The New European Development Scoreboard for SDG11 at the European Level

Abstract

Urban development is a current priority in terms of improving the sustainability of cities amid demographic pressure and intensive economic development in the European Union. In this context, we aim to critically analyze the progress achieved by the European Member States in the period of 2010–2022 from the perspective of Sustainable Development Goal 11—Sustainable Cities and Communities—and conceptualize the new development scoreboard from the perspective of SDG11. The methods used consist in applying principal components analysis for a set of 15 sustainability indicators related to the studied objective and designing the new sustainability index from the perspective of the ODD11 and the European ranking. The results of the study will allow for the formulation of public policies useful for European decision makers to improve the progress made relating to this objective, and we believe that their implementation could support the transformation of European cities in a sustainable and equitable way.

1. Introduction

Sustainable Development Goal (SDG11)—“Sustainable Cities and Communities”—is one of the 17 Sustainable Development Goals adopted by the United Nations in 2015 as part of the 2030 Agenda for Sustainable Development [1]. This objective emphasizes the importance of sustainable urban development and community resilience, given the growing challenges of rapid urbanization, climate change and socio-economic inequalities. Rapid urbanization has led to a number of complex problems, including increasing population density, insufficient infrastructure and services, and environmental pressures. Currently, 55% of the world’s population lives in urban areas, and this is expected to rise to 68% by 2050 [2]. Projections indicate that urbanization, the gradual shift of the population from rural to urban areas, coupled with overall global population growth, could add another 2.5 billion people to urban areas by 2050, according to studies published by the United Nations [3].

In the European context, cities play an important role in promoting sustainable development due to their high level of urbanization and multiple responsibilities in implementing environmental, economic and social policies. The analysis of the main indicators of SDG 11 at the European level provides a detailed insight into the progress and challenges in achieving the goal of creating sustainable cities and communities. Relevant indicators for assessing progress on SDG 11 include access to adequate housing, sustainable public transport, waste management, air quality and green spaces, and community involvement in decision-making. The analysis of these indicators makes it possible to assess the extent to which European cities are succeeding in developing urban environments that provide a high quality of life for all citizens while respecting and protecting the environment.

We appreciate that the integration of these indicators into a growth scoreboard will allow for a comprehensive and dynamic visualization of the current state and future trends in urban development. Such a tool will not only make it easier to monitor and assess progress but will also support decision making by highlighting areas in need of urgent interventions or policy adjustments. The scoreboard is a scientific novelty, acting as a barometer of economic sustainability and quality of life by comparing performance between different European countries.

The general aim of the research is to analyze the main indicators related to SDG 11 and to integrate them into a dashboard of economic growth in order to highlight the level of urban development in the European context and by components.

The research objectives are as follows:

• O1—Study urban development models in the literature from the perspective of SDG11;
• O2—Data standardization for applying the PCA method;
• O3—Designing the European Scoreboard from an SDG11 perspective using the PCA method;
• O4—Public policy-making on urban development in the European Union.

This holistic approach will highlight the progress made by the European Union towards Sustainable Development Goal 11—Sustainable Cities and Communities—as well as provide an analytical framework for identifying solutions to support the transformation of European cities in a sustainable and equitable way.

2. Literature Review

Sustainable urban development is a major challenge in the contemporary context of accelerated urbanization and climate change. The United Nations’ Sustainable Development Goal 11 (SDG11) is thus becoming a key priority for governments, urban planners and researchers, aiming to create cities and communities that are not only environmentally sustainable but also safe, resilient and inclusive.

Integrating economic, social and environmental aspects into urban planning and development, SDG11 emphasizes the need for a holistic approach to ensure long-term sustainability. From waste management and energy efficiency to affordable housing and social inclusion, the goal promotes innovative and sustainable solutions that can make cities better places to live for all citizens.

Sustainable urban development is a central pillar of Sustainable Development Goal 11, given the rapid growth of the global urban population. Cities are responsible for about 70% of global CO₂ emissions and consume more than 60% of energy resources [4]. Sustainable practices are therefore key to reducing negative environmental impacts and improving the quality of life of urban dwellers.

The literature highlights the need for coherent and well-informed policies to address current urban challenges such as population growth, climate change and social inequalities [5,6,7]. Cities contribute significantly to global economic development, generating over 80% of the world’s gross world product [8], with just 600 urban areas producing 60% of this total [9]. Rapid urbanization, climate change and poor management of water and waste infrastructure present urgent challenges for cities’ resilience. A study conducted by Koop and van Leeuwen [10] focused on 45 municipalities in Europe, classified cities into five sustainability categories, and highlighted the need for a proactive Urban Agenda and regional learning platforms to accelerate transitions towards resource-efficient and adaptable cities.

Transformative urban development is key to achieving sustainable development and future well-being. Webb and collaborators [11] present two conceptual frameworks to support the development of transdisciplinary strategies: a framework for ‘transforming urban systems’ and a framework for ‘knowledge for transforming urban systems’, each providing the tools and relevant knowledge needed for urban transformation. These frameworks provide insights into transdisciplinary processes and key strategies that can guide urban transformation from local to national levels.

Sustainable urban development involves not only economic growth but also environmental protection and the promotion of social inclusion. A holistic approach is essential to achieving sustainability goals, emphasizing the importance of integrating urban planning, environmental policies and economic initiatives [12]. Sustainable urban development is a multidimensional concept that transcends mere economic growth, integrating environmental protection and promoting social inclusion to create resilient and sustainable cities. In the literature, the concept of sustainable urban development is analyzed from multiple perspectives, emphasizing the need to strike a balance between the economic, environmental and social dimensions of sustainability [13,14,15]. On the one hand, the economic dimension involves promoting economic growth and urban competitiveness, while the environmental dimension emphasizes the importance of protecting natural resources and reducing negative environmental impacts. The social dimension emphasizes the creation of equitable and inclusive communities, ensuring access to adequate housing, quality services and a healthy living environment for all inhabitants.

