scholarly journals GREEN SUPPLIER SELECTION BASED ON THE INFORMATION SYSTEM PERFORMANCE EVALUATION USING THE INTEGRATED BEST-WORST METHOD

2021 ◽  
Vol 19 (3) ◽  
pp. 345
Author(s):  
Hamed Fazlollahtabar ◽  
Navid Kazemitash
Keyword(s):  
System Performance ◽  
Supplier Selection ◽  
Global Markets ◽  
Environmental Laws ◽  
Green Supplier Selection ◽  
Green Suppliers ◽  
A Company ◽  
Contemporary Technology ◽  
Different Levels ◽  
Best Worst Method

Information Systems (IS) have become crucial for all the organizations to survive in contemporary technology-oriented environment. Consequently, the number of companies and organizations which have invested widely in their IS infrastructures to present better services and to produce higher value products is increasing. On the other hand, nowadays, because of the increase of governmental rules and serious requirements of more people in the case of environmental protection, it seems necessary for all the enterprises to follow these regulations if they want to survive in the global markets. However, what is at issue here is not just the companies’ agreement with the environmental laws; in addition, they should apply some strategies to decrease the negative environmental impacts of their products in some countries. Thus, the aforementioned arguments are the reasons for the compulsory use of the green supplier selection (GSS) in all firms. Considering the mentioned contents, the purpose of this study is representation of the relation between ISs and GSS as two vital components of firms in a novel way which has not been done before. Actually, it shows the ISs' performance or effectiveness to select the green suppliers taking into account the different levels of importance of GSS measures (including eight criteria and 31 sub-criteria), using a multi-criteria decision-making method called Best Worst Method (BWM) to identify the weights (importance) of GSS measures and compute the GSS performance of 10 ISs in a company using the data gathered in a survey from ISs' experts.

scholarly journals GREEN SUPPLIER SELECTION PRACTICES AND ITS IMPLICATIONS OF GREEN PURCHASING: CASE STUDY AT 5 STARS HOTEL IN BALI

2020 ◽  
Vol 4 (2) ◽  
pp. 140-149
Author(s):  
I Ketut Astawa ◽  
◽  
I Ketut Budarma ◽  
Cokorda Istri Sri Widhari ◽  
◽  
...  
Keyword(s):  
Supplier Selection ◽  
Environmentally Friendly ◽  
Green Supply Chain ◽  
Green Supplier Selection ◽  
Descriptive Research ◽  
Market Opportunities ◽  
Green Purchasing ◽  
Green Suppliers ◽  
Selection Of

Purpose: The purpose of this study is to examine the practice of selecting green suppliers conducted by companies to be environmentally friendly and how these practices have implications for purchasing green products in 5-star hotels in Bali. Research methods: This study is guided by the green supply chain management model and the green selection model. A descriptive research design is used. Data were collected using a questionnaire. The population consists of 63 employees from companies that supply room supplies, food & beverage, chemical, and Spa. Data were analyzed using SPSS and presented using tables, graphs, frequencies, and percentages. Results and discussions: The study revealed that the selection of environmentally friendly suppliers had a positive and significant effect on the implementation of environmentally friendly purchases. The implications of selecting green suppliers create new market opportunities. Hotel cooperation with suppliers is getting closer and mutually committed to operational purchasing activities. Conclusion: The study revealed that the selection of environmentally friendly suppliers had a positive and significant effect on the implementation of environmentally friendly purchases. The indication was that green supplier selection is a major factor that influences the implementation of green purchasing at 5 stars hotel in Bali.

A risk-based integrated decision-making model for green supplier selection

Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1229-1252 ◽  
Author(s):  
Morteza Yazdani ◽  
Prasenjit Chatterjee ◽  
Dragan Pamucar ◽  
Manuel Doval Abad
Keyword(s):  
Risk Factors ◽  
Decision Making ◽  
Supplier Selection ◽  
Potential Contribution ◽  
Effect Analysis ◽  
Content Type ◽  
Green Supplier Selection ◽  
Construction Company ◽  
Green Suppliers ◽  
Decision Making Model

Purpose Supply chain (SC) environment is surrounded by risk variables. This issue is regarded as an emerging and strategic problem which must be resolved by SC executives. The ability to measuring green supplier’s performance and affecting risk variables to demonstrating effective suppliers list has a potential contribution to be investigated. This paper aims to develop a decision-making model to assess green suppliers under legislation and risk factors. This leads to fewer disruptions in managing the SC and its impact to further improvement. It also presents research concepts forming a new approach for identification, prediction and understating relationship of supply risk. Design/methodology/approach At primal stage, different risk factors that influence green suppliers’ performance are indicated and their relationship is analyzed using decision-making trial and evaluation laboratory (DEMATEL) method. At the same time, failure mode and effect analysis is used to determine risk rating of each supplier. Finally, the evaluation based on distance from average solution (EDAS) method ranks suppliers and several comparisons and analysis are performed to test the stability of the results. The approaches include comparison to technique for order performance by similarity to ideal solution, multi-attributive border approximation area comparison, Vlse Kriterijumska Optimizacija I Kompromisno Resenje and complex proportional assessment methods, followed by analysis of rank reversal, weight sensitivity analysis and effect of dynamic metrics. Findings A real-time case study on green supplier selection (GSS) problem of a reputed construction company of Spain has been presented to demonstrate the practical aspects of the proposed method. In practice, though organizations are aware of various risks from local and global suppliers, it is difficult to incorporate these risk factors for ranking the suppliers. This real-case application shows the evaluation and incorporation of risk factors into the supplier selection model. Practical implications The proposed multi-criteria decision model quantitatively aids managers in selecting green suppliers considering risk factors. Originality/value A new model has been developed to present a sound mathematical model for solving GSS problems which considers the interaction between the supplier selection risk factors by proposing an integrated analytical approach for selecting green suppliers strategically consisting of DEMATEL, FMEA and EDAS methods.

scholarly journals q-Rung Orthopair Fuzzy Prioritized Aggregation Operators and Their Application Towards Green Supplier Chain Management

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 976
Author(s):  
Muhammad Riaz ◽  
Dragan Pamucar ◽  
Hafiz Muhammad Athar Farid ◽  
Masooma Raza Hashmi
Keyword(s):  
Supplier Selection ◽  
Weighted Average ◽  
Sustainable Growth ◽  
Fuzzy Information ◽  
Chain Management ◽  
Green Supplier Selection ◽  
Scientific Decision ◽  
Green Suppliers ◽  
Prioritized Aggregation Operators ◽  
Relationship Of

Supply management and environmental concerns are becoming increasingly relevant to scientific decision analysis around the world. Several companies have implemented the green supply chain management (GSCM) approach for attaining economic advantages while retaining sustainable growth for the environment. Green supplier selection has also been analyzed in many literary works as an important part of GSCM, which is considered an important multi-criteria group decision making (MCGDM) problem. The lack of consideration of the relationships of alternatives to the uncertain environment will be the main reason for weak conclusions in some MCGDM problems. To address these drawbacks, we introduce a new approach for selecting green suppliers with the q-rung orthopair fuzzy information, in which the input assessment is considered by using q-rung orthopair fuzzy numbers (q-ROFNs). A q-ROFN is extremely valuable in representing vague information that occurs in these real-world circumstances. The priority relationship of the alternatives to q-rung orthopair fuzzy information is very helpful to deal with GSCM. Consequently, we develop some prioritized operators with q-ROFNs named the q-rung orthopair fuzzy prioritized weighted average (q-ROFPWA) operator and q-rung orthopair fuzzy prioritized weighted geometric (q-ROFPWG) operator. Several important characteristics of these operators such as idempotents, boundary, and monotonicity are also well proven. Finally, an application of the proposed operators is presented for green supplier selection in GSCM. The scientific nature of the proposed methodology is illustrated by a numerical example to validate its rationality, symmetry, and superiority.

scholarly journals An Application of Fuzzy Integrated Model in Green Supplier Selection

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Alptekin Ulutaş ◽  
Ayşe Topal ◽  
Rim Bakhat
Keyword(s):  
Supply Chains ◽  
Supplier Selection ◽  
Social Issues ◽  
Selection Index ◽  
Green Supplier Selection ◽  
The Third ◽  
Novel Method ◽  
Green Suppliers ◽  
Decision Making Model ◽  
Selection Of

“Sustainability” term has not only become increasingly important globally for individual companies, but also become important for whole supply chains. The selection of supplier is a significant decision for the sustainability of supply chains. Literature review revealed that supplier selection is made traditionally based on economic attributes which are insufficient for sustainability of supply chains as sustainability requires taking economic, environmental, and social issues into account. For this purpose, this paper proposes determining the green supplier selection attributes and then developing a methodology for assessment and ranking of green suppliers based on determined attributes. The first contribution of this study is to propose a novel method, which is FROV (fuzzy extension of range of value) to literature. The latter is to utilize fuzzy extension of preference selection index (FPSI) to identify the weights of attributes. The third is to develop a novel fuzzy multiattribute decision-making model consisting of FPSI and FROV to determine the best supplier for a Turkish textile company.

Rough MCDM model for green supplier selection in Iran: a case of university construction project

2020 ◽  
Vol 10 (3) ◽  
pp. 437-452 ◽  
Author(s):  
Payam Shojaei ◽  
Ana bolvardizadeh
Keyword(s):  
Construction Industry ◽  
Supplier Selection ◽  
Construction Projects ◽  
Rough Set Theory ◽  
Multicriteria Decision Making ◽  
Environmental Management System ◽  
State Universities ◽  
Content Type ◽  
Green Supplier Selection ◽  
Green Suppliers

PurposeThe construction industry has a significant function in improving the quality of life in the urban environment; meanwhile, greening the supply chain is becoming a seriously pressing issue in the construction industry. This paper seeks to select green suppliers in construction projects implemented at Iranian state universities via multicriteria decision-making (MCDM) models through rough set theory.Design/methodology/approachA mixed methodology design was conducted through a literature review of studies concerned with green suppliers to identify the related criteria and the rough MCDM techniques. As such, 15 criteria were finalized through content validity ratio (introduced by Lawshe, 1975). The weights of the criteria were calculated through the rough AHP and the suppliers were prioritized using the rough TOPSIS to contribute to the Construction Department.FindingsThe study proposed a hierarchical structure of the decision process for green supplier selection in construction projects. According to the weighting results, environmental awareness, green social responsibility and the environmental management system were the most important criteria.Research limitations/implicationsBecause the scope of the study was limited to state universities and the methods worked according to the experts' views, the results should be generalized with more caution. The validity of the results should be examined by applying the model to similar contexts.Originality/valueThe study conceptualizes green supplier selection in construction projects at state universities. Furthermore, the method used makes it possible to deal with the uncertainty arising from experts' limited awareness of only part of the problem rather than the whole system under investigation.

Green Supplier Selection Using Improved TOPSIS and Best-Worst Method Under Intuitionistic Fuzzy Environment

Informatica ◽  
2018 ◽  
Vol 29 (4) ◽  
pp. 773-800 ◽  
Author(s):  
Zhang-Peng Tian ◽  
Hong-Yu Zhang ◽  
Jian-Qiang Wang ◽  
Tie-Li Wang
Keyword(s):  
Supplier Selection ◽  
Green Supplier Selection ◽  
Intuitionistic Fuzzy ◽  
Fuzzy Environment ◽  
Best Worst Method

scholarly journals Decision Support System for Green Supplier Selection Using the Fuzzy Inference System Method in Abrasive Companies

2021 ◽  
Vol 2 (2) ◽  
Author(s):  
Defi Norita ◽  
Ririn Regiana Dwi Satya ◽  
Andary Asvaroza Munita ◽  
Asep Endih Nurhidayat
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Inference System ◽  
Supplier Selection ◽  
Fuzzy Inference ◽  
Inference System ◽  
Green Supplier Selection ◽  
System Method ◽  
Green Suppliers

The development of information and communication technology makes it easier for users in the industrial world to make decisions in choosing environmentally friendly suppliers more easily. This study aims to determine the selection of green suppliers of all the criteria that have been determined and make a decision support system for selecting green suppliers with the Fuzzy Inference System method. The method used in making identification of green supplier selection is to create criteria based on fuzzy rules and to make digital business modeling using business process modeling notation. Decision support there are 4 criteria used, namely price, reject quality, late delivery and environmental management. Based on the results of research conducted it is known that with the fuzzy inference system method that is assisted using matlab software, the optimization results on the fuzzy inference system show that prices are 20.5%, quality is 5.5%, environment is 5.5%, and material delays are 3%, then supplier performance in selecting green suppliers with a decision making system of 55% so that green supplier selection is obtained at abrasive companies.

scholarly journals A Multi-criteria Picture Fuzzy Decision-making Model for Green Supplier Selection based on Fractional Programming

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Guo Cao
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Supplier Selection ◽  
Decision Makers ◽  
Fuzzy Decision Making ◽  
Fuzzy Decision ◽  
Green Supplier Selection ◽  
Relative Closeness ◽  
Green Suppliers ◽  
Decision Making Model

Due to the increasing complexity in green supplier selection, there would be some important issues for expressing inherent uncertainty or imprecision of decision makers’ cognitive information in decision making process. As an extension of intuitionistic fuzzy sets (IFSs) and neutrosophic sets (NSs), picture fuzzy sets (PFSs) can better model and represent the hesitancy and uncertainty of decision makers’ preference information. In this study, an attempt has been made to present a multi-criteria picture fuzzy decision-making model for green supplier selection based on fractional programming. In this approach, the ratings of alternatives and weights of criteria are represented by PFSs and IFSs, respectively. Based on the available information, some pairs of fractional programming models are derived from the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and the proposed biparametric picture fuzzy distance measure to determine the relative closeness coefficient intervals of green suppliers, which are aggregated for the criteria to generate the ranking order of all green suppliers by computing their optimal degrees of membership based on the ranking method of interval numbers. Finally, an example is conducted to validate the effectiveness of the proposed multi-criteria decision making (MCMD) method.

scholarly journals A CLOUD TOPSIS MODEL FOR GREEN SUPPLIER SELECTION

2020 ◽  
Vol 18 (3) ◽  
pp. 375 ◽  
Author(s):  
Krishnapuram Ravi Ramakrishnan ◽  
Shankar Chakraborty
Keyword(s):  
Supplier Selection ◽  
Selection Process ◽  
Cloud Model ◽  
Evaluation Criteria ◽  
Human Cognition ◽  
Green Supplier Selection ◽  
Adopted Model ◽  
Qualitative Attribute ◽  
Green Suppliers ◽  
Topsis Model

Due to stringent governmental regulations and increasing consciousness of the customers, the present day manufacturing organizations are continuously striving to engage green suppliers in their supply chain management systems. Selection of the most efficient green supplier is now not only dependant on the conventional evaluation criteria but it also includes various other sustainable parameters. This selection process has already been identified as a typical multi-criteria group decision-making task involving subjective judgments of different participating experts. In this paper, a green supplier selection problem for an automobile industry is solved while integrating the Cloud model with the technique for order of preference by similarity to an ideal solution (TOPSIS). The adopted method is capable of dealing with both fuzziness and randomness present in the human cognition process while appraising performance of the alternative green suppliers with respect to various evaluation criteria. This model identifies green supplier S4 as the best choice. The derived ranking results using the adopted model closely match with those obtained from other variants of the TOPSIS method. The Cloud model can efficiently take into account both fuzziness and randomness in a qualitative attribute, and effectively reconstruct the qualitative attribute into the corresponding quantitative score for effective evaluation and appraisal of the considered green suppliers. Comparison of the derived ranking results with other MCDM techniques proves applicability, potentiality and solution accuracy of the Cloud TOPSIS model for the green supplier selection.

Investigation of Green Criteria With Clustering Analysis in Green Supplier Selection

2022 ◽  
pp. 207-228
Author(s):  
Mehmet Ali Taş ◽  
Serap Akcan
Keyword(s):  
Clustering Analysis ◽  
Supplier Selection ◽  
Crucial Importance ◽  
Green Supplier Selection ◽  
The Past ◽  
Usage Frequency ◽  
Public Pressure ◽  
Green Suppliers ◽  
Green Criteria ◽  
Selection Of

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.

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