Evaluation and Selection of Public Transportation Projects in Terms of Urban Sustainability Through a Multi-Criteria Decision-Support Methodology

Abstract

Climate change, the consequences of which have been more intense than ever in the last few decades, makes the need for sustainable transportation even more imperative. The promotion of public transportation and the discouragement of private car use are among the main priorities of sustainable transport planning in modern urban areas. However, the selection of the most appropriate transport project, apart from significant opportunities, is also accompanied by significant challenges, especially under the demand of compromising—often conflicting—social, environmental, and economic criteria, as well as different stakeholders’ interests. The aim of the present paper is to provide decision analysts and policy-makers with a decision-support tool for the prioritization and optimum selection of public transport projects for an urban area within the framework of sustainability. For this purpose, a comprehensive inventory of criteria for the evaluation of urban public transport systems (alternatives), along with a standardized table with the relevant performance of the most common alternatives (i.e., metro, tram, monorail, and BRT) are provided based on international literature review. A multi-criteria decision-aiding methodology based on TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), allowing for the direct exclusion of an alternative not meeting certain “binding” criteria from further evaluation, thus saving time, effort and cost, taking into account different stakeholders’ interests and preferences, as well as the particularities and special characteristics of the study area, is then proposed and tested through a theoretical case study.

1. Introduction

Approximately 25% of global CO₂ emissions are due to the transport sector, with road transportation being responsible for roughly 75% of these emissions [1,2]. The problem is even worse in urban areas, where the majority of the global population lives (with increasing trends) and to which the greatest percentage (over 78%) of energy consumption, as well as CO₂ emissions (over 70%), is attributed [3,4]. Regarding Europe, private cars are responsible for about 60.6% of total CO₂ emissions due to road transportation [5].

Aiming at becoming climate-neutral (an economy with net-zero greenhouse gas emissions (GHGs)) by 2050, the EU launched the European Green Deal in 2019, with the aforementioned goal integrated into a legal framework through the European Climate Law [6,7,8]. Especially concerning the transport sector, the adoption of sustainable mobility solutions, through the promotion—among others—of public transportation and zero-emission vehicles is considered to be of high importance towards achieving the goal of a climate-neutral EU economy by 2050 and—as an intermediate goal—reducing net GHGs by at least 55% by 2030 compared to 1990 levels [7,8].

Hence, apart from the positive consequences of the transport sector in terms of socio-economic development through the transport of goods and people, there are negative consequences as well, which are mainly related to climate change and local air pollution [9], making the shift to more sustainable transport options mandatory. The global socio-economic and environmental crisis of the last few years make even more imperative the need for sustainable transport planning, especially in urban areas, where the majority of the population lives. Sustainable transport planning constitutes a high priority for governments, institutions, and research centers all over the world, especially in the European Union (EU). During the last few decades, a high number of initiatives with a view to promoting sustainable urban mobility have taken place in the EU, with Sustainable Urban Mobility Plans (SUMPs) constituting an important tool towards this direction. The promotion of mass transit systems, along with the discouragement of private car use, are among the main priorities of sustainable transport planning in modern urban areas. Thus, urban mass transit systems, and especially urban guided transport systems (such as metro, tram, monorail and Bus Rapid Transit-BRT), arise as particularly promising solutions to sustainable mobility challenges, gaining more and more ground globally in urban areas [2,10,11,12,13,14,15].

Cost–Benefit Analysis (CBA) and Multi-Criteria Analysis (MCA) methods seem to be the most common evaluation methods for transport projects [16,17,18], supporting relevant decision-making, while Cost-Effectiveness Analysis (CEA) is also implemented in certain cases [19]. It should be noted, though, that MCA methods become more and more popular, while CBA and similar methods (e.g., CEA) are seen with skepticism due to the need to translate all parameters of the analysis into monetary units (often leading to not only uncertain or misleading results—and therefore decisions—but also to ethical questions, such as those regarding measuring the value of human life and experience) and to the inability to address the interests of different stakeholders [18,20,21,22]. On the contrary, MCA methods offer the opportunity for the inclusion of both qualitative (e.g., visual intrusion, travel comfort, etc.) and quantitative parameters in the analysis without the need for translating them into monetary units, while—at the same time—allowing for the inclusion of experts’ opinions and different stakeholders’ interests in the analysis. MCA can be used for the efficient management of large volumes of data by a decision analyst, especially in the case of transport project evaluation with sustainable mobility criteria (in the context of which conflicting social, economic, and environmental criteria must be met at the same time) [16,17,18,19,20,23].

“Public transport has the potential to reach the lowest transport intensity, as it traditionally uses high-capacity vehicles, well suited to serve high-density and high-demand mobility corridors” [24]. Given that public transport use is promoted within the framework of sustainable urban mobility, the development of efficient urban public transport systems can substantially contribute to a lower dependence on private cars, accompanied by all the relevant benefits related with sustainable transportation [25,26]. Urban guided transport systems, in specific, are considered a highly promising solution to sustainable mobility problems in urban areas. However, they are characterized by higher complexity and increased requirements (thus, more criteria) compared to other transport projects. For these reasons, the present work focuses on the most common urban guided transport systems (metro, tram, monorail, and BRT). Given that new vehicle technologies, such as autonomous vehicles, have emerged as promising alternatives in the context of sustainable urban mobility [18], intelligent transport systems, such as autonomous BRTs, could also constitute alternatives to be evaluated in future applications of the proposed methodology.

Given the absence of a standardized decision support tool for the evaluation and selection of urban transport projects within the framework of sustainability in the international literature, including all potential evaluation criteria, as well as the performance of the most common urban transport systems with regard to each criterion, the aim of the present paper is to provide decision-makers and decision analysts with a support tool for the prioritization and optimum selection of urban public transport projects for a specific area, taking into account the particularities and different needs of each system and urban area, within the framework of sustainability. For this purpose, first of all, a comprehensive inventory of evaluation criteria is provided based on exhaustive literature review. Moreover, a table with the performance of each transport system with regard to each evaluation criterion, “translated” into numbers, is also provided, so that any MCA can be applied by a decision analyst or policy-maker for the comparison of the above-mentioned systems. Finally, a multi-criteria decision-aiding approach is proposed and applied in a numerical example.

The structure of the paper is as follows. The proposed TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method for MCA and also the features of the examined urban public transport systems are briefly described in Section 2. The inventory of evaluation criteria and the suggested performance values of each alternative in terms of each criterion are presented in Section 3. The steps of the proposed methodology for the evaluation of urban transport systems in the context of sustainability are also included in Section 3. A numerical example, along with a sensitivity analysis, is presented in Section 4, while the main conclusions can be found in Section 5.

2. Materials and Methods

2.1. Brief Description of TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)

As mentioned in Section 1, MCA methods are regarded as ideal for project evaluation and selection within the framework of sustainable urban mobility, as they allow for a holistic evaluation of different urban transport projects, integrating sustainability aspects. MCA methods outweigh other traditional methods for transport project evaluation, such as CBA and CEA, for the reasons already mentioned in Section 1.

AHP (Analytic Hierarchy Process), VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), ELECTRE (Élimination et Choix Traduisant la Réalité), and PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations), either alone or in combination, are among the most common MCA methods for transport project evaluation [16,18], especially in the context of sustainability [18,27,28,29,30,31]. There is no right or wrong MCA method, but there is an appropriate method for each problem, while, in many cases, the same problem can be solved by more than one MCA method, with the majority of them being characterized by similar organization and decision matrix construction, with the only differentiation referring to data synthesis [18,32]. In this research work, given the large number of evaluation criteria, TOPSIS was selected for the evaluation of urban transport systems in the context of sustainability. Apart from the large number of evaluation criteria, making TOPSIS particularly appropriate for such a problem, TOPSIS is also characterized by the fewest rank reversal problems compared to other MCA methods and is easy to understand and to apply, while it does not require the purchase of a specific software for its application, as it can be easily applied by using MS Excel [18].

For the application of TOPSIS [33], a decision matrix, as that shown in Equation (1), for n criteria and m alternatives is formulated, where the element x_ij represents the performance of the alternative A_i in terms of the criterion C_j, where i = 1, 2, …, m and j = 1,2, …, n.

$$\begin{gathered} {\mathrm{C}}_1\hspace{1em}{\mathrm{C}}_2\hspace{1em}\dots \hspace{1em}{\mathrm{C}}_{\mathrm{n}} \\ \mathrm{D}=\begin{array}{c}{\mathrm{A}}_1\\ {\mathrm{A}}_2\\ \dots \\ {\mathrm{A}}_{\mathrm{m}}\end{array}\left[\begin{array}{cccc}{\mathrm{x}}_{11}& {\mathrm{x}}_{12}& \dots & {\mathrm{x}}_{1\mathrm{n}}\\ {\mathrm{x}}_{21}& {\mathrm{x}}_{22}& \dots & {\mathrm{x}}_{2\mathrm{n}}\\ \dots & \dots & \dots & \dots \\ {\mathrm{x}}_{\mathrm{m}1}& {\mathrm{x}}_{\mathrm{m}2}& \dots & {\mathrm{x}}_{\mathrm{m}\mathrm{n}}\end{array}\right] \end{gathered}$$

(1)

Then, the above decision matrix is normalized by applying a normalization technique. For example, adopting the vector normalization technique, the elements r_ij of the matrix can be calculated using Equation (2):

$${\mathrm{r}}_{\mathrm{i}\mathrm{j}}={\displaystyle \frac{{\mathrm{x}}_{\mathrm{i}\mathrm{j}}}{\sqrt{\sum _{\mathrm{i}=1}^{\mathrm{m}}{\mathrm{x}}_{\mathrm{i}\mathrm{j}}^2}}},$$

(2)

The weighted normalized matrix, with the v_ij elements, is then formulated using Equation (3):

$${\mathrm{v}}_{\mathrm{i}\mathrm{j}}={\mathrm{w}}_{\mathrm{j}}·{\mathrm{r}}_{\mathrm{i}\mathrm{j}} ,$$

(3)

where w_j is the weight of the criterion C_j (where j = 1, 2, …, n), and Σwj = 1.

The ideal (A⁺) and negative-ideal (A⁻) solutions are then calculated:

A⁺ = {(max_iv_ij|j ∈ J), min_iv_ij|j ∈ J′)|i = 1, 2, …, m} = {v₁⁺, v₂⁺, …, v_j⁺, …, v_n⁺}

(4)

A⁻ = {(min_iv_ij|j ∈ J), max_iv_ij|j ∈ J′)|i = 1, 2, …, m} = {v₁⁻, v₂⁻, …, v_j⁻, …, v_n⁻},

(5)

where J = {j = 1, 2, …n, and j refers to benefit criteria}, and J′ = {j = 1, 2, …n, and j refers to cost criteria}.

The distance of each alternative from the ideal and the negative-ideal solution (“separation measure”) is then calculated, applying the “Euclidian distance method”.

The Euclidian distance of the alternative A_i from the ideal solution (S_i⁺) is calculated as follows:

$${{\mathrm{S}}_{\mathrm{i}}}^{+}=\sqrt{{\sum }_{\mathrm{i}=1}^{\mathrm{m}}{({\mathrm{v}}_{\mathrm{i}\mathrm{j}}-{\mathrm{v}}_{\mathrm{i}}^{+})}^2}, \mathrm{where} \mathrm{i}=1,2,\dots ,\mathrm{m}.$$

(6)

The Euclidian distance of the alternative A_i from the negative-ideal solution (S_i⁻) is calculated as follows:

$${{\mathrm{S}}_{\mathrm{i}}}^{-}=\sqrt{{\sum }_{\mathrm{i}=1}^{\mathrm{m}}{({\mathrm{v}}_{\mathrm{i}\mathrm{j}}-{\mathrm{v}}_{\mathrm{i}}^{-})}^2}, \mathrm{where} \mathrm{i}=1,2,\dots ,\mathrm{m}.$$

(7)

Finally, the relative closeness c_i⁺ to the ideal solution is calculated:

$${{\mathrm{c}}_{\mathrm{i}}}^{+}={\displaystyle \frac{{\mathrm{S}}_{\mathrm{i}}^{-}}{({\mathrm{S}}_{\mathrm{i}}^{+}+{\mathrm{S}}_{\mathrm{i}}^{-})}}, \mathrm{where} 0\le {{\mathrm{c}}_{\mathrm{i}}}^{+}\le 1\mathrm{for} \mathrm{i}=1,2,\dots ,\mathrm{m} ({{\mathrm{c}}_{\mathrm{i}}}^{+}=1 \mathrm{if} {\mathrm{A}}_{\mathrm{i}}={\mathrm{A}}^{+} \mathrm{and} {{\mathrm{c}}_{\mathrm{i}}}^{+}=0 \mathrm{if} {\mathrm{A}}_{\mathrm{i}}={\mathrm{A}}^{-})$$

(8)

The calculated c_i⁺ values are used for the final ranking of the alternatives (maximum c_i⁺ value → best alternative).

2.2. A Brief Description of the Examined Urban Public Transport Systems

As mentioned in Section 1, urban guided public transport systems are a highly promising solution to sustainable mobility problems in urban areas, while their evaluation is characterized by a higher complexity and increased requirements in terms of evaluation compared to other transport projects. For these reasons, the present work focuses on the most common urban guided public transport systems (metro, tram, monorail, BRT), which are briefly described below.

The term “urban guided public transport systems” refers to “all public urban guided passenger transport systems: metros, trams on tracks or tires and other similar rail systems” [34], which are “the most consolidated terrestrial means of transport along a dedicated corridor, i.e., a fixed permanent way” [10].

It should be noted that the present work exclusively refers to ‘point-to-point’ routes shorter than 40 km (one way), thus transport systems such as suburban railways and tram-trains have not been taken into consideration and have not been examined.

2.2.1. Metro

A metro (heavy or light, depending on the maximum transport capacity) is an urban guided public transport system, the operation of which is mainly based on traditional steel railway wheels, and in certain cases on rubber tires, with electric traction. This transport system, also referred to as a “subway” or “underground railway”, operates underground for the longest part of the route and is always grade-separated from the urban road network used by road vehicles and pedestrians [35,36]. A metro is a relatively complex transport system and is generally preferred as a transport project in urban areas with the following: a population higher than 1,000,000 people, travel demands higher than 10,000 passengers/hour/direction, air pollution problems, and the scarcity of public space required for transport infrastructure [35]. A metro is characterized by a high system capacity, reliability, safety (with the main danger related to evacuation in case of fire), travel comfort, environmental friendliness, high speed, and affordability for all users, while it provides opportunities for urban development through higher spatial accessibility and less uptake of public space [13,36,37,38].

