Clustering of Regional Tourism Products Based on Bibliometric Analysis: The Case of Mangystau Region

Despite the growing importance of interdisciplinary approaches in tourism studies, there remains a lack of structured analytical frameworks for clustering regional tourism products and aligning them with effective marketing tools. The present study aims to develop a theoretical and methodological model for clustering regional tourism products based on bibliometric analysis, followed by comparing clusters with effective marketing promotion tools. The method used is a systematic bibliometric analysis of 245 peer-reviewed publications from 2010 to 2023, selected from the Web of Science Core Collection database using the PRISMA protocol. The analysis was carried out using RStudio (Biblioshiny package) and VOSviewer, which allowed us to build maps of co-authorship, co-quoting and co-use of keywords. The results of the analysis revealed four thematic clusters: (1) sustainable development and innovation in tourism, (2) quality of service and tourist satisfaction, (3) cultural and event tourism, and (4) gastronomic tourism and territorial identity. Based on them, the Matrix Design model has been developed to ensure consistency between the types of travel products and specific promotion tools. As part of the empirical testing, a study of the Mangystau region of Kazakhstan was presented, confirming the model’s applicability: problems of fragmented positioning of the region were identified, as well as solutions for digital segmentation, cluster management and strategic branding were proposed. Future research should explore cross-regional applications of the model and examine the integration of digital technologies, such as AI and data analytics, to further optimize marketing strategies for regional tourism development.

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