Multiple Criteria Hierarchy Process with ELECTRE and PROMETHEE

Robust Ordinal Regression (ROR) supports Multiple Criteria Decision Process by considering all sets of parameters of an assumed preference model, that are compatible with preference information elicited by a Decision Maker (DM). As a result of ROR, one gets necessary and possible preference relations in the set of alternatives, which hold for all compatible sets of parameters, or for at least one compatible set of parameters, respectively. In this paper, we propose an extension of ELECTRE and PROMETHEE methods to the case of the hierarchy of criteria, which was never considered before. Then, we adapt ROR to the hierarchical versions of ELECTRE and PROMETHEE methods.     

组合评价方法在银行信用风险评价中的应用

针对贷款客户评价选择问题,在对已有研究方法分析的基础上,提出了以熵权与偏好顺序结构评估法相结合的排序方法。以借贷人的财务状况、借贷人的管理水平、借贷人的行业地位、借贷人资产的变现性和借贷人历史信用状况为评价准则,利用信息熵来确定评价准则的权重,用偏好顺序评价法确定贷款客户的贷款顺序,并进行了灵敏度分析。最后通过算例证明了该方法的有效性。     

基于区间数的PROMETHEE Ⅱ方法中权重确定

本文引入一种新的区间数距离测度,扩展了可直接处理特征空间为区间数的PROMETHEE Ⅱ多属性决策方法。并在分析属性加权向量ω与最终综合优先序值之间关系的同时,提出了一种基于区间数的PROMETHEE Ⅱ方法的属性权重ω确定原理。应用实例表明了该方法的可行性和有效性,具有推广应用价值。     

Application of hybrid framework to facilitate lean six sigma implementation: a manufacturing company case experience

This study aims to propose a hybrid framework for lean six sigma (LSS) based on the prioritisation of barriers and solution approaches, to facilitate hassles free applications for handling the challenges of wastes reduction and quality improvement. The study identifies 27 LSS barriers and 22 solution approaches through literature review and utilises feedback from industry experts. For framework, study uses fuzzy AHP-PROMETHEE to prioritise LSS barriers and solution approaches. Incorporating fuzzy sets in analytical hierarchy process (AHP) ensures the optimality of barrier weights. Whereas, preference ranking organisation method for enrichment of evaluations (PROMETHEE) helps in pairwise comparisons of solution approaches with respect to each LSS barrier, facilitating fair judgements. This research guides regarding the development of framework and checks its suitability and robustness through case application of an Indian manufacturing organisation. Authors expect that researchers and practitioners will find study useful for LSS and multi criteria decision making(MCDM) domains.     

Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain

The food sector has a prodigious focus and is constantly gaining in importance in today’s global economic marketplace. Due to an increasing global population, society faces a greater challenge for sustainable food production, quality, distribution, and food safety in the food supply chain. Adopting green supply chain management (GSCM) elements is essential for utilizing the food supply chain in an environmentally benign way. As a solution to the above challenge, the economic and green characteristics for supplier selection in green purchasing are studied in this paper. For an organization, the evaluation and selection of the green supplier is a vital issue due to several tangible and intangible criteria involved. Accordingly, we apply multiple criteria decision aiding techniques.We propose a hybrid approach that combines the revised Simos procedure, PROMETHEE methods, algorithms for constructing a group compromise ranking, and robustness analysis. At first, the revised Simos procedure is used to derive the criteria weights. Next, the PROMETHEE method is applied to rank the suppliers according to each Decision Maker׳s (DM׳s) preferences. Then, the compromise ranking is constructed to minimize the distance of the individual׳s rankings from the solution adopted by the whole group. For this purpose, we introduce and apply some original procedures based on Binary Linear Programming. Finally, the results are validated against the outcomes of robustness analysis. The applicability and efficiency of the proposed approach is endorsed with a case study in an Indian food industry.     

产业集群参与者交互偏好与知识网络演化:模型与仿真

知识网络是产业集群网络演化的重要组成部分和先决条件,本文将产业集群中参与者进行交互的偏好分为任务导向型和知识导向型,建立了一个基于多智能主体的产业集群知识网络模型,利用Blanche软件实现了知识网络演化模型的仿真计算,通过仿真研究了任务导向型和知识导向型知识网络的对网络演化的不同影响.最后,本文提出了研究的局限性和下一步研究的方向.     

