Pieter Cornelis NHTV Breda University - IAAPA - The

The impact of new attractions

Pieter CornelisNHTV 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 3 min.

• How can the effects of new attractions be explained? 15 min.

• Q&A 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

# %

2009

# %

2010

# %

Total

# %

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

Source: Pieter Cornelis (2010d)

For water rides please refer to

ewrdb.com

Source: AECOM (2010)

Long-term importance Short-term importance

Factor % 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

Perceived importance of new attractions

Source: Cornelis (2009)

Source: Poiesz & Van Raay (2002)

Vicious price circleLower

price premium

Decreasing

added value

Less investment

opportunity

Less profit

possibilities

price

innovation distribution

communication

Vicious marketing circles

Predicting the unpredictable?!

Production of meaning

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

Dynamics of theme park developmentby world region

Water parks versus theme parks…?!

Source: Anton Clavé (2007)

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)

The Number of Visitors to

(European )Theme ParksNew Attraction

Uncontrollable

•Income

•Relative prices

•Cost of travelling

•Vacations

•National Holidays

•Weekend days

•Temperature

•Precipitation

•Etc.

•Price Policy

Controllable

•Marketing expenditures

•Opening days

•Opening hours/day

•Special events

•Hotel accommodation

•Number of shows

•Number of F&B outlets

•Etc.

•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.)

Direct effect

Moderating effect

Backx, R. and Cornelis, P. (2006).

Force of attraction. Tilburg University.

4 year = 40 cents

5 year = 50 cents

6 year = 60 cents

7 year = 70 cents

8 year = 80 cents

9 year = …

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

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

Summation of all

variables in model

Short term effect Long term effect

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

Cornelis (2010)

New attraction + 10%

Rule of thumb?!

Cornelis (2010a)

First year 65%

Second year 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%

Every three years 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%

* 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

Important variables

European Pleasure Garden Amusement Park

Theme park Cinema/ movie

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

response

Economic

response

Brand

response

Park

response

Before Long termShort termDirect

Attraction/ area

Individual response

Aggregated 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.

Natural surroundingFairy-tale forest

PandaVision3d/4d show

Dreamflightdarkride

Volk van laaf

Python roller coaster

Holle Bolle Gijs

Fairytale forest

PandaVision

Steamtrain

,878

-,805

,800

,901,867

,808

Component

1 6

Principal component analysis with varimax rotation

Volk van laaf

Python roller coaster

Holle Bolle Gijs

Fairytale forest

PandaVision

Steamtrain

,878

-,805

,800

,901,867

,808

Component

1 6

Principal component analysis with varimax rotation

Three layers of a brand (Kapferer, 1996)

tone code style

brand

kernel

products arguments segments

Brand essence

Brand style

Brand themes

Brand essence concept

Physical

brand identity

Brand Assets Efteling*

Dreamflight PandaVision

• Fairy tales

• Enchantment

• Fantasy

• Mothering and caring /

• Bonding /

• Transformation

* Cornelis, P. (2006). Theme parks and branding.

Presentation Tile Conference

** Wiering, C. (2008). De Efteling: pretpark en TV-

producent. 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 Top 10 parks

Name & Signage 85.1 87.6 83.6 89.8**

Landscaping 44.2* 38.2 40.1 41.2

Entrance & external architecture 44.6 52.8** 40.1 59.4***

Queue & internal architecture 19.2 26.8** 15.3 32.6***

Ride / transport system 84.4 85.4 85.3 84.6

Staff members 0.7 27.3*** 6.6 26.8***

Live entertainment 0.0 1.8** 0.0 2.2***

Sound / music 20.3 31.6*** 16.1 38.5***

Ambient conditions 12.3 16.2* 6.6 23.1***

Food & Beverage/ merchandise

locations

5.8 6.6 0.9 12.0***

Table 2 Percentage applied theming component according to kind and size of park * = p<0.10 (two-sided test); ** = p<0.05 (two-sided test); *** = p<0.01 (two-sided test)

Tangible theming-10 components

Intangible theming- Storytelling

- Secondary layer of meaning

Source: Cornelis (2010d)

Kind of park Size of park

Theming component Amusement park Theme park Other parks Top 10 parks

Name & Signage 85.1 87.6 83.6 89.8**

Landscaping 44.2* 38.2 40.1 41.2

Entrance & external architecture 44.6 52.8** 40.1 59.4***

Queue & internal architecture 19.2 26.8** 15.3 32.6***

Ride / transport system 84.4 85.4 85.3 84.6

Staff members 0.7 27.3*** 6.6 26.8***

Live entertainment 0.0 1.8** 0.0 2.2***

Sound / music 20.3 31.6*** 16.1 38.5***

Ambient conditions 12.3 16.2* 6.6 23.1***

Food & Beverage/ merchandise

locations

5.8 6.6 0.9 12.0***

Table 2 Percentage applied theming component according to kind and size of park * = p<0.10 (two-sided test); ** = p<0.05 (two-sided test); *** = p<0.01 (two-sided test)

0 points no theming

1-3 decoration

4-10 macro theming

4-10 + eye for detail micro theming

Source: Cornelis (2010d)

Kind of park Size of park

Theming component Amusement park Theme park Other parks Top 10 parks

Name & Signage 85.1 87.6 83.6 89.8**

Landscaping 44.2* 38.2 40.1 41.2

Entrance & external architecture 44.6 52.8** 40.1 59.4***

Queue & internal architecture 19.2 26.8** 15.3 32.6***

Ride / transport system 84.4 85.4 85.3 84.6

Staff members 0.7 27.3*** 6.6 26.8***

Live entertainment 0.0 1.8** 0.0 2.2***

Sound / music 20.3 31.6*** 16.1 38.5***

Ambient conditions 12.3 16.2* 6.6 23.1***

Food & Beverage/ merchandise

locations

5.8 6.6 0.9 12.0***

Table 2 Percentage applied theming component according to kind and size of park * = p<0.10 (two-sided test); ** = p<0.05 (two-sided test); *** = p<0.01 (two-sided test)

Theming top20 parks Europe 2010

Source: Cornelis (2010d)

Kind of park Size of park

Theming category # attr. Mean

Year 1

Mean

Year 2

AP

Year 1

TP

Year 1

Small

Year 1

Large

Year 1

Micro theming 5 15.0% 10.2% -- 15.0% 18.5% 12.7%

Macro theming 13 9.6% 5.9% 14.5% 7.4% 10.2% 9.3%

Decoratie 14 9.2% 3.5% 12.6% 4.7% 9.4% 9.0%

No theming 4 7.5% 3.1% 7.5% -- 9.0% 7.0%

36 10.0% 5.3% 11.8% 8.5% 10.9% 9.3%

Impact new attraction

Source: Cornelis (2010d)

Motivation

Capacity

Ability

Three conditions for effective theming processing

Wrap up

• What’s the importance?

– Many new rides & slides

– High investments

• What are the effects?

– Contextual

– Include right variables

• How to explain?

– Branding

– Theming Predicting the unpredictable…?!

cornelis.p@nhtv.nl pcmcorne

www.pietercornelis.com

pieter cornelis

Q&A