一体化供应链下的项目采购管理与供应商管理战略

本文针对汽车行业讨论了产品项目开发中采购管理的重要作用,根据目前项目采购中暴露出的问题,总结出项目采购管理其实质即为对供应商战略管理的理念,从而提出在一体化供应链下项目采购管理中对供应商管理的战略模型。该模型包括四个路径:"构造供应商库,选择和评价供应商,供应商参与项目开发,定义目标供应商平台",并体现如何应用该模型以提高一体化供应链的竞争性。     

跨国公司采购面临的问题与对策探讨

随着跨国公司在全球运作的不断发展，跨国公司的采购工作也日益全球化。分析了跨国公司的采购在材料总成本、转移价格、供应商关系及采购管理等方面所面临的问题，并针对这些问题提出了一些对策，如开展发本地供应商，建立适当的供应方式、有效的采购组织和新型供应商关系等等。     

基于损失成本理论的供应商持续改进评价

利用质量成本理论中的损失成本理论，将供应商所导致的损失成本作为评价供应商绩效的标准。通过ABC分析，发现了供应商和供应商主要问题之所在，对供应商自身以及供应商之间作了比较评价，以促使供应商的持续改进。     

中国造船工业供应商评价指标体系与管理体制构建

对于中国造船企业，构建完整的供应商管理体系是其从分散型采购体系向一体化采购体系整合的关键步骤之一。本文主要针对中国造船工业供应商管理的特点以及所存在的不足，将质量、交付能力、价格、服务能力和持续改进这5个定量评价指标与供货商关系指标和供货商管理能力指标这2个定性评价指标相结合，运用AHP法，构建了造船行业的供应商评价指标体系，并依据这一指标体系，构建了与造船行业集中化采购体系相适应的供应商管理体制。     

绿色采购环境下的供应商选择研究

本文从绿色采购角度出发,构建了供应商的选择评价指标模型,同时运用层次分析法进行了求解,证明了该方法解决绿色采购环境下的供应商选择问题的有效性和可行性。     

土建项目供应商管理的问题与对策分析

运用采购管理、供应链管理、供应商评价理论,通过对项目采购管理现状的深入调查,从提高企业核心竞争力,降低项目采购成本的目的出发,分析指出了存在于项目供应商管理中的问题,得出了在供应商选择和关系管理方面、项目采购管理规章制度方面等项目采购管理方面存在不足。应用先进理论与本单位实际情况结合得出了完善规章制度及队供应链理论为基础的供应商关系管理实施。     

军品包装供应商评价指标体系和方法研究

目的 为了实现快速响应、可靠高效的装备（器材）和物资保障,提高军事物流整体质量,对军品包装供应商进行科学管理。方法 构建军品包装供应商的筛选模型,确立评价指标体系,提出一种集历史、现状和未来为一体的新的综合评价方法,并进行算例验证。结果 通过采用科学的评价方法,对军品包装供应商进行综合评价和遴选,解决了军品包装产品筹措和采购环节由于供应商引起的不确定性问题,使军品包装产品质量得到了有效保证。结论 建立军品包装供应商选择和评价体系,是加强供应商管理的重要基础,也是现代军事物流的重要内容,对推动军品包装发展有重要意义。     

基于贝叶斯方法的包装企业供应商评价与选择模型

目的建立基于贝叶斯方法的供应商选择模型。方法建立一个供应商选择动态过程,将供应商的历史信息与供应商提供的自身信息联系起来;利用贝叶斯方法对供应商达成采购企业目标的能力进行评判和修订,并进一步评估供应商风险。结果贝叶斯方法为包装企业评价和选择供应商提供了规避风险的有效手段,可以提高包装企业的竞争力。结论基于风险视角下的供应商选择与评价模型,是保证包装企业在控制供应商风险的前提下对供应商进行选择评价的重要工具。     

与供应商的采购合作关系分析

对与供应商的采购合作关系进行了初步的分析，通过需求分析、选择供应商、正式建立合作关系、实施和加强合作关系4个过程展开，分别对筛选战略、供应管理计划流程、供应商的评估和选择、认证管理等关键问题进行初步分析，旨在使采购工作趋于完美。     

