Pergamon

PII: S0261-5177(97~00103-9

Tmtrism Management, Vol. 19, No. 2, pp. 119-126, 1998 © 1998 Elsevier Science Ltd. All rights reserved

Printed in Great Britain (1261-5177/98 $19.(}0 + ().(X)

Risk management in the Irish tourism industry: the contribution of a portfolio investment approach

Vincent Kennedy Department of Economics, University of Limerick, Limerick, Ireland

Economies that have become dependent on the tourism industry for job creation, income generation and foreign exchange revenues should encourage diversification within their tourism markets in order to limit the adverse effects of a downturn in tourist demand. Policy makers and strategists with responsibility for the long term development of the industry should seek to attract a range of nationalities which will minimize the volatility of demand. The problem facing the policy maker is analogous to that of the investor confronted with a range of securities which exhibit different levels of risk and return. A portfolio selection methodology utilized by investors in the securities markets is applied to Irish tourism markets, and a range of market mixes which minimize risk and maximize revenue growth are estimated. © 1998 Elsevier Science Ltd. All rights reserved.

Keywords: risk management , planning, portfolio analysis, diversification

Introduction

In recent years much attention has been given to the growth in world tourism, and to its importance as an export industry and as an earner of foreign exchange. This is hardly surprising, as tourism is currently one of the largest components in the world's foreign trade. More than 270 million tourists spend $92 billion, annually, outside of their own countriesL There is no doubt that this industry has the ability to create employment and generate income in developed and developing nations, but it is not without its own adverse side effects. The mass tourism generated by many countries has led to detrimental environmental and social change. These external costs are now being counted, and it is from this starting point that most research sees the task of tourism management, i.e. lessening these negative impacts and increasing the economic benefits of tourism£

There is, however, a further aspect of the industry that has been ignored in traditional tourism accounting ~. Some economies, by becoming over- dependent on tourism for their livelihood, have made themselves vulnerable to changes in tourist demand. In circumstances of such high dependency, decreases in the level of tourist expenditure can have considerable adverse effects on the destination economy. The demand for tourism can be affected

by a number of variables, such as changes in prices, incomes, travel costs, political unrest or changing tastes and fashions. Studies of the demand for tourism have shown that different nationalities exhibit differing elasticities with respect to these variables ~-'. Combined, with this, each nationality has a different level of expenditure in the host nation, as they stay in different categories of accom- modation and spend different amounts in the local economy. Thus, each nationality can be identified with different levels of risk and return. Clearly the potential returns from tourism can be high, but there may also be a considerable risk attached to the industry. This aspect of tourism should not be overlooked; when setting industry targets, policy makers should examine each market in terms of its risk and return. To avoid economic disruption, caused by fluctuations in demand, the goal of risk management should be incorporated into the planning process: countries needs to attract a distri- bution of tourists such that the total level of varia- tion in tourist expenditure is minimized.

Portfolio analysis can be used to calculate the risk-minimizing distribution of tourists. Portfolio theory is used primarily in the field of financial analysis to aid investors in their choice of allocating portions of their budget to different securities, given that the events of the forthcoming holding period are unknown 7. Each security has a unique level of

119

Risk management in the Irish tourism industry: V Kennedy

risk and expected return. Faced with the available group of securities the investors will be seeking those portfolios that are expected to produce the maximum return for a given level of risk. Portfolio analysis tries to compute the risk-minimizing portfolio of assets given the historic risk and expected returns of the individual assets. Similar to securities, tourist markets have different levels of risk and expected return, which allows the portfolio selection methodology to be applied, and various portfolios to be estimated ~. Although there are some important caveats to be employed due to the tenta- tive analogy between the workings of tourism and securities markets, the exercise should serve to focus the attention of policy makers on the concept of risk management. Once the various market portfolios have been estimated, it should then be possible to compare the actual mix of tourists to the policy maker's optimal mix, which will depend on his or her aversion to risk. This will give policy makers clear guidelines for a marketing programme that could be aimed at influencing market distribution and ultimately putting the tourism industry on a sounder, more stable, base.

This paper examines the risk and return associ- ated with individual overseas markets and applies a portfolio selection model to estimate various portfolios or market mixes. Each portfolio is associ- ated with a different expected revenue growth rate and level of risk, depending on the weight taken by its component markets. The growth target set out in the Operational Programme for Tourism 1994-1999" can then be used as a benchmark to evaluate current policy in light of the various risk-minimizing options available.

The economic impact of tourism

Historically, Ireland has not experienced the mass influx of tourists that would be consistent with global rates of growth. This is due in part to a cool temperate climate, combined with an island location on the western periphery of Europe. The strengths of Irish tourism have been identified as: a friendly people; a vibrant folk tradition; a clean unspoiled environment; a distinctive architectural and cultural heritage; a good accommodation base; and a world- wide ethnic market'". The overall effect of the growth in world tourism, combined with changing preferences towards destinations such as Ireland", has led to considerable'changes in the Irish tourism industry over the last two decades. Over the last 20 years the number of overseas tourists has almost quadrupled, from 1.2 million in 1965 to 4.3 million in 1995, with most of this increase occurring from 1986 onwards. Ireland achieved the fastest growth in earnings from international tourism among 15 other destinations in the period 1980-1992 '2. The poten- tial for even further increases in tourist numbers is

evident from the fact that our share of European arrivals fell from 2.7% in 1960 to 1.3% in 1989 '~. So there is scope for the recovery of lost market share.

After manufacturing and agriculture, tourism is Ireland's largest industry; in 1995 overseas tourists contributed £1.4 billion, in foreign exchange revenue, to the Irish economy. The sector accounts for 6.4% of GNP, and employment--both direct and indirect--supported by tourism has grown by 51% since 1981, to 102000 jobs in 1995. This represents 30% of all jobs created during this period '4. The total foreign exchange revenues from tourism account for 5.8% of the earnings from all exports, while the industry is responsible for 56% exportable services. Furthermore, the economic impact of tourism is not specific to any one sector; expenditure spills over into all sectors of the economy, supporting employment in agriculture, manufac- turing, retailing, distribution and personal services '~.

Although Ireland is not totally dependent on tourism, the industry has grown rapidly and has had a strong positive effect on all sectors of the economy. If the demand and supply targets are realized over the next 10 years, tourism could become more important than agriculture to the economy'". Unfortunately, with the benefits come the risks: the more a country relies on tourism the bigger the adverse effects will be on the economy if there is a fall in demand for its tourism product. A fall-off in demand for tourism in Ireland would result in rising unemployment, decreasing levels of income, falling tax revenues, wasted investment and a decrease of confidence in the industry, which could have serious long term effects. Therefore, proper management and planning for the industry are of vital importance. One aspect of this manage- ment and planning would be to try, in the case of stated targets for growth, to minimize the levels of volatility that might be associated with a specific mix of tourism markets.

It is instructive to look at the actual demand for our tourism product and the level of volatility it has exhibited in the past. One method of examining this is to use real expenditure by overseas tourists in Ireland as a proxy for the demand for our tourism product. Figure 1, displays the growth rate of

mOO-

IO.QO- ®

2 ~ -5.00-

-10.00 -

-16.00

-~ .00 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

19~ 1971 1973 1975 1977 1979 lg81 19B3 1~6 19~ 198B 1991 1 ~ 1 ~

Figure l Growth rate of overseas tourism revenues (1995 £): 1969-1995

120

revenues from overseas tourists in real terms between 1969 and 1996.

The level of cyclical volatility experienced throughout the 1970s and the early 1980s was quite high, as most of the markets were experiencing turbulent economic conditions. Ireland's unfavorable inflation rate in conjunction with political unrest in Northern Ireland may also have contributed to this volatility. From 1986 onwards the underlying trend has been in an upward direction, but there have been some large fluctuations. The largest of these fluctuations occurred in 1992 when economic stagnation in most markets caused tourism revenues to fall by 11% between 1990 and 1992. The aim of the policy makers and strategists within the industry should be to minimize these fluctuations in demand while at the same time seeking to attain their desired growth rate.

Portfolio analysis Given the level of cyclical volatility displayed by Irish overseas markets, an attempt must be made to smoothen out the growth path. In order to begin to minimize these variations it is necessary to look at the components of these overseas markets and analyse their individual effects, in terms of volatility and returns.

