Abstract

Abstract Supplier selection and evaluation are among the most critical issues in supply chain management, affecting companies’ performance because of the important role of suppliers in the chain’s profitability. For this reason, it is important for companies to have an objective methodology to evaluate and choose an appropriate supplier based on convenient criteria in a competitive market. Determination of a convenient supplier selection is a multi-criteria decision-making (MCDM) problem. In the literature, several applications of the MCDM methods for supplier evaluation and selection can be found; however, research studies in the clothing industry are still limited. Indeed, apparel supply chain managers have to consider their supplier-related decisions to reduce risks affecting the company’s performance. This study aims to fill this gap by providing apparel manufacturers with different hybrid models for selecting the best supplier. According to a literature review and questionnaire conducted, the main criteria related to supplier selection were identified and determined. Then, the analytic hierarchy process method was performed to determine the criteria’s weights, and then suppliers were ranked using hybrid multicriteria decision-making models (AHP-TOPSIS, AHP-WSM, and AHP-WPM) to select the suitable one in the apparel chain. This research methodology can be considered useful for apparel companies and other industries.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.