物资招标采购中组合预测的线性规划方法

结合企业在物资招标采购中大批量订货时,对物资采购量的供应商合理分配及采购费用问题,利用灰色预测法、自适应滤波法及线性回归预测法进行组合预测确定物资采购量,运用层次分析法确定供应商相应权重的基础上建立线性规划模型,力图达到采购的合理分配和采购费用最低的目的.因此,对于解决企业大批量物资采购招标中供应商的合理分配及供应量的确定,以达到企业采购成本最小化的问题,提出了一种有效的方法.     

A comparison of stochastic dominance and stochastic DEA for vendor evaluation

Vendor selection involves decisions balancing a number of conflicting criteria. Data envelopment analysis (DEA) is a mathematical programming approach capable of identifying non-dominated solutions, as well as assessing relative efficiency of dominated solutions. A simple multi-attribute utility function can be applied to a small set of alternatives, providing a tool to assess relative value, but is subject to error if estimated measures are not precise. This paper compares stochastic DEA with a multiple-criteria model in a vendor selection model involving multiple criteria, reporting simulation experiments varying the degree of uncertainty involved in model parameters.     

Enterprise risk management: a DEA VaR approach in vendor selection

Enterprise risk management (ERM) has become an important topic in today's more complex, interrelated global business environment, replete with threats from natural, political, economic, and technical sources. The development and current status of ERM is presented, with a demonstration of how risk modelling can be applied in supply chain management. Within supply chain management, a major managerial decision is vendor selection. We start with discussion of the advanced ERM technology, i.e. value-at-risk (VaR) and develop DEA VaR model as a new tool to conduct risk management in enterprises. A vendor selection set of data is used to demonstrate how this model can be used to assess supply risks in ERM. Such models provide means to quantitatively improve decision making with respect to risk.     

Vendor selection problem: a multi-criteria approach based on strategic decisions

Many factors in the current scenario have influenced manufacturing organisations to have a competitive edge by concentrating on entire supply chains. Sourcing decisions are one of the strategic decisions because they enable companies to reduce costs and improve profit figures. The main task in sourcing is vendor selection. Recent challenges such as shortened product life cycle, just-in-time environment, and the importance of strategic partnerships in upstream chains always influence companies to prioritise vendor selection. In addition, outsourced parts and components account for a significant contribution in the cost of finished goods. Thus evaluating and selecting the right vendor is the key to business. Vendors are selected merely on the basis of cost factors in the traditional approach. However, companies eventually have understood that their approach which emphasises costs as the sole criterion is inefficient and needs to be changed. To deal with the complex process of vendor evaluation, multiple criteria decision-making techniques have evolved. This study presents the integrated approach of multiple multi criteria decision making (MCDM) techniques such as fuzzy logic, strength-weakness-opportunity-threat (SWOT) analysis, and data envelopment analysis. The efficacy of the proposed approach is evident from the case study of an automotive component manufacturer involving 20 vendors, comprising of pre-qualification by fuzzy SWOT and final selection by DEA.     

Value-at-risk and data envelopment analysis: comments on Wu and Olson (2010)

In this note, we identify three major errors contained in Wu and Olson [Wu, D.D. and Olson, D., 2010. Enterprise risk management: a DEA VaR approach in vendor selection. International Journal of Production Research, 48 (16), 4919–4932]. It is shown that the ‘DEA VaR’ model named by the authors is not truly a Value-at-risk (VaR) minimisation problem. It is also pointed out that the authors confused two concepts of stochastic efficiency. Finally, it is revealed that the linearisation technique proposed by the authors is questionable under some conditions and a correction is suggested.     

