供应商竞争关系下的第三方物流融资及物流服务决策

研究第三方物流企业（3PL）在处于竞争关系中的供应商面临资金约束时的融资策略选择问题。考虑由两个竞争关系的供应商和一个零售商构成的两级供应链,3PL企业为供应链提供代采购、物流及融资服务,分别考虑在代采购中向供应商提供融资能够获得价格折扣和代采购中考虑额外资金成本情况下,3PL融资意愿选择,向供应商提供（不提供）融资。建立3PL、供应商和零售商在不同情况下的收益模型,并给出供应商和零售商的最优定价,以及3PL的最优物流服务收费决策,通过比较融资前后各个企业的收益分析3PL参与供应链融资的积极作用。研究发现3PL向处于竞争环境下的资金短缺供应商提供融资能够增加3PL、零售商和供应链整体的收益,且3PL更愿意在考虑自身资金成本的情况下向供应商提供融资,并且供应商之间竞争越激烈,3PL和零售商的获益越大。     

Structured methodology for supplier selection and evaluation in a supply chain

Supply chain management (SCM) is one of the most important competitive strategies used by modern enterprises. The main aim of supply chain management is to integrate various suppliers to satisfy market demand. Meanwhile, supplier selection and evaluation plays an important role in establishing an effective supply chain. Traditional supplier selection and evaluation methods focus on the requirements of single enterprises, and fail to consider the entire supply chain. Therefore, this study proposes a structured methodology for supplier selection and evaluation based on the supply chain integration architecture.In developing the methodology for supplier selection and evaluation in a supply chain, enterprise competitive strategy is first identified using strengths weaknesses opportunities threats (SWOT) analysis. Based on the competitive strategy, the criteria and indicators of supplier selection are chosen to establish the supplier selection framework. Subsequently, potential suppliers are screened through data envelopment analysis (DEA). Technique for order preference by similarity to ideal solution (TOPSIS), a multi-attribute decision-making (MADA) method is adapted to rank potential suppliers. Finally, the Taiwanese textile industry is used to illustrate the application and feasibility of the proposed methodology.This study facilitates the improvement of collaborator relationships and the management of potential suppliers to help increase product development capability and quality, reduce product lifecycle time and cost, and thus increase product marketability.     

集成化服务供应链的物流服务商选择研究

在分析集成化服务供应链的基础上,从客户满意度、服务质量、服务成本、企业资质、协同能力和绿色竞争力六个方面,构建了比较全面客观的物流服务供应商评价指标体系。通过熵权计算出物流服务供应商权值向量和专家打分计算出各个二级指标的权重,构建定性和定量相结合的供应商评价模型,通过综合评价计算出各个物流服务供应商的评价总权值。最后,结合案例说明,建立的服务供应商评价指标体系和综合评价模型能够比较全面地评价供应商,为研究物流供应商选择提供有益参考价值。     

A framework for measuring the performance of service supply chain management

Despite the increasing attention to the service supply chain management by both practitioners and academics, the performance measurement of service supply chains still remains unexplored. Most service firms realize that, in order to evolve an efficient and effective service supply chain, service supply chain management needs to be assessed for its performance. A literature review was conducted on performance measurement issues of service supply chains. This paper develops a framework of service supply chain performance measurement. Based on the strategic, tactical and operational level performance in a service supply chain, measures and metrics are discussed. The emphasis is on performance measures dealing with service supply chain processes such as demand management, customer relationship management, supplier relationship management, capacity and resource management, service performance, information and technology management and service supply chain finance. And to prioritize service supply chain performance measurement indicators to improve service supply chain performance, a methodology based on the extent fuzzy analytic hierarchy process is stressed. The developed framework of service supply chain performance measurement is applied to the hotel supply chain. The results of this study are useful both to practitioners in the service supply chain and to researchers carrying out further studies in the field.     

