Investigation of Green Criteria With Clustering Analysis in Green Supplier Selection

Green supplier selection has a crucial importance for businesses. In the past, the selection of suppliers was solely based on conventional criteria such as cost, quality, and flexibility whereas expectations of businesses transformed in today's world on grounds of raised environmental awareness, public pressure, and regulations. Alternatives called green suppliers sensitive to the environment, preserving the ecological balance, managing wastes, and preventing pollution increased in value. This study analyzes practices on the selection of green suppliers. The articles between 2014 and 2021 were analyzed from the perspective of green criteria. The green criteria in the 50 articles determined are divided into 28 groups. With the k-means algorithm, these criteria groups are divided into four clusters, which was aimed to analyze the usage frequency of green criteria. This study is intended to contribute to green supplier selection practices in academia and industry in the future.

Extension of a Hybrid MABAC–DANP Method Under Gray Environment for Green Supplier Selection

Nowadays, environmental problems have attracted the attention of many craftsmen and researchers. They have developed various policies and practices to protect the environment throughout the supply chain. Since suppliers are one of the supply chain partners, paying attention to these policies by them will be very effective in keeping the supply chain green. In today’s dynamic environment, there is uncertainty in all decisions of the organizations. The wood and paper industry also faces uncertainty in choosing green and environmentally friendly suppliers. These uncertainties must be taken into account when selecting suppliers. Decision-making techniques will cover uncertainty if developed in a gray environment. Many techniques have been developed in a gray environment. But using a combination of DANP and MABAC techniques in a gray environment will be very useful because of the benefits of each. Therefore, using the combination of DANP and MABAC in a gray environment in order to select a green supplier in the wood and paper industry is a gap that is felt and in this paper we try to overcome it. The research findings show that the identified criteria will be very effective in selecting the green supplier and Gray DANP–MABAC can be used for managers’ decisions in the wood and paper industry.

The Multi-Attributive Border Approximation Area Comparison (Mabac) Method for Decision Making under Interval-Valued Fermatean Fuzzy Environment for Green Supplier Selection

In the era of sustainable development, green supplier selection has become a key component of supply chain management, as it considers criteria such as carbon footprint, water usage, energy usage and recycling capacity. Since the green supplier selection problem involves subjective criteria and uncertainty in preferences, it is well suited to using multi-criteria decision-making methods (MCDM). Although few researchers have investigated MCDM for green supplier selection under uncertainty using intuitionistic and Pythagorean fuzzy sets. Still, the newly developed fermatean fuzzy can handle greater data uncertainty than intuitionistic and Pythagorean fuzzy sets. Since interval extension of fuzzy theory provides more accurate modeling, in this paper, we propose an interval extension of fermatean fuzzy set and discuss its fundamental set operations, arithmetic operations and related properties. We propose the Hamming distance function and the score function of the interval-valued fermatean fuzzy numbers. The recently developed Multi-attribute Border Approximation Area Comparison (MABAC) method is also considered due to its stable and simple computation compared to other conventional MCDM methods. Therefore, an interval-valued fermatean fuzzy MABAC method is proposed and solved to select a green supplier based on multiple criteria. The proposed method's comparative analysis and sensitivity analysis validate the proposed method's effectiveness and robustness.

A Hybrid Model for Green Supplier Selection and Order Allocation: DEMATEL, ANP, and Multi-criteria Goal Programming Approach

Increased competition in the industrial world forces companies to increase their competitiveness through Green Supply Chain Management (GSCM). The key to the success of GSCM is the selection of suppliers and the allocation of the proper order by taking into account environmental aspects. This decision involves several criteria and must also pay attention to the relationship between criteria. This study proposes a hybrid procedure to solve Green Supplier Selection and Order Allocation (GSSOA). The integration of Decision Making Trial and Evaluation Laboratory (DEMATEL), Analytic Network Process (ANP), and Multi-Criteria Goal Programming (MCGP) are proposed to solve this problem. The DEMATEL is used to calculate the relationship between criteria. Furthermore, the ANP is proposed to determine the weight of the criteria and supplier ranking. Finally, the MCGP method is offered for allocating orders based on priority suppliers. A case study on the food industry in Malang, Indonesia, was conducted to apply this procedure. The results showed that the low defects rate criterion is the most important compared to other criteria. The best supplier was successfully selected, and the order allocation was completed. Order allocation priority is to suppliers D, C, A, and B. This study also presents a sensitivity analysis for order allocation.

Green Supplier Selection Based on Customer Needs Using Markov Chain and MCDM Method

Supplier selection is a problem that has been widely discussed and addressed from different angles, but few works address the supplier selection problem by considering the needs of customers. After a literature review of the studies done on this topic none of them considered the changing desires and behavior of customers when evaluating green suppliers. This contribution then, will aim to design a green supplier selection model based on customer need using a recent MCDM decision making method and the Markov chain. The Markov chain is used to model and track changes in customer preferences and find a transition model. Then the (BWM) method is used to select the best ecological supplier.