Application of Alternative Multi-criteria Decision Making Approaches to Supplier Selection Process

Purpose – The problem of supplier selection gets complicated when a company looks for various criteria to evaluate different suppliers. The decision criteria used for supplier selection process can be different for different organizations due to a large number of factors. Hence, it can be said that supplier selection is basically, a multiple criteria decision-making (MCDM) problem. The purpose of this paper is to propose a hybrid data envelopment analytical hierarchy process (DEAHP) approach to solve the supplier selection problem for an automobile company. Design/methodology/approach – In this study, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. Literature review suggested that majority of researches found it appropriate using DEA and AHP methodologies for supplier selection process; hence it is felt that a hybrid DEAHP would be a useful methodology to offer a MCDM model for supplier selection problem. Findings – First, the key criteria of the supplier selection problem for the company are identified. Then a model is developed and implemented for supplier selection using DEAHP approach. This study concluded that quality, cost and service are the most crucial criteria for an automobile company operational in a developing country like India. Sensitivity analysis further helped to evaluate suppliers based on each criterion. Research limitations/implications – As this analysis and findings are based on only one case study of an Indian automobile company, and this necessitates caution in interpreting the results. The limited number of interviewed managers in a company restricts the generalizability of the results. Though the company selected for this study is typical of developing country businesses, the findings of the paper may not be readily extensible to other companies. Second, this study used retrospective settings, based on the interviewed feedback after the events had occurred. This method naturally poses limitations due to respondent recall and the accuracy of information provided. Third, the problem chosen for this study is based in a single country context and further additional research will be required to examine if the findings could be extended to other automobile companies in other developing nations. Also in some cases technique used in the study may pose some extra computational efforts. Practical implications – This study points out the importance of the supplier selection problem. It provides key criteria for supplier selection in Indian context also proposes a framework to deal with multiple criteria. proposed model deals with two crucial criteria long term relationships and flexibility which were relatively less discussed and considered in the literature in past. Originality/value – The proposed MCDM model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment.

Supplier selection problem has a major regard in terms of the performance of supply chain of an organization. Several various approaches were proposed, including the analytic hierarchy process, fuzzy analytic hierarchy process, and fuzzy technique for order of preference by similarity to ideal solution (TOPSIS). However, no comparative researches of these three approaches related to the supplier selection problem have been carried out. Therefore, this article proposes a methodology to evaluate the selected approaches. The evaluation was conducted based on the following factors: agility during the decision process, computational complexity, number of criteria and alternative suppliers, and adequacy in supporting a group decision. The methodology is implemented in X company. The results show that each approach is convenient to the supplier evaluation and selection problem, particularly toward the support of group decision-making and uncertainty modeling. In terms of computational complexity, analytic hierarchy process performs better than fuzzy TOPSIS and fuzzy analytic hierarchy process. Moreover, the fuzzy TOPSIS approach is better suited to the supplier evaluation and selection in terms of agility during the decision process, the number of criteria and alternative suppliers, and the adequacy in supporting a group decision.

Recently, many organizations intend to make their supply chains more responsive to the change in demand in terms of volume and variety and hence consider agility one of the most critical evaluation criteria in addition to other well-known criteria such as general management capability, manufacturing capability, and collaboration capability. This paper formulates the supplier evaluation and selection problem as a multi-criteria decision-making (MCDM) problem with subjective and fuzzy preferences of decision makers over available evaluation criteria and provides the decision maker with a decision support system that presents the Pareto fronts, a set of best possible high-quality suppliers and optimized business operation levels from such suppliers. In addition, this paper quantifies the importance of agility and its sub-criteria in the process of evaluating and selecting agile suppliers by measuring the magnitude of bullwhip effect as a measurement of the business impact of resulting agile supply chain. The proposed system based on fuzzy analytic hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) successfully determines the priority weights of multiple criteria and selects the best fitting supplier after taking the vagueness and imprecision of human assessments. More importantly, it presents approximated Pareto fronts of resulting supplier chains as the priority weights of agility criterion and sub-criteria within agility are varied.KeywordsSupplier selectionAgile supply chainPareto fronts, Bullwhip effectFuzzy AHPFuzzy TOPSIS

