An Integrated PIPRECIA and COPRAS Method under Fuzzy Environment: A Case of Truck Tractor Selection

Abstract

Selecting the right truck tractor is critical for logistics companies involved in road freight transportation. The fact that having many conflicting criteria and many alternatives complicates the decision-making process for the decision-makers (DMs). The determination of the criteria that are effective in the selection of truck tractors and then the evaluation of the alternatives are the main objectives of this study. In this context, a hybrid Multi-Criteria Decision-Making (MCDM) model composed of Fuzzy PIPRECIA (F-PIPRECIA) and Fuzzy COPRAS (F-COPRAS) methods is proposed to be used in the selection of truck tractors. In the related literature, no studies that applied F-PIPRECIA and F-COPRAS together to determine the best truck tractor have been published yet. In this regard, this study is thought to contribute to the literature both in terms of the methods used and the application of truck tractor selection. Moreover, the findings of this study will pave the way for those who conduct academic studies and the authorities of companies involved in road transport in the logistics sector.