Green Logistics Outsourcing Employing Multi Criteria Decision Making and Quality Function Deployment in the Petrochemical Industry

Mona Najar Vazifehdan, Soroush Avakh Darestani

Research output: Contribution to journalArticlepeer-review

30 Citations (Scopus)
98 Downloads (Pure)

Abstract

The present study seeks to provide a comprehensive and coherent model for assessing and ranking the outsourcing green logistics, while identifying the indigenous factors involved in the outsourcing process. The employed research methodology is a hybrid fuzzy multi criteria decision making for distinguishing relationships between factors and their degree of importance and combines the techniques quality function deployment (QFD). The results showed that among the main factors “government green decision making” is the most influential and “quality” is the most susceptible factor. The highest weight allocates to “customer satisfaction”. The results of house of quality showed that the “convenient and appropriate logistics services” ranked as first, the “implementation of transportation infrastructure for green policies” ranked as second, “having the necessary expertise and experience in similar industries” ranked third which reflects the importance of these requirements comparing to other requirements. The calculation results indicate that the fourth supplier is the final choice of decision making process.
Original languageEnglish
Pages (from-to)243-254
Number of pages12
JournalThe Asian Journal of Shipping and Logistics
Volume35
Issue number4
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes

Bibliographical note

Copyright ©2019 The Korean Association of Shipping and Logistics, Inc. Production and hosting by Elsevier B.V. This is an open access article under the CC-BY- NC- ND license.

Keywords

  • Green Logistics Outsourcing
  • Quality Expansion Technique
  • Fuzzy Dematel
  • Fuzzy Network Analysis
  • Superiority Inferiority Ranking method

ASJC Scopus subject areas

  • Business, Management and Accounting(all)

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