The Demographic Effect on the Performance Level of Private Clubs

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  • This article was downloaded by: [California Poly Pomona University]On: 15 October 2014, At: 16:31Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH,UK

    Journal of Hospitality & LeisureMarketingPublication details, including instructions forauthors and subscription information:http://www.tandfonline.com/loi/whmm19

    The Demographic Effect on thePerformance Level of PrivateClubsRaymond R. Ferreira PhD, MBA, BA a b c da Cecil B. Day School of Hospitality Administration ,Georgia State University, College of BusinessAdministration , University Plaza, Atlanta, GA,30303-3083, USAb University of Maryland , USAc University of Minnesota , USAd Rutgers University , USAPublished online: 20 Oct 2008.

    To cite this article: Raymond R. Ferreira PhD, MBA, BA (1998) The DemographicEffect on the Performance Level of Private Clubs, Journal of Hospitality & LeisureMarketing, 5:4, 23-32, DOI: 10.1300/J150v05n04_03

    To link to this article: http://dx.doi.org/10.1300/J150v05n04_03

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  • The ~ e m o ~ r s ~ h i c Effect on the Performance Level

    of Private Clubs R a y m o n d R. Ferreira

    ABSTRACT. This study explored which dcmographic variables had the largest intluence on five different financial perforn~ance mcasure- menis (total revenue, dues incomc, initiation feesideposits, average mcmber spending, and gross operating profits) and thc number of full- privilege members for private clubs (e.g., country clubs, city-dining clubs, yacht clubs, and athletic clubs). Data was collected from 58 private clubs in eleven major cities across the United States. The vari- ance in four of the six private club performance measurements could be explained from the demographic variables measured within a ten mile radius of the club. The percentage of variance explained by the demo- graphic variables for the following performance measurcrnents: initia- tion feesJdeposits, number of full-privilege members, total revenue, and average member spending, was between 49 and 61 peicent. [A~.licle copies uvuiluble for u fee from Tlte Huwo,?h Doc~ime~rf Delive~y Savice: 1-800-342-9678. E-muil udd~zss: ~e~i~~fofb@l~owor~lr~re~si~~c.co~n~

    KEY WORDS. Private club, marketing, demographics, membership

    INTRODUCTION

    T h e location of a business can often be the key component in determining the success or failure of that business. Location, or place

    Raymond R. Ferreira is Assistant Professor in the Cecil B. Day School of Hos- pitalit; Administration at Georgia State University, College of ~us;liess Administra- tion, University Plaza, Atlanta, GA 30303-3083. He holds a PhD from the University of Maryland, an MBA from the University of Minnesota, and a BA from Rutgers University and is a member of the Club Managers Association of America, the American Marketing Association, and the Council on Hotel, Restaurant, and Institu- t io~~al Education.

    Journal of Hospitality Sr Leisure Marketing, Vol. 5(4) 1998 O 1998 by Tl~c Haworth Press, Inc. All rights reserved. 23

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  • 24 .lOURNAL OF HOSPITALITY& LEISURE MARKETING

    as it is referred to in the marketing mix, is also one of the key compo- nents in the development of a marketing strategy for a business or organization. The location of the business can be a strength, a weak- ness, or have no effect on that business. Many hospitality businesses are somewhat dependent on their locations. A hospitality business location could be considered a strength due to a number of reasons: its proximity to a customer's place of business, its proximity to a custom- er's place of residence, its convenience to or from one's residence, the physical beauty of the location, etc. (Lewis, Chambers, & Chacko, 1995; Kotler, Bowen, & Makens, 1996).

    Another important factor for hospitality businesses, such as restau- rants, in regard to their location, is that many customers are only willing to travel a certain distance to purchase the businesses' prod- ucts. Often, if the market is not near the business' location, i t will not travel or travel as frequently to purchase the product. Therefore, in selecting a location, most businesses would prefer a location that is close to the market i t is serving. Determining if the market segment a business wants to capture is present in that location is a difficult procedure. Some hospitality businesses have been able to identify their market segment based on demographic descriptors: age, gender, profession, income level, etc. (Andreasen, 1988).

    The hospitality industry's reliance on demographic description of its market segment has led many large hospitality businesses to make key decisions on acquisitions and development of properties based on the demographics of the location being considered. Some restaurant franchises mandate that any location being considered for acquisition or development first have a demographic profile developed before spending any additional resources or development time onthe project (Melaniphy, 1992). This typically involves acquiring the demograph- ics within a certain radius, such as 3 miles, to determine if there is a sufficient number of households within a certain income level, if there are enough businesses in the area, if there are enough people workitlg in the area, if there is enough traffic flow past the proposed locatio;, etc. The minimum demographic requirements are often derived from a company's records and demographic profiles of its successful and unsuccessful ventures. These demographic numbers are placed in the company's model to forecast potential sales for a proposed location (Melaniphy, 1992).

    There have been very few academic studies completed with private

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  • Ruynzorrd R. Ferreiru 25

    clubs in the hospitality industry. Furthermore, because of the exclusive nature of private clubs, the topic of marketing is one that many clubs have been reluctant to address. Many private clubs, today, find that they do not have a waiting list for members and that revenues have declined because of the following factors: overbuilding of private clubs, poor economics, companies downsizing management positions, companies moving from downtown areas to the suburbs, more com- petition from other hospitality businesses, etc. (Coyne, 1992).

    A recent survey conducted by the Club Managers Association of America (CMAA) indicated that the marketing and selling of member- ships was a high priority for club managers in that association. This interest in the marketing of private clubs to increase membership has occurred recently. The majority of clubs across the country are now seeking members, whereas a decade ago these same clubs had a waiting list of individuals wanting to be members. Less members result in a decrease in revenues, initiation fees, dues income, covers, etc., and possi- bly a decrease in gross operating profit for the club (Ferreira, 19971-3).