The mean variance approach is an ideal tool for solving the type of problem outlined above". Given the variance and the expected returns of individual securities, one can predict the variance and expected return of a portfolio, based upon the characteristics of the securities that go into it. This requires the assumption that the rate of return on any security is a random variable, which can be described by its mean and variance, and also that the variance is a good measure of the security's risk. In order to apply this methodology to Irish tourism markets, the total overseas tourism market can be broken into seven individual markets or 'securities', which will allow an examination of their separate effects on the total overseas market. Because of data problems only the following individual markets can be observed: Britain, North America, France, Germany, Holland, Rest of Europe and Other Overseas.

The expected return and variance of any portfolio formed with a combination of the above markets will depend on the expected return and variance of each market contained in the portfolio. Clearly, the weight taken by each security within the portfolio will also be an important factor in determining the overall performance. This can be seen in expression eqn (1), which is used to calculate the expected return of a portfolio consisting of N securities:

L,,,,= xA (1) i = 1

Risk management in the Irish tourism indusm': V Kennedy

Where: R ...... is the expected return of the portfolio; X, is the proportion of the portfolio's initial value invested in security i; R, is the expected return on security i; and N is the number of securities in the portfolio. Similarly, the variance of the portfolio is dependent on the variance and covariance of its components, plus the relative weights of the assets in the portfolio. The interesting factor here is that diversification can benefit the investor by spreading risk over several assets. For example, the variance of a portfolio comprising of two securities will have the following format.

o~-,,,,,, = X~-,a2,+X22aL_+2X,X~_a,~_ (2)

Where the variances of the two securities are given as a 2, and o2_~, and their covariance is denoted by o , . The respective weights of the two securities within the portfolio are X, and X2, where 0_<X, and 0 <X, and X,+X: = 1. As long as the covariance between security 1 and security 2 is less than 1, then the variance of the portfolio will be less than the weighted sum of the individual assets. If we examine the case of uncorrelated returns, where ale = 0, we can clearly see how portfolio diversification reduces risk. In such a situation the variance of the portfolio would be:

o2,,,,,, = X2,a~-,+X~2o~_ (3)

As X, and X2 are between 0 and 1, then X,: <X~ and X / < X , , and therefore the variance of the portfolio has to be less than the weighted sum of the variances of the individual assets. Under these circumstances proper diversification can reduce the risk of a portfolio containing multiple assets below that of the risk associated with only one of its constituent assets--the lowest risk security. This will only occur where the covariance of the assets is less than 1, which causes the third term in eqn (2) to fall; obviously if the returns are negatively correlated the benefits from diversification are even greater, with the ideal situation arising from perfectly negative correlation causing the portfolio variance to fall to zero. In reality, we would expect the returns on most assets--be they securities or tourists' returns--to be positively correlated, as all markets will be affected, to some degree, by general economic conditions. This should give a positive covariance, whose strength depends on the sensi- tivity of individual assets to changes in market conditions. This portion of risk which investors cannot diversify away is known as systematic risk, as it is dependent on general market conditions which will affect all returns. The risk that can be elimi- nated by the diversification process outlined previously is specific to the individual security, and is known as non-systematic risk.

The problem now facing the investor is to deter- mine all possible efficient portfolios that can be formed from the available securities. An efficient portfolio will offer the maximum expected return for

121

Risk management in the Irish tourism industry." V Kennedy

varying levels of risk, and offer minimum risk for varying levels of expected return'L In order to achieve this, the expected return and variance of each security must be estimated, and furthermore the pairwise covariance between securities must be derived. When the expected returns vector and the variance-covariance matrix have been calculated the problem is reduced to the optimization of a quadratic function subject to linear constraints'". The variance and expected returns the of individual efficient portfolios can be calculated using the following model:

Minimize: ~2 X2,a2,+ ~, ~ X,Xia. (4) i = 1 i - I ] = 1

Subject to: (I) Z X, = 1, (2) X,R, = R,,,,,., i = l i = 1

(3) Xi>_ O, i= 1 .... . N

By varying R,,,,,, the algorithm will identify the composition of a range of portfolios, from the one with the highest expected return, to the minimum variance portfolio. This allows the investor to choose the level of risk and expected return that are compatible with his or her preferences.

