Speakers
Description
The increasing availability of data due to effective and fast sharing methods offered by technological advances has catalyzed new approaches like network science to process large data sets and transcend traditional statistical tools analysis; hence we introduce the tripartite: destinations-rates-advisories network to make connections between complex non-linear interrelations that affect Mexican tourism industry. In the construction of this network the first set of nodes are 70 main Mexican tourist destinations; the second set corresponds to occupancy rates each destination had in 2017 and 2018; and the third set captures travel advisories emitted in 2017 and 2018 for some Mexican tourist destinations. Our network analysis is an attempt to extract useful information from a large amount of data, identifying occupancy rates prevalence, variation and their correlation with travel advisories; pertinent to develop deep understanding of tourism encoded interactions and to lead informed strategic decision making and operational coordination to amplify range of responses to adverse scenarios in tourism industry.
