A comparative perspective in sustainable supplier selection by integrated MCDM techniques

Abstract

Keywords: Foundry sector; fuzzy AHP; fuzzy TOPSIS; fuzzy VIKOR; fuzzy MULTIMOORA; sustainable supplier selection.

1. Introduction

Companies have investigated new ways to respond customer requests in a timely, accurate and fast as a result of changing competitive environment. Supply chain management (SCM) is a network between a company and its corporates who are interlinked by each other even they require a lot of skill and expertise. Purchasing and sourcing in a company is crucial, and successful SCM operations are based on strategic alliances with the right suppliers. The purchasing cost of parts for a business involves a large part of the total cost of a product. A large part of the total production cost (about 70%) of companies is composed of parts costs and the selection of suitable suppliers leads to a considerable decrease in the purchasing costs of the

Corresponding Author: e-mail: ahmetcalik51@gmail.com, tel: (332) 444 12 51 / 7651 835

companies. Therefore, supplier selection is considered the key for achieving intended objectives in the SCM [1, 2]. Instead of fo cusing only on economic performance, businesses have begun to address social, environmental and economic dimensions together in SCM. The need to change in increasing market demand and consumption models has led to the emergence of the concept of sustainability beginning in the 1990s [3]. Leading international companies such as Shell, Bristol-Myers Squibb and Unilever who recognize the importance of sustainability have included three dimensions of sustainability for sustainable development into the overall strategies of their companies [4]. As well as all over the world, some of the leading companies in Turkey have begun to implement sustainability practices to survive in the global market. The Turkish foundry sector is one of the keystones of the Turkish manufacturing industry. Foundry products are used as inputs in almost all industrial branches, thus foundry sector has an essential significance in the manufacturing industry. In fact, there is at least one foundry product in 90% of the produced industrial products [5]. In order to keep the size of the Turkish foundry industry reached in recent years, foundry manufacturers have begun to focus on selecting and evaluating suppliers. The supplier selection is a Multi-Criteria Decision Making (MCDM) problem that allow the evaluation of many strategic and operational factors at the same time. Usage of these methods guide to the managers and allows them to make the right decisions [6]. Over the years, changing consumer requirements, strict legislation and legal regulations have led to changes in priorities of criteria that enterprises use in supplier evaluation and reveals the concept of sustainable suppliers [7, 8]. Sustainable supplier selection (SSS) requires operational considerations to take into account certain qualifications beyond conventional supplier selection criteria [9, 10]. Even though companies evaluate suppliers' performance considering conventional criteria such as cost, quality, and on time delivery however dimensions of sustainability should be taken into consideration in the selection of suppliers [11]. The economic dimension [7, 10], environmental dimension[12] and social dimension [10] has been investigated from many researchers. In the light of these discussed issues, companies must address not only on the traditional criteria for supplier selection but also dimensions of sustainability. Therefore, in this study, the three dimensions of sustainability are investigated in the Turkish foundry industry for SSS. In this sense, the following research questions will be answered:  To identify the criteria for SSS in the foundry industry  To determine which sustainability dimension is important for the assessment of sustainable suppliers in the foundry industry  To obtain the level of importance of main criteria and sub-criteria for SSS in the foundry industry  Identifying and ranking the appropriate suppliers with different MCDM methods for SSS in the foundry industry  To determine which method is the most suitable for the SSS in the foundry industry  To determine whether there is a relationship between supplier rankings obtained for the SSS in the foundry industry  To demonstrate the managerial and practical results of working in the foundry industry Based on the above questions the main purpose of this work is to present a framework for SSS in a foundry company which is the main supplier of production plants in Turkey. For this purpose, an integrated approach has been proposed to find answers and identify appropriate sustainable suppliers. A nominal group technique is used at a meeting with government officials, business managers and academics to define the criteria to be used in selecting and evaluating sustainable suppliers in the foundry sector. Later the level of importance of the criteria are obtained by industry managers and experts responsible for field experts based on a questionnaire. The fuzzy AHP method is utilized to address uncertainty of experts' views and to determine the

