Conclusion
This paper carried out a unique literature review to classify MCDM techniques with focus on automotive industries. The review categorized 45 scholarly papers from 33 journals until October 2015 into 5 application areas. We classified them by publication year, publication journal, country of application. We found that MCDM techniques have been successfully applied to a wide range of applications in automotive industry. The methods in engineering design are the most frequent, followed by environment and supply chain. We observed that AHP was the most consistent technique followed by PROMETHEE. Integrated approaches were more usual than individual ones. Application of fuzzy methods to tackle uncertainty was also observed [127,24,85,38,14,132,27,90,74]. There is a gap on the use of MCDM for automotive design focused in EE, although a review of the published literature on automotive industry analyzed here indicates greater applicability of MCDM methods for dealing with complex decision-making in automotive sectors with different subjects and terms. None of them focused on EE from automakers point of view. Although there are papers for fleet selection [5,133,74] and fuel selection [134,135,17,129,136] none of them focused on supporting a rational decision on which features should be adopted on each vehicle in order to enhance EE. The methods have been widely used to handle multiple, conflicting criteria even though increasing popularity and applicability of these methods beyond 2010 indicate a paradigm shift in MCDM approaches. It is clear that application of MCDM on automotive design for EE is an option and should be object of future researches.
