United Nations publication. Sales no. E.08.XVII.28--T.p. verso.

The 2020 edition analyses tourism performance and policy trends across 51 OECD countries and partner economies. It highlights the need for coherent and comprehensive approaches to tourism policy making, and the significance of the tourism economy, with data covering domestic, inbound and outbound tourism, enterprises and employment, and internal tourism consumption.

Big data is already being used to measure, monitor, and manage tourism development, but its potential remains to be fully exploited. This report discusses the trends, opportunities, and challenges in using big data and digitalization in the tourism sector. It highlights how big data is being leveraged for COVID-19 recovery and examines its relationship with statistical frameworks to better measure the economic, social, and environmental impact of tourism. Case studies of partnerships in Asia and the Pacific between the public and private sector demonstrate ways to tap big data.

The purpose of a Tourism Satellite Account is to analyse in detail all the aspects of demand for goods and services associated with the activity of visitors; to observe the operational interface with the supply of such goods and services within the economy; and to describe how this supply interacts with other economic activities. The present volume provides an updated framework for constructing a Tourism Satellite Account. It should permit greater internal consistency of tourism statistics with the rest of the statistical system of a country, as well as increased international comparability of these data.

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

Understanding, for each of the 197 countries, where its inbound tourism is generated is key for analysing international tourism flows and devising marketing strategies. With the most complete statistical database available on the tourism sector, the "Yearbook" offers data to total arrivals and overnight stays, broken down by country of origin.