Risk management in Irish tourism

If we arc to employ this methodology to help us to determine the optimum mix of nationalities from our overseas tourist markets, there are certain simplifying assumptions that need to be made. Drawing the analogy to the tourism industry, the 'investor' could be seen as the policy maker with responsibility for the long term growth strategy of the industry. The expected return on the portfolio in this case would be the target growth rate of revenues from our overseas markets. However, the ability to change the market mix (portfolio composi- tion) would be dependent on our ability to influence the demand for our product through the use of our marketing budget, which would be analogous to the funds available to the investor at the beginning of the decision period. Obviously the opportunity to change the composition of a portfolio of securities is facilitated by immediate access to the financial markets, allowing the composition or weights of any portfolio to be changed almost instantly. The ability to change the market mix of tourists arriving in the country would be subject to a time lag, as it would take some time to redirect marketing funds and for the effects of these programmes to work. The appli- cation of portfolio investment analysis to tourism markets also greatly simplifies the investment choice, as there is a wide range of investment instru- ments available in the financial markets, allowing investors to chose securities from similar and competing categories. As a result of these

constraints, portfolio analysis would not be as precise a tool when applied to the tourism industry. However, an important point to note, is that the fundamental differences in the workings of these two systems does not affect the extent to which proper diversification might reduce the level of non-systematic risk. Therefore the style of analysis suggested here may help policy makers to make the role of risk management more explicit in the planning process.

Portfolio estimation

In order to apply the portfolio selection methodo- logy to Irish overseas tourism markets and test the composition of various efficient portfolios, the total overseas tourist market was broken into seven sub-markets: Britain, North America, France, Germany, Holland, Rest of Europe and Other Overseas (see Appendix A). The revenues from these markets were expressed in 1995 Irish pounds and their growth rates were calculated between 1969 and 1995. The expected return vector and variance- covariance matrix were estimated and the quadratic programming algorithm was applied using a special- ized software package, Invest. The graph in Figure 2 shows the minimum variance frontier. Each of the portfolios on the minimum variance frontier has the lowest standard deviation achievable with the avail- able population of markets, for a specified level of expected return. The minimum variance portfolio (MVP) would represent the least risky portfolio attainable with the available population of markets. The portfolio with the highest expected return (HER) is composed of just one market, which in this case is the Rest of Europe. It is clear from the minimum variance frontier that there is considerable scope for the reduction of non-systematic risk, as there is a whole range of portfolios--up to portfolio 7--which offer a lower standard deviation and higher expected growth rates than the lowest risk market, North America.

There are an infinite number of portfolios between the MVP and the portfolio with the highest expected return. The composition of various efficient portfolios corresponding to different levels of risk are reported in Table 1.

16

1 2 -

"-a!

:t

ro0: . . . . . . .

• Get•Get• FrF * O.Ov~t3el

~'s ZI5 30 o ~o 4s 20 s.o

Figure2 The minimum variance frontier

122

Risk management in the Irish tourism industry: V Kennedy

Table 1 Portfolio composition

Portfolio MVP 2 3 4 5 6 7 8 9 HER

Expected Growth ( ~ ) 3.8 5.0 6.0 7.0 8.0 9.0 10.0 12.0 13.0 14.5

Standard Deviation 8.1 8.4 8.9 9.7 10.6 11.6 12.0 15.6 17.5 22.4

Britain 36.4 32.0 29.3 26.1 23.2 20.3 t 7.3 00.0 00.0 00.0 North America 48.5 39.6 31.7 24.4 16.9 9.3 01.8 00.0 00,0 00.0 France (/11.11 111.5 04.3 07.0 09.8 12.6 15.4 18.1 10.7 00.0 Germany 01.0 (16.9 119.9 13.0 16.(/ 19.0 22.1 19.5 01.4 00.0 Holland 14.1 14.4 14.0 13.4 12.6 12.0 11.6 15.5 19.0 0(I.0 Rest of Europe 00.11 02.6 116. I 09.7 13.2 16.8 211.5 30.6 50.1 100.0 Other Overseas 00.0 113.0 04.7 (/6.4 (/8.3 10.0 t 1.9 16.3 18.8 00.0

The minimum variance portfolio, which offers a standard deviation of 8.1 and an expected return of 3.8%, is composed mainly of Britain and North America. These two markets account for 84.9% of this portfolio, while Holland makes up the majority of the remainder (14.1%), with Germany accounting for only 1.0%. Interestingly, it is North America which takes the largest weight (it has the lowest variance of the seven markets), and which therefore takes a position of prominence in the lower risk portfolios. Although, it must also be remembered that the covariance between the markets is also an important determinant of a country's weight within the portfolio. From the covariance matrix in Table 2 we can see that the American market exhibits a relatively low covariance with all other markets, and even has a negative covariance with Holland.

