投标与拍卖的几个数学模型

主要介绍关于投标与拍卖的几个典型的决策理论模型，包括Friedman模型、Gates模型、Nanssman—Rivett模型和Willenbrock模型，并对它们进行简短评述     

基于博弈模型和模糊预测的投标报价策略研究

本文根据工程投标竞争活动所带有的典型博弈特征,运用不完全信息静态博弈理论对竞标报价行为进行了诠释,进而运用模糊预测方法进行竞争情报的处理,建立了基于博弈模型和模糊预测的工程投标报价决策方法,并进行了实证分析.     

非确定型决策方法决策目标及决策结果可靠性研究

目前国内外缺乏关于非确定型决策方法的理论研究.本文对非确定型决策方法的决策目标的本质进行了经济学分析,提出了非确定型决策方法决策结果的可靠性概念和计算公式,并运用可靠性概念对非确定型决策方法使用中存在的误区进行了解释.     

非参数方法的多单位序贯英式拍卖模型的估计与识别

在独立私人价值范式下研究了多单位序贯英式拍卖,竞标者的竞标是连续的随机变量,在竞标中给定标的数量、竞标的人数.竞标者赢得的竞标是可以估计的,其联合价值分布函数依赖于赢者的经验分布.     

交通BOT项目特许经营权竞标机制设计

本文从项目拍卖者的角度,对交通BOT项目进行特许经营权机制设计,设计了一套科学合理的竞标机制来提高项目拍卖者对特许经营权的配置效率。我们运用激励机制设计思想建立了竞标机制模型,在保证竞标企业参与投标和真实显示自己的经营能力的条件下最大化期望社会福利,通过求解此模型得到了最优的竞标机制;鉴于最优机制在形式上的复杂性,我们给出了得分规则拍卖和供应契约拍卖两种最优拍卖方式。     

基于案例推理技术的企业经营决策支持模型设计

本文提出了一个基于案例推理技术的企业经营决策支持模型的设计思想和实现方法。该模型通过对案例库中记忆的源案例企业的经营指标进行相似性搜索,在分析源企业实施的各项决策及实施后收到的经营效果的基础上,对目标企业未来经营策略进行指导。在关键技术(相似度搜索)上,模型采用了一种新的混合相似性搜索的方法,克服了传统的只能对确定性指标进行搜索的缺陷。     

需求具有价格敏感性的供应链收益共享契约设计研究

本文研究了供应链收益共享契约的协调问题。在综合考虑最终销售价格为内生变量和剩余产品残值与生产成本相关的情况下,建立了供应链收益共享契约协调模型,并借助报童模型对零售商和供应商的决策行为进行分析,给出零售商最优决策行为和契约参数φ取值范围的计算公式。最后进行了数值实例分析,验证了供应链收益共享契约的有效性。     

无限理性还是有限理性？——齐当别抉择模型在经济行为中的应用

长期以来以期望价值为核心的主流决策理论秉承无限理性的基本假设。有别于传统“最大化”规则模型,齐当别抉择模型遵循有限理性假设,对主流决策理论提出一系列挑战。文章以实例介绍了齐当别抉择模型对不同领域决策问题的解释,如一般性违背决策公理或原则现象（独立性原则、不变性原则、偏爱反转）、博弈问题、消费者的非理性行为及时间折扣问题。文章并从决策的双系统理论及与其他有限理性决策模型比较的角度,对齐当别模型的发展进行了展望,冀为风险决策提供更好的预测和解释模型。     

关键词拍卖中基于广义第一价格的投标价格决策分析

在关键词拍卖中,由于广告商不能保证对关键词的估价是最优投标价格,因此如何选取最优的关键词投标价格一直是广告商急于解决的问题。基于与Friedman投标模型假设条件等价的关键词拍卖投标假设条件,计算了各个关键词广告位置的胜标概率,并在广义第一价格拍卖机制下建立了关键词投标价格决策模型。该模型可以使广告商选取最优的关键词投标价格。最后通过仿真验证了该模型的有效性。     

优化离散灰色幂模型及其应用

考虑已有的灰色预测模型主要能对指数型发展系统或幂函数型发展系统进行模拟预测,本文构建了一种不仅能够模拟指数型和幂函数型的发展系统,并且能够体现出二者之间的相互作用关系的离散灰色幂模型;并针对初始条件对离散灰色幂模型模拟精度的影响,首先给出了离散灰色幂模型的建模步骤,然后以平均相对误差最小化为目标、参数之间的关系为约束条件,构建了离散灰色幂模型初始条件的优化模型,实现对离散灰色幂模型初始条件的优化。结果表明,优化的离散灰色幂模型使得平均相对误差在理论上达到了最小化,其模拟精度和预测精度都高于传统模型。最后,通过中国网络购物人数数据预测和仿真数据分析,说明了本文优化方法的有效性和适用性。     

Automating Knowledge Acquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model*

An important application of expert systems technology is to provide support for nonstructured decision making. Usually, nonstructured decision making is characterized by heavy reliance on heuristic knowledge, which is very difficult to articulate or document, and therefore traditional knowledge acquisition approaches are not very successful. The quality and effectiveness of an expert system supporting unstructured decision making is affected when traditional knowledge acquisition approaches are used. To alleviate this problem a model is proposed that combines inductive inference and neural network computing, and an example is presented that illustrates the potential of this model in unstructured decision support.     