A novel fuzzy hybrid neutrosophic decision-making approach for the resilient supplier selection problem

The objectives of this study are to mitigate the risk and disturbances to the supply chain, to offer required models for resolving the complex issues that arise, and to maintain the stability of the support system. Also, the uncertain conditions in a supply chain force decision-makers and experts to adopt a fuzzy-based evaluation platform to ensure secure and reliable consequences. The current study proposed a fuzzy neutrosophic decision-making approach for supplier evaluation and selection. The model is composed of a new weight aggregator that uses pairwise comparison, which has not been reported to date. The model uses a Dombi aggregator that is more qualified than other aggregators. The Dombi t-conorms and t-norms have the same properties as those of the general t-conorm and t-norm, which can enhance the flexibility of the information aggregation process via the adjustment of a parameter. A decision-making environment with uncertain conditions and multiple factors is supposed. We applied this approach in a construction company to analyse the suppliers in a resilient supply chain management (RSCM) system using a MABAC (multiattribute border approximation area comparison) tool. The accuracy of the proposed model was examined via sensitivity analysis tests. This study proposes a novel fuzzy-neutrosophic-based approach for resilient supplier selection. The main contributions of this study work are the design, implementation and analysis of a multiattribute evaluation system with respect to fuzzy neutrosophic values. In this evaluation system, a new pairwise comparison is conducted with trapezoidal neutrosophic linguistic variables to determine the importance weights of supplier criteria. Typically, the provision of opinions regarding the qualitative performances of suppliers is a difficult and confusing responsibility for experts and supplier evaluators. Therefore, the proposed approach overcomes this problem by utilizing a pairwise comparison by neutrosophic values and proposes original Dombi aggregation operators for dealing with fuzzy neutrosophic sets.     

A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information

Both academic and corporate interest in sustainable supply chains has increased in recent years. Supplier selection process is one of the key operational tasks for sustainable supply chain management. This paper examines the problem of identifying an effective model based on sustainability principles for supplier selection operations in supply chains. Due to its multi-criteria nature, the sustainable supplier evaluation process requires an appropriate multi-criteria analysis and solution approach. The approach should also consider that decision makers might face situations such as time pressure, lack of expertise in related issue, etc., during the evaluation process. The paper develops a novel approach based on fuzzy analytic network process within multi-person decision-making schema under incomplete preference relations. The method not only makes sufficient evaluations using the provided preference information, but also maintains the consistency level of the evaluations. Finally, the paper analyzes the sustainability of a number of suppliers in a real-life problem to demonstrate the validity of the proposed evaluation model.     

供应商协同能力评价指标体系研究

供应链协同已经成为供应链集团在与其他集团之间日趋激烈的竞争中创造竞争优势的势在必行的现代管理战略,供应商选择对供应链协同至关重要。通过控制进化种群划分与进化过程,利用压缩变异与Gauss变异设计一种组合变异方式,进而提出改进的模糊C-均值聚类遗传算法（IFCMGA）;在初步确定面向供应链协同的供应商评价指标后,利用IFCMGA算法对供应商协同能力评价指标进行分类,构建了面向供应链协同的供应商评价指标体系。结合模糊层次分析法与重要指标筛选法进行指标分析和筛选以及指标体系重构,以为供应商评价与选择提供科学决策依据。     

Application of a hybrid intelligent decision support model in logistics outsourcing

Outsourcing is an increasingly important issue pursued by corporations seeking improved efficiency. Logistics outsourcing or third-party logistics (3PL) involves the use of external companies to perform some or all of the firm's logistics activities. This paper proposes an intelligent decision support framework for effective 3PL evaluation and selection. The proposed framework integrates case-based reasoning, rule-based reasoning and compromise programming techniques in fuzzy environment. This real-time decision-making approach deals with uncertain and imprecise decision situations. Furthermore, the integration of different methodologies takes the advantage of their strengths and complements each other's weaknesses. Consequently, the framework leads to a more accurate, flexible and efficient retrieval of 3PL service providers (alternatives) that are most similar and most useful to the current decision situation. Finally, a real industrial application is given to demonstrate the potential of the proposed framework.     