2.2.2. Tram

The modern tramway is a steel wheel electric train, either catenary-fed or catenary-free (powered by a Ground-Level Power Supply, Onboard Energy Storage System, or Onboard Power Generation System), operating on the same level as road traffic in urban and suburban areas [35,39]. It uses the same infrastructure as road vehicles, moving on a specially built right-of-way or segregated (protected) lane, which may be located in the middle of a road or at a single side or at two opposite sides [10,35]. A typical tramway uses a double track (two one-way traffic lines), constructed either with conventional flat bottom rails or with grooved rails embedded in the pavement [35]. A tramway is generally preferred as a transport project in urban areas with the need for urban regeneration or upgrades, with air pollution problems, and with a relatively low travel demand (<10,000–15,000 passengers/hour/direction) or with a travel demand higher than 10,000 passengers/hour/direction and in cases where a metro system cannot be constructed due to economic “stringency” or issues related to subsoil or archeological findings [35]. A tram tends to decrease the use of private cars in an area, mainly through the integration of the tramway corridor along existing roads, thus significantly reducing the street capacity and parking space for private cars [10].

2.2.3. Bus Rapid Transit (BRT)

According to the US Federal Transit Administration (2024) [40], “Bus Rapid Transit (BRT) is a high-quality bus-based transit system that delivers fast and efficient service that may include dedicated lanes, busways, traffic signal priority, off-board fare collection, elevated platforms, and enhanced stations”. BRT, also referred as “bus-metro” or “surface metro”, is as fast, reliable, and flexible as a traditional urban rail system and as economic as a conventional bus system [41,42]. According to Cervero, 2013 [42], there are two main categories of BRTs, “light BRTs” and “high-end (full) BRTs”, with “high-end (full) BRTs”, which are examined in the present study and will be referred to as BRTs hereinafter, being characterized by a higher service level [42]. BRT moves on a dedicated lane of a slightly modified road infrastructure [14]. BRT is generally preferred as a transport project in urban areas with relatively low or medium travel demands (3000–8000 passengers/hour/direction). It can be also applied in the case of higher travel demands (more than 10,000 passengers/hour/direction), if a tramway, a monorail, or a metro cannot be constructed due to issues related to topography, urban sprawl, or economic “stringency” [14]. It is implicit that there is land available for the construction of terminals in the urban area periphery, as well as that the existing road infrastructure allows for the construction of a dedicated lane per direction for the BRT in order to select such an urban guided transport system for an urban area [14,43].

2.2.4. Monorail

A monorail is an electrified light rail passenger transport system, usually constituting 2–6 (in rare cases 7–8) vehicles and operating—in most cases—on rubber-tire wheels, using a permanent way (guideway) [10,35]. This permanent way, which in most cases is elevated (despite the fact that a monorail may also move at grade, below grade, or in subway tunnels for certain parts of the route), is in fact a beam, taking over the traffic loads and guiding and supporting monorail vehicles [35]. A monorail is generally preferred as a transport project in urban areas with touristic attractions; for relatively short routes; for the connection of areas separated by natural barriers (e.g., rivers); for amusement parks, zoos etc.; or in environmentally protected areas, where the introduction of a surface or underground guided system is difficult. During the last few years, an increasing use of monorail systems has been recorded at airports, shopping malls, etc. The size and headway of a monorail system determine the system volume capacity, with the ability to achieve significant maximum volume capacity values (20,000–25,000 passengers/hour/direction), e.g., line 15 of the Sao Paolo monorail in Brazil) [10].

3. Inventory of Evaluation Criteria, Suggested Alternatives’ Performance, and Proposed Methodological Framework

3.1. Inventory of Evaluation Criteria Based on International Literature Review

In the first phase of this research, an inventory of evaluation criteria for the optimum selection of urban transport systems for an area based on an international literature review is presented in

Table 1. Inventory of evaluation criteria for the optimum selection of urban mass transit systems for an area based on international literature review.

Categories	Criteria	Description	Sources
Environmental	Air pollution and greenhouse gas (GHG) emissions	PMX, COVNM, NOX, CO, and CO2 emissions	[2,28,29,36,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62]
	Noise pollution	Noise generated by the operation of transport systems, disturbing citizens	[44,45,46,48,50,51,52,53,60,61,62,63,64,65,66]
	Visual intrusion	Degradation or improvement of the landscape due to transport (e.g., tramway cables, signaling equipment, vehicles, track superstructure, etc.)	[10,35,46,52,53,67]
	Vibrations	Vibrations generated by the operation of transport systems, harassing people and buildings	[10,65,66,68,69]
	Energy consumption	Energy consumption of the transport system	[48,50,51,53,54,56,58,70,71,72]
	Land take	Land consumption due to transport infrastructure	[14,35,44,45,46,48,50,59,61,73]
Social	Safety	Transport safety relating to traffic accidents both at frequency and at severity levels, evacuation difficulty, etc.	[2,36,44,45,46,48,49,50,52,53,54,55,56,57,58,59,65,67,69,74,75,76,77,78,79,80,81,82]
	Security	Exposure of transport means users or employees are exposed to delinquent/criminal behavior (robbery, theft, terrorist attacks, etc.)	[57,74,80,83,84,85,86]
	Impact on residents, land use, the economy, other transport modes, etc. (construction phase)	Impact on residents, land use, the economy, motorized and non-motorized transport, etc., during construction phase	[10,35,46,49,66,87]
	Impact on residents, land use, the economy, other transport modes, etc. (operation phase)	Impact on residents, land use, the economy, motorized and non-motorized transport, etc., during operation phase	[10,35,36,46,49,66,68,71,88,89]
	Public acceptance	Approval or support of the project by the community	[10,52,53]
Economic	Initial investment/Implementation cost	Costs relating to design, construction, rolling stock acquisition, signaling equipment, expropriation, etc.	[28,46,48,49,51,52,53,54,55,59,60,67,69,70,74,83,90,91,92]
	Operation and maintenance cost	Costs relating to the operation, management, and maintenance of the system	[28,29,35,46,48,51,52,53,54,55,58,60,68,70,74,75,90,92,93]
Strategic planning	Integration in terms of ground surface	Placement of the transport system with regard to the ground level (underground, elevated, or at ground level)	[35,36,61,78,92]
	Spatial and urban development of the area	Contribution of the construction and operation of the transport system to the spatial and urban development of the area	[36,44,45,47,53,54,55,59,82,88]
	Revitalization, redesign, and upgrading of the area	Contribution of the construction and operation of the transport system to the revitalization and redesign of the area	[44,45,54,59,82,88]
	Discouragement of private car use in the area	Contribution of the transport system to the discouragement of private car use and to the promotion of public transport in the area	[36,44,45,47,54,55,57,59,62,94]
Design and Construction	Track horizontal alignment difficulties	Difficulties related to track horizontal alignment with regard to the minimum curve radius	[10,14,35,70]
	Track vertical alignment difficulties	Difficulties related to vertical alignment with regard to maximum gradient	[10,14,48,70]
	Route length	Length of the route connecting the origin and destination point	[10,48,82,95]
	Constructability of stops/stations	Easiness of constructing stops/stations (flexibility related with geometric integration and construction)	[14,35,46,48]
	Availability of depot facilities	Availability of required facilities for parking, servicing, system maintenance, administration buildings, staff facilities, etc.	[10,14,35,73]
	Technology availability in the market	Easiness of finding the required technology (of infrastructure and rolling stock) in the industry market	[10,35,77]
	Barriers related to archeological discoveries during the construction phase	Barriers related to archeological findings during the construction phase	[10,87,96]
	Implementation/construction time	Time required for the completion of the project	[53,55,67,83,87,97]
	Flexibility in line/network expansion	Easiness of expanding the line/network in the future	[46,67]
Functional and Operational	Maximum transport system capacity	Maximum passenger capacity for each route during operating hours in a day	[13,14,36,46,48,51,55,67,74,75,83,85,90]
	Travel time (first/last mile time)	Door-to-door time	[2,50,52,53,55,56,59,70,74,81]
	Commercial speed (run time)	Time required for a vehicle to make one trip along the whole length of the route	[13,14,35,36,51,57,67,69,75]
	Service reliability	The ability of a transport system to provide consistent service over a period of time, with a comparison between real and scheduled time (this may be affected by the weather, congestion, number of passengers, etc.)	[36,46,48,54,60,74,75,77,79,85,98]
	Difficulty with maintenance	Difficulty in maintaining the transport system (e.g., monorail may be characterized by relatively high difficulty in maintenance)	[10,48,55,82,92]
	Travel comfort	Dynamic comfort, space comfort, and staying comfort during traveling	[2,36,46,54,57,65,67,74,77,80,81,99]
	Accessibility	Easiness of reaching bus stops and accessibility relating to people with impairments	[2,35,46,49,52,53,54,57,60,67,75,94,100,101,102,103]
	Frequency/headway	Frequency is the rate at which transit units pass a fixed point, usually expressed per hour; it is the inverse of headway but is usually expressed in minutes	[2,35,46,48,57,67,70,74,77,90,98]
	Complementarity/Inter-modality with other transport means	Complementarity degree with other means of transport, walking, cycling, park-and-ride solutions, etc.	[36,48,49,51,57,59,70,94,103]