The British market carries slightly more risk and so takes a lower weight in the less risky portfolios. One would expect the closeness of the British market, and the strong ethnic ties, to have made this market the most stable. However, some very strong recessions, combined with escalating violence in Northern Ireland, which also extended to Britain itself, may account for the slightly higher variance. Britain also exhibits the kind of covariance which would make it an important component in any portfolio seeking to diversify risk. These two markets combined are clearly the most important for a stable, moderate growth rate, as they take the largest weights in all portfolios up to an 8.0% expected return. Thereafter they tend towards zero,

suggesting that these markets would not be part of a portfolio that seeks to attain high levels of growth.

An interesting feature of the minimum variance portfolio is the fact that three of the component markets take zero weight in this portfolio. While this is a necessary condition for the minimum variance portfolio, it is a result that should be interpreted quite carefully in the tourism context. It would obviously be unrealistic for policy makers to totally exclude tourists from these markets in order to minimize the risk associated with these countries. Given that we have discussed the ability to influence the composition of a portfolio, as a function of our marketing strategy, we could interpret these weights as indications of the direction in which marketing funds should be allocated. In the case of the MVP, an intensive marketing campaign could be carried out in Britain, North America and Holland, while decreasing, or holding constant, efforts in the other markets. It is important to note that although the kind of distribution suggested in the MVP may be impossible to attain in reality, it does help to define the type, and the importance, of a strategy that would lower the fluctuations in demand within the industry. If the targets suggested by the above analysis can help focus the minds of the policy makers, then the industry can only benefit and the portfolio model is useful.

The Rest of Europe market has the highest expected return at 14.5%, and is therefore the only market contained in the H E R portfolio. This portfolio would be chosen by a policy maker with a

Table 2 The expected returns and variance-covariance matrix of the tourist markets

Britain North America France Germany Holland Rest Other

E.(R)% 2.0 1.7 10.4 9.8 12.6 14.5 11.1

Britain 1 9 9 . 2 . . . . . . North America 3.8 1 6 3 . 0 . . . . . France 69.2 43.8 5 3 4 . 6 . . . . Germany 27.5 48.5 145.5 275.3 - - - Holland 40.1 - 106.8 245.0 170.6 681.9 - - Rest of Europe - 6.(/ 46.7 274.2 239.6 281.0 507.6 -

Other Overseas 46.5 116.7 235.2 124.6 22.9 170.5 676.1

123

Risk management in the Irish tourism industry: V Kennedy

strong preference for risk (the standard deviation is 22.4). Unfortunately, due to data restrictions, a further breakdown of this market is not possible. It would be interesting to see the separate effects of Spain, Italy, Benelux, Switzerland, Denmark, Norway and Sweden in the composition of high expected returns portfolios. All that can be said from this analysis is that some combination of these markets would give a high rate of growth, but they will also subject the industry to a considerable level of risk.

The composition of various portfolios on the minimum variance frontier has also been included in Table 1 to highlight the changing weights taken by the individual markets as we move along the frontier. In general, it gives us an idea of the type of structural change that needs to occur in the compo- sition of our overseas market as we aim to achieve higher growth rates. The model suggests that the engine of this growth will come from European markets, and from the Rest of Europe category in particular. This correlates closely to the type of change that has occurred in the Irish industry since 1987. Strong growth from previously sluggish markets can only be welcomed, however the purpose of this paper is to examine the management of this growth so as to avoid an over reliance on potentially volatile markets.

Industry performance and current targets The Operational Programme for Tourism 1994- 1999 2,, has set targets of £2.25 billion a year in foreign exchange revenues by 1999, an extra 35 000 full-time job equivalents, including: 17250 in direct tourism; 6000 in construction and associated capital works; while the balance of 11 750 will be created by indirect and induced employment. The finance for this programme is outlined in the Operational Programme, which was approved by the European Union. There is a planned investment of £652 million over the course of the programme, which will combine funds from the European Social Fund, the European Regional Development Fund and the public and private sectors. This programme also aims to tackle the seasonality profile of our overseas tourists, so that two-thirds of visitors, rather than the 50% at present, will come outside the peak summer season. The marketing sector of the industry is to receive an extra £130 million in order to achieve the revenue target and the seasonality

objective. In order to meet the new demands of the industry, and, presumably, to achieve the targets outlined in the Operational Programme, Bord Failte, the organisation responsible for the develop- ment, marketing and planning of Irish tourism, had its structure and responsibilities changed signifi- cantly in 1995. Bord Failte's new role is to aggres- sively market Irish tourism world-wide, with many of its previous functions being transferred to outside sources.