Sustainable economic growth is fundamental to financing the necessary urban infrastructure and public services. Cities that implement sustainable economic development strategies tend to favor green industries and technological innovation. Studies show that cities that invest in green technologies and sustainable infrastructure not only diversify their economies but also generate jobs and improve citizens’ quality of life [16,17,18].

Protecting the environment is essential for maintaining ecological balance and securing the natural resources needed by future generations. In the context of accelerated urbanization, sustainable cities need to invest in green infrastructure, efficient waste management and the use of renewable energy resources to ensure long-term sustainability [19,20]. Green infrastructure, such as urban parks, vertical gardens, and green roofs, play a useful role in improving environmental conditions in urban areas.

Studies highlight that green infrastructure brings multiple benefits to the environment, the economy and society [21,22,23]. In terms of the environment, it helps improve air and water quality and promotes biodiversity. Economically, green infrastructure reduces energy and maintenance costs, stimulates job creation and increases real estate values [24,25]. Socially, access to green space improves mental and physical health, reduces stress and promotes social interaction, as well as providing educational and recreational opportunities. Green infrastructure integration is thus essential for sustainable urban development [26]. Urban parks and vertical gardens improve residents’ air quality and quality of life by providing green and recreational spaces. They help cities to adapt to climate change by absorbing rainwater, reducing the risk of flooding and pressure on sewage systems. They also help reduce the urban heat island effect caused by overheating of paved surfaces and buildings.

Efficient waste management is a vital component of environmental protection in sustainable cities [27]. Well-implemented recycling systems and waste-to-energy technologies can significantly reduce the amount of waste going to landfill [28], and programs to recycle organic waste and convert it into compost or biogas contribute to reducing methane emissions and renewable energy production [29,30,31].

The use of renewable energy resources, such as solar, wind and hydropower, is of major importance for reducing dependence on fossil fuels and cutting carbon emissions [32,33,34,35]. Investing in renewable energy technologies not only reduces the carbon footprint of cities, but also creates jobs and stimulates technological innovation. Cities that adopt policies to incentivize the use of solar panels on residential and commercial buildings help increase clean energy production and reduce long-term energy costs [36,37,38].

Social inclusion is a central pillar of sustainable urban development, ensuring equal access to resources and opportunities for all citizens and preventing social exclusion and segregation. According to studies in the literature, building cohesive and equitable cities requires the provision of affordable housing, quality health services, education and employment opportunities [39,40,41]. This is in line with the Sustainable Development Goals, which emphasize the importance of social inclusion in creating resilient and prosperous communities.

Housing affordability is a key determinant of social inclusion. Studies show that affordable housing reduces the risk of social and economic exclusion by providing stability and housing security for vulnerable groups [42,43]; social housing initiatives in European cities demonstrate how affordable housing policies can promote social and economic inclusion, thereby reducing urban inequalities [44,45].

Access to quality health services is essential for social inclusion and for the overall well-being of the urban population. Cities that invest in public health infrastructure and provide accessible and quality services contribute to reducing health disparities and creating more equitable communities [46,47].

Education and employment opportunities are important components of social inclusion. Access to quality education is fundamental for developing human capital and reducing social and economic inequalities. Education policies that promote inclusion can help integrate marginalized groups and create equal opportunities for all citizens [48,49]; access to decent and well-paid jobs is essential for ensuring a decent quality of life and reducing urban poverty [50,51].

Urban development policies must be coherent and based on sound data and detailed analysis to be effective. This implies rigorous urban planning, including all aspects of sustainable development. Policies need to be adaptable and flexible to respond to the rapid dynamics of urban change, with studies showing that cities that implement long-term strategies and integrated development plans perform better in terms of sustainability [52,53,54].

Rapid urban population growth imposes significant pressures on existing infrastructure and available resources. Managing this growth is essential to avoid overcrowding problems such as traffic congestion, pollution and inadequate access to basic services [55,56,57]; thus, urban policies must include measures to expand infrastructure and optimize land use to accommodate this growth [58,59].

Climate change is another big challenge for modern cities. Darjee and co-authors [60], as well as Rezvani and their team [61], highlighted the importance of proactive measures to reduce greenhouse gas emissions and adapt to adverse climate impacts. Various studies [62,63] have argued that integrating environmental policies into urban planning can reduce cities’ vulnerability to natural disasters and promote resilience. Proposed measures include developing green infrastructure, using renewable energy technologies and implementing sustainable resource management systems.

Another important aspect that needs to be addressed to ensure sustainable urban development is the analysis of social and economic inequalities. Sustainable cities must be inclusive, providing equal access to resources, services and opportunities for all citizens regardless of their socio-economic status. The literature emphasizes the need to promote affordable housing, quality education, health services and employment opportunities. Urban policies must be geared towards reducing poverty and combating social exclusion. Social inclusion is a determining factor in sustainable urban development [64,65], aiming to remove barriers and inequalities to enable full participation of all social groups in the economic, cultural and political life of a city. Equal access to education, health and adequate housing reduces socio-economic disparities and promotes equity. Efficient public services, such as public transport and health infrastructure, improve quality of life and support equitable urban development [66,67,68]. Equal economic opportunities, the promotion of entrepreneurship and vocational training programs are essential to ensure equal participation in the labor market and the benefits of economic growth.

Principal component analysis (PCA) is a data dimensionality reduction method that enables synthesizing information from a large set of variables into a smaller number of principal components [69]. This methodology is particularly useful in assessing progress towards Sustainable Development Goal 11 (SDG 11), which aims to create sustainable, safe, resilient and inclusive cities and communities. Within the literature, PCA is recognized for its ability to simplify data complexity and facilitate the interpretation and comparison of urban sustainability indicators [70,71,72]. From the perspective of SDG 11, PCA allows for the identification of the main components that influence urban sustainability, such as greenhouse gas emissions, energy efficiency, use of renewable energy and access to public transport [73,74,75,76].

