A new hybrid model based on rough step-wise weight assessment ratio analysis for third-party logistics selection


ULUTAŞ A., Topal A.

SOFT COMPUTING, vol.26, no.4, pp.2021-2032, 2022 (SCI-Expanded) identifier

  • Publication Type: Article / Article
  • Volume: 26 Issue: 4
  • Publication Date: 2022
  • Doi Number: 10.1007/s00500-021-06374-0
  • Journal Name: SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Page Numbers: pp.2021-2032
  • Keywords: 3PL provider selection, Rough SWARA, RPSI, Rough IOCRA, SERVICE PROVIDERS, 3PL PROVIDERS, SUPPLY CHAIN, CRITERIA, PERFORMANCE, ALGORITHM, BENEFITS, SYSTEMS, SET
  • Inonu University Affiliated: Yes

Abstract

Increasing competition as a result of globalization has forced the businesses to increase efficiency by focusing on the core competencies. This led businesses to outsource logistics. As a result, most of the businesses started to use third-party logistics (3PLs). There are various and conflicting criteria involved in 3PL selection, thus the selection of 3PL is a complex task for businesses. There are several methods in the literature used for 3PL selection, most of them are multi-criteria decision-making methods. A new hybrid model including Rough step-wise weight assessment ratio analysis (SWARA), Rough preference selection Index (RPSI), and Rough improved operational competitiveness rating analysis (IOCRA) has been used to select optimal third-party logistics providers in this study. There are two contributions to this study. First one is the development of a new hybrid rough model for 3PL selection. Second one is addressing the 3PL selection decision problem with newly developed Rough PSI and Rough IOCRA methods. Using this model and conducting a comprehensive analysis, the best option as a 3PL provider may be determined as a partner for logistics. The model effectiveness has been tested in a real case with a textile business and several 3PL providers.