An approach to the display and analysis of multiobjective problems

In all operations research applications, the problem of implementation rests on the information conveyed to the decision maker. The presentation of results is a critical link in the success of a project. An ineffective transfer of information will reduce the chance of decision maker acceptance. This final step in the analysis is particularly difficult in multiobjective analyses, where the amount of relevent information increases with each performance measure.This paper will describe an alternative to the typical graphical approach to multiobjective display, which is adaptable to any number of objectives. A real world example is given and some theoretical insights are developed.     

Decision making with imprecise probabilistic information

We develop an axiomatic approach to decision under uncertainty that explicitly takes into account the information available to the decision maker. The information is described by a set of priors and a reference prior. We define a notion of imprecision for this informational setting and show that a decision maker who is averse to information imprecision maximizes the minimum expected utility computed with respect to a subset of the set of initially given priors. The extent to which this set is reduced can be seen as a measure of imprecision aversion. This approach thus allows a lot of flexibility in modelling the decision maker attitude towards imprecision. In contrast, applying Gilboa and Schmeidler [J. Math. Econ. 18 (1989) 141] maxmin criterion to the initial set of priors amounts to assuming extreme pessimism.     

Unawareness, priors and posteriors

This note contains first thoughts on awareness of unawareness in a simple dynamic context where a decision situation is repeated over time. The main consequence of increasing awareness is that the model the decision maker uses, and the prior which it contains, becomes richer over time. The decision maker is prepared to this change, and we show that if a projection-consistency axiom is satisfied unawareness does not affect the value of her estimate of a payoff-relevant conditional probability (although it may weaken confidence in such estimate). Probability-zero events however, pose a challenge to this axiom, and if that fails, even estimate values will be different if the decision maker takes unawareness into account. In examining evolution of knowledge about relevant variable through time, we distinguish between transition from uncertainty to certainty and from unawareness to certainty directly, and argue that new knowledge may cause posteriors to jump more if it is also new awareness. Some preliminary considerations on convergence of estimates are included.      

基于投影模型的不确定语言型多属性决策方法及应用

研究了不确定语言型多属性决策评价结果与决策者对方案的偏好信息之间存在偏差的问题,提出了基于投影模型的不确定多属性决策方法。该方法通过建立与区间型语言标度对应的术语指标矩阵,及方案综合属性值与决策者主观偏好值之间的投影模型,确定属性的权重,然后运用加权法得到方案的综合属性值,利用已有的可能度矩阵排序公式得到决策方案的排序。最后,通过算例对该方法的实用性和有效性进行了说明。     

Time‐to‐market,window of opportunity,and salvageability of a new product development

The time‐to‐market in the presence of a window of opportunity is analyzed using ;a probabilistic model, i.e. a model where the completion time of new product development is a random variable characterized by a gamma distribution. Two cases are considered: the first, a case where the discounted return‐on‐investment exceeds the return expected from a conservative investment—e.g. investment in bonds—termed ‘the profitable case’; and the second, a case where the discounted return‐on‐investment just balances the cost of new product development, termed ‘the salvageable case’. The model constructed is focused on the financial aspects of new product development. It allows a decision‐maker to monitor, as well as terminate, a project based on its expected value (at any time prior to completion) by computing the mean time‐to‐market that provides profit, investment salvage, or loss. The mean time‐to‐market computed by the model may be compared with that estimated by the technology development team for decision‐making purposes. Finally, in the presence of a window of opportunity and for the specific cases analyzed, we recommend to always keep the expenditure rate lower than the expected return rate. This will provide the decision‐maker a salvageable exit opportunity if project termination is decided. Copyright © 2002 John Wiley & Sons, Ltd.     

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.     

Strategic real options under asymmetric information

This paper studies the effect of private information on the capital allocation decisions of firms who operate under imperfect competition. I analyze two interactive firms, one with private information and the other without, who must decide when to undertake an irreversible and uncertain investment decision. Traditional non-strategic models of irreversible investment under uncertainty involve a single decision maker and result in an optimal period of delay before the investment is undertaken. In a strategic setting, firms must balance their desire to delay against competitive advantages from early investment. I find that an equilibrium may not exist within the standard continuous framework when the private information is over revenues. Moreover, when an equilibrium does exist the competitive pressures from the uninformed firm are weak. This is in contrast to existing models with asymmetric information over costs, where an equilibrium always exists and the competitive pressures remain strong (Hsu and Lambrecht, 2007). This work shows that the investment timing decision, and thus the value of the private information, is highly sensitive to the nature of incomplete information.     

