2011Logistics TechnologyRequires access

Application of Fuzzy Comprehensive Evaluation in Logistics Business Outsourcing

Ning Li

Open publisher page 1 citations

Abstract

In this paper,a third-party logistics enterprise evaluation index system is established using a combination of quantitative and qualitative analytical methods,which,coupled with AHP and two-layered fuzzy comprehensive evaluation method,is capable of evaluating and selecting third-party logistics enterprises.

About this research paper

What this paper is about

In this paper,a third-party logistics enterprise evaluation index system is established using a combination of quantitative and qualitative analytical methods,which,coupled with AHP and two-layered fuzzy comprehensive evaluation method,is capable of evaluating and selecting third-party logistics enterprises.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

In this paper,a third-party logistics enterprise evaluation index system is established using a combination of quantitative and qualitative analytical methods,which,coupled with AHP and two-layered fuzzy comprehensive evaluation method,is capable of evaluating and selecting third-party logistics enterprises.

Key concepts: Outsourcing, Analytic hierarchy process, Fuzzy logic, Business, Third party, Evaluation methods, Process management, Integrated logistics support

Related papers

Back to paper searchBrowse research topicsOriginal source
Application of Fuzzy Comprehensive Evaluation in Logistics Business Outsourcing — Research Paper | ScholarLens