，并使被评价决策单元的效率尽可能接近理想解的效率，同时，尽可能远离负理想解的效率。根据该思想，分别在乐观前沿面和悲观前沿面下求解交叉效率值并进行集结，避免了由于前沿面的选择不同导致的差异以及决策者对仁慈型和激进型交叉效率策略进行抉择的困难。最后，将本文方法与现有方法进行对比分析，并将本文方法应用于我国东部地区10个省(直辖市)的创新效率评价中，以验证方法的有效性。     

基于修正Russell方法的模糊决策单元的排序

文章首先建立基于修正Russell方法的超效率DEA模型,然后基于模糊数的比较,建立并求解模糊环境下的基于修正Russell方法的超效率DEA模型,从而解决了模糊决策单元的全排序问题。文末的算例将基于修正Russell方法的模糊超效率DEA模型,与基于CCR模型的模糊超效率DEA模型的结果进行了比较分析。     

A Knowledge Based Decision Support System for Setup Reduction

The issue of setup reduction is important for firms seeking to incorporate advanced procedures and concepts such as flexible manufacturing systems (FMS) and just-in-time (JIT) manufacturing to improve manufacturing productivity. Investing adequate amounts in setup reduction is a complex decision affected by many factors including the existing level of automation, worker characteristics, product features, and the manufacturing environment. The consequences of improper investment (i.e., over- and underinvestment) includes possible disruption of manufacturing operations as well as wasted resources. Much of the knowledge involved in the investment decision is heuristic and experience-based, and takes on greater significance when the form of the setup reduction function is not known a priori. This paper describes the development of a knowledge-based decision support system (KBDSS) that combines both heuristic and procedural knowledge to provide support for the setup reduction investment decision. The system uses codified manufacturing expertise to improve both the accuracy and effectiveness of setup-reduction decision making. Use of the KBDSS is illustrated by two examples based on disparate manufacturing contexts.     

A system for decision support without explicit objective functions

This paper presents a conversational decision support system: Resource Allocation in Business Operation under Uncertain Worth (RAINBOW). The focus is placed on the loosely structured decision situation where the multiple objective functions are given only implicitly and should be locally approximated by the decision maker as the decision making process proceeds. Basically, RAINBOW supports the process of convergence to a preferred alternative by giving the decision maker information which will help him form consistent evaluations of the utility function, the objective functions and the solution for the decision problem.     

基于CI-TOPSIS的梯形直觉模糊多准则群决策分类方法

模糊群决策分类方法广泛应用于政治、经济与社会生活各个领域,可有效避免个人知识与经验局限性所导致的决策失误。针对信息不完备的多准则群决策问题,提出基于CI-TOPSIS的梯形直觉模糊多准则群决策分类方法。首先,给出梯形直觉模糊集及广义梯形直觉模糊几何聚类算子,兼顾考虑群决策中相应依赖属性与决策者的决策偏好。其次,给出基于离散Choquet积分的TOPSIS算子（CI-TOPSIS）,以此为基础,进一步给出基于CI-TOPSIS的梯形直觉模糊多准则群决策分类步骤,用于确定具有最大可信度群体一致案例比较信息集,并逐步引导决策者给出部分及全部方案的精确分类,充分考虑模糊决策环境下决策者偏好与案例比较信息的级别关系。最后,通过一个投资决策实例对所提出的多准则分类方法进行验证。实例分析表明：该方法克服了决策过程中信息的遗漏,充分保留了决策过程中信息的完备性,更适用于直觉模糊群决策环境下的决策实践,是一种非常有效和科学的方法,可应用推广到更多决策领域。本文所得结论,对于有效解决多人多投资方案的群决策问题,具有一定的借鉴意义。     

综合集成研讨厅体系中专家群体行为的规范

首先扼要介绍了国内外在复杂系统、复杂性方面的研究情况 .然后 ,讨论了宏观经济决策问题 .由于宏观经济决策问题属于开放的复杂巨系统范畴 ,解决这一问题的有效方法是采用钱学森教授于 1 992年提出的“从定性到定量的综合集成研讨厅体系”的方法 ,它是将专家群体的定性认识综合后再用适当的建模方法处理 ,最终得出解决问题的结果 .研讨厅体系可以看作是由三部分组成 :群体专家体系、信息与知识体系、计算机软硬件技术 .在研讨厅体系中专家群体是一个非常重要的组成成分 ,专家个人和群体的行为直接影响着决策的结果 .专家本人及专家群体的思维和行为难免有一些不足 ,并且他们的行为也受个体、群体行为规律的支配 .本文通过分析个体、群体行为的缺陷 ,为参加研讨的专家制定一个行为规范 ,使他们克服人类行为的不足之处 ,结合先进的决策技术和工具以及建模方法 ,以得到更好的决策结果     

区间概率条件下属性值为不确定语言变量的风险型多属性决策研究

针对区间概率条件下属性值为不确定语言信息且属性权重未知的风险型多属性决策问题,提出了一种基于概率理论和不确定语言变量的TOPSIS决策方法。首先建立了区间概率转化为点概率的数学模型,通过期望值将风险型决策矩阵转化为确定型矩阵;然后利用方案与理想解越近方案越优,与负理想解越远方案越优的原则建立属性权重确定模型,并利用TOPSIS方法的相对优属度大小确定方案的排序;最后通过应用案例说明了本方法的决策步骤。     

