Development of a decision support framework for sustainable freight transport system evaluation using rough numbers
Morteza Yazdani,
Dragan Pamucar,
Prasenjit Chatterjee and
Shankar Chakraborty
International Journal of Production Research, 2020, vol. 58, issue 14, 4325-4351
Abstract:
Among various operational decision-making tasks in a transportation system, sustainable performance evaluation has a very promising and direct influence on the community as well as environment. To prevent and reduce the negative impacts of a freight transportation system, a constant monitoring and performance measurement system has of paramount significance in the process of supply chain management. However, studies of complex transport evaluation systems are very scarce in the existing literature. This paper aims to resolve the problem of freight transport system’s performance measurement while developing a comprehensive framework with incorporation of sustainable elements and establishing a rough set-based decision-making approach. The applicability of the proposed framework is investigated to evaluate the performance of seven freight transportation companies in Spain. A decision support tool is designed by integrating rough number-based decision-making trial and evaluation laboratory (DEMATEL) and multi-attributive border approximation area comparison (MABAC) methods for their performance appraisal. Sensitivity analysis and comparison with other popular methods are also performed to validate the efficacy of the proposed approach. It is established that rough number-based methodologies have advantages over fuzzy or interval-based models.
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2019.1651945 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:58:y:2020:i:14:p:4325-4351
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2019.1651945
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().