Two-phase selection framework that considers production costs of suppliers and quality requirements of buyers

Buyers are faced with selecting the optimal supplier, while suppliers are left to consider production costs. In this study, we developed a two-phase selection framework that allows buyers to evaluate the performance of suppliers while taking production costs into account for value maximisation. This scheme is a win-win solution capable of promoting long-term relationships between buyers and suppliers. Under the assumption of normality, the first phase involves constructing a new Six Sigma quality capability analysis chart (SSQCAC) which takes production costs into account. The objective is to evaluate all potential suppliers using the 100?×?(1–α)% upper confidence limit (UCL) of an integrated Six Sigma quality index (SSQI) Q_PIh when dealing with products with smaller-the-better (STB), larger-the-better (LTB), or nominal-the-best (NTB) quality characteristics. According to interval estimation theory, this method can have a significant impact on the consumption of resources; i.e. the production costs of the supplier can be decreased by reducing the production quality to below that required by the buyer. The proposed method also filters out unsuitable suppliers in order to simplify the decision problem and reduce computational demands and operational risks/costs without compromising the quality of the final product. In the second phase, a detailed analysis is conducted using Euclidean distance measure to select the optimal supplier from among the remaining candidates. We conducted a real-world case study to evaluate the efficacy of the proposed method. We also conducted comparisons with existing methods to demonstrate the advantages of the proposed method and its managerial implications. Suggestions for future study are also provided.     

A branch-and-bound algorithm for the concave cost supply problem

Effective supplier selection and allocation of order quantity among multiple suppliers are indispensable to the success of a manufacturing company. While companies have begun to turn into a comprehensive multi-criteria approach, most buyers still consider purchasing cost to be their primary concern in selecting their suppliers. In this paper, we consider the concave cost supply problem where a manufacturer seeks to select the suppliers and simultaneously procure the quantity of material/component required for production at the minimum total cost during a standard production period. We provide and validate an effective and efficient branch-and-bound algorithm that is finite and that finds the global optimal solution of the problem without any restrictions on the cost functions or on the set of input parameters used in the problem. Numerical experiments are conducted to evaluate the performance of the proposed algorithm.     

Inventory decision-making models for a closed-loop supply chain system

In this paper, we investigate how buyers’ and suppliers’ distinct perceptions of technology uncertainty affect the relationship between communication frequency and supplier performance. Information processing theory suggests that a fit is desirable between perceived environmental uncertainty and the communication processes between organisations. However, if partners in a buyer-supplier relationship do not concur on the high level of technology uncertainty, it is highly questionable whether increased communication will be effective in increasing supplier performance. Using dyadic data from 86 buyer-supplier relationships, involving 388 respondents, we found that communication frequency was positively related to supplier performance only when both suppliers and buyers perceived high levels of technology uncertainty. When buyers perceived greater technology uncertainty than their suppliers, communication frequency was negatively related to supplier performance. The findings in this study show that it is important to take the distinct perceptions of buyers and suppliers of technology uncertainty into account when assessing the effects of communication frequency. It appears that increased communication is only effective when both parties acknowledge the need to communicate, and can be unfavourable when only one party sees the benefits of it.     

Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach

This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.     

Co-procurement: making the most of collaborative procurement

While the procurement decision is generally made by individual buyers, this study investigates how a group of buyers can make a shared decision. We call this collaborative approach, co-procurement. A mathematical model is formulated for the decision of procurement from multiple suppliers. The model is solved for individual buyers. The outcome shows the optimal number of items a buyer should buy from different suppliers such that the total cost is minimised for that buyer. Next, it is investigated how a group of buyers could make this decision together. The proposed model takes into account transaction costs of collaboration, to determine the optimal size of the collaboration and the involved parties. The idea is new in the old direction of procurement and it introduces the concept of transaction costs in this area and analyses its impact on the optimal collaboration size and mix. A case study from Dutch Food Valley is provided to investigate the benefits of co-procurement and validate the developed structure. The results indicate that co-procurement can bring considerable cost-savings through consolidation of orders and more efficient transportation schedules. A sensitivity analysis is conducted to determine the impact of changes in the transaction cost in favour of the co-procurement.     

