Analysis of tourist systems predictive models applied to growing sun and beach tourist destination

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Date
2021-01-15
Author
Ruiz Palacios, Miguel Angel
Pereira Teixeira de Oliveira, Cristiana
Serrano González, José
Saenz Flores, Soledad Gisela
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Abstract
ABSTRACT This study aims to present a new diagnosis model of Sun and beach destinations, we analyzed a set of explanatory theories about the tourism system, because current models do not reflect the real dynamics of an emerging tourist destination. We create a new predictive model so it served us to be used as a diagnostic method for the tourism system. Ancon district is a coastal town of Peru, it is the second-largest and oldest of Metropolitan Lima district. The study analyzed all tourist attractionsandlocalresourcesincludingreservedzoneLomasdeAncón,with10,962hectares. Itused a qualitative method and its design is grounded theory and phenomenological. The research covers theperiodfromMay2018toMarch2019,whereitwaspossibletoappreciatethehightouristdemand andwildfloraandfaunaoftheLomasdeAncóninitstwoseasons: winterseason(2018)andsummer 2019 (dry season). The study concludes that the new analysis model allows us identifying and understanding the dynamic and potential of sun and beach tourist destinations in the growth phase. The Ancón district has resources and attractions that would allow it to develop new tourist products and diversify the local tourist offer.
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URI
https://hdl.handle.net/11537/28432
Bibliographic citation
Ruiz, M. A., ...[et al.]. (2021). Analysis of tourist systems predictive models applied to growing sun and beach tourist destination. Sustainability, 13 (2). https://doi.org/10.3390/su13020785
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