Applied Data Science In Tourism
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Applied Data Science in Tourism
Access to large data sets has led to a paradigm shift in the tourism research landscape. Big data is enabling a new form of knowledge gain, while at the same time shaking the epistemological foundations and requiring new methods and analysis approaches. It allows for interdisciplinary cooperation between computer sciences and social and economic sciences, and complements the traditional research approaches. This book provides a broad basis for the practical application of data science approaches such as machine learning, text mining, social network analysis, and many more, which are essential for interdisciplinary tourism research. Each method is presented in principle, viewed analytically, and its advantages and disadvantages are weighed up and typical fields of application are presented. The correct methodical application is presented with a "how-to" approach, together with code examples, allowing a wider reader base including researchers, practitioners, and students entering the field. The book is a very well-structured introduction to data science – not only in tourism – and its methodological foundations, accompanied by well-chosen practical cases. It underlines an important insight: data are only representations of reality, you need methodological skills and domain background to derive knowledge from them - Hannes Werthner, Vienna University of Technology Roman Egger has accomplished a difficult but necessary task: make clear how data science can practically support and foster travel and tourism research and applications. The book offers a well-taught collection of chapters giving a comprehensive and deep account of AI and data science for tourism - Francesco Ricci, Free University of Bozen-Bolzano This well-structured and easy-to-read book provides a comprehensive overview of data science in tourism. It contributes largely to the methodological repository beyond traditional methods. - Rob Law, University of Macau
International Handbook of Skill, Education, Learning, and Research Development in Tourism and Hospitality
This handbook provides new dimensions and directions to design tourism education curriculums and transform students' learning. It delves into issues such as job opportunities, business opportunities, required skill sets, and the role of critical and creative thinking in tourism education, and focuses on a shift in mindset from R&D (research and development) to L&D (learning and development), to aid in gaining in-the-field knowledge. It presents a global perspective on the latest trends, innovative curriculum, research, and skill needs in the travel, tourism, and hotel industry via empirical, theoretical, and conceptual chapters, as well as through global case studies. This handbook explores how to develop the skills, attributes and prospects for employment in these competitive industries, and also highlights what employers in the tourism and hospitality sectors expect from graduate and/or post-graduate candidates. Besides examining the contribution of tourism education towards a better society, this handbook introduces a new way of designing curriculums, and examines the past practices, current trends, and future opportunities in the field.
Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies
Disruptive innovations are now propelling Industry 4.0 (I4.0) and presenting new opportunities for value generation in all major industry segments. I4.0 technologies' innovations in cybersecurity and data science provide smart apps and services with accurate real-time monitoring and control. Through enhanced access to real-time information, it also aims to increase overall effectiveness, lower costs, and increase the efficiency of people, processes, and technology. The Handbook of Research on Data Science and Cybersecurity Innovations in Industry 4.0 Technologies discusses the technological foundations of cybersecurity and data science within the scope of the I4.0 landscape and details the existing cybersecurity and data science innovations with I4.0 applications, as well as state-of-the-art solutions with regard to both academic research and practical implementations. Covering key topics such as data science, blockchain, and artificial intelligence, this premier reference source is ideal for industry professionals, computer scientists, scholars, researchers, academicians, practitioners, instructors, and students.