. An inventory of the evaluation criteria was constructed so as to include the most common urban guided transport systems (metro, tram, monorail, BRT) and to cover the higher complexity and increased requirements of the respective public transport projects compared to other urban transport projects. The identified criteria are categorized in six main categories, integrating sustainability principles, i.e., environmental, social, and economic, as well as covering the requirements for strategic planning, design and construction, and functional and operational features.

Apart from the classification in the above-mentioned categories, some of the identified evaluation criteria can also be characterized as “binding” in cases where they have to be definitely met, as imposed by the preferences of the contracting authorities or the particularities and needs of the study area. For example, in cases where a contracting authority is not willing to adopt an elevated system due to visual intrusion reasons, the criterion of “visual intrusion” is characterized as “binding”, and the alternative of a monorail system is directly excluded from further evaluation. Another example of a “binding” criterion might be related to financial stringency, which may lead to the characterization of the criterion of “implementation cost” as “binding” and thus to the direct exclusion of a metro system from further evaluation, given that it is characterized by the highest implementation cost.

Given that each urban area is unique and has its own characteristics and needs, the formulation of a common list of evaluation criteria of “candidate” transport systems is not feasible. For this reason, the inventory of evaluation criteria shown in Table 1 can serve as a “pool” for the decision-makers or decision analysts and can be adapted to each specific area, taking into account its specific characteristics, conditions, and needs. This way, certain criteria might be removed, while others might be added, depending on the urban area for which the alternative public transport systems are evaluated. Regarding the “binding” criteria, obviously, a criterion characterized as “binding” for one study area may not be “binding” for another study area, and vice versa.

3.2. Suggested Performance Values of the Examined Urban Public Transport Systems with Regard to Each Criterion

In the second phase of this research, a table including the performance of each examined urban transport system (alternative) with regard to each evaluation criterion was formulated (

Table 2. Performance of urban guided mass transit systems with regard to each criterion (benefit functions).

Category	Criteria	Performance of Each System with Regard to Each Criterion (1–10 Scale, Where 1 → Worst Rating and 10 → Best Rating)
		Metro	Tram	BRT	Monorail
Environmental	Air pollution and GHG emissions	9	7	2	7
	Noise pollution	9	3	7	5
	Visual intrusion	10	6	6	2
	Vibrations	4	4	8	6
	Energy consumption	8	9	2	6
	Land take	10	4	3	7
Social	Safety	8	8	8	5
	Security	6	8	8	8
	Impact on residents, land use, economy, other transport modes, etc. (construction phase)	3	2	8	3
	Impact on residents, land use, the economy, other transport modes, etc. (operation phase)	8	2	9	6
	Public acceptance	9	7	7	4
Economic	Initial investment/Implementation cost	2	6	9	4
	Operation and maintenance cost	2	2	5	3
Strategic planning	Integration in terms of ground surface	9	5	5	5
	Spatial and urban development of the area	10	8	3	6
	Revitalization, redesign, and upgrading of the area	8	9	2	3
	Discouragement of private car use in the area	8	9	7	4
Design and Construction	Track horizontal alignment difficulties (minimum curve radius)	3	9	8	7
	Vertical alignment difficulties (maximum gradient)	3	5	5	9
	Route length	8	5	5	5
	Constructability of stops/stations	2	4	9	5
	Availability of depot facilities	5	2	9	5
	Technology availability in the market	10	10	9	6
	Barriers related to archeological discoveries during the construction phase	2	7	10	10
	Implementation/construction time	2	7	10	7
	Flexibility in line/network expansion	9	3	3	5
Functional and Operational	Maximum transport system capacity	10	4	4	3
	Travel time (first/last mile time)	2	9	9	4
	Commercial speed (run time)	10	4	2	6
	Service reliability	8	5	2	8
	Difficulty in maintenance	4	5	7	5
	Travel comfort	5	7	4	7
	Accessibility	6	9	10	4
	Frequency/headway	8	4	5	5
	Complementarity/Inter-modality with other transport means	8	8	8	4

). In Table 2, the performance of each alternative in terms of each criterion is “translated” into a numerical value so that Table 2 can be used within the framework of an MCA method (e.g., TOPSIS or VIKOR) by a decision analyst or policy-maker for a comparative evaluation of the above-mentioned public transport systems. For the assignment of numerical values, a 1–10 scale (with 1 corresponding to the worst and 10 to the best rating) is used to express the evaluated performance of each alternative with regard to each criterion. The attributed values are based on the literature review, with the corresponding references included in Table 1. Table 2 can serve as a solid basis for adjustments to each study area and the overall evaluation of the performance of each public transport system in terms of each criterion. Aiming at minimizing any subjectivity, it is suggested that a group of local experts, having deep knowledge of the study area, participate in the assignment of the performance values to the alternatives with regard to each criterion during the adaptation of Table 2 to a real case study referring to a specific urban area. The values attributed to criteria such as public acceptance, accessibility, safety, and security depend on each individual case and should be defined in relation to the characteristics and conditions of the study area, the potential users, the route, etc.

Τhe following assumptions were made during the construction of Table 2 based on the technical and operational characteristics of a typical metro, tram, BRT, and monorail system, deriving from a review of the references included in Table 1:

