Node Prioritization in Digital Tourism Business Networks Using Graph Analysis Method

Digital tourism business ecosystems are complex networks comprising interconnected stakeholders, playing a vital role in the tourism industry's success. The performance of these ecosystems hinges on the intricate web of connections and interactions between various entities within them, making their optimization a formidable challenge. In this study, we introduce a novel graph analysis approach to prioritize nodes within digital tourism business ecosystems. Our methodology leverages three key graph metrics: degree centrality, betweenness centrality, and clustering coefficient along with associated weights. These metrics provide a comprehensive understanding of the network's structure and dynamics, enabling stakeholders to identify crucial nodes and relationships within the ecosystem. By focusing on these pivotal entities, organizations can uncover opportunities for collaboration and pinpoint areas for improvement, ultimately enhancing the overall competitiveness of the digital tourism business ecosystem. Through the insights gained from our analysis, tourism industry professionals can foster valuable partnerships, identify potential collaborators, and strategically position themselves in the evolving landscape of digital tourism, paving the way for sustainable growth and success.