A comparative study of three methods of eliciting preference information

The study reported in this paper compared three methods of eliciting preference information from a decision maker and estimating weights with this information for use in a multiple objective decision making model. The design of the study included issues of implementing computerized interactive models vs more traditional question and answer techniques in the light of different decision models (in terms of level of complexity) and differing levels of decision maker experience. Results indicate that decision makers, regardless of prior exposure to computer terminals, are not intimidated by their use. Additionally, methods which required non-quantitative statements of preferences were preferred over techniques which requested numerical estimates of tradeoffs or marginal rates of substitution between objectives.     

Optimal ordering and pricing decisions for a target oriented newsvendor

This paper is the first to study pricing and target oriented decision making together in the newsvendor model. Specifically, this paper studies a newsvendor who decides on order quantity and selling price to maximize the probability of achieving both profit and revenue targets simultaneously. First, it is shown that the probability of a newsvendor achieving both targets depends critically on the relative magnitudes of the profit margin and the ratio between the profit target and the revenue target. Second, the closed-form expressions of the optimal order quantity, the optimal selling price, and the maximal profit and revenue probability are obtained. It is shown that if the product has greater price elasticity, the best strategy is always to price lower and order more.     

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。     

AN APPROACH TO COST—VOLUME—PROFIT ANALYSIS UNDER UNCERTAINTY*

Cost-Volume-Profit analysis is a tool of cost accountants aiding in the choice of an optimal course of action in the solution of a managerial problem. C-V-P is a limited analysis since all the needs of management in determining the optimal strategy are not fulfilled. Factors pertinent to the choice of the optimal strategy under uncertainty are variables, although traditional C-V-P treats these factors as constants. Hence, an approach to C-V-P where pertinent factors necessary for decision making are considered as variables is more desirable than traditional C-V-P. By introducing uncertainty, it is also beneficial to broaden C-V-P to fulfill the following desire of management. Should management choose a course of action based only on its own estimates of the decision parameters or is it advisable to postpone a terminal decision until additional research into the decision parameters is accomplished? Broadened C-V-P solves this problem with the aid of Bayesian Decision Theory for the choice of the optimal course of action in the face of uncertainty.     

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.     

群决策与个体决策的一致性分析

本文针对群决策与个体决策的一致性问题,将负熵理论应用到集对分析理论中,给出了系统的联系熵与转换熵的概念,探讨了其性质,通过定义联系熵的势,可转换熵的势作为群体决策与个体决策一致性的度量,得到一个新的判断群集结的有效性定理。     

A Framework for the Analysis of Error in Conjunctive,Multi-Criteria,Satisficing Decision Processes*

This paper examines the impact of certain types of error on ad hoc, unstructured decision making that incorporates a satisficing strategy in a multi-criteria context using the conjunctive rule. The impacts of error in evaluation and of error in minimal or satisficing levels are systematically modelled for each of the decision criteria. Error functions, analytical expressions, and procedures are developed to obtain information such as the likelihood of correct decision making in the presence of evaluation and minimal criteria level error. These are applied to a specific research design, which is then analyzed. This highlights certain features of decision making in a satisficing context, such as the importance of keeping the number of decision criteria to a minimum. The results yield various insights, some of which confirm information obtained from previous analyses. A major advantage of the framework presented is that it can provide quantitative measurements which support ideas previously couched in qualitative terms only. Although the framework is applied in the context of decision making that uses the conjunctive rule in the case of multiple criteria, other satisficing strategies can be accommodated as well.     

基于案例推理的直觉模糊决策方法

目前大多数决策方法的定权问题仅依靠决策矩阵而忽略了决策背景。针对上述问题,将案例推理方法融入到直觉模糊决策问题。首先根据直觉模糊数的内涵构建一种相似度公式,将案例推理模型跟相似度测度结合求得最优权重以及分类半径,进而进行择优排序。最后通过案例分析详细说明了本文方法的优势之处:根据决策数据又考虑专家意见,使得决策结果与现实情况更加一致,并提出一种解决面向直觉模糊决策问题的新思路。     

考虑安全性的层次分析法

本文从决策的现实特点出发,提出了安全矩阵、风险矩阵、安全指数等一系列概念;并进一步给出了在运用决策方法(如:AHP等)时考虑安全性的具体方法。该方法(1)可表示、度量、计算、分析决策结果对安全性要求的具体程度;(2)可解决某些AHP无法直接解决的决策问题;(3)可使决策者对决策结果有重要的安全感。值得指出的是,本文给出了安全指数的解析表达式,并解决了式中参数的辩识问题,从而使本方法更具实用价值。