• The integration, in terms of ground surface, is underground for a metro, overground for a monorail, and on the ground for a tram and BRT.
• The route length of a metro, tram, BRT, and monorail is equal to 10–40 km, 5–20 km, 3–30 km, and 5–50 km (urban use), respectively.
• The distance between successive stops is equal to 500–1000 m for a metro, 200–800 m for a tram, 350–600 m for BRT, and 800–1500 m for a monorail.
• The commercial speed (run time) of a metro, tram, BRT, and monorail is equal to 30–40 km/h, 12–30 km/h, 18–40 km/h and 15–40 km/h, respectively.
• The energy consumption of a metro, tram, BRT, and monorail (expressed in kwh per passenger-kilometer-kwh/pkm) is equal to approximately 0.03, 0.008, 0.19, 0.07, respectively.
• The maximum transport system capacity (expressed in passengers/hour/direction) of a metro, tram, BRT, and monorail is equal to approximately 45,000, 15,000, 15,000, and 12,500 (even 20,000 in certain cases), respectively.
• The travel time (first/last mile) of a metro, tram, BRT, and monorail is equal to approximately 4 min, 0 min, 0 min, and 3 min, respectively.
• The headway values are the following: <15 min (usually 2–8 min and minimum 1 min) for a metro, <20 min (usually 5–15 min and minimum 90 s) for a tram, <30 min (usually 3–15 min and minimum headway of 20 s) for BRT, and <20 min (usually 3–15 min and minimum 1 min) for a monorail.
• The land take (width) for a metro, tram, BRT, and monorail equals almost zero for a metro, 6–7 for a tram, 7–8 for BRT, and 2–3 m for a monorail, respectively.
• The track horizontal alignment (minimum curve radius) of a metro, tram, BRT, and monorail equals 150 m, 25 m, 90 m, 45 m, respectively.
• The vertical alignment (maximum gradient) (%) of a metro, tram, BRT, and monorail equals 5%, 8%, 8%, 20%, respectively.
• The implementation cost (expressed in million euros per kilometer (MEUR/km) for a double track and including infrastructure and rolling stock) of a metro, tram, BRT, and monorail is equal to 70–140, 15–35, 3–20, 30–90, respectively.
• The implementation time of a metro, tram, BRT, and monorail is equal to approximately 5–10 years, 2 years, 1–2 years, and 2 years, respectively, for a length of 10 km.
• A tram refers to a conventional system with cables (another evaluation may include a catenary-free system, as mentioned in Section 2.2).
• BRT moves with diesel fuel used by internal combustion engines, as this is a common practice.

3.3. The Steps of the Proposed Methodology and Integrating the Evaluation Criteria Tool and the Alternatives’ Performance Tool

In the third phase of this research, an MCA model was adopted for the prioritization and optimum selection of urban public transport projects for an area in the context of sustainability. The proposed model, integrating Table 1 and Table 2 as toolboxes, is summarized in the logic diagram shown in Figure 1.

As mentioned in Section 1, CBA and MCA methods are the most common evaluation methods for transport projects [16,17,18], supporting relevant decision-making, with MCA methods gaining more and more ground and CBA being seen with skepticism due to the need to translate all parameters of the analysis into monetary units (often leading not only to uncertain or misleading results—and therefore decisions—but also to ethical questions, such as regarding the measuring of the value of human life and experience) and to its inability to address the interests of different stakeholders [18,20,21,22]. At the same time, MCA methods offer the opportunity for the inclusion of both qualitative (e.g., visual intrusion, travel comfort, etc.) and quantitative parameters in the analysis without the need for translating them into monetary units, while—at the same time—allowing for the inclusion of experts’ opinions and different stakeholders’ interests in the analysis. Moreover, MCA can be used for the efficient management of large volumes of data by a decision analyst, especially in the case of transport project evaluation with sustainable mobility criteria (in the context of which conflicting social, economic, and environmental criteria must be met at the same time) [16,17,18,19,20,23]. Thus, aiming at optimum decision-making, the proposed methodology, as summarized in Figure 1, could be combined with a CBA in two different ways:

(a)

The result (e.g., Net Present Value calculated for each alternative) of a CBA could constitute a criterion for the application of the proposed methodology;

(b)

A CBA could be executed for the, e.g., two alternatives found at the top of the final ranking, as derived from the application of the proposed methodology.

4. Case Study

In order to assist the reader in understanding the proposed methodology better, a relevant application to a theoretical case study is included in the present section.

It should be noted that given that the case study included in the present work is theoretical, both the weighting of evaluation categories and criteria and the performance values of alternatives are directly assessed using the inventories of Table 1 and Table 2, respectively, without stakeholder participation, which would be needed for an adjustment of the methodology to the real-life conditions of a specific study area.

In this framework, weights are directly attributed to the evaluation categories and to the evaluation criteria selected on the basis of the relevant inventory of Table 1. In the case of a real case study, Table 1 would be adapted to a real urban area, with certain criteria being added or others being removed. For example, the impact of the examined transport systems on biodiversity might constitute a criterion for an area, depending on the specific study area characteristics, as well as the type of urban transport systems under evaluation. Furthermore, as mentioned in Step 7 of the proposed methodology, in the case of a real case study, the corresponding weights could be derived either through direct assignment of the weights or through the execution of pair-wise comparisons by experts and/or stakeholders, according to AHP [104]. Moreover, as mentioned in Section 3, a group of local experts, having deep knowledge of the study area, could participate in the assignment of the performance values to the alternatives with regard to each criterion during the adaptation of Table 2 to a real case study referring to a specific urban area. The weights attributed to the criteria categories, as well as to the criteria, are shown in

Table 3. Weights (%) attributed to the criteria and to the criteria categories.

Criteria Category	Category Weight	Criteria	Criterion Weight	Final Criterion Weight (Category Weight × Criterion Weight)
Environmental	0.25	Air pollution and GHG emissions	0.2500	0.0625
		Noise pollution	0.2000	0.0500
		Visual intrusion	0.1000	0.0250
		Vibrations	0.1000	0.0250
		Energy consumption	0.2500	0.0625
		Land take	0.1000	0.0250
Social	0.20	Safety	0.2500	0.0500
		Security	0.1500	0.0300
		Impact on residents, land use, the economy, other transport modes, etc. (construction phase)	0.2000	0.0400
		Impact on residents, land use, the economy, other transport modes, etc. (operation phase)	0.2500	0.0500
		Public acceptance	0.1500	0.0300
Economic	0.15	Initial investment/Implementation cost	0.6000	0.0900
		Operation and maintenance cost	0.4000	0.0600
Strategic planning	0.10	Integration in terms of ground surface	0.2500	0.0250
		Spatial and urban development of the area	0.2500	0.0250
		Revitalization, redesign, and upgrading of the area	0.2500	0.0250
		Discouragement of private car use in the area	0.2500	0.0250
Design and Construction	0.10	Track horizontal alignment difficulties (minimum curve radius)	0.0500	0.0050
		Vertical alignment difficulties (maximum gradient)	0.0500	0.0050
		Route length	0.1000	0.0100
		Constructability of stops/stations	0.1000	0.0100
		Availability of depot facilities	0.1000	0.0100
		Technology availability in the market	0.1000	0.0100
		Barriers related to archeological discoveries during the construction phase	0.1000	0.0100
		Implementation/construction time	0.2000	0.0200
		Flexibility in line/network expansion	0.2000	0.0200
Functional and Operational	0.20	Maximum transport system capacity	0.2000	0.0400
		Travel time (first/last mile time)	0.1000	0.0200
		Commercial speed (run time)	0.1000	0.0200
		Service reliability	0.1000	0.0200
		Difficulty in maintenance	0.0500	0.0100
		Travel comfort	0.1000	0.0200
		Accessibility	0.1500	0.0300
		Frequency/headway	0.1000	0.0200
		Complementarity/Inter-modality with other transport means	0.1000	0.0200

. Moreover, the maximum transport system capacity, route length, track horizontal alignment, and vertical alignment are defined as “binding” criteria. It is assumed that none of them leads to the exclusion of any of the examined alternatives from the evaluation process. As a result, all of the four alternatives are evaluated.

TOPSIS is then applied for the extraction of the final ranking of the alternatives, according to the steps included in Section 2.1, as follows. The decision matrix for the application of TOPSIS is formulated, according to Equation (1), expressing the performance of each alternative in terms of each criterion shown in

Table 4. Decision matrix for TOPSIS application.

