An integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation

Purchasing is one of the most vital functions within a company and supplier performance evaluation is one of the most important business processes of the purchasing function. Traditionally, companies have considered factors such as price, quality, flexibility, etc. while evaluating suppliers. However, environmental pressures urge them to consider green issues. This study proposes a decision model for supplier performance evaluation by considering various environmental performance criteria. An integrated, fuzzy group decision-making approach is adopted to evaluate green supplier alternatives. More precisely, a fuzzy analytic hierarchy process (AHP) is applied to determine the relative weights of the evaluation criteria and an axiomatic design (AD)-based fuzzy group decision-making approach is applied to rank the green suppliers. Finally, a case study is given to demonstrate the potential of the methodology.     

Supplier development: communication approaches,activities and goals

Operations managers rely on the purchasing function to obtain production inputs from suppliers and to ensure supplier performance. The link between supplier development activities performed by buying firms with their suppliers, in terms of operational outcomes and impact on competitive advantage for the buying firm has been well documented. However, a buying firm should, prior to setting up a supplier development program and investing in supplier development activities, establish goals it wants to achieve and determine how to achieve these goals. Until now, supplier development goals in general and their relationship with supplier development activities have received little research attention. The results from this empirical study suggest that the relationship between the goal to improve a supplier's capabilities and knowledge transfer from the buyer to the supplier firm is moderated by the degree of human interaction. Buying firms pursuing the strategy to improve supplier capabilities rely more intensively on training and co-location of buyer and supplier employees to leverage the knowledge transfer to the supplier firm.     

Supplier selection for outsourcing from the perspective of protecting crucial product knowledge

This paper considers the supplier selection problem in terms of the characteristics of the products/processes to be outsourced. Emphasis is placed on the possible risk that may arise in sharing or transferring crucial product/process knowledge to suppliers during outsourcing. Two indices are employed to assess the suitability of a supplier for outsourcing a product/process. The first measures the supplier's capability for technological innovation in the products for which they offer outsourcing services, and includes investment in R&D projects and the ratio of R&D personnel to the total work force. The second index measures the supplier's practices in protecting its clients’ intellectual property rights, and includes corporate image, track record in protecting clients’ intellectual property rights, and compliance with internal and external requirements. These two indices are then used to classify suppliers into four major groups, which are in turn assigned to classes of components/processes depending on their strategic importance and vulnerability – a portfolio approach. The proposed portfolio approach has been validated via a substantial empirical study involving data for 401 parts, 216 suppliers, and 36 manufacturing companies operating in China.     

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.     

Bootstrap approach for supplier selection based on production yield

Current manufacturing industries have increased their level of out-sourcing and relied more heavily on their supply chain as a source of competitive advantage. Supplier selection decisions have become an important component of production management. Those decisions have a significant impact on a firm's marketing competition, and suppliers may account for a large portion of the production cost. Production quality is one of the key factors in supplier evaluation. The manual of supplier certification includes a discussion of process capability analysis, which recommends a procedure for evaluating the most prevalent process capability index C _pk. However, the recommended procedure is applicable only when evaluating an individual supplier's performance. In this paper, we apply the bootstrap method to the supplier selection problem. We construct lower confidence intervals for the capability difference and ratio between two given suppliers. Performance comparisons are made among various bootstrap methods in terms of error probability and selection power. For convenience of applications, the sample sizes required for various designated selection power are also tabulated.     

Study on suppliers’ flexibility in supply chains: is real-time control necessary?

