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The future of leisure
The future of leisure A. J. Veal
The author reviews a range of mainly British and US research on future leisure behaviour and in particular: general scenarios, forecasts of the amount of leisure time, activities, and expenditure. He discusses the limitations of one of the most widely used approaches - cross-sectional analysis. He notes some of the problems facing policy makers: there has been an overconcentration on sporting and outdoor activities, and the distributive effects of their policies have been largely ignored, eg leisure facilities meet the needs of the better-off sections of the population. A.J. Veal is at the Centre for Urban and Regional Studies, University of Birmingham, PO Box 363, Birmingham B15 ZTT, UK. This article is based on research financed by the UK Social Science Research Council.
Most writings about the future of Western society have either ignored the phenomenon of leisure, or treated it very much as a residual. Yet in highly productive economies, leisure can be seen as a key element in the economic equation. Although many of the consumer goods which have appeared on the scene during the twentieth century have been designed to save time, many - and television is the prime example - require time to enjoy. It has been estimated that in the 20th century approximately 80% of the fruits of increased productivity have been taken in the form of additional income and 20% in the form of reduced working hours.’ In the postwar era reduced working hours in most of the Western world have been taken in the form of rapidly increasing holidays while the working week has stayed resolutely at around 40 hours since the 19.50s. However, it is not necessarily easy to achieve a balance between the desire for additional material goods and services and the desire for increased free time in which to enjoy them. Linder has noted that modern man is compressing more and more activity into the by, and to some extent the same amount of time,* surrounded captive of, more and more consumer goods. He diagnoses a developing “time famine” and refers to the busy, well-off members of economically advanced societies as “the harried leisure class”. America, has also noted this De Grazia, writing of modern phenomenon: An age that breeds technology must be one that is beguiled by and desirous of material things and therefore must buy or somehow acquire them, to do which it must use up the time any one machine or device may save. Any primitive tribe enjoys more free time than a resident of the United States today. It is doubtful that any civilisation ever had as little free time as we do. The commodity mentality, fascinated by the made and purchasable thing, holds the American worker in a vice of working overtime to buy time-saving devices and ‘leisure goods’.3
1. Kenneth Society
Roberts, Contemporary
and the Growth
of Leisure
(London, Longmans, 1978), page 15. 2. Stefan Linder, The Harried Leisure Class (New York, Columbia University Press, 1970). 3. S. De Grazia, “The problems and promise of leisure”, in W.R. Ewald, ed, Environment and Policy: The Next Fifty Years (Bloomington, University of Indiana Press, 1968), pages 112-133.
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Researchers into leisure have, at least since the early 196Os, been interested in forecasting leisure behaviour. Their efforts to date, however, have been largely technical demand-forecasting exercises which generally fail to consider the wider issues of the role of leisure in society. I would like to review here the range of approaches which have been attempted, the sorts of findings they have produced and their limitations. The Delphi technique is familiar to forecasters as a means by which opinions about future events are gathered from panels of experts. In successive rounds of questioning respondents are infor-
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The future
of leisure
med about the results of previous rounds (usually in the form of average probability scores) so that they have the opportunity to adjust their own views in the light of information about other respondent’s views. The only substantial known use of this technique in the leisure area was by Shafer et al, 4 using a panel of 405 American experts, mainly involved in natural resources management. Examples of predictions which resulted were:
4. E.L. Shafer, G.H. Moeller, and R.E. Gethv. “Future leisure environments”. Ekis&s, July 1975, 40 (236), pages ’ 68-72. 5. In the UK the GPO’s ‘Prestel’ system already includes information on sports and holidays supplied by the Sports Council and the English Tourish Board. 6. Ian Miles. Sam Cole. and Jay Gershuny, “Images of the future”, in Cbristooher Freeman and Marie Jahoda; eds, World Futures: The Great Debate (London, Martin Robertson, 1987), pages 279-342. See also “Scenarios of world development”, Futures, February 1978, 1 O( 1). pages 3-21.
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Use of computers to advise people where to go for recreation (by 1980).’ Most people work a 4-day, 32-hour week (by 1985). Year-round skiing on artificial surfaces. Remote sensing devices used to monitor national-park use; waste-disposing bacteria incorporated into recreation average retirement age 50 years; ‘weekends’ equipment; distributed throughout the week; leisure is an accepted lifestyle (all by the year 2000). Man-made islands created solely for recreation (by 2000). Most middle-income families own their own vacation homes (by 2030). Self-contained underwater resorts; first park established on the moon; average worker has 3 months annual vacation; 20% of the available workforce used to produce goods and services for the entire population (sometime after 2050). Miles et al produce outlines of 12 different possible futures by taking three ‘worldviews’, each analysed according to four ‘profiles’.6 The ‘worldviews’ are: conservative, reformist, and radical; and the ‘profiles’ are: high growth/more equal, high growth/inegalitarian, low growth/inegalitarian, and low growth/more equal. This framework of analysis is applied to 17 areas of human activity or concern, one of which is leisure. Each scenario is viewed from the point of view of rich and poor countries. The aim and result of this exercise is not to come to conclusions about which future scenario is the more likely but to explore the possible consequences of different sets of assumptions. Thus the possible leisure futures which they discuss include an increasingly packaged and marketed leisure age, contrasted with one which concerns itself more with education and activities ‘orientated to improving mind and body’; increasing reliance on passive spectator entertainments possibly involving more institutionalised violence; and stimulation-seeking and compensatory leisure.
The amount of leisure time In leisure research it is important to remember that empirical work has only been carried out on any scale since the early 1960s starting with the massive investigation conducted by the US Outdoor Recreation Resources Review Commission. A great deal of research output has as a result been descriptive, the aim being simply to discover what people do with their leisure time, which activities are popular, and which less popular. This is particularly true of an area which has come to be known as time-budget research. Time-budget research is based on ‘diaries’ kept by a sample of individuals over a specified period - usually a few days. The BBC’s
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March 1980
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The future of leisure
audience research surveys’ and a cross-national, six-nation timebudget study directed by &alai8 are the main examples of this work: both are essentially descriptive and fail to use the enormous quantities of data collected for forecasting purposes. Holman’ produced a national time budget for the year 2000 for the USA based on predicted changes in the distribution of the time of individuals and the growth of the population. Making some rather heroic assumptions - for instance that the working week will fall to 28 hours by the year 2000 - she suggested that the total amount of ‘discretionary’ time available would rise from 450 thousand million hours per annum (3000 hours per head of population) in 1950 to 1100 thousand million hours (3400 hours per head) in the year 2000. This work seems to have been an isolated exercise which has not been repeated for other countries, and has not been updated as population predictions and assumptions about economic growth have changed. A more recent example of thinking in this area has been the work of Best”. He is concerned that the current ‘linear life plan’, involving a sequence of youth/education, adulthood/work and oldage/retirement phases, is not flexible enough to cope with the demands of the future. He shows that if all growth in productivity between the years 1975 and 2000 (at 4% per annum) were to be taken in the form of reductions in working hours rather than increased production, annual working hours could fall from 1900 hours to 970 hours. The possible implications for leisure time would be either: a 0 0 0
7. British Broadcasting
The People’s Activities
Corporation, (London,
BBC. 1965 and 1979). 8. A. Szalai, The Use of Time (The Hague. Mouton. 1972) 9. M.A. Holmai, “A national timebudget for the year 2000”. Socioloav andSocial Research, October 196 ly46(l). IO. F. Best, “The time of our lives: the parameters of lifetime distribution of education, work and leisure”, Society and Leisure, April 1978. IO(l), pages 95-124. 11. E. Lippold, “The utilisation of time-budget data for planning”, Society and Leisure, 1973,5 (I), pages 17-30.
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a 20-hour working week, or 27 weeks of annual paid holidays, or a 39-month paid sabbatical every 7 years, or retirement at age 39.
In fact Best suggests that US workers are likely to take only about 25% of the projected growth in the form of free time. Nevertheless work patterns might be varied at different stages of the life-cycle to suit individual circumstances. Thus people with children might wish to have shorter working weeks but forego longer holidays and sabbaticals, whereas those without children might be happy to work a longer week and take their free time in larger blocks. Sabbaticals would facilitate education and retraining during adult life. The result might be a movement towards a ‘cyclical’ rather than ‘linear’ life plan. In the socialist countries of the Eastern block a great deal of research on time budgets has been conducted: conscious decisions about the extent of the workers’ free time and acceptable use of it is an aspect of economic and social planning. An East German study shows how the planned increase in the proportion of professionally qualified workers will lead to increases in leisure because of differencesinlifestyle between manual and nonmanual workers,” and relates investment in the production of convenience foods and the labour time involved in their production, to the aggregate time savings of the consumer. There have been no time-budget-based studies recent enough to have been able to take account of the recent advances in technology which have awakened public interest in the problems of jobs, work time, and leisure. Jenkins and Sherman’s study The Collapse of International
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of Tourism
Management
March 1980
T77efuture of leisure
Work,‘* for instance, stops short of any detailed analysis of the leisure implications of the reduced working time which they foresee.
Forecasting leisure expenditure A considerable amount Britain has been carried quantitative forecasts it tions about underlying study Martin and Mason
of work on future leisure expenditure in out by Martin and Mason. To make any is necessary to make some firm assumpsocial and economic trends. For their assume that there will be: l3
a declining child population, an increasing proportion of women working, growing pressure for better housing and environmental conditions, more flexibility in working arrangements, a tendency still to take the bulk of the potential rise in standard of living in the form of higher incomes rather than free time, more self-employment, part-time working, and optigg out, some reduction in working hours - about 250 hours reduction by 199 1, taken in the form of Friday afternoon off, plus 8 or so extra days holiday, annual economic growth of 3-3.5%, 4.5% annual growth in leisure spending (90% growth between 1976 and 1991), and a preference for social activities outside the family, local community related activities, leisure at home, activities associated with the car, jobs and part-time work.
12. C. Jenkins and B. Sherman, The Collapse of Work (London, Eyre and Methuen, 1979). 13. W.H. Martin and S. Mason, The Prospects for Leisure: The Next Five Years and Beyond (London, Leisure Consultants, 1975). 14. I. Koltai, “Development and longterm forecast of leisure time expenditure in Hungary”, Society and Leisure. 1972. 4 (4), pages 91-109.
International
educational
activities,
and
second
They see total leisure spending in Britain increasing from 27.6 thousand million in 1977 to 210.2 thousand million in 1982 (at 1970 prices, multiply by approximately 2.9 to convert to 1979 prices). This is a rise from 20 to 22% of total consumer expenditure. In fact ‘leisure spending’ is very difficult to identify from UK official sources - mainly the annual family expenditure survey. Table 1, which shows the distribution of leisure expenditures in 1977 and the 1982 predictions, illustrates why. Many of the categories, such as books, alcoholic drink, and eating out, include nonleisure elements. In addition travel and much leisure clothing is excluded. Despite these limitations the data is clearly of some interest. The main feature is perhaps the dominance of alcoholic drink. Secondly it might be noted that the only significant change in relative magnitude over the 5-year period is the increase of 3% in the holidays element. Koltai14 has described research on the projected growth in leisure-related expenditure in Hungary. A fourfold increase was envisaged between 1967 and the mid 198Os, distributed as shown in Table 2. It is possible to detect some similarities between the Hungarian and British pattern, despite the differing lists of categories of expenditure. Most notable is that both see a more than average increase in tourism/holidays. The British model assumes consumerled growth whereas the Hungarian model assumes some control
Journal of Tourism Management
March 1980
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The future of leisure Table
1. Distribution
of the leisure pound
Leisure spending devoted
Books, newspapers, TV,
to
magazines
radio, audio
Do it yourself Hobbies
and gardening
and pastimes
Alcoholic
drink
1977
1982
(%I
(%I
7.7 10.2
6.9 9.8
8.4
8.1
7.3
5.9
39.5
39.9
Eating out
5.9
6.1
Gambling
4.3
3.8
Entertainment
2.2
1.9
Sport
3.0
3.2
11.5
14.4
and recreation
Holidays
Source:
Martin and Mason, 1977.13
over the consumer by the state through availability of consumer goods, thus:
its control
over
the
The individual choice by consumers of the utilization of leisure time can be influenced by large and differentiated supplies which correspond to society’s goals.
“society’s
Among
goals” is the principle
socially dangerous consequences side-effects should be prevented.
of increased
Hence perhaps, the failure to mention in the table of expenditure at all.
Cross-sectional
that: leisure time and undesirable
the consumption
of alcohol
analysis of activities
This is perhaps the most firmly established forecasting technique in this area. It identifies those social characteristics which appear to relate to variations in levels of leisure participation among Table
1967
2. Leisure-related
-mid
expenditure
1980s
in Hungary
Average
Distribution
annual
1967
(%) mid 1980s
increase (%I Cars, motorcycles Television/telephone Books,
periodicals,
and weekend
Social life, entertainment
tourism
Musical
instruments,
37
17
12
5
14
7
13
8
14
8
22
19
9
3
5
3
3 1
(out-of-
doors) Sport and camping
22
7 and cultural
events Recreation
12
goods photography
12
2
4
Gambling
3
9
3
Total
9
100
Hobbies,
Source:
gardening
100
Koltai. 1972. l4
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.March 1980
The future of leisure
15. J.G. Settle, Leisure in the North West: A Tool for Forecasting, Sports Council Study 11 (London, Sports Council. 1977).
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of Tourism
people. This might be achieved using multiple regression or the related technique of discriminant analysis, eg it is often found that level of personal income distinguishes very clearly between those who do and those who do not take part in certain leisure activities: higher-income groups usually take part more than low-income is known, and if the relationship groups. If this relationship between levels of income and distribution of income is known, future levels of leisure participation can be predicted. This approach can of course be followed using other variables, such as age, car ownership, hours of work, family situation, and so on. Multiple-regression techniques allow the relative importance of a number of such factors to be taken into account so that more than one variable can be incorporated in the forecasting equation. This requires forecasts of these independent variables to be produced for the forecast to be carried out. The key assumption in the method is that the relationship between the social variables and leisure participation will remain constant, eg that people who acquire cars in the future who have not previously had a car will behave in a similar way to those who currently have a car. It assumes that the leisure patterns of the elderly of the future will be similar to those of the elderly of today. It assumes that patterns of expenditure of lower-income groups will change as they move into h.igher absolute-income brackets. Of course factors interact, and the model can accommodate this. Thus the elderly may change their behaviour because they have more cars or more income. Two alternative approaches to the detailed development of this model have been used. The fist uses, as the basic unit of analysis, the individual. The individual who participates in a given leisure activity is given a score of 1 and the individual who does not is give a score of 0. Alternatively a score may be given reflecting the number of times the individual has engaged in the activity in the given time period. The independent variables used in the analysis are then that person’s own attributes - his income, age, whether he has a car, etc. The alternative method uses as the unit of analysis groups of individuals with common characteristics. In this case the focus of attention - the dependent variable - is the percentage of people in that group who participate: the independent variables used are the attributes of the group - its average age, average income, etc. Settle argues that the latter method is statistically superior and that the results are easier to interpret.” It is certainly true that in practice any forecasting activity is likely to be related to groups with common characteristics in the community rather than to individuals. A characteristic of research using this approach is that it requires large data sets in order to provide sufficient numbers of individuals in the various age/sex/income/car ownership ‘cells’. This is particularly true when analysing less-popular activities. One of the earliest attempts to use large-scale survey data for prediction purposes was the work of the US Outdoor Recreation Resources Review Commission (ORRRC), already referred to. The National Recreation Survey, conducted in 196 1, involved a sample of 4400 persons over the age of 12 and was confined to outdoor recreation mainly or a rural nature. One ORRRC report states:
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March 1980
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The future of leisure
it was assumed that participation in a given outdoor activity is predictable from the social and economic characteristics of the participant. l6 In an appendix to the report this proposition is explored by Proctor. He first of all classifies 15 outdoor activities, using factor analysis, into four groups: 0 0 l
0
Backwoods group: including camping, fishing, hunting, nature walks, hiking, mountain climbing, and canoeing. Boat culture group: including boating, water-skiing. Country club to picnic ground group: including sailing, swimming, bicycling, riding, outdoor games or sports, picnicking. Passive pursuits group: including driving for pleasure, walking for pleasure, sightseeing, attending outdoor concerts, and attending sporting events.
