Analysis of Guests’ Expectations Using Negative Reviews Towards Theme Parks PDF Free Download
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Analysis of Guests’ Expectations Using Negative Reviews Towards Theme Parks
Jihee Park
Advisor: Dr. Andrei Kirilenko
College of Health and Human Performance
University of Florida
2
Abstract
Satisfying guests’ expectations has been the most important components in the service
and hospitality industry. Guests have high expectations for theme parks in all aspects of their
visit, including how crowded they are, price, facilities management, guest services, the
operations system, and much more. As the Internet has been used as a main resource for people
make their decisions on destinations to visit, people have been easily influenced by reviews on
online travel review websites. Thus, guest expectations have been reflected by online reviews
such as those published on TripAdvisor. TripAdvisor is one of the largest online travel review
websites that people rely on before visiting their destinations. Therefore, theme parks, one of the
main hospitality industries, have to be particularly conscious of negative reviews in order to
provide guests with a better quality of service and experience as well as attract more guests with
improvements based on guests’ complaints. This study uncovers some of the main topics of
negative reviews of different theme parks located in Orlando, Florida and aims to analyze
negative reviews on TripAdvisor to clearly understand the target market that visits destinations,
and ultimately help business providers to provide better service for future guests.
Introduction and Literature Review
Guest satisfactions have long been the most important element out of all other elements
for any business provider, especially in the hospitality and tourism industry, such as lodging
properties, restaurants, and theme parks. Guests’ reviews and comments have been widely used
by service providers as a primary source for identifying weaknesses or strengths of their overall
quality of service and to fully satisfy the needs of past and current guests, as well as the
expectations of future guests (Cadotte & Turgeon, 1988, p. 45). Since the hospitality and tourism
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industry is a guest-oriented industry, achieving and maintaining guests’ satisfaction is a key
challenge faced by service providers in the industry (Yen-Lun Su, 2004).
Among the hospitality and tourism industry, theme parks have grown and expanded
significantly, especially in the United States, for the past several decades. Statistically,
approximately 244 million people visited the top 25 most popular theme parks worldwide, and
the number of visitors has been constantly increasing (Street, 2018). Meanwhile, out of more
than 400 theme parks and attractions in the United States, a majority of the largest and the most
popular parks are located in Orlando, Florida. The three main theme parks that most people visit
in Orlando are Walt Disney World, Universal Orlando, and SeaWorld Orlando (Holcomb,
Okumus, & Bilgihan, 2010). As the theme park industry is rapidly growing and attracting a
significant number of tourists and visitors, it has become increasingly important for service
providers to thoroughly understand what guests want and to reflect their feedbacks efficiently to
enhance guests’ experience (Milman, Li, & Wang, 2012).
Recently, the Internet and social network websites have been rapidly applied to the
hospitality and tourism field, such as the lodging and theme park industry. In North America,
online travel sales reached 190.4 billion U.S. dollars in 2016 and were forecasted to be added up
to 232.49 billion U.S. dollars by 2021 (Tnooz, n.d.). Due to the accessibility and simplicity of the
Internet, tourists tend to search for online information that they need for travel and can be
significantly influenced by user-generated content (Ye, Law, Gu, & Chen, 2011).
Online travel review websites allow people to virtually navigate their travel destination
and make their decisions by looking at others’ reviews. There are numerous websites that publish
travel reviews, such as TripAdvisor, Travellerspoint, or Travelocity. TripAdvisor is an Internet-
based travel company headquartered in Needham, Massachusetts. TripAdvisor has grown to
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become the world’s most popular online travel website, and it had over 661 million user reviews
and opinions as of 2018, covering approximately 7.7 million hotels, inns, B&Bs, restaurants,
travel destinations, attractions, etc. (TripAdvisor Reports, 2018).
It has become obvious that a significant number of people utilize various online travel
review websites for their decision-making. According to the data gathered by TripAdvisor
(2017), 62% of all worldwide users started their decision process and subsequently booked travel
online in 2016. Furthermore, approximately 8 in 10 users (82%) agreed that the reviews
published on TripAdvisor helped them to plan better trips. Globally, 96% of global TripAdvisor
users considered reading reviews important when planning and booking hotels. Therefore, it is
imperative for major travel destinations such as theme parks and hotels to thoroughly analyze
and understand the reasons why people leave negative reviews and improve based on those
results (TripAdvisor Network, 2017).
There is a numerous number of direct or indirect factors that affected people to leave
negative reviews online for theme parks they visited. For example, according to the research
conducted by Geissler and Rucks (2011), 18 major attributes were developed: Landscaping, park
cleanliness, restroom cleanliness, signs/directions, employee courtesy, variety of attractions
available, restaurant variety, educational experience, fun experience, atmosphere of park, quality
of food, food price/value, gift quality, ride/show wait-lines, admission price value, satisfaction
with total cost, restaurant cleanliness, and taste of meals. Respondents rated these attributes
based on their overall experiences at theme parks.
To sum up, analyzing negative reviews on online travel review websites such as
TripAdvisor is essential for theme parks and other hospitality business providers in general, to
attract more guests by understanding previous guests’ needs as well as enhancing the overall
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quality of service for future guests. The research conducted by Smyth, Wu, and Greene (2010)
found that the improved information efficiency from online travel websites such as TripAdvisor
would significantly influence both people who were making decisions based on online reviews
and business providers who were seeking to improve their service quality, because the views and
opinions from guests would be rapidly spread out to a wide audience.
This research was conducted for the use of determining categories that might affect
people to leave negative reviews published on TripAdvisor in 2016 and analyzing how those
reviews were distributed based on those categories for three major theme parks located in
Orlando, Florida, which are Walt Disney World, Universal Orlando, and SeaWorld Orlando.
This research was non-experimental and produce correlational results. The subsequent sections
are organized as follows:
Data section shows how the original data was collected, the number of reviews and
reviewers, and the details of the data. It also briefly discusses the distribution of overall ratings
on TripAdvisor in 2016. Methodology section talks about how negative reviews were sorted
from the original data, how categories were developed to classify the negative reviews, the actual
categorization, and Pearson’s chi-square test of independence to see if negative reviews based on
parks and categories are significantly associated each other. Results section graphically shows all
the results collected from previous processes. It visualizes percentage of negative reviews,
distribution of negative reviews of each park, and the result of Pearson’s chi-square test of
independence. Discussion and conclusion section explain the reasoning behind the results of
each park and how this research might help business providers in the hospitality and tourism
industry.
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Data
In order to achieve the proper data needed to form a conclusion, the original data was
provided by Dr. Kirilenko which contains the total of 41,112 reviews and ratings collected from
TripAdvisor for the entire year of 2016. The original data includes 13 different columns total,
which are “id,” “name (of park),” “id2,” “moderation status,” “date published,” “review URL,”
“rating,” “language,” “title,” “text,” “author name,” “location,” and “trip type”. In this study,
only 5 columns, “id,” “name,” “rating,” “title,” and “text” were used out of 13 columns that are
necessary for the purpose of the study. Reviewers in the data are people who left their opinions
for parks as of 2016, and opinions and ratings of 20,390 individuals were collected for the
original data. The distribution of overall ratings is described in Figure 1. 27,289 people rated 5
(excellent) for six theme parks, 8,282 people rated 4 (very good), and 5,541 rated 3 or under
(from average to terrible).
Figure 1. Distribution of Ratings
0
5000
10000
15000
20000
25000
30000
12345
Counts
Rating
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Methodology
The goal of the analysis is established in the following ways:
1. Determine whether there is a significant association between negative reviews based on
parks and categories.
2. Determine whether distribution of negative reviews of each park is significantly different.
If so, how it is different from each other.
Data were analyzed in the following process:
1. Sorting reviews that have “negative” ratings from the original data
In order to process the analysis of negative ratings and reviews, “rating” column
in the original data that users rated from 1 to 5 (1 – terrible, 2 – poor, 3 – average, 4 –
very good, and 5 – excellent) was used. In this study, “negative review” was defined as
reviews ranged from 1 to 3 (1 being the lowest number and 3 being the middle number).
As a result, 5,541 negative reviews out of 41,112 total reviews were found with ratings
from 1 to 3.