In a supply chain, the suppliers’ flexibility is considered as a tool to cope with the environmental uncertainties. Flexible suppliers are capable of supplying/processing other jobs in addition to the one for which they are the original supplier. In a cluster of flexible suppliers, it is expected that flexibility of suppliers be utilized more expressively through better control of the supply chain. The online real-time information system is considered as one of the tools for effective control of the supply chain. However, in a cluster of flexible suppliers, the physical and operating characteristics of alternative suppliers (available by virtue of suppliers’ flexibility) may vary from each other for doing the same operation, which may result in a different lead-time to process the same job. This paper presents a simulation study on suppliers’ flexibility level (SFL) in relation to information system automation level of the supply chain and physical characteristics of the flexible suppliers. This paper contributes an approach for decision-makers to identify the information system automation level and variations in physical characteristics of the alternative suppliers with respect to suppliers’ flexibility level that can help in improving the overall delivery lead-time. A decision-maker can reach a trade-off between benefits obtained from supplier's flexibility and the investment required to have a suitable information system automation level and physical characteristics of suppliers. Results of simulation study show that if automation level of information system is not matching to the suppliers’ flexibility level then supplier's flexibility may become counterproductive. Further, a relative change in physical characteristics of the alternative flexible suppliers as compared to the original supplier is more than a certain limit then suppliers’ flexibility may again be counterproductive. However, a cost intensive real-time information system may not be needed when suppliers’ flexibility levels are lower. Study identifies the productive and counterproductive performance regions for suppliers’ delivery lead-time.     

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.     

A supplier pre-selection model for multiple products with synergy effect

In practice, it is common for companies to purchase multiple products simultaneously. For the multiple required products, a large number of interested suppliers are involved. It is necessary for the purchasing company to shortlist a small number of qualified and competitive potential suppliers prior to finalising the suppliers for order fulfilment. In addition, synergy effect which is an effect arising between two or more products that produce an effect greater than the sum of their individual effects, could exist in the multi-product supplier selection environment. Since synergy effect between products can affect the choice of suppliers, it is also necessary to incorporate the synergy effect between products in the supplier selection for multiple products. However, few research efforts have been focused on the supplier pre-selection problem, let alone explicitly for multiple products with synergy effect. This paper presents a supplier pre-selection model for multiple products with synergy effect. The model is able to evaluate interested suppliers on the multiple pre-selection criteria, by the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based supplier pre-selection algorithm, and shortlist a small number of potential suppliers. Illustrative examples are conducted to demonstrate the function and application of the supplier pre-selection model for multiple products with synergy effect.     

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.     

Pre-selection of suppliers through an integrated fuzzy analytic hierarchy process and max-min methodology

There are a variety of analytical models for supplier selection ranging from simple weighted techniques to complex mathematical programming approaches. However, these models are specifically aimed at supporting a decision maker in a single phase, especially in the final selection phase and they have failed to consider the supplier selection process from a holistic point of view. Although the methodology presented in this paper primarily focused on the prequalification of potential suppliers, the outputs of the previous phases, namely problem definition and formulation of criteria, are used as inputs in this methodology. The methodology utilises a fuzzy analytic hierarchy process (AHP) method to determine the weights of the pre-selected decision criteria, a max-min approach to maximise and minimise the supplier performances against these weighted criteria, and a non-parametric statistical test to identify an effective supplier set. This information supports decision makers in making the final selection with effective alternative choices. Potential application of the proposed methodology is demonstrated in Audio Electronics in Turkey's electronics industry.     

An integrated weighted fuzzy multi-objective model for supplier selection and order scheduling in a supply chain

This paper presents a new weighted fuzzy multi-objective model to integrated supplier selection, order quantity allocation and customer order scheduling problem to prepare a responsive and order-oriented supply chain in a make-to-order manufacturing system. Total cost and quality of purchased parts as well as the reliability of on-time delivery of customer orders are regarded as the objectives of the model. On the other hand, flexible suppliers can contribute to the responsiveness and flexibility of entire supply chain in the face of uncertain customer orders. Therefore, a mathematical measure is developed for evaluating the volume flexibility of suppliers and is considered as the other objective of the model. Furthermore, by considering the effect of interdependencies between the selection criteria and to handle inconsistent and uncertain judgments, a fuzzy analytic network process method is used to identify top suppliers and consider as the last objective. In order to optimise these objectives, the decision-maker needs to decide from which supplier to purchase parts needed to assemble the customer orders, how to allocate the demand for parts between the selected suppliers, and how to schedule the customer orders for assembled products over the planning time horizon. Numerical examples are presented and computational analysis is reported.     

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.     

