Navigating the Twin Transition: Unveiling Left-Behind Regions and Mobility Flows in the EU
At the recent International Conference on Regional Science in October, the MOBI-TWIN partners showcased a series of impactful presentations. Among them, Anastasia Panori from the School of Spatial Planning and Development at Aristotle University of Thessaloniki presented a collaborative study co-authored with Tuomas Väisänen, Milad Malekzadeh, and Olle Järv from the Department of Geosciences and Geography at the University of Helsinki. Their research, titled Navigating the Twin Transition: Unveiling Left-Behind Regions and Mobility Flows in the EU, provides an in-depth analysis of mobility dynamics in the era of the Twin Transition.
Key Research Questions
The study aims to understand mobility patterns in relation to the green and digital transitions, particularly focusing on left-behind regions. One of the primary research questions addresses how interregional mobility patterns relate to different types of left-behindness. The researchers seek to analyze the extent to which regions experiencing economic decline, demographic shifts, or social inequalities exhibit distinct mobility behaviors compared to more developed areas.
Another key question explores the relationship between the Twin Transition and spatial mobility patterns. The Twin Transition encompasses both green and digital transformations, and the study investigates how these changes are influencing the movement of people across regions. By examining the push and pull factors associated with green and digital innovations, the research attempts to uncover whether certain regions become more attractive or whether some are left further behind due to infrastructural and policy limitations.
Furthermore, the study seeks to understand how these interrelationships influence regional attractiveness. With the growing significance of sustainable and digital advancements, some regions may experience increased investments and workforce migration, while others struggle to retain talent and resources. By examining these dynamics, the research contributes to a more comprehensive understanding of how mobility patterns affect regional competitiveness in the context of the Twin Transition.
Preliminary Insights
The research identifies notable differences among clusters of regions, each exhibiting distinct characteristics in terms of left-behindness and levels of Twin Transition. The first cluster consists of highly developed regions with minimal vulnerability to the green transition. These regions have a strong economic foundation, significant innovation potential, and substantial digital transformation. Due to their robust technological infrastructure and supportive policies, they are well-positioned to lead in both green and digital advancements.
On the other end of the spectrum, the fifth cluster represents the least developed regions, characterized by high poverty rates and heightened vulnerability to the green transition. These regions face significant challenges in adapting to environmental policies and integrating digital technologies. Despite having widespread internet access, digital transition remains modest due to factors such as insufficient infrastructure, low digital literacy, and economic constraints. Limited innovation potential further exacerbates the difficulties these regions face in keeping pace with more developed areas.
The second, third, and fourth clusters occupy intermediate positions, exhibiting a mixture of characteristics related to the Twin Transition. While these regions do not face the same level of vulnerability as those in the fifth cluster, they still experience varying degrees of left-behindness. Some may struggle with transitioning to a greener economy, while others may lag in digital development despite showing promise in certain sectors. These variations highlight the complexity of regional disparities and emphasize the need for targeted policies that address specific challenges faced by different regions.
Next Steps…
Moving forward, the study will undertake several steps to deepen its analysis. One key aspect involves identifying additional variables to better measure the Twin Transition and refine the identified clusters. By incorporating more granular data, researchers aim to develop a more nuanced understanding of the factors driving regional disparities in mobility patterns, green vulnerability, and digital transformation.
A more detailed analysis of each cluster will also be conducted to establish stronger connections between different types of mobility patterns and regional characteristics. This in-depth examination will help clarify how economic, social, and environmental factors interact to shape mobility trends in each category of regions. Understanding these dynamics is crucial for developing policies that can support lagging areas while sustaining growth in more developed regions.
Another important step involves mapping the identified clusters to investigate potential geographical patterns. By visually representing the distribution of different clusters across the EU, researchers can determine whether specific regions exhibit common trends or if particular areas are disproportionately affected by the challenges of the Twin Transition. This geographical analysis will provide insights into spatial dependencies and potential areas for intervention.
Finally, the study will explore how variations in mobility patterns correspond to differences in regional policies. By examining the effectiveness of different policy approaches, researchers aim to identify best practices that can be replicated in other regions. This comparative analysis will help inform policymakers on strategies that can enhance regional attractiveness, mitigate left-behindness, and ensure an inclusive transition to a greener and more digital future.
As Europe navigates the complexities of the Twin Transition, understanding these regional disparities and mobility flows will be crucial for shaping policies that foster balanced development and inclusivity across all EU regions. Stay tuned for more insights from this ongoing research!