In order to meet the target foreign exchange figure set out in the Operational Programme, foreign exchange revenues will need to grow at a rate of 8.5% per annum between 1994 and 1999. It is helpful to have these targets denominated in monetary terms rather than actual tourist numbers, as presumably this target could be met with different market mixes which would not necessarily mean more tourists visiting the country. In light of the present focus on risk management, it is also useful to have such a growth target available as it will allow us to estimate an efficient portfolio and examine the risk factor associated with this growth rate. The composition of the minimum variance portfolio associated with an expected return of 8.5% is reported in Table 3. In order to obtain the composi- tion of a target portfolio, a fourth constraint must be added to eqn (4):

~ Xidi > D, i - I

where D is the target rate of return and d, stands for the yield on market i.

An efficient portfolio with an expected rate of return of 8.5% contains a standard deviation of 11.2, providing that individual markets take the weights outlined in Table 3. While the distribution appears even across the markets, the total European sector accounts for 56.1% of the portfolio which is consid- erably higher than Europe's actual share of the overseas tourism revenues in 1995 at 32.2%. In 1995, the British and North American markets accounted for 60.3% of overseas revenues from tourism, which is far greater than the combined weight suggested in Table 3, of 34.8%. The Other Overseas sector, comprising mostly Australia, New Zealand and Japan--with South and Central America, Asia and Africa also included--takes a value of 9.2% in the minimum variance portfolio which is close to its weight in the actual 1995 portfolio of 7.5%.

Table 3 Minimum variance portfolio for an 8.5% target growth rate

Britain North America France Germany Holland Rest of Europe Other overseas

Growth target 8.5% 21.7 13.1 11.1 17.5 12.3 15.1 9.2 Standard deviation 11.2

124

While the composition of the efficient portfolio in Table 3 gives the minimum variance for an 8.5% expected return, it is important to note that there are a whole range of portfolios which offer less risk, albeit for lower rate of returns. Under current industry targets the signals to the investor or policy maker in this instance, are clear: in order to achieve and maintain growth rates of 8.5% there needs to be a large shift towards the Mainland European customer. The growth rates experienced within the industry over the last number of years would suggest that this structural change is already underway. For example, North American tourists exceeded those from Europe in each year up to 1988, during which time they averaged 350000 visitors annually -'~. The dramatic upsurge in European tourists in the late 1980s resulted in 900000 visitors from this market in 1992, more than double that from the USA and Canada. Most of the increases came from the Italian, Spanish, German, French and Dutch markets, which is in line with the type of change suggested by the portfolio selection model employed in this paper.

Conclusion The application of the portfolio selection methodo- logy to the tourism industry is a fruitful exercise, despite the fundamental differences in the way in which securities markets and tourism markets work. The portfolio investment approach provides some tentative answers to the issue of diversification, and will hopefully serve to make the issue of risk management more explicit in the planning process. While the lack of detailed revenue data for all markets prohibits the estimation of a more informa- tive portfolio, the methodology has not been put forward not as a precise tool, but rather as an aid to tourism policy makers, allowing them to focus on the factors which affect the stability of the industry. Proper consideration of these issues should lead to stable revenue growth, ensuring lasting employment, and the maintenance of the confidence and invest- ment from the private sector. It would be in the long term interest of the industry to place more weight on stable markets rather than achieving short term gains at the expense of stability.

There are further issues that tie directly into this objective; most importantly, the specified seasonality target outlined in the Operational Programme. Tourists from the British and North American markets, which exhibit the lowest variance in returns, are also the most evenly spread throughout the year, while 40% of European tourists arrive in July and August. The stability of demand for our tourism product is, of course, a broader issue than the portfolio selection problem: the importance of sustaining quality and reputation 22, and the damage which can be caused by mass tourism, especially at

Risk management in the Irish tourism indusm': V Kennedy

peak season, are also long-run factors that need serious consideration from policy makers.

