Predicting Attendance ABsTRAcT At southeastern U.s. This research examines the extent to which Amusement Parks traditional geographic concepts of proximity can explain attendance to amusement parks Using Accessibility- and in the Southeastern United States. Accessi- Amenity-Based Models bility models were calculated for nineteen parks using both miles and driving times as James Andrew McCall measures of distance from population cen- Miami-Dade County Park & Recreation ters. Results show only weak relationships Department between attendance and distance from popu- Miami, Florida 33128 lation. To test whether other factors are more important predictors of attendance, regres- Joe Weber* sion analysis was carried out using variables Department of Geography describing amenities and characteristics of University of Alabama the parks. The results show that a high level Tuscaloosa, AL 35487 of explanation for attendance to parks is E-mail: [email protected] provided by ticket price, parking cost, the number of years the park has been open, and centrality within the Southeast. Geographic proximity to population does not appear to be important to park attendance. Key Words: Amusement Parks, Accessibil- ity, Distance, Attendance INTRodUcTIoN Tourism in the Southeast has been associ- ated with all manner of colorful and well- known attractions and locales, including not only Disney World but the beach resorts of the Florida panhandle (Hollis 2004), Mam- moth Cave in Kentucky (Algeo 2004), the Smoky Mountains (Tooman 1997), assorted roadside and urban attractions (Jakle 1985; Hollis 1999; Newman 1999; Starnes 2003), and amusement parks. The latter can be de- fined as entertainment-oriented businesses, usually requiring admission fees, containing attractions, rides, food, and shopping, and other entertainment (Adams, 1991). These amusement parks are enclosed and separated from the tasks of everyday life, and range in size from small family-owned business to vast corporate parks. Theme parks involve the application of an overall theme to a particular amusement park. In the early twentieth century amusement park development was strongly tied to local * Corresponding author urban populations, but since the 1950s the The Geographical Bulletin 47: 45-59  ©2006 by Gamma Theta Upsilon James Andrew McCall and Joe Weber rebirth of the park industry has been tied ments, to European pleasure gardens from more to automobile travel and regional or the eighteenth and nineteenth centuries, even international tourist travel (Adams and to the Chicago Columbian Exposition 1991). Increasing ease of long distance travel, of 1893 (Adams 1991; Younge 2002). This and the growth of tourist complexes centered Exposition included the first Midway with around beaches, national parks, or large cities food and themed entertainment as well as has made any expectation that local popula- an overarching theme for the entire event. tions will make up a large component of total The first enclosed amusement parks with attendance appear doubtful. Despite this, rides, games, food, and other entertainment proximity to population remains a concern appeared on Coney Island in the 1890s, and for amusement park operators (Adams 1991). these soon spread throughout the country This research will examine accessibility of (Adams 1991). These early parks were located theme parks to the surrounding population within urban areas at locations well served by in the Southeast U.S. and relate this to at- streetcar or subway lines (and in fact were tendance, with the goal of understanding the often created by streetcar lines to generate importance of population proximity to park passengers), and benefited from shorter attendance patterns. working weeks and rising incomes during the early 20th century. By 1920, there were ThEME PARk dEvEloPMENT IN as many as 2000 amusement parks in the ThE soUThEAsTERN U.s. U.S., but they began a steady decline through The origins of amusement parks have the automobile era, Great Depression, the been traced back to medieval trade fairs Second World War, and the television era that became popular for their entertain- (Adams 1991). Figure 1: Amusement Parks in the Southeastern United States  Predicting Attendance At Southeastern U.S. Amusement Parks Using Accessibility- and Amenity-Based Models The return of the amusement parks to plans to build Disney America in Virginia, importance, or, in the terminology of the but abandoned the idea after strong public destination life-cycle model, their rejuvena- opposition (Moe and Wilkie 1997). tion (Butler 1980; Tooman 1997), is due to GEoGRAPhIc ANAlysIs of ThEME Disneyland and the success of theming, with PARks their attention to a safe, clean environment, and a mix of rides and attractions for all Tourist oriented areas, including amuse- family members (Adams 1991). New parks, ment and theme parks, have been examined often controlled by large corporations, soon from a range of perspectives in recent decades followed, with the 1970s seeing the construc- (Jakle 1985; Adams 1991; Marling 1997; tion of most of the postwar theme parks now Young 2002). Theme parks, especially Dis- operating. Many of these parks cater to va- neyland and Disney World, have attracted cationers from distant locations rather than a great deal of attention for how they have local residents, and are typically located in been designed, their impact on guests, and a suburban location, adjacent to freeways. for their economic and political impact on Since the opening of Disneyland, no new surrounding communities (Zukin 1991; theme park has succeeded in a traditional Findlay 1992; Sorkin 1992; Francaviglia urban location (Adams 1991). 