The literature highlights the numerous advantages of using principal component analysis (PCA) to assess and monitor progress towards Sustainable Development Goal 11 (SDG 11) [77,78,79,80]. When monitoring urban sustainability indicators, the data collected are often voluminous and heterogeneous, coming from multiple sources and covering a wide range of variables. The PCA methodology simplifies these complex datasets by reducing the number of variables and extracting the main components, thus facilitating data analysis and interpretation [81,82,83,84].

For SDG 11, where multiple urban sustainability indicators are monitored, reducing data complexity through PCA is essential [85,86,87]. Indicators such as greenhouse gas emissions, energy efficiency, use of renewable energy, access to public transport and air quality are essential for assessing progress towards sustainable cities. Applying PCA allows these indicators to be synthesized into a smaller number of principal components that capture most of the variation in the original data. The PCA methodology thus facilitates not only downscaling but also the identification of the variables that have the greatest influence on urban sustainability.

Another significant advantage of PCA is its ability to identify and assess the key drivers of sustainability. By using the PCA methodology, it is possible to quickly identify the factors that contribute most to urban sustainability and prioritize the necessary interventions and policies [88,89,90,91]. By extracting the principal components, the PCA methodology can highlight critical variables and provide a sound basis for policy-making aimed at reducing negative environmental impacts and improving urban quality of life. PCA also facilitates the comparison of performance across different cities and regions in relation to SDG 11 indicators. This enables the identification of patterns and differences in sustainability performance between cities, providing a solid basis for benchmarking [92,93]. The use of principal components to represent different dimensions of urban sustainability allows a clearer and more concise analysis of the data, eliminating redundancy and facilitating the interpretation of the results.

3. Methodology

For the conceptualization of the overall dashboard, principal component analysis of the consolidated database was applied according to the information in

Table 1. Table of indicators used to construct the overall scoreboard.

Section	Symbol	Description	Source
Economic indicators on SDG11	SHDPOV	Severe housing deprivation rate by poverty status (Percentage)	Eurostat [94]
	GDPCAP	Real GDP per capita (euro per capita)	Eurostat [95]
	LTUNE	Long-term unemployment rate (Percentage)	Eurostat [96]
	LWP	Labor productivity per person employed and hour worked (Nominal labor productivity per person)	Eurostat [97]
	GDERD	Gross domestic expenditure on R&D Percentage of gross domestic product (Percentage of GDP)	Eurostat [98]
Infrastructure indicators on SDG11	RTD	Road traffic deaths, by type of roads (Percentage)	Eurostat [99]
	BTIPT	Share of buses and trains in inland passenger transport (Percentage)	Eurostat [100]
	LIAH	Level of internet access—household-(Percentage)	Eurostat [101]
	IUIND	Internet use by individuals (Percentage of individuals)	Eurostat [102]
Environmental indicators on SDG11	PHN	Population living in households considering that they suffer from noise, by poverty status (Percentage)	Eurostat [103]
	PDFP	Premature deaths due to exposure to fine particulate matter (Percentage)	Eurostat [104]
	GMW	Generation of municipal waste per capita (Kilograms per capita)	Eurostat [105]
	NGGE	Net greenhouse gas emissions (Tonnes per capita)	Eurostat [106]
	SREN	Share of renewable energy in gross final energy consumption (Percentage)	Eurostat [107]
	EEF	Energy efficiency of primary energy consumption (million tons of oil equivalent)	Eurostat [108]

Source: Authors’ calculations based on Eurostat data.

. This multivariate statistical technique was used to reduce the dimensionality of the database while preserving the essential variation present in the data (eigenvalues of the 15 variables in Table 1 were determined). The PCA method was used to identify the directions of maximum variation among the data (eigenvectors) and to determine the communalities on the basis of which the dashboard was compiled.

Since PCA is sensitive to the scale of the variables, we proceeded to standardize the debt using the mean and standard deviation of the data series. Thus, the matrix-constructed database of 5460 observations for the 15 variables, 27 states and 13 years (2010–2022) was standardized using SPSS software version no. 26 through the factor analysis module according to the following formula:

$${\mathrm{X}}_{\mathrm{s}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{a}\mathrm{r}\mathrm{d}}={\displaystyle \frac{\mathrm{X}-\mathsf{\mu }}{\mathsf{\sigma }}}$$

(1)

where μ is the mean and σ is the standard deviation for each variable, using the indicators presented in Table 1.

Then, the eigenvalues (λ) and eigenvectors (v) of the covariance matrix Σ were determined:

$$\mathsf{\Sigma }\mathrm{v}=\mathsf{\lambda }\mathrm{v}$$

(2)

The eigenvalues represent the variance captured by each principal component, and the eigenvectors represent the directions of the principal components.

The eigenvalues of the 15 variables were thus determined for each Member State (

Table 2. Eigenvalues of the 15 variables per Member State.