2. Generating groups of random samples from the original data
Data distribution across the parks was highly skewed towards the most popular
parks. For example, 3,258 out of 5,541 negative reviews, which is approximately 59% of
all negative reviews, were related to the Walt Disney World (Table 3 and Figure 2). With
that being said, it was determined that the Walt Disney World would be separated into 4
individual parks, Magic Kingdom, Epcot, Hollywood Studios, and Animal Kingdom, to
match the overall ratio of negative reviews between all parks. Meanwhile, while
Universal Orlando also had two separate parks, it would be combined as “Universal
Orlando” because the number of its negative reviews did not exceed the half of the entire
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number of negative reviews (40%). The final dataset incorporated 3,258 negative reviews
for the Walt Disney World parks (1,300 reviews for Magic Kingdom, 691 for Epcot, 763
for Hollywood Studios, and 504 for Animal Kingdom), 1,680 negative reviews for
Universal Orlando, and 603 negative reviews for SeaWorld Orlando were collected
(Table 3).
Finally, in order to analyze the equal number of samples from each park, 300 was
determined as a sample size. 300 samples were randomly selected from the number of
negative reviews of each park using Excel.
3. Development of classification categories
Preliminary categories were developed before a list of categories was fully
created. According to the survey collected from Geissler and Rucks (2011), 18 categories
were developed to evaluate the overall theme park experience of visitors. 18 categories
are as follows: Landscaping, park cleanliness, restroom cleanliness, signs/directions,
employee courtesy, variety of attractions available, restaurant variety, educational
experience, fun experience, atmosphere of park, quality of food, food price/value, gift
quality, ride/show wait lines, admission price value, satisfaction with total cost, restaurant
cleanliness, and taste of meals. Based on these categories, full texts of subsets of samples
were thoroughly evaluated, and a list of categories was narrowed down to nine categories
total: express line management system, crowdedness, price, outdatedness, general
disappointment, guest service, operation, food, and other. Developed categories were
described in Table 1.
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Table 1. Comparison Between Original (Geissler and Rucks, 2011) and Developed Categories
Original Categories (Geissler & Rucks, 2011)
Developed Categories
Landscaping
Outdatedness
Park Cleanliness
Operation
Restroom Cleanliness
Signs/Directions
Employee Courtesy
Guest Service
Variety of Attractions Available
General Disappointment
Fun Experience
Educational Experience
Not Used
Restaurant Variety
Not Used
Taste of Meals
Food
Quality of Food
Food Price/Value
Gift Quality
Not Used
Ride/Show Wait Lines
Crowdedness (Wait Lines, Wait Times)/
Express Line Management System
Admission Price Value
Price
Satisfaction with Total Cost
Restaurant Cleanliness
Not Used
Atmosphere of Park
Not Used
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4. Development of a codebook and classification validation
In order to test the accuracy of selecting categories and classifying the negative
reviews, 100 samples of negative reviews from all four parks at Walt Disney World and
another 100 samples from SeaWorld Orlando were initially randomly selected and
classified. Sampled negative reviews were manually evaluated based on their full texts. A
codebook containing the detailed description of each category was created and provided
to a graduate student at the University of Florida to repeat the same process. The
acceptance level was preset prior to categorization. If the percentage of similarity
between both results is greater than 85%, it is expected to be reliable to proceed to
categorize 300 samples of each park. The comparison was completed by Excel, and the
accuracy percentage of categorization between them was 88% for Walt Disney World
and 92% for SeaWorld Orlando, respectively. Therefore, determined categories were
assumed to represent the reviews well, and it seemed that there is no problem to continue
to categorize full samples from each park. The created codebook and the detailed
explanation of each category are described in Table 2.
Table 2. A Codebook
Category #
Category Name (Label)
Description
1
Express Line
Management System
- There are three different express line
management systems for Walt Disney World,
Universal Orlando, and SeaWorld Orlando,
which are FastPass+, Express Pass, and Quick
Queue, respectively.
- Reviews about issues with systems (technical
issues, or other operation issues) listed above
fall under this category.
- Disney has its own versatile app service that is
linked to the FastPass+ system
(complimentary). Thus, comments regarding
Disney’s app service could be included in this
category.