1996; Warren, 1996; Archer 1997; Marling Within the Southeast United States a 1997; Foglesong 2001; Mannheim 2002; number of amusement parks exist (Fig. 1). Young and Riley 2002). Critiques of down- There is great diversity among these parks, town commercial-entertainment districts in from small family-owned facilities to large large cities have used the metaphor of theme corporate structures. Six Flags Over Georgia parks to describe these areas and the way they opened in 1967 outside of Atlanta and was structure activities (Warren 1994; Hannigan the first modern theme park in the Southeast 1998; Young 2002; Bryman 2004). Theming (Adams 1991). Parks in this area range in size is not limited to amusement parks or down- from the five-acre Family Kingdom Amuse- towns, and can be applied to entire cities ment Park in Myrtle Beach, South Carolina, or small towns, such as the UFO-oriented to Paramount’s colossal 400-acre King’s theme developed for Roswell, New Mexico Dominion amusement park in Richmond, (Paradis 2002). Virginia. There is also great variation in the Rather than examining the cultural mean- number of rides and attractions offered at ing and design of theme parks, the goal here each park (Table 1). Several of the smaller is to better understand attendance and their parks contain only one roller coaster and a relationship to local population patterns. few adult rides. Large corporate parks owned There is a limited amount of geographical by Six Flags and Paramount have as many as research and analysis of amusement park at- twelve roller coasters and as many as thirty tendance patterns in the U.S., and no recent adult rides and attractions. studies have been published on amusement In addition, at least eighty Southeastern park attendance. This research addresses this amusement parks have closed their gates in shortage by examining the extent to which the twentieth century (Samuelson and Ye- traditional geographic concepts of proximity goiants 2001; Styer 2005). Even with close are useful for explaining yearly attendance proximity to urban populations, at least five to amusement parks in twelve states of the amusement parks built in Atlanta failed, Southeastern U.S. Given the increasing scale while Nashville also experienced at least five of amusement parks, the greater the distance closings. Baltimore has been historically the they attempt to attract visitors from, and worst place in the Southeast to build amuse- the longer time these visitors will remain, ment parks, with at least twelve defunct it is tempting to ask whether traditional ap- parks. In addition, there have been failed proaches to accessibility will remain relevant attempts to create new parks, as when the to them. An analysis of attendance at amuse- Walt Disney Company announced in 1993 ment parks is also useful because it provides  James Andrew McCall and Joe Weber Year Data Available 2002 2002 2002 2002 2002 2002 2002 2002 2002 1997 2002 2002 2002 2001 2000 2002 2001 2002 2002 hops 0 9 1 9 0 1 0 1 1 3 2 7 10 16 12 19 4 0 6 S nts a aur 0 6 1 8 0 1 0 7 0 17 30 7 24 15 16 21 5 2 19 est R hows no yes yes yes no yes yes yes yes yes yes yes yes yes yes yes yes no yes S r e at by WPark no yes no yes yes no no no yes no yes yes yes yes no yes yes yes yes r a e N Adult Rides 12 8 15 11 12 6 16 7 12 12 11 18 20 19 17 21 11 6 26 oller asters 1 6 3 3 2 2 3 3 5 6 11 12 9 7 6 9 2 1 9 Ro C e Annual Attendanc 400,000 2,600,000 105,000 2,300,000 80,000 140,000 375,000 250,000 280,000 2,000,000 1,850,000 2,090,500 1,550,000 1,200,000 1,095,000 2,250,000 400,000 175,000 1,250,000 n e p ys O 95 167 93 215 200 135 80 65 60 145 120 130 135 145 122 151 105 150 304 a D d e n Ope 898 975 903 961 992 961 925 976 978 972 973 975 982 990 000 967 998 987 997 r 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 a Ye e rk SizAcres) 368 360 26 100 5 67 150 88 140 70 105 400 345 59 140 245 70 20 170 Pa( - h D eristics of Soutent Parks Location Bowling Green, KY Williamsburg, VA Huntington, WV Pigeon Forge, TN Myrtle Beach, SC Maggie Valley, NC Rossville, GA Memphis, TN Hot Springs, AR Nashville, TN Charlotte, NC Doswell, VA Upper Marlboro, M Louisville, KY New Orleans, LA Austell, GA Bessemer, AL Gulf Shores, AL Valdosta, GA Table 1. Characteastern Amusem Amusement Park Beech Bend Park Busch Gardens Williamsburg Camden Park Dollywood Family Kingdom Amusement Park Ghost Town in the Sky Lake Winnepesaukah Amusement Park Libertyland Magic Springs Opryland USA Paramount’s Carowinds Paramount’s King’s Dominion Six Flags America Six Flags Kentucky Kingdom Six Flags New Orleans Six Flags Over Georgia Visionland Waterville USA Wild Adventures Theme Park  Predicting Attendance At Southeastern U.S. Amusement Parks Using Accessibility- and Amenity-Based Models a perspective on the aspects and amenities at More recently, Meyer-Arendt (1997) used parks that are most attractive to visitors. a version of the traditional gravity model to explain attendance at casinos in Mississippi. dIsTANcE, PoPUlATIoN, ANd This strongly suggests that amusement parks AccEssIBIlITy To ThEME PARks can be examined in the same fashion, with Proximity to population is of fundamental parks being patronized primarily by local concern to theme park developers and op- populations. Both travel costs (measured erators, with close populations given greater linearly with distance) and area and ameni- weight than more distant potential visitors. ties of water recreation sites were found to For example, the local population might be be important (Siderelis and Moore 1998). counted “within radiuses of 25, 50, 100, and Travel times have been used to predict at- 150 miles of a potential site” (Adams 1991, tendance at recreation sites with some suc- p. 109). A market penetration model refines cess (Brainard, Lovett, and Bateman 1997). this into the primary, secondary, and tertiary This study used estimates of highway driving markets (Miami Metrozoo 2003). The size of time and the origin locations of visitors to each market area is based on the percentage a park. It can be expected that incorporat- of residents who will visit an attraction. The ing information about the attractiveness of primary market for a theme park might be a recreation destinations as well as the presence radius of 25 miles, while the secondary market of competing destinations will improve such would include the population between one an approach. and two hours driving time, and the tertiary However, there are increasing reasons to market consists of populations (especially in suspect that traditional proximity-based ap- larger cities) located between three and four proaches might no longer be valid in the case hours driving time away. The tertiary market of theme parks. The growth of commercial is however quite variable, with little or none air travel and the construction of the Inter- for a small attraction, and the entire world state Highway System have shrunk travel for Disney World. times between cities, resulting in space-time However, the use of discrete distance inter- convergence (Janelle 1968). This has been vals can be problematic, for it has been shown mapped for the Southeast U.S., showing in a wide variety of situations that interaction greatly reduced driving times between 1950 falls off at a non-linear rate, an effect com- and 1975 (Carstensen 1981). In response to monly known as distance decay. This idea faster speeds of travel (resulting in greater ac- has long been a part of recreation planning cessibility to major cities), amusement parks (Clawson and Knetsch 1966; Hanink and in larger cities may experience increased pa- White 1999). One study concluded that, tronage due to a wider area from which to “The average number of trips made to Six draw visitors. Similar issues apply to tourist Flags Over Georgia in 1968 decreased accord- attractions that increasingly function on a ing to an exponential function as the travel global scale (Williams 1998). time to Six Flags Over Georgia increased” An important issue with tourism is that (Dyer 1970, p. 33). In their study of the ef- travel can be an important and valued part fects of distance on travelers’ attendance to of the vacation experience, and so cannot the Great Smoky Mountains National Park, necessarily be expected to show a distance Cole and Mitchell (1969, p. 14) conclude decay effect for all forms of travel (Hanink that attendance is “a negative function of and White 1999). In the case of theme parks, distance.” However, in another study it was which may be infrequently visited or are found that distance decay had only limited part of a larger vacation, this appears to be power to explain attendance, in this case to a strong possibility. While this is very likely a Saudi Arabian national park, due perhaps the case with Disney World and adjacent to the uneven local population distribution parks, it may also be the case for many other and importance of distant urban populations Southeastern parks. A shrinking importance (Paul and Rimmawi 1992). for distance could also be the result of the  James Andrew McCall and Joe Weber increasing role of new and larger attractions on proximity to population. Two parks are at parks. Theme parks increasingly compete located adjacent to the Great Smoky Moun- by building new rides, especially thrill rides tains National Park, which is the most visited such as roller coasters (Newman 2004). National Park in the country and clearly an These new rides are essential for attracting ideal place to attract tourists. repeat customers (Braun and Soskin 1999), Since Florida has many large amusement whose loyalties may not be based on prox- parks, it may seem unusual that it is not in- imity. These conflicting possibilities for the cluded. However, several of Florida’s amuse- importance of proximity to population will ment parks, especially Walt Disney World be tested with data about amusement park in Orlando, are attractive globally, whereas attendance in the Southeast. most parks in the study are attractive only regionally. Consequently, the inclusion of sTUdy AREA ANd dATA amusement parks in Florida would greatly This study examines amusement parks skew the results. In addition, three parks were located in the Southeastern United States, excluded because they offer free admission excluding those in Florida. Amusement parks and are located along public piers that also were identified as entertainment-oriented at- contain restaurants, clubs, and shopping tractions that charged admission and had at attractions. Yearly attendance estimates for least one roller coaster. There are nineteen these piers were reported in local papers, but amusement parks distributed throughout the it is impossible to know how many of the twelve states of this area, with the majority people that visited the pier actually visited of the parks located near large cities (Table the amusement park. Finally, one additional 1). This is not surprising given the emphasis park was excluded because no attendance es- Figure 2: Attendance at Amusement Parks Figure 2: Attendance at Amusement Parks 0 Predicting Attendance At Southeastern U.S. Amusement Parks Using Accessibility- and Amenity-Based Models timates were found and park officials refused Another set of accessibility models have to release attendance data. While Opryland is been termed population potential or Hansen no longer open, it represents a modern and measures, first developed in the 1940s (Pooler recently operating theme park and so was 1987) and suggested as an accessibility mea- included in the study. sure by Hansen (1959). These measures take For each park, the attendance data used into account not only the distance from the in the analysis were for the most recent year origin to destinations, but the size of destina- available. Figure 2 shows attendance at parks tions. In this case, the closer a park is to more in the study area. Tourist attendance is vola- and larger population centers, the higher its tile over time, and related to many factors accessibility. The population potential model that extend beyond the attributes of the des- can be written as follows: tination (Frechtling 2001). This represents P the effective demand, and not the potential A = k j demand for these destinations, represented i D b by the total population interested in attend- ij ing such a park (Hall and Page 1999). While where accessibility of park i is equal to the there are several variables that could be used sum of the population of each center (Pj) di- to represent attendance, here the number of vided by distance from the park to that center visitors per year is used. (Dij b). k represents a calibration constant. Finding attendance data for amusement Distance is raised to a power represented parks can be quite troublesome, as “many by b, which allows for non-linear distance amusement parks by policy do not reveal or decay. This is similar to the formulation of report attendance figures even to industry distance decay in gravity models for spatial associations . . .” (Adams 1991, 168). The interaction, with higher b values meaning following sources were used to compile atten- that accessibility will fall off more rapidly dance data: Amusement Business (ten parks), with distance. articles in local papers furnished by local This population potential accessibility visitors’ centers and tourism development measure has been used in many recreation councils (seven parks), and phone interviews applications, including accessibility to golf with public relations personnel (two parks). courses (Mitchelson and Lazaro 2004), and the accessibility of national parks to popu- AccEssIBIlITy of lation (Hanink and White 1999; Hanink soUThEAsTERN PARks and Stutts 2002). It has been suggested for Accessibility is a fundamental concept in evaluating the accessibility of wilderness areas geography, which in its traditional proximity- to population, although because support for based form relates a set of origin locations to wilderness areas tends to be greatest among one or more destination locations (Pirie 1979; those living farthest away, multiplying the Kwan and Weber 2003). A number of different attractiveness of the wilderness by distance accessibility measures exist, depending on how could actually give a more suitable measure they take into account distance and whether for the value of wilderness to society (Hanink they incorporate the size of the destination. 