level of importance of main criteria and sub-criteria by of paired comparisons. Later on, Techniques for Order Preference by Similarity to Ideal Solution (TOPSIS), Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and MULTIMOORA methods are used in a fuzzy environment to select sustainable suppliers and compare the performance of these three popular MCDM methods. The rest of paper is structured as follows. Section 2 provides an overview of supplier selection and SSS. Section 3 introduces Fuzzy AHP, fuzzy TOPSIS, fuzzy VIKOR and fuzzy MULTIMOORA methods. Section 4 contains the case study application and discussion of results. Section 5 clarifies conclusion and outlook for future studies.

2. Literature Review

For first time, Dickson [13] raised considerable ideas about supplier selection and prepared a list for supplier selection and shed light on the next researcher who will work on this area. This work was later extended by Weber et al. [14] for supplier selection. In the past five decades, various studies have been performed to evaluate suppliers. However, most of the studies in supplier selection utilities economic criteria, including cost, quality, delivery time and service level. In terms of environmental criteria, many authors have completed a series of literature reviews with supplier selection. Igarashi et al. [15] reviewed articles in the field of green supplier selection. Saputro et al. [16] presented a literature survey for material handling equipment selection problem. Since suppliers can be assessed from different perspectives, various models of MCDM are proposed for supplier selection. [17–21]. According to Zimmer et al. [22] the electronics and automotive industry is the most preferred research area in sustainable supplier management. Textile, chemicals and pharmaceuticals and mining and quarrying industries are coming after the electronics and automotive industry. Although, the number of studies has increased rapidly in last decades, it has not been found any study on supplier selection in foundry sector. By controlling the sustainability factors, companies take a more economically proper position, and for this reason many researchers have researched the sustainable SCM in different areas [17]. Rajeev et al. [3] performed a literature review over the period 2000-2015 (July) by studying 1068 articles. They showed that studies in developed economies have led than from developing economies and general sustainable development studies have potential for future researches especially for developing economies. Since there are more than 2500 articles between 2000 and 2015, only SSS has been considered in this section. SSS has a number of advantages while the above studies deal with supplier selection in crisp and fuzzy environments. Some of the recent researches on SSS are described as follows: Kahraman et al. [23] used fuzzy AHP to select best supplier for a white good manufacturer in Turkey. Rouyendegh and Saputro [24] combined fuzzy TOPSIS with Multi Choice Goal Programming to specify the appropriate supplier and determine order allocation of each appropriate supplier. Rouyendegh [25] presented a hybrid model using both the ANP and Intuitionistic Fuzzy TOPSIS models for supplier selection. Dai and Blackhurst [26] developed an integrated approach using AHP with quality function deployment to express the sustainability requirements of the stakeholders. Azadi et al. [11] proposed a Data Envelopment Analysis (DEA) model to evaluate suppliers for an Iranian company. Zimmer et al. [22] analyzed the publications between 1997 and 2014 to address on sustainable supplier management. Fallahpour et al. [17] determined the importance of sustainable criteria in the evaluation of suppliers’ sustainability and developed an integrated MCDM model using fuzzy preference programming and fuzzy TOPSIS methods. Luthra et al. [8] used AHP-VIKOR based approach to prioritize SSS criteria on an automotive company in India. Song et al. [27] proposed an integrated approach considering pairwise comparison method, DEMATEL, and rough set theory that is validated in a case study of solar air-conditioner manufacturer. Awasthi et al. [28] presented a fuzzy AHP-VIKOR approach