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- Universal Orlando and SeaWorld Orlando do
not provide a virtual reserving system as of
2016. Thus, general reviews about express line
management system could be included in this
category.
2
Crowdedness
- Reviews which explain contents about
crowdedness and waiting would be included in
this category.
- Reviews containing words such as “how
crowded the park was,” “how packed the park
was,” “waiting lines to go on specific rides,”
and “wait time” fall under this category.
- This category also encompasses reviews about
“lines,” “number of strollers,” “number of
wheelchairs.”
3
Price
- Reviews which explain contents about price
and money would be included in this category.
- Reviews containing words such as
“overpriced,” “expensive,” “money-grabbing,”
“commercialized,” “waste of money,” “rip-
off,” “money,” “money-making machine,”
“additional charge” would fall under this
category.
4
Outdatedness
- Reviews which explain contents about old
facilities, dated attractions, and general
outdatedness would be included in this
category.
- Reviews including words such as “dated,”
“old,” “outdated,” “needs refreshment,” “needs
revamp,” “needs renovation,” “needs
refurbishment” would fall under this category.
5
General
Disappointment
- Reviews which show their general
disappointment towards parks are included in
this category.
- Reviews containing words like “mediocre,”
“nothing special,” “not good for certain ages
(kids, thrill seekers, teenagers, or adults),”
“lack of entertainment,” “not what they
expected,” “not much to do,” “boring,” “took
only half day or just a few hours” could fall
under this category.
- If they provided reviews for multiple
categories and an evaluator cannot decide
whether they fall to which category, it is
assumed as a general disappointment, so they
fall under this category.
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6
Guest Service
- If reviews complain about “rude employees,”
“employees are not smiling,” “employees are
not happy with their jobs” go under this
category.
- Reviews are related to customer service.
- Reviews complain about aggressive security
situations, racism, discrimination, bad
experience because of employees at parks.
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Operation
- Reviews are related to operation management
of parks.
- Reviews complain about technical issues of
attractions and rides, such as ride breaking-
down situations.
- Reviews complain about constructions,
renovations, refurbishment, etc.
- Reviews complain about park hours such as an
early close.
- If certain parks have animal issues including
words like “there are not a lot of animals,”
“it’s a cruel captivity,” “they need to be set
free” go under this category. Animal kingdom
reviewers complain about the issues after
riding on Kilimanjaro Safaris and SeaWorld
reviewers bring up issues after watching
animal-involved shows. Thus, those reviews
fall under this category.
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Food
- Reviews are related to the food quality (menu,
vegetarian menu, quality).
- Reviews complain about restaurant operation
in general.
- Reviews complain about its meal plan and
dining plan.
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Other
- Reviews that do not have any bad experience.
- Reviews including words such as “better than
expected,” “It was a good day overall” fall
under this category.
- If review provides some tips and
recommendations for future visitors, it goes to
this category.
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5. Classification (300 random samples for each park)
The randomly selected 300 negative reviews from each park (1,800 samples for
all six parks) were manually classified based on determined categories.
6. Distribution graphs and Pearson’s chi-square test of independence
When examining the data results, distribution graphs were obtained to show how
negative reviews are distributed by each category within each park and described in the
results section. Pearson’s chi-square test of independence using SPSS was also conducted
to statistically show if there is a significant association between the type of park and
determined categories. Furthermore, the test showed detailed percentages of negative
reviews by each category for each park (Table A-1). If the p-value found in the test is
greater than .05, the null hypothesis cannot be rejected, and it is concluded that there is
no significant difference between parks in what the people are complaining about. If it is
less than .05, the null hypothesis is rejected, and it is concluded that there is a significant
difference between parks in what the people are complaining about. This method was
chosen in order to create an unbiased, uniform evaluation of categorization results based
on statistical analysis.
Results
Distribution of Negative Review
Table 3 shows the percentage of negative reviews (ratings from 1 to 3) from overall
reviews (ratings from 1 to 5) for each park. The result states that Disney’s Hollywood Studios’
percentage of negative review is 23.98%, which is the highest percentage of negative reviews out
of six parks. Meanwhile, Universal Orlando’s percentage of negative reviews was the lowest,
which is 9.51%.
