Transcript Leisure, Sport and Tourism: Politics, Policy and Planning

Leisure, Sport and
Tourism: Politics,
Policy and Planning
A.J. Veal
Chapter 11
Planning Tools 3:
Forecasting
CONTENTS
• The past of the future: a brief history of
leisure, sport and tourism forecasting
• Forecasting what?
• Demand change factors
• Forecasting techniques
THE PAST OF THE FUTURE:
a brief history of leisure, sport & tourism forecasting
• 1962: US Outdoor Recreation Resources Review
Commission: quantitative modelling of demand
• Leisure/sport demand forecasting generally
undertaken by academics + private sector
• Tourism forecasting (international) often sponsored
by government agencies
– often proved wrong because of significant international
events, such as 9/11 and Global Financial Crisis
FORECASTING WHAT? TYPES OF DEMAND
Type
Definition
Existing/expressed/current/
effective demand
Activity currently taking place
Unmet or latent demand
Activity frustrated by supply conditions
or personal circumstances
Supply induced/generated demand Activity materializing when supply
conditions change
Diverted demand
Activity transferred from an existing
facility to a new one
Substituted demand
Activity transferred from one activity to
another when a new facility/service
becomes available
DEMAND CHANGE FACTORS
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
Demography
Income
Supply: the activities of producers
Leisure time and work time
Transport
Technology
The environment, including climate change
Changing tastes and lifestyles
Changing attitudes and values
The media
Post-industrialism, postmodernism and globalization
1. Demography
Demographic change: UK, 2007-2031
4.50
Increase, 2007-31, millions
4.00
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
0-4
5-15
16-44
Age-group
45-M64/F59 M65/F60+
Australian data
on website:
Webfile11.01
2. Income
Trends in household expenditure, UK 1995-2006
Total exp.
Fig. 11.2
Leisure services
Leisure goods
Alcohol/tobacco
Food/non-alcoholic drink
Clothing/footwear
Personal goods/services
Household goods/services
Housing/energy
Transport
-40.0
-30.0
-20.0
-10.0
0.0
10.0
20.0
30.0
% Real change 1995/96 to 2005/06
40.0
50.0
3. Supply: activities of producers
•
•
•
•
‘Supply’ side of the demand-supply relationship
Suppler actions have some effect on activity
Public campaigns: eg. ‘Sport for All’, ‘Life. Be in it’
Provision of facilities – eg. 2000+ indoor leisure
centres in UK; cheap airlines
• Note also, the role of media, communications, critics
and ‘culture brokers’ between producers and
consumers
• The idea of ‘multi-purpose platforms’
4. Leisure/work time: Relatively little recent change
Actual hours worked per week
60
55
50
Aust. F/T
UK F/T
Aust. F+P/T
45
UK F+P/T
40
F + P/T = 1 fulltime + 1 part-time
35
98
99
00
01
02
03
04
05
06
5. Transport: Leisure travel, UK, 1995-2008: trend: 
300
Trips per person per year
250
200
Day trip
Holiday: to base
150
Sport: participate
Entertainment
100
Visit friends
50
Fig. 11.5
0
95/97
98/00
2002
2004
2006
2008
6. Technology: Trends in durable goods ownership, UK, 1970-07
100
90
% of households
80
70
60
50
40
30
20
10
0
1970 1975 1980 1985 1990 1995 2000 2005 2007
Cars
VCR
DVD
Home computer
7. Environment/climate change
• Leisure activities have an impact on the environment,
eg.:
–
–
–
–
golf courses require water
pedestrians compact soil, which can cause run-off /erosion
hotels/resorts generate sewage and litter
all take land which may be habitat of wildlife
• Climate change: most identified research focuses on
impacts/adaptation
Climate change (Box 11.1):
• World Tourism Organization Davos Declaration:
www.unwto.org/climate/support/en/support.php
• Research:
• McEvoy et al.:
– Coastal dune system with recreation: increased visitor numbers
and pressures
– Peak District NP: more fires
– Lake District NP: footpath erosion and loss of snow cover
– Manchester city centre: more demand for outdoor living
• Scott & Jones
– Golf: in Toronto: increased demand + longer season
• McBoyle et al.:
– Snowmobiling in Canada: reduction in the length of season, possibly to
zero for some areas
8. Changing tastes and lifestyles
• Difficult to predict
• Passing fads, fashions, crazes
• In some areas just as relevant to the public
sector as to the private sector
9. Changing attitudes and values
• The (Protestant) sees work as honourable,
compared with leisure (‘the devil makes work
for idle hands’)
• Some have called for a new attitude, to
embrace more leisure, to resist the ‘time
squeeze’
10. The mass media
• Television the major leisure activity in
contemporary economically developed
societies
• Novel other ‘screen-based’ activities replacing
some TV-watching time
11. Post-industrialism, postmodernism, globalization
• Post-industrial: services replace manufacturing
• Modernism: secularisation, rationalisation of society:
continuous technical, economic and social progress.
• Postmodernism: the idea of ‘progress’ and
hierarchies of excellence rejected: pop as valid as
Shakespeare; fashion, media, pop shape society
• Globalization: instant, world-wide communication,
economic systems, sport, music, fashion – with major
implications for leisure, sport & tourism
FORECASTING TECHNIQUES
1.
2.
3.
4.
5.
6.
7.
8.
9.