for SSS dealing with risk concerns. Kannan [29] implemented a real-world case study designing a decision support system based on the triple bottom line approach. Vahidi et al. [30] proposed a hybrid framework with SWOT and quality function deployment for choosing the most relevant sustainability criteria. Rouyendegh et al. [31] applied Intuitionistic Fuzzy TOPSIS method to determine the most appropriate green supplier according to 10 criteria. Rouyendegh et al. [32] determined the best suitable site for wind power plant in Turkey by Intuitionistic Fuzzy TOPSIS method. Table 1 contains a summary and comparison of studies on SSS. Integrated MCDM methods are generally used for SSS, as seen in the literature review. AHP or fuzzy AHP methods have been used in different areas for companies in their strategic decisions to calculate criteria weights and achieve better results [7]. Although there are many techniques for identifying suitable suppliers, Fuzzy TOPSIS, VIKOR and MULTIMOORA methods that ease of calculation, representing human preferences and generating an alternative order based on the ideal solution approximation are preferred in this study [2, 28]. Additionally, different criteria weights are used in the solution phase in the Fuzzy TOPSIS and VIKOR methods however the criteria weights are not used in the MULTIMOORA method. Therefore, MULTIMOORA method also is applied in this study in order to investigate influence of weights in solution. Table 1. Summary of literature on SSS Dimension Authors / year

Fuzzy preference programming - Fuzzy Fallahpour et al. [17] *

Topsis

Fuzzy AHP - Fuzzy multi-objective Shaw et al. [18] * linear programming

Dematel

Fuzzy TOPSIS and multi objective * programming Fuzzy DEMATEL, Taguchi Loss * Functions and bi-objective model Best–worst method, TOPSIS and fuzzy * multi-objective linear programming Fuzzay AHP - Fuzzy TOPSIS - Fuzzy * VIKOR - Fuzzy MULTIMOORA

Copras-G

Automotive company Solar air-conditioner manufacturing company Electronic goods manufacturing company

Iranian textile manufacturing company Garment manufacturing company Resin production company

Hypothetical data Packaging films in a food industry A paper manufacturing company Online retailer company Computer purchasing company A foundry manufacturing company

3. The Proposed Integrated Methodology

In this section, the integrated methodology is introduced and the steps of the methodology are explained. The methodology starts with using the fuzzy AHP method to reach criteria weights and the methodology is terminated by the ordering of alternatives with TOPSIS, VIKOR, and 838

MULTIMOORA methods under fuzzy environment. Flowchart of the proposed methodology is given in Fig. 1. In construction stage of the problem, the hierarchical structure of the problem is designed by defining the purpose and scope of the problem, main criteria, sub-criteria and alternatives, decision makers (DMs) and linguistic variables. Then weights of the main criteria and sub-criteria are determined through the pairwise of the DMs by using fuzzy AHP method. Then, fuzzy TOPSIS, fuzzy VIKOR and fuzzy MULTIMOORA methods are applied to evaluate sustainable suppliers considering relevant criteria.

4. The Numerical Application

SSS problem in foundry which producing bearing house, V-belt pulley, and coupling for many firms in Turkey is sought by using the integrated methodology stated in Section 3. The company began to operate in foundry sector in 1973 (abbreviated as MP), and have been manufacturing bearing house, V-belt pulley, and Coupling since 1980. MP is one of the leading foundry company in Konya. MP is installed in a total area of 5500m² with 3000m² closed area, has a foundry capacity of 20 tons per day. It also has ISO 9001:2008 OHSAS18001 and TSE certified. It produces the highest quality foundry products used in different industries such as engineering, automotive and durable consumer sectors. The commitment of the company in improving environmental or sustainability performance is a significant advantage for the prospect of this work. Company managers need to maximize their performance for sustainable development and capture continuous improvement in production activities. Additionally, the company produce innovative products due to increasing competition conditions and varying customer needs. Recently, problems arising in orders have forced the company to reassess its relationships with its suppliers and to identify suppliers that can work for long periods of time in accordance with company requests. Although the company has undertaken various activities in the SCM (procurement, transportation, packaging, recycling, etc.), there is still shortage of SSS criteria and evaluation of existing suppliers among the managers. Therefore, the company seeks to select the best sustainable supplier, taking into account the sustainability dimensions. Another important point is that the company wants to achieve the priority of sustainability dimensions for further development in long-term operations. In this context, we help with the managers to determine the SSS criteria and alternative suppliers with the proposed methodology.