Portfolio analysis provides a useful additional concept for planners and policy makers within the tourism sector. The methodology employs the use of portfolio investment techniques to estimate the optimal distribution of nationalities for various growth paths. This aspect of the industry's strategy should not be overlooked as the desire to achieve a short term revenue target may lead to the over- development of volatile markets. As tourism gains a position of importance in the economy, the industry must plan for its long-term maintenance and consol- idation. The style of analysis being suggested in this paper should encourage policy makers to select a portfolio of markets which matches the expansion path they desire. They can then achieve this path with the policy instruments and resources available to them.

Acknowledgements The author would like to thank Dr Michael Keane, Department of Economics, University College Galway, for his assistance and insightful comments on earlier drafts of this work.

References 1. Mathieson, A. and Wall, G. Tourism; Economic, Physical and

Social Impacts Longman Social and Scientific, London, 1993. 2. Wilkinson, P. F., Strategies for tourism in island microstates.

Annals ~f Tourism Research 1989, la(2), 153-178. 3. Board, J., Sinclair, T. and Sutcliffe, C., A portfolio approach

to regional tourism. Built Environment 1985, 13(2), 124-137. 4. Deaton, A. S. and Muellbaur, J., An almost ideal demand

system. American Economic Review 1980, 70(3), 312-326. 5. White, K. J., An international travel and demand model: US

travel to Western Europe. Annals of Tourism Research 1985, 13(3), 349-365.

6. Crouch, G., Effect of income and price on international travel. Annals of Tourism Research 1992, 19, 643-664.

7. Sharpe, W. F. and Gordon, J. A. Investments Prentice Hall International (UK) Limited, London, 1990.

8. Op cit ref 3. 9. Stationery Office Operational Programme J'or Tourism

1994-1999 Government Publications, Dublin, 1994. 10. Stationery Office Operational Programme ]'or Tourism

1989-1993 Dept of Tourism and Trade, Dublin, 1989. 11. Theobald, W. F. Global Tourism the Next Decade Butter-

worth-Heinemann, London, 1994. 12. The Economist March 4 1995, 334 (7904) 43. 13. Tansey Webster and Associates The Economic Effect of

Tourism in Ireland: A Study of the Economic Impact of Tourism in Ireland 1989-1993 Irish Tourism Industry Confederation, Dublin, 1995.

14. Bord Failte The Failte Business: Tourism's Role in Economic Growth Bord Failte, Dublin, 1996.

15. Dearie, B. and Hendry, F. 'The Economic Impact of Tourism' Irish Banking Review Winter 1993, 35-47.

16. Economic and Social Research Institute Medium Term Review 1994-2000 ESRI, Dublin, 1994.

17. Elton, J. E. and Gruber, M. J. Modern Portfolio Theory and Investment Analysis John Wiley. New York, 1995.

18. Op cit ref7.

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Risk management in the Irish tourism industry: V Kennedy

19. Op cit ref 17. 20. Op cit ref 9. 21. Dineen, D. 'Tourism policy and performance in Ireland:

Long-term strategy or short-term opportunism?', in Convery, F. and Flanagan, S. (eds) Investing for Tourism in Ireland Environmental Institute, University College Dublin, 1994.

22. Keane, M. J., Sustain.ing quality in tourism destinations: An economic model wi~" an application. Applied Economics 1996, 28, 1545-1553.

Received May 1997 Accepted July 1997

Appendix A: Overseas tourist revenues and numbers to Ireland, 1968-1995

Year Britain N. America France Germany Holland Rest of Europe Other overseas Total overseas