Indicators	SHDPOV	PHN	RTD	PDFP	BTIPT	GMW	LIAH	IUIND	GDPCAP	LTUNE	LWP	NGGE	SREN	EEF	GDERD
Belgium	0.92	0.845	0.939	0.808	0.851	0.591	0.967	0.974	0.751	0.936	0.971	0.95	0.972	0.926	0.979
Bulgaria	0.99	0.967	0.636	0.86	0.945	0.805	0.995	0.989	0.976	0.814	0.97	0.849	0.959	0.939	0.881
Czech Republic	0.958	0.834	0.868	0.852	0.847	0.95	0.975	0.965	0.961	0.982	0.963	0.952	0.975	0.892	0.844
Denmark	0.498	0.839	0.941	0.696	0.853	0.944	0.766	0.939	0.923	0.9	0.875	0.976	0.889	0.902	0.849
Germany	0.884	0.934	0.9	0.95	0.919	0.968	0.972	0.985	0.909	0.991	0.887	0.932	0.991	0.882	0.966
Estonia	0.687	0.822	0.813	0.782	0.814	0.873	0.954	0.974	0.959	0.94	0.879	0.844	0.838	0.805	0.782
Ireland	0.811	0.809	0.824	0.794	0.747	0.886	0.962	0.904	0.986	0.914	0.982	0.874	0.875	0.94	0.95
Greece	0.915	0.689	0.986	0.788	0.878	0.907	0.982	0.977	0.918	0.936	0.932	0.966	0.966	0.955	0.983
Spain	0.829	0.834	0.953	0.523	0.791	0.976	0.991	0.995	0.939	0.908	0.938	0.97	0.965	0.933	0.957
France	0.901	0.851	0.965	0.94	0.922	0.585	0.992	0.983	0.943	0.7	0.69	0.936	0.955	0.926	0.946
Croatia	0.956	0.877	0.91	0.725	0.578	0.967	0.946	0.967	0.966	0.905	0.92	0.875	0.917	0.93	0.918
Italy	0.686	0.829	0.94	0.665	0.933	0.938	0.967	0.943	0.938	0.746	0.969	0.959	0.964	0.902	0.953
Cyprus	0.838	0.867	0.684	0.698	0.908	0.952	0.99	0.987	0.982	0.871	0.891	0.901	0.976	0.949	0.967
Latvia	0.95	0.955	0.709	0.832	0.912	0.945	0.992	0.995	0.984	0.917	0.984	0.915	0.92	0.961	0.635
Lithuania	0.865	0.807	0.951	0.665	0.761	0.905	0.989	0.982	0.988	0.948	0.968	0.966	0.866	0.559	0.843
Luxembourg	0.875	0.685	0.838	0.939	0.676	0.904	0.869	0.905	0.481	0.907	0.934	0.971	0.963	0.887	0.854
Hungary	0.905	0.818	0.782	0.659	0.948	0.745	0.975	0.929	0.923	0.98	0.879	0.961	0.809	0.94	0.742
Malta	0.841	0.772	0.535	0.752	0.923	0.734	0.988	0.986	0.959	0.965	0.738	0.962	0.997	0.747	0.73
Netherlands	0.839	0.902	0.903	0.912	0.968	0.891	0.955	0.832	0.904	0.906	0.873	0.941	0.98	0.788	0.975
Austria	0.84	0.801	0.95	0.919	0.958	0.972	0.988	0.953	0.917	0.978	0.924	0.912	0.922	0.935	0.953
Poland	0.932	0.917	0.917	0.98	0.856	0.854	0.987	0.977	0.976	0.899	0.964	0.91	0.911	0.954	0.984
Portugal	0.865	0.795	0.983	0.911	0.918	0.889	0.985	0.993	0.984	0.944	0.953	0.848	0.942	0.987	0.927
Romania	0.978	0.939	0.989	0.954	0.931	0.967	0.994	0.993	0.97	0.915	0.989	0.977	0.981	0.947	0.914
Slovenia	0.846	0.904	0.775	0.825	0.863	0.848	0.974	0.967	0.918	0.937	0.94	0.913	0.883	0.886	0.933
Slovakia	0.775	0.975	0.692	0.778	0.973	0.971	0.964	0.944	0.961	0.973	0.92	0.915	0.903	0.854	0.646
Finland	0.916	0.761	0.834	0.844	0.889	0.947	0.969	0.97	0.887	0.717	0.531	0.924	0.972	0.958	0.978
Sweden	0.898	0.657	0.867	0.866	0.904	0.944	0.904	0.883	0.939	0.856	0.819	0.939	0.982	0.912	0.912

), and the average eigenvalue representation of the communalities in the overall dashboard was determined.

The analysis of Table 2 highlights a frequency of representativeness of eigenvalues whose maximum point is Romania. Thus, this country records the highest mean value (0.963) in the overall table, associating a diffuse effect of concentration of urban development, unlike countries such as Luxembourg and Malta, which accumulate a greater specialization of development through SDG11.

4. Results and Discussion

Differences in urban development between EU countries are marked by significant variations in infrastructure, living standards and access to resources, reflecting historical, economic and political disparities. The causes of these differences lie in a multitude of factors, including each country’s distinct history, which has influenced economic and social development trajectories, differences in government policies and national priorities, and unequal access to European funds and foreign investment. Figure 1 shows a representation of the vector magnitude of urban development in terms of the Sustainable Development Goals on Sustainable Cities and Communities (SDGs11) for different European countries over the period 2010–2022.

The differences in urban development between EU countries are highlighted by the significant variations in performance in achieving the Sustainable Development Goals (SDGs11), depicted in Figure 1. In this context, higher values indicate a higher degree of variable uptake due to the non-specialization of urban development, while lower values reflect a better structuring of eigenvalues by the principal component analysis (PCA) method. Thus, countries such as Romania, with a score of 0.963, show a poorer performance in achieving the SDG11 targets, indicating a diffuse structuring of urban variables. In contrast, Malta, with a score of 0.842, reflects a higher degree of specialization in urban development. Differences in levels of economic development and integration into the global economy contribute significantly to these disparities.

The comparative analysis provides a detailed insight into how the different EU Member States manage and structure sustainable urban development, highlighting the need for tailored and adaptive policies to reduce disparities and promote balanced and sustainable urban development. From Figure 1, it can be observed that the Romanian model manages to integrate the selected variables the most fully, an explanation being the weaker smart city development in Romania, which does not allow for significant differentiations in the development of indicators.