This technique of grouping activities by means of factor analysis started what almost became an industry. In essence it groups activities by analysing patterns of participation: if people who participate in activity x also tend to participate in activity y then x and y appear in the same group. The supposition is that people of similar socioeconomic or psychological characteristics will be attracted by activities in the same group.” Proctor then produced scores for each individual for each of these activity groups, based on their level of participation in activities in that group (in days per annum) and related these analysis, to some 30 different scores, by multiple-regression independent variables. The variables spanned the usual socioeconomic range including age, sex, income, occupation, and residential location data. The results are complicated and inconclusive : After having applied the elaborate regression computations, it is apparent that the technique is helpful in performing a screening operation on all causal connections leading from independent to dependent variables but falls far short of being very precise concerning the amount of influence.
Intercorrelation between the independent variables is suggested as one explanation for the lack of clarity in the results. It is found that the following variables are the most influential in each group: l l l l
16. Outdoor Recreation Resources Review Commission, Ngtional Recreation Survey, Study Report 19 (Washington, DC., ORRRC, 1962). 17. For a discussion of the implications of this technique see: Tourism and Recreation Research Unit,
Recreational Activitv Scotland (Edinburgh,
48
Substitution TRRU,
in
1977).
Backwoods: income. Boat culture: colour, urbanisation, health, income. Country club: age. Passive pursuits: education, health.
occupational
status,
Some fairly basic conclusions are drawn: that levels of participation in those activities strongly associated with demographic variables, place of residence, and health conditions will not change rapidly since these variables themselves are fairlvI stable. This would inelude particularly the active ‘country club’ group of activities. Those activities related to educational !evel and income may be expected to increase in popularity in line with increases in educational levels and incomes: this applies mainly to the passive pursuits and, to a lesser extent, to the backwoods group. Cicchetti produced a highly technical work using this form of recreation f&recasting in his study Forecasting Recreation in the International
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of Tourism
Management
March 1980
The future of leisure United States. l8 A key aspect of his work was the inclusion of the supply of facilities in the models, reflecting the fact that consumption, or participation, results from the interaction of supply and demand. He also included total demand as an independent variable in the demand equation as an indicator of croihrding. Six sets of forecasts were produced based upon three ‘supply scenarios’ and two alternative population projections. Table 3 summarises the forecasts for the lower population estimates and two of the supply scenarios: one where the supply of facilities grows in proportion to demand and, more realistically, one where supply grows in accordance with funds likely to be available. The main growth areas according to this study are in camping and sailing. E.xercises in the quantitative forecasting of leisure activity in Britain to date have mainly been based on regional data from the northern, north-west and south-east regions of England and from Scotland. These are areas where demand surveys have been conducted. The Northern Regional Planning Committee in their 1969 study were concerned with active, mainly outdoor, activities.” Discriminant analysis was used to identify the social and economic variables which best differentiated between participants and nonparticipants. Participation rates for subgroups of the population defined by these variables (eg car owners/not car owners in different age groups) were then applied to the population structure as envisaged in 1980, to obtain forecasts of participation for that Table
3. Forecasts of US outdoqr
Activity
recreational
Growth
supply
activity
in participation,
of facilities
grows in proportion
1965ZOl!IO
‘realistic’ supply
(%)
growth
in
of facilities
to demand Swimming
395
137
Water
536
101
skiing
Fishing
171
Sailing
1977
Other
boating
309
Hunting
113
-34
317
-26
(remote)
259
136
Picnicking Sight-seeing
559 435
221 -7
3168
391
(developed)
Horse riding Playing outdoor
of Tourism
26
Hiking
6 icycling
Journal
158
886
Camping
International
283
Canoeing Camping
18. C.J. Cicchetti, Forecasring Recreation in the United States: An Economic Review of Methods and Applications to Plan for the Required Environmental Resources (Lexington, Mass, Lexington Books, 1973). i9. Northern Regional Planning Committee, Outdoor Leisure Activities in the Northern Region (Newcastle. NRPC, 1969).
16
.
58
74
189
683
83
Attending outdoor sports Attending outdoor concerts Driving for pleasure
124 309 48
134
Walking
258
23
All activities
309
68
Days per capita increase
199
25
Source:
Management
games/sports
558
for pleasure
Cicchetti.
March 1980
64 -35
1973.18
49
The future of leisure
year. These ‘basic’ forecasts were further modified by examining data from the survey on the numbers of people who expressed a wish to take up activities. In some cases, such as water activities, fishing, golf, camping and caravanning, and motor sports, this resulted in substantial increases over the ‘basic’ forecasts. Finally the study also produced information on the projected numbers of people actually engaging in activities on an average Saturday and an average Sunday, the peak demand periods. The fastest growing activities were golf, camping and caravanning, motor sports, and trips to the countryside. In the study of Leisure in the North West multiple regression was used to relate participation in recreation activities to background variableszO Equations were derived for day trips, half-day trips, turf sports, indoor dry sports, outdoor water sports, ruralarea sports, swimming, fishing, golf, tennis, and bowls. Forecasts were produced only for fishing, as a case study, producing an increase over the period 1969-I 98 1 of about 14%. Further work using the Leisure in the North West data was carried out by Settle in 1977.” This is a particularly thorough study statistically. In a foreword to the study Professor Brian Rodgers states: It is believed that this report takes the methodology of the analysis of recreational patterns by mathematical means about as far as it is profitable to do so (in our present state of knowledge, and in the particular directions chosen in this study) so as to create predictive tools.
but he goes on: It must be confessed that it is difficult, almost to impossibility, to judge whether the methods adopted and the tools fashioned in this study will be successful in application. They work well enough as applied to present circumstances. But the whole economic and social environment of recreation is changing quickly, at least in the middle term: wage restraint, inflation, petrol prices, financial pressure on the public sector, all have their influence. The study does not in fact produce forecasts. For each activity considered it identifies the variables which produce the best explanation of levels of participation via multiple regression. It then produces the ‘predicted’ level of participation for each group of the population as defined by the variables included in the equation. Thus, for instance, in the case of fishing, the variables identified are age, sex, and possession of a driving licence. Six age groups are used. For each age group the population can be divided into four groups: males and females with and without driving licences. There are therefore 24 groups altogether. The report produces the percentage rates of participation for each of these groups. It is anticipated that local planners could apply these rates to the future population in their own area (divided by age, sex, and driving licence), to arrive at levels of participation. Note that ‘predicted’ is in inverted commas. The participation rates are only ‘predicted’ in the mathematical sense: they are merely a mathematical representation of the current pattern of participation. The forecasting elements of the exercise arises in the application of these rates to jitture population levels. Considerable work on forecasting recreation behaviour has been carried out in Scotland at the Tourism and Recreation Research 20. North West Sports Council, Leisure in the North West (Salford, Department of the Environment and NWSC. 1972).
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Unit at Edinburgh University. tion in central Scotland based
age, income,
*r In a study of recreation participaon a multiple-regression model using
and car ownership International
as independent
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1980
The future of leisure
found that the fastest-growing outdoor activities would be sailing, angling, golf, sea-fishing, and field sports (Table 4). The list of activities is different from that used in the northern region study but the period covered is similar. Apart from golf however, the predicted changes in levels of participation are very different: camping is at the bottom of the list. Young and Willmott’s forecasting exercise included in their Symmetrical Family study was based on a survey carried out in the south eastern region of England in 1970.22 Again multiple regression was used. The rates of participation found in the south east were applied to the UK population, taking account of demographic, social, and economic differences: forecasts were then produced for the year 200 1. The results were as in Table 5. In this study the fastest-growing activities by far were expected to be watching winter sports and playing rugby, although both of these activities had very small samples of participants. In the second rank were sailing, badminton and squash, horse riding, car cleaning, painting and sculpture, and ‘working at home’. A feature of this study is the wide range of activities included. Young and Willmott themselves sum up the picture presented: The outstanding feature of the forecasts is that almost everything is likely to increase. This is a reflection of the main fiidings of the survey - that richer, higher-status, more-educated, car-owning people did more of almost everything. Since we assume that people will be richer, more educated, doing higher-status jobs and owning more cars, it follows that almost every activity should have more participants in 2001.