Using Real‐Time Decision Tools to Improve Distributed Decision‐Making Capabilities in High‐Magnitude Crisis Situations*

Multi‐organizational collaborative decision making in high‐magnitude crisis situations requires real‐time information sharing and dynamic modeling for effective response. Information technology (IT) based decision support tools can play a key role in facilitating such effective response. We explore one promising class of decision support tools based on machine learning, known as support vector machines (SVM), which have the capability to dynamically model and analyze decision processes. To examine this capability, we use a case study with a design science approach to evaluate improved decision‐making effectiveness of an SVM algorithm in an agent‐based simulation experimental environment. Testing and evaluation of real‐time decision support tools in simulated environments provides an opportunity to assess their value under various dynamic conditions. Decision making in high‐magnitude crisis situations involves multiple different patterns of behavior, requiring the development, application, and evaluation of different models. Therefore, we employ a multistage linear support vector machine (MLSVM) algorithm that permits partitioning decision maker response into behavioral subsets, which can then individually model and examine their diverse patterns of response behavior. The results of our case study indicate that our MLSVM is clearly superior to both single stage SVMs and traditional approaches such as linear and quadratic discriminant analysis for understanding and predicting behavior. We conclude that machine learning algorithms show promise for quickly assessing response strategy behavior and for providing the capability to share information with decision makers in multi‐organizational collaborative environments, thus supporting more effective decision making in such contexts.     

移情关系影响下的群体共识决策模型研究

群体成员之间的社会关系及其网络结构特征是影响群决策的重要因素。移情关系是客观存在于一些现实群决策问题中的一种社会关系，但目前考虑移情关系的群决策研究尚不多见。为拓展群决策模型的应用范围，面向移情网络环境提出一种群体共识决策方法，并揭示移情关系对群体共识决策的影响规律。首先，从偏好交互影响的角度出发，构建局部移情模型和全局移情模型，并由此确定移情关系影响下决策者偏好演化的结果。其次，利用个体偏好分解为内在偏好和移情偏好的结构特点，为群体共识达成过程设计一种有效的移情关系引导的反馈机制，该机制可以通过内在偏好层面的偏好调整实现个体偏好层面的共识收敛。最后，数值仿真分析表明：群体成员之间的移情关系提升了群体共识水平，而且全局移情关系比局部移情关系更有利于群体共识的达成；移情网络结构和群体规模是影响移情网络环境下群体共识达成的重要因素。相关决策模型和研究结论可为移情网络环境下的群体共识决策提供理论和方法支持。     

受资源限制且带有缺货惩罚的季节性产品供应链协调

季节性产品供应链中,制造商受到资源限制时边际成本随产量递增,市场缺货时销售商面临缺货惩罚.以单个制造商和单个销售商组成的供应链为研究对象,首先分析了非合作状态下制造商和销售商最优决策行为,制造商根据销售商的订购量确定批发价格,并给出了集中控制下整个供应链系统的最优产量.接着建立了基于退货策略的协调模型,对合作状态下参与双方的决策行为进行了分析.结果表明,在退货策略激励下,销售商接受使供应链整体利润最优的产量决策,但在一定取值范围内制造商提供的批发价格和折价系数之间需满足正向变化的约束.此时,合作双方达到了"双赢",从而有效地协调了供应链.最后,进行了数值分析,验证了结果的有效性.     

Risk Decision Making in Operational Safety Management– Experience from the Nordic Benchmark Study

Technical Research Centre of Finland (VTT) and Studsvik AB, Sweden, have simulated decision making of the Swedish Nuclear Power Inspectorate and a power company by applying decision models in a benchmark study. Based on the experience from the benchmark study, a decision analysis framework to be used in safety related problems is outlined. By this framework both the power companies and the safety authorities could be provided with a more rigorous, systematic approach in their decision making. A decision analytic approach provides a structure for identifying the information requirements of the problem solving. Thus it could serve as a discussion forum between the authorities and the utilities. In this context, probabilistic safety assessment (PSA) has a crucial role of expressing the plant safety status in terms of reactor core damage accident probability and of risk contributions from various accident precursors. However, a decision under uncertainty should not be based solely on probabilities, particularly when the event in question is a rare one and its probability of occurrence is estimated by means of different kinds of approximations.     

Applications and Implementation DECISION SUPPORT SYSTEMS: AN EMPIRICAL ASSESSMENT FOR DECISION MAKING

A laboratory experiment examined the effects of applying decision support system (DSS) technology to decision making in ill-structured problem environments under varying information conditions. Marketing executives participated in the experiment which investigated the effects of DSS availability, DSS training, and data availability on dependent variables that included: (1) the number of alternatives considered by a subject during decision making, (2) the period of time spent by a subject to complete the decision-making process, (3) the subject's perceived confidence in the decisions he or she had made, (4) the amount of data considered by a subject's during decision making, (5) the individual subject's decision processing, and (6) the subject's performance overall. Our results indicate that all three factors significantly affect the number of alternatives considered by subjects during the decision-making process. We therefore suggest that DSS training be coordinated with decision training in order to realize the potential of DSSs as described in the DSS literature.