VG VG VG EE

S3 P P P OHS S3 G G VG F G F S4 VP P VP S4 G G F VG G F S5 G F F S5 F G F G VG VG S1 F F F S1 G G VG G G G S2 F F P S2 G F G G F F WUM S3 G G F WET S3 G G VG P VP VP S4 P VP P S4 G VG G VG G G S5 F G F S5 F F G G G G S1 P P VP S1 G F G F G P S2 P P P S2 P P P VG G G WRM S3 G G F S3 F G G D F P F S4 F P P S4 F F P F VG G S5 G G G S5 G G G

The closeness coefficient of alternatives is computed and is shown in table 11. Table 11. The results of fuzzy TOPSIS method 𝑑𝑖+ 8.084 8.225 8.032 8.330 8.059

Finally, the ranking of each alternative is shown by the decreasing order of the closeness coefficient, as 𝑆3 > 𝑆5 > 𝑆1 > 𝑆2 > 𝑆4. 4.2.2. Fuzzy VIKOR analysis The steps of the fuzzy VIKOR method are applied using the fuzzy decision matrix obtained in the TOPSIS method. First, the fuzzy best (𝑓𝑗∗ ) and the fuzzy worst (𝑓𝑗− ) values are computed, then the values of fuzzy 𝑆̃𝑖 , 𝑅̃𝑖 and 𝑄̃𝑖 are calculated by taking ν = 0.5 for each alternative. In the last stage, the fuzzy numbers are defuzzified and 𝑆, 𝑅 and 𝑄 values are found. The obtained results are shown in Table 12. According to the index values, alternatives are sorted by in ascending order. Table 12. The results of fuzzy VIKOR method 𝑄 Suppliers S1 S2 S3 S4 S5

It can be reached from the results of Table 12 the ranking of suppliers are 𝑆3 > 𝑆5 > 𝑆1 > 𝑆2 > 𝑆4. 4.2.3. Fuzzy MULTIMOORA analysis The fuzzy decision matrix is normalized. Then, suppliers are ranked by fuzzy ratio system, and the results are given in Table 13. Also, suppliers are ranked by fuzzy reference point (see Table 14). Table 13. The results of fuzzy ratio system Suppliers S1 S2 S3 S4 S5

Table 14. The results of reference point approach Suppliers C Q CI

EE WUM WRM OHS WET

D 𝑚𝑎𝑥 𝑑 Ranking S1 0.040 0.000 0.022 0.054 0.038 0.225 0.164 0.000 0.017 0.225 4 S2

The third supplier (S3) is considered the best one, whereas the fourth supplier the worst one (S4) for the fuzzy Ratio System. Table 15. Ranking of suppliers by integrated MCDM techniques Suppliers

Multimoora

Similar ranking results are achieved by using different methods in the evaluation of SSS. While S3 has highest second rank only according to the fuzzy reference point approach, it has the first rank in all other methods (see Table 15). These results show that S3 supplier is the best sustainable supplier in the case study. Although the criteria weights obtained in the first stage are used in distance calculation in the fuzzy TOPSIS method, the weights used in the last 𝑆 and 𝑅 calculation in the fuzzy VIKOR method. Additionally, fuzzy MULTIMOORA method does not take into account the weights for calculations. Different ranks can be obtained with the fuzzy MULTIMOORA method that it uses only the assessments of suppliers, not the criteria weights. Three different methods use different normalization techniques. While the fuzzy TOPSIS method uses vector normalization, the linear normalization function in the fuzzy VIKOR method and the internal normalization in the fuzzy MULTIMOORA method. Table 16. Spearman’s rank correlation coefficients for integrated MCDM techniques Fuzzy

Multimoora

Fuzzy MULTIMOORA 1.000** ,900* 1 (Fuzzy Ratio) Fuzzy MULTIMOORA 0.8 0.6 0.8 (Reference Point Approach) *. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed).

Spearman rank-order correlations are conducted in order to determine if there are any relationships between the rankings of MCDM techniques. A two-tailed test of significance indicated the there is a significant positive relationship between the rankings. Except for the Fuzzy MULTIMOORA (Reference Point Approach) technique, all correlation coefficients are statistically significant since threshold value is 0.05 (see Table 16).