The variables used in this analysis were: age, income, occupational class, age of finishing full-time education, and car ownership. These findings illustrate the problems of the cross-sectional model. Thus the characteristics of the present participants alone, may well indicate that the level of church going will increase and bingo will decrease in popularity but other factors would suggest the opposite. So again we are reminded that forecasts of this sort are no more than the nature of the models implies - ie they measure the effect of changes in the ‘predictor’ variables only: all the other factors Table
4. TRRU
Activity
Sailing
2
1. J.T. Coppock and B.S. Duffield,
forecasts for central Scotland
Growth
in participation
levels 1969-1981 50
Angling
40
Golf
40
Sea fishing
40
Field sports
38
Skiing
30
Horse riding
29
Pleasure boating
24
Nature studies Hiking, walking
23
(%)
The future of leisure
which we know are influential in determining leisure behaviour, such as changes in fashion or taste and technological changes, remain to be added in. The problem is that these additional factors are not predictable or quantifiable. My own study made use of the UK 1973 general household survey, an omnibus social survey of 20 000 people carried out annually by the Office of Population Censuses and Surveys, which, in 1973, contained questions on leisure participation.23 Equations Table 5. Young and Willmott recreation forecasts for the UK Activity
Participation (%ja 1970 2001
Swimming
29
Sailing
3
28 50 43 11 17
7
10
Fishing
9
10
Soccer
6
7
Cricket
4.5
5
11
Tennis
8
10
25
11
13
18
2
2
0
9
10
11
tennis
Bowls Ten-pin
bowling
Athletics Badminton
and squash
2
2
3
4.5
<05
8 ugby Boating Skating Horse riding
swimming
Watching
golf
Watching
soccer
Watching
rugby
Watching
cricket
Watching
tennis
Watching Watching
.
250
1.5
1.5
1.5
0 0
1.5
50
44
Watching
1
0 50
1.5 1
All sports
52
6
6.5
2.5
3
20 35 10
22 4.5 13
18 8 20 10 29 30
5.5
7.5
athletics
3
3.5
17
motor
7
8
14
sports
36
Watching
boxing
3
3
0
Watching
wrestling
4
4
0
5.5
7
27
1
250
Watching
horse racing
Watching
winter
Watching
show jumping
All watching
sports
sport
<0.5 2
2.5
40
45
record player etc)
68
70
Playing an instrument
9
Listening
25 13
to music (on radio,
Home decorations
or repairs
Car maintenance
52
4.5
Golf
Table
23. A.J. Veal, The Future of Leisure. Report to the Social Science Research Council (Birmingham, Centre for Urban and Regional Studies, University of Birmingham, unpublished, 1979).
37
Change (%Ib
11.5
3 28
60
66
10
20.5
27
32
Car cleaning
33
50
Knitting
46
44
51 -4 10
and sewing
Reading
67
74
Gardening
63
67
Model
5.5 12
6.5 13.5 5.5
building
Collecting
stamps etc
Handicrafts
5
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of Tourism
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Management
(con timed)
March 1980
The future of leisure Table
5 (continued)
Participation 1970
Activity
Technical
Notes: a Percentage of adults aged 18 and over doing the activity at least once in a year. b Young and Willmott prod&e a range ofincreases, reflecting the uncertainties in the data and the method. The percentage changes liven here are mv own calculations From the data g&en.
(%ja 2001
5
hobbies
6
Change (%jb
20
11.5
35
3
4
33
Cooking
2.5 3
3.5 4.5
40
Painting/sculpture Working
4.5
7.5
67
Playing cards/chess
8.5
Crosswords
at home
50
Going to cinema
53
58
9
Going to theatre
37
45
Going to museum Going to art gallery
25
32
22 28
17
25
47
Going out for a meal
62
70
13
Going to a pub Attending church Voluntary work
62
69
11
37
41
11
15
19
27
Billiards/snooker
12
12.5
Darts
21
22
4 5
Dancing
31
35
13
Going for a walk of 1 mile or
65
68
5
Going for a drive
68
78
15
Camping
7 10
8
14
11
10
more
Caravanning Bingo Adult
Source:
education
Young and Willmott,
1973,22
3.5
3
3.5
6.5
-14 9
pages 369-372.
using age, sex, personal income, and car ownership as independent variables were used to produce forecasts of participation in England and Wales to 199 1. The results for some 30 activities, were mixed with R2 as low as 0.11 and as high as 0.8 1; but when groups of activities were taken together, such as all outdoor sport or all sport the value of HZ was as high as 0.85. The average rates of growth obtained were as set out in Table 6, with camping, golf, tennis, badminton and squash, and watching motor racing showing the highest rates of growth.
The implications for leisure policy What conclusions can be drawn from this review? First we might note that the buIk of leisure forecasting has adopted a limited canvas. It has been concerned with the relative growth of different activities rather than the potential growth of leisure as a whole. It has been further limited by concentration on outdoor and sporting activities, largely because these have been the concerns of the public agencies sponsoring the research. With the exception of Cichetti’s work, the supply side of the equation has been ignored, a factor which is more important for some activities (such as water-based activity) than others. Most of the research reviewed has been commissioned by public bodies or has been concerned with the public-policy implications of the forecasts and yet, curiously, the distributive effects of basing provision policies on such forecasts have been ignored. The fastestInternational
Journal
of Tourism
Management
March 1980
53
The future of leisure
growing activities are generally those engaged in by the better-off, more mobile sections of the community and the cross-sectional model assumes that as wealth and mobility spreads so will participation increase. It is therefore the wealthiest and the most mobile half or two-thirds of the population with which we are concerned. It does not in all cases follow that the provision to meet growing demand should come from the public sector or that the facilities provided should be subsidised. But in many cases this is the pattern. The result could be that public policy based on such forecasts could be concentrating on the needs of the better-off and neglecting those of the poorer sections. There are signs from governments, on both sides of the Atlantic, that this is being recognised.24 Table 6. Rates of growth of leisure activities in England and Wales, 1973-1991 Activity
Projected growth in number of participants 1973-1991 (%)
Camping Golf Soccer Cricket Tennis Bowls Fishing Swimming outdoors Outdoor sport
33 33 7 21 37 17 19 25 23
Badminton/squash Swimming indoors Table tennis Billiards/snooker Darts Indoor sport
59 21 29 23 -5 23
All sport
21
Watching horse racing motor racing soccer cricket Total watching
10 33 15 19 19
Visiting parks Visiting seaside Visiting countryside Visiting historical buildings Visiting museums Visiting zoos Going to films
24. See, for example: Department of the Environment, Recreation and
Going to theatre Amateur music/drama
(London, HMSO, 1975), United States Department of the Interior,
Going out for meal Going for drink Dancing Bingo
US Government 1978).
Source:
Deprivation in Inner Urban Areas
National Urban Recreation Study: Executive Report (Washington, DC,
54
Printing Office,
6 17 21 25 25 18 18 20 25 21 15 17 -4
Veal, 1 979.23
International
Journal of Tourism Management
March 1980
The future of leisure
By its very nature forecasting of leisure activity must be one of the more difficuit areas of social forecasting, given that the very essence of leisure is freedom of choice. We have little evidence on the success of past forecasting exercises in recreation partly because most of the forecasts have been for the mid 1980s and beyond, to the year 2000. Despite the limitations of the tools available continued research in this area would seem necessary if only to open up the debate about leisure futures. Julian Huxley wrote, in 1959:
25. J. Huxley, “The future of man”, Bulletin of the Atomic Scientists, 1959, I5 (2), pages 402-404 and 409.
International
The leisure problem is fundamental. Having to decide what we shall do with our leisure is inevitably forcing us to reexamine the purpose of human existence, and to ask what human fulfiment really means . . . this involves a comprehensive survey of human possibilities and methods of realising them; it also implies a survey of the obstacles to their realisationz
Journal of Tourism Management
March 1980
The author reviews a range of mainly British and US research on future leisure behaviour and in particular: general scenarios, forecasts of the amount of leisure time, activities, and expenditure. He discusses the limitations of one of the most widely used approaches - cross-sectional analysis. He notes some of the problems facing policy makers: there has been an overconcentration on sporting and outdoor activities, and the distributive effects of their policies have been largely ignored, eg leisure facilities meet the needs of the better-off sections of the population. A.J. Veal is at the Centre for Urban and Regional Studies, University of Birmingham, PO Box 363, Birmingham B15 ZTT, UK. This article is based on research financed by the UK Social Science Research Council.
Most writings about the future of Western society have either ignored the phenomenon of leisure, or treated it very much as a residual. Yet in highly productive economies, leisure can be seen as a key element in the economic equation. Although many of the consumer goods which have appeared on the scene during the twentieth century have been designed to save time, many - and television is the prime example - require time to enjoy. It has been estimated that in the 20th century approximately 80% of the fruits of increased productivity have been taken in the form of additional income and 20% in the form of reduced working hours.’ In the postwar era reduced working hours in most of the Western world have been taken in the form of rapidly increasing holidays while the working week has stayed resolutely at around 40 hours since the 19.50s. However, it is not necessarily easy to achieve a balance between the desire for additional material goods and services and the desire for increased free time in which to enjoy them. Linder has noted that modern man is compressing more and more activity into the by, and to some extent the same amount of time,* surrounded captive of, more and more consumer goods. He diagnoses a developing “time famine” and refers to the busy, well-off members of economically advanced societies as “the harried leisure class”. America, has also noted this De Grazia, writing of modern phenomenon: An age that breeds technology must be one that is beguiled by and desirous of material things and therefore must buy or somehow acquire them, to do which it must use up the time any one machine or device may save. Any primitive tribe enjoys more free time than a resident of the United States today. It is doubtful that any civilisation ever had as little free time as we do. The commodity mentality, fascinated by the made and purchasable thing, holds the American worker in a vice of working overtime to buy time-saving devices and ‘leisure goods’.3
1. Kenneth Society
Roberts, Contemporary
and the Growth
of Leisure
(London, Longmans, 1978), page 15. 2. Stefan Linder, The Harried Leisure Class (New York, Columbia University Press, 1970). 3. S. De Grazia, “The problems and promise of leisure”, in W.R. Ewald, ed, Environment and Policy: The Next Fifty Years (Bloomington, University of Indiana Press, 1968), pages 112-133.
42
Researchers into leisure have, at least since the early 196Os, been interested in forecasting leisure behaviour. Their efforts to date, however, have been largely technical demand-forecasting exercises which generally fail to consider the wider issues of the role of leisure in society. I would like to review here the range of approaches which have been attempted, the sorts of findings they have produced and their limitations. The Delphi technique is familiar to forecasters as a means by which opinions about future events are gathered from panels of experts. In successive rounds of questioning respondents are infor-
0143-25
16/80/010042-l
5 $02.00
@ 1980 IPC Business Press
The future
of leisure
med about the results of previous rounds (usually in the form of average probability scores) so that they have the opportunity to adjust their own views in the light of information about other respondent’s views. The only substantial known use of this technique in the leisure area was by Shafer et al, 4 using a panel of 405 American experts, mainly involved in natural resources management. Examples of predictions which resulted were:
4. E.L. Shafer, G.H. Moeller, and R.E. Gethv. “Future leisure environments”. Ekis&s, July 1975, 40 (236), pages ’ 68-72. 5. In the UK the GPO’s ‘Prestel’ system already includes information on sports and holidays supplied by the Sports Council and the English Tourish Board. 6. Ian Miles. Sam Cole. and Jay Gershuny, “Images of the future”, in Cbristooher Freeman and Marie Jahoda; eds, World Futures: The Great Debate (London, Martin Robertson, 1987), pages 279-342. See also “Scenarios of world development”, Futures, February 1978, 1 O( 1). pages 3-21.
International
Journal
of Tourism
Use of computers to advise people where to go for recreation (by 1980).’ Most people work a 4-day, 32-hour week (by 1985). Year-round skiing on artificial surfaces. Remote sensing devices used to monitor national-park use; waste-disposing bacteria incorporated into recreation average retirement age 50 years; ‘weekends’ equipment; distributed throughout the week; leisure is an accepted lifestyle (all by the year 2000). Man-made islands created solely for recreation (by 2000). Most middle-income families own their own vacation homes (by 2030). Self-contained underwater resorts; first park established on the moon; average worker has 3 months annual vacation; 20% of the available workforce used to produce goods and services for the entire population (sometime after 2050). Miles et al produce outlines of 12 different possible futures by taking three ‘worldviews’, each analysed according to four ‘profiles’.6 The ‘worldviews’ are: conservative, reformist, and radical; and the ‘profiles’ are: high growth/more equal, high growth/inegalitarian, low growth/inegalitarian, and low growth/more equal. This framework of analysis is applied to 17 areas of human activity or concern, one of which is leisure. Each scenario is viewed from the point of view of rich and poor countries. The aim and result of this exercise is not to come to conclusions about which future scenario is the more likely but to explore the possible consequences of different sets of assumptions. Thus the possible leisure futures which they discuss include an increasingly packaged and marketed leisure age, contrasted with one which concerns itself more with education and activities ‘orientated to improving mind and body’; increasing reliance on passive spectator entertainments possibly involving more institutionalised violence; and stimulation-seeking and compensatory leisure.
The amount of leisure time In leisure research it is important to remember that empirical work has only been carried out on any scale since the early 1960s starting with the massive investigation conducted by the US Outdoor Recreation Resources Review Commission. A great deal of research output has as a result been descriptive, the aim being simply to discover what people do with their leisure time, which activities are popular, and which less popular. This is particularly true of an area which has come to be known as time-budget research. Time-budget research is based on ‘diaries’ kept by a sample of individuals over a specified period - usually a few days. The BBC’s
Management
March 1980
43
The future of leisure
audience research surveys’ and a cross-national, six-nation timebudget study directed by &alai8 are the main examples of this work: both are essentially descriptive and fail to use the enormous quantities of data collected for forecasting purposes. Holman’ produced a national time budget for the year 2000 for the USA based on predicted changes in the distribution of the time of individuals and the growth of the population. Making some rather heroic assumptions - for instance that the working week will fall to 28 hours by the year 2000 - she suggested that the total amount of ‘discretionary’ time available would rise from 450 thousand million hours per annum (3000 hours per head of population) in 1950 to 1100 thousand million hours (3400 hours per head) in the year 2000. This work seems to have been an isolated exercise which has not been repeated for other countries, and has not been updated as population predictions and assumptions about economic growth have changed. A more recent example of thinking in this area has been the work of Best”. He is concerned that the current ‘linear life plan’, involving a sequence of youth/education, adulthood/work and oldage/retirement phases, is not flexible enough to cope with the demands of the future. He shows that if all growth in productivity between the years 1975 and 2000 (at 4% per annum) were to be taken in the form of reductions in working hours rather than increased production, annual working hours could fall from 1900 hours to 970 hours. The possible implications for leisure time would be either: a 0 0 0
7. British Broadcasting
The People’s Activities
Corporation, (London,
BBC. 1965 and 1979). 8. A. Szalai, The Use of Time (The Hague. Mouton. 1972) 9. M.A. Holmai, “A national timebudget for the year 2000”. Socioloav andSocial Research, October 196 ly46(l). IO. F. Best, “The time of our lives: the parameters of lifetime distribution of education, work and leisure”, Society and Leisure, April 1978. IO(l), pages 95-124. 11. E. Lippold, “The utilisation of time-budget data for planning”, Society and Leisure, 1973,5 (I), pages 17-30.
44
a 20-hour working week, or 27 weeks of annual paid holidays, or a 39-month paid sabbatical every 7 years, or retirement at age 39.