An organisation's progress strongly depends on the selection of an appropriate supplier. The selection of suitable supplier is a multi criteria decision making (MCDM) problem, which is based on several qualitative, quantitative and even conflicting criteria. This paper aims to propose a hybrid MCDM technique for the supplier selection problem. The fuzzy analytical hierarchy process (FAHP) is used to analyse the structure of supplier selection problem and to determine the weights of the criteria. The preference ranking organisation method for enrichment evaluation (PROMETHEE) is used to obtain the final ranking of the suppliers. The effectiveness of the proposed FAHP–PROMETHEE method is compared to AHP–PROMETHEE and it is illustrated using a real–time case study from a refrigerator manufacturing industry.

Supply chain management determining the competitive position of corporations in a rival and fast-changing environment is one of the favourite topics in engineering economics. Since the performance of suppliers affects the performance of the whole supply chain, the selection of a supplier is a significant problem in supply chain management. When solving a supplier selection problem, there are many criteria needed to be considered. Therefore, the supplier selection problem is a multi-criteria decision making (MCDM) problem. In the supplier selection process, most of the time, expert data is involved, and the judgement of experts includes ambiguous, imprecise and uncertain data. Thus, there are many methods to solve supplier selection issues by utilising fuzzy set theory, grey theory and rough theory to handle vagueness of a problem. This study also proposes a fuzzy model to solve this problem. In this study, an integrated fuzzy MCDM model including the Fuzzy Analytic Hierarchy Process (FAHP) and the Fuzzy Operational Competitiveness RAting (Fuzzy OCRA) will be proposed to solve supplier selection problem for a Turkish textile company. The FAHP is utilised to determine the weights of considered eight criteria and the fuzzy OCRA is used to rank five fabric suppliers concerning their performances on eight measures. This study is original and it contributes to the literature in two ways: first, this study proposes a fuzzy extension of the OCRA method and second, this study offers a new integrated fuzzy MCDM model consisting of the FAHP and the Fuzzy OCRA. By using a real case study of supplier selection problem, it is attempted to indicate the applicability of the new integrated fuzzy MCDM model for actual circumstances.

Multi-Criteria Decision Making techniques for the management of public procurement tenders: A case study

Materials constitute a large proportion of the total project cost and the absence of right materials in the right quantities and quality on site when needed is one of the most commonly experienced causes of delays in construction projects. Although supplier selection is a strategic issue, contractors generally select suppliers based on their past experi­ences, which may result in selecting wrong suppliers. Supplier selection decision is generally made by multiple decision makers and is affected by several criteria. Therefore, selecting the right supplier among many alternatives considering several compromising and conflicting criteria is a multi-criteria group decision-making (MCGDM) problem. This paper proposes an integrated fuzzy MCGDM approach, which employs fuzzy analytic hierarchy process (AHP) and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) together, for the supplier selection problem. In the proposed approach, fuzzy AHP is used to analyse the structure of the supplier selection problem and to determine the weights of the criteria, and the fuzzy TOPSIS method is employed to rank the alternative suppliers. The proposed approach is applied to a problem of selecting the most appropriate rail supplier and company management found the proposed decision approach satisfactory and implementable in future supplier selection problems.

In the last decades, supply chain management (SCM) has become a significant issue in real life and in the literature due to increasing globalisation. Moreover, supplier selection and periodical evaluation has become an important tool for the companies in order to maintain an effective SCM. The main goal of this study is to construct an integrated method to build a decision support system for supplier evaluation and selection that incorporates quantitative and qualitative calculations together to deal with vague and uncertain data available to decision makers. A methodology, which is capable of evaluating and monitoring suppliers' performance, is constructed, using fuzzy analytic hierarchy process (AHP) to weight the established decision criteria and ELECTRE III to evaluate, rank and classify performance of suppliers regarding relative criteria. The proposed methodology is applied to a real-life supplier-selection and classification problem of a pharmaceutical company.

