10% off all books and free delivery over £40 - Last Express Posting Date for Christmas: 20th December
Buy from our bookstore and 25% of the cover price will be given to a school of your choice to buy more books. *15% of eBooks.

Big Data Analytics for the Prediction of Tourist Preferences Worldwide

View All Editions

The selected edition of this book is not available to buy right now.
Add To Wishlist
Write A Review

About

Big Data Analytics for the Prediction of Tourist Preferences Worldwide Synopsis

Big Data analytics and machine learning are being adopted in a range of industries – but how can these technologies be utilised and what can they offer to the tourism industry? In the process of their journeys and in their decision-making processes, people who travel contribute to the generation of a huge flow of data; all this information is a potential base for creating smart destinations and improving tourism organizations’ potential to customize their products and service offerings. The real execution of such inventive forms of data-driven value generation in tourism continues to be more restricted to the theory or used in a few exceptional cases. Big data and machine learning techniques in tourism persists as an unclear concept and a subject of investigation that necessitates closer analysis from an extensive range of field and research methods. Big Data Analytics for the Prediction of Tourist Preferences Worldwide tackles this challenge, exploring the benefits, importance and demonstrates how Big Data can be applied in predicting tourist preferences and delivering tourism services in a customer friendly manner. The authors provide theoretical and experiential contributions designed to see a wider adoption of these technologies in the tourism industry.

About This Edition

ISBN: 9781835493397
Publication date: 22nd February 2024
Author: Dr N SRI Padmavati Mahila Visvavidyalayam, India Padmaja, Dr Rajalakshmi Talaash Research Consultants, India Subramaniam
Publisher: Emerald Publishing Limited
Format: Hardback
Pagination: 144 pages
Series: Emerald Points
Genres: Hospitality, sports, leisure and tourism industries
E-commerce: business aspects
Business innovation
Data capture and analysis