The development of FFMD Pyramid: Fuzzy Family_Marriage Deployment as decision support method to improve human resources performance

Improvement action to human resource (HR) in organization plays important role in determining the success of organization. Many studies have been done to discuss on how the organization may improve their HR performance. However, not many studies yet discuss the level of improvement that organization shall taken appropriately. Identification of organization’s priority level of improvement seems found to be a complicated work to do in most emerging organizations. High intangible and invisible variables and attributes contribute to unclear situations and perceptions in the organization itself. The complexity and limitation in tools and techniques, make each solution taken is less efficient and effective. Therefore, this study will discuss the development of Fuzzy Family_Marriage Deployment (FFMD) Pyramid. FFMD Pyramid is a new method for decision support in organization especially for HR by equally deploy dimension and variable of family and marriage to quality dimension and variable in organization then identify priorities by considering the deployment value (crisp value) and fuzzy value (non-crisp value) as decision support for organization to plan and decide proper improvement action with proper percentage (%) level of priority of improvement action. As result, a concise and simple pyramid shall present an informative yet effective and efficient to the decision maker to support their better decision especially with regard to the improvement action for HR performance. In addition, the Family_Marriage value that utilize in this study may bring about a new perspective that decision maker shall consider to support their decision process especially for the HR improvement action.     

Judgmental adjustment of forecasts: A comparison of methods

Attention has recently been given to combinations of subjective and objective forecasts to improve forecast accuracy. This research offers an extension on this theme by comparing two methods that can be used to adjust an objective forecast. Wolfe and Flores (1990) show that forecasts can be judgmentally adjusted by analysts using a structured approach based on Saaty's analytic hierarchy process (AHP). In this study, the centroid method is introduced as a vehicle for forecast adjustment and is compared to the AHP. While the AHP allows for finer tuning in reflecting decision maker judgement, the centroid method produces very similar results and is much simpler to use in the forecast adjustment process.     

数据仓库在零售业中的应用及优化

针对连锁零售业经营决策的需要，采用高速读取技术处理海量销售数据，提出了系统数据仓库的解决方案及其实现快速处理业务数据过程，进而设计出数据仓库、数据挖掘模型和报表模型，最后通过商业智能工具向企业数据分析人员和经营决策人员提供操作简便、界面友好的平台。     

Timing of information in agency problems with hidden actions

This paper endogenizes in a standard hidden action model the point in time when a risk neutral and wealth constrained agent and the principal observe the realization of an additional signal: before the agent’s effort choice (ex ante information) or after (ex post information). In a decision problem, ex ante information does (weakly) better than ex post information because the decision maker can tailor efforts to the information. We show that this is not the case for incentive problems: a negative incentive effect arises under ex ante information that prevails even though the principal tailors the agent’s effort to the information.     

投资者决策行为与信息披露

本文认为对会计师而言,理解投资者如何作出决策(实证理论)以及应如何作出决策(规范理论)是相当重要的。通过对投资者决策行为的研究,可能有助于提高财务信息准确地描述真实经济事项的能力;有助于理解财务会计信息的数量、类型和形式如何影响投资者的判断或预测;有助于理解决策者准确地对其认知的环境作出反应的能力;有助于理解投资者如何解决决策的复杂性,以及不同的决策风格对信息利用方式的影响。     

A representation of decision by analogy

We give a representation of analogical reasoning in choice under uncertainty. A decision maker is faced with two decision problems, a familiar and a novel one. It is shown that, under assumptions that capture the salience of alignable differences in choice, the decision maker can be construed as choosing between acts in the novel decision problem as if drawing all likelihood information from a multi-valued correspondence between states of the world in the familiar domain and states of the world in the novel domain. The latter is interpreted as an analogy between the two decision problems, and the fuzziness of the analogy is related to revealed ambiguity in the novel decision problem.     

