Development Trajectories of Two Industrial Regions in the EU Due to Different Transformation Paths—The Silesian Voivodeship in Poland and North Rhine–Westphalia in Germany

Abstract

This article compares the socio-economic development of the two industrial EU regions, the Silesian Voivodeship Poland and the Düsseldorf District in North Rhine–Westphalia, Germany, in the last 20 years of the 21st century. The Ninth Cohesion Report, the EU Regional Competitiveness Index 2.0, and the two concepts of the regional development trap and just transition in the EU were used. It investigated whether the applied EU regional policy, cohesion policy, had the expected effect of strengthening sustainable growth in the regions. This article aims to compare development trajectories, identify development traps and barriers, consider the just transition in the analyzed regions, and provide recommendations for regional policy. Those heavily industrialized regions must respond to the demographic challenges of labor shortages and an aging population. In the case of the Silesia region, the indicated course of action includes labor activation of women and migration management. For both regions, improving productivity is the key. The vital economic challenges include: for the Silesian Voivodeship—strengthening innovation; for the Düsseldorf region—maintaining innovation momentum and increasing resilience. Developing skills that meet industries’ needs is essential. Regarding social cohesion, the Silesia region should focus on equality measures. On the other hand, the Düsseldorf region should strengthen social protection against poverty.

1. Introduction

The Cyclical Cohesion Reports, published since 1996, presents a trajectory for regional development in the EU focusing on cohesion, solidarity, and equal opportunities. The focus on reducing regional disparities is a part of the treaty obligation of the European Union [1], Article 175 TFEU [2]. However, published Reports provide insight into the convergence process across the EU and include a compendium of information on the economic, social, and spatial development of EU regions as a single document presents the results of many regional policy studies. The reports are, therefore, the basis for further scientific studies on socio-economic issues. This is demonstrated, among other things, by the number of research included in the Researchgate database for the ‘Ninth Report on Economic, Social and Territorial Cohesion’ on 10th September 2024, which contains 6855 items. The problem of rebuilding and maintaining the sustainable development of regions in the EU is theoretical and empirical and is a prominent political challenge for the EU. The importance of this topic is underlined by the fact that the last two decades have been abundant on the one hand with events and phenomena categorized as ‘black swans’, in turn, to the financial crises in 2008, the pandemic in 2020, and the crisis caused by Russia’s aggression against Ukraine in 2022.

On the other hand, during this period, European integration deepened by creating the economic and monetary union and three EU enlargements. This article presents two European post-mining/mining regions (NUTS 2) in statistical terms, i.e., the Silesian Voivodeship (Śląskie region) in Poland and the Düsseldorf region in North Rhine–Westphalia in Germany. Taking into account the processes of socio-economic development in the last 20 years of the 21st century, the challenges they faced were identified, such as maintaining competitiveness in the context of a just transformation and taking into account the risk of a development trap. To this end, this article used the results of the studies included in the Ninth Cohesion Report [3] and the EU Regional Competitiveness Index 2.0 [4], and two concepts were used: the regional development trap and the just transition in the EU.

This article sets out a trajectory for the socio-economic development of two regions. The Silesian Voivodeship and the Ruhr area, where the Düsseldorf region is located, have similar historical roles as industrial powerhouses of their countries and Europe, particularly in coal and steel production. Both regions face socio-economic challenges transitioning from an industrial past to more diversified, green, innovative economies. These similarities underline the shared experiences of industrialized regions in the EU facing the need for socio-economic and energy transformation. Although the Silesian Voivodeship and the Ruhr area share a common industrial heritage, their development paths have diverged due to different political and economic influences. Both regions, from a social perspective (i.e., their population, including the number of people employed in carbon-intensive industries) as well as from an economic perspective (i.e., their contribution to GDP and GNP of national economies), pose challenges not only to regional and national but also to European regional policy, especially about the EU climate policy stemming from the implementation of the Green Deal [5].

Previous comparative studies on the Silesian Voivodeship and the Düsseldorf region were conducted over 15 years ago, i.e., in other development realities, and focused on narrower topics, e.g., restructuring of the coal sector, revitalization, development of post-industrial areas or post-industrial tourism [6,7,8,9,10,11,12,13]. Hence, a comprehensive examination of the development trajectory of the two studied industrialized post-mining/mining regions in the first two decades of the 21st century fills the research gap.

This article compares the dynamics of the socio-economic development of both statistical regions during the first two decades of the 21st century with the concept of a regional development trap [14,15,16] and the concept of just transition [17,18,19,20]. In light of the above, the following question should be asked: has the applied EU regional policy, particularly cohesion policy, delivered the expected results by strengthening sustainable growth in both regions? The thesis was formulated that EU regional policy aimed explicitly at industrialized post-mining/mining regions requires dedicated comprehensive measures to mitigate the risk of falling or being trapped in a development trap and supporting the just transition process.

This article aims to compare development trajectories, identify development traps and barriers, taking into account the just transition being in the EU NUTS 2 statistical regions, the Silesian Voivodeship and the Düsseldorf Regency, and provide recommendations for implementing regional policy.

2. Research Area

The survey area consists of two EU NUTS 2 statistical units, i.e., the Śląskie region in Poland and the Düsseldorf in North Rhine–Westphalia, Germany.

North Rhine–Westphalia (NUTS 1) is one of the 16 federal states of the Federal Republic of Germany. It comprises five government districts—Regencies (NUTS 2): Arnsberg, Detmold, Düsseldorf, Cologne, and Münster (Figure 1A). The capital city of the federal state is Düsseldorf. North Rhine–Westphalia is the most economically strong German federal state (accounting for more than 20% of the country’s DAB in 2022) with a highly industrialized and innovative economy (199.6 points in the Innovation Index of European Regions, i.e., a decisive innovator). The Regional Union of the Ruhr represents the Ruhr region in North Rhine–Westphalia. It is an area with one of the world’s largest coal, rock salt, zinc, and lead deposits. Together with the adjoining cities (min. Düsseldorf, Cologne, and Bonn), the Ruhr region is the largest polycentric agglomeration in Germany, with an estimated population of about 10–12 million inhabitants. In 2020, a coal phase-out law was adopted in Germany, which included deadlines and support measures for coal regions. As a well-advanced transition to climate neutrality, North Rhine–Westphalia has set itself a more ambitious target, i.e., to bring forward the deadline for the phase-out of lignite in the Rhine Mining Area by 8 years (until 2030). The federal state aims to become Europe’s first climate-neutral industrial region and a leader in the energy and heating transition [21]. The district of Düsseldorf, analyzed in this article, is located in the north-western part of the federal state and consists of 10 cities with county rights and five districts, subregional level NUTS 3 (Figure 2A). It is Germany’s most populous and densely populated region, although 52% of the land is farmed and one-seventh consists of forests. The area is 5.292 km², the population is 5.28 million, and the density is 997 inhabitants per square kilometer. The most important cities are Düsseldorf, Duisburg, Essen, and Bielefeld. The basis for development was the rich coal reserves in the Ruhr and lignite in the Dolnorensk region. Today, it is an area of paramount economic importance, with the headquarters of many German industrial companies.