	Air Pollution and GHG Emissions	Noise Pollution	Visual Intrusion	Vibrations	Energy Consumption	Land Take	Safety	Security	Impact on Residents, Land Use, the Economy, Other Transport Modes, etc. (Construction Phase)	Impact on Residents, Land Use, the Economy, Other Transport Modes, etc. (Operation Phase)		Public Acceptance
Metro	9	9	10	4	8	10	8	6	3	8		9
Tram	7	3	6	4	9	4	8	8	2	2		7
BRT	2	7	6	8	2	3	8	8	8	9		7
Monorail	7	5	2	6	6	7	5	8	3	6		4
	Initial investment/Implementation cost	Operation and maintenance cost	Integration in terms of ground surface	Spatial and urban development of the area	Revitalization, redesign, and upgrading of the area	Discouragement of private car use in the area	Track horizontal alignment difficulties (minimum curve radius)	Vertical alignment difficulties (maximum gradient)	Route length	Constructability of stops/stations	Availability of depot facilities	Technology availability in the market
Metro	2	2	9	10	8	8	3	3	8	2	5	10
Tram	6	2	5	8	9	9	9	5	5	4	2	10
BRT	9	5	5	3	2	7	8	5	5	9	9	9
Monorail	4	3	5	6	3	4	7	9	5	5	5	6
	Barriers related to archeological discoveries during the construction phase	Implementation/construction time	Flexibility in line/network expansion	Maximum transport system capacity	Travel time (first/last mile time)	Commercial speed (run time)	Service reliability	Difficulty in maintenance	Travel comfort	Accessibility	Frequency/headway	Complementarity/Inter-modality with other transport means
Metro	2	2	9	10	2	10	8	4	5	6	8	8
Tram	7	7	3	4	9	4	5	5	7	9	4	8
BRT	10	10	3	4	9	2	2	7	4	10	5	8
Monorail	10	7	5	3	4	6	8	5	7	4	5	4

. As mentioned above, the performance values for the specific case study derive directly from the suggested values of Table 2.

The normalized decision matrix for the application of TOPSIS, based on Equation (2) and Table 4, is shown in

Table 5. Normalized decision matrix for TOPSIS.

	Air Pollution and GHG Emissions	Noise Pollution	Visual Intrusion	Vibrations	Energy Consumption	Land Take	Safety	Security	Impact on Residents, Land Use, the Economy, Other Transport Modes, etc. (Construction Phase)		Impact on Residents, Land Use, the Economy, Other Transport Modes, etc. (Operation Phase)	Public Acceptance
Metro	0.6653	0.7028	0.7538	0.3482	0.5882	0.7581	0.5431	0.3974	0.3235		0.5882	0.6445
Tram	0.5175	0.2343	0.4523	0.3482	0.6617	0.3032	0.5431	0.5298	0.2157		0.1470	0.5013
BRT	0.1478	0.5466	0.4523	0.6963	0.1470	0.2274	0.5431	0.5298	0.8627		0.6617	0.5013
Monorail	0.5175	0.3904	0.1508	0.5222	0.4411	0.5307	0.3394	0.5298	0.3235		0.4411	0.2864
	Initial investment/Implementation cost	Operation and maintenance cost	Integration in terms of ground surface	Spatial and urban development of the area	Revitalization, redesign, and upgrading of the area	Discouragement of private car use in the area	Track horizontal alignment difficulties (minimum curve radius)	Vertical alignment difficulties (maximum gradient)	Route length	Constructability of stops/stations	Availability of depot facilities	Technology availability in the market
Metro	0.1709	0.3086	0.7206	0.6917	0.6364	0.5521	0.2106	0.2535	0.6786	0.1782	0.4303	0.5617
Tram	0.5126	0.3086	0.4003	0.5534	0.7160	0.6211	0.6317	0.4226	0.4241	0.3563	0.1721	0.5617
BRT	0.7689	0.7715	0.4003	0.2075	0.1591	0.4830	0.5615	0.4226	0.4241	0.8018	0.7746	0.5055
Monorail	0.3417	0.4629	0.4003	0.4150	0.2387	0.2760	0.4913	0.7606	0.4241	0.4454	0.4303	0.3370
	Barriers related to archeological discoveries during the construction phase	Implementation/construction time	Flexibility in line/network expansion	Maximum transport system capacity	Travel time (first/last mile time)	Commercial speed (run time)	Service reliability	Difficulty in maintenance	Travel comfort	Accessibility	Frequency/headway	Complementarity/Inter-modality with other transport means
Metro	0.1257	0.1407	0.8082	0.8422	0.1482	0.8006	0.6385	0.3730	0.4241	0.3931	0.7016	0.5547
Tram	0.4401	0.4925	0.2694	0.3369	0.6671	0.3203	0.3990	0.4663	0.5937	0.5896	0.3508	0.5547
BRT	0.6287	0.7036	0.2694	0.3369	0.6671	0.1601	0.1596	0.6528	0.3393	0.6551	0.4385	0.5547
Monorail	0.6287	0.4925	0.4490	0.2526	0.2965	0.4804	0.6385	0.4663	0.5937	0.2620	0.4385	0.2774

, while the weighted normalized decision matrix for the application of TOPSIS, using the criteria weights shown in Table 3 and according to Equation (3), is described in

Table 6. Weighted normalized decision matrix for TOPSIS.

	Air Pollution and GHG Emissions	Noise Pollution	Visual Intrusion		Vibrations	Energy Consumption	Land Take	Safety	Security	Impact on Residents, Land Use, the Economy, Other Transport Modes, etc. (Construction Phase)	Impact on Residents, Land Use, the Economy, Other Transport Modes, etc. (Operation Phase)	Public Acceptance
Metro	0.0416	0.0351	0.0188		0.0087	0.0368	0.0190	0.0272	0.0119	0.0129	0.0294	0.0193
Tram	0.0323	0.0117	0.0113		0.0087	0.0414	0.0076	0.0272	0.0159	0.0086	0.0074	0.0150
BRT	0.0092	0.0273	0.0113		0.0174	0.0092	0.0057	0.0272	0.0159	0.0345	0.0331	0.0150
Monorail	0.0323	0.0195	0.0038		0.0131	0.0276	0.0133	0.0170	0.0159	0.0129	0.0221	0.0086
	Initial investment/Implementation cost	Operation and maintenance cost	Integration in terms of ground surface	Spatial and urban development of the area	Revitalization, redesign, and upgrading of the area	Discouragement of private car use in the area	Track horizontal alignment difficulties (minimum curve radius)	Vertical alignment difficulties (maximum gradient)	Route length	Constructability of stops/stations	Availability of depot facilities	Technology availability in the market
Metro	0.0154	0.0185	0.0180	0.0173	0.0159	0.0138	0.0011	0.0013	0.0068	0.0018	0.0043	0.0056
Tram	0.0461	0.0185	0.0100	0.0138	0.0179	0.0155	0.0032	0.0021	0.0042	0.0036	0.0017	0.0056
BRT	0.0692	0.0463	0.0100	0.0052	0.0040	0.0121	0.0028	0.0021	0.0042	0.0080	0.0077	0.0051
Monorail	0.0308	0.0278	0.0100	0.0104	0.0060	0.0069	0.0025	0.0038	0.0042	0.0045	0.0043	0.0034
	Barriers related to archeological discoveries during the construction phase	Implementation/construction time	Flexibility in line/network expansion	Maximum transport system capacity	Travel time (first/last mile time)	Commercial speed (run time)	Service reliability	Difficulty in maintenance	Travel comfort	Accessibility	Frequency/headway	Complementarity/Inter-modality with other transport means
Metro	0.0013	0.0028	0.0162	0.0337	0.0030	0.0160	0.0128	0.0037	0.0085	0.0118	0.0140	0.0111
Tram	0.0044	0.0099	0.0054	0.0135	0.0133	0.0064	0.0080	0.0047	0.0119	0.0177	0.0070	0.0111
BRT	0.0063	0.0141	0.0054	0.0135	0.0133	0.0032	0.0032	0.0065	0.0068	0.0197	0.0088	0.0111
Monorail	0.0063	0.0099	0.0090	0.0101	0.0059	0.0096	0.0128	0.0047	0.0119	0.0079	0.0088	0.0055