1968 1 115 (32.5) 216 (15.5) 22 (1.01 29 (1.3) 6 (0.3) 19 (0.8) 20 (1.1) 1427 (52.11 1969 1 125 (33.6) 267 (19.3) 32 (1.5) 36 (1.7) 9 (0.4) 27 (1.3) 26 (1.5) 1522 (59.3) 1970 1061 (32.9) 258 (19.6) 31 (1.6) 41 (2.0) l l (0.6) 27 (1.3) 30 (1.9) 1459 (59.9) 1971 947 (31.3) 279 (24.4) 35 (2.1) 52 (3.1) 14 (0.8) 34 (2.0) 36 (2.7) 1397 (66.4) 1972 750 (25.1) 259 (23.5) 28 (1.8) 50 (3.1) 15 (0.9) 34 (2.2) 28 (2.2) 1 164 (58.8) 1973 845 (34.9) 261 (25.6) 34 (2.1) 53 (3.7) 20 (1.0) 41 (I.71 30 (1.6) 1284 (70.6) 1974 820 (39.7) 252 (31.4) 37 (2.4) 60 (5.4) 25 (1.7) 43 (3.1) 28 (1.61 1265 (85.3) 1975 817 (45.5) 256 (34.4) 43 (3.9) 64 (5.8) 28 (2.4) 53 (3.9) 28 (2.2) 1 289 (98.1) 1976 797 (47.5) 266 (41.7) 51 (4.7) 67 (7.9) 30 (2.7) 59 (6.2) 27 (3.2) 1 297 (113.9) 1977 864 (58.0) 297 (51.61 66 (7.3) 77 (10.9) 37 (3.9) 72 (8.8) 55 (7.2) 1468 (148.5) 1978 1055 (79.0) 309 (52.7) 84 (9.4) 94 (12.8) 43 (5.1) 99 (10.7) 71 (8.0) 1 755 (177.71 1979 1077 (95.4) 293 (57.8) 94 (12.31 102 (17.2) 47 (6.5) 115 (16.3) 66 (11.9) 1 794 (217.4) 1980 1068 (113.8) 260 (50.9) 85 (12.81 95 (17.3) 43 (6.7) 113 (18.7) 67 (13.5) 1731 (233.7) 1981 1008 (110.5) 278 (68.4) 92 (14.81 90 (17.2) 39 (6.7) 81 (16.7) 75 (17.2) 1680 (251.5) 1982 1031 (123.4) 315 (97.3) 93 (17.6) 86 (18.8) 38 (8.0) 78 (19.8) 60 (16.5) 1719 (301.4) 1983 1049 (128.4) 31(1 (125.4) 81 (14.7) 92 (21.7) 29 (5.0) 73 (20.6) 60 (19.5) 1714 (335.3) 1984 1021 (161.2) 334 (134.0) 83 (15.1) 93 (23.5) 33 (7.0) 80 (25.5) 63 (17.9) 1903 (348.2) 1985 1 123 (173.0) 423 (176.6) 96 (20.9) 99 (25.9) 33 (7.3) 92 (31.6) 69 (23.7) 1951 (459.0) 1986 1 130 (185.8) 343 (14(I.3) 89 (17.2) 100 (25.7) 33 (10.4) 115 (34.9) 71 (22.2) 1881 (436.5) 1987 1236 (213.6) 398 (158.5) 113 (23.1) 103 (33.8) 40 (8.1) 134 (40.6) 74 (26.6) 2098 (504.3) 1988 1508 (267.0) 419 (165.5) 111 (31.0) 113 (35.9) 38 (9.1) 146 (47.7) 90 (37.6) 2425 (593.8) 1989 1716 (305.5) 427 (177.41 138 (36.7) 154 (45.3) 46 (10.71 209 (67.1) 114 (44.7) 2804 (687.4) 1990 1785 (333.0) 443 (166.4) 198 (68.2) 178 (56.5) 72 (19.8) 296 (104.7) 124 (47.2) 3096 (795.8) 1991 1746 (348.6) 356 (153.5) 220 (72.3) 203 (82.7) 83 (32.3) 335 (117.6) 108 (49.7) 305t (856.8) 1992 1765 (341.1) 417 (156.0) 220 (82.0) 230 (88.1) 73 (27.1) 351 (128.9) 118 (46.2) 3 174 (869.5) 1993 1857 (375.1) 422 (182.1) 242 (88.3) 265 (114.0) 69 (29.3) 369 (176.0) 124 (54.7) 3348 (1013.5) 1994 2038 (451.9) 494 (213.4) 231 (74.4) 269 (110.4) 80 (30.0) 408 (156.8) 159 (77.2) 3679 (1 114.1) 1995 2285 (501.2) 641 (275.0) 234 (83.8) 319 (122.4) 94 (35.5) 455 (172.7) 204 (96.5) 4231 (1286.4)

Numbers of tourists are given in thousands. The numbers in brackets are the revenues in £m. Source: Bord Failte, Tourist Numbers and Revenues, Various Years. Bord Failte: Dublin.

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