基于模糊决策的供应商选择方法

在分析建立供应商评价指标体系所应遵循的三大原则的基础上，提出了一套供应商评价指标体系。由于供应商选择问题中包含大量的不确定和模糊因素，为此将模糊集合论的思想和方法引入供应商评价中，建立了供应商模糊评价模型，最后给出实例予以验证。     

一种多阶段供应商选择的混合整数规划模型

在建立供应链合作伙伴关系中,供应商的选择是供应链管理的一项重要内容.在现有文献的基础上对供应商的选择模型进行了改进,建立了集成单阶段与多阶段供应商选择的混合整数规划模型:既可以选择单阶段供应商,也可选择多阶段供应商即供应商的供应商的供应商等等.在模型中考虑了每个潜在供应商的能力约束,以供应商在产品价格、质量、配送水平等三个方面引起总的客户不满意度最小化作为选优的依据.     

Vendor selection in a modified re-buy situation using a strategy-aligned fuzzy approach

The supplier/vendor selection is a decision-making problem at the strategic management level that involves a semi-structured process. The majority of the existing approaches obtained their optimal solutions without considering their fits with the strategy of the firm. This study utilizes the supplier positioning matrix, modified from the product-process change matrix, to link the capability of suppliers with the requirements of the customers to identify the strategy-aligned criteria for vendor selection in a modified re-buy situation. A fuzzy factor rating system is then used to evaluate the potential vendors based on the type of components required by the customers. In addition, in the proposed model, the final decision-maker is given the authority to synthesize the scores of individual alternatives based on the risks of individual vendors to accommodate the differences among the vendors to the specific environment. An empirical case study is performed to demonstrate the efficacy of the proposed system and to identify the best potential vendor(s) for further negotiation and development. The results of the case study also provide interesting managerial implications.     

厂商制造伪劣商品原因及对策浅析

本文通过对厂商制造伪劣商品现象的透析,假设厂商具有单一的追求利润的目标函数,提出厂商收益函数,分析厂商选择制造伪劣商品的经济学本质,并得出如下结论:市场信息不流畅造成的买方卖方信息不对称,交易成本过高,地方政府的地方保护主义,以及消费者在一定程度上处于弱势地位都是某些厂商选择制造伪劣商品的重要原因。     

A new approach for the selection of advanced manufacturing technologies: DEA with double frontiers

Selection of advanced manufacturing technologies (AMTs) is an important yet complex decision which requires careful consideration of various performance criteria. This paper proposes the use of data envelopment analysis (DEA) with double frontiers for the selection of AMTs, which considers not only the best (optimistic), but also the worst (pessimistic) relative efficiencies of each AMT. Compared with the traditional DEA, the DEA approach with double frontiers can identify the best AMT correctly and easily without the need to impose any weight restriction or the need to calculate the cross-efficiency matrix, which requires a large number of computations and may also result in inconsistent conclusions by aggressive and benevolent cross-efficiency models. Four numerical examples are examined using the DEA approach with double frontiers to illustrate its simplicity and usefulness in AMT selection and justification.     

An innovation funnel process for set-based conceptual design via DOE exploration,DEA selection and computer simulation

This paper presents a conceptual design approach including pattern creation from designers, alternative exploration with a DOE matrix, alternative analysis via computer simulation and alternative selection by DEA analysis. Designers possessing domain knowledge create various design patterns to meet the requirements of product performance and customer expectations. Then, based on these design patterns, the alternatives, considered as decision-making units (DMUs), are extracted from various quality level combinations by following the use of the DOE matrix. The nature of the DOE matrix ensures that distinctive representatives are constructed for all design alternatives. The total alternatives (DMUs) consist of the alternatives associated with all the patterns. Computer simulation with ANSYS software is introduced to convert the quality level combination of each alternative (DMU) into simulated outputs, which are further categorised into DEA inputs and DEA outputs for DEA frontier analysis. Four DEA methods, CCR-min input, CCR-max output, BCC-min input and BCC-max output, are used for analysing typical market representatives resulting from market uncertainty. The found efficiencies are used to rank and select the explored alternatives (DMUs) for the next stage of the detailed design. A bike-frame product is chosen as an example to demonstrate the proposed approach. The results clearly show that the proposed approach enables designers to economically select appropriate design alternatives that satisfy performance expectations during the conceptual design stage.