A 3PL supplier selection model based on fuzzy sets

Authors:
Fachao Li;Ling Li;Chenxia Jin;Ruijiang Wang;Hong Wang;Lili Yang
Affiliations:
School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China;Department of Information Technology and Decision Sciences, Old Dominion University, Norfolk, VA 23529, USA;School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China;School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China and School of Business and Economics, Beijing Jiaotong University, Beijing 100044, China ...;School of Business and Economics, North Carolina A&T State University, Greensboro, NC 27411, USA;School of Business and Economics, Loughborough University, Leicestershire LE11 3TU, UK
Venue:
Computers and Operations Research
Year:
2012

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Abstract

Outsourcing is an increasingly important task pursued by enterprises seeking improved efficiency. Logistics outsourcing, or third-party logistics (3PL), involves the use of external companies to perform some or all of the firm's logistics activities. In this paper, through analyzing the features and role of third-party logistics, for 3PL provider selection, we propose an indicator system and a method for data integration. We also establish a comprehensive evaluation model for 3PL suppliers based on fuzzy sets; furthermore, we propose a compound quantification model based on centralized quantification values, a comparison method based on the synthesis effect, and a 3PL supplier selection model. A real-world case analysis is provided. The results show that the proposed 3PL supplier selection model can effectively integrate decision preferences into decision processes.