The scientific literature divides the transformation of the Ruhr region into two distinct phases. The first lasted from 1960 to the mid-1980s and was economically motivated. During this period, the coal and steel industries were protected by investing in their further development, and selective protective support for laid-off workers was addressed. In the second phase—from the mid-1980s to the present, the emphasis was on procedural justice, including a broader range of stakeholders (especially employees and employers) in the transformation process. In this phase, the focus was also on recognizing justice, although with less success, emphasizing communities’ diverse needs and experiences, especially marginalized groups. It was a time-consuming process, requiring significant financial resources, ultimately constituting a successful example of transformation from hard coal mining to an economy based on knowledge, a dynamic service sector, and modern higher education [22].

Śląskie (NUTS 2) is one of the 16 Polish voivodships (Figure 1B), with eight subregional levels (NUTS 3) (Figure 2B). It is divided into 19 cities with county rights and 17 districts. There is the only metropolitan union in Poland, i.e., ‘Górnośląsko-Zagłębiowska Metropolia’. Silesian Voivodeship is the most urbanized and densely populated region of Poland: the surface area is 12,333 km², the population is 4.35 million, and the density is 352 inhabitants per square kilometer. The most important cities in terms of population are, for example, Katowice, Częstochowa, Sosnowiec, Gliwice, and Bielsko-Biała. The region’s development was based on the rich coal reserves in the Upper Silesian coal area. It is an area of high economic importance; the main economic sectors are services and industry, including manufacturing. The Śląskie Voivodeship is, on the one hand, the largest mining region in the EU in transition with still active coal mines and a plan to phase them out by 2049 [23].

On the other hand, it is an economically strong voivodship (in 2022, accounting for 12% of the country’s DAB), where the share of mining and quarrying in the marketed production of the industry is gradually decreasing, as shown by figures for 2022 when this share was only 10.43% compared to 82.3% for industrial processing [24]. Innovation remains a challenge for the region (62.6 points in the Innovation Index of European Regions, i.e., an emerging innovator). In the case of Śląskie Voivodeship, like the other Polish coal regions, it is necessary to develop a comprehensive transition concept that includes the creation of new development paths that comprehensively address technological, economic, and social dimensions [13].

Figure 1. Location of research areas at regional level (NUTS 2): the Düsseldorf in North Rhine–Westphalia, Germany, and the Śląskie in Poland. Source: own elaboration using the MapChart [25].

Figure 1. Location of research areas at regional level (NUTS 2): the Düsseldorf in North Rhine–Westphalia, Germany, and the Śląskie in Poland. Source: own elaboration using the MapChart [25].

Figure 2. Location of research areas for economic development indicators and development traps aggregated at sub-region level (NUTS 3) in the Düsseldorf, North Rhine–Westphalia, Germany, and in the Śląskie in Poland. Source: own elaboration using the MapChart [25].

Figure 2. Location of research areas for economic development indicators and development traps aggregated at sub-region level (NUTS 3) in the Düsseldorf, North Rhine–Westphalia, Germany, and in the Śląskie in Poland. Source: own elaboration using the MapChart [25].

3. Research Review

Contemporary theoretical and practical discourses on the socio-economic development of the regions of the European Union (OECD reports) [26,27,28,29,30,31,32,33] for almost two decades have emphasized applying a ‘place-based approach’ integrated approach, taking into account the ‘people-based approach’ dimension [34,35,36,37,38,39,40,41,42,43]. Publications on these topics are important in understanding regional growth and development, focusing on more efficient development processes. The analysis of the pace of economic convergence defined by GDP per capita used the beta (β) convergence pattern [44], according to which lower-income regions—for this article—Silesia, grow faster than those with higher incomes. As a result, this reduces interregional disparities. The process of smoothing the pace of development has been maintained despite economic shocks [45]. For the second research area, Düsseldorf, the concept of ‘secular stagnation’ [46] was used, i.e., the long-term slowdown in productivity growth characteristic of strong economies. For both regions and their sub-regions, the focus was on assessing prospects for positive and negative development scenarios using the development trap concept [15,16,47,48,49,50], defined by the weaker performance of European regions in GDP, productivity, and employment relative to them and to other regions in their countries. This approach identifies regions trapped in or at risk of falling into the development trap shortly. As both regions are examples of complex settlement systems, the risk of being stuck on the development path affects not only the whole region but also parts of it [51], hence the risks at the level of the NUTS 3 statistical sub-regions. The complexity of the settlement system also translates into a unique trajectory for the socio-economic and spatial transformation of post-industrial areas [52], as illustrated by the data included in this article. The idea of being stuck in the development trap is combined with another concept, i.e., the geography of growth, stagnation, and discontent [32,33,49,53], as poor economic performance and lack of employment opportunities generate certain social costs linked to both an increase in political discontent and a decline in support for democratic values. The socio-economic development trajectories of both regions were significantly influenced by modern megatrends, i.e., transformation, economic integration, globalization, and post-modernization [41,54]. According to the P. Churski concept, the impact of megatrends should be analyzed, taking into consideration the different development paths of Western Europe; in the case of this article, it is the Düsseldorf region and Central and Eastern Europe, represented by the Śląskie Voivodeship. In the Śląskie region, as proposed by Micek et al. [55], the emergence of a new development path from endogenous development in the IT services sector and exogenous foreign direct investment in the automotive industry is being diagnosed. According to Gwosdz et al. [56], the new development path for old coal regions is part of launching a polycentric coal-housing region in a post-industrial polycentric metropolitan (pp. 9–10).

Both regions have been in the process of just transitioning for years. Defining the concept of just transition, Newell emphasizes the issues of equality and social justice as dominant to over energy and climate justice [17]. In turn, Heffron proposes an inclusive approach to the concept, integrating three forms of justice: energy, environment, and climate [18]. Martin emphasizes the key importance of justice in sustainable development [19]. Wang reviewed various approaches to the concept of just transitions, emphasizing: the employee aspect, the justice framework, the socio-technical transformation, the management strategy, and the social perception. In his work, he emphasized the need for further empirical research [20]. Arora’s comprehensive account of the transformation of the Ruhr region (from a coalfield to a knowledge-based economy), including successes and failures, provides a knowledge base for the just energy transition process for adaptation to other economic, social and political contexts [22]. For Poland and the Silesian region, where a large part of the coal mining industry is concentrated, just transition plans were approved by the European Commission in December 2022. The just transition policy is entering the implementation phase. That is why there is a need for continuous monitoring and research of just transition policies [57,58].

Cohesion policy plays an important role in the development of the European Union regions, the main objective of which is to reduce economic [59,60,61], social [62,63,64] and territorial [65,66,67,68] disparities between regions and to ensure their continuous sustainable development [69,70,71,72]. Cooperation and relations between individual EU countries or regions in the management and implementation of EU funds, as well as undertaking joint initiatives in the use of cohesion policy, also play an important role [73].

4. Methods and Data

The research objectives above have been verified using the scientific data in the Ninth Cohesion Report [3] and the EU Regional Competitiveness Index 2.0 [4].