A⁺ = {0.0416 0.0351 0.0188 0.0174 0.0414 0.0190 0.0272 0.0159 0.0345 0.0331 0.0193 0.0692 0.0463 0.0180 0.0173 0.0179 0.0155 0.0032 0.0038 0.0068 0.0080 0.0077 0.0056 0.0063 0.0141 0.0162 0.0337 0.0133 0.0160 0.0128 0.0065 0.0119 0.0197 0.0140 0.0111}; A⁻ = {0.0092 0.0117 0.0038 0.0087 0.0092 0.0057 0.0170 0.0119 0.0086 0.0074 0.0086 0.0154 0.0185 0.0100 0.0052 0.0040 0.0069 0.0011 0.0013 0.0042 0.0018 0.0017 0.0034 0.0013 0.0028 0.0054 0.0101 0.0030 0.0032 0.0032 0.0037 0.0068 0.0079 0.0070 0.0055}.

.

The A⁺ and A⁻ values for TOPSIS were calculated according to Equations (4) and (5) and are given at the end of Table 6. It should be noted that the way Table 2 (and, subsequently, Table 4) is formed turns all functions into benefit functions, i.e., the highest number is the best as regards the performance of each alternative with regard to each criterion.

The calculated values for S_i⁺, S_i⁻, and c_i⁺ for TOPSIS, according to Equations (6), (7), and (8), respectively, as well as the final ranking of the alternatives are shown in

Table 7. Calculated S_i⁺, S_i⁻, and c_i⁺ values and alternatives’ ranking according to TOPSIS model.

	Si+	Si−	ci+	Ranking
Metro	0.0683	0.0702	0.5067	2
Tram	0.0664	0.0588	0.4696	3
BRT	0.0604	0.0781	0.5637	1
Monorail	0.0686	0.0435	0.3880	4

.

As concluded from Table 7, the ranking of the alternatives by TOPSIS is the following: BRT ranks first, Metro follows, Tram is found in the third position, while the last position is held by Monorail.

Furthermore, in order to reveal the impact of each criteria category on the final ranking of the alternatives, a sensitivity analysis was executed. For this reason, it is assumed that the criteria categories are not of equal importance, but a weight coefficient equal to 100% is assigned to each category, assuming that the weight coefficients of the other categories is equal to 0, while all the other values of the analysis remain the same as those in Table 3. The results are shown in

Table 8. Differentiation of the results based on the weight coefficient changes of the criteria categories.

Criteria Category	Category Weight
Environmental	0.25	1	0	0	0	0	0
Social	0.20	0	1	0	0	0	0
Economic	0.15	0	0	1	0	0	0
Strategic planning	0.10	0	0	0	1	0	0
Design and Construction	0.10	0	0	0	0	1	0
Functional and Operational	0.20	0	0	0	0	0	1
Transport system	TOPSIS ci+ values and ranking
Metro	0.5067 (2)	0.8422 (1)	0.5476 (2)	0.0000 (4)	0.8838 (1)	0.4423 (3)	0.6871 (1)
Tram	0.4696 (3)	0.5741 (2)	0.2567 (4)	0.4600 (2)	0.6798 (2)	0.3745 (4)	0.4208 (2)
BRT	0.5637 (1)	0.2848 (4)	0.8999 (1)	1.0000 (1)	0.2023 (4)	0.5768 (1)	0.3925 (3)
Monorail	0.3880 (4)	0.5293 (3)	0.3580 (3)	0.2961 (3)	0.2346 (3)	0.5045 (2)	0.3095 (4)

.

Based on Table 8, the following are apparent:

• Metro is characterized by the highest performance with regard to environmental, strategic planning, and functional and operational criteria;
• Tram exhibits relatively high performance regarding environmental, economic, and strategic planning and functional and operational criteria;
• BRT is characterized by the highest performance in terms of social, economic, and design and construction criteria;
• Monorail exhibits relatively high performance regarding design and construction criteria.

Moreover, a sensitivity analysis at the individual criterion level was also conducted, setting one’s criterion weight equal to 1 (100%) and the weights of all the other criteria of the same category to 0 so that the impact of that specific criterion on the final output can be derived. The corresponding results (with TOPSIS c_i⁺ values and relevant rankings in parentheses) are shown in

Table 9. Sensitivity analysis at the criterion level (with TOPSIS c_i⁺ values and relevant rankings in parentheses).

Transport System	Original Analysis		Environmental Criteria
	Original Analysis		Air Pollution and GHG Emissions	Noise Pollution	Visual Intrusion	Vibrations		Energy Consumption	Land Take
Metro	0.5067 (2)		0.6703 (1)	0.6509 (2)	0.7000 (1)	0.2971 (3)		0.6308 (2)	0.6753 (1)
Tram	0.4696 (3)		0.5931 (2)	0.2457 (4)	0.4747 (3)	0.2888 (4)		0.6958 (1)	0.2673 (4)
BRT	0.5637 (1)		0.3604 (4)	0.6725 (1)	0.5614 (2)	0.7633 (1)		0.3616 (4)	0.3551 (3)
Monorail	0.3880 (4)		0.5719 (3)	0.3291 (3)	0.1542 (4)	0.4089 (2)		0.4874 (3)	0.4907 (2)
Transport system	Social criteria
	Safety		Security	Impact on residents, land use, the economy, other transport modes, etc. (construction phase)		Impact on residents, land use, the economy, other transport modes, etc. (operation phase)			Public acceptance
Metro	0.5423 (3)		0.4814 (3)	0.3521 (2)		0.6230 (2)			0.5992 (1)
Tram	0.5600 (2)		0.5334 (2)	0.2898 (3)		0.3295 (4)			0.5352 (3)
BRT	0.5676 (1)		0.5472 (1)	0.7079 (1)		0.6716 (1)			0.5462 (2)
Monorail	0.3521 (4)		0.4365 (4)	0.2692 (4)		0.4829 (3)			0.2990 (4)
Transport system	Economic criteria			Strategic planning criteria
	Initial investment/Implementation cost		Operation and maintenance cost	Integration in terms of ground surface	Spatial and urban development of the area	Revitalization, redesign, and upgrading of the area			Discouragement of private car use in the area
Metro	0.4246 (3)		0.4792 (2)	0.5218 (2)	0.5483 (1)	0.5455 (1)			0.5145 (2)
Tram	0.5143 (2)		0.3602 (4)	0.4326 (3)	0.4940 (3)	0.5450 (2)			0.4992 (3)
BRT	0.6287 (1)		0.5849 (1)	0.5441 (1)	0.5105 (2)	0.4946 (3)			0.5793 (1)
Monorail	0.3608 (4)		0.3928 (3)	0.3698 (4)	0.4003 (4)	0.3497 (4)			0.3663 (4)
Transport system	Design and Construction criteria
	Track horizontal alignment difficulties (minimum curve radius)	Vertical alignment difficulties (maximum gradient)	Route length	Constructability of stops/stations	Availability of depot facilities	Technology availability in the market	Barriers related to archeological discoveries during the construction phase	Implementation/construction time	Flexibility in line/network expansion
Metro	0.4673 (3)	0.4523 (4)	0.5249 (2)	0.4311 (3)	0.4959 (2)	0.5216 (2)	0.4531 (4)	0.4422 (3)	0.5679 (1)
Tram	0.5255 (2)	0.4531 (3)	0.4551 (3)	0.4361 (2)	0.3966 (3)	0.4902 (3)	0.4947 (2)	0.4992 (2)	0.4083 (3)
BRT	0.5848 (1)	0.5344 (1)	0.5424 (1)	0.6245 (1)	0.6213 (1)	0.5679 (1)	0.6067 (1)	0.6154 (1)	0.4885 (2)
Monorail	0.4226 (4)	0.4930 (2)	0.3682 (4)	0.3947 (4)	0.3941 (4)	0.3714 (4)	0.4918 (3)	0.4361 (4)	0.3741 (4)
Transport system	Functional and Operational criteria
	Maximum transport system capacity	Travel time (first/last mile time)	Commercial speed (run time)	Service reliability	Difficulty in maintenance	Travel comfort	Accessibility	Frequency/headway	Complementarity/Inter-modality with other transport means
Metro	0.6676 (1)	0.3392 (4)	0.6810 (1)	0.6318 (1)	0.4208 (3)	0.4665 (4)	0.4465 (3)	0.4864 (2)	0.5572 (3)
Tram	0.3309 (3)	0.6560 (2)	0.3612 (3)	0.4853 (3)	0.4502 (2)	0.5505 (1)	0.5770 (2)	0.4757 (3)	0.5605 (2)
BRT	0.4048 (2)	0.7038 (1)	0.3538 (4)	0.4090 (4)	0.6356 (1)	0.5060 (3)	0.6689 (1)	0.5843 (1)	0.6349 (1)
Monorail	0.2375 (4)	0.3453 (3)	0.4610 (2)	0.6269 (2)	0.3857 (4)	0.5139 (2)	0.2929 (4)	0.4005 (4)	0.3326 (4)

. The criterion, the weight of which is set equal to 1 in each case, is shown in each column, with the corresponding derived results exactly below this criterion.

As can be observed from the results of the sensitivity analysis at the category and criterion level (Table 8 and Table 9, respectively), the derived results from the application of the proposed methodology are in alignment with the relevant literature (as summarized in Table 1).

It is noted that in the case of applying the proposed methodology to a real case study, no sensitivity analysis would be necessary, as the weights would be attributed to the criteria and the criteria categories by local experts and stakeholders.

5. Discussion and Conclusions

The contribution of the present research to the existing literature and policy-making is three-fold. First of all, decision-makers, policy-makers, and decision analysts are provided with a comprehensive inventory of criteria for the evaluation, prioritization, and optimum selection of public transport projects, incorporating all elements of both sustainable urban mobility and transport system effectiveness. This inventory, based on an exhaustive international literature review, includes all the criteria that are fundamental for such a selection and can be adapted to any urban area, taking into account its specific characteristics and needs. Thus, Table 1 can be used as a “pool” from where criteria for the evaluation of urban mass transit systems can be extracted. Furthermore, based on the above-mentioned inventory of the evaluation criteria, a standardized tool (Table 2) for the evaluation of the most common urban mass transit systems was also created. Table 2 includes suggested values that express the performance of each alternative (public transport system) in terms of each criterion based on the international literature review. Table 2 can, therefore, be used as a basis for the evaluation of the four most common urban public transport systems. Finally, a multi-criteria decision-aiding model, based on TOPSIS, was proposed and applied in a theoretical case study using the above-mentioned tools (Table 1 and Table 2).

Secondly, the proposed methodological framework, along with Table 1 and Table 2, can serve as an effective decision support tool for decision analysts and decision-makers (such as national, metropolitan, and local authorities), which can complement and be combined with other methods (e.g., CBA), for the evaluation, prioritization, optimum selection, and funding of urban public transport projects. This creates a more solid background for optimum decision-making in a transparent environment, reconciling any conflicting criteria and different stakeholders’ interests and allowing—at the same time—for the inclusion of quantitative and qualitative parameters in the analysis.

Finally, the added value of the present research is that it is aligned with the principles of contemporary planning for sustainable urban mobility, such as the principles of the EU Sustainable Urban Mobility Plan (SUMP). The transport sector is the only economic sector in Europe that is characterized by increased GHG emissions since 1990 (about 25% of total GHG emissions), and it is responsible for the majority of NO_x emissions, which are particularly harmful to public health and the environment, and substantially contributes to noise pollution [105,106]. Aiming at a climate-neutral Europe by 2050 [7], the New EU Urban Mobility Framework [107] aims to promote the decarbonization and the development of safe, resilient, smart, accessible, affordable, inclusive, and emission-free urban transport systems. In specific, capitalizing on rapid technological development, this EU policy supports the digital transition of a transport system by supporting sustainable and smart public transport projects as the backbone of collective transportation, which integrates conventional public transport with new mobility services, such as autonomous mobility and micromobility (e.g., e-scooters) [107,108]. In this framework, the strategic development of public transport systems is crucial for enabling both the green and the digital transition of urban mobility [107]. Moreover, the current EU’s trans-European transport (TEN-T) policy stresses the importance of targeted investments to improve mobility in TEN-T urban nodes, i.e., cities connected with the TEN-T network [109]. Thus, a holistic MCA approach in decision-making on urban transport projects’ selection within the framework of sustainability is of particularly high importance.

The application of the proposed methodology can achieve the following:

• It can result in direct exclusion from further evaluation of an urban transport system that does not meet one or more “binding” criteria for contracting authorities, thus saving time, effort, and costs.
• It can take into account the preferences and the—often conflicting—interests of different stakeholders, achieving a prompt compromise through a transparent process.
• It can complement CBA, either by integrating its result in the multi-criteria evaluation process as a separate criterion or by evaluating only the top-ranking alternatives through CBA, e.g., the first two in the final ranking.

The most relevant previous research work [52] refers to the application of an AHP-fuzzy TOPSIS model for the evaluation of three alternatives/urban transport projects (i.e., electric municipality bus, light rail system, modernization of existing vehicles, and network optimization) for the city of Kırıkkale, Turkey, in the context of sustainability based on 14 criteria, which are categorized in 4 main categories (i.e., environmental, economic, social, and transport). To our knowledge, there is no previous work including a TOPSIS model which integrates a comprehensive inventory of 35 criteria for the evaluation and selection of urban transport projects within the framework of sustainability, along with an inventory of the performance of the most common urban transport systems translated into numbers in a 1–10 scale based on exhaustive literature review. However, the main disadvantage of the proposed tool in this paper is related to its application to a theoretical case study. In the context of such a case study, aiming at a better comprehension of the proposed methodology by the reader, weights are directly attributed to the criteria of Table 1 and the criteria categories, while Table 2 is adopted as it is, without adaptations to a real urban area. In the case of applying the methodology to a real case study referring to a specific urban area, experts and stakeholders would participate in the process, and both Table 1 and Table 2 would serve as a basis, with certain criteria probably being removed and others being added, while binding criteria might lead to the direct exclusion of one or more alternatives. For this reason, the application of the proposed methodology to real case studies referring to specific urban areas is suggested as future work, with the involvement of local experts and stakeholders in the process. Finally, the evaluation of evolving transport trends in the context of green and intelligent urban transport systems, such as autonomous electric vehicles (e.g., autonomous electric BRTs), is also suggested in future applications to real case studies and pilot tests [110,111,112].