The matrix of communes at the national level was multiplied by the averages of the economic indicators to determine the overall economic component of development from the perspective of SDG 11 according to the formula:

$${{\mathrm{T}\mathrm{G}}_{\mathrm{E}}}_{\mathrm{i}}={\displaystyle \frac{{\sum }_{\mathrm{n}=1}^5\left[\begin{array}{c}{\mathrm{V}}_{{\mathrm{E}1}_{\mathrm{i}}}\\ \dots \\ {\mathrm{V}}_{{\mathrm{E}\mathrm{n}}_{\mathrm{i}}}\end{array}\right]·\left[\begin{array}{c}{\mathsf{\mu }}_{{\mathrm{E}1}_{\mathrm{i}}}\\ \dots \\ {\mathsf{\mu }}_{\mathrm{E}{\mathrm{n}}_{\mathrm{i}}}\end{array}\right]}{\sum {\mathrm{E}\mathrm{n}}_{\mathrm{i}}}}$$

(3)

where

• TG_E—General Economic Overview Score for country i, i = [1,27] over the analyzed period of 2010–2022;
• ${\mathrm{V}}_{\mathrm{E}{\mathrm{n}}_{\mathrm{i}}}$—Matrix of own economic vectors for country i in the period;
• En—number of variables considered when determining the score, n = [1,5]; n ϵ {SHDPOV, GDPCAP, LTUNE, LWP, GDERD}.

In Figure 2, the graphical representation of the scores of the Overall Scorecard of Economic Development by category of indicators from the perspective of ODD11 is presented by country.

Figure 2 provides a detailed picture of the average representation of economic community eigenvalues for different European countries. The indicators used for this analysis include the severe housing deprivation rate (SHDPOV), real GDP per capita (GDPCAP), long-term unemployment rate (LTUNE), labor productivity (LWP), and gross domestic expenditure on research and development (GDERD).

Performing countries, such as Ireland, Luxembourg, Denmark and Sweden, benefit from a well-defined strategic approach (focused on innovation, economic development and productivity), which allows them to perform well on all the economic indicators analyzed (as shown in Table 1). These countries have very high ranks in terms of economic communalities, showing robust economic development. Ireland, with an average value of 51,061.55 units, ranks first in economic development, followed by Luxembourg (40,361.78 units), providing clear examples of very well-developed economies with high levels of labor productivity and significant investment in research and development (GDERD). Germany, France and Austria also show high values, although not as extreme as Ireland and Luxembourg. These countries have stable economies with sizable GDP per capita and moderate long-term unemployment rates, indicating a sound and well-balanced economic structure.

Romania is at a lower level, with an average economic communities of 7855.37 units, reflecting a lower level of economic development compared to other European countries. It is characterized by lower labor productivity and limited investment in research and development, which underlines the need for reforms and investment to improve these aspects. Bulgaria, Latvia and Lithuania show similar or even lower values than Romania, indicating significant economic challenges. Bulgaria, for example, economic commonalities of 5945.08 units reflect acute economic difficulties that require policy and economic interventions to stimulate growth and development.

Figure 2 highlights significant economic disparities between EU Member States, with developed economies benefiting from strong infrastructures, high productivity and substantial investment in R&D, compared to emerging economies with major deficiencies in these areas. Countries with low economic performance, such as Romania, Bulgaria and Latvia, require major structural reforms and strategic investments to improve labor productivity, boost R&D and increase GDP per capita. These measures will help reduce economic disparities and promote sustainable economic development. Innovation and digitalization play crucial roles in economic growth. Countries that invest in R&D and adopt advanced technologies tend to perform better economically. Promoting a knowledge and technology-based economy is, therefore, essential for achieving sustainable development goals. This detailed analysis highlights the importance of an integrated and strategic approach to sustainable economic development in Romania and other emerging European countries. Coherent and well-planned policies, including investment in infrastructure, innovation and digitization, are essential to ensure a prosperous and equitable future for all citizens.

Applying the same algorithm, the matrix of infrastructure communities at the national level was multiplied by the averages of the infrastructure indicators to determine the overall infrastructure component of development from the perspective of SDG 11 according to the following formula:

$${{\mathrm{T}\mathrm{G}}_{\mathrm{I}}}_{\mathrm{i}}={\displaystyle \frac{{\sum }_{\mathrm{n}=1}^4\left[\begin{array}{c}{\mathrm{V}}_{{\mathrm{I}1}_{\mathrm{i}}}\\ \dots \\ {\mathrm{V}}_{{\mathrm{I}\mathrm{n}}_{\mathrm{i}}}\end{array}\right]·\left[\begin{array}{c}{\mathsf{\mu }}_{{\mathrm{I}1}_{\mathrm{i}}}\\ \dots \\ {\mathsf{\mu }}_{{\mathrm{I}\mathrm{n}}_{\mathrm{i}}}\end{array}\right]}{\sum {\mathrm{I}\mathrm{n}}_{\mathrm{i}}}}$$

(4)

where

• TG_I—The General Table of Infrastructure Indicators score for country i, i = [1,27] over the period 2010–2022;
• ${\mathrm{V}}_{{\mathrm{n}}_{\mathrm{i}}}$—Matrix of infrastructure eigenvectors for country i in period;
• In—The number of infrastructure variables considered for scoring, n = [1,4]; n ϵ {RTD, BTIPT, LIAH, IUIND}.

In Figure 3, the graphical representation of the scores of the overall Infrastructure Development Scorecard by indicator category from the perspective of SDG11 is presented by country.

Figure 3 provides a visual representation of the average eigenvalues of infrastructure communities for various European countries, using relevant indicators such as road traffic fatalities (RTDs), share of buses and trains in inland passenger transport (BTIPT), level of internet access (LIAH), and internet usage (IUIND).