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Table 3. Percentage of negative review
Park
Total Reviews
Negative Reviews
Negative Reviews (%)
Magic
Kingdom
8,507
1,300
15.28
Epcot
4,325
691
15.98
Hollywood
Studios
3,182
763
23.98
Animal
Kingdom
3,722
504
13.54
Universal
Orlando
17,665
1,680
9.51
SeaWorld
Orlando
3,711
603
16.25
Total
41,112
5,541
100
Figure 2 shows that how negative reviews is distributed for each park. As previously
mentioned, the graph states that Hollywood Studios and Universal Orlando were the highest and
the lowest; other parks similar percentages of negative reviews (cir. 15%).
Figure 2. Overall Distribution of Negative Review
0
5
10
15
20
25
30
Magic
Kingdom
EPCOT Hollywood
Studios
Animal
Kingdom
Universal
Orlando
SeaWorld
Orlando
Percentage of Negative
Reviews (%)
Park
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Distribution
Plots from Figure 3 to Figure 8 were created to effectively demonstrate how the number
of negative review is distributed based on determined categories by each park. The x-axis is
“category,” and the y-axis is “number of negative review”. In x-axis, 1 denotes “express line
management system,” 2 denotes “crowdedness,” 3 denotes “price,” 4 denotes “outdatedness,” 5
denotes “general disappointment,” 6 denotes “guest service,” 7 denotes “operation,” 8 denotes
“food,” and 9 denotes “other”.
Figure 3 clearly shows that a significant number of negative review was classified as
crowdedness at Magic Kingdom. The second largest amount of negative review was classified as
general disappointment, otherwise, the rest of the categories had less than 40 negative reviews.
Figure 3. Distribution of Negative Review (Magic Kingdom)
Figure 4 shows that more than 140 negative reviews were classified as a general
disappointment. The second largest amount of negative review was classified as outdatedness,
otherwise, the rest of categories had less than 20 negative reviews.
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Figure 4. Distribution of Negative Review (Epcot)
Figure 5 shows that more than 180 negative reviews were classified as a general
disappointment. The second largest amount of negative review was classified as operation,
otherwise, the rest of categories were similarly distributed and had less than 40 negative reviews.
Figure 5. Distribution of Negative Review (Hollywood Studios)
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Figure 6 shows that almost 200 negative reviews were classified as a general
disappointment. The second largest amount of negative review was classified as operation,
however, the number of negative review of general disappointment is significantly higher than
the rest of the categories.
Figure 6. Distribution of Negative Review (Animal Kingdom)
Figure 7 shows that the largest amount of negative reviews was classified as a general
disappointment. The second largest amount of negative review was classified as price, however,
the number of negative review of the rest of categories except general disappointment is
relatively similarly distributed.
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Figure 7. Distribution of Negative Review (Universal Orlando)
Figure 8 shows that the largest amount of negative reviews was classified as a general
disappointment. The second largest amount of negative review was classified as operation, and
otherwise, the number of negative review of the rest of categories is relatively similarly
distributed compared to that of general disappointment and operation.
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Figure 8. Distribution of Negative Review (SeaWorld Orlando)
Pearson’s Chi-square Test of Independence
Pearson’s Chi-square test of independence was conducted to see if there is a significant
association or difference between negative reviews of park and category. Null hypothesis is that
there is no relationship between the negativity expressed in different categories and the parks.
Null hypothesis was rejected with p<0.001 (Table 4). Thus, it is concluded that there is a
significant difference between parks in what the people are complaining about.
Table 4. Pearson’s Chi-Square Test of Independence
Chi-Square Tests
Value
df
Asymptotic
Significance (2-
sided)
Pearson Chi-Square
635.729a
40
.000
Likelihood Ratio
560.735
40
.000
N of Valid Cases
1800
a. 12 cells (22.2%) have expected count less than 5. The minimum
expected count is 3.00.
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Figure 9 and Table A-1 show how the number of negative review for each park is
distributed based on determined categories using bar chart and percentage. According to Figure 9,
most of parks had their largest amount of negative review in category 5, which is general
disappointment. Animal Kingdom had the most number of negative reviews in category 5 among
them, which is 22%. Magic Kingdom had a significant amount of negative review in category 2,
crowdedness, compared to the other five parks, which is 52.2%. Universal Orlando had the
largest portion of negative reviews, 35.1%, in category 3, which is price, compared to other parks.
