Abstract
The sustainable performance of the intermodal transport chain has gained popularity in recent decades, especially due to climate change and numerous European laws aimed at minimizing the negative impacts of transport. In this paper, we have developed a novel three-phase, two-stage approach that is a combination of distance-based analytic hierarchy process/data envelopment analysis (AHP-DEA). The added value of this multi-criteria approach is in evaluating a sustainable intermodal transport chain, with prioritization of the most efficient combinations of transport in accordance with the weights derived from its users. Instead of the classic pairwise comparison, the weights of the criteria were determined using a new distance-based AHP method in which respondents were asked to sort the criteria (transportation time, price, emissions, and variability) pre-selected from the literature in order of greatest importance. Therefore, the approach determines the most efficient transport chain in the transportation corridor. Since a transportation corridor was previously defined, the settings for this corridor were set to constant initial variables. In this way, the above criteria were chosen as inputs, with DEA aimed at minimizing these variables and presenting the results in ranks from highest to lowest efficiency. The potential of our approach was presented in a case study, where the most efficient of the selected transport chains between Asia and the northern Adriatic were chosen. The results show that there are different intermodal transport chains, each of which consists of either maritime and rail transport or maritime and road transport. The paper concludes that the presented multicriteria approach has greater discriminatory power than the current DEA, as well as greater flexibility, since the weights can be derived faster and more effortlessly than is typical. Therefore, this method can help transportation organizers to determine which intermodal transportation chain is the most efficient or sustainable in any given situation.
Subject
Ocean Engineering,Water Science and Technology,Civil and Structural Engineering
Cited by
5 articles.
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