1995). The Shimbel or network accessibility measure, The population potential model was cal- which was first introduced to geography by culated using ArcView 3.2 Geographic In- a pioneering analysis of accessibility in the formation System (GIS). County centroids Southeast (Garrison 1960), measures the were used to represent population centers, highway distance from each city to all other using population values from the 2000 cities. Lower total mileage values represent Census. A short script was written to allow greater accessibility to other cities. This has ArcView to calculate population potential been a common means for measuring accessi- models between each amusement park and bility among cities (Gauthier 1968; Murayama every county in the study area. To account 1994; and Spence and Linneker 1994). for visitors to parks from outside the study  James Andrew McCall and Joe Weber area, a 200-mile buffer was created around models there has been considerable discus- the entire study area, and counties inside this sion about the proper b value (Pooler 1987; buffer added to those in the Southeast. Mikkonen and Luoma 1999). Because there Both highway mileage and driving time is no expectation about exactly at what rate were used to represent distance. Doing so proximity to population will decrease as a allows some indication of how households potential influence on park attendance, b choose parks. While travel times to parks can parameters ranging from 1 to 3 were used be important given long trips, mileage may for mileage, and 1 to 2 with travel time. If be of more importance to households on long distance is cubed instead of being squared in vacations. In both cases the 2003 National the model, lower predictions of attendance Transportation Atlas Database (Bureau of should result. Transport Statistics 2003), which includes EXPlAINING AMUsEMENT PARk GIS representation of all major highways ATTENdANcE in the Southeast, was used for the highway network. Because there is no highway driving The accessibility results were tested to see time data present in this dataset, travel times whether variations in attendance were strong- were estimated for each highway link. To do ly related. Pearson correlation analysis was this, average driving speeds were estimated used to test the accuracy of the population for different classes of roads, a common ap- potential accessibility model predictions with proach at the interurban level (Carstensen the actual yearly attendance data for each 1981; Brainard, Lovett, and Bateman 1997). park. Network distances and travel times Average speeds of 62.3 mph were computed were used, with several beta values (Table 2). for Interstates and 52.1 mph for other major The best results were obtained with linear dis- highways based on average values for these tance, which shows very clearly that distance highways throughout the Southeast (Rand decay is not as great a factor for amusement McNally 2004). These average speeds were park attendance as it is for other kinds of converted to driving times and assigned to all trips (Hanson and Schwab 1995). However, links in the street network database. because amusement park trips are likely to In addition to calculating population be rare for most households, it should not potential using travel times and miles, ac- be surprising that other considerations are cessibility was measured using different far more important. For travel times a beta distance decay values. In the case of gravity exponent of 1 again provided the most accu- rate prediction of attendance to amusement Table 2. Results of Correlation Analysis parks in the Southeast. The fact that travel time provides a higher level of explanation than distance must be due to the uneven- ness of travel times on the highway system, Measure of Correlation as expected from space-time convergence Distance Beta Value Coefficient (Carstensen 1981). Miles 1 0.485a Although proximity to population pro- Miles 1.5 0.457a vides a moderate level of explanation for at- tendance, a variety of other factors can also Miles 2 0.397 be expected to contribute to attendance at Miles 2.5 0.362 amusement parks. These could include an Miles 3 0.347 amusement park’s location near physically attractive features like beaches or mountains; Travel Time 1 0.488a the possibility of attending an adjacent water Travel Time 1.5 0.456a park, restaurants, or shopping center; elabo- Travel Time 2 0.397 rate marketing schemes by parks and local tourism developers; incentives to bring large a Statistically Significant at p <=.05 institutionalized tourist groups to the park; 2 Predicting Attendance At Southeastern U.S. Amusement Parks Using Accessibility- and Amenity-Based Models cheaper admission rates for senior citizens open for longer periods during the year and for stays longer than one day; and the should attract more tourists. Ownership by appeal of amusement parks as a perfect fam- a larger corporation such as Six Flags would ily vacation destination. These are a more likely be associated with a park being bet- restricted set of variables than might be used ter known and as a indicator of quality and for more general tourism studies, but include satisfaction. As all of these parks are seasonal, destination attractiveness, distance, and price the number of days each operated per year (Frechtling 2001). And like national parks, was included, with the expectation that amusement parks include a wide range of longer seasons should be related to higher features that appeal to different segments attendance. Price information includes adult, of the tourist market, making it difficult to child, senior admissions, season pass, and select variables (Hanink and White 1999). daily parking fees. The lower these prices, Although most of these parks do not reach the greater the expected attendance. the level of