Epcot occupied 51.7% of negative reviews in category 4, outdatedness. Hollywood Studios and
SeaWorld Orlando both were significantly higher than other parks in category 7, operation,
which are 33.7% and 34.2%, respectively.
Figure 9. Distribution of Categories for Each Park
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Discussion
From the result of Pearson’s chi-square test of independence, it is statistically shown that
there is a significant difference between the parks in negative review categories. Furthermore,
plots and tables regarding distribution of negative reviews also showed that parks exhibit
significant differences regarding the negative review categories.
For example, Magic Kingdom showed the most significant percentage of 52.2% in
crowdedness out of all parks evaluated (Figure 9 and Table A-1). In addition, 44% of negative
reviews were classified as crowdedness within Magic Kingdom. Magic Kingdom is the main
park among four parks at Walt Disney World. Cinderella Castle is located in Magic Kingdom,
and it is known as the busiest park with lots of crowds regardless of the season. Crowds likely
cause delayed wait time and make queues longer. Therefore, the obtained statistical results
seemed to be reasonable that Magic Kingdom had the largest portion in crowdedness. The
company would need to consider methods that could limit the maximum capacity of guests that
could enter in the park at once.
Epcot showed the most significant percentage of 51.7% in outdatedness out of all parks.
Table A-1 also described that 24.7% out of overall negative reviews of Epcot complained about
outdatedness. Although Epcot had the largest percentage in general disappointment within its
own distribution, it also showed that its percentage of outdatedness was the most significant out
of other parks. Since Epcot, especially Future World at Epcot, had not gone through a major
renovation on its attractions and facilities for several decades, the majority of reviews pointed
out that Future World at Epcot would need a major refurbishment for future guests. Thus, the
company might need to consider upgrading attractions and facilities as well as the entire
atmosphere at Epcot to attract more guests.
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Hollywood Studios and SeaWorld Orlando both showed the most significant percentage
in operation out of all other parks. Since Hollywood Studios was under construction in 2016 for
Toy Story Land and Star Wars: Galaxy’s Edge, the majority of the park was closed for the public.
Reviewers complained that half of the park was closed, so there was nothing much to do after all.
Meanwhile, SeaWorld’s theme is mainly related to animals and the majority of negative
reviewers complained about the animal shows, such as the killer whale and dolphin show.
According to the codebook (Table 2), it is stated that attractions and shows fall under operation
category. Thus, statistical results and analysis show that a significant percentage of negative
reviews were under operation category for both of the parks.
Animal Kingdom showed the most significant percentage on general disappointment.
Since Animal Kingdom is the smallest park and the park that is the least related to the Disney’s
theme, negative reviewers complained about the size of the park, lack of entertainment, or two or
multiple complaints which fell under general disappointment. From these results, it seemed
reasonable for Animal Kingdom to receive the most significant amount of negative reviews on
general disappointment out of all parks. However, since The World of Avatar was built in 2018,
it is expected that negative reviews complaining about a lack of entertainment would be
significantly reduced.
Universal Orlando received a significant amount of negative reviews on general
disappointment (Figure 7). Compared to other parks (Table A-1), it received the largest
percentage of negative reviews on price. Since some reviews explained that there is a lack of
entertainment and attractions other than The Wizarding World of Harry Potter, improving the
overall entertainment quality of theme park could be one of major suggestions to the company.
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Conclusion
Based on the results obtained from the analysis of negative reviews and statistical data, it
was shown that each theme park had different and unique trends regarding the distribution of
negative reviews. From the analysis of reviews on TripAdvisor, we showed that most people’s
opinions are reflected by their online reviews. On top of that, most people rely on online reviews
when making their decisions on hotels, restaurants, attractions and travel destinations. Thus,
business providers are expected to clearly understand the reasoning behind guests’ complaints by
studying negative reviews. Furthermore, analyzing negative reviews on online travel review
websites such as TripAdvisor is essential for theme parks and other hospitality business
providers in general, to attract more guests by understanding previous guests’ needs as well as
enhancing the overall quality of services for future guests. For example, Magic Kingdom at
Disney could lower the maximum capacity of guests to decrease the number of complaints about
crowd size. Epcot at Disney could renovate their attraction and facilities so that they could
satisfy guests who complained about it being outdated. Through this research, business providers
in the theme park industry should be able to improve their quality of service for future guests and
satisfy guests’ expectations by applying lessons learned from the research.