5. Conclusion And Outlook

With the increasing influence of environmental awareness and globalization, companies have begun to develop new business strategies to preserve their competitive position. In addition, technological developments have changed consumer behaviour to a large extent and have begun to exert high pressure on companies. These pressures have led businesses to invest in environmental and social issues as well as economic investments. Sustainable supply chain dimensions, such as economic, social and environmental co-operation, play an important role in achieving triple bottom-line benefits and contributing to the sustainable development of the community. For this reason, it is very important for businesses to tackle all dimensions of sustainability together and establish a balance between them so that they can continue their existence in the future. The SSS process is seminal to achieving a successful SCM in business. In this context, when choosing suppliers, it is appropriate not only to focus on cost but to evaluate on different dimensions. In this paper, an integrated approach that companies achieve high benefits usage of sustainability is proposed in supplier selection. The aim of this study is to propose a decision-making framework that takes into account sustainability dimensions and uncertainties in the DMs’ assessments. The sustainable supplier problem is a MCDM problem which qualitative and quantitative factors influence this decisionmaking process. For MCDM problems, it is the most important stage is to specify main criteria and sub-criteria clusters. For this reason, in this study, firstly a comprehensive literature search is carried out to determine the main criteria and sub-criteria clusters, and then the sub-criteria to be used in the research are listed with the NGT. As a result, three main criteria and three sub-criteria to be grouped under each criterion are determined. Decision-makers who evaluate the specified criteria often make linguistic assessments that are not fully expressed by crisp numbers. For this reason, in many studies to deal with uncertainty in evaluations, the fuzzy set theory is preferred by combining MCDM methods. From this viewpoint, SSS problem is presented combining with fuzzy MCDM approaches and sustainability criteria. During the weighting and evaluation process, the opinions of the experienced experts from two to twelve years working in the business are converted into a single group decision. The proposed approach is carried out in two stages. First, the fuzzy AHP method is applied to obtain the weights of the criteria. Second, fuzzy TOPSIS, VIKOR and MULTIMOORA methods are used to measure the sustainable performance of suppliers and to generate a general performance score for each supplier. Finally, a sensitivity analysis is conducted to determine the effect of criteria weights in the decision-making process. During the implementation phase, a case study is presented to a better understanding of the proposed approach. The fuzzy AHP method is performed for the main criteria and sub- criteria weights. When the results are examined, the most important criterion is determined as economic criteria with the rate of 66% for fuzzy AHP. The other criteria are social criteria with the rate of 25% in the second place. After determining the weights, first of all, the application is carried out by the fuzzy TOPSIS method, and the TOPSIS method results showed that supplier 3 (S3) as the most preferred supplier. According to this result, if the main manufacturer expands the current business volume with the S3 supplier, it will gain a more efficient supply chain network. After the S3 supplier, the most preferred supplier would be the supplier 2. The fact that the main producer works with multiple suppliers at every turn is particularly important in terms of having a

competitive edge in the price criteria. Later, the fuzzy VIKOR and MULTIMOORA methods are used to rank suppliers and found that the S3 ranks first. There are many limitations in this work. First of all, it is difficult to establish SSS criteria in the foundry sector. In addition, the criteria specified are applied only to small and medium-sized enterprises operating in the foundry industry. Another limitation of our work is the lack of quantitative data and the presence of a limited number of participants in the study. For a possible future study, sustainability criteria such as carbon footprint, resource consumption, reliability and employees' interests and rights can be added as new criteria by looking at supplier selection criteria. Companies can create a supplier selection model not only for supplier selection but also for order allocation. In addition, supplier selection problem can be solved in addition to these solution techniques, such as ELECTRE, PROMETHEE, DEA and so on. The proposed methodology may be extended considering different objectives such as digitalization, blockchain smart technologies smart supply chain management, and other emerging areas of operations research and economics. Furthermore, the obtained results for the problem can be addressed to different sectors or may be considered or evaluated as a large-scale enterprise in different regions of Turkey.

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