Abstract
The different tourism activities that can be carried out in a destination are interconnected, not only due to the characteristics of the tourism available but also the tourists’ profile. The implementation of a connectivity analysis not only identifies the connections between various tourist activities, gender preferences, and seasonal fluctuations, but also discloses the hierarchical structure within these elements. Understanding the hierarchical structure - certain activities function as key attractions while others serve as supplementary offerings to enhance the whole experience - provides insights for the destination managers to effectively distribute resources and improve the overall experience of visitors. This novel approach utilizes data analytics, network theory, and statistical methods to reveal the complex network of interrelationships among various tourist activities. In this study, we use a large public database from the Canary Islands (almost 165.000 tourists observed from 2018 to 2022) including attractions visited, services consumed, socioeconomic and demographic characteristics, as well as the seasonal fluctuations in tourist numbers, to discerns not only the activities that are most favoured by visitors, but also the hierarchical connections that exist among them. Results are used to implement some policy recommendations in order to maximize resource allocation and tourist satisfaction.
Presenters
Andrea Rodriguez RamoaPhD Student, Análisis Económico Aplicado, Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain Eugenio Diaz Fariña
Professor, Applied Economics, Universidad Las Palmas de Gran Canaria, Las Palmas, Spain Aythami Santana Padrón
PIF, Economic Applied, ULPGC, Spain
Details
Presentation Type
Paper Presentation in a Themed Session
Theme
2024 Special Focus—Tourism, Leisure and Change: Transforming People and Places
KEYWORDS
Tourism, Interdependence, Connectivity Analysis
