Big data analytics for the prediction of tourist preferences worldwide
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...
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| Format: | E-Book |
| Sprache: | English |
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Bingley, U.K.
Emerald Publishing Limited
2024
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| Schriftenreihe: | Emerald points
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| 100 | 1 | |a Padmaja, N. | |
| 245 | 1 | 0 | |a Big data analytics for the prediction of tourist preferences worldwide |c Dr. N. Padmaja (SRI Padmavati Mahila Visvavidyalayam, India), Dr. Rajalakshmi Subramaniam (Talaash Research Consultants, India), Dr. Sanjay Mohapatra (Batoi Systems Pvt Ltd, India) |
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| 520 | |a 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. | ||
| 700 | 1 | |a Mohapatra, Sanjay | |
| 700 | 1 | |a Subramaniam, Rajalakshmi | |
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| spelling | Padmaja, N. Big data analytics for the prediction of tourist preferences worldwide Dr. N. Padmaja (SRI Padmavati Mahila Visvavidyalayam, India), Dr. Rajalakshmi Subramaniam (Talaash Research Consultants, India), Dr. Sanjay Mohapatra (Batoi Systems Pvt Ltd, India) Bingley, U.K. Emerald Publishing Limited 2024 ©2024 1 Online-Ressource (144 Seiten) txt c cr Emerald points Includes index. 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. Mohapatra, Sanjay Subramaniam, Rajalakshmi Erscheint auch als Druck-Ausgabe 9781835493380 Erscheint auch als Druck-Ausgabe 9781835493397 TUM01 ZDB-55-ELD TUM_PDA_ELD https://doi.org/10.1108/9781835493380 Volltext |
| spellingShingle | Padmaja, N. Big data analytics for the prediction of tourist preferences worldwide |
| title | Big data analytics for the prediction of tourist preferences worldwide |
| title_auth | Big data analytics for the prediction of tourist preferences worldwide |
| title_exact_search | Big data analytics for the prediction of tourist preferences worldwide |
| title_full | Big data analytics for the prediction of tourist preferences worldwide Dr. N. Padmaja (SRI Padmavati Mahila Visvavidyalayam, India), Dr. Rajalakshmi Subramaniam (Talaash Research Consultants, India), Dr. Sanjay Mohapatra (Batoi Systems Pvt Ltd, India) |
| title_fullStr | Big data analytics for the prediction of tourist preferences worldwide Dr. N. Padmaja (SRI Padmavati Mahila Visvavidyalayam, India), Dr. Rajalakshmi Subramaniam (Talaash Research Consultants, India), Dr. Sanjay Mohapatra (Batoi Systems Pvt Ltd, India) |
| title_full_unstemmed | Big data analytics for the prediction of tourist preferences worldwide Dr. N. Padmaja (SRI Padmavati Mahila Visvavidyalayam, India), Dr. Rajalakshmi Subramaniam (Talaash Research Consultants, India), Dr. Sanjay Mohapatra (Batoi Systems Pvt Ltd, India) |
| title_short | Big data analytics for the prediction of tourist preferences worldwide |
| title_sort | big data analytics for the prediction of tourist preferences worldwide |
| url | https://doi.org/10.1108/9781835493380 |
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