A model for performance monitoring of suppliers

The purchasing function is central to the strategic operations of effective supply chain management. This centrality is mainly due to the significant impact of material costs on profits, increased investments in inter-organizational advanced manufacturing and information technologies, and a growing emphasis on the just-in-time operations philosophy. The critical business processes of the purchasing function include supplier selection, negotiation of supply contracts, monitoring supplier performance, and acting as an interface between an organization and its suppliers. Within these core processes of purchasing, this paper narrows its scope to focus upon the supplier performance evaluation and monitoring process, which assists in maintaining effective customer-supplier linkages. While price has been traditionally considered as the single most important factor in evaluating suppliers, it has been agreed upon that value performance emphasis needs to include other important factors such as quality, delivery and flexibility. Given this evolving business competitiveness environment, the contribution of this research is threefold. First, it applies a new multi-criteria evaluation model for supplier performance evaluation by considering various performance criteria. Second, a proposed application extension of this model serves as a monitoring and control mechanism for the performance of suppliers, thus supporting continuous process improvement to achieve efficient customer-supplier relationships. Third, the paper presents this technique as a new methodological extension to data envelopment analysis research by improving the discriminatory power of an existing variable returns to scale model. The model and its application are demonstrated through a previously published illustrative case example.     

Global supplier selection: a fuzzy-AHP approach

Global supplier selection has a critical effect on the competitiveness of the entire supply chain network. Research results indicate that the supplier selection process appears to be the most significant variable in deciding the success of the supply chain. It helps in achieving high quality products at lower cost with higher customer satisfaction. Apart from the common criteria such as cost and quality, this paper also discusses some of the important decision variables which can play a critical role in case of the international sourcing. The importance of the political-economic situation, geographical location, infrastructure, financial background, performance history, risk factors, etc., have also been pointed out in particularly in the case of global supplier selection. Supplier selection problem related to the global sourcing is more complex than the general domestic sourcing and as a result it needs more critical analysis, which could not be found properly in past available literatures. This paper discusses the fuzzy based Analytic Hierarchy Process (fuzzy-AHP) to efficiently tackle both quantitative and qualitative decision factors involved in selection of global supplier in current business scenario. The fuzzy-AHP is an efficient tool to tackle the fuzziness of the data involved in deciding the preferences of the different decision variables involved in the process of global supplier selection. The triangular fuzzy numbers are used to transform the linguistic comparison of the different decision criteria, sub-criteria and performance of the alternative suppliers. The pairwise comparison matrices help in deciding the synthetic extent value of each comparison and finally, the priority weights of one alternative over another are decided in this paper. An example from a manufacturing industry searching for the global supplier for a critical component is used to demonstrate the effective implementation procedure of proposed fuzzy-AHP technique. The proposed model can provide the guidelines and directions for the decision makers to effectively select their global suppliers in the current competitive business scenario.     

Sustainable Supplier Selection Model in Supply Chains During the COVID-19 Pandemic

As global supply chains become more developed and complicated, supplier quality has become increasingly influential on the competitiveness of businesses during the Covid-19 pandemic. Consequently, supplier selection is an increasingly important process for any business around the globe. Choosing a supplier is a complex decision that can result in lower procurement costs and increased profits without increasing the cost or lowering the quality of the product. However, these decision-making problems can be complicated in cases with multiple potential suppliers. Vietnam's textile and garment industry, for example, has made rapid progress in recent years but is still facing great difficulties as the supply of raw materials and machinery depends heavily on foreign countries. Therefore, it is extremely important for textile and garment manufacturing companies in Vietnam to implement an effective supplier evaluation and selection process. While multicriteria decision-making models are frequently employed to assist with supplier evaluation and selection problems, few of these models consider the problem under the condition of a fuzzy decision-making environment. The aim of this paper is to create a hybrid MCDM model using the Fuzzy Analytical Hierarchy Process (FAHP) model and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to assist the supplier selection process in the garment industry in a fuzzy decision-making environment. In this study, the FAHP method is used to evaluate the performance and the weight of each criterion. TOPSIS is then used to rank all potential suppliers. The proposed model is then applied to a real-world case study to demonstrate both the process of calculation as well as its real-world applicability. The results from the case study provide empirical evidence that the model is feasible. The proposed approach can also be used in combination with other MCDM models to better support decision makers and can be modified to be applied in similar supplier selection processes for different industries.     

