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Sustainability is a global megatrend that has drastically changed how industries operate [ 1 3 ]. Sustainability is a concept where economic, social, and environmental indicators are holistically considered [ 4 ]. With this megatrend, not only economic prosperity is emphasized, but environmental and social consciousness have also been further awakened in people. This topic has been gaining importance because of some critical factors, such as the rapid depletion of natural resources, increasing population, and climate change. To enable future generations to sustain their lives with what is left of rapidly depleting natural resources, a shift towards a more sustainable lifestyle is necessary.

Sustainable supply chains refer to the management of products, services, and information from the raw material stage to the end consumer, intending to balance economic, social, and environmental sustainability. In recent years, the concept of sustainability has gained significant importance in the business world, as consumers and companies have become more conscious of the impact of their actions on the environment and society.

One of the critical benefits of sustainable supply chains is that they could lead to cost savings through improved efficiency and reduced waste [ 5 6 ]. For example, by implementing sustainable practices in transportation and logistics, companies could reduce emissions and save on fuel costs [ 7 9 ]. Additionally, sustainable supply chains could improve brand reputation, as consumers are more likely to choose products and services from companies committed to sustainability [ 10 11 ].

However, implementing sustainable supply chains could also be challenging, as it often requires significant changes to existing systems and processes. Companies need to consider a range of factors, including the environmental impact of their suppliers, the conditions of workers in their supply chain, and the use of sustainable materials.

In the contemporary business landscape, supplier selection transcends cost and quality to encompass more nuanced and critical aspects such as lean processes and sustainability. Key performance indicators (KPIs) related to lean processes and sustainability have therefore emerged as indispensable metrics in the evaluation of suppliers. These KPIs address a gamut of considerations ranging from resource efficiency and waste reduction to environmental stewardship and social responsibility. By adopting a systematic approach to measure and track these KPIs, organizations could make informed, holistic decisions that align economic viability with environmental and social objectives. Hence, this study aims to contribute to both theoretical and practical dialogues by proposing a robust supplier selection framework that incorporates lean and sustainable KPIs as integral components of the evaluation criteria.

Despite the challenges regarding the sustainability transformation of business, sustainable supply chains are becoming increasingly important as companies and consumers become more conscious of the impact of their actions on the environment. While implementing sustainable supply chains could be challenging, the benefits of improved efficiency, cost savings, and improved brand reputation make it a worthwhile investment for companies.

Such challenges and opportunities exist within any industry. One of these industries is the wood furniture industry, whose outputs, as an element, have a history spanning over 5000 years. The significance it held in the past is something that it will continue to maintain in the present and future [ 12 ]. Like every other sector, the wood furniture industry strives to sustain its existence optimally by staying open to evolving technology and all innovations. Among these innovations, leanness- and sustainability-focused developments are among the ones with primary importance and are expected to remain relevant. One fact separates this industry from others; a high proportion of raw material input of the wood furniture industry is a renewable resource with a natural carbon sequestration potential. Once the procurement, production, and delivery activities are carried out sustainably and efficiently, this industry could transform into one of the most sustainable industries.

When efficiency improvement is the concern, Lean Management is the first modern management technique that comes to mind. It is more than just a production method; it is a culture. It first emerged with Toyota’s efforts to improve efficiency by doing more with less. It was developed by Taiichi Ohno, the father of the Toyota Production System, in the late 1970s [ 13 ]. The philosophy of Lean Management aims to increase efficiency by minimizing all sorts of waste. Since then, Lean Management principles have been expanded to cover and transform supply chain operations. When implemented successfully, businesses could gain a significant competitive advantage by taking advantage of opportunities in the business environment as a function of increased leanness and flexibility, reduced costs, and maximized profits.

One of the most critical activities within a supply chain is the procurement activities, which involve crucial decisions such as supplier selection, lot-size determination, logistics management, and warehousing. The proper supplier selection in supply chain management could be a “success or failure” decision for a business. The supplier selection problem is one of the multi-criteria decision-making problems that consist of defining methods and models to analyze and measure a series of suppliers’ performance to enhance the competitive power of organizations. The diversity of quantitative and qualitative criteria varies depending on the characteristics of the encountered problem, making supplier selection a complex decision [ 14 ]. The methodology used to solve the supplier selection and a series of similar complex problems is called Multi-Criteria Decision Making (MCDM).

Multi-Criteria Decision Making (MCDM) methods are used to make the most accurate decision by considering multiple criteria. The use of these methods helps businesses make more informed decisions in their supplier selection process. MCDM methods could be used across all complex decision-making processes, regardless of the sector. They are employed in various sectors, from automotive [ 15 ] to textile, and from textile [ 16 ] to health [ 17 ]. With MCDM methods, many decision-making criteria could be used to evaluate multiple alternatives. Given the inherently complex nature of supplier selection problems, they could be solved using MCDM methods. However, there are situations in which uncertainty comes into play in using MCDM methods. When such a situation is encountered, solutions should be produced using MCDM methods in a fuzzy environment [ 18 19 ]. MCDM methods solved with fuzzy numbers perform better where quantitative data are insufficient, and there are more linguistic data and uncertainty. Therefore, many techniques with fuzzy numbers have been introduced into the literature for this purpose [ 20 22 ].

Not only for the furniture industry but in all businesses, companies that apply lean supplier selection in supply chain management aim to adopt a model that allows both the company and the supplier to profit while meeting customer needs. At the same time, sustainable supplier selection presents a robust and holistic selection model in terms of economic, social, and environmental indicators [ 23 ]. Businesses combining the lean philosophy developed by Ohno with sustainability concepts could achieve true sustainability more quickly and easily and gain a competitive advantage [ 24 ].

Literature Review

Upon reviewing academic studies conducted in past years, it has been observed that lean management, sustainability, and Multi-Criteria Decision Making (MCDM) have been used in numerous sectors and very different combinations. Both empirical and review studies were included in the review. The primary focus was to explore and understand the current state-of-the-art in terms of variety, quantity, and practicality of the criteria and to identify the research gap in the intersection of MCDM, supply chain management, and Lean and Sustainability Performance.

Aouadni et al. (2019) carried out a literature review on supplier selection and order allocation problems in their study. They reviewed studies published on the subject matter from 2000 to 2017. The studies under review were examined from three different perspectives: summaries of existing evidence on the problems, identifying gaps in current research to help identify areas that may require further research, and positioning new research activities. Overall, this paper provides valuable insights and guidance for researchers in the field of supplier selection and order allocation, helping them to position their research and contribute to the advancement of knowledge in this area [ 25 ].

Pınar (2020) studied the Multi-Criteria Decision-Making (MCDM) methods used in supplier selection. By examining 153 academic studies conducted over the last 20 years, it was determined that the most commonly used methods in supplier selection are AHP and Fuzzy TOPSIS. Moreover, it was observed that the interest in fuzzy methods has increased in recent years. The article highlights the importance of effective supplier selection in an efficient supply chain and its impact on product quality, cost reduction, flexible production, and customer satisfaction [ 26 ].

Schramm et al. (2020) reviewed 82 articles on sustainable supplier selection published in the last thirty years in their study. The reviewed articles were classified into two categories: (1) approaches based on single methods, (2) approaches based on co-employment of techniques. The methods used in both categories were MCDM methods and their variations. The results indicated that one or more methods could yield satisfactory results. The integration of multiple techniques has been a trend in this field, but the fundamental differences among the methods should be well understood before integrating them to avoid inconsistent results. Additionally, the paper emphasized the need for more research on the applicability of these approaches to real-life supplier selection problems, particularly in terms of the cognitive effort required from decision makers and their confidence in the recommendations provided by the approaches [ 27 ].

Naqvi and Amin (2021) conducted a literature review on supplier selection and order allocation in their study, regardless of the sector. Ninety-two articles between 2015 and 2020 were analyzed and classified according to operational research methods used in the study. The classifications were made under the titles of literature reviews, deterministic optimization, and uncertain optimization. The practical implications of this study included the identification of practical challenges in applying the various methods, the suggestion of case studies to demonstrate the applications of MCDM methods, and the exploration of new methods for special circumstances such as COVID-19. The study also highlighted the potential use of advanced forecasting techniques such as machine learning, deep learning, and neural networks to estimate parameters in optimization models [ 28 ].

Link to EISHOAdditional reading:
Rattan

In their study, Abdollahi et al. (2015) chose lean- and agile-focused evaluation criteria for supplier selection. The weights of these criteria were calculated using the ANP method. Later, twenty suppliers were evaluated using the DEA method with the calculated criterion weights. The DEA score obtained through this approach served as a surrogate for the overall competence and capability of a supplier, providing a comprehensive evaluation that could not have been easily discerned through traditional supplier audits. The framework also allowed for the identification of strategically important suppliers and provided benchmarks for improving the operations of poorly performing suppliers [ 29 ].

