of the book. The authors present models as tools toencourage new ways of thinking, as opposed to prescrip-tive models, which is an appropriate way to "nish theirwork. Consequently, at the end of the book, the authorsare looking forward to new approaches rather than backto what has been.So, does this publication o!er anything new, or is it

a synthesis of known material? In such a complex andwell-documented area as ecotourism, a good synthesis ofthe material would be invaluable. The authors succeed inthis (in the areas they have covered), but also go further,providing some excellent commentary on what is

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happening in the world as opposed to merely a theoret-ical synopsis. This publication is in a "eld that is burstingat the seams, however the authors have managed toidentify a need and respond to it. If only the title wasmore re#ective of the range of the publication. I for onewould never have taken the time to consider it from thetitle alone.

Sue BeetonLa Trobe University, P.O. Box 199, Bendigo,

Victoria 3632, AustraliaE-mail address: s.beeton@latrobe.edu.au.

Tourism demand modelling and forecastingH. Song and S.F. Witt; Pergamon, Oxford, 2000,178 pages, US$75 hard cover, ISBN 0-08-043673-0

This book is a very timely description and applicationof advanced causal forecasting methods for tourism dataseries. Causal time-series has become more complex inrecent years particularly as a result of the recently recog-nized (in tourism) problem of stationarity. Stationarity isassumed in commonly used multiple regression model-ling. However, it is now recognized that largely becauseof the growing nature of tourism demand series, that themean of the time-series data is unlikely to be stationary,and the accuracy of the forecasting regression modelstatistics are highly suspect. This in turn has forced fore-casters to examine more complex methodology in whichthe stationarity problem can be overcome, and has laidwaste much of the research previously comparing thestatistical output of di!erent multiple regression models(meta research). The question is how important is theneed for using complex models to overcome stationarity,what are these models and how do they compare to the&traditional' approach? These questions are the focus ofthis book.Consequently, the material is aimed primarily at the

research level, postgraduate studies and advanced under-graduate programs. The reader is required to have somequantitative knowledge but not overly so, certainly not inorder to understand the general concepts and argumentsof the book, but more so to apply the techniques in othersituations. In particular, the reader needs to distinguishat an early stage between forecasting accuracy within andwithout samples. This aspect of forecasting is explainedlater in the book, but still could be confusing if not reallyunderstood. The testing of accuracy and comparison ofcausal models done within sample has the future valuesof the independent variables known in advance for test-ing purposes, whereas beyond sample forecasting re-quires the independent variables to be forecast "rst,

before a causal model can be applied. Indeed this is thegreat weakness of all causal modelling when applied toreal world forecasting problems, where the future of theindependent variables is equally as unknown as the fu-ture of the tourism arrival series.This book uses within sample forecasting because

the emphasis is upon demand modelling and not realworld forecasting. The reason for this emphasis is thealready stated focus upon introducing and explainingmethodologies to overcome the critical problem ofstationarity, as opposed to developing new tools forpractitioners.The book has nine chapters. However, it is a small

book of only 178 pages. The "rst three chapters set thescene by introducing the current state of demand model-ling, the determinants (causes) as currently understood,and the traditional multiple regression approach. Chap-ter 4 outlines very clearly what the problem of non-stationarity is, and introduces the concept of a co-integ-rated series to obtain stationarity, and the testing re-quired to determine whether co-integration exists.Chapter 5 presents the Error Correction Model asa means of modelling a co-integrated set of variables.Chapter 6 examines Vector Autoregression (VAR) as animportant form of simultaneous equation analysis, andalso explains why co-integrated series are well handledby VAR modelling, especially if there are more than oneco-integrated series within one analysis. Chapter 7 exam-ines the time varying parameter model, which is parti-cularly useful, as it has had little exposure in the tourismliterature. This method allows the coe$cients to changeover time and hence allows the various causal measuresto change in their level of in#uence over time, which ispotentially more realistic of real world in#uences ontravel #ow. Chapter 8 looks at Panel data analysis whichallows for the introduction of cross-sectional (as opposedto time series) data into a forecasting framework, themain advantage of which is to allow for other causes suchas social variables not easily measured as a time-series, to

