Book reviews

PII: S0261-5177(97)00120-9

Practical Tourism Forecasting Douglas C Frechtling Butterworth Heinemann, Oxford (1996) pp. 245, ISBN

Over the last 5 to 10 years, text books dealing with issues related to Tourism have proliferated. However, until this book was published, none have presented a clear step by step guide to forecasting tourism demand. This book is therefore a very welcome addition to the growing library of tourism textbooks.

Douglas Frechtling has aimed the book at postgraduate students in tourism and hospitality degree programmes, but also points out its usefulness to managers and adminis- trators who need demand forecasts. In particular it focuses on thirteen different forecasting techniques and takes the reader in easy stages through each.

The first three chapters give the reader a general background picture of the book and its rationale, generic forecasting issues and the basic steps involved in producing forecasts of demand into the future. Chapters four to nine then look in more depth at (1) Basic extrapolative models and decomposition, (2) Intermediate extrapolative methods, (3) The Box-Jenkins approach to forecasting, (4) Regression Analysis, (5) Structural models and (6) Qualitative forecasting methods. The book concludes with a summary of learning points about tourism demand forecasting and some general guidelines to help the reader avoid some common mistakes.

Overall Douglas Frechtling has produced an easy to follow basic guide to tourism forecasting. The novice should find it relatively easy to produce forecasts, particularly when using the methods covered in the earlier chapters of the book. However, unfortunately, the book is somewhat

marred by some inconsistencies, which in places make the explanations diffi- cult to follow. For example, on page 83 in Table 5.2, the value of SES, , is given as 1138 at the beginning of the line and as 1137 at the end of the line. The student may also be surprised to find that 1323-14=1310 in Table 5.1! Chapter 5 seems to have an unfair share of these minor errors, which is unfortunate, because clearly, if illustrations are inaccurate, it is very difficult for a student to link the concept with the example.

A difficulty which faces any author attempting to write such a book, is 'pitching' the explanations at the correct level. How much prior under- standing of general statistics will the reader have? The book, at the outset, seems to assume little knowledge, and concepts are explained very clearly. At a very early stage in Chapter 1, various terms are defined, and in addition, at the end of the book, the author has included a very useful glossary of terms, In places the author has had to refer the reader to a later section in the book for a fuller explan- ation of a term or technique, however, in other places terms have been used before they have been defined/ explained and without reference to a later section. For example, in Chapter 5, on page 78, the author uses the term 'differencing' without reference to the later section (pages 96-97) where the term is explained. Similarly on page 113 the author states 'If the autocorrelations show a decaying sine wave pattern...'. A sine wave pattern is illustrated on page 131, but the two references are not linked in any way. Given the target audience this is likely to cause a problem for many readers.

Chapter 6 is perhaps the most diffi- cult of the book. The author has made a valiant attempt at explaining a fairly complex procedure. Some prior knowledge of statistics would be of help to the reader in this section of the book.

What was disappointing was

Chapter 7. In this chapter regression models were explained. Although the author did not claim to go into the area in great depth and the coverage was kept to the basics with the inter- ested reader being referred to other texts for further in depth discussion, the chapter contains what could be considered to be a couple of fairly major flaws. When using time series data, a problem can be caused by inflation. A commonly adopted solution to this is to express the data series in 'real terms'. For example, if the cost of travel is included in a model, the actual cost (i.e. actual fares) should not be used, but the effects of inflation should be taken out. If air fares have not been rising as quickly as the general cost of living, although in actual terms the cost seems to have gone up, relatively speaking the cost may have gone down. This issue is not fully covered in the text and in fact, the author has developed a series of models in which only one of the explanatory variables out of the four which should have been deflated has been expressed in real terms. This could in part explain why the second problem occurred. The signs of some of the estimated parameters were also contrary to expectation and economic theory. Whilst the author had earlier expressly pointed out that such results could indicate a mis-specification of the model, the models presented were still accepted and subsequently tested!

Despite the reservations expressed above, this first attempt at a step by step guide to Practical Tourism Forecasting will surely prove to be a very useful addition to the tourism literature.

C A Hope University of Bradford

Management Centre Emm Lane

Bradford West Yorkshire BD9 4JL

UK

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