Informed speculation
Asking the public
Asking the experts (the Delphi technique)
Scenario writing
Time series analysis
Spatial analysis
Cross-sectional analysis
Comparative analysis
Composite methods
1. Informed speculation
• Personal reflections on the future of (informed?)
commentators .. eg. on the amount of work and
leisure in future
• Typically in final chapters of books
• No specific methodology
2. Asking the public
• Some surveys include questions asking people what leisure
activities they would like to, or plan to, take up.
• But does it work?
• Example: Australian 1991 survey (Box 11.2)
–
–
–
–
–
asked people what activities they would like to take up
most popular responses:
Men: golf 7% fishing 7%
Women: tennis 5% aerobics/keep fit 5%
Recent Australian surveys show aerobics/keep fit  but tennis, golf,
fishing 
– Why?
– Surveys show greatest claimed constraint on participation is ‘lack of
time’
3. Asking the experts: Delphi technique
• Named after classical Greek Delphic Oracle which
foretold people’s futures
• A method for finding consensus among experts
• A list/panel of experts is identified
• Can be conducted face-to-face, but more usually by
mail/email
• First round: Experts asked to give opinions on future
events in their field – likelihood, timing, etc.
• Results of first round are collated and circulated –
experts may revise their estimates
• May go to additional rounds
4. Scenario writing
• Devising alternative pictures of the future based
on key variables, eg economic/political (Fig. 11.7):
High unemployment
Scenario A
Implications for
leisure/sport/
tourism worked
out for each
scenario
Scenario B
Conservative
government
Leftist
government
Scenario C
Scenario D
Low unemployment
5. Time series analysis
• Continuation of past trends
• Depends on availability of time-series data. eg. gambling
expenditure in Australia, 1981-2005
Expenditure, $billion, 2006 prices
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
81 84 87 90 93 96 99 02 05 08 11 14 17 20
Time series analysis contd: projection to 2020
Expenditure, $billion, 2006 prices
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
81 84 87 90 93 96 99 02 05 08 11 14 17 20
Actual
Moving avge
Long-term trend
Structured: one variable reacts to changes in another
40
35
Demand
responds to
income change
1-2 years later
$'000s per annum
30
25
20
15
10
5
0
90
91
92
93
94
Income
95
96
Demand
97
98
99
00
6. Spatial analysis
• See Ch. 10 (Box 10.4) + Clawson method in Ch.
12.
• Quantitative modelling: see Box 11.4
7. Cross-sectional analysis
• analysis of variation of leisure participation
within – or across – the population
• as the structure of the population changes
(eg. ageing) so will overall participation
• Two methods:
a) Cohort
b) Regression equation
a. Cohort method
Current year
Age
group
Part’n
rate %
Population
A
B
Survey
Census
Est. participants (n)
%
C
AxB/100
14-19
14.9
15,600
19.5
2324
20-24
11.5
15,200
19.0
1748
25-29
7.4
11.360
14.2
841
30-39
5.2
16,880
21.1
878
40-49
4.8
7,200
9.0
346
50-59
3.5
6.160
7.7
216
60+
2.5
7,600
9.5
190
Total
8.2
80,000
100.0
6543
a. Cohort method contd
Current year
Age
group
Part’n
rate %
Prediction: year
2020
Population
A
B
Survey
Census
Est. partic- Population
ipants (n)
%
C
D
%
AxB/100
14-19
14.9
15,600
19.5
2324 12,000
14.9
20-24
11.5
15,200
19.0
1748 12,100
15.0
25-29
7.4
11.360
14.2
841 10,000
12.4
30-39
5.2
16,880
21.1
878 17,100
21.2
40-49
4.8
7,200
9.0
346 10,300
12.8
50-59
3.5
6.160
7.7
216
9,200
11.4
60+
2.5
7,600
9.5
190
9,800
12.2
Total
8.2
80,000
100.0
6543 80,500
100.0
NB. Big
increases
are in the
less active
age-groups
a. Cohort method contd
Current year
Age
group
Part’n
rate %
Prediction: year 2020
Population
A
B
Survey
Census
Est. partic- Population
ipants (n)
%
C
D
Predict
participants
%
AxB/100
E
AxD/100
14-19
14.9
15,600
19.5
2324 12,000
14.9
1788
20-24
11.5
15,200
19.0
1748 12,100
15.0
1392
25-29
7.4
11.360
14.2
841 10,000
12.4
740
30-39
5.2
16,880
21.1
878 17,100
21.2
889
40-49
4.8
7,200
9.0
346 10,300
12.8
494
50-59
3.5
6.160
7.7
216
9,200
11.4
322
60+
2.5
7,600
9.5
190
9,800
12.2
245
Total
8.2
80,000
100.0
6543 80,500
100.0
5870
Participation numbers fall
b. Regression-based techniques
• Example:
• P = a + bVAR1 + cVAR2 +dVAR3 etc
• where:
–
–
–
–
P = participation
VAR1, VAR2, VAR3 etc are independent, influencing variables
a, b, c etc coefficients determined by the analysis
forecasts of VAR1, VAR2, VAR3 etc provide forecasts of P
• see also Box 11.4
• see example on website (www.leisuresource.net)
8. Comparative method
• The idea that a version of the future can be seen in
other, more economically developed, countries –
Dumazedier
• Similarly, John Naisbitt (Megatrends) identified
‘bellweather’ states in USA, which are in advance of
the other states, in terms of lifestyles, consumption
9. Composite approaches
• More than one methodology is often used in
forecasting exercises
• eg. Kelly and Warnick, in Recreation Trends
and Markets (1999),use a combination of
methods:
– cross-sectional (cohort) and
– time series analysis