基于粗集属性重要性的供应链信息共享的模糊综合评价

供应链信息共享是供应链渠道协调的重要方法，信息共享的程度评价为供应链节点企业的信息共享激励决策以及合作伙伴关系的评估提供重要依据。文章提出了信息共享的评价指标体系．利用评价指标属性的重要性作为权重值，解决了确定权重值的主观性问题。利用粗糙集理论结合模糊数学的有关理论建立了供应链信息共享的综合评价模型并进行了算例分析，为节点企业的激励决策和合作伙伴关系的评价提供依据和理论指导。     

Robustness as a corporate objective under uncertainty

This paper examines the nature of the objective function of the firm when operating under conditions of uncertainty. Robustness is presented as a purposeful maximand for decision making both under conditions of certainty and uncertainty - a robust decision being one in which the decision maker retains the maximum flexibility with regard to future decisions after an initial decision has been made. Its incorporation within a managerial objective function provides a measurable scale for making choices between alternative courses of action, including under conditions of internal organizational conflict and environmental reaction by other decision makers.     

Application of fuzzy mathematical programming to imprecise project management decisions

In real-world project management (PM) decisions, the input data and environmental coefficients are generally imprecise/fuzzy because of incompleteness and unavailability of relevant information over the project planning horizon. This work aims to present a fuzzy mathematical programming approach to solve imprecise PM decision problems with fuzzy goal and fuzzy cost coefficients. The designed PM decision model attempts to minimize total project costs with reference to direct costs, indirect costs, contractual penalty costs, duration of activities and the constraint of available budget. The proposed approach achieves greater computational efficiency by employing the simplified triangular fuzzy number to represent imprecise goal and cost coefficients, and provides a systematic framework that facilitates the decision-making process, enabling a decision maker to interactively modify the imprecise data and related parameters until a satisfactory solution is obtained. An industrial case is implemented to demonstrate the feasibility of applying the proposed approach to practical PM problems. The computational methodology developed in this work can easily be extended to any other situations and can handle the realistic PM decisions in fuzzy environments.     

The pricing accuracy of alternative equity valuation models: Scandinavian evidence

In many decision contexts, there is a need for benchmark equity valuations, based on simplified modeling and publicly available information. Prior research on U.S. data however shows that the accuracy of such valuation models can be low and sensitive to the choice of model specifications and value driver predictions. In this paper, we test the applicability and pricing accuracy of three fundamental valuation (dividend discount, residual income, and abnormal earnings growth) models, all based on forecasts of company dividends, earnings, and/or equity book values. Extending prior research, we apply these models to Scandinavian firms with accounting data from the period 2005–2014, explicitly testing two approaches for the prediction of the value drivers—exogenously forecasted numbers versus projected historical numbers. Given access to the forecasted value drivers, the dividend discount model comes out as the most accurate valuation model. In particular, this holds in a comparison between the most parsimonious model specifications. The residual income valuation model generates the best pricing accuracy given the prediction of value drivers based on historical financial numbers. Notably, we observe pricing errors that in general are lower than what has been reported in prior U.S.‐based research for the dividend discount and the residual income valuation models. The pricing accuracy of the abnormal earnings growth models is surprisingly weak in the Scandinavian setting. However, these models improve somewhat after a couple of complexity adjustments, in particular with value driver predictions based on the projected history setting.     

Bayesian learning with variable prior

How much can be learned from a noisy signal about the state of the world not only depends on the accuracy of the signal, but also on the distribution of the prior. Therefore, we define a general information system as a tuple consisting of both a signal technology and a prior. In this paper we develop a learning order for general information systems and characterize the order in two different ways: first, in terms of the dispersion of posterior beliefs about state quantiles and, second, in terms of the value of learning for two different classes of decision makers. The first class includes all agents with quasi-linear quantile preferences, and the second class contains all agents with supermodular quantile preferences.     

Similarity-based mistakes in choice

We characterize the following choice procedure. The decision maker is endowed with two binary relations over alternatives, a preference and a similarity. In every choice problem she includes in her choice set all alternatives which are similar to the best feasible alternative. Hence she can, by mistake, choose an inferior option because it is similar to the best. We characterize this boundedly rational behavior by suitably weakening the rationalizability axiom of Arrow (1959). We also characterize a variation where the decision maker chooses alternatives on the basis of their similarities to attractive yet infeasible options. We show that similarity-based mistakes of either kind lead to cyclical behavior. Finally, we reinterpret our procedure as a method for choosing a bundle given a set of individual items, in which the decision maker combines the best feasible item with those that complement it.     

空军航材运输方式选择的模糊决策方法

基于层次分析的思想，本文建立了航材运输方式的评价指标体系，并运用多目标模糊决策的方法。提出了航材运输方式选择的模糊决策模型。通过该决策模型的应用，决策者可以将定性指标定量化，从而提高决策的客观性、科学性。