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dc.contributor.authorSharif, A.
dc.contributor.authorIrani, Z.
dc.contributor.authorLove, Peter
dc.contributor.authorKamal, M.
dc.date.accessioned2017-01-30T14:56:51Z
dc.date.available2017-01-30T14:56:51Z
dc.date.created2015-03-03T20:15:16Z
dc.date.issued2012
dc.identifier.citationSharif, A. and Irani, Z. and Love, P. and Kamal, M. 2012. Evaluating reverse third-party logistics operations using a semi-fuzzy approach. International Journal of Production Research. 50 (9): pp. 2515-2532.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/42014
dc.identifier.doi10.1080/00207543.2011.581012
dc.description.abstract

The responsiveness and efficiency of distributed and multi-echelon supply chains are increasingly reliant upon reduced cycle times within forward and reverse logistics operations. Within the high-tech industry, Reverse Logistics (RL) in the form of end-of-life, stock balancing, defective/warranty, recycle, and re-use product returns, is particularly important owing to the complexity and dependency that exist throughout the extended supply chain in order to maintain brand loyalty and customer satisfaction (source, OEM vendors and end customers alike). RL is fast becoming a strategy to acquire an organisational competitive advantage, making the quest to exploit such a function a premeditated decision. The introduction of Third-Party Logistics (3PL) providers has become a necessity for those supply-chain operations where issues of cost and risk mitigation need to be balanced with agility and responsiveness. This paper develops a conceptual framework of the factors influencing Reverse 3PL based upon Information Systems (IS) and associated Resource Commitment (RC) factors. The framework is then tested using a mixed-method research based approach using a 3PL organisation based in Thailand. The research findings reveal that among the proposed factors, IS- and RC-based operating performance, resource cost-effectiveness and RC (at financial, managerial and technological levels in the firm) were deemed to have a stronger positive relationship and input into reverse 3PL operations for the firm in context. The model is validated using the techniques of System Dynamics and Fuzzy Cognitive Mapping.

dc.publisherTaylor & Francis
dc.titleEvaluating reverse third-party logistics operations using a semi-fuzzy approach
dc.typeJournal Article
dcterms.source.volume50
dcterms.source.number9
dcterms.source.startPage2515
dcterms.source.endPage2532
dcterms.source.issn00207543
dcterms.source.titleInternational Journal of Production Research
curtin.departmentDepartment of Construction Management
curtin.accessStatusFulltext not available


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