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。     

The market for genetically modified foods: consumer characteristics and policy implications

Conjoint analysis was used to explore consumer preferences for food products that are the product of genetically modified organisms (GMOs). The results of a cluster analysis indicated that consumers fell into three homogeneous groups based on their preference for a branded, low-priced, or GMO-free product. There were some differences between the segments based on the sociodemographic characteristics of age, education, and income. However, consumers in the segment that wished to avoid GMOs were most easily distinguished from consumers in the other two segments based on their high level of risk averseness and belief that GMOs do not positively affect the quality or safety of food products. Implications for food marketers and policymakers are discussed.     

Best Nonparametric Bounds on Demand Responses

This paper uses revealed preference inequalities to provide the tightest possible (best) nonparametric bounds on predicted consumer responses to price changes using consumer‐level data over a finite set of relative price changes. These responses are allowed to vary nonparametrically across the income distribution. This is achieved by combining the theory of revealed preference with the semiparametric estimation of consumer expansion paths (Engel curves). We label these expansion path based bounds on demand responses as E‐bounds. Deviations from revealed preference restrictions are measured by preference perturbations which are shown to usefully characterize taste change and to provide a stochastic environment within which violations of revealed preference inequalities can be assessed.     

基于风险规避和公平偏好的供应链收益共享契约协调研究

在一个简单的二级供应链系统中,建立了供应商和零售商同时具有风险规避和公平偏好的收益共享契约协调模型,通过修正、扩展FS效用收益模型,先后考察并分析了分散决策和集中决策下供应链的协调状态,研究发现,供应商和零售商的风险规避系数和公平偏好系数及收益份额必须满足特定的条件,收益共享契约才能使系统供应链整体达到协调状态;在此基础上,对风险规避和公平偏好因素进行敏感度分析,得到供应商和零售商行为偏好系数对供应链及成员最优订货量的影响;最后进行演化博弈算例分析和结论验证,体现了该协调模型的有效性和实用性。由此说明供应商和零售商的风险规避和公平偏好因素同时作用会改变系统供应链协调时的最优订货量,并对决策人的决策行为产生很大的影响。     

The Alignment between Organizational Critical Success Factors and Information Technology Capability in Academic Institutions*

Alignment between organizational critical success factors (CSFs) and competencies is widely believed to improve performance. This study examines the performance implications of alignment between CSFs and one source of competence, the organization's information technology (IT) capability. The effects of three antecedent factors–environmental uncertainty, integration, and IT management sophistication–are also examined. This paper uses survey data from 244 large academic institutions, along with some secondary data. Following the profile deviation approach to measure alignment, the academic institutions are divided into three clusters based on their CSFs: the academic comprehensives, the reputed giants, and the small educators. The ideal profile of IT capability is next developed for each cluster in terms of four dimensions: information retrieval, electronic communication, computing facilities for students, and computer-aided education. Alignment is then computed for each institution as the proximity of its IT capability profile from the ideal IT capability profile for the cluster to which it belongs. The results suggest that alignment facilitates both perceived IT success and organizational performance. Moreover, sophisticated IT management facilitates both alignment and perceived IT success, environmental uncertainty facilitates perceived IT success but not alignment, and integration facilitates neither alignment nor perceived IT success.     

两级供应链中订货延迟的影响分析

基于报童模型,在1个供应商和2个零售商组成的供应链系统中,建模分析了零售商实行订货延迟策略对自身、供应商和供应链系统的利润影响,得出了它们各自的订货时机偏好,并根据服务水平描绘了供应商和零售商的订货偏好区域分布图,由此得到零售商订货时的Pareto最优区域。研究结果表明,在通常情况下供应商希望零售商预订,而零售商喜欢延迟订货,这和现实情况是相符的。结果还表明,在某些情况下零售商延迟订货对自身有利,但对系统不利;当供应商服务水平较高时,零售商延迟订货对自身、对系统都有利。     

信息系统外包决策的AHP/PROMETHEE方法

针对信息系统外包项目优选这一重要问题,在已有方法的基础上,结合层次分析法与偏好顺序结构评估法,提出了一种基于这两种方法相结合的信息系统外包项目选择决策方法。以管理、战略、技术、经济、质量与风险6项因素作为评价准则,用层次分析法确定信息系统外包项目选择问题的层次结构与评价准则的权重,用偏好顺序结构评估法确定信息系统外包项目的排序,并通过算例说明该方法的有效性。     

公平偏好员工的锦标激励研究

传统锦标理论建立在员工是纯粹自利的假设上,而行为合约理论认为员工是具有公平偏好的.本文分析在完全竞争和不完全竞争的劳动力市场和产品市场中,针对具有公平偏好的员工的最优锦标机制设计及产出效率问题.以期为企业劳动舍约的设计提供一种更加接近现实的、可供借鉴的思路.     