In fact Best suggests that US workers are likely to take only about 25% of the projected growth in the form of free time. Nevertheless work patterns might be varied at different stages of the life-cycle to suit individual circumstances. Thus people with children might wish to have shorter working weeks but forego longer holidays and sabbaticals, whereas those without children might be happy to work a longer week and take their free time in larger blocks. Sabbaticals would facilitate education and retraining during adult life. The result might be a movement towards a ‘cyclical’ rather than ‘linear’ life plan. In the socialist countries of the Eastern block a great deal of research on time budgets has been conducted: conscious decisions about the extent of the workers’ free time and acceptable use of it is an aspect of economic and social planning. An East German study shows how the planned increase in the proportion of professionally qualified workers will lead to increases in leisure because of differencesinlifestyle between manual and nonmanual workers,” and relates investment in the production of convenience foods and the labour time involved in their production, to the aggregate time savings of the consumer. There have been no time-budget-based studies recent enough to have been able to take account of the recent advances in technology which have awakened public interest in the problems of jobs, work time, and leisure. Jenkins and Sherman’s study The Collapse of International
Journal
of Tourism
Management
March 1980
T77efuture of leisure
Work,‘* for instance, stops short of any detailed analysis of the leisure implications of the reduced working time which they foresee.
Forecasting leisure expenditure A considerable amount Britain has been carried quantitative forecasts it tions about underlying study Martin and Mason
of work on future leisure expenditure in out by Martin and Mason. To make any is necessary to make some firm assumpsocial and economic trends. For their assume that there will be: l3
a declining child population, an increasing proportion of women working, growing pressure for better housing and environmental conditions, more flexibility in working arrangements, a tendency still to take the bulk of the potential rise in standard of living in the form of higher incomes rather than free time, more self-employment, part-time working, and optigg out, some reduction in working hours - about 250 hours reduction by 199 1, taken in the form of Friday afternoon off, plus 8 or so extra days holiday, annual economic growth of 3-3.5%, 4.5% annual growth in leisure spending (90% growth between 1976 and 1991), and a preference for social activities outside the family, local community related activities, leisure at home, activities associated with the car, jobs and part-time work.
12. C. Jenkins and B. Sherman, The Collapse of Work (London, Eyre and Methuen, 1979). 13. W.H. Martin and S. Mason, The Prospects for Leisure: The Next Five Years and Beyond (London, Leisure Consultants, 1975). 14. I. Koltai, “Development and longterm forecast of leisure time expenditure in Hungary”, Society and Leisure. 1972. 4 (4), pages 91-109.
International
educational
activities,
and
second
They see total leisure spending in Britain increasing from 27.6 thousand million in 1977 to 210.2 thousand million in 1982 (at 1970 prices, multiply by approximately 2.9 to convert to 1979 prices). This is a rise from 20 to 22% of total consumer expenditure. In fact ‘leisure spending’ is very difficult to identify from UK official sources - mainly the annual family expenditure survey. Table 1, which shows the distribution of leisure expenditures in 1977 and the 1982 predictions, illustrates why. Many of the categories, such as books, alcoholic drink, and eating out, include nonleisure elements. In addition travel and much leisure clothing is excluded. Despite these limitations the data is clearly of some interest. The main feature is perhaps the dominance of alcoholic drink. Secondly it might be noted that the only significant change in relative magnitude over the 5-year period is the increase of 3% in the holidays element. Koltai14 has described research on the projected growth in leisure-related expenditure in Hungary. A fourfold increase was envisaged between 1967 and the mid 198Os, distributed as shown in Table 2. It is possible to detect some similarities between the Hungarian and British pattern, despite the differing lists of categories of expenditure. Most notable is that both see a more than average increase in tourism/holidays. The British model assumes consumerled growth whereas the Hungarian model assumes some control
Journal of Tourism Management
March 1980
45
The future of leisure Table
1. Distribution
of the leisure pound
Leisure spending devoted
Books, newspapers, TV,
to
magazines
radio, audio
Do it yourself Hobbies
and gardening
and pastimes
Alcoholic
drink
1977
1982
(%I
(%I
7.7 10.2
6.9 9.8
8.4
8.1
7.3
5.9
39.5
39.9
Eating out
5.9
6.1
Gambling
4.3
3.8
Entertainment
2.2
1.9
Sport
3.0
3.2
11.5
14.4
and recreation
Holidays
Source:
Martin and Mason, 1977.13
over the consumer by the state through availability of consumer goods, thus:
its control
over
the
The individual choice by consumers of the utilization of leisure time can be influenced by large and differentiated supplies which correspond to society’s goals.
“society’s
Among
goals” is the principle
socially dangerous consequences side-effects should be prevented.
of increased
Hence perhaps, the failure to mention in the table of expenditure at all.
Cross-sectional
that: leisure time and undesirable
the consumption
of alcohol
analysis of activities
This is perhaps the most firmly established forecasting technique in this area. It identifies those social characteristics which appear to relate to variations in levels of leisure participation among Table
1967
2. Leisure-related
-mid
expenditure
1980s
in Hungary
Average
Distribution
annual
1967
(%) mid 1980s
increase (%I Cars, motorcycles Television/telephone Books,
periodicals,
and weekend
Social life, entertainment
tourism
Musical
instruments,
37
17
12
5
14
7
13
8
14
8
22
19
9
3
5
3
3 1
(out-of-
doors) Sport and camping
22
7 and cultural
events Recreation
12
goods photography
12
2
4
Gambling
3
9
3
Total
9
100
Hobbies,
Source:
gardening
100
Koltai. 1972. l4
International
Journal of Tourism Management
.March 1980
The future of leisure
15. J.G. Settle, Leisure in the North West: A Tool for Forecasting, Sports Council Study 11 (London, Sports Council. 1977).
International
Journal
of Tourism
people. This might be achieved using multiple regression or the related technique of discriminant analysis, eg it is often found that level of personal income distinguishes very clearly between those who do and those who do not take part in certain leisure activities: higher-income groups usually take part more than low-income is known, and if the relationship groups. If this relationship between levels of income and distribution of income is known, future levels of leisure participation can be predicted. This approach can of course be followed using other variables, such as age, car ownership, hours of work, family situation, and so on. Multiple-regression techniques allow the relative importance of a number of such factors to be taken into account so that more than one variable can be incorporated in the forecasting equation. This requires forecasts of these independent variables to be produced for the forecast to be carried out. The key assumption in the method is that the relationship between the social variables and leisure participation will remain constant, eg that people who acquire cars in the future who have not previously had a car will behave in a similar way to those who currently have a car. It assumes that the leisure patterns of the elderly of the future will be similar to those of the elderly of today. It assumes that patterns of expenditure of lower-income groups will change as they move into h.igher absolute-income brackets. Of course factors interact, and the model can accommodate this. Thus the elderly may change their behaviour because they have more cars or more income. Two alternative approaches to the detailed development of this model have been used. The fist uses, as the basic unit of analysis, the individual. The individual who participates in a given leisure activity is given a score of 1 and the individual who does not is give a score of 0. Alternatively a score may be given reflecting the number of times the individual has engaged in the activity in the given time period. The independent variables used in the analysis are then that person’s own attributes - his income, age, whether he has a car, etc. The alternative method uses as the unit of analysis groups of individuals with common characteristics. In this case the focus of attention - the dependent variable - is the percentage of people in that group who participate: the independent variables used are the attributes of the group - its average age, average income, etc. Settle argues that the latter method is statistically superior and that the results are easier to interpret.” It is certainly true that in practice any forecasting activity is likely to be related to groups with common characteristics in the community rather than to individuals. A characteristic of research using this approach is that it requires large data sets in order to provide sufficient numbers of individuals in the various age/sex/income/car ownership ‘cells’. This is particularly true when analysing less-popular activities. One of the earliest attempts to use large-scale survey data for prediction purposes was the work of the US Outdoor Recreation Resources Review Commission (ORRRC), already referred to. The National Recreation Survey, conducted in 196 1, involved a sample of 4400 persons over the age of 12 and was confined to outdoor recreation mainly or a rural nature. One ORRRC report states:
Management
March 1980
47
The future of leisure
it was assumed that participation in a given outdoor activity is predictable from the social and economic characteristics of the participant. l6 In an appendix to the report this proposition is explored by Proctor. He first of all classifies 15 outdoor activities, using factor analysis, into four groups: 0 0 l
0
Backwoods group: including camping, fishing, hunting, nature walks, hiking, mountain climbing, and canoeing. Boat culture group: including boating, water-skiing. Country club to picnic ground group: including sailing, swimming, bicycling, riding, outdoor games or sports, picnicking. Passive pursuits group: including driving for pleasure, walking for pleasure, sightseeing, attending outdoor concerts, and attending sporting events.
