What is it about?
Tourism is a major driver of economic development, and it is important to identify and develop tourist routes that are both attractive and efficient. This research proposes a new methodology for identifying tourist routes that is based on clustering techniques. The methodology first identifies potential tourist sites based on a set of criteria, such as natural attractions, cultural attractions, and infrastructure. These sites are then clustered into groups based on their similarity. Finally, routes are designed that connect the sites within each cluster.
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Why is it important?
This work proposes a new methodology for identifying tourist routes based on clustering techniques. This is a significant advance in the field of tourism planning, as it allows tourism planners to identify and develop tourist routes that are both attractive and efficient. In addition, this work is timely because it implements a growing interest in using data science and machine learning to solve problems in the tourism industry, improving the efficiency and effectiveness of tourism planning, and it could also help to promote tourism in regions that are not as well-known.
Perspectives
I am very excited about this publication, as it is the first time I have applied my research on clustering techniques to the field of tourism planning. I believe this methodology can revolutionize how tourist routes are identified and developed, and I am eager to see how tourism planners and managers will use it in the future. I am also grateful to my co-authors for their contributions to this work. Their expertise in tourism planning and data science was essential to the success of this project.
Mr Leonardo Hernan Talero-Sarmiento
Universidad Autonoma de Bucaramanga
Read the Original
This page is a summary of: Methodological proposal for the identification of tourist routes in a particular region through clustering techniques, Heliyon, April 2021, Elsevier,
DOI: 10.1016/j.heliyon.2021.e06655.
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