3PL evaluation and selection using integrated analytical modeling. (8th May 2017)
- Record Type:
- Journal Article
- Title:
- 3PL evaluation and selection using integrated analytical modeling. (8th May 2017)
- Main Title:
- 3PL evaluation and selection using integrated analytical modeling
- Authors:
- Haldar, Abhijeet
Qamaruddin, Umer
Raut, Rakesh
Kamble, Sachin
Kharat, Manoj Govind
Kamble, Sheetal Jaisingh - Abstract:
- Abstract : Purpose: The purpose of this paper is to propose a framework for evaluating and selecting the most optimal third-party logistics (3PL) service provider vendor among the available ones. Selection is done based on the performance values of the vendors on certain predefined criteria. Design/methodology/approach: An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem has been used to develop a new model for the selection of 3PL vendor. First, DEA is used to evaluate the efficiency of each vendor according to the identified criteria. Second, TOPSIS is applied to rank the maximally efficient vendors. Finally, LP problem is stated and solved to ascertain the quantities to be allocated to each maximally efficient vendor in the context of multiple logistics provider. The proposed DEA–TOPSIS–LP (DETOLP) model is finally tested with real-time industry data for 3PL vendor evaluation and selection. The study, thus, proposes a three-step hierarchical technique for selection of 3PL vendor based on the multiple criteria decision-making approach. Findings: The paper focuses on assessing the performance of 26 vendors using a combined approach of DEA, TOPSIS and LP. It is observed that vendor V4 outperforms all the considered vendors, which exactly corroborates with the present scenario within the company. Research limitations/implications: Exclusion ofAbstract : Purpose: The purpose of this paper is to propose a framework for evaluating and selecting the most optimal third-party logistics (3PL) service provider vendor among the available ones. Selection is done based on the performance values of the vendors on certain predefined criteria. Design/methodology/approach: An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem has been used to develop a new model for the selection of 3PL vendor. First, DEA is used to evaluate the efficiency of each vendor according to the identified criteria. Second, TOPSIS is applied to rank the maximally efficient vendors. Finally, LP problem is stated and solved to ascertain the quantities to be allocated to each maximally efficient vendor in the context of multiple logistics provider. The proposed DEA–TOPSIS–LP (DETOLP) model is finally tested with real-time industry data for 3PL vendor evaluation and selection. The study, thus, proposes a three-step hierarchical technique for selection of 3PL vendor based on the multiple criteria decision-making approach. Findings: The paper focuses on assessing the performance of 26 vendors using a combined approach of DEA, TOPSIS and LP. It is observed that vendor V4 outperforms all the considered vendors, which exactly corroborates with the present scenario within the company. Research limitations/implications: Exclusion of qualitative criteria for 3PL vendor selection and the judgment of weights for TOPSIS can be considered as the limitations of the present work. The study has significant practical implications for organizations belonging to any sector or industry. It can help them in evaluating the existing 3PL vendors and selecting the most efficient among them. Originality/value: This paper deals with a framework modeled for 3PL vendor selection. It is the first attempt to utilize an integrated approach, i.e. DETOLP model for evaluation and selection of 3PL. For assessment of the model, real data from an Indian company has been taken to analyze the result and compare it with the present scenario within the company. … (more)
- Is Part Of:
- Journal of modelling in management. Volume 12:Number 2(2017)
- Journal:
- Journal of modelling in management
- Issue:
- Volume 12:Number 2(2017)
- Issue Display:
- Volume 12, Issue 2 (2017)
- Year:
- 2017
- Volume:
- 12
- Issue:
- 2
- Issue Sort Value:
- 2017-0012-0002-0000
- Page Start:
- 224
- Page End:
- 242
- Publication Date:
- 2017-05-08
- Subjects:
- Performance management -- Decision-making -- Operations management -- Supply chain management -- MCDM -- DEA -- TOPSIS -- Linear programming -- Third-party logistics
Industrial management -- Mathematical models -- Periodicals
Industrial management -- Computer simulation -- Periodicals
Business -- Mathematical models -- Periodicals
Business -- Computer simulation -- Periodicals
658.4033 - Journal URLs:
- http://firstsearch.oclc.org ↗
http://rave.ohiolink.edu/ejournals/issn/17465664/ ↗
http://www.emeraldinsight.com/info/journals/jm2/jm2.jsp ↗
http://www.emeraldinsight.com/ ↗ - DOI:
- 10.1108/JM2-04-2015-0016 ↗
- Languages:
- English
- ISSNs:
- 1746-5664
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5020.575500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 59.xml