This technique of grouping activities by means of factor analysis started what almost became an industry. In essence it groups activities by analysing patterns of participation: if people who participate in activity x also tend to participate in activity y then x and y appear in the same group. The supposition is that people of similar socioeconomic or psychological characteristics will be attracted by activities in the same group.” Proctor then produced scores for each individual for each of these activity groups, based on their level of participation in activities in that group (in days per annum) and related these analysis, to some 30 different scores, by multiple-regression independent variables. The variables spanned the usual socioeconomic range including age, sex, income, occupation, and residential location data. The results are complicated and inconclusive : After having applied the elaborate regression computations, it is apparent that the technique is helpful in performing a screening operation on all causal connections leading from independent to dependent variables but falls far short of being very precise concerning the amount of influence.
Intercorrelation between the independent variables is suggested as one explanation for the lack of clarity in the results. It is found that the following variables are the most influential in each group: l l l l
16. Outdoor Recreation Resources Review Commission, Ngtional Recreation Survey, Study Report 19 (Washington, DC., ORRRC, 1962). 17. For a discussion of the implications of this technique see: Tourism and Recreation Research Unit,
Recreational Activitv Scotland (Edinburgh,
48
Substitution TRRU,
in
1977).
Backwoods: income. Boat culture: colour, urbanisation, health, income. Country club: age. Passive pursuits: education, health.
occupational
status,
Some fairly basic conclusions are drawn: that levels of participation in those activities strongly associated with demographic variables, place of residence, and health conditions will not change rapidly since these variables themselves are fairlvI stable. This would inelude particularly the active ‘country club’ group of activities. Those activities related to educational !evel and income may be expected to increase in popularity in line with increases in educational levels and incomes: this applies mainly to the passive pursuits and, to a lesser extent, to the backwoods group. Cicchetti produced a highly technical work using this form of recreation f&recasting in his study Forecasting Recreation in the International
Journal
of Tourism
Management
March 1980
The future of leisure United States. l8 A key aspect of his work was the inclusion of the supply of facilities in the models, reflecting the fact that consumption, or participation, results from the interaction of supply and demand. He also included total demand as an independent variable in the demand equation as an indicator of croihrding. Six sets of forecasts were produced based upon three ‘supply scenarios’ and two alternative population projections. Table 3 summarises the forecasts for the lower population estimates and two of the supply scenarios: one where the supply of facilities grows in proportion to demand and, more realistically, one where supply grows in accordance with funds likely to be available. The main growth areas according to this study are in camping and sailing. E.xercises in the quantitative forecasting of leisure activity in Britain to date have mainly been based on regional data from the northern, north-west and south-east regions of England and from Scotland. These are areas where demand surveys have been conducted. The Northern Regional Planning Committee in their 1969 study were concerned with active, mainly outdoor, activities.” Discriminant analysis was used to identify the social and economic variables which best differentiated between participants and nonparticipants. Participation rates for subgroups of the population defined by these variables (eg car owners/not car owners in different age groups) were then applied to the population structure as envisaged in 1980, to obtain forecasts of participation for that Table
3. Forecasts of US outdoqr
Activity
recreational
Growth
supply
activity
in participation,
of facilities
grows in proportion
1965ZOl!IO
‘realistic’ supply
(%)
growth
in
of facilities
to demand Swimming
395
137
Water
536
101
skiing
Fishing
171
Sailing
1977
Other
boating
309
Hunting
113
-34
317
-26
(remote)
259
136
Picnicking Sight-seeing
559 435
221 -7
3168
391
(developed)
Horse riding Playing outdoor
of Tourism
26
Hiking
6 icycling
Journal
158
886
Camping
International
283
Canoeing Camping
18. C.J. Cicchetti, Forecasring Recreation in the United States: An Economic Review of Methods and Applications to Plan for the Required Environmental Resources (Lexington, Mass, Lexington Books, 1973). i9. Northern Regional Planning Committee, Outdoor Leisure Activities in the Northern Region (Newcastle. NRPC, 1969).
16
.
58
74
189
683
83
Attending outdoor sports Attending outdoor concerts Driving for pleasure
124 309 48
134
Walking
258
23
All activities
309
68
Days per capita increase
199
25
Source:
Management
games/sports
558
for pleasure
Cicchetti.
March 1980
64 -35
1973.18
49
The future of leisure
year. These ‘basic’ forecasts were further modified by examining data from the survey on the numbers of people who expressed a wish to take up activities. In some cases, such as water activities, fishing, golf, camping and caravanning, and motor sports, this resulted in substantial increases over the ‘basic’ forecasts. Finally the study also produced information on the projected numbers of people actually engaging in activities on an average Saturday and an average Sunday, the peak demand periods. The fastest growing activities were golf, camping and caravanning, motor sports, and trips to the countryside. In the study of Leisure in the North West multiple regression was used to relate participation in recreation activities to background variableszO Equations were derived for day trips, half-day trips, turf sports, indoor dry sports, outdoor water sports, ruralarea sports, swimming, fishing, golf, tennis, and bowls. Forecasts were produced only for fishing, as a case study, producing an increase over the period 1969-I 98 1 of about 14%. Further work using the Leisure in the North West data was carried out by Settle in 1977.” This is a particularly thorough study statistically. In a foreword to the study Professor Brian Rodgers states: It is believed that this report takes the methodology of the analysis of recreational patterns by mathematical means about as far as it is profitable to do so (in our present state of knowledge, and in the particular directions chosen in this study) so as to create predictive tools.
but he goes on: It must be confessed that it is difficult, almost to impossibility, to judge whether the methods adopted and the tools fashioned in this study will be successful in application. They work well enough as applied to present circumstances. But the whole economic and social environment of recreation is changing quickly, at least in the middle term: wage restraint, inflation, petrol prices, financial pressure on the public sector, all have their influence. The study does not in fact produce forecasts. For each activity considered it identifies the variables which produce the best explanation of levels of participation via multiple regression. It then produces the ‘predicted’ level of participation for each group of the population as defined by the variables included in the equation. Thus, for instance, in the case of fishing, the variables identified are age, sex, and possession of a driving licence. Six age groups are used. For each age group the population can be divided into four groups: males and females with and without driving licences. There are therefore 24 groups altogether. The report produces the percentage rates of participation for each of these groups. It is anticipated that local planners could apply these rates to the future population in their own area (divided by age, sex, and driving licence), to arrive at levels of participation. Note that ‘predicted’ is in inverted commas. The participation rates are only ‘predicted’ in the mathematical sense: they are merely a mathematical representation of the current pattern of participation. The forecasting elements of the exercise arises in the application of these rates to jitture population levels. Considerable work on forecasting recreation behaviour has been carried out in Scotland at the Tourism and Recreation Research 20. North West Sports Council, Leisure in the North West (Salford, Department of the Environment and NWSC. 1972).
50
Unit at Edinburgh University. tion in central Scotland based
age, income,
*r In a study of recreation participaon a multiple-regression model using
and car ownership International
as independent
Journal of Tourism
variables,
Management
it was
blarch
1980
The future of leisure
found that the fastest-growing outdoor activities would be sailing, angling, golf, sea-fishing, and field sports (Table 4). The list of activities is different from that used in the northern region study but the period covered is similar. Apart from golf however, the predicted changes in levels of participation are very different: camping is at the bottom of the list. Young and Willmott’s forecasting exercise included in their Symmetrical Family study was based on a survey carried out in the south eastern region of England in 1970.22 Again multiple regression was used. The rates of participation found in the south east were applied to the UK population, taking account of demographic, social, and economic differences: forecasts were then produced for the year 200 1. The results were as in Table 5. In this study the fastest-growing activities by far were expected to be watching winter sports and playing rugby, although both of these activities had very small samples of participants. In the second rank were sailing, badminton and squash, horse riding, car cleaning, painting and sculpture, and ‘working at home’. A feature of this study is the wide range of activities included. Young and Willmott themselves sum up the picture presented: The outstanding feature of the forecasts is that almost everything is likely to increase. This is a reflection of the main fiidings of the survey - that richer, higher-status, more-educated, car-owning people did more of almost everything. Since we assume that people will be richer, more educated, doing higher-status jobs and owning more cars, it follows that almost every activity should have more participants in 2001.