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Appendix
Table A-1. Cross-Table Percentage of Negative Review
Category * Park Crosstabulation
Disney
SeaWorld
Orlando
Universal
Studios
Florida
Total
Animal
Kingdom
Hollywood
Studios
Epcot
Magic
Kingdom
Category
1
Count
4
2
1
11
1
6
25
% within Category
16.0%
8.0%
4.0%
44.0%
4.0%
24.0%
100.0%
% within Park
1.3%
0.7%
0.3%
3.7%
0.3%
2.0%
1.4%
% of Total
0.2%
0.1%
0.1%
0.6%
0.1%
0.3%
1.4%
2
Count
22
23
19
132
12
45
253
% within Category
8.7%
9.1%
7.5%
52.2%
4.7%
17.8%
100.0%
% within Park
7.3%
7.7%
6.3%
44.0%
4.0%
15.0%
14.1%
% of Total
1.2%
1.3%
1.1%
7.3%
0.7%
2.5%
14.1%
3
Count
16
8
21
25
26
52
148
% within Category
10.8%
5.4%
14.2%
16.9%
17.6%
35.1%
100.0%
% within Park
5.3%
2.7%
7.0%
8.3%
8.7%
17.3%
8.2%
% of Total
0.9%
0.4%
1.2%
1.4%
1.4%
2.9%
8.2%
4
Count
9
14
74
20
17
9
143
% within Category
6.3%
9.8%
51.7%
14.0%
11.9%
6.3%
100.0%
% within Park
3.0%
4.7%
24.7%
6.7%
5.7%
3.0%
7.9%
% of Total
0.5%
0.8%
4.1%
1.1%
0.9%
0.5%
7.9%
5
Count
199
181
152
89
141
141
903
% within Category
22.0%
20.0%
16.8%
9.9%
15.6%
15.6%
100.0%
% within Park
66.3%
60.3%
50.7%
29.7%
47.0%
47.0%
50.2%
% of Total
11.1%
10.1%
8.4%
4.9%
7.8%
7.8%
50.2%
6
Count
12
3
14
13
19
20
81
% within Category
14.8%
3.7%
17.3%
16.0%
23.5%
24.7%
100.0%
% within Park
4.0%
1.0%
4.7%
4.3%
6.3%
6.7%
4.5%
% of Total
0.7%
0.2%
0.8%
0.7%
1.1%
1.1%
4.5%
7
Count
28
66
9
5
67
21
196
% within Category
14.3%
33.7%
4.6%
2.6%
34.2%
10.7%
100.0%
% within Park
9.3%
22.0%
3.0%
1.7%
22.3%
7.0%
10.9%
% of Total
1.6%
3.7%
0.5%
0.3%
3.7%
1.2%
10.9%
8
Count
5
0
3
3
7
0
18
% within Category
27.8%
0.0%
16.7%
16.7%
38.9%
0.0%
100.0%
% within Park
1.7%
0.0%
1.0%
1.0%
2.3%
0.0%
1.0%
% of Total
0.3%
0.0%
0.2%
0.2%
0.4%
0.0%
1.0%
9
Count
5
3
7
2
10
6
33
% within Category
15.2%
9.1%
21.2%
6.1%
30.3%
18.2%
100.0%
% within Park
1.7%
1.0%
2.3%
0.7%
3.3%
2.0%
1.8%
% of Total
0.3%
0.2%
0.4%
0.1%
0.6%
0.3%
1.8%
Total
Count
300
300
300
300
300
300
1800
% within Category
16.7%
16.7%
16.7%
16.7%
16.7%
16.7%
100.0%
% within Park
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
100.0%
% of Total
16.7%
16.7%
16.7%
16.7%
16.7%
16.7%
100.0%