In their study, Zulqarnain and Dayan (2017) analyzed a problem involving the selection of the best alternative for an automotive company using four criteria and five alternatives, using the Intuitionistic Fuzzy TOPSIS (IF-TOPSIS) method. They determined that the A3 alternative provided the best result. The study proposed and validated a technique that could improve decision-making processes by taking into account the uncertain nature of linguistic evaluations, which could be valuable in various industries, including the automotive sector [ 30 ]. In another study, Oztel et al. (2018) utilized the entropy-based TOPSIS method to evaluate the annual sustainability performances of an energy company. The sustainability performance of seven years was evaluated with fourteen criteria. The paper was observed to be part of the broader academic discussion on corporate sustainability and its relationship with organizational culture. It added to the understanding of how corporate sustainability could be integrated into business strategies and decision-making processes [ 31 ].

Buyukozkan and Gocer (2018) focused on the supplier selection problem for the digital supply chain in their study. They utilized the IVIF AHP method to calculate the weights of the five main and 16 sub-criteria selected for the problem, and the IVIF ARAS method was used to evaluate eight alternatives. The ease of use and ability to extend the proposed methodology to an IVIF environment overcame the limitations of classical Multiple Criteria Decision Making (MCDM) methodologies, making it a practical and accessible tool for organizations. The study also suggested future research directions, such as exploring the use of classical fuzzy logic and comparing its results with sensitivity analysis, integrating other MCDM methods with fuzzy or IF sets, and applying the proposed model to different MCDM problems [ 32 ]. Abdullah et al. (2019) focused on green supplier selection using the PROMETHEE method in their work. They attempted to solve the identified decision-making problem with seven evaluation criteria and four alternatives based on the input of 5 decision-makers. The paper demonstrated the use of different preference functions in evaluating and comparing green suppliers based on seven economic and environmental criteria. The results showed that despite the differences in preference functions used, supplier A1 consistently emerged as the most preferred alternative. This suggested that the choice of preference function may not significantly impact the final preference for green suppliers [ 33 ].

Tasdemir and Gazo (2019) and Tasdemir et al. (2020) developed and validated a holistic sustainability benchmarking tool by incorporating modern management philosophies such as Lean Management and Six Sigma with sustainability to assess the true sustainability performance of companies and supply chains. The study involved a complex assessment mechanism with 33 key performance indicators stratified under three hierarchical levels. The authors emphasized that the synergies between Lean Management and sustainability could be harnessed to achieve true sustainability. The authors’ motivation for the study included the wood products industry’s failure to become a frontier of innovation and sustainability, its relatively low profit margins, the potential benefits of triple bottom line sustainability investments, the need to assess and benchmark the sustainability performance of the value-added wood products industry and SMEs, and the true sustainability potential of the wood products industry due to the renewable, recyclable, and biodegradable nature of wood. The study also focused on a small-sized manufacturing operation to demonstrate the benefits of sustainability initiatives for SMEs [ 24 34 ].

In their study, Hosseini and Khaled (2019) addressed the supplier selection decision for a firm in the USA that manufactures water and sewer plastic pipes. The study proposed a hybrid ensemble-AHP to calculate potential suppliers’ resilience based on absorptive, adaptive, and restorative capacities. Eight contributors to supplier resilience were identified, analyzed, and ranked using the proposed community method. Five suppliers with higher resilience values were selected based on robustness, reliability, and redirection. The proposed approach successfully aided the decision-making process of the resilient supplier selection problem under investigation. Shandong (China) supplier was the best supplier [ 35 ].

In the study by Zulqarnain et al. (2020), the TOPSIS method based on fuzzy set theory was used to evaluate five candidates applying to work at a bank, and the best two candidates were selected. The bank’s head office determined five criteria for the selection of the candidates and calculations were made in accordance with the methodology. The best two selected candidates were Y1 and Y5. The study contributed to the research field by providing a practical technique for decision-making and expanding the knowledge and application of fuzzy set theory [ 36 ]. In another 2020 study, Zulqarnain et al. used the TOPSIS method to solve a problem involving the selection of a clinic for emergency illness diagnosis, based on four criteria and four alternatives. The best alternative, H1, was determined in accordance with the methodology. This study contributed to the field of medical decision-making and aids health professionals in making informed choices for emergency illness diagnosis [ 37 ].

Rouyendegh et al. (2020) addressed a green supplier selection problem aiming for the selection of the most lean, agile, environmentally sensitive supplier that prioritized sustainability and resilience. To reduce the impact of uncertainty and indecisiveness on the problem, the Intuitive Fuzzy TOPSIS approach was employed. The problem consisted of ten criteria and four alternative suppliers. The problem was successfully tackled with the fuzzy approach, and the A2 alternative was selected as the best-performing supplier in regard to leanness, agility, sustainability, and resilience. The paper contributed to the field of supply chain management by addressing the problem of green supplier selection (GSS) and its importance in enhancing competitive pressure and meeting environmentalist attitudes [ 38 ].

