Detecting potential cooperative network for tourist attractions in a destination using search data.

ABSTRACT: This study addresses the critical need for regional tourism integration and sustainable development by identifying cooperation opportunities among tourist attractions within a region. We introduce a novel methodology that combines association rule mining with complex network analysis and utilizes search index data as a dynamic and contemporary data source to reveal cooperative patterns among tourist attractions. Our approach delineates a potential cooperative network within the destination ecosystem, categorizing tourist attractions into three distinct communities: core, intermediary, and periphery. These communities correspond to high, medium, and low tourist demand scales, respectively. The study uncovers a self-organizing network structure, driven by congruences in internal tourist dema

SUBMITTER: Ma X 

PROVIDER: S-EPMC10849253 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature