The impact of new attractions

Pieter Cornelis NHTV Breda University

Central research question • What is the impact of new attractions on the performance of (European) theme parks and how may this effect be explained? 1. What is the relative and perceived importance of investing in new attractions? 2. What are the effects of investing in new attractions? 3. How can the effects of investments in new attractions be explained?

Structure • Intro • What’s the importance of investing in new attractions?

15 min.

• What are the effects of investing in new attractions?

15 min.

– econometrics

• How can the effects of new attractions be explained? • Q&A

3 min.

15 min. 15-20 min.

What is the relative and perceived importance of investing in new attractions?

Paid admissions + 36% Operating revenues +62% Ticket revenue+58% EBITDA +82% Spending per cap +21% Merchandise +104%

Rides and slides (in Europe) #

2008 %

Coaster

27

17.9

40

20.7

35

22.3

102

20.4

Water ride

10

6.6

18

9.3

12

7.6

40

8.0

Family ride

69

45.7

59

30.6

48

30.6

176

35.1

Kids ride

14

9.3

28

14.5

18

11.5

60

12.0

Flat ride

22

14.6

17

8.8

11

7.0

50

10.0

3D/4D-show

4

2.6

15

7.8

18

11.5

37

7.4

Divers

5

3.3

16

8.3

15

9.6

36

7.2

Totaal

151

100

193

100

157

100

501

100

#

2009 %

#

2010 %

#

Total %

Source: Pieter Cornelis (2010d)

For water rides please refer to ewrdb.com

Source: AECOM (2010)

Perceived importance of new attractions Long-term importance

Factor

Short-term importance

%

Factor

%

1

New attraction

38.7 1

Weather

35.4

2

Weather

12.5 2

New attraction

28.5

3

Marketing budget

12.2 3

Marketing budget

10.0

4

Other investments in park

7.4 4

Entrance fee

8.1

5

Entrance fee

6.3 5

Special events

7.3

6

Special events

5.9 6

New shows/entertainment

3.8

7

New shows/entertainment

4.8 7

Competition

3.1

8

Other …

4.4 8

Disposable income/leisure time

1.9

9

Opening new hotel

4.0 9

Other investments in park

1.5

10

Competition

1.8 10

Opening new hotel

0.4

11

Disposable income/leisure time

1.5 11

Other …

0.0

12

Investments in Food&Beverage

0.5 12

Investments in Food&Beverage

0.0

Total

100

Total

100

Source: Cornelis (2009)

Vicious price circle Decreasing added value

Lower price premium

Less investment opportunity

Less profit possibilities

Source: Poiesz & Van Raay (2002)

Vicious marketing circles

price

communication

innovation

distribution

Predicting the unpredictable?!

Production of meaning

Source: Anton Clavé (2007); Hesmondalgh (2007)

Dynamics of theme park development by world region

Source: Anton Clavé (2007)

Water parks versus theme parks…?!

What are the effects of investing in new attractions?

What is the impact of investing 1 mio euro in a new ride…?! R2 = 0.0217

Beat the average...!

Source: Harrison “Buzz” Price (2002)

•Number of new attractions •Development period •Year of introduction •Characteristic of new attraction •Storytelling, theming, IP •Kind of ride •Initial investment •Hard characteristics (G-force etc.)

The Number of Visitors to (European )Theme Parks

New Attraction

•Price Policy

Direct effect Moderating effect Backx, R. and Cornelis, P. (2006). Force of attraction. Tilburg University.

Uncontrollable •Income •Relative prices •Cost of travelling •Vacations •National Holidays •Weekend days •Temperature •Precipitation •Etc.

Controllable •Marketing expenditures •Opening days •Opening hours/day •Special events •Hotel accommodation •Number of shows •Number of F&B outlets •Etc.

4 year = 40 cents 5 year = 50 cents 6 year = 60 cents 7 year = 70 cents 8 year = 80 cents 9 year = …

Y = 0,1X 4 year = 40 cents 5 year = 50 cents 6 year = 60 cents 7 year = 70 cents 8 year = 80 cents 9 year = …

Y = 0,05 + 0,1X Y = 0,05 + 0,1X1 + 0,03X2 Y = 0,05 + 0,1X1 + 0,03X2 + 0,01X3

Difference Net Number of Visitors

Short term effect

Long term effect

Summation of all variables in model

Multipliers Elasticities

On rainy day 20% less visitors

10% higher temperature means 3% more attendance

Small amusement park in Holland

Medium amusement & water park in Denmark

So please keep in mind…. • New attraction is just one X (variable) in the model! • What are the other variables that effect the number of visitors in your situation?!

Impact of new attractions • 10 European parks participated – – – – – –

Number of visitors between 0.2 – 4.0 mio Theme parks/ amusement parks Two parks have water park One park in water area Resort /day trip North/South Europe

• Data on daily/weekly basis – 10-25 years history

Rule of thumb?!

Cornelis (2010)

New attraction + 10%

Cornelis (2010a)

First year Second year

65% 35%

Impact of investment (first year) Frequency of investment

Major investment*

Major and minor investment **

Every year

4.2%

4.6%

Every two years

6.7%

7.2%

10.0%

11.9%

Every four years

6.2%

6.5%

Every five years

5.4%

5.4%

Less than every five years

4.3%

3.0%

7.5%

8.3%

Every three years

* ANOVA (F = 2.425; Sig. = 0.049) ** ANOVA (F = 2.645; Sig. = 0.043) Source: Cornelis (2009)

Warning • Differences between areas • Differences between parks

• Differences within parks – Dreamflight + 425.000 – PandaVision + 285.000

My first steps in econometrics

The first steps… • What are the (most) important variables in your situation?! • • • • •

Collect data in Xcell/SPSS Get connected to the data set Compute dependent variable Compute all independent variables Do the regression analysis

European Pleasure Garden

Theme park

Amusement Park

Cinema/ movie

Important variables

Collect data in Xcell/SPSS

Get connected to the data set

Three minute explanation how to do an error correction model (slide 47-60)

Source: Cornelis (2010a)

Dependent variable -Delta -LN

Compute dependent variable

Dependent variable -Delta -LN

Independent variables -Delta (short term) -LN

Independent variables -T-1 (long term) -LN

Compute all independent variables

Use (step)dummies for multipliers

Convert all prices to real prices

Independent variables -Delta -LN

Independent variables -T-1 -LN

Standard OLS regression

How can the effects of investments in new attractions be explained?

Attraction/ area

Individual response

Before

Direct

Short term Long term

Attraction response

Park response Brand response Aggregated response

Economic response Attraction Response Matrix

+ 285.000 + 425.000 Source: Cornelis (2010b)

Some interesting results • Importance branding – Brand essence, brand assets

• Importance theming – Decoration, macro theming, micro theming

Brand essence and brand assets

Brand Assets Efteling* • • • • • •

Fairy tales Enchantment Fantasy Mothering and caring Bonding Transformation

* Cornelis, P. (2006). Theme parks and branding. Presentation Tile Conference , Maastricht (Netherlands) ** Wiering, C. (2008). De Efteling: pretpark en TV-producent. Tijdschrift voor marketing, april 2008, 40-42.

Fairy-tale forest

Natural surrounding

PandaVision 3d/4d show

Dreamflight darkride

Component 1

Volk van laaf Python roller coaster Holle Bolle Gijs Fairytale forest PandaVision Steamtrain

,878 -,805 ,800 ,901

Principal component analysis with varimax rotation

6

,867 ,808

Component 1

Volk van laaf Python roller coaster Holle Bolle Gijs Fairytale forest PandaVision Steamtrain

,878 -,805 ,800 ,901

Principal component analysis with varimax rotation

6

,867 ,808

Three layers of a brand (Kapferer, 1996)

Brand essence concept

Brand essence

brand kernel

Brand style Physical brand identity

tone

code

style Brand themes

products

arguments

segments

Brand Assets Efteling* • • • • • •

Fairy tales Enchantment Fantasy Mothering and caring Bonding Transformation

Dreamflight

PandaVision

     

   / / 

* Cornelis, P. (2006). Theme parks and branding. Presentation Tile Conference ** Wiering, C. (2008). De Efteling: pretpark en TVproducent. Tijdschrift voor marketing, april 2008, 40-42. Source: Cornelis (2010c)

Macro and micro theming

Kind of park

Size of park

Theming component

Amusement park Theme park

Other parks

Name & Signage

Tangible theming

Landscaping

Entrance & external architecture Queue & internal architecture Ride / transport system Staff members

Live entertainment Sound / music Ambient conditions Food & Beverage/ merchandise locations

Top 10 parks

85.1

87.6

83.6

89.8**

44.2*

38.2

40.1

41.2

**

40.1

59.4***

19.2

26.8**

15.3

32.6***

84.4

85.4

85.3

84.6

0.7

27.3***

6.6

26.8***

0.0

1.8**

0.0

2.2***

44.6 components 52.8 -10

Intangible theming -20.3Storytelling 31.6 16.1 6.6 -12.3Secondary16.2 layer of meaning 5.8

***

38.5***

*

23.1***

6.6

0.9

12.0***

Table 2 Percentage applied theming component according to kind and size of park * = p