Fei (2020) focused on the supplier selection decision in his study. In this decision-making problem, a choice was made among three alternative suppliers using six evaluation criteria and the D-ANP and D-AHP MCDM methods for the selection. The paper extended the traditional Analytic Network Process (ANP) method using D numbers, which allowed for the management of dependencies and interactions at different levels. This extension overcame the limitations of the Analytic Hierarchy Process (AHP) and provided more flexibility, rationality, and credibility [ 39 ]. In another study, Li et al. (2020) dealt with the lean and agile supplier selection problem in the textile sector in China. The evaluation criteria were selected through a literature review and analyzed using the DEMATEL method. The study emphasized the importance of quality as a conventional criterion for enhancing competitive advantage, while market sensitivity holds less influence [ 40 ].

Ecer (2021) proposed a model for solving sustainable supplier selection decision-making problems within the automotive spare parts sector. This model included 12 criteria across three sustainability dimensions and was used to evaluate five alternative suppliers. The FUCOM method was used to calculate the criteria weights, while the MAIRCA method was used to rank the supplier alternatives [ 41 ]. Kaya and Ayçin (2021) worked on the proper supplier selection in the textile sector during the Industry 4.0 era. The study utilized an integrated Interval Type 2 Fuzzy AHP and GOPRAS-G methodology. The Interval Type 2 Fuzzy AHP method was used to determine the weights of the supplier evaluation criteria, and the Gray GOPRAS method was applied subsequently to evaluate the alternative suppliers. The paper provided insight into how Industry 4.0 strategies influence supplier selection, aiming to benefit both practitioners and researchers [ 42 ].

In another study, Fallahpour et al. (2021) developed a new integrated model involving various sustainability- and Industry 4.0-related criteria for supplier selection within the textile industry. The proposed method employed the Fuzzy Best-Worst Method (FBWM) and two-stage Fuzzy Inference System (FIS) in supplier selection. The paper aimed to address the concept of Industry 4.0 and its integration with Sustainable Supply Chain Management (SSCM) [ 43 ].

Rahimi et al. (2021) used the Intuitive Fuzzy ENTROPY method to rank and select suppliers according to their qualifications. The main supplier to provide the necessary materials for a company’s production line in Iran was chosen using five criteria among five alternatives. The paper contributed by introducing a new intuitionistic fuzzy entropy measure for selecting suppliers. It built on the work of Burillo and Bustince, who defined interval-valued fuzzy sets and IFSs and introduced the distance measure between IFSs using entropy measures [ 44 ].

In their study, Sonar et al. (2022) developed the LARGS paradigm for lean, agile, flexible, green, and sustainable supplier selection, determining twenty-two selection criteria. Using the ISM approach, they also created a hierarchical structure between the chosen twenty-two criteria. The paper tried to fill a research gap by being the first of its kind to identify supplier selection criteria in the LARGS paradigm and develop hierarchical relationships between them using the ISM approach [ 45 ].

In his study, Baki (2022) developed a decision-making approach using Structural Equation Modeling (SEM) and Fuzzy Additive Ratio Assessment (ARAS) techniques for ranking in the green supplier selection process. Eight main and twenty-seven sub-criteria were determined, and six alternative suppliers were evaluated considering these criteria. The new approach was successfully used to conclude that Supplier 1, which demonstrated the best performance, should be chosen as the vendor. The approach developed in the study could be used for effective and impartial strategic decision-making, especially in challenging situations like GSS where conflicts of opinion could be intense [ 46 ].

Afrasiabi et al. (2022) followed a hybrid MCDM approach to address the sustainable, resilient supplier selection problem in their studies. The best-worst method was used to determine criteria weights. The Fuzzy Gray Relational Analysis and TOPSIS methods were used to evaluate suppliers. Sixteen evaluation criteria were divided into four main categories: economic, environmental, social, and flexible. Six alternative suppliers were evaluated with the determined criteria, and it was concluded that Supplier A6 was the best. The results were then examined with other MCDM methods, namely F-WASPAS, F-MOORA, and F-VIKOR, confirming the accuracy of the outcome. By presenting an evaluation framework for supplier selection that considers the resilience concept and the three pillars of sustainability (economy, society, and environment) simultaneously, and by boosting the use of the Fuzzy Best-Worst Method (FBWM) to assign weights to criteria in real-life situations involving ambiguous and uncertain data, the study made significant contributions to the field [ 47 ].

Nasri et al. (2022) delivered a solution to the sustainable supplier selection problem in the oil industry by integrating Fuzzy DEMATEL, ANP, Data Envelopment Analysis, and the Anderson–Peterson rating model. The paper presented a novel procedure for solving the sustainable supplier selection problem, allowing decision-makers to prioritize suppliers based on their performance [ 48 ]. In another recent study, Menon and Ravi (2022) used an integrated AHP-TOPSIS approach for sustainable supplier selection. In their study, the authors added the ethical dimension to sustainability’s economic, environmental, and social dimensions. Four main and 16 sub-criteria were determined. These selected criteria were used to evaluate six suppliers. AHP was used to calculate criteria weights, while the TOPSIS method was utilized to evaluate suppliers. The fifth alternative was chosen as the best supplier. Overall, the paper contributed to the field of sustainable supplier selection in the electronic industry by providing a comprehensive and practical approach to address the complex decision-making process involved in selecting sustainable suppliers [ 49 ].

Çalık (2022) focused on the supplier selection problem in his study. The model created for the supplier selection problem included two main, eight sub-criteria, and ten alternative suppliers. The Fuzzy AHP was used to determine criteria weights, and the Fuzzy ARAS method was utilized to evaluate alternative suppliers. Fuzzy MCDM methods were effectively used in the presence of uncertainty. The findings of the study highlighted the importance of resilience in supplier selection, with factors such as supplier flexibility and responsiveness being crucial within the resilience factor [ 50 ].

The comprehensive review of the extant literature on sustainable supplier selection demonstrates both academic and industrial significance. From a scientific standpoint, the integration of various fuzzy and original MCDM methods like TOPSIS, ARAS, AHP, DEMATEL, MAIRCA, VIKOR, and MOORA reveals a growing interest in tackling the multifaceted nature of decision-making under uncertainty. Such advancements broaden the methodological toolkit for researchers and indicate the maturation of the field. Additionally, the focus on incorporating resilience and ethics into sustainability criteria sets a new precedent for future academic inquiries. From a practical perspective, these studies offer valuable insights for businesses across sectors, from oil to textile, in making informed, impartial, and effective supplier selection decisions. They also enhance the resilience and competitiveness of supply chains by allowing for a holistic evaluation that encompasses economic, environmental, and social dimensions. However, it was noted that the furniture industry, particularly wood furniture manufacturing, is underrepresented in current literature, signifying a pertinent avenue for immediate research focus. This is especially crucial given the current global emphasis on sustainability and lean operations.

Based on the comprehensive review of the state-of-the-art, it could be concluded that a business’s supplier selection decision is a typical MCDM problem. When the objective is lean and sustainable supplier selection, which considers lean, environmental, economic, and social aspects simultaneously, the problem becomes more complex and uncertain.

While various studies have engaged in the evaluation of sustainable supplier selection using Multiple-Criteria Decision-Making (MCDM) methods, such as TOPSIS, ARAS, AHP, DEMATEL, MAIRCA, VIKOR, and MOORA, across sectors like oil, textiles, and electronics, a conspicuous gap exists when it comes to the wood furniture manufacturing industry. Despite this industry’s ongoing transformation toward sustainability, there is a paucity of research focused on the integration of both lean and sustainability metrics in supplier selection. Moreover, based on the literature in the field, fuzzy MCDM methods performed well in the presence of a lack of data availability and increased uncertainty. Furthermore, the integrated use of fuzzy MCDM methods made a more informed decision-making process possible through comparative discussions of the results.

Furthermore, existing literature has largely neglected to establish a standardized set of criteria that assess suppliers’ leanness and sustainability performance concurrently, regardless of firm size. In today’s evolving world, investing in sustainability is not an option but a necessity. On the other hand, the competition within the sectors shifted from the company level to the supply chain level. Moreover, resource scarcity, tightening profit margins, and elevated supply chain interruptions across all sectors have been forcing companies to do more with less by increasing their efficiency. Due to such dynamic industrial conditions, with every passing day, an increasing number of companies are seeking sustainable options in all areas of operations, including supplier selection. Therefore, this study tried the answer the research question of “is it possible to simultaneously address lean and sustainable supplier selection problem with help of fuzzy MCDM methods?” and sought to bridge this gap by proposing an integrated, systematic approach for supplier selection in the wood furniture manufacturing sector. As part of the proposed systematic methodology, the study also aimed to develop and deploy a set of valid criteria that could be utilized to assess the leanness and sustainability performance of suppliers across diverse operational scales.

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