Quantitative Methods in Tourism: A Handbook

Author: Rodolfo Baggio, Jane Klobas

Related Formats:
Hardback, Ebook(PDF), Ebook(EPUB)
Channel View Publications
Number of pages:
234mm x 156mm

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In this revised second edition, Baggio and Klobas build upon the work of their previous volume, offering a presentation of quantitative research methods for tourism researchers. This accessible and rigorous guide goes beyond the approaches usually covered in introductory textbooks on quantitative methods to consider useful techniques for statistical inquiry into tourism matters of all but the most econometrically complex kind. The first part of the book concerns common issues in statistical analysis of data and the most widely-used techniques, while the second part describes and discusses several newer and less common approaches to data analysis that are valuable for tourism researchers and analysts.

Updates to the second edition include:

• a new chapter on "Big Data" 
• consideration of data screening and cleaning
• the use of similarity and diversity indexes for comparing samples
• observations about the partial least squares (PLS) approach to path modelling
• a new section on multi-group structural equation modelling
• a new section on common method variance and its treatment
• revised and updated section on software
• fully updated references and examples

New material in the second edition of this handbook includes a chapter on big data and updated coverage of agent-based modelling. Illustrated throughout with a variety of well-chosen examples pertaining to a wide range of tourism topics, this is an essential addition to the book shelves of all tourism graduate students and researchers.

Sarah Nicholls, Michigan State University, USA

With wide coverage of quantitative approaches and practical examples in tourism, this book walks readers through the essentials of quantitative methods that are required to keep pace with the fast-changing tourism industry. The book provides a thorough review of quantitative techniques and addresses pressing issues such as "Big Data", making it a must-read reference for researchers, educators, practitioners, and students.

Rob Law, The Hong Kong Polytechnic University, Hong Kong

An excellent practical guide for researchers, analysts, industry consultants and students, providing a rigorous yet readable account of standard and new quantitative statistical applications in tourism contexts. This usable reference book deserves a prominent place on every tourism scholar's bookshelf.

Larry Dwyer, University of Ljubljana, Slovenia

I highly recommend the reading of this book to all tourism researchers using quantitative methods. It offers a complete vision of all the methods that can be used, and provides important and extensive information. From a technical point of view, it is the most rigorous and reliable book in this field.

Tourism Analysis, Vol. 25

Rodolfo Baggio is Professor of the Master of Economics and Tourism at Bocconi University, Italy. His research interests focus on information technology and tourism and his current work combines complexity theory and network analysis methods to the study of tourism destinations.

Jane Klobas is an Education and Research Consultant, based in Australia and Italy. She is an Adjunct Professor at Murdoch University, Australia and a Visiting Professor at the University of Bergamo, Italy and other universities in Europe and Asia. Her interests include research development, adult learning, knowledge and information management and applications of the theory of planned behaviour.


Introduction to the Second Edition


Part I – The Analysis of Data

Introduction to Part I

Chapter 1 – The Nature of Data in Tourism

Chapter 2 - Testing Hypotheses and Comparing Samples

Chapter 3 – Data Reduction

Chapter 4 - Model Building

Chapter 5 - Time Dependent Phenomena and Forecasting

Part II - Numerical Methods

Introduction to Part II

Chapter 6 - Maximum Likelihood Estimation

Chapter 7 – Monte Carlo Methods

Chapter 8 – Big Data

Chapter 9 - Simulations and Agent-Based Modelling

Appendix: Software Programs

Postgraduate, Research / Professional, Undergraduate
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