publicity of Florida’s large theme Variables were also included describing at- parks, it may be that they draw on popula- tractions present in the parks. The number of tions well beyond those found locally. Strong roller coasters, rides for adults and children, loyalties or preferences to particular parks presence of a nearby water park, shows, res- might also account for attendance patterns taurants, and shops were included. Adding that are not based on distance. new rides and attractions is essential to allow- These possibilities were explored using ing a park to stand out from the competition, stepwise multiple regression analysis. Al- and make the park more appealing as a family though tourist attendance is commonly mod- destination and as a repeat destination (New- eled and predicted using time series analysis man 2004; Cobb 2005). It can be expected (Frechtling 2001), a regression analysis with that the presence of more of these amenities a range of geographical data is used here, and features will have a positive effect on since the goal is not to predict attendance attendance. The population potential ac- based on past patterns, but instead to relate cessibility measures discussed earlier were attendance to cross-sectional explanatory included in the regression model. Shimbel variables. As the attributes of visitors, or accessibility was also included, representing their origin locations, are not available, the the total distance from each park to all county analysis necessarily focuses on destination centroids. A high accessibility value for this attributes (Table 1). Yearly attendance at measure indicates a park is less central, as it each of the nineteen amusement parks in has a higher total mileage from the park to the study area was the dependent variable, all county centroids, and vice versa. with 34 independent variables describing Stepwise regression produced a model that amenities and attractive characteristics of the used five variables to explain attendance to parks (Table 3). Independent variables were amusement parks in the Southeastern U.S. obtained from the websites and brochures for (Table 4). These variables are the adult-one each individual park. The 34 independent day admission price for each park, daily variables for each park fit into five general parking fees, year the park opened, a coding groups: 1) General park information; 2) Park for the year parks opened, and the network admission price information; 3) Accessibility; accessibility of each park. Although the 4) Park ride information; and 5) Park attrac- limited number of parks in the Southeast tions and amenities. The original continuous allows for a small number of observations, data were also recoded to create seventeen the overall model was significant and the categorical variables to better isolate parks model has a very high level of explanation with similar features. for park attendance (R2 = 0.953). However, As with national parks (Hanink and White interpretation of the explanatory variables is 1999), it is expected that older theme parks not straightforward. will be more widely known. Larger parks Surprisingly, variables describing the at- should offer more attractions, while those tractions and amenities offered in the park  James Andrew McCall and Joe Weber Table 3. Regression Variables Variable Description Park Size Acres CODE Park Size <100 acres=1, 101-199=2, 200-299=3, ≥ 300=4 Year Opened Year CODE Year Opened Before 1945=1, 1946-1977=2, 1978-2003=3 Length of Operating Season Days of Operation per Year CODE Operating Season 1-99 days=1, 100-150=2, 151-199=3, ≥ 200=4 CODE Owned by Corporation NO=0, YES=1 CODE Owned by Six Flags NO=0, YES=1 Adult 1-Day Admission $ CODE Adult 1-Day Admission 0$=0, 1-19=1, 20-29=2, 30-39=3, 40-49=4, ≥ 50=5 Child 1-Day Admission $ CODE Child 1-Day Admission 0$=0, 1-16=1, 17-26=2, 27-34=3, ≥ 35=4 Senior 1-Day Admission $ CODE Senior 1-Day Admission 0$=0, 1-16=1, 17-26=2, 27-34=3, ≥ 35=4 Season Pass Price $ CODE Season Pass 0$=0, 1-49=1, 50-79=2, 80-105=3, ≥ 106=4 Parking Fees/Day $ CODE Parking Fees/Day 0$=0, 1-4=1, 5-8=2, 9-12=3 Population Potential Accessibility Network Accessibility Number of Roller Coasters CODE # of Roller Coasters 1=1, 2-5=2, 6-8=3, ≥ 9=4 Number of Adult Rides CODE # of Adult Rides 1-5=1, 6-10=2,11-15=3, 16-20=4, 21-25=5, ≥ 26=6 Number of Child Rides CODE # of Child Rides 1-5=1, 6-10=2,11-15=3, 16-20=4, 21-25=5, ≥ 26=6 CODE Nearby Water Park NO=0, YES=1, OCEANFRONT=2 Shows Number of shows in park CODE Shows NO=0, YES=1 Restaurants Number of restuarants and food stands in park CODE Restaurants 0=0, 1-5=1, 6-10=2, 11-15=3, ≥ 16=4 Shops Number of shops in park CODE Shops 0=0, 1-5=1, 6-10=2, ≥ 11=3 CODE Conventions, Catering 0=NO, YES=1 do not show up. Instead, the most important a relationship between willingness to pay a variable in the regression analysis is the adult high fee and satisfaction from previous vis- one-day admission charge. Adult one-day ad- its (or expectations prior to a visit). Higher mission price is directly related with yearly priced parks therefore reflect high demand attendance at each park. This must indicate based on their attractiveness. This is surpris-