A Bayesian priorization procedure for AHP-group decision making

This paper proposes a new priorization procedure for Analytic Hierarchy Process Group Decision Making (AHP-GDM). Unlike the methods normally employed in AHP-GDM, this process does not require intermediate filters for the actors’ initial judgements. The procedure is based on a Bayesian analysis of the problem and in general, it provides more efficient estimates than the techniques conventionally applied in the literature for AHP-GDM: aggregation of individual judgements (AIJ) and aggregation of individual priorities (AIP). The proposed procedure naturally extends to the analysis of incomplete and/or imprecise pairwise comparison matrices, enhancing realism, practicality and scope. The methodology has been illustrated by the analysis of a case study.     

A systematic procedure to evaluate an automobile manufacturer–distributor partnership

Automobile manufacturer–distributor partnerships are fundamental to the success of automobile companies. The complexity of the overall partnership model often causes difficulties in partnership study. This paper presents a systematic procedure to evaluate an automobile manufacturer–distributor partnership consisting of a large number of system variables. Firstly, Interpretive Structure Modeling (ISM) is used to sort system variables into groups of various characteristics. This sorting process provides an effective means to develop a three-stage hierarchic/network model of the partnership, including Stage I: partnership selection, Stage II: partnership establishment, and Stage III: partnership maintenance. Secondly, Analytic Hierarchy Process (AHP)/Analytic Network Process (ANP) are applied to partnership evaluation based on as many as 20 system variables. Relative importance weight of all variables is quantitatively determined. The most investment-worthy variables found are management strength and power. Finally, this paper makes a comparison between the optimum distributors identified by the present procedure and in practical cases. The usefulness and efficiency of the proposed procedure are ascertained with highly consistent results in the comparison.     

层次分析法判断矩阵可靠性探讨

层次分析法判断矩阵中可能会存在相互矛盾的一系列判断元素.通过一个房产评估例子论述这种矛盾造成的原因.为解决这类矛盾,对层次分析法的判断矩阵进行改进:判断矩阵的元素不是通过直接两两比较重要性而得,而是首先按照一定的标准建立评分矩阵,然后对评分矩阵进行矩阵变换形成判断矩阵.根据AHP法改进判断矩阵形成的过程,提出判别层次分析法判断矩阵可靠性的方法.     

我国建筑企业核心竞争力评价体系研究

对建筑企业核心竞争力的理论渊源与内涵特征进行了分析,并通过对国内建筑企业的调研,构建了包括建筑引领能力、建筑整合能力和建筑品牌能力三个方面的建筑企业核心竞争力评价指标体系.在此基础上,运用层次分析法(AHP)和模糊综合评判方法(FCE)建立了建筑企业核心竞争力评价模型,并以实例为证,为建筑企业有效的识别与评价其核心竞争力提供了理论依据.     

模糊数学在企业创新能力评定中的应用

建立了企业创新的系统结构图,并利用模糊综合评价法建立了一个对企业创新能力进行评定的三级模糊综合评判的数学模型,采用层次分析法更加合理的确定了权重的分配,通过实例说明了该模型的使用方法,得到了更有效的结果.     

AHP-based synergy allocation to the partners in a merger

Many corporations try to overcome vulnerabilities by external alliances with other corporations. This paper concentrates on the merger case in member states of the European Community under the premise that synergies are to be expected from such a transaction. In this context synergy will be understood as the difference between the capitalized earning power of the merger firm and the sum of the capitalized earning powers the companies could expect when operating alone. This article presents a method to allocate the financial effect to the partners in a merger. Based on the formal procedure of the Analytic Hierarchy Process, the method allocates synergy to the partners according to the impact intensities of their performance potentials on this synergistic effect.     

企业选择SaaS 供应商的决策及实例研究

选择合适的SaaS供应商是很多企业信息化顺利进行的保障．本文建立了合理的SaaS供应商选择评价指标体系及SaaS供应商选择的多层次评估模型,阐述了基于层次分析法综合评估SaaS供应商的过程,并将该方法应用于某一企业,选择出了恰当的SaaS供应商．     

ANP application for evaluating Turkish mobile communication operators

The proposed decision model, based on Analytic Network Process (ANP), has been developed in order to determine the dynamics of the Global System for Mobile Communications (GSM) market. In accordance with the sequence of ANP, first of all, the problem was structured and modeled. At the next step, a quantitative analysis was conducted with the customers in order to assess the importance of the related factors and forecast the market shares of the Turkish mobile communication operators. The forecasted market share values were compared with actual ones for the validation of the decision model. The assessed importance of the factors in a valid model would be a potential competitive advantage for the mobile operators.     

模糊广义判断矩阵的一致性检验及合成排序

决策评价过程中往往包含诸多不确定性、随机性和模糊性,广义判断下的ＡＨＰ－ＧＪＡＨＰ是一种广义ＡＨＰ,Ｆｕｚｚｙ 环境下的ＧＪＡＨＰ决策方法是应用集值统计的方法,在区间判断标度基础上确定模糊判断矩阵元素的正模糊数表示,并根据模糊集理论的扩展原理,求得Ｆｕｚｚｙ 环境下的模糊排序权值向量。本文给出模糊广义判断矩阵的一致性定义,讨论了各类判断形式条件下的一致性检验法与Ｆｕｚｚｙ 环境下递阶层次结构中的合成排序问题     

基于广义判断形式的模糊排序方法

广义判断下的ＡＨＰ（ＧＪＡＨＰ）是一种广义ＡＨＰ。它是在研究不完全信息下的决策排序问题时，通过构造广义判断矩阵的数学模型而建立的一种广义ＡＨＰ。本文应用集值统计的方法，在区间判断标度基础上确定模糊判断矩阵元素的正模糊数表示。给出了基于模糊区间数排序权值向量的特征根算法。讨论了Ｆｕｚｚｙ环境下求解各种判断形式的模糊排序权值向量的方法。     

Integrated Fuzzy AHP–TOPSIS for selecting the best plastic recycling method: A case study

Due to the rapid depletion of natural resources and undesired environmental changes in a global scale, it is necessary to conserve the natural resources and protect the environment. Industries which manufacture plastic based products have the necessity to recycle plastics. There are number of methods to recycle plastics. Since the selection of the best recycling method involves complex decision variables, it is considered to be a multiple criteria decision-making (MCDM) problem. This article develops an evaluation model based on the fuzzy Analytic Hierarchy Process (AHP) and the technique for order performance by similarity to ideal solution (TOPSIS) to enable the industry practitioners to perform performance evaluation in a fuzzy environment. The purpose of the study is to determine the best method for recycling plastics among the various plastic recycling processes. By observing the results, it is identified that mechanical recycling process is found to be the best plastic recycling process using the integrated approach.     

The impact of DSS use and information load on errors and decision quality

This paper uses a laboratory experiment to examine the effect of DSS use on the decision maker’s error patterns and decision quality. The DSS used in our experiments is the widely used Expert Choice (EC) implementation of the Analytic Hierarchy Process. Perhaps surprisingly, our experiments do not provide general support for the often tacit assumption that the use of a DSS such as EC improves decision quality. Rather, we find that, whereas a DSS can help decision makers develop a better understanding of the essence of a decision problem and can reduce logical error (especially if the information load is high), it is also susceptible to introducing accidental effects such as mechanical errors. In some cases, as in our study, the accidental errors may outweigh the benefits of using a DSS, leading to lower quality decisions.     

Technology selection: application of the PROMETHEE in determining preferences—a real case of nanotechnology in Iran

PROMETHEE (Preference Ranking Organization METHod for Enrichment) is a family of outranking methods. In this paper, we explore its application to technology selection by first providing a generic comparison of PROMETHEE with other ranking methods. We start our investigation by comparing the strengths and weaknesses of PROMETHEE to prevalently used methods in technology selection, such as Analytic Hierarchical Process (AHP), technology selection framework and Fuzzy Analytic Hierarchical Process (FAHP with Fuzzy Delphi). We then explain how PROMETHEE can be applied to a particular technology selection application by detailing the steps for selecting among various nanotechnology application fields. Lastly, we compare PROMETHEE to other methods in this context and explain the advantages and constraints of its use.     