The variables used in this analysis were: age, income, occupational class, age of finishing full-time education, and car ownership. These findings illustrate the problems of the cross-sectional model. Thus the characteristics of the present participants alone, may well indicate that the level of church going will increase and bingo will decrease in popularity but other factors would suggest the opposite. So again we are reminded that forecasts of this sort are no more than the nature of the models implies - ie they measure the effect of changes in the ‘predictor’ variables only: all the other factors Table
4. TRRU
Activity
Sailing
2
1. J.T. Coppock and B.S. Duffield,
forecasts for central Scotland
Growth
in participation
levels 1969-1981 50
Angling
40
Golf
40
Sea fishing
40
Field sports
38
Skiing
30
Horse riding
29
Pleasure boating
24
Nature studies Hiking, walking
23
(%)
The future of leisure
which we know are influential in determining leisure behaviour, such as changes in fashion or taste and technological changes, remain to be added in. The problem is that these additional factors are not predictable or quantifiable. My own study made use of the UK 1973 general household survey, an omnibus social survey of 20 000 people carried out annually by the Office of Population Censuses and Surveys, which, in 1973, contained questions on leisure participation.23 Equations Table 5. Young and Willmott recreation forecasts for the UK Activity
Participation (%ja 1970 2001
Swimming
29
Sailing
3
28 50 43 11 17
7
10
Fishing
9
10
Soccer
6
7
Cricket
4.5
5
11
Tennis
8
10
25
11
13
18
2
2
0
9
10
11
tennis
Bowls Ten-pin
bowling
Athletics Badminton
and squash
2
2
3
4.5
<05
8 ugby Boating Skating Horse riding
swimming
Watching
golf
Watching
soccer
Watching
rugby
Watching
cricket
Watching
tennis
Watching Watching
.
250
1.5
1.5
1.5
0 0
1.5
50
44
Watching
1
0 50
1.5 1
All sports
52
6
6.5
2.5
3
20 35 10
22 4.5 13
18 8 20 10 29 30
5.5
7.5
athletics
3
3.5
17
motor
7
8
14
sports
36
Watching
boxing
3
3
0
Watching
wrestling
4
4
0
5.5
7
27
1
250
Watching
horse racing
Watching
winter
Watching
show jumping
All watching
sports
sport
<0.5 2
2.5
40
45
record player etc)
68
70
Playing an instrument
9
Listening
25 13
to music (on radio,
Home decorations
or repairs
Car maintenance
52
4.5
Golf
Table
23. A.J. Veal, The Future of Leisure. Report to the Social Science Research Council (Birmingham, Centre for Urban and Regional Studies, University of Birmingham, unpublished, 1979).
37
Change (%Ib
11.5
3 28
60
66
10
20.5
27
32
Car cleaning
33
50
Knitting
46
44
51 -4 10
and sewing
Reading
67
74
Gardening
63
67
Model
5.5 12
6.5 13.5 5.5
building
Collecting
stamps etc
Handicrafts
5
International
Journal
of Tourism
6 18 73 10
Management
(con timed)
March 1980
The future of leisure Table
5 (continued)
Participation 1970
Activity
Technical
Notes: a Percentage of adults aged 18 and over doing the activity at least once in a year. b Young and Willmott prod&e a range ofincreases, reflecting the uncertainties in the data and the method. The percentage changes liven here are mv own calculations From the data g&en.
(%ja 2001
5
hobbies
6
Change (%jb
20
11.5
35
3
4
33
Cooking
2.5 3
3.5 4.5
40
Painting/sculpture Working
4.5
7.5
67
Playing cards/chess
8.5
Crosswords
at home
50
Going to cinema
53
58
9
Going to theatre
37
45
Going to museum Going to art gallery
25
32
22 28
17
25
47
Going out for a meal
62
70
13
Going to a pub Attending church Voluntary work
62
69
11
37
41
11
15
19
27
Billiards/snooker
12
12.5
Darts
21
22
4 5
Dancing
31
35
13
Going for a walk of 1 mile or
65
68
5
Going for a drive
68
78
15
Camping
7 10
8
14
11
10
more
Caravanning Bingo Adult
Source:
education
Young and Willmott,
1973,22
3.5
3
3.5
6.5
-14 9
pages 369-372.
using age, sex, personal income, and car ownership as independent variables were used to produce forecasts of participation in England and Wales to 199 1. The results for some 30 activities, were mixed with R2 as low as 0.11 and as high as 0.8 1; but when groups of activities were taken together, such as all outdoor sport or all sport the value of HZ was as high as 0.85. The average rates of growth obtained were as set out in Table 6, with camping, golf, tennis, badminton and squash, and watching motor racing showing the highest rates of growth.
The implications for leisure policy What conclusions can be drawn from this review? First we might note that the buIk of leisure forecasting has adopted a limited canvas. It has been concerned with the relative growth of different activities rather than the potential growth of leisure as a whole. It has been further limited by concentration on outdoor and sporting activities, largely because these have been the concerns of the public agencies sponsoring the research. With the exception of Cichetti’s work, the supply side of the equation has been ignored, a factor which is more important for some activities (such as water-based activity) than others. Most of the research reviewed has been commissioned by public bodies or has been concerned with the public-policy implications of the forecasts and yet, curiously, the distributive effects of basing provision policies on such forecasts have been ignored. The fastestInternational
Journal
of Tourism
Management
March 1980
53
The future of leisure
growing activities are generally those engaged in by the better-off, more mobile sections of the community and the cross-sectional model assumes that as wealth and mobility spreads so will participation increase. It is therefore the wealthiest and the most mobile half or two-thirds of the population with which we are concerned. It does not in all cases follow that the provision to meet growing demand should come from the public sector or that the facilities provided should be subsidised. But in many cases this is the pattern. The result could be that public policy based on such forecasts could be concentrating on the needs of the better-off and neglecting those of the poorer sections. There are signs from governments, on both sides of the Atlantic, that this is being recognised.24 Table 6. Rates of growth of leisure activities in England and Wales, 1973-1991 Activity
Projected growth in number of participants 1973-1991 (%)
Camping Golf Soccer Cricket Tennis Bowls Fishing Swimming outdoors Outdoor sport
33 33 7 21 37 17 19 25 23
Badminton/squash Swimming indoors Table tennis Billiards/snooker Darts Indoor sport
59 21 29 23 -5 23
All sport
21
Watching horse racing motor racing soccer cricket Total watching
10 33 15 19 19
Visiting parks Visiting seaside Visiting countryside Visiting historical buildings Visiting museums Visiting zoos Going to films
24. See, for example: Department of the Environment, Recreation and
Going to theatre Amateur music/drama
(London, HMSO, 1975), United States Department of the Interior,
Going out for meal Going for drink Dancing Bingo
US Government 1978).
Source:
Deprivation in Inner Urban Areas
National Urban Recreation Study: Executive Report (Washington, DC,
54
Printing Office,
6 17 21 25 25 18 18 20 25 21 15 17 -4
Veal, 1 979.23
International
Journal of Tourism Management
March 1980
The future of leisure
By its very nature forecasting of leisure activity must be one of the more difficuit areas of social forecasting, given that the very essence of leisure is freedom of choice. We have little evidence on the success of past forecasting exercises in recreation partly because most of the forecasts have been for the mid 1980s and beyond, to the year 2000. Despite the limitations of the tools available continued research in this area would seem necessary if only to open up the debate about leisure futures. Julian Huxley wrote, in 1959:
25. J. Huxley, “The future of man”, Bulletin of the Atomic Scientists, 1959, I5 (2), pages 402-404 and 409.
International
The leisure problem is fundamental. Having to decide what we shall do with our leisure is inevitably forcing us to reexamine the purpose of human existence, and to ask what human fulfiment really means . . . this involves a comprehensive survey of human possibilities and methods of realising them; it also implies a survey of the obstacles to their realisationz
Journal of Tourism Management
March 1980