578 Book reviews / Tourism Management 22 (2001) 571}580

be introduced. Chapter 9 evaluates the forecasting per-formance of the various models presented earlier andcompares the models within sample, so the problems offorecasting the independent variables do not arise.The perplexing "nding of Chapter 9 relates back to

earlier parts of the book. The time varying parametermodel performs best on the example data set. This ofcourse does not mean that it would always perform beston other data. Indeed the failure to compare on morethan one data set (arrivals to South Korea from the UKand USA from 1962 to 1994), and with a wider range ofindependent variables, and possibly with disaggregationinto travel types, could be considered a weakness in thischapter. More interestingly, the &no change' model alsoperforms well. The perplexing issue is that this bookmustconclude that whilst overcoming stationarity doesimprove forecasts, the more complex models do notperform well against a simple no change forecast. This"nding continues to support the "ndings in current liter-ature (as stated earlier in the book) that causal modelstend to be less accurate than might be expected. Alsofrom a practitioner's point of view, beyond sample fore-casting, where the independent variables must also beseparately forecast can only increase error and furtherreduce accuracy, and hence further favour the nochange model. The classical answer to this problem byeconomists is to suggest that either the correct causes

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have not been found (readers can then refer to Chapter8 and the use of Panel data) or the model is not correctlyspeci"ed (hence the more complex modelling techniques).However, it seems that despite the increased complexityof the models, and their capacity to include morevariables, the causal models still fail to be particularlyaccurate.Overall this book is very important in raising the level

of technical expertise required to achieve accuratecausal model forecasts, and explaining why this isnecessary. As a text, the book pushes the understandingof tourism forecasting methodology out to currently ac-cepted econometric standards, and must become a stan-dard research reference work for economic forecasting oftourism series. Furthermore, the research "ndings of thebook suggest we still have some way to go in formulatingan accurate causal demand model, so watch thisspace.Finally, the book is perhaps highly priced at US$75,

but is high quality, hard cover and very well presented.

Lindsay TurnerSchool of Applied Economics,

Victoria University of Technology,P.O. Box 14428 MC,

Melbourne, VIC 8001, AustraliaE-mail address: lindsay.turner@vu.edu.au.

Consumer behaviour in tourismJohn Swarbrooke, SusanHorner; Butterworth-Heinemann,Oxford; 1999, 453 pp. ISBN 07506 3283 6

&Consumer Behaviour in Tourism' is described asa &concise overview' providing an introductory text froman international perspective. It aims to highlight topicalissues, latest research "ndings and to link theory topractice. It achieves the latter by providing several de-tailed case studies. The authors (or their publishers) aimthe text at students, lecturers and practitioners. It wasonly here after reading the text that I would beg to di!er.This certainly is a welcome text, as much of the literatureregarding consumer behaviour is more general. I feel surethat those reading this review would agree that the nu-merous unique attributes of tourism make for somerather more complex aspects of consumer behaviour thanwould be found in other spheres of life. However, it isstudents who will "nd this book most welcome and thenperhaps their lecturers. In my view, this text is clearlyaimed at the undergraduate market and it is here thatmost of its sales will come from. To that end it is writtenclearly and concisely with short but connected chapters,with discussion points and essay questions. It is to the

undergraduate market, though, as opposed to the post-graduate where this text has its strength. Key authors areintroduced in a sensible way, but the text is not overlycluttered with too many references. Some may see this asa weakness, but the authors convey an approachablestyle that will engage students. Perhaps though, I wasa little surprised that the &bibliography and further read-ing' section was only a list of (useful) source material. Theauthors could have recommended a small number of keytexts following each chapter in addition to this list.The text is divided into eight substantive parts, plus

a glossary of relevant terms. Within each &part' there areone to four chapters, while part eight, covering nearly 200pages, is made up of 22 case studies. Parts 1}4, coveringthe "rst 11 chapters are more introductory in nature.Part 1, &Context' has an historical review and introducesa range of models used or adapted to explain consumerbehaviour in tourism. Some of these are described asbeing simplistic or inadequate. Part 2 looks at the pur-chase-decision process with three chapters on moti-vators, determinants and models of the purchasedecision-making process. Part 3 is dedicated to aspects oftourist typologies and segmentation. Here is a goodexample of where Swarbrooke and Horner will be

Book reviews / Tourism Management 22 (2001) 571}580 579