The supplier–buyer integrated production-inventory model with random yield

This paper revisits the traditional supplier–buyer integrated production-inventory model which deals with the problem of a manufacturer (supplier) supplying a product to a retailer (buyer) serving the consumer market with constant stationary demand. The product is manufactured in batches at a finite rate. The supplier's production batch is depleted by the buyer's replenishment orders at periodic intervals. The buyer's inventory is then consumed by the market demand at a fixed rate. The problem is the simultaneous computation of the manufacturer's production lot-size and the buyer's replenishment order quantity, i.e. the integrated production-inventory policy parameters. The key characteristic considered in this paper is that the manufacturing process is imperfect, and, hence, there are defective items in each production lot. As a result, each replenishment order shipped to the buyer includes defective products and the non-defective percentage in each such shipment is random. Considering the case where the supplier replenishes the buyer via equal-sized shipments, we develop an analytical expression of the total expected cost for the supplier–buyer system under consideration, with and without a considerable inspection time. We first examine the case where the inspection time is negligible, and then we present a generalisation to consider the inspection time explicitly. Our goal is to model the impact of random yield on the system performance. Our findings are useful for computing the integrated production-inventory policy parameters while considering the supply uncertainty due to an imperfect manufacturing process. Through numerical examples, we quantify the impact of supply with random yield on the system performance and illustrate its relationship with the demand and production rate.     

The optimal sales format for green products considering downstream investment

With the increasing public awareness of environmental protection and the popularisation of suppliers' green production, a growing number of e-tailers are also investing in green products or services. The greenization of an e-tailer brings additional sales to the online channel but weakens the bargaining power of the supplier and further complicates the supplier's online channel format choice. This study focuses on the interaction between the e-tailer's green investment strategy and the supplier's choice of online channel format. First, we find that the e-tailer's investment forces the supplier to consider a new factor, the supplier's investment efficiency, which the supplier does not consider when the e-tailer does not invest and completely changes the e-tailer's own preferences. Second, we obtain the counterintuitive result that the supplier does not always benefit from the e-tailer's greenization; in the reseller channel, a supplier with a high investment efficiency is made worse off due to the increased retail price resulting from the e-tailer's investment. Additionally, the e-tailer will go green only when the upstream investment efficiency is high, regardless of the online channel format. The intuition behind this result hinges on each player wanting to free ride but worrying that the other has the same idea.     

An integration of a hybrid modified TOPSIS with a PGP model for the supplier selection with interdependent criteria

This paper deals with the supplier selection process when the criteria of selection are not independent. The primary aim is to illustrate that ignoring the interdependencies among these criteria leads to an unrealistic decision. Since supplier selection is a multiple-criteria decision-making (MCDM) process, the general structures of the relative methods are outlined in this paper. The proposed methodology then presents a comprehensive approach to find the best ranking among the alternative suppliers of a typical product. A hybrid modified TOPSIS is integrated with a preemptive goal programming model in this study and then compared to an analytical hierarchy process (AHP) to show the effect of considering interdependencies in the supplier selection process. The results indicate that the proposed methodology provides a higher total value of purchasing (TVP) than AHP while the total cost of purchasing (TCP) of both methods are equal. Empirical proof is offered based on a case study.     

Supplier selection problem revisited from the perspective of product configuration

Collaboration with suppliers is essential for developing and producing a competitive product and it begins with selecting the right suppliers. This article addresses the supplier selection problem from the perspective of product configuration. We discuss first how the conventional decision models of supplier selection should be extended, considering the fact that supplier configuration requires supplier selection for each subsystem of a product. We then highlight the need to consider interrelationships between suppliers, namely, supplier–supplier relationships during the selection process of the combination of suppliers. Finally, we introduce the supplier configuration graph in order to provide a clear picture of the problem. Discussions are provided along with an example of a smartphone configuration.