
Regional development is an intricate process that involves various components and actors interacting within complex, evolving environments. Despite numerous studies on specific aspects of the field, a comprehensive overview of the intellectual structure has remained underexplored. This fragmentation limits the ability to grasp broader trends and interconnections shaping regional development research. To address this gap, this study utilizes a bibliometric analysis to examine the intellectual structure of regional development over the past 25 years. Drawing from initially 15,226 source documents extracted from Scopus, the study constructs a document citation network including 15,488 co-citations (edges) among 7,882 source documents (nodes). Citation relationships among these publications are analyzed using weighted in-degree calculations in Gephi, while the Louvain modularity algorithm identifies research communities based on shared themes. Additionally, topic modeling techniques in R, utilizing word frequency and co-occurrence analysis, uncovering dominant thematic areas within the field. Key findings reveal the interconnectedness of various research communities, with a particular emphasis on path dependence and industrial evolution, the role of Higher Education Institutions, regional disparities and inequality, entrepreneurial ecosystems, EU Cohesion Policy, the rise of the city-regions, tourism and globalized regional development. This study provides a comprehensive framework for understanding the intellectual landscape of regional development, offering valuable insights for researchers, policymakers, and practitioners aiming to navigate this complex and evolving field.
Bibliometrics, topic modeling, text mining, Regional development
Bibliometrics, topic modeling, text mining, Regional development
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