Fuzzy logic modifications of the Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) is a measurement methodology based on pair-wise comparisons that relies on judgment to derive priority scales. During its implementation, one constructs hierarchies, then makes judgments or performs measurements on pairs of elements with respect to a criterion to derive preference scales, which are then synthesized throughout the structure to select the preferred alternative.One of the areas where the AHP finds application is in the subjective phases of risk assessment (RA), where it is used to structure and prioritize diverse risk factors, including the judgments of experts. Since fuzzy logic (FL) has been shown to be an effective tool for accommodating human experts and their communication of linguistic variables, there has been research aimed at modeling the fuzziness in the AHP (FAHP), and recently the focus of some of that modeling has been with respect to RA.The literature discusses more than one FAHP model, which raises the question as to which are the prominent models and what are their characteristics. In response to this question, we examine three of the most influential FAHP models. The article proceeds as follows. It begins with a brief overview of the AHP and its limitations when confronted with a fuzzy environment. This is followed by a discussion of FL modifications of the AHP. A RA-based likelihood score example is used throughout. The article ends with a commentary on the findings.     

基于粗糙集与层次分析法的组合预测方法

本文在改进的属性约简启发式算法 ,即应用加权平均的属性重要度对属性进行约简的基础上 ,将粗糙集理论和层次分析相结合 ,给出了一种全新的组合预测方法 .     

Adapting RRI public engagement indicators to the Spanish scientific and innovation context: a participatory methodology based on AHP and content analysis

The paradigm proposed by Responsible Research and Innovation in the European Commission policy discourse identifies Public Engagement as a key area for exchange and dialogue among multiple actors following an inclusive and participatory process. Two definite set of indicators have already arisen at European level to monitor Public Engagement activities in the Science and Innovation realm. Our study aims to propose a deliberative participatory process, which involves selected stakeholders, for the adaptation of the European indicators to the specific Spanish scientific and innovation context. The methodological procedure is of exploratory nature and will be based in a combination of, on the one hand, qualitative content analysis techniques for the in-depth study of the deliberative process and the generation of indicators; and, on the other hand, a multi-criteria decision analysis technique such as the Analytic Hierarchy Process for the prioritization of the indicators. The discussion will focus on the procedure to articulate stakeholders’ values and use them as the basis for creating a context-based improved list of indicators. Two types of research questions arise: (i) Is the proposed methodology adequate for the adaptation of the European indicators to the Spanish context? (ii) What are the main indicators to monitor and to expand reflection on the public engagement in the Spanish science and innovation?

     

基于模糊综合评判的航空公司战略联盟合作伙伴选择研究

航空公司战略联盟成功的关键是能否选择出理想的合作伙伴,这是一个复杂的决策问题.提出了一个比较新颖的算法.首先根据AHP方法确定模糊评价矩阵和权重向量,并针对航空联盟的敏捷性要求和特定的市场需求,提出了评价指标两两间的比较标度的修正方法,然后通过模糊运算对目标函数进行排序,实现对合作伙伴的最优选择.最后以实例表明本算法能有效的支持伙伴选择.     

层次分析中排序的一种新方法

Saaty提出的特征向量排序方法（EM）已被广泛应用于层次分析（AHP）中。本文提出一种判断矩阵排序的最小扰动性（LPM）,并给出一个收敛性迭代算法和一些算例。LPM在几个重要方面优于EM。理论分析和数据结果表明：LPM是一种可行且有效的排序方法。     

双边投资协定与外商直接投资——基于信号模型的博弈分析

在Jan Peter Sasse(2011)分析的基础上,进一步放宽其假设条件,利用不完全信息下的信号传递模型,对双边投资协定(Bilateral Investment Treaty,BIT)的信号效应机制进行分析.研究发现:BIT作为东道国传递给投资者的信号,该信号有效的条件在于BIT遵守成本的差异,投资者因此有了区分不同类型东道国的依据.东道国之间的引资竞争关系,会不断升级BIT的版本与内容,直至投资环境较差东道国的遵守成本高至无法覆盖签订BIT所带来的投资收益,此时高标准BIT的二次信号有效.此外,在模型拓展分析的基础之上,试图解释了“为何当前高标准BIT已成为各国所关注的对象?以及投资环境越自由的东道国所签订的BIT标准为何越高?”等问题,这对于理解BIT影响外商直接投资的信号机制提供了新的视角与思路.     

The specification of a reference direction using the analytic hierarchy process

In this paper we deal with the use of the Analytic Hierarchy Process (AHP) for specifying a reference direction, which is used to find a search direction in the visual interactive method developed by Korhonen and Laakso for multiple criteria problems. The reference direction describes how the decision maker would like to improve the values of multiple objectives and we show that the AHP is a convenient way to structure requisite preference information.