    An analysis of the variables that could possibly influence the mem- bership size and financial performance of a private club is needed, given the state of the industry. Information on market penetration rates, market share and the impact of demographics is not available in the private club industry (Ferreira, 1997a). The purpose of this study was to address some of these important issues.

    The intent of this project was to explore which demographic vari- ables had the largest influence on different performance measurements for private clubs (e.g., country clubs, city-dining clubs, yacht clubs, and athletic clubs). This study investigated if there were any relation- ships between select demographic variables and various financial per- formance nleasurements and the number of members at private clubs in eleven major cities across the United States.

    RESEARCH OBJECTIVES

    The intent of this study was to answer the following questions:

    Which demographic variables, if any, account for the variance in a club's membership size? (These variables were measured within a ten mile radius of the private club.) The demographic variables collected at a ten mile radius from the clubs were the number of:

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  • 26 JOURNAL OF HOSPITALITY& LEISURE MARKETING

    Residents Owner occupied households Properties of over $150,000 in value Households with over $100,000 income Businesses CEOslexecutives/professionals Individuals with a college degree

    Which demographic variables have any relationship with the fol- lowing financial performance measurements at private clubs?

    Total revenue Total initiation fees/deposits Dues income Average member spending Gross operating profit

    The general hypothesis for this study is that the different perfor- mance levels for private clubs will be influenced by certain demo- graphic variables within a ten mile radius of the club.

    METHODOLOGY

    The subjects were 58 proprietary private clubs (country clubs, city clubs, city-athletic clubs, and yacht clubs) that have been in operation for five or more years located in the following greater metropolitan areas:

    Atlanta, GA Austin, TX Charlotte, NC Chicago, IL Cincinnati, OH Dallas, TX Houston, TX Los Angeles, CA Phoenix, AZ San k ~ t o n i o , TX Tampa, FL

    The demographic information for each of the private club's location was provided by Equifax's National Decision System's (NDS) market research branch. The southwest regional headquarters of Club Corpo- ration of America (CCA) provided information on the six annual performance measurements for the 58 clubs they own or manage in those eleven cities.

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  • The data collected ,from the private clubs and the demographic variables for each club were entered in a computer data file. The data was analyzed using the SPSSIPCt statistical package (Norusis, 1992). Significant relationships among the performance measurements and the demographic variables were explored through correlation coeffi- cients and stepwise regression analysis.

    RESULTS

    Table 1 displays the means and standard deviations for the six performance variables and seven demographic variables for the 5 8 private clubs. Table 2 lists the correlation values among the variables. The following statistically significant correlations existed between the dependent (performance) variables and the independent (demograph- ic) variables. Initiation feesldeposit significantly correlated with household income levels (.71) and property values (.67). The tzumber of full-privilege members significantly correlated with the number of businesses (.63), property values (.S8), owner occupicd households (.57), number of CEOs/executives (.56), and household income levels

    TABLE 1. Private Club Variables

    Characteristic n Mean Std. Dev.

    Performance Variables

    Initiation FeesiDeposit 58 $282,946.14 $344,964.93 Dues Income 58 $1,628,263.40 $1,435,807.88

    Number of Fuil-Privilege Members 58 91 4.66 984.99 Total Revenue 58 $1,741,971.70 $1,092,045.34

    Average Member Spending 58 $1,612.62 $1,088.18 Gross Operating Profits 58 $1,087,914.10 $1,143,716.33

    Demographic Variables Within Ten Mile Radius

    Residential Population Owner Occupied Households

    Property Values Household Income Levels

    Number of Businesses Number of CEOslExecutives Number with College Degree

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  • 28 JOURNAL O F HOSPITALITY LQ LEISURE MARKETING

    TABLE 2. Correlation of Private Club Variables

    Variables Correlation Coefficients

    Performance Variables 1 Intiation FeaiDeposit - 2 Dues Income ,637 -

    X

    3 Number of Full- .21 .68 - Privilege Members **

    4 Total Revenue .69 .77 .41 - X X

    5 Average Member .22- .17 -29 .26 - Spending

    6 Gross Operating 6 1 .93 5 0 .84 -.09 - Profits X X X X

    Demographic Variables 7 Residential Population .14-.16 .17 .21 .19- .14 - 8 Owner Occupied .22 .18 .57 .61 .41 .19 .39 -

    Households ** **

    9 Property Values .67 .12 .58 .47 .62 .09- .12 .47 - +, +, +,

    10 Household Income .71 - .O1 .55 .41 .62 .17- .09 .43 .50 - Levels * ... ...

    11 Number of Businesses .09 .I1 -.63 .66 - . I0 .18 .19 .16 .17 .08 - ... * 12NumberofCEOs -.07-.04 .56 .32 .14 .13 .09 .21-.14 .04 .44 -

    Executive/Mgrs. ft 13 Numberwithcollege .15 .09 .04 .19 .18 .08-. l l '.09-.03 .07 .17 .51 -

    Degree

    ** Significant at ,001 level

    (.55). To~ul revenue was significantly related to the number of busi- nesses (.66) and owner occupied households (.61). Average member sperzdirzg highly correlated with property values (.62) and household income levels (.62).

    Dues income only had significant correlation values with other performance variables and not with any demographic variables: gross operating profit (.93), total revenue (.77), number of full-privilege members (.68), and initiation feestdeposit (.67). Gross operating profil had significant correlation values only with performance variables as

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  • well: dues income (.93), total revenue (.84), number of full-privilege members (.60), and initiation feesldeposit (.61).

    The variance in four of the six priva...

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