Supply chain management: a modular Fuzzy Inference System approach in supplier selection for new product development

The critical objectives of purchasing departments include obtaining the product requested, at the right cost, in the right quantity, with the best quality, at the right time, from the right supplier. These goals require effective decisions concerning supplier selection at the early stage of product development. This work provides an application of fuzzy set theory in supply chain management, specifically in supplier selection for new product development. Here, a Fuzzy Inference System is proposed as an alternative approach to handle effectively the impreciseness and uncertainty that are normally found in supplier selection processes. This paper also shows that the proposed decision-making model is applicable to any supply chain system.     

A case based reasoning approach on supplier selection in petroleum enterprises

Petroleum is an important strategic material which is connected with the vitals and safety of the national economy, and the supplier selections are related to the safety of petroleum production and supply. However, the traditional approaches for supplier selections are limited in subjective evaluation of weights, inaccurate assessing rules, and inefficient decision-making. Although most of the current methods are widely applied in corporation management, a more efficient approach needs to be proposed for supplier selection of oil enterprise.This paper summarizes the particular characteristics of the supply chain of Chinese petroleum enterprises, analyzes the limitations of the traditional methods of supplier selection, and brought forward the method based on case reasoning system (CBR) for petroleum enterprises. The method based on data mining techniques which solves three key problems of CBR, includes calculating the weights of the attributes with information entropy in case warehouse organizing process objectively, evaluating the similarities with k-prototype clustering between the original and target cases in case retrieving process exactly, and extracting the potential rules with back propagation neural networks from conclusions in maintenance and revising process efficiently. It demonstrates the advantages, practicability and validity of this method via case study finally.     

考虑碳排放量与数量折扣的闭环供应链网络设计与多目标决策优化研究

由于闭环供应链网络在环境法规、客户压力等方面都受到关注,故供应商选择在供应链管理中更具挑战性,本文所提闭环供应链网络模型可解决上述问题.其中,供应商会提供数量折扣以激励买家购买更多的产品.模型的目标函数是将经济成本与碳排放量降至最低,最大限度提升客户满意度等参数,并确定出最佳的供应商、采购量、运输方式、技术类型、碳排放量、库存量及工厂间运输流量.本研究基于MATLAB R2010a软件包对测试问题进行模型验证及敏感性分析,结果表明:考虑数量折扣后,可显著降低供应链的总成本.随着碳排放成本的上升,供应链的总成本也会随之上升,随之碳减排率也会不断提升.可知该模型具有有效性与实用性,可为供应链网络设计者提供决策依据,为政府制定碳补贴政策实现减排提供理论依据.     

A 3PL supplier selection model based on fuzzy sets

Outsourcing is an increasingly important task pursued by enterprises seeking improved efficiency. Logistics outsourcing, or third-party logistics (3PL), involves the use of external companies to perform some or all of the firm's logistics activities. In this paper, through analyzing the features and role of third-party logistics, for 3PL provider selection, we propose an indicator system and a method for data integration. We also establish a comprehensive evaluation model for 3PL suppliers based on fuzzy sets; furthermore, we propose a compound quantification model based on centralized quantification values, a comparison method based on the synthesis effect, and a 3PL supplier selection model. A real-world case analysis is provided. The results show that the proposed 3PL supplier selection model can effectively integrate decision preferences into decision processes.     

基于供应链的采购管理系统的研究与实现

从供应链和现代ERP两个角度,阐述采购管理在现代企业管理中的重要作用。在比较传统的库存采购和基于订单驱动的准时化采购的区别的基础上,阐明战略伙伴关系在供应链中的重要地位。在分析了供应商选择的诸多主要因素之后,进而给出供应商评价选择中的三个最重要的指标——质量、价格、交货期,最后给出一个基于供应链的采购管理原型系统的总体设计方案。     

An integrated fuzzy TOPSIS and MCGP approach to supplier selection in supply chain management

Supplier selection is an important issue in supply chain management. In recent years, determining the best supplier in the supply chain has become a key strategic consideration. However, these decisions usually involve several objectives or criteria, and it is often necessary to compromise among possibly conflicting factors. Thus, the multiple criteria decision making (MCDM) becomes a useful approach to solve this kind of problem. Considering both tangible and intangible criteria, this study proposes integrated fuzzy techniques for order preference by similarity to ideal solution (TOPSIS) and multi-choice goal programming (MCGP) approach to solve the supplier selection problem. The advantage of this method is that it allows decision makers to set multiple aspiration levels for supplier selection problems. The integrated model is illustrated by an example in a watch firm.     

