An improved collaborative filtering model based on time weighted correlation coefficient and inter-cluster separation

Lan, Ruike; Tian, Donghong; Wu, Qianqian; Li, Min

doi:10.1007/s13042-023-01849-y

Cited by 2 publications

References 38 publications

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Predictors of the Success of Yacht Charter in Andalusia from a Leading P2P Platform Using Machine Learning

Jiménez-Jiménez,

Sancha,

Martín-Álvarez

et al. 2024

Springer Proceedings in Business and Economics

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Research related to the sharing economy in yacht charter is scarce compared to other tourism services such as accommodation, so more contributions are needed. Yacht rental has become essential in the tourist services of coastal destinations, providing important benefits. The vertiginous growth of the boat rental offer hosted on p2p platforms requires analysis, characterization, and search for product patterns that allow a better knowledge of it. The data obtained, based on machine learning techniques, can be used as predictors to detect which products are suitable for the growth and development of the sector in each Andalusian marina. The results provide a relevant contribution to the sector and the enrichment of the literature.

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Predictors of the Success of Yacht Charter in Andalusia from a Leading P2P Platform Using Machine Learning

Jiménez-Jiménez,

Sancha,

Martín-Álvarez

et al. 2024

Springer Proceedings in Business and Economics

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Beyond Chartering: Adapting the Offer to Customer Behavior for a Sustainable Yachting Industry

Jiménez-Jiménez,

Sancha,

Gessa

2024

Sustainability

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The significant and ongoing growth of the yacht charter sector plays a crucial role in the tourism industry as a whole, especially in nautical tourism. This study provides a detailed analysis of the yacht charter market, focusing on the opportunities for and challenges in its sustainable growth, with a specific emphasis on Andalusia, Spain. The main objective is to align the yacht charter offer with customer preferences, enabling yacht owners or companies to make more informed decisions and contributing to the sustainability of the sector and the region. Using machine learning techniques, researchers have analyzed extensive datasets to identify patterns in customer behavior and yacht characteristics. Industry companies and yacht owners can use the results of this research to develop more effective marketing strategies, improve customer experience, and efficiently manage their fleets, thus directly contributing to the socio-economic and environmental sustainability of mooring locations. Furthermore, this research enhances the understanding of yachting tourism, laying the groundwork for future research and developments in the industry.

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An improved collaborative filtering model based on time weighted correlation coefficient and inter-cluster separation

Cited by 2 publications

References 38 publications

Predictors of the Success of Yacht Charter in Andalusia from a Leading P2P Platform Using Machine Learning

Predictors of the Success of Yacht Charter in Andalusia from a Leading P2P Platform Using Machine Learning

Beyond Chartering: Adapting the Offer to Customer Behavior for a Sustainable Yachting Industry

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