Model of Determining the Optimal, Green Transport Route among Alternatives: Data Envelopment Analysis Settings

Abstract

Data envelopment analysis (DEA) is a useful method for determining relative efficiency in many types of businesses, including the transport sector. In line with the European Union’s (EU) policy of sustainable development of transport, external costs become the competitiveness factor of the transport route valorization. Presenting specific DEA settings, the paper aims to show and test a developed model for determining the optimal transport route among alternatives towards the same destination where external cost as a socio-ecological factor is included in DEA, along with transport cost (quantitative factor) and transport time (qualitative factor). In order to adhere to the principles of the least possible energy consumption, the given distance that also included in DEA settings represents the shortest route between the starting point and destination, as a unique and constant output variable. Therefore, the optimal direction selected by the DEA stands for the green route. The capabilities of the DEA, set up in this way within the broader model, are demonstrated in the practical case.

Current State of Environmental Awareness of Transport Service Stakeholders and End-Customers in the Intermodal Transport Chain

“…Nevertheless, there are several areas in the literature that attempt to solve the problem of minimizing emissions from the perspective of comparing entire intermodal transport chains and their efficiency, as well as their individual transport legs and transhipment points as intermodal terminals. Vukić et al (2020) proposed a DEA-based model to determine the most efficient route of multiple intermodal transport chains based on the lowest external cost and the shortest route and called it green route. Similarly, Saeedi et al (2019) proposed a network model DEA to identify inefficiencies in intermodal transport chain and give an opportunity for policy makers to prepare a more tailored measures.…”

The Impact of an Environmental Way of Customer’s Thinking on a Range of Choice from Transport Routes in Maritime Transport

“…To determine the approximation [19] function, we come out from the measured values ((xi, yi), i = 0, 1, 2,..., n), where the selected values of the measurement are represented with xi variable and the measured values yi represent the values of the function f(x) at point xi. In that case, the resulting approximation function has the following form:…”

“…With an increasing number of transported containers, we can expect an increase in the loading capacity of container ships; this is also related to the volume of consumed fuels and released emissions. Thus, in the future, it can be anticipated that the trend development of container transport's impact on the environment will copy the trend of the container transport's growth on individual transport routes [19][20][21]. Since there is no need to know the exact values but rather a long-term trend of the development, it is appropriate to apply the method of least squares due to its simplicity and time undemandingness.…”

“…To determine the approximation [19] function, we come out from the measured values ((x i , y i ), i = 0, 1, 2, . .…”

“…With an increasing number of transported containers, we can expect an increase in the loading capacity of container ships; this is also related to the volume of consumed fuels and released emissions. Thus, in the future, it can be anticipated that the trend development of container transport's impact on the environment will copy the trend of the container transport's growth on individual transport routes [19][20][21]. Likewise, many studies state that from the point of view of the total performance of vessels and installation of marine engines, the main share will mostly represent container ships (Table 3), and as noted in Table 3, the average operating hours of these vessels per year is expected to reach 6700-7200 h/year [7].…”