Supplier evaluation and selection are key components in the supply chain because supplier performance directly affects the supply chain's efficiency. Therefore, companies should think strategically when they need to select their suppliers. Thus, selecting and evaluating new suppliers is essential in shaping the supply chain's smoothness and efficiency. Selecting suppliers is a complex issue as it involves many factors and decisions to be considered and needs to be assessed with an auditing process. However, a supplier audit is an expensive way to evaluate supplier capability. This research aims to propose a supplier selection model for a corrugated carton manufacturing company. The SOCCER model, developed by Steve Rogers, was used as the supplier selection criteria. Analytical Hierarchy Process (AHP) was used in the supplier selection. A face-to-face interview method was used in collecting data. The results show that the cost structure is the ultimate concern on supplier selection which bears 44.2% of the SOCCER model, followed by operational capability (23%), customer approach (13.5%), economic performance (8.3%), strategic direction (6.9%), and lastly research and development (4.1%). The percentages inform the company how much attention they need to pay when evaluating and selecting a new supplier. ABSTRAK: Penilaian dan pemilihan pembekal adalah kunci utama dalam rantaian bekalan kerana prestasi pembekal secara langsung melibatkan kecekapan rantaian bekalan. Oleh itu, syarikat perlu memikirkan secara strategik apabila ingin memilih pembekal. Dengan demikian, pemilihan dan penilaian pembekal baru adalah penting dalam pembentukan kelancaran rantaian bekalan dan kecekapan. Pemilihan pembekal adalah isu kompleks kerana ianya melibatkan banyak faktor dan keputusan perlu difikirkan dan perlu dinilai bersama proses audit. Namun, audit pembekal adalah mahal bagi menilai kemampuan pembekal. Kajian ini mencadangkan model pemilihan pembekal bagi syarikat pembekal kotak karton. Model SOCCER dicipta oleh Steve Rogers, telah digunakan sebagai kritia pemilihan pembekal. Proses Hirarki Analitikal (AHP) digunakan dalam pemilihan pembekal. Kaedah temuduga bersemuka digunakan dalam pengumpulan data. Dapatan kajian menunjukkan struktur harga adalah kehendak utama dalam pemilihan pembekal iaitu 44.2% daripada model SOCCER, diikuti kemampuan operasi (23%), pendekatan pelanggan (13.5%), prestasi ekonomi (8.3%), misi strategik (6.9 %), dan akhirnya penyelidikan dan pembangunan (4.1%). Peratusan ini berguna untuk syarikat dalam memberi keutamaan dalam penilaian dan pemilihan pembekal baru. ABSTRAK: Supplier evaluation and selection are key components in the supply chain because supplier performance directly affects the supply chain's efficiency. Therefore, companies should think strategically when they need to select their suppliers. Thus, selecting and evaluating new suppliers is essential in shaping the supply chain's smoothness and efficiency. Selecting suppliers is a complex issue as it involves many factors and decisions to be considered and needs to be assessed with an auditing process. However, a supplier audit is an expensive way to evaluate supplier capability. This research aims to propose a supplier selection model for a corrugated carton manufacturing company. The SOCCER model, developed by Steve Rogers, was used as the supplier selection criteria. Analytical Hierarchy Process (AHP) was used in the supplier selection. A face-to-face interview method was used in collecting data. The results show that the cost structure is the ultimate concern on supplier selection which bears 44.2% of the SOCCER model, followed by operational capability (23%), customer approach (13.5%), economic performance (8.3%), strategic direction (6.9 %), and finally research and development (4.1%). The percentages inform the company how much attention they need to pay when evaluating and selecting a new supplier.

The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of intuitionistic multi-criteria supplier selection methods in a fuzzy environment. The intuitionistic fuzzy AHP and TOPSIS methods are thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the paper mill. For this purpose, 3 alternative green suppliers have been identified. To evaluate the alternatives, 10 criteria in three dimensions including supplier performance, environmental protection and supplier risk have been selected. Since the Multi-Criteria Decision Making (MCDM) methods are often used in problem of supplier selection from past to present. The Intuitionistic Fuzzy Sets (IFS) are used to reflect approval, rejection, and hesitation of decision makers by dealing with real life uncertainty, imprecision, vagueness, and linguistic human decisions. The main purpose of this study is to define the weights of criteria with Intuitionistic Fuzzy AHP. After that, the Intuitionistic Fuzzy TOPSIS and AHP method were used to rank alternatives from best to worst. At the end of the study the results related with alternatives were compared and interpreted.

