**Table 1.** *Cont.*

### *2.5. Review of Unclassified Inputs and Outputs*

Moreover, some unreasonably classified and unsorted variables, such as *available seat kilometers* (ASK) with fuel consumption added as inputs, *revenue per ton kilometers* (RTK) as output and *carbon emissions* as undesirable output to estimate the environmental efficiency of airlines were employed in Chang et al. [17]. Cui and Li [37] evaluated the transportation carbon efficiency through inputs such as *carbon dioxide emissions*, *number of employees* in the transportation sector, and *transportation service import volume* for each selected country, while *freight and passenger turnover* volume were used as outputs. The evaluation was conducted with a virtual frontier DEA, while for the investigation of factors of the impact of carbon efficiency was made with Tobit regression. Cui et al. [38] evaluated factors that influence airline energy efficiency. The evaluation was performed using the Virtual Frontier Dynamic Slacks Based Measure, where the *number of employees* and *aviation kerosene* are used as the inputs, while *revenue ton kilometers*, *revenue passenger kilometers* and *total business income* are the outputs. The

evaluation of impacts of including aviation into EU EST on airline efficiency, for each stage Li et al. [35] defined inputs and outputs. Within the operations stage, the *number of employees* and *aviation kerosene* were used as inputs, while *available seat kilometers* and *available ton kilometers* were used as outputs. For service stage, inputs were the *available seat kilometers*, *available ton kilometers* and *fleet size*, while outputs were the *revenue passenger kilometers* and *revenue ton kilometers* and undesirable output is *greenhouse gas emission* (the unique undesirable output). The *revenue passenger kilometers*, and the *revenue ton kilometers* and *sales costs* were inputs within the sales stage, while the *total business income* was output for this stage. In addition, through stages—i.e., operations and carbon abatement stages, Cui and Li [34] have evaluated the airline energy efficiency using Network SBM with weak disposability. *Salaries*, *wages and benefits*, *fuel expenses* and *total assets* were used as inputs within the operation stage, while *revenue passenger kilometers*, revenue *ton kilometers* and *estimated carbon dioxide* represented outputs. In carbon abatement, stage inputs were *estimated carbon dioxide* and *abatement expense*, while *carbon dioxide represented* the output. In measuring the energy efficiency of airlines Li et al. [35,39] Virtual Frontier Dynamic range adjusted measure was used, where the *number of employees* and *tons of aviation kerosene* represented inputs, while outputs were *revenue ton kilometers*, *revenue passenger kilometers*, and *total business income*.

In Beltrán-Esteve and Picazo-Tadeo [23] three environmental pressures—i.e., *global warming potential*, *tropospheric ozone formation potential* and *acidification potential* were used as inputs, while the *economic outcome* of the transport industry was used as an output which was measured using real gross output in purchasing parity power in evaluation environmental performance. The three environmental impact categories, i.e., *carbon footprint*, *water footprint* and *energy footprint* represented inputs, while a single output was *\$*/*ton-km carriage*, used by Egilmez and Park [24] for evaluation of environmental vs. economic performance of manufacturing sectors.

### *2.6. Review of Application of TOPSIS Method for Transport EEE Evaluation*

In the field of transport *EEE* evaluation, the real picture regarding the TOPSIS method is rather different compared to DEA. One could find a few studies where the TOPSIS method was employed in the field of the estimation of environmental efficiency of thermo power plants [40], decision making among various alternatives in eco-efficient chemical processes design [41], benchmarking building energy performance [42], selection of optimal solutions for energy consumption and thermal comfort [43], finding optimal solutions for district heating systems through various aspects such as fuel, temperature regime, level of building energy efficiency [44]. Moreover, Wang et al. [7] have used the TOPSIS method to analyze the overall hydropower efficiency in Canada from different points of view, which imply environment, technology, economy, benefits and social responsibility. However, the application of the TOPSIS method in the evaluation of transport *EEE* is not present in the literature.

### *2.7. Review of Definitions of EEE*

Several papers have presented definitions of energy efficiency or environment/environmental efficiency. For example, eco-efficiency in Egilmez and Park [24] was defined as "the ratio of total economic activity in million dollars to the overall environmental impact". Transport energy in Cui and Li [15] was defined as "an efficiency, which is calculated by comparing the relationship between the outputs and the inputs". Additionally, Cui and Li [25] have considered energy efficiency for airlines as "the relationship between the outputs and the inputs". Environmental performance has been defined by Beltrán-Esteve and Picazo-Tadeo [23] as "the quotient between economic performance and ecological performance". Since the definitions of *EEE* of transport are missing in the reviewed papers, in this paper *energy-environment e*ffi*ciency* of transport sectors is defined as the ratio of the total amount of energy consumption to production of GHG emissions as a result of the transportation process.