High-performing countries, such as Finland, Germany and Austria, are taking a strategic approach, with high performance in both the infrastructure and economic dimensions, ensuring that both physical and economic infrastructure are well developed and interconnected to support sustainable development. These countries show high values in terms of infrastructure communalities, indicating a well-developed and modernized infrastructure. Finland, with a score of 195.75, highlights the remarkable performance of its infrastructure thanks to substantial investment in transport and technological innovation. The Netherlands, Belgium and Sweden show considerable values, reflecting a solid infrastructure supporting economic and social development. Sweden, with 185.34, demonstrates the efficiency of its public transport system and the high degree of digitalization. Romania has a score of 159.84, placing it in the second half of the ranking, indicating significant infrastructure challenges. Main problems include an aging transport fleet, lack of charging points for electric vehicles and poor road and rail infrastructure. Bulgaria, with a score of 145.27, is at the lowest level, highlighting major infrastructure difficulties affecting overall development. This illustrates significant disparities between countries with well-developed infrastructure and those in need of substantial investment and upgrading. Latvia, Lithuania and Croatia, while performing better than Bulgaria, nevertheless face similar infrastructure challenges. These countries require coordinated development and investment strategies to improve infrastructure efficiency and stimulate economic growth. Romania is in an intermediate position, better than Bulgaria and Latvia, but below countries like Finland and Germany. This suggests that while there are some improvements, more attention needs to be paid to modernizing and expanding infrastructure to bring it up to European standards. Romania and other countries with similar scores need to invest in modernizing transport infrastructure, in particular rail and road networks, to increase efficiency and safety. Digital infrastructure development is also essential to support economic growth and improve connectivity. We recognize the importance of implementing policies to reduce regional disparities in infrastructure. These should include funding and support programs for less developed regions, thus stimulating balanced and sustainable development. Innovation and sustainability must be the main pillars of infrastructure development strategies. Investments in green and energy-efficient technologies will contribute to the creation of a modern, sustainable and adaptable infrastructure to future challenges. We believe that the implementation of these measures could contribute to Sustainable Development Goal 11, which promotes sustainable cities and communities. Robust and modern infrastructure is essential for sustainable urban development, thus ensuring a high quality of life for all citizens and contributing to equitable and sustainable economic development. Applying the same algorithm, the matrix of environmental communalities at the national level was multiplied by the averages of the environmental indicators to determine the overall environmental component from the perspective of SDG 11 according to the following formula:

$${{\mathrm{T}\mathrm{G}}_{\mathrm{M}}}_{\mathrm{i}}={\displaystyle \frac{{\sum }_{\mathrm{n}=1}^6\left[\begin{array}{c}{\mathrm{V}}_{{\mathrm{M}1}_{\mathrm{i}}}\\ \dots \\ {\mathrm{V}}_{\mathrm{M}{\mathrm{n}}_{\mathrm{i}}}\end{array}\right]·\left[\begin{array}{c}{\mathsf{\mu }}_{{\mathrm{M}1}_{\mathrm{i}}}\\ \dots \\ {\mathsf{\mu }}_{{\mathrm{M}\mathrm{n}}_{\mathrm{i}}}\end{array}\right]}{\sum {\mathrm{M}\mathrm{n}}_{\mathrm{i}}}}$$

(5)

where

• TG_M—The score of the General Table of Environmental Indicators for country i, i = [1,27] over the period 2010–2022;
• ${\mathrm{V}}_{{\mathrm{n}}_{\mathrm{i}}}$—Matrix of environmental eigenvectors for country i over the period;
• In—Number of environmental protection variables considered for scoring, n = [1,6]; n ϵ {PHN, PDFP, GMW, NGGE, SREN, EEF}.

In Figure 4, the graphical representation of the scores of the General Scoreboard of the level of environmental protection according to the category of indicators from the ODD11 perspective is presented by country.

Figure 4 provides a detailed analysis of the average of the environmental community eigenvalues for different European countries using an inverse scale. This means that lower values indicate better environmental and sustainability performance. Indicators assessed include road traffic deaths (RTDs), share of buses and trains in inland passenger transport (BTIPT), level of internet access (LIAH), and internet usage (IUIND).

None of the EU27 countries seem to take a completely holistic approach, with balanced performance in all three areas (environment, infrastructure, and economic). Countries, such as Finland and Sweden, which are not mentioned as top performers in Figure 4, may have a more balanced approach, but do not specifically excel in all areas. Germany and Denmark have a strategic approach, focusing on economic development and infrastructure, but with poor environmental performance, suggesting a need to improve sustainability policies.

Estonia (with a value of 369.42 communes) shows the best performance in the field of environmental protection. This suggests effective measures to reduce greenhouse gas emissions and sustainable resource management. Romania (451.77) is among the countries with lower values, indicating an apparent performance in the implementation of environmental policies (under the impact of deindustrialization). However, at the Romanian level, the quality of infrastructure and urban logistics generate significant risks for the population in terms of road traffic fatalities. Romania must continue to invest in renewable energy, waste management and energy efficiency to further improve its performance.

Malta (533.05), Portugal (533.58), and Poland (516.34) have moderate values, suggesting that these countries are making notable progress in environmental protection but still have room for improvement.

The Netherlands (601.31) and Finland (603.15) demonstrate a strong commitment to environmental policies and sustainability, but significant environmental challenges can be seen to exist, especially in industrial regions and large urban agglomerations. Similarly, Germany (962.50) and Denmark (868.45) show high communalities, suggesting significant challenges in managing resources efficiently and reducing the negative environmental impacts of industrial activity.

Countries with high community values need to invest in green technologies and practices to reduce emissions and manage resources in a sustainable way. These investments are key to improving the quality of the environment and citizens’ lives. Innovation and the use of advanced technologies play a significant role in sustainable development. Countries must promote innovative solutions to manage resources efficiently and reduce negative environmental impacts.

The overall picture represented on the basis of the individual distributions of economic, infrastructure and environmental components relative to the European averages is presented in

Table 3. European-level scoreboard and design of the design of the new sustainability index from the perspective of the SDG11.