基于大数据的电网设备供应链溯源管理评价研究

为了加强电网设备质量源头治理,解决设备质量可追溯性问题,实现贯穿设备全寿命周期的全程质量管控。本文从大数据理念出发,首先建立了基于大数据的电网设备供应链溯源管理评价框架模型,指明了电网设备供应链溯源管理评价的技术路线,其次设计采用网络爬虫技术对散落的海量数据进行爬取和处理,从而提取电力设备供应商的信息,然后构建了包含5个一级指标、8个二级指标和两个维度的三级指标的电力物资供应商评价指标体系,分析了指标间的相互关系,最后对如何合理配指标权重进行了探索,对主观赋权法、客观赋权法和模糊综合评价三种权重确定方法进行了对比分析,从而搭建了具有追溯性的电网设备供应链溯源管理评价模型,为电网企业进行供应商的评价优化提供借鉴。     

An intelligent supplier management tool for benchmarking suppliers in outsource manufacturing

A global corporation's supply chain usually consists of enterprises and manufacturers that are graphically dispersed around the world, whereby each company is involved in a wide variety of supply chain activities such as order fulfillment, international procurement, acquisition of information technology, manufacturing, and customer service. However, selecting suppliers based on accumulated experience is not both effective and scientific due to subjective judgment and lack of systematic analysis. Therefore, continuously tracking and benchmarking performance of suppliers and forming an appropriate supplier selection mechanism is one of the crucial activities in supply chain management. This paper presents an intelligent supplier management tool (ISMT) using the case-based reasoning (CBR) and neural network (NN) techniques to select and benchmark suppliers. The development of ISMT and how the CBR and NN techniques are used in benchmarking suppliers during the process of new product development in Honeywell Consumer Products (Hong Kong) Limited are presented.     

基于群决策的供应链伙伴选择与评价过程

分析了供应商选择与评价过程的两个基本阶段静态评价和动态评价,提出了基于群决策的供应链伙伴选择与评价方法,构造了选择矩阵,证明了选择过程的可控性,举例说明了问题的求解过程,结果证明了方法的有效性.     

A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach

This study presents a strategy-aligned fuzzy simple multiattribute rating technique (SMART) approach for solving the supplier/vendor selection problem from the perspective of strategic management of the supply chain (SC). The majority of supplier rating systems obtained their optimal solutions without considering firm operations management (OM)/SC strategy. The proposed system utilizes OM/SC strategy to identify supplier selection criteria. A fuzzy SMART is applied to evaluate the alternative suppliers, and deals with the ratings of both qualitative and quantitative criteria. The final decision-maker incorporates the supply risks of individual suppliers into final decision making. Finally, an empirical study is conducted to demonstrate the procedure of the proposed system and identify the suitable supplier(s).     

Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem

Supplier selection is nowadays one of the critical topics in supply chain management. This paper presents a new decision making approach for group multi-criteria supplier selection problem, which clubs supplier selection process with order allocation for dynamic supply chains to cope market variations. More specifically, the developed approach imitates the knowledge acquisition and manipulation in a manner similar to the decision makers who have gathered considerable knowledge and expertise in procurement domain. Nevertheless, under many conditions, exact data are inadequate to model real-life situation and fuzzy logic can be incorporated to handle the vagueness of the decision makers. As per this concept, fuzzy-AHP method is used first for supplier selection through four classes (CLASS I: Performance strategy, CLASS II: Quality of service, CLASS III: Innovation and CLASS IV: Risk), which are qualitatively meaningful. Thereafter, using simulation based fuzzy TOPSIS technique, the criteria application is quantitatively evaluated for order allocation among the selected suppliers. As a result, the approach generates decision-making knowledge, and thereafter, the developed combination of rules order allocation can easily be interpreted, adopted and at the same time if necessary, modified by decision makers. To demonstrate the applicability of the proposed approach, an illustrative example is presented and the results analyzed.