Supplier selection is one of the most important functions to be performed by the purchasing department. The supplier selection is a multi-criteria decision making (MCDM) problem involving both qualitative and quantitative criteria. In order to select the best suppliers, it is necessary to make a trade off between tangible and intangible criteria that conflict with each other. Today's globally competitive business environment warrants suppliers to supply raw materials punctually in the right quantity and quality. Manufacturers are increasingly concerned about supplier selection since reliable suppliers enable them to reduce inventory costs and improve product quality. This paper proposes an integrated model based on fuzzy analytical hierarchy process (AHP) for supplier selection. A decision support system (DSS) has been developed using Visual Basic and MS Access. The case study was conducted in a leading steel plant to demonstrate the application of the proposed model.

This paper aims to apply a hybrid method of supplier selection to a well-known Turkish company operating in the appliance industry. The data envelopment analytic hierarchy process (DEAHP) methodology developed by Ramanathan, R., (Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process. Computers and Operations Research, 2006, 33, 1289–1307) was chosen as the survey method. In this method, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. This research concluded that the DEAHP method outperforms the AHP method for supplier selection despite the findings that the AHP model suggested supplier 1 to be the best supplier, contradicting the suggestion made by the DEAHP model and the real action taken by BEKO in selecting supplier 2. These findings imply that DEAHP criteria reflect closer to the real optimum of the decision made. Drawing on a real case our study has supported Ramanathan's (2006) work confirming the view that the DEAHP method provides a better decision than the AHP method for supplier selection. Because the DEAHP model is relatively more cumbersome to apply, its application will be more appropriate for high-value components where stringent purchasing criteria are required. In contrast, AHP would remain to be an appropriate approach for relatively lower value components (C class). The novelty of this research lies in the application of a hybrid approach to a real industry case–the DEAHP method for supplier selection, where little has been done on this subject. This study has dealt with one of the most important subjects in supply chain management providing a better decision for supplier selection using appropriate quantitative approaches.

Selecting process of a machine tool has been very important issue for companies for years, because the improper selection of a machine tool might cause of many problems affecting negatively on productivity, precision, flexibility and company’s responsive manufacturing capabilities. On the other hand, selecting the best machine tool from its increasing number of existing alternatives in market are multiple-criteria decision making (MCDM) problem in the presence of many quantitative and qualitative attributes. Therefore, in this paper, an analytic hierarchy process (AHP) is used for machine tool selection problem due to the fact that it has been widely used in evaluating various kinds of MCDM problems in both academic researches and practices. However, due to the vagueness and uncertainty on judgments of the decision-maker(s), the crisp pair wise comparison in the conventional AHP seems to insufficient and imprecise to capture the right judgments of decision-maker(s). That is why; fuzzy number logic is introduced in the pair wise comparison of AHP to make up for this deficiency in the conventional AHP. Shortly, in this study, an intelligent approach is proposed, where both techniques; fuzzy logic and AHP are come together, referred to as fuzzy AHP. First, the fuzzy AHP technique is used to weight the alternatives under multiple attributes; second Benefit/Cost (B/C) ratio analysis is carried out by using both the fuzzy AHP score and procurement cost, of each alternative. The alternative with highest B/C ratio is found out and called as the ultimate machine tool among others. In addition, a case study is also presented to make this approach more understandable for a decision-maker(s).

Supplier selection of a telecommunications system is an important problem to a telecommunications company as the telecommunications system is a long-term investment for the company and the success of telecommunications services is directly affected by the supplier selection decision (Tam and Tummala, 2001). The aim of this study is to model for supplier selection problem for a real world application in India which is the most populated country in world. A number of conflicting qualitative and often accompanied by ambiguities and vagueness. This makes fuzzy logic a more natural approach to this kind of multi-criteria decision-making (MCDM) problems. The paper proposes a combined MCDM methodology. Fuzzy analytic hierarchy process (AHP) and linear programming (LP) are utilised for assigning weights of the criteria for supplier selection and linear programming (technique for order preference by similarity to ideal solution) is used to determine the most suitable alternative using these criteria weights.

Entscheiden bei unschärfe — Fuzzy decision support systeme: Springer-Verlag, Berlin, 1988, ix + 304 pages, DM45.00