Indicator/Country	Economic		Infrastructure		Environment		New Sustainability Index for SDG 11	Ranking
	${{\mathbf{T}\mathbf{G}}_{\mathbf{E}}}_{\mathbf{i}}$	${\mathbf{T}\mathbf{G}}_{\mathbf{E}}=\frac{{{\mathbf{T}\mathbf{G}}_{\mathbf{E}}}_{\mathbf{i}}}{\raisebox{1ex}{$\left({\sum }_{\mathbf{i}=1}^{27}{{\mathbf{T}\mathbf{G}}_{\mathbf{E}}}_{\mathbf{i}}\right)$}\!\left/ \!\raisebox{-1ex}{$27$}\right.}$	${{\mathbf{T}\mathbf{G}}_{\mathbf{I}}}_{\mathbf{i}}$	${\mathbf{T}\mathbf{G}}_{\mathbf{I}}=\frac{{{\mathbf{T}\mathbf{G}}_{\mathbf{I}}}_{\mathbf{i}}}{\raisebox{1ex}{$\left({\sum }_{\mathbf{i}=1}^{27}{{\mathbf{T}\mathbf{G}}_{\mathbf{I}}}_{\mathbf{i}}\right)$}\!\left/ \!\raisebox{-1ex}{$27$}\right.}$	${{\mathbf{T}\mathbf{G}}_{\mathit{M}}}_{\mathbf{i}}$	${\mathbf{T}\mathbf{G}}_{\mathbf{M}}=\frac{{{\mathbf{T}\mathbf{G}}_{\mathit{M}}}_{\mathbf{i}}}{\raisebox{1ex}{$\left({\sum }_{\mathbf{i}=1}^{27}{{\mathbf{T}\mathbf{G}}_{\mathit{M}}}_{\mathbf{i}}\right)$}\!\left/ \!\raisebox{-1ex}{$27$}\right.}$	$\mathbf{T}\mathbf{G}=\frac{{\mathbf{T}\mathbf{G}}_{\mathbf{E}}{+\mathbf{T}\mathbf{G}}_{\mathbf{I}}{+\mathbf{T}\mathbf{G}}_{\mathbf{M}}}{3}$
Austria	33,669.04	146.94%	190.63	109.17%	747.34	128.29%	111.36%	9
Belgium	26,168.80	114.21%	186.66	106.90%	417.75	71.71%	120.19%	5
Bulgaria	5945.08	25.95%	145.27	83.19%	571.60	98.12%	70.35%	27
Czech Republic	16,127.22	70.39%	182.30	104.40%	544.18	93.41%	93.95%	18
Cyprus	23,074.58	100.71%	168.76	96.64%	720.62	123.70%	92.73%	19
Croatia	11,394.68	49.73%	154.35	88.39%	523.06	89.79%	83.17%	26
Denmark	43,375.31	189.31%	179.60	102.85%	868.45	149.08%	119.75%	6
Estonia	13,367.59	58.34%	180.23	103.22%	369.42	63.41%	106.42%	10
Finland	31,849.44	139.00%	195.75	112.10%	603.15	103.54%	115.90%	7
France	30,088.54	131.32%	188.41	107.90%	609.79	104.67%	111.58%	8
Germany	31,384.06	136.97%	191.14	109.46%	962.50	165.22%	102.32%	11
Greece	16,135.63	70.42%	153.71	88.03%	604.69	103.80%	84.93%	24
Ireland	51,061.55	222.85%	174.70	100.05%	584.94	100.41%	140.83%	1
Italy	24,978.60	109.02%	159.99	91.63%	698.53	119.91%	94.68%	17
Latvia	10,932.06	47.71%	180.03	103.10%	494.09	84.81%	89.57%	21
Lithuania	12,192.30	53.21%	158.38	90.70%	500.40	85.90%	86.78%	23
Luxembourg	40,361.78	176.15%	184.48	105.65%	721.80	123.90%	120.84%	3
Malta	19,448.48	84.88%	175.95	100.76%	533.05	91.50%	98.31%	12
Netherlands	36,390.55	158.82%	185.44	106.20%	601.31	103.22%	120.63%	4
Poland	11,368.72	49.62%	174.04	99.67%	516.34	88.63%	87.37%	22
Portugal	17,094.01	74.60%	156.38	89.56%	533.58	91.59%	91.11%	20
Romania	7855.37	34.28%	159.84	91.54%	451.77	77.55%	84.92%	25
Slovakia	14,076.96	61.44%	179.71	102.92%	484.42	83.15%	94.87%	16
Slovenia	17,572.89	76.69%	168.32	96.39%	492.94	84.62%	97.09%	13
Spain	22,066.38	96.31%	176.48	101.07%	624.06	107.12%	96.91%	14
Sweden	39,720.39	173.36%	185.34	106.14%	530.13	91.00%	129.79%	2
Hungary	10,942.94	47.76%	178.79	102.39%	419.09	71.94%	96.38%	15

Source: Authors’ calculations based on Eurostat data.

.

According to the data in Table 3, Romania ranks 25th out of the 27 Member States, with the graphical representation of the General Table being highlighted in Figure 5.

Figure 5 provides a comprehensive visual representation of the progress of different European countries towards Sustainable Development Goal 11 (SDG11), which aims to make cities and communities inclusive, safe, resilient and sustainable. Ireland (at 140.83% of the European average) is at the top of the league table, demonstrating exceptional performance in achieving SDG11. This is due to significant investment in urban infrastructure, active environmental policy and extensive use of advanced technologies. Sweden (129.79%), Luxembourg (120.84%), the Netherlands (120.63%) and Belgium (120.19%) also show very high scores, indicating a strong commitment to sustainable urban development and effective environmental protection measures. Austria (111.36%), France (111.58%), and Finland (115.90%) demonstrate solid performance towards SDG11, thanks to well-implemented energy efficiency and urban resource management strategies. Germany (102.32%) and Estonia (106.42%) stand out with well-developed urban infrastructure and proactive measures to reduce emissions and protect the environment. Romania (84.92%), although in an intermediate position, shows the need for substantial improvements in infrastructure and environmental policies to reach the performance levels of the top countries. Bulgaria (70.35%) is at the lower end of the spectrum, highlighting major challenges in implementing sustainable urban development measures. The significant disparities between the best and worst-performing countries underline the need for concerted efforts and the transfer of know-how to support the less-performing countries in achieving the sustainability goals.

Based on the results, we formulate the following public policies for urban development at the European level:

Public policies in the economic field:

• Promoting innovation and increasing the share of R&D spending is a public policy priority that will have the effect of accelerating the development and deployment of green technologies and increasing the sustainability of urban development through the well-being of European cities’ citizens. In this respect, national strategies should focus on effectively exploiting the development options offered by Horizon Europe programs, including by emerging economies, and efficiently implementing innovative projects through country-level collaboration between academia, the private sector and government.
• Another currently underdeveloped public policy is the fight against social inequalities and the promotion of inclusion across the European Community in line with the objectives of the European Strategy on Social Rights. Member States’ national strategies should also focus on financial support from the European Regional Development Fund (ERDF) and the European Social Fund Plus (ESF+). At the urban level, the economic effects of this policy will ensure a more stable and balanced level of well-being of European citizens and will allow the authorities to reallocate funds earmarked for the social protection of disadvantaged citizens towards sustainable community development projects. At the Member State level, depending on the economic score recorded in the scoreboards, policies should be implemented that focus on building social housing and modernizing existing ones, thus reducing inequalities and ensuring a high quality of life for all European citizens. Sound insulation measures and the creation of urban green spaces can also be integrated into urban regeneration strategies financed through the ERDF, contributing to improving the quality of life in urban areas.

Public policies on infrastructure:

• The first category of public policy that we consider necessary is the strengthening of logistics development and transport infrastructure. At the Member State level, this policy should be developed in line with cohesion policies and the funding guidelines provided by the European Regional Development Fund (ERDF). In this respect, national strategies should also incorporate funding for cross-border infrastructure projects (thus taking advantage of the opportunities offered by the Interreg programme) to facilitate cooperation between EU regions. This will enable European regions to improve their connectivity and boost economic growth through the development of road infrastructure that meets high safety and sustainability standards. At the same time, depending on the variations observed between regions, particular attention should be paid to the extension and modernization of the network of motorways and express roads. This will facilitate not only inter-urban mobility but also economic growth with a direct effect on economic development at the European level. Policies should focus on strict construction and maintenance standards to ensure the sustainability and safety of infrastructure, in line with the “traffic fatalities” variable, which emphasizes the importance of road safety.
• Another relevant policy is digital inclusion, which at the national level should take up the facilities offered by the Digital Europe Program and the ERDF, with a particular focus on bridging the digital divide in less developed regions. National policies should focus on expanding high-speed internet networks and promoting digital literacy, ensuring that all citizens have access to the opportunities offered by the digital economy.

Public policies on environmental protection:

• Sustainable waste management and environmental protection should be promoted at the level of each Member State in line with the EU Action Plan for the Circular Economy and with the financial support provided by the European Regional Development Fund and the Cohesion Fund. Member States should implement an effective system of separate waste collection, develop infrastructure for recycling and composting and reduce the environmental impact of waste, in line with the EU’s objectives of reducing pollution and protecting natural resources.
• Promoting green transport and the energy transition in line with the European Green Deal and with the support provided through the Just Transition Fund are very important public policies for all Member States to achieve their targets for renewable energy consumption and energy efficiency in order to make the transition to climate neutrality. Public policies must support the installation of electric vehicle infrastructure and stimulate the purchase of electric vehicles by the population. At the same time, more concrete measures are needed to improve the energy efficiency of buildings and reduce the energy consumption of the population by empowering them and implementing green energy solutions for household consumption.

The implementation of these policies and a holistic approach to the urban development process will enable the European Union to improve progress towards Sustainable Development Goal 11—Sustainable Cities and Communities—supporting the transformation of European cities in a sustainable and equitable way.

5. Conclusions

This study addressed the sustainable development of the EU countries from the perspective of SDG 11. All the objectives of this research have been achieved, being projected the general scoreboard of the development of the European Union Member States from the perspective of SDG 11, which is a novelty that contributes to the literature, both in terms of the investigative purpose and the replicability of the methodology presented in detail throughout the research. The results show the disparities in development at the EU level. None of the EU27 countries seem to take a completely holistic approach, with balanced performance in all three areas (environment, infrastructure, and economic). Thus, Eastern European countries, in general, show lower scores compared to Western European countries, indicating a greater need for resources and effective policies to improve the quality of urban life and environmental protection. South Eastern European countries need to significantly improve their infrastructure, including transportation networks, energy efficiency and digital infrastructure. Investments in rail and road infrastructure are essential to increase connectivity and urban mobility. Strong environmental policies are needed to reduce greenhouse gas emissions and manage waste in a sustainable way. Developing renewable energy and promoting resource efficiency are critical to achieving sustainability goals. They need to stimulate economic growth by promoting innovation and R&D.

We appreciate that the holistic approach is important to achieving SDG 11, with balanced performance in all three areas (environment, infrastructure, and economic). The implementation of coherent and well-planned policies (as outlined in the discussion chapter), including investments in infrastructure, innovation and environmental protection, contribute to the creation of sustainable and resilient cities and communities. The overall scoreboard for SDG11 at the European level highlights both the remarkable progress and the significant challenges that countries need to address to ensure a sustainable and resilient future for all citizens.

The analysis of urban development in Europe for the period 2010–2022 reveals considerable differences between countries in their ability to achieve the SDG11 targets. Central and Eastern European countries, including Romania, need to address multidimensional challenges to improve the quality of urban life and ensure sustainable development. These findings can guide policy makers in targeting investments and formulating policies that support balanced and sustainable urban development across Europe.

The limitations of this study are the relatively limited period of only 13 years over which the analysis was carried out, and the authors intend to extend this research on a future occasion, determining sustainable development scenarios based on the revised scoreboard, which will allow the refinement of urban development policies and the improvement of urban development strategies.