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Kinesiology Faculty Publications Department of Kinesiology and Health

2005

Statistical Data Analysis Techniques Employed in Sport Marketing Statistical Data Analysis Techniques Employed in Sport Marketing

Quarterly: 1992 to 2004 Quarterly: 1992 to 2004

Jerome Quarterman

Brenda Pitts Georgia State University, bpitts@gsu.edu

E. Newton Jackson University of North Florida, newton.jackson@unf.edu

Kyoungtae Kim

Jongback Kim

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Recommended Citation Recommended Citation Quarterman, J., Pitts, B. G., Jackson, E. N., Kim, K., & Kim, J. (2005). Statistical data analysis techniques employed in the Sport Marketing Quarterly 1992 to 2002. Sport Marketing Quarterly, 14 (4), 227-238.

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Sport Marheting Quarterly, 2005, 14, 227-238, © 2005 West Virginia University

Statistical Data Analysis TechniquesEmployed in Sport MarketingQuarterly: 1992 to 2004

Jerome Quartcrman, Brenda G. Pitts, E. Newton Jackson, Jr., Kyoungtae Kim, and Jongback Kim

AbstractThis investigation was an assessment of data analysis

statistical techniques used in Sport Marketing Quarterly(SMQ) from 1992 to 2004. In 159 quantitative databased articles reviewed, 360 uses of statistical dataanalysis techniques were identified. The techniqueswere classified by type of statistical data analysismethod as descriptive statistics, parametric statistics,and nonparametric statistics. One half (50.00%) wereused as descriptive statistics, 41.94% as parametric sta-tistics, and less than one tenth (8.06%) as nonparamet-ric statistics. Percentages and frequencies were themost frequent descriptive statistics used to answer theresearch purposes, questions, and/or hypotheses by theresearchers of SMQ for this period. One-way ANOVAand regression analysis were the most frequent para-metric statistics used and chi-square was the most fre-quent nonparametric statistic used. The intent of this

Jerome Quarterman, PhD, is an associate professor ofsport management at Florida State University. Hisresearch interests include study of individual behaviors ofmanagers who practice in organizations oj the sportindustry.

Brenda G. Pitts, PhD, is a professor of sport manage-ment at Georgia State University. Her research interestsinclude sport marketing, sponsorship, and consumerbehavior.

E. Newton Jackson Jr., PhD, is an associate professoroj sport management and chair of the Department ojHPER at Florida A&M University. His research interestsinclude sport marketing and the social and culturalaspects of sport.

Kyoungtae Kim, is a doctoral student at Florida StateUniversity. His research interests include service market-ing and statistics.

Jongback Kim, PhD, is a researcher at Korea SportScience Institute. His research interests include servicequality and consumer behavior.

"One way to measure progress and credibility in arelatively new and emerging field is to periodicallyconduct a comprehensive critical self-examinationof the academic literature, such as research topics,methodology, and statistical techniques used in the

new and emerging field ..."

investigation was to provide undergraduate and gradu-ate students, their instructors, and other scholars withan overview of the most frequently used statistical dataanalysis techniques used in SMQ during its first 13years. In addition, this study has provided some insightinto the directions of the research conducted in sportmarketing studies from a research methodology stand-point. For a new and developing academic area such assport marketing, it is important for its consumers toknow how such an area advances relative to itsresearch methods.

IntroductionResearch in sport marketing has a relatively short

history. The launch of the Sport Marketing Quarterly(SMQ) as the first research journal for the discipline ofsport marketing in i992 was important in developingsport marketing research. Prior to the founding ofSMQ, research related to sport marketing was pub-lished in journals specializing in general marketing orfeatured in sport study related journals. Although sportmarketing is now recognized as an emerging field ofstudy, it is still young when compared to its founda-tional discipline, marketing, or to other related fieldssuch as business.

During the past decade, published research in thefield of sport marketing studies has grown significant-ly. The recent formation of the Sport MarketingAssociation (SMA) is indicative of the growing recog-nition of sport marketing as a field of study, as well asa sign for an increased awareness of the need for morerigorous research in the area of sport marketing. The

Volume 14 • Number 4 • 2005 • Sport MarHeCing Quarterly 111

vision statement of the SMA is to "expand the body ofknowledge in the sport marketing field, disseminatingthe resulting research findings and market-orientedsolutions via mass as well as targeted media sources,internal and external to the Association" (SMA, 2003,p. 1). Several scholars in sport management haveemphasized that more rigorous research is needed forthe development and credibility of a new field (Barber,Parkhouse, & Tedrick, 2001; Olafson, 1990; Parkhouse,Ulrich, & Soucie, 1982; Paton, 1987; Zakrajsek, 1993).Therefore, like any new and emerging academic field,sport marketing must strive for credibility and accept-ance by more established disciplines such as marketingand management. Without a rigorous approach toresearch, sport marketing as a new and emerging fieldof study may not survive in the higher education enter-prise. One way to measure progress and credibility in arelatively new and emerging field is to periodicallyconduct a comprehensive critical self-examination ofthe academic literature, such as research topics,methodology, and statistical techniques used in thenew and emerging field (Crawford-Welch & McCleary,1992; Reid & And'ereck, 1989; Riddick, DeSbriver, &Weissinger, 1984). Indeed, it has been noted that sportmanagement academics should seek methods toenhance tbe scbolarsbip in sport management (Parks,1992}. Numerous scholars in sport management havestated that the literature should be evaluated to helpdetermine its state and to detect development needs(Barber, Parkbouse, & Tedrick, 2001; Chclladurai,1992; Olafson, 1990; Parks, 1992; Paton, 1987; Pitts,2001). Indeed, "a body of knowledge that includes allknown facts, theories, and principles about a subject isnecessary for tbe continued and sustained growth of anacademic field" (Pitts, 2001, p. 88).

Sport Marketing Quarterly (SMQ)Currently, SMQ is recognized as tbe central forum of

conceptual and empirical research in sport marketingstudies. Founded in 1992, SMQ was the first and solesport marketing specific outlet tor scholarly articles inthe area of sport marketing. It is a refereed journalthrough wbicb theory development and research aredisseminated to individuals interested in sport market-ing. As stated inside the front cover of each issue, thepurpose of SMQ is to "provide a publishing outlet fortbe dissemination of sport marketing information forboth practicing professionals and academicians"(SMQ, 2004, p. 1). These two important constituenciesnow have an opportunity to develop a relationship thatis intended to be mutually beneficial. For practitioners,SMQ provides a vehicle to sbare marketing successeswith peers. For academicians, SMQ provides a forumfor sharing research. A variety of colleges and universi-

ties and individuals in the United States, Canada, andmany foreign countries subscribe to SMQ.

Conceptual Relevance for Examining theLiterature in Sport Management

One of the pioneers of the sport management field ofstudy once stated "Any profession must have a soundbody of knowledge to under gird it if it is to survivewith its professional status fully recognized by society"(Zeigler, 1987, p. 15). Scholars in sport managementare just now beginning to examine its literature criti-cally to determine its state and investigate whereimprovements can be made. It has been stated that"Academic journals mirror tbe direction of a disci-pline's research" (Van Doren & Heit, 1973, p. 67).Moreover, "improvement of any discipline is partiallydependent on an appraisal of the past; therefore, tbeneed to examine tbe methodological quality ofresearch reported in academic iournals" (Barber,Parkbouse, & Tedrick, 2001; Hoyer, Raskind, &Abrahams, 1984; Riddick, Deshriver, & Weissinger,1984; Stokes & Miller, 1975). Various scholars haveexamined tbe state of tbeir journals and other litera-ture in tbeir disciplines via content analysis and a vari-ety of other research methodologies (Bagloglu &Assante, 1999; Barber, Parkbouse, & Tedrick, 2001).Therefore, critical examination of the literature in afield is needed to assist its growth and development.

Until recently, there has been no critical examinationof sport management or sport marketing journals.Those recent studies include examinations of tbe fol-lowing journals and one study of sport managementtextbooks. Tbe first known study of a sport manage-ment journal was by Barber, Parkhouse, and Tedrick(2001) on the journal oj Sport Management and pub-lished in July 2001. Soon after, another study byPedersen & Pitts (2001), a content analysis of the SportMarketing Quarterly, was published in September,2001. Another study by Pitts and Pedersen (2003)involved an examination of the Journal of SportManagement and was presented at a conference in June2003. A study of the new Journal of Sports Economicswas conducted and published by Mondello andPedersen (2003) in February 2003. Further, a study ofsport management books has been undertaken and waspresented at a conference in September, 2004 by Pittsand Danylcbuk (2004). Prior to these studies on sportmanagement iournals and books, there was examina-tion of and reviews of sport management dissertationabstracts (Parkhouse, Ulrich, & Soucie, 1982), otherpublished abstracts (Paton, 1987); sport managementarticles and dissertations (Cornwell & Maignan, 1998;Douvis & Douvis, 2000; Olafson, 1990; Pope, 1998;Shannon, 1999); sport management conference

228 Volume 14 • Number 4 • 2005 • Sport Marheting Quarterly

abstracts (Soucie & Dohcrty, 1996); and, subjectivedescriptive reviews of sport management journals andtextbooks (Mahony & Pitts, 1998; Slack, 1996).

It is the more recent research that is the beginning ofcritical examination of the sport management litera-ture. These studies incorporated various researchmethodologies and were focused on various aspects ofthe journals. Barber et al, (2001) studied the researchmethodologies used in the studies published in theJournal of Sport Management. Pedersen and Pitts(2001) used content analysis to examine numerousaspects of the Sport Marketing Quarterly. Pitts andPedersen (2003) and Mondello and Pedersen (2003)also used content analysis to examine a variety ofaspects of the Journal of Sport Management and theJournal of Sports Economics, respectively.

''After a comprehensive literature search, theauthors discovered that an increasing number ofinvestigations of this type have been conducted inseveral academic fields and disciplines, and thatthere are the beginnings of examination of sport

management literature."

All investigators in all of the aforementionedresearch called for further critical examination of thesport management literature. Indeed, they suggestedthat every type of literature be examined critically witha variety of methods for a more complete examinationof the literature. In addition, there is precedent torconducting this type of research. Most fields of studyhave done so with the goal of ascertaining the state oftheir literature and, perhaps more importantly, indetermining weaknesses and strengths in the literature.Therefore, there is a need to critically examine all ofthe literature in sport marketing to help determine itscurrent state and identify strengths and weaknesses sothat scholars and academics can begin to strengthenthe literature.

Moreover and specifically, the conceptual relevanceused to guide this investigation was grounded in thecomponents of quantitative research methodology(Creswell, 2003} and the basic methods and techniquesused for understanding research results (DePoy &Gitlin, 1994; Gall, Gall, & Borg, 2003; McMillan &Schumacher, 2001; Neuman, 2003). Usually six toeight typical components make up quantitativeresearch methