Digital Supplier Selection for a Garment Business Using Interval Type-2 Fuzzy Topsis

Özbek, Ahmet; Yıldız, Aytaç

doi:10.32710/tekstilvekonfeksiyon.569884

Cited by 19 publications

(10 citation statements)

References 35 publications

(62 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Indeed, the authors calculated the importance of the criteria using the BWM and ranked the alternatives applying the WASPAS method. Özbek and Yildiz ( 2020 ) studied the digital SSP due to the I4.0 transformation. They identified 20 sub-criteria and three suppliers in the apparel industry in Turkey.…”

Section: Literature Reviewmentioning

confidence: 99%

“…On the other side, the main motivation for considering the leanness, agility, sustainability, and I4.0 aspects is their importance in the supply chain management problem. In the literature, there are several works that studied the sustainable SSP (for example, Sen et al (2018), Hendiani et al (2020a, b), Beiki et al (2021), Tong et al (2022), Salimian et al (2022)), the lean and agile SSP (for example, Alimardani et al (2013), Abdollahi et al (2015), Li et al (2020), Foladi (2020, Alamroshan et al (2022)), and the I4.0-based SSP (for example, Özbek and Yildiz (2020); Çalık (2021); Fallahpour et al (2021b), Fallahpour et al (2021c). However, there is no research that considers all of these crucial aspects, simultaneously.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool

ForouzeshNejad

2022

Environ Sci Pollut Res

View full text Add to dashboard Cite

Given the crucial role of the supplier selection problem (SSP) in today’s competitive business environment, the present study investigates the SSP by considering the leagile, sustainability, and Industry 4.0 (I4.0) indicators for the medical devices industry (MDI). In this regard, at the outset, the list of criteria and sub-criteria is provided based on the literature and experts’ opinions. Then, the importance of the indicators is measured utilizing the rough best–worst method (RBWM). In the next step, the potential suppliers are ranked employing the multi-attributive border approximation area comparison (IR-MABAC) method. Due to the crucial role of medical devices during the COVID-19 outbreak, the present work selects a project-based organization in this industry as a case study. The obtained results show that agility and sustainability are the most important criteria, and manufacturing flexibility, cost, reliability, smart factory, and quality are the most important sub-criteria. The main theoretical contributions of this study are considering the leagile, sustainability, and I4.0 criteria in the SSP and employing the hybrid RBWM-IR-MABAC method in this area for the first time. On the other side, The results of this research can help supply chain managers to become more familiar with the sustainability, agility, leanness, and I4.0 criteria in the business environment.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool

ForouzeshNejad

2022

Environ Sci Pollut Res

View full text Add to dashboard Cite

show abstract

“…Sahu et al (2016) used the fuzzy TOPSIS to transform the evaluation information against subjectivity indices into mathematical dimensionless numbers in order to develop a multiple criterion appraisement index model for supplier selection. Ozbek and Yildiz (2020) built a model using the fuzzy TOPSIS method to select the best digital supplier for a company. Gunduz and Gunduz (2019) calculated a closeness coefficient based on the fuzzy TOPSIS to obtain the performance ranking of suppliers.…”

Section: Figure 3 Abstract Co-occurrencementioning

confidence: 99%

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Liao

Zavadskas

2021

Technological and Economic Development of Economy

View full text Add to dashboard Cite

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM.

show abstract

“…Robot assisted production helps the SCs to decrease labor cost, enhancing worker productivity, reducing error rate, optimize picking, etc. Intelligent systems act as enablers for supply chain efficiency (Özek and Yıldız, 2020). The automation of SCs will help in developing SCQM practices to optimize the firm's performance.…”

Section: Systematic Literature Reviewmentioning

confidence: 99%

Digital supplier selection reinforcing supply chain quality management systems to enhance firm's performance

Sharma

Joshi

2020

TQM

View full text Add to dashboard Cite

PurposeThe geographical scattering of physical facilities in conventional supply chains enforces firms to shift toward digital supply chains (DSCs). While switching to DSCs, the decision-making becomes more complex with an upsurge in the size of the manufacturing firms. The manufacturing firms need to develop supply chain quality management (SCQM) systems to improvise their processes for delivering advance products and services. For developing SCQM, the role of the digital supplier is significant, as they may recuperate the quality management systems (QMS) for enhancing the firm's performance. The purpose of this paper is to explore the factors that affect the selection of digital suppliers. The other purpose is to evaluate the alternatives for identifying the best supplier that enhances the QMS for DSCs.Design/methodology/approachThe decision-making is complex for digital supplier selection (DSS) and thus, the study has utilized integrated SWARA-WASPAS methods for their critical evaluation. The stepwise weight assessment ratio analysis (SWARA) method has been utilized for identifying the weightage of factors and weighted aggregated sum product assessment (WASPAS) for assessing the digital suppliers to explore the best alternative. The integrated SWARA-WASPAS method is the most advance approach in multi-criteria decision-making (MCDM) for the evaluation of the factors.FindingsThe study reveals that supplier competency is the most significant factor in selecting digital supplier in DSC that may improve the product and service quality. The study also explores that manufacturing firms needs an efficient system for developing value for the internal and external partners that help them to cope up with the dynamic world. On the basis of the WASPAS results, supplier S8 has been ranked as the best supplier who has highest competency in the form of responsiveness, resilience, sustainable practices and digital innovation.Research limitations/implicationsThe factors are assessed on the decision team of experts that may be biased and thus, the research may further be validated through empirical studies. The research has to be extended in other nations for exploring how organizations and customers are responding to the DSCs.Practical implicationsThe study has given insights to the manufacturing firms to consider the crucial factors for DSS, as it affects the overall performance of the organizations. The decision makers of manufacturing organizations should consider the factors such as supplier competency, digital innovation and information sharing for value creation that may provide them better opportunities for developing their DSCs along with their digital suppliers to connect with stakeholders appropriately.Social implicationsThe improved SCQM aligned with DSS will offer quality products that are sustainable and provide social and economic benefits to the society. The DSS will be able to provide improvisation of the existing products and services for developing a sustainable value chains for the manufacturing organizations. This process will bring more transparency, viability and sustainability in the product and services. As a result, the DSC partners will be more transparent, viable and resilient.Originality/valueThe research on DSS and its importance in enhancing QMS is limited. This research is the novel approach to understand the criteria behind the selection of the digital suppliers’ role and their presence in enhancing the quality of products and services.

show abstract

Digital Supplier Selection for a Garment Business Using Interval Type-2 Fuzzy Topsis

Cited by 19 publications

References 35 publications

Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool

Leagile and sustainable supplier selection problem in the Industry 4.0 era: a case study of the medical devices using hybrid multi-criteria decision making tool

An Overview of Fuzzy Techniques in Supply Chain Management: Bibliometrics, Methodologies, Applications and Future Directions

Digital supplier selection reinforcing supply chain quality management systems to enhance firm's performance

Contact Info

Product

Resources

About