基于OWG算子的不同形式偏好信息 的群决策方法

具有不同形式偏好信息的群决策是决策分析及群决策支持系统研究的一个新课题,它对 于进一步提高群决策支持系统的实用性和灵活性方面具有重要意义. 针对这类群决策分析,提 出了一种具有效用值、序关系值、模糊互补判断矩阵、互反判断矩阵等4 种形式偏好信息的群 决策方法. 在该方法中,首先给出了将不同形式的偏好信息均转化为互反判断矩阵形式的计算 公式;然后基于OWG算子将各决策者的偏好信息集结为群的偏好并进行方案的优选;最后给 出了一个算例.     

一种改进型专家模糊核聚类赋权方法研究

针对传统基于判断矩阵的专家模糊核聚类赋权方法，由于归一化条件的制约，导致离群点对聚类结果产生不良影响的问题，提出一种改进型模糊核聚类算法。该方法在聚类过程中，通过放宽归一化约束条件，削弱离群点对聚类结果的影响；并且针对传统基于信息熵与一致性系数线性耦合的聚类标准的局限性，提出一种基于偏差熵的赋权方法，依据专家对自身类别的聚类贡献度，确定专家权重，克服了传统方法的不足。算例表明，该方法可行、有效。     

No‐Betting‐Pareto Dominance

We argue that the notion of Pareto dominance is not as compelling in the presence of uncertainty as it is under certainty. In particular, voluntary trade based on differences in tastes is commonly accepted as desirable, because tastes cannot be wrong. By contrast, voluntary trade based on incompatible beliefs may indicate that at least one agent entertains mistaken beliefs. We propose and characterize a weaker, No‐Betting, notion of Pareto domination which requires, on top of unanimity of preference, the existence of shared beliefs that can rationalize such preference for each agent.     

Neo-Marshallian Clusters and Global Networks: The Linkages of Media Firms in Central London

This paper examines the nature of the external linkages of firms in the media cluster of Central London, and draws implications for the competitive advantages that firms in clusters develop. The analysis suggests that although these firms are strongly embedded in the local cluster and rely heavily on resources and processes available locally, they also maintain linkages that extend well beyond the local cluster. We argue that firms need to identify a successful balance between localised sources of interaction and those residing at wider geographic areas, and to establish linkages at these different geographic scales in order for them to compete successfully.     

基于冲突图模型策略优先权排序法的强度偏好排序研究

冲突分析图模型中强度偏好的引入增加了决策者的感情色彩,进一步丰富了决策者的偏好信息。在强度偏好下运用冲突分析图模型理论对冲突进行建模时,有一个非常重要的问题——强度偏好的排序。本研究首先将简单偏好下的策略优先权排序法扩展到强度偏好;然后以"兰州水污染事件"为例,在兰州威立雅水务公司、地方政府和中石化兰州分公司存在强度偏好的情况下,运用扩展后的策略优先权排序法求取各决策者的强度偏好序列,并对此次水污染事件引发的冲突进行建模、分析,模拟了冲突事件中的谈判和协商过程,求得冲突各方的均衡解,案例分析过程也从战略层面为我国实现经济的可持续发展提供借鉴。     

一种具有不确定偏好序信息的多指标群决策方法

针对具有不确定偏好序信息的多指标群决策问题,给出了一种决策分析方法。在本文中,首先对具有不确定偏好序信息的多指标群决策问题进行了描述;然后给出了将不确定偏好序转换为投票数的计算公式;进一步地,依据Bernardo方法的基本思想,根据每个专家给出的不确定偏好序信息,计算相应的投票数并构建群体投票矩阵,并基于群体投票矩阵构建0-1整数规划模型,通过求解模型可得到方案排序结果。最后,通过一个算例以及与已有方法的对比分析说明了本文给出的方法的可行性和有效性。