Using integrated fuzzy DEMATEL and fuzzy C: means algorithm for supplier evaluation and selection

Decision-making techniques are used to help evaluate the current suppliers’ aim at classifying performance of individual suppliers against desired levels of performance, so as to design suitable plans to increase the performance and capabilities of suppliers. In this study, an integrated model is introduced and proposed for increasing the supplier selection and evaluation quality. The methodology is composed of two steps. The first stage is fuzzy decision-making trial and evaluation laboratory method in which the interactions between the evaluation criteria and the criteria weight have been computed. At the second stage, performances of suppliers are assessed using both the criteria weights obtained at the first stage and fuzzy c-means clustering algorithm by classifying the vendors according to their performances. Obtained results show that the proposed model is very well suited as a decision-making tool for supplier selection decisions.     

Collaboration in humanitarian supply chains: an organisational culture framework

The purpose of this study was to determine the impact that institutional logics and, more specifically, organisational culture can have on humanitarian supply chain (HSC) collaboration. A framework was developed that explicates buyer–supplier collaboration in a humanitarian setting. Twenty-nine semi-structured interviews were conducted with buyers and suppliers. The data indicated that in a HSC, collaborative outcomes, such as new product development, inventory management, and product/service delivery, are influenced by the buyers’ and suppliers’ organisational cultures. Based on suppliers’ characteristics, they can be classified as humanitarian suppliers, commercial suppliers, and humanitarian and commercial suppliers. These groups have distinct organisational cultures. An unexpected finding is that suppliers that serve commercial buyers primarily claim to have encountered no issues in supply chain collaboration with humanitarian buyers, although they have different types of organisational cultures. The factors that lead to successful collaboration are identified as trust, commitment, information sharing and mutual respect. Simultaneously, dominant institutional logics are observed in the dyadic relationship.     

基于BP神经网络和DEA的物流供应商选择

把交叉模型的评价结果设定为样本的期望值,将BP神经网络和交叉评价模型有机结合起来,构建了物流供应商选择模型。以2006年22家上市物流供应商的数据为样本进行了研究。该方法从统计数据出发,避免了主观因素对评价结果的影响,使物流供应商选择结果具有相对客观性。实例表明,该选择模型能够确定出备选物流供应商的评价等级和大小,为物流供应商的选择提供了一种新方法。     

Effect of delivery timing interaction and disasters on co-supplier evaluation

Most supplier evaluation and selection models found in the literature evaluate candidate suppliers individually on various dimensions such as price, quality and delivery timing. Combinations of suppliers used together are modelled as linear combinations of the individual suppliers’ characteristics on each relevant dimension. The existing models are contextual in that they incorporate factors of importance to the buyer. However, they do not consider the interaction between co-suppliers and the interaction between the suppliers’ characteristics and the ordering policy used by the buyer. The present paper proposes a set of stochastic models that explicitly incorporate these interactions. Computational experiments are performed and the results reported. The results show that taking into account the ordering policy and the interaction effects it can induce can lead to co-supplier evaluations that can differ significantly from those obtained from existing models that do not consider these effects.     

Maintenance supplier selection considering life cycle costs and risks: a fuzzy goal programming approach

In this study, we address a new variant of supplier selection problem named maintenance supplier selection problem faced by a manufacturer. The production system consists of different multi-component equipments whose maintenance activities require several components (parts) each of which could be provided by multiple suppliers. A multi-objective mathematical model is developed to decide about the supply base of each part as well as the purchasing quantity of each part from each selected supplier. The model accounts for the total life cycle costs of purchased parts and various risks threatening the candidate suppliers. A fuzzy/soft lexicographic goal programming approach with soft priorities between objectives is proposed to enable the decision-maker to make preferred trade-offs between objectives by which the effects of various risks in each phase of life cycle of procured parts are investigated. The capability and effectiveness of the proposed model is validated through a case study. Some sensitivity analyses are also carried out for investigating the impact of cost, risk and objectives’ priorities on the final preferred compromise solution. Finally, some managerial insights and concluding remarks are provided.     

Decision model for partnership development in virtual enterprises

A virtual enterprise has been considered as a temporary consortium of companies. Recently, researchers have investigated virtual enterprises from various perspectives, such as business activities and workflows, information exchanges and their standards, organizational behaviours between companies, etc. However, real collaborative activities among companies in a virtual enterprise cannot be done before a partnership is developed among companies. Besides, though partnership is important in virtual enterprises, a decision model for partnership development is seldom studied. This research develops a decision model from a micro view (i.e. from a company's perspective). A company may use the model to specify its current partnership strategy and determine its future partnership strategy with another company. Four factors are considered in the model: the format of the relationship with suppliers, the number of suppliers, the type of service provided by suppliers and the method of service delivery from suppliers. However, a partnership strategy has to be updated based on internal and external changes. This research finds out that six factors are associated with a change on partnership. With those factors, a decision process is developed for a company to update its partnership strategy. The partnership of IBM to Acer is also investigated to illustrate the application of the model. The results validate the applicability of the decision model.     

Supplier selection by testing the process incapability index

In the competitive global business environment of the 21st century, enterprises must respond effectively to customer demands. The selection of suppliers and the evaluation of their performance are becoming major challenges that face manufacturing managers. Assessing a group of suppliers and selecting one or more of them is a complex task because various criteria must be considered in the decision making process. Quality is an essential factor in qualifying a corporation to enter the marketplace. In fact, the quality of parts obtained from suppliers determines the quality of the finished product. Hence, quality is the fundamental factor for supplier evaluation among various criteria. This study applies the process incapability index C_pp to develop an evaluation model that assesses the quality performance of suppliers. The model simplifies the evaluation of suppliers, facilitates their effective selection, and provides insights into the process situation of suppliers who may enter into a long-term partnership with a company.     

Consignment and vendor managed inventory in single-vendor multiple buyers supply chains

In this paper we model a consignment (CS) and vendor-managed inventory (VMI) policy for a single vendor and multiple buyers supply chain with known demand. We study three vendor–buyers partnerships: (i) the vendor and the buyers act independently, (ii) the vendor enters in a vendor-managed inventory consignment (VMI&CS) partnership with the buyers and (iii) the vendor and the buyer belong to a vertically integrated firm where a single decision maker decides about the ordering policies. We use relationships (i) and (ii) to study the benefits of the VMI&CS agreement. We provide analytical and numerical results. We find that such an agreement is more beneficial when the vendor has a flexible capacity. It is also more attractive to buyers when they have significant order costs and the vendor's setup cost is not large. Finally we find that under VMI&CS the vendor will tend to make more frequent shipments with smaller lots.     

A four-phase AHP–QFD approach for supplier assessment: a sustainability perspective

Recently, companies have become increasingly aware of the need to evaluate suppliers from a sustainability perspective. Introducing the triple bottom line (economic, social, and environmental performance) into supplier assessment and selection decisions embeds a new set of trade-offs, complicating the decision-making process. Although many tools have been developed to help purchasing managers make more effective decisions, decision support tools, and methodologies which integrate sustainability (triple bottom line) into supplier assessment and selection are still sparse in the literature. Moreover, most approaches have not taken into consideration the impact of business objectives and requirements of company stakeholders on the supplier evaluation criteria. To help advance this area of research and further integrate sustainability into the supplier selection modelling area, we develop an integrated analytical approach, combining Analytical Hierarchy Process (AHP) with Quality Function Deployment (QFD), to enable the ‘voice’ of company stakeholders in the process. Drawing on the sustainable purchasing strategy development process, our AHP–QFD approach comprises four hierarchical phases: linking customer requirements with the company's sustainability strategy, determining the sustainable purchasing competitive priority, developing sustainable supplier assessment criteria, and lastly assessing the suppliers. An illustrative example is provided to demonstrate the application of the proposed approach.     

A genetic algorithm based grey goal programming (G3) approach for parts supplier evaluation and selection

The problem of part supplier selection is a major concern for all manufacturers when seeking to enhance the products’ quality and productivity. The objective of this paper is to propose an integrated genetic algorithm based grey goal programming (G³) approach to solve the part supplier selection problem. The main factor in part supplier selection is the assembly relation of the parts so as to find the suitable suppliers combination for the parts of a product. We first identify the main factors affected on supplier selection. We then present a grey-based goal programming model to work as the fitness function to evaluate the suppliers with respect to the total deviation the factors have from the ideal values. Since the objective is to find the best solution, a genetic algorithm is used to solve this problem for faster and better evaluation. The novelty of this integrated approach is to apply both qualitative and quantitative factors at once in one model and to use the grey theory to cover the lack of information of qualitative factors in order to find a solution in a near real situation.     

Transaction attributes and buyer-supplier relationships in AMT acquisition and implementation: the case of Malaysia

This paper explores how transaction attributes of technology affect differences in the relationship between technology buyers and suppliers. It also examines the impact on performance of different patterns of relationship between technology buyers and suppliers. Data obtained from 147 manufacturing firms in Malaysia are used to test several hypotheses, which were derived from a review of the literature on technology, transaction cost theory and buyer–supplier relationships (BSR). The research results indicate that the higher the level of technological complexity, specificity and uncertainty, the more firms are likely to engage in a closer relationship with technology suppliers. Even though the majority of firms reported improvements in their performance, results indicate that firms demonstrating a closer relationship with technology suppliers are more likely to achieve higher levels of performance than those that do not. It is also shown that with high levels of transaction attribute, implementation performance suffers more when firms have weak relationships with technology suppliers than with moderate and low levels of transaction attribute.     

A utility-driven approach to supplier evaluation and selection: empirical validation of an integrated solution framework

Supplier evaluation and selection (SES) problems have long been studied, leading to the development of a wide range of individual and hybrid models for solving them. However, the lack of widespread diffusion of existing SES models in the industry points to a need for simpler models that can systematically evaluate both qualitative and quantitative attributes of potential suppliers while enhancing the flexibility decision-makers need to account for relevant situational factors. Furthermore, empirical validations of existing models in SES have been few and far between. With a view to addressing these issues, this paper proposes an integrated solution framework that can be used to evaluate both tangible and intangible attributes of potential suppliers. The proposed framework combines three individual methods, namely the fuzzy analytic hierarchy process, fuzzy complex proportional assessment and fuzzy linear programming. The framework is validated through application in a Turkish textile company. The results generated using the proposed framework is compared with the actual historical data collected from the company. Additionally, a feasibility assessment is conducted on the sample supplier selection criteria employed, as well as assessment of the results generated using the proposed model.     

A novel approach for supplier selection based on the Kano model and fuzzy MCDM

This paper proposes a three-phase approach for supplier selection based on the Kano model and fuzzy Multi Criteria Decision-Making. Since the supplier selection problem involves different criteria, quality attributes have been assumed to denote the importance weight of the criteria for supplier selection. Furthermore, to consider the inherent vagueness of human thought, a fuzzy logic has been utilised. Initially, the importance weight of the criteria has been calculated using a fuzzy Kano questionnaire and fuzzy analytic hierarchy process. In the second phase, the Fuzzy TOPSIS technique has been used to screen out in capable suppliers. Finally, in the third phase, the filtered suppliers which are qualified, once again will be evaluated by the same approach for the final ranking. The proposed approach has also been examined in a case study.     

Concurrent process planning and scheduling in distributed virtual manufacturing

With the fast development of the world economy, distributed virtual manufacturing is becoming increasingly important since it can respond rapidly to market changes and make resource sharing more efficient among manufacturing partners. In this environment, partners may be located at different geographical locations, and co-operation among partners is a vital task and thus concurrent planning and scheduling has become a challenging research topic. This paper presents a computerized model that can integrate these manufacturing functions and resolve some of the critical problems in distributed virtual manufacturing, such as virtual cooperation, optimal partner selection, etc. This integration model is realized through a multi-agent approach that provides a practical approach for software integration in a distributed environment. A cost function is proposed and adopted for optimal partner selection in a virtual enterprise, which not only considers a partner's manufacturing capability and process requirements, but also the processing time, partner's location and product due date. Through establishing a virtual manufacturing model in a simulated environment, the proposal was validated with a case study. It shows that the proposed methodology can satisfy the distribution and agility requirements. This approach is able to contribute to the reduction of product cost, improving product quality and shortening lead time, compared to the sequential approach in the normal engineering and production practice.     

A two objective optimisation model for order splitting among parallel suppliers

To correctly split an order among parallel suppliers is one of the most important ways to improve the agility and competitiveness of a supply chain. For this order splitting problem, an evaluation criterion of production load equilibrium among parallel suppliers is introduced and a two objective order splitting model is developed to minimise the comprehensive cost and balance the production loads among the selected suppliers. The procedure of the suppliers’ selection is proposed and non-dominated sorting genetic algorithm (NSGA-II) is applied to find the feasible solution set of Pareto. The simulation results indicate that the proposed model and algorithm is capable of obtaining satisfactory solutions.