This article focuses on data pointing to long-lasting trends in economic convergence and the short-term impact of the COVID-19 pandemic when economic cohesion is defined. In addition, data for the high-growth path and risk of development trap implying a ‘geography of discontent’ have been included. In practice, classical statistical indicators have been used, i.e., GDP per capita, productivity, employment and unemployment rates, and working-age population, as well as synthetic indicators, i.e., Economic Development Index and Development trap index. Social cohesion is defined using statistics on the labor market (unemployment, employment in specific growth sectors), education (early, vocational, higher, continuous), poverty (at risk of poverty in various dimensions), and gender equality, equality of migrants and other minorities (difference in employment and education rates, living conditions of minorities). Regional competitiveness was measured using a synthetic indicator, i.e., the EU Regional Competitiveness Index 2.0.

In order to ensure comparability of data, this article analyses the EU statistical territorial unit NUTS 2, i.e., the Voivodship of Śląskie in Poland (identified in NUTS 2 as PL22) and the government district of Düsseldorf (Regency) in North Rhine–Westphalia in Germany (identified in NUTS 2 as DEA1). The information generated at the sub-region level was used for two synthetic indicators, i.e., NUTS 3. In addition, due to the administrative division in the case of Germany, the recommendations were addressed at the level of the NUTS 1 macro-region, i.e., the federal state of North Rhine–Westphalia. In the case of Poland, this is further the level of the NUTS 2 region, i.e., the Voivodship of Śląskie.

The statistical part is complemented by graphs on economic development indicators and development traps aggregated by EU statistics at the sub-region level (NUTS 3) based on data from the Ninth Report on Economic, Social and Territorial Cohesion [3]. In addition, graphs defining regional competitiveness using the EU Regional Competitiveness Index 2.0 aggregated by EU statistics at the regional level (NUTS 2) have been developed using the results for the 2016, 2019, and 2022 editions [4].

We relied on economic and social meters when examining the development trajectories of NUTS 2 regions using the concepts of the development trap and just transition. Data selection was made concerning the above concepts. Detailed data, based on the Ninth Report on Economic, Social and Territorial Cohesion [3], are included in Table 1. Table 2 includes information based on the EU Regional Competitiveness Index 2.0 [4].

The use of the data set from the Ninth Cohesion Report, covered in a time series of over 20 years, allowed for a comprehensive description of the process of economic and social convergence, including an examination of the resilience of the two described regions. The Regional Competitiveness Index RCI 2.0. is a synthetic measure of 3 sub-indices and 11 pillars. Data from its three last editions were used to identify various aspects of the competitiveness of the Silesian Voivodeship and the Düsseldorf region in the short and long term. Using the above statistical data in connection with applying two concepts, i.e., the development trap and just transformation, allowed for a comparative examination of the socio-economic development trajectories of two industrialized EU regions representing different paths for Western Europe and Central and Eastern Europe. This allowed for the formulation of both research conclusions and implementation recommendations.

Table 1. The database is based on the Ninth Economic, Social, and Territorial Cohesion Report.

Name of Indicator	Date Measured	Śląskie Region	Düsseldorf Region	EU Average
GDP per capita	2022	83.5	118.9	100
Growth of: GDP per capita productivity employment rate working-age population	Average 2001–2021	3.49 2.6 0.3 0.57	0.61 0.18 0.55 −0.11
Growth of GDP per head in real terms 2001–2021, main sub-periods (four main sub-periods) 2001–2008 2009–2013 2014–2019 2020–2021	2001–2021	3.81 2.32 4.49 2.26	1.67 −0.69 0.77 −0.85
GDP per capita	2004	49.2	116.2	EU15 = 100
GDP per capita	2021	78.6	121.6	EU27 = 100
Economic development index at NUTS 3 level—Economic Development Index (EDI)	2001–2021	Częstochowski 0.62 Bielski 0.6 Rybnicki 0.56 Bytomski 0.56 Gliwicki 0.6 Katowicki 0.59 Sosnowiecki 0.55 Tyski 0.52	Düsseldorf 0.32 Duisburg 0.43 Essen 0.39 Krefeld 0.44 Mönchengladbach 0.4 Mülheim an der Ruhr 0.41 Oberhausen 0.36 Remscheid 0.28 Solingen 0.45 Wuppertal 0.31 Kleve 0.58 Mettmann 0.49 Rhein-Kreis Neuss 0.48 Viersen 0.35 Wesel 0.56
Development trap index at NUTS-3 level	2001–2018	Częstochowski 0.42 Bielski 0.4 Rybnicki 0.44 Bytomski 0.46 Gliwicki 0.42 Katowicki 0.44 Sosnowiecki 0.46 Tyski 0.49	Düsseldorf 0.71 Duisburg 0.52 Essen 0.64 Krefeld 0.63 Mönchengladbach 0.56 Mülheim an der Ruhr 0.59 Oberhausen 0.58 Remscheid 0.68 Solingen 0.5 Wuppertal 0.64 Kleve 0.41 Mettmann 0.56 Rhein-Kreis Neuss 0.48 Viersen 0.65 Wesel 0.41
EU Regional Competitiveness Index 2.0	2022	96.9	128.6	EU27 = 100
EU Regional Competitiveness Index 2.0: change between 2016 edition and 2022 edition		14.2	−10.6
Employment rate (20–64)	2022	74.6	77.3	EU27 = 74.6
Change in employment rate (20–64)	2013–2022	14.0	4.7	EU27 = 7.8
Unemployment rate (15–74)	2022	2.2	3.8	EU27 = 6.2
Change in unemployment rate (15–74)	2013–2022	−7.5	−2.6	EU27 = −5.4
Employment growth in the Information and Communication sectors	2013–2020	50.3	0.2	EU27 = 14
Employment growth in professional, scientific, technical, administrative and support service	2013–2020	1.2	8.2	EU27 = 8
Tertiary education rates (25–64)	2022	32.9	28.9	EU27 = 34.3
Vocational education and training attainment rates (25–64)	2022	54.1	43.1	EU27 = 35.3
The gap in employment rate between tertiary and secondary vocational graduates aged 20–34	2022	3.8	7.5	EU27 = 6.4
Participation of adults aged 25–64 in education and training	2022	7.0	8.2	EU27 = 11.9
Participation rates in early childhood education (3–6/7)	2021	91.6	92.4	EU27 = 92.5
Early leavers from education or training (18–24)	2020–2022	6.2	12.8	EU27 = 9.8
Population at risk of poverty or social exclusion	2022	10.5	28.0	EU27 = 21.7
Population at risk of poverty	2022	7.8	19.4	EU27 = 16.5
Population living in severe material and social deprivation (0–64)	2022	2.8	9.3	EU27 = 6.7
Population in households with very low work intensity	2022	3.4	14.6	EU27 = 8.3
Food poverty	2021	3.4	11.7	EU27 = 7.3
Heating poverty	2021	3.6	3.7	EU27 = 6.9
Arrears on utility bills	2021	4.1	4.1	EU27 = 6.4
Difference between female and male employment rates	2022	−12.5	−8.9	EU27 = −10.7
Difference between female and male tertiary education level rates	2022	11.4	−3.5	EU27 = −5.7
Women in regional assemblies	2023	40.0	34.4
Change in the participation of women in regional assemblies	2013–2023	8.8	4.8
People born in another EU country	2022	0.1	7.9	EU27 = 3.8
People born outside the EU	2022	0.2	16.9	EU27 = 9.6
Living conditions for immigrants from other countries (15+)	2022	74.8	83.4
Living conditions for racial and ethnic minorities (15+)	2022	71.6	81.0
Living conditions for gay and lesbian people (15+)	2022	55.0	79.2

Source: own elaboration on the base of the Ninth Cohesion Report Map Data [74].

Table 1. The database is based on the Ninth Economic, Social, and Territorial Cohesion Report.

Name of Indicator	Date Measured	Śląskie Region	Düsseldorf Region	EU Average
GDP per capita	2022	83.5	118.9	100
Growth of: GDP per capita productivity employment rate working-age population	Average 2001–2021	3.49 2.6 0.3 0.57	0.61 0.18 0.55 −0.11
Growth of GDP per head in real terms 2001–2021, main sub-periods (four main sub-periods) 2001–2008 2009–2013 2014–2019 2020–2021	2001–2021	3.81 2.32 4.49 2.26	1.67 −0.69 0.77 −0.85
GDP per capita	2004	49.2	116.2	EU15 = 100
GDP per capita	2021	78.6	121.6	EU27 = 100
Economic development index at NUTS 3 level—Economic Development Index (EDI)	2001–2021	Częstochowski 0.62 Bielski 0.6 Rybnicki 0.56 Bytomski 0.56 Gliwicki 0.6 Katowicki 0.59 Sosnowiecki 0.55 Tyski 0.52	Düsseldorf 0.32 Duisburg 0.43 Essen 0.39 Krefeld 0.44 Mönchengladbach 0.4 Mülheim an der Ruhr 0.41 Oberhausen 0.36 Remscheid 0.28 Solingen 0.45 Wuppertal 0.31 Kleve 0.58 Mettmann 0.49 Rhein-Kreis Neuss 0.48 Viersen 0.35 Wesel 0.56
Development trap index at NUTS-3 level	2001–2018	Częstochowski 0.42 Bielski 0.4 Rybnicki 0.44 Bytomski 0.46 Gliwicki 0.42 Katowicki 0.44 Sosnowiecki 0.46 Tyski 0.49	Düsseldorf 0.71 Duisburg 0.52 Essen 0.64 Krefeld 0.63 Mönchengladbach 0.56 Mülheim an der Ruhr 0.59 Oberhausen 0.58 Remscheid 0.68 Solingen 0.5 Wuppertal 0.64 Kleve 0.41 Mettmann 0.56 Rhein-Kreis Neuss 0.48 Viersen 0.65 Wesel 0.41
EU Regional Competitiveness Index 2.0	2022	96.9	128.6	EU27 = 100
EU Regional Competitiveness Index 2.0: change between 2016 edition and 2022 edition		14.2	−10.6
Employment rate (20–64)	2022	74.6	77.3	EU27 = 74.6
Change in employment rate (20–64)	2013–2022	14.0	4.7	EU27 = 7.8
Unemployment rate (15–74)	2022	2.2	3.8	EU27 = 6.2
Change in unemployment rate (15–74)	2013–2022	−7.5	−2.6	EU27 = −5.4
Employment growth in the Information and Communication sectors	2013–2020	50.3	0.2	EU27 = 14
Employment growth in professional, scientific, technical, administrative and support service	2013–2020	1.2	8.2	EU27 = 8
Tertiary education rates (25–64)	2022	32.9	28.9	EU27 = 34.3
Vocational education and training attainment rates (25–64)	2022	54.1	43.1	EU27 = 35.3
The gap in employment rate between tertiary and secondary vocational graduates aged 20–34	2022	3.8	7.5	EU27 = 6.4
Participation of adults aged 25–64 in education and training	2022	7.0	8.2	EU27 = 11.9
Participation rates in early childhood education (3–6/7)	2021	91.6	92.4	EU27 = 92.5
Early leavers from education or training (18–24)	2020–2022	6.2	12.8	EU27 = 9.8
Population at risk of poverty or social exclusion	2022	10.5	28.0	EU27 = 21.7
Population at risk of poverty	2022	7.8	19.4	EU27 = 16.5
Population living in severe material and social deprivation (0–64)	2022	2.8	9.3	EU27 = 6.7
Population in households with very low work intensity	2022	3.4	14.6	EU27 = 8.3
Food poverty	2021	3.4	11.7	EU27 = 7.3
Heating poverty	2021	3.6	3.7	EU27 = 6.9
Arrears on utility bills	2021	4.1	4.1	EU27 = 6.4
Difference between female and male employment rates	2022	−12.5	−8.9	EU27 = −10.7
Difference between female and male tertiary education level rates	2022	11.4	−3.5	EU27 = −5.7
Women in regional assemblies	2023	40.0	34.4
Change in the participation of women in regional assemblies	2013–2023	8.8	4.8
People born in another EU country	2022	0.1	7.9	EU27 = 3.8
People born outside the EU	2022	0.2	16.9	EU27 = 9.6
Living conditions for immigrants from other countries (15+)	2022	74.8	83.4
Living conditions for racial and ethnic minorities (15+)	2022	71.6	81.0
Living conditions for gay and lesbian people (15+)	2022	55.0	79.2

Source: own elaboration on the base of the Ninth Cohesion Report Map Data [74].

Table 2. The database is based on the EU Regional Competitiveness Index 2.0 for 2016, 2019, and 2022.

Name of Region	RCI 2.0	Final Score	Basic Sub-Index	Efficiency Sub-index	Innovation Sub-Index
Düsseldorf	2016	139.3	137.8	144.1	135.9
Düsseldorf	2019	134.5	129.8	144.6	124.5
Düsseldorf	2022	128.6	122.3	140.9	115.6
Düsseldorf	2016–2022 (average)	134.1	130.0	143.2	125.3
Düsseldorf	2022–2016 (difference)	−10.7	15.5	−3.2	−20.3
Śląskie	2016	82.7	88.1	98.5	58.3
Śląskie	2019	87.0	74.3	101.7	65.9
Śląskie	2022	96.9	93.8	106.3	69.0
Śląskie	2016–2022 (average)	88.9	85.4	102.2	64.4
Śląskie	2022–2016 (difference)	14.2	5.7	7.8	10.7

Source: own elaboration on the base of RCI_2_0_scores_2022_2019_2016 [75].

Table 2. The database is based on the EU Regional Competitiveness Index 2.0 for 2016, 2019, and 2022.

Name of Region	RCI 2.0	Final Score	Basic Sub-Index	Efficiency Sub-index	Innovation Sub-Index
Düsseldorf	2016	139.3	137.8	144.1	135.9
Düsseldorf	2019	134.5	129.8	144.6	124.5
Düsseldorf	2022	128.6	122.3	140.9	115.6
Düsseldorf	2016–2022 (average)	134.1	130.0	143.2	125.3
Düsseldorf	2022–2016 (difference)	−10.7	15.5	−3.2	−20.3
Śląskie	2016	82.7	88.1	98.5	58.3
Śląskie	2019	87.0	74.3	101.7	65.9
Śląskie	2022	96.9	93.8	106.3	69.0
Śląskie	2016–2022 (average)	88.9	85.4	102.2	64.4
Śląskie	2022–2016 (difference)	14.2	5.7	7.8	10.7

Source: own elaboration on the base of RCI_2_0_scores_2022_2019_2016 [75].

5. Results of Research

5.1. Different Convergence Trends, Development Trap Risk

The level of economic development varies significantly between the two NUTS 2 regions. Düsseldorf is a highly developed area with a GDP without a headcount of around 119% relative to 100% of the EU average and, in addition, above the German average. For the Śląskie, the indicator is lower at 83.5%, close to the Polish average. In the region, we are witnessing a steady dynamic economic convergence with the most dynamic GDP growth per capita in 2001–2008 and 2014–2019. Since Poland acceded to the EU, the GDP rate (per capita) in Śląskie has increased by 30 pp from 49% of the EU average to almost 79%. In this case, the convergence process strengthened the megatrends of economic integration and transformation.

On the other hand, for Düsseldorf, this indicator shows a minimal increase or even a decrease, as was the case in 2009–2013 and 2020–2021. Thus, the total increase in GDP per capita between 2004 and 2021 was 6 pp, i.e., from 116% to 122% of the EU average. The above figures show that Düsseldorf has not returned to a rapid growth path, and the effects of both crises (the 2008 financial crisis and the 2020 pandemic) are still visible. This, in turn, points to the more significant impact of globalization and post-modernization megatrends and, consequently, the region’s lower resilience to external shocks. In the case of Śląskie, the effects of these crises were only a temporary slowdown in GDP growth per capita. It should be noted that the average higher growth rate for the Śląskie is due to the beta convergence theory, according to which a region with low GDP per capita has higher GDP growth, which is a typical example of the convergence of Eastern European regions with regions from North-Western Europe. However, none of the external shocks disrupted this process, demonstrating the greater resilience of the Śląskie compared to Düsseldorf.

This strong trend of economic convergence in the Śląskie between 2001 and 2021 is confirmed by the dynamics of both GDP per capita (an increase of 0 3.5 pp) as well as productivity (an increase of 2.4 pp), employment level (an increase of 0.3 pp), and the share of the active population (an increase of 0.6 pp). In the case of Düsseldorf, the picture is more complex because, over the same period, the German region experienced less growth in GDP per capita (an increase of 0.6 pp) and productivity (an increase of 0.18 pp) and a decrease in the share of the labor force (−0.11 pp). On the other hand, the employment rate for Düsseldorf is almost twice as dynamic as for the Śląskie region (an increase of 0.55 pp). This may indicate that the economically strong German region has a more substantial capacity to attract workers, as confirmed by the labor migration figures later in this article.

Productivity is a key condition for economic growth, including people’s well-being. Between 2001 and 2021, productivity in Düsseldorf increased slightly, i.e., by 0.18 pp, while employment increased simultaneously, which was compensated by a slight decline in the share of the labor force. According to the hypothesis of ‘secular stagnation’, small growth up to 1 pp or stagnation is typical of developed economies. Using green digital transformation and artificial intelligence as a flywheel to accelerate innovative technologies in the industry can provide an opportunity to overcome the slowdown in productivity growth in Düsseldorf. In the case of Śląskie, as for most Eastern European regions, productivity increased above average by 2.6 pp as employment increased and the share of the labor force increased. This is typical of beta convergence.

Further productivity growth may be one of the compensatory tools for a shrinking regional labor market. However, the further growth of Śląskie requires competitive advantages besides cheap labor and standardized technologies in industry. This is confirmed by the concept of a regional development trap aimed at industrialized European regions at a medium level of development.

In the Ninth Cohesion Report [3], the first two decades of the 21st century were divided into four cycles illustrating the dynamics of each region’s development (p. 19). The observed trajectories for these cycles differ for the development of Düsseldorf and Śląskie. The first period, the ‘convergence years’ (2001–2008), followed the same trend for both regions, i.e., GDP per capita increased. According to the convergence theory, the growth for the Śląskie was more than twice as dynamic as for Düsseldorf. In the following years, characterized as the ‘low employment period’ (2009–2013), the Śląskie grew.

On the other hand, Düsseldorf, whose majority of public and private investment was financed by the banking sector, was hit harder by the 2008 financial crisis, with a fall in GDP. The following years have been defined by the ‘delayed recovery’ (2014–2019). At that time, both regions grew in GDP. However, in the case of Śląskie, this was a dynamic acceleration compared to the pre-recession value. On the other hand, in Düsseldorf, this was an increase below the pre-crisis rate. The last period—after two crises, i.e., COVID-19 and the war in Ukraine—called the ‘quick rebound’ (2020–2022). In this case, Śląskie recorded a further increase in GDP per capita, although it was less dynamic, i.e., at a level close to that after the recession.

On the other hand, Düsseldorf has been hit harder by the pandemic, as shown by a decrease in the ratio that was higher than after the 2008 financial crisis. The topic needs to be explored, but perhaps the structure of Düsseldorf’s economy includes sectors for which global supply chains have not yet been rebuilt or have not been rebuilt, so the health phase takes longer. This is confirmed by the more significant impact of globalization and post-modernization megatrends and, consequently, the region’s lower resilience to external shocks.

In addition, in the cumulative period 2001–2021, both regions are characterized by employment growth, which is more dynamic in Düsseldorf. Thus, a rebound in both industrialized regions was observed after the temporary reduction of employment during the pandemic.

In order to further define the convergence process, the Ninth Cohesion Report [3] includes two new synthetic indicators estimating the likelihood of two different development trajectories of the different EU sub-regions measured over the period 2001–2021 aggregated at sub-region level (NUTS 3). The first indicates the risk of being in a development trap. The second—as an inversion—shows the chances of pursuing the path of high growth. The first synthetic indicator is based on statistics on GDP per capita, productivity, and employment levels for the last five years. If they were lower than the EU, country, or region average, the sub-region is identified as at risk of falling into a development trap. For the Economic Development Index (EDI), the methodology considers identical indicators, i.e., GDP per capita, productivity, and employment for the last 5 years. However, in this case, the values must be higher than the EU, country, or region average. A rapid growth path is recorded for EDI above 0.5 within the range of 0–1.

The probability of placing in the high-growth path for the different sub-regions located in the analyzing areas of both regions, it is identified the much more significant disparities in convergence (almost twice the differences) between the sub-regions of Düsseldorf with an oscillating range between 0.32% for the Düsseldorf towns with county rights and 0.58% for the Kleve land county. In the Śląskie sub-regions, the development dynamics are closer to the lowest score for the Tyski sub-region (0.02) and the largest for the Częstochowski sub-region (0.62). The coefficient of variation for the Düsseldorf sub-regions is as high as 20%, compared with 7% for the Śląskie sub-regions. When analyzing the probability of being in the development trap in the Düsseldorf region, it is the highest for the Düsseldorf cities with county rights (0.71) and the smallest for the Kleve and Wesel land county (0.42). In the Śląskie region, the estimated probability is the highest for the Tyski sub-region (0.49) and the lowest for the Bielski sub-region (0.40). However, the data show a similar development trajectory for the entire set of sub-regions of Śląskie. In this case, the coefficient of variation for the Düsseldorf sub-regions is 16%, compared with 10% for the Śląskie sub-regions. Thus, for both synthetic indicators of Düsseldorf sub-regions, the development trajectories are much more volatile, as shown in Figure 3 and Figure 4.

The EU Regional Competitiveness Index 2.0 [4] defines a region’s competitiveness as the ability to offer an attractive and sustainable environment for businesses and residents regarding their living and working conditions (p. 8). The EU Regional Competitiveness Index 2.0 also shows the increased dynamics of Śląskie between 20016 and 2022, which shows an increase of 14.2 pp compared to a decline in the scoring of Düsseldorf by minus 10.6 pp. This shows that in the case of Śląskie, there has been an intense process of catching up on inequalities and that simple growth reserves have been exhausted for Düsseldorf. It should be noted, however, that in the case of Düsseldorf as a region with a high level of development, a different importance was applied to the innovation sub-index when calculating the final score than for the Śląskie. Nevertheless, the analysis of the scores for all three sub-index confirms the above negative trend for Düsseldorf, as the 2016–2022 editions showed significant scoring decreases for all three sub-index, i.e., the base (a decrease of 15.5 pp), the efficiency (3.2 pp decrease) and the innovative (reduction of 20.2 pp). For Śląskie, these are increases in all three dimensions, i.e., basic sub-index (an increase of 5.7 pp), efficiency (an increase of 7.8 pp), and innovation (an increase of 10.7 pp).

The results of the RCI 2.0 for the Düsseldorf, covering both the final score and the sub-data for all three sub-indexes, are illustrated in Figure 5 below.

The results of the RCI 2.0 indicator for the Śląskie, covering both the final score and sub-data for all three sub-indexes, are illustrated in Figure 6 below.

The EU Regional Competitiveness Index RCI 2.0 considers 11 pillars that describe different aspects of competitiveness, which are grouped into three sub-indents. The first sub-index basic name considers the economy’s main drivers. The second sub-index—efficiency—measures the skills of the workforce and labor market performance. The third sub-index—innovation includes advanced indicators of economic development.

The results of the 11 pillars of RCI 2.0, 2022 edition for Düsseldorf and Śląskie are illustrated in Figure 7 below.

The chart above shows the asymmetric development of the competitiveness pillars of Düsseldorf, which entails the risk of the region being less resilient to external shocks. There was a significant advantage in the market size pillar. However, basic and partly effective sub-indexes related to health, primary education, higher education, lifelong learning, and labor market efficiency show lower or similar values in the index score to those of the Śląskie. Therefore, strengthening the competitiveness of Düsseldorf should include measures aimed at increasing innovation and, above all, dedicated to strengthening the quality of essential public services for people to live and work in. The competitive position of Śląskie is more balanced with an apparent deficit in the pillars, technological readiness, business sophistication, and innovation, which once again indicates the recommended course of action for the Silesian region related to innovation development.

Data from the Ninth Cohesion Report [3] and the EU Regional Competitiveness Index 2.0 [4] show that Düsseldorf is less resilient to external crises than the Śląskie. However, as highly populated, large functional urban areas (FUAs), both regions benefit from the scale of agglomerations, i.e., population concentration and business. However, further developing and reducing inequalities at the sub-regional level is essential to further develop labor mobility within the FUA, especially regarding Düsseldorf as a more internally polarized region. The question remains as to how the advantages of the agglomeration will balance the cost of living in heavily urbanized areas linked to congestion, insufficient housing supply, and underdeveloped blue–green infrastructure.

5.2. Qualified Workers Shortages

Analyzing the labor force indicators in both regions, one can see an increase in employment between 2013 and 2022. In the case of Śląskie, this is an increase of 14 pp, with an employment rate of 74.6%, i.e., at the EU average level. In contrast, Düsseldorf has a less dynamic trend throughout 4.7% pp, with 77.3% in 2022. Both regions have unemployment rate levels below the EU average (6.2%), i.e., 2.2% for Śląskie and 3.8% for Düsseldorf. This translates into a decrease in the level of unemployment for Śląskie voivodships of minus 7.5 pps, which is above the EU average of minus 5.4 pp. In the case of Düsseldorf, the rate of decline in unemployment is much lower at minus 2.6 pp.

In summary, in both regions, labor markets have shown resilience to external shocks, and employment has continued to grow with varying dynamics depending on the region’s level of development. The recorded unemployment level is also below the EU average. However, both regions are experiencing negative demographic trends, which will increasingly hamper the smooth functioning of labor markets. Tackling skills shortages and job mismatches is a common challenge for Śląskie and Düsseldorf.

Further indicators broaden information on employment levels in key sectors that generate long-term growth. Regarding employment in the ICT sector, employment in Śląskie grew by 50 pp between 2013 and 2020, well above the EU average of 14 pp. In the case of Düsseldorf, this was a minimal increase of 0.2 pp. We can see the opposite dynamic in employment growth in professional, scientific, technical, administrative, and support services. In this case, Düsseldorf increased at the level of the EU average, i.e., 8.2 pp compared to 8 pp for the EU. In the Śląskie, the increase was minimal at 1.2 pp. The above figures illustrate the high level of innovative and technological development in Düsseldorf and the deficits of the Śląskie, which argues in favor of the need for the Śląskie to strengthen measures aimed at the development of the RIS ecosystem sectors.

A skilled workforce is key to sustainable, socially fair growth. Higher and vocational education prepares staff to absorb or generate innovation, which is essential for increasing productivity and accelerating smart growth. Both regions have a share of tertiary education below the EU average, with a slight difference of around 1% in the case of Śląskie and more than 4% for Düsseldorf. This argues in favor of strengthening the promotion and accessibility of higher education, especially in Düsseldorf.

On the other hand, the share of people with vocational education in both regions is well above the EU average. This is almost 20% for the Śląskie and 8% for Düsseldorf, which correlates with industrial post-mining/mining their economic structure. Both regions have staff with technical and practical skills; they must be appropriately matched to the needs of the labor market. The observed percentage of continuous adult learning for both regions is 7% for the Śląskie region and 8.2% for the city of Düsseldorf, below the EU average of 11.9%. The above data confirm both regions’ industrial post-mining/mining profile, rewarding vocational education, which is usually acquired at the start of working life and not updated afterward. That connects with the risk of low complexity activities and narrow regional sectoral specialization. Both regions face challenges: firstly, to actively promote a culture of lifelong learning, and secondly, most notably, design and implementation of a comprehensive education system, including vocational, higher, and continuous education tailored to the needs of industrial transformation. Furthermore, it is important to take action to increase the number of people with tertiary education in the regions as one of the key enablers for smart growth, including the creation and production of new and more complex products and services. The above actions are crucial for increasing the resilience of both regions for the risk of falling into a development trap and strengthening the just transition process.

Silesian differs significantly from Düsseldorf in the labor market participation of underrepresented groups. This can be one of the instruments to address labor shortages. The difference between female and male employment rates for the Śląskie is minus 12.5%, below the EU average of 10.7%, and 8.9% for Düsseldorf. The difference between women’s and men’s tertiary educational attainment rates is different: for the Śląskie, this is 11.4%, for Düsseldorf, minus 3.5%, with the EU average of minus 5.7%. Thus, in the Śląskie, the proportion of female workers continues to be significantly lower than the EU average and the results for Düsseldorf. This is even though in Śląskie, a much higher proportion of women have higher education. The indicators for access to childcare included in the scoreboard do not differentiate between the two regions and are at the level of the EU average. Therefore, Śląskie should activate gender-segregation measures as an important tool to increase the number of people active in the labor market. In addition, women with tertiary education are a valuable resource for the labor market. They can be an important success factor in building a complex modern economy, filling staff shortages for smart growth for Düsseldorf and Śląskie.

The role of migration as a tool for the labor market is different in both regions. In the Śląskie, intra-EU migration is 0.1% compared to 7.8% for Düsseldorf and 3.8% of the EU average. A similar trend is also observed for external migration, with a score of 0.2% for the Śląskie region, compared to 16.9% for Düsseldorf and 9.6% for the EU average. To sum up, the regional labor market of Düsseldorf is strengthened by internal and external migrants that fill the gap in labor shortages. This may challenge the effective socio-cultural adaptation of this part of the population in Düsseldorf. In turn, Silesia faces the challenge of developing practical tools to attract migrants to the region and to integrate them actively.

5.3. External Shocks, Increasing Material and Social Deprivation

Despite two decades of prosperity growth, two external shocks, i.e., the pandemic and Russia’s aggression in Ukraine, have translated inflationary pressures, including price hikes for energy and food supplies. This is particularly true for lower-income households. The proportion of the population declaring a risk of poverty has increased across the EU after a double crisis, disrupting the long-term convergence process.

In order to comprehensively reflect the scale of the problems related to poverty in the broader sense, the Commission has developed an AROPE indicator. It concerns people with at least one of the three components of poverty, i.e., relative monetary poverty, material/social deprivation, and living in a household with very low work intensity. For indicators relating to the share of people at risk of poverty or social exclusion, the results for Śląskie are well below the EU average; for example, 10% of the population at risk in Śląskie, compared with 21.7% of the EU average. In the case of Düsseldorf, the situation is more difficult as this risk covers as much as 28% of the population. A similar trend can be observed for the poverty indicator. For the Śląskie, it is only 7.8%; for Düsseldorf, as much as 19.4%, compared with 16.5% as the EU average. Another variable is connected to the population living in severe material and social deprivation. For the Śląskie, this is only 2.8%; for Düsseldorf, as much as 9.3%, compared with 6.7% as the EU average. The third component of AROPE, i.e., the share of the population in households with very low work intensity, also confirms the above trend, i.e., it scores 3.4% for the Śląskie, 14.6% for Düsseldorf, compared with 8.3% as the EU average. The identified risks of poverty in the broader sense do not relate to the Śląskie. However, they pose a challenge to Düsseldorf, and the above figures should signal the launch of a comprehensive package of social measures to mitigate the risk of poverty. It should be mentioned that both regions have indicators relating to energy poverty and are financed below the EU average. This indicates that this element of material deprivation does not pose a significant challenge for them in the convergence process.

5.4. Women’s Activation and Migration Policies

Equal opportunities, including gender equality, are a key priority for the EU. Women’s labor and social activation can have a direct impact on the development of the region, including, in particular, the labor market, especially in the context of the challenges of an aging society. However, women’s balanced participation is important for economic and social cohesion [3] (p. 73). In the case of the indicator concerning the participation of women in regional authorities, Śląskie has a higher value, i.e., 40% compared to 34.4% for Düsseldorf. Similarly, the variable defining the change in women’s participation in regional authorities measured for 2013–2023 is presented. For Śląskie, the process dynamics are reflected by an increase of 8.8 pp compared to 4.8 pp in Düsseldorf. The balanced representation of women in public decision-making bodies, i.e., 40% or more, is an objective outlined by the Commission. This is a significant challenge for Düsseldorf, especially since in the German region, as one of the few in the EU, fewer women than men have a tertiary education. Therefore, Düsseldorf should take measures to activate women through education and politics.

Due to the shrinking labor market and falling number of birthdays, migration policy is one of the most important pillars of the EU’s development. It is subject to competition between particularly industrialized regions that need economic and human resources. In the case of the Gallupa indicator on the living conditions of immigrants from other countries, the assessment for the Southern macro-region, which includes the Śląskie, is 74.8%, i.e., 9 pp less than the North Rhine–Westphalia macro-region, which includes Düsseldorf a similar difference of 10 pp concerning the living conditions of racial and ethnic minorities. The most significant difference concerns the assessment of the sound quality of life of gays and lesbians—in this case, 24 pp, to the detriment of Śląskie.

6. Discussion

This article reaffirms the importance of contemporary discourses on how to shape the socio-economic development of the regions of the European Union better, recommending strengthening convergence through ‘place-based approach’ integrated approaches, taking into account the human dimension [34,37,39,42].

The Ninth Cohesion Report (2024) and its previous editions [76,77,78] and documents [79,80] show that European regions are increasingly diverse both in terms of fundamental parameters (income per capita, employment, and demography) and in terms of direction and dynamics of change. This trend is confirmed by Iammarino et al. [15] and Rodríguez-Pose [16,39], which points to the need to counteract development inequalities in the EU, including a new approach to strengthening development in industrial regions post-mining/mining. On the other hand, this article confirms the concept developed by Diemer et al. [14] on a regional development trap in Europe, explicitly targeting medium-level regions (between 75% and 100% of GDP for the EU). However, researchers have diagnosed the risk of falling and being trapped in a development trap for a larger group of European industrialized regions at all levels of development. This article further develops this approach about Düsseldorf, a highly developed region facing the challenge of regaining the old development dynamics, including improving the just transition process.

On the other hand, Śląskie, which is changing categories from a weak region to a transition region, faces the challenge of rebuilding its economy and basing it on advantages other than low personnel costs and standard industry technology. This challenge is compounded by the need to strengthen and continue further actively pursuing the process of just transformation. In the case of Düsseldorf, according to the authors, stagnation and decline include a wider range of indicators than GDP alone, with productivity and employment. This observation is confirmed by the work of Dijkstra et al. on the EU Regional Competitiveness Index RCI 2.0 [4], which recorded a decline in the competitive position of Düsseldorf over the last three editions (2016–2022) what is important—and in line with the above assumptions—concerned in particular the base sub-index and innovation, which are key parameters for diagnosing the trajectories of the region’s development, including the risk of stagnation. In the case of the Śląskie, the low risk of falling into the development trap is confirmed by the RCI 2.0 indicator, as the region has a steady increase in its competitive position in the index. Stucking in the development trap is combined with another concept, i.e., the geography of growth, stagnation, and discontent with Dijkstra et al. [53], Rodríguez-Pose et al. [16,49], and OECD [33]. According to Immariano et al. [48] and Diemer et al. [14], in transition regions, once simple comparative advantages have been exhausted, there is a need to move toward productivity growth based on more demanding, more ambitious measures. This includes investments in hardware, software, and increased skills of workers in the business sector, as well as horizontal investments, i.e., support for more advanced regional infrastructure, human capital, and the quality of institutions. Researchers point to different types of regional development blockage, which is confirmed by the development traps in this article. In addition, the above concept makes it possible to examine the intensity of the traps. The first metric is per capita income, customarily used to measure well-being. The data from the Cohesion Report confirm that GDP per capita is less dynamic for Düsseldorf and, after the crises, even a decline. A second important measure is productivity. According to Rodríguez-Pose et al. [40], there is a strong connection between productivity and the quality of local institutions, as they act as a catalyst for increasing the impact of local human capital and local innovation potential on labor productivity. The last third metric, the employment-to-population ratio, diagnoses both demand-side and supply-side disturbances in the labor market. This is a challenge, especially for the Śląskie, which needs to create new specialized jobs in a transformative economy. Notably, the concept of Diemer et al. [14] identifies regions that are approaching stagnation in the high-growth trajectory, regardless of income levels, as seen in the case of Düsseldorf. The modest productivity increase gains for Düsseldorf are in line with the hypothesis of ‘secular stagnation’ [46] and the beta (β) convergence pattern [44], maintained despite economic shocks [45]. The different trajectories for the socio-economic development of Düsseldorf and Śląskie, as compared in this article, confirm the concept of Churski et al. [41], Konecka-Szydłowska et al. [54] on modern megatrends and their varying impact depending on the different development paths of Western and Central and Eastern Europe. The development trajectories of Śląskie included in this article align with the proposal of Micek et al. [55] on creating a new unique development path. For both regions in particular, Śląskie applies, as described by Gwosdz et al. [81], the process transformation of starting the polycentric mining and metallurgical region in a post-industrial, polycentric metropolitan area.

Both regions have been in the process of a just transformation for years. The identified significant social inequalities in the Düsseldorf region indicate the need to strengthen actions aimed at increasing social justice, which is consistent with the concept of Newell and Martin [17,19] emphasizing the key importance of justice for the most vulnerable social groups. Lower readiness, including acceptance of pro-climate actions in the Silesian Voivodeship, confirms Heffron’s concept, according to which issues from the areas of energy, environment, and climate should be more closely integrated, including them in a coherent, socially acceptable process of a just transformation [18]. This work describing the development trajectory of post-mining/mining regions, in particular their socio-technical transformation, implements the postulate of further empirical research raised by Wang [20]. Arora’s comprehensive account of the transformation of the Ruhr region, including its successes and failures, is supported in this work by discretionary justice, which focuses on the unequal treatment of marginalized groups affected by high social inequalities [22].

The work of Dijkstra et al. [53] and Rodríguez-Pose et al. [16,49] raises the risk of geography of discontent. While both regions face the challenges of socio-economic transition as a derived energy transition, it is much more challenging for Düsseldorf to counter asymmetries in developing sub-regions defined by the synthetic development trap index. This challenge for Düsseldorf is confirmed by higher than the EU average performance for material deprivation indicators. Hence, the region faces a significant challenge in increasing intra-regional convergence. Otherwise, the high polarization in the development of sub-regions and the wealth of society can lead to an increase in the geography of discontent, i.e., an increase in social discontent and political reluctance to the system. According to the OECD [33] report, this may result in a decline in support for democratic values and an increase in reluctance toward the EU.

Both regions are examples of complex settlement systems. This article confirms the unique trajectory of socio-economic and spatial transformations of the Śląskie described by J. Runge [52]. Adapting this concept to Düsseldorf, which is also characterized by a complex settlement system, requires separate studies. The synthetic development trap index defined by the EC applies to complex settlement systems characterized by functional heterogeneity, periphery, and intermediate locations [51]. Hence, the risk of being stuck on the development path concerns not only the entire territory of the industrial regions but, in particular, parts of it, for this article defined as statistical sub-regions of NUTS 3.

The Ninth Cohesion Report [3] (p. 32) notes that a common feature of all sub-regions at risk of falling into the development trap is the lack of human capital, including insufficient educational opportunities and the outflow of the educated population. This is universal, independent of the level of economic development. In addition, integration with global value chains is recommended as a factor of structural change and, ultimately, a shift to more complex innovation-based economic activities. In summary, the opportunity to create new paths for regional growth, thus reducing the risk of falling or being stuck in the development trap, makes it possible to increase administrative and innovation capacity and investment dynamism. However, focusing on people and territorial capital is the most important success factor. Radovan’s work [82] underlines the importance of an enabling working environment and equitable access to educational resources to achieve sustainable economic growth and reduce inequalities. According to Lee et al. [83], significant measures for the Śląskie to improve innovation should consider the increase in female employment in R&D, accentuating the importance of a diverse workforce as a strategic business resource.

In conclusion of the discussion, it should be noted that territorial cooperation is an important aspect of regional development in the context of EU cohesion policy. In the years 2021–2027, territorial cooperation concerns four components: cross-border cooperation [84,85], international cooperation, interregional cooperation [86], and cooperation in the outermost regions. European territorial cooperation as an objective of cohesion policy solves problems beyond national borders and requires a standard solution, enabling joint development of the potential of different areas. In studies on Poland’s cooperation with neighboring countries under cohesion policy, various dimensions (economic, social, territorial) and levels of research (local, regional, international) are considered, for example, Ł. Lewkowicz [87] analyzed new forms of territorial cooperation on the Polish–Slovak border. The most important spheres of Polish–Slovak cross-border cooperation were also the subject of research by M. Więckowski [88]. In turn, the work of Studzieniecki et al. [89] presented the development of Polish–Lithuanian cross-border cooperation in the established Cross-Border Functional Area (CFA), which included nine cities and municipalities from the Sejny and Suwałki counties and three Lithuanian local governments: Łaźnie, Wiłykowiszki and Kalwaria. Other researchers have identified differences in the quantitative demographic potential of the Polish–German and Polish–Lithuanian transborder regions [90]. Cross-border cooperation studies attempt to identify factors that facilitate or hinder this cooperation [91] and emphasize the role of appropriate planning of cross-border cooperation [92]. Although the above examples of Polish–Slovak or Polish–Lithuanian cooperation in cohesion policy are good examples for some regions in Poland, due to the strongly marked component of industrialization and urbanization development as well as just transformation, it was considered that the Silesian Voivodeship in Poland is more favorably compared to a similar industrial region, North Rhine–Westphalia in Germany.

7. Conclusions

This article compares the development trajectories of two NUTS 2 regions in the EU, i.e., the Śląskie Voivodship in Poland and the Düsseldorf Regency in North Rhine–Westphalia, Germany, using data from the Ninth Cohesion Report and the EU Regional Competitiveness Index 2.0. to examine their development trajectories taking into consideration the two concepts of a development trap and a just transition. This allowed for the formulation of a recommendation. Both highly industrialized regions must respond to the demographic challenge, which translates into labor shortages and an aging population. In the case of the Śląskie, this action line covers the activation of women into the labor market and the management of migration, i.e., the emigration of the region’s inhabitants and the strengthening of immigration. For both regions, it is crucial to improve productivity as a key component of sustainable growth while compensating for the loss of labor market resources. Economic challenges include strengthening innovation for Silesia by developing and strengthening business-science cooperation using the Regional Innovation Strategy. For Düsseldorf, it is crucial to maintain the dynamics of innovation (using technological breakthroughs) and to increase resilience, e.g., by rebuilding supply chains. Skills development based on (vocational, higher, and continuous) education that meets transformation industry needs is essential for these activities. Both regions should activate economic and social flows within their functional urban areas. This is more challenging for Düsseldorf due to the much more divergent results of the Economic Development Index (EDI) for the different sub-regions. Regarding social cohesion, the Śląskie should focus on equality measures. Düsseldorf, on the other hand, should significantly strengthen social protection against the risk of poverty.

From this explanatory perspective, the analysis presented in this article should be helpful for decisions on strategic development measures for the two identified European NUTS 2 regions and the development policy for other EU industrialized regions challenged by a just transition and, at the same time, at risk of falling into a development trap.