We live in a research world increasingly awash with rich sources of micro-level data and powerful analytical tools. The field of tourism research can benefit from these trends in many ways. With the continued collection of national, regional and local level data on tourist behaviour, as well as tourist self-reporting through the creation of online user-generated content, the opportunities for quantitative data analysis are greater than ever. This makes Quantitative Methods in Tourism a timely book, and one that should reach a receptive audience.
The goals of this book are to highlight several quantitative methods within one volume, describing each method with an accessible tone and greater depth than permitted in the context of a journal manuscript. By placing quantitative methods within a tourism-relevant context, the authors argue for wider consideration and adoption of these techniques. To accomplish these goals, the authors bring together quantitative statistical methods that have a strong existing or potential presence in tourism research, and illustrate them with tourism-relevant case studies and notes.
The authors target this book towards an audience of masters and PhD students, active researchers, practitioners and industry consultants. This broad target audience requires a range of content. First, there should be a pedagogic component, to instruct students about quantitative methods. Second, the book needs to contain enough cutting-edge material to interest the veteran researcher. For practitioners, there must clearly be an applied, real-world relevance to each and every section.
The book is structured into two parts, the first ‘Analysis of Data’ and the second, ‘Numerical Methods’. Part 1 covers many of the staple topics of quantitative methods, devoting a chapter to each of: the nature of data in tourism; testing hypotheses; data analysis; model building; and time-dependent phenomena and forecasting. Within each chapter, the topics covered vary in detail.
Chapter One: ‘The Nature of Data in Tourism’, provides a general overview of data types, data quality, criteria for selecting a dataset, and even the basic differentiations between primary and secondary data. This very readable introduction carries over into Chapter Two: ‘Testing Hypotheses’, where the reader is presented the statistical fundamentals of parametric and non-parametric tests. Though tourism-specific examples are used, these are primarily concerned with the mechanics of the statistical tests, rather than the application of these tests to provide insight into the tourism phenomenon. Chapter 3: ‘Data Analysis’ ramps up the level of mathematical presentation quickly, making this chapter a challenge for those without a statistics primer. The section on factor analysis is highlighted by an extended example of evaluating a destination website. Chapter 4: ‘Model Building’ begins with a return to a more step-by-step format, describing linear regression. The authors cover common practices, including the calculation of R2. The latter half of this chapter introduces the reader to structural equation modelling, with a focus on using this approach to study intention to return. This section makes a very clear case for the use of structural equation modelling to understand one of the more nuanced – and critical – aspects of tourist behaviour. Chapter 5: ‘Time-dependent Phenomena and Forecasting’, provides a review of what many would consider as a key component of understanding tourism – change over time. This chapter covers basic concepts of a time-series, using seasonal variations in tourist arrivals as an example. The authors extend this discussion to include forecasting and turn a critical eye to questions of predictability.
Part 2: ‘Numerical Methods’ is a significant departure from Part 1, in that it presents several methods – though prevalent in other fields – that are not necessarily well known in tourism studies. This is an ambitious approach, as the authors try to provide an introduction to methods without the benefit of a large amount of tourism-related literature to support the discussion or to direct readers for follow-up. All three methods discussed; maximum likelihood estimation, Monte Carlo methods, and agent-based modelling, can be considered computational approaches, in that they require the use of modern computing power to some degree. Considering the complexity of these approaches, readers who are intrigued by this general overview will certainly wish to search out both books that focus exclusively on each topic, and those journal articles that can provide context to how these approaches can be used and their results analysed. I applaud the authors for including this non-traditional material as a way to increase the exposure of tourism readership to methods that are being rapidly adopted in other fields.
The authors note that quantitative methods can be a difficult topic for many, and attempt to inject real-world examples to keep the interest level high. However, the book attempts a difficult balancing act between breadth, depth and accessibility. At a slim 256 pages, it cannot provide the detailed step-by-step instruction, examples and referencing required to be considered a textbook. Also, considering one goal of the book is to present quantitative methods in a user-friendly, accessible light, the reader should expect a detailed explication of concepts and terminology, accompanied by richly described case studies that place the quantitative method in a context of place, problem, action, solution and evaluation. This goal is difficult to achieve in 256 pages, especially considering the broad scope of the book's table of contents. It should also be noted that in making technical concepts accessible, attention should be paid to providing well-labelled and informative graphics, charts and tables. This is one area that could have been done better, with greater use of descriptive labels on charts and tables.
In conclusion, Quantitative Methods in Tourism is a timely book motivated by a lofty set of goals. Whether these goals are met depends largely on the background of the reader. The student (particularly one with little background in statistics) will need the detailed, step-by-step instruction, glossary and referencing found in a dedicated textbook on statistics. The veteran researcher will find some interest in the condensed overview provided for each method, and the list of tourism-specific references, but it is very possible that much of this will be a repeat, with the possible exception of Part 2. The power stats user will already have a list of textbooks and references to which they prefer to turn. For a reader from industry, they may well find the discussion of methods interesting, but may also be disappointed with the generality of the examples used, and may find it difficult to see application to their own work in what can be a very high-level discussion of statistics. Overall, Quantitative Methods in Tourism takes on a challenging task – to distill a set of methods that are not easily communicated without a high level of detail. This is a task that the book accomplished in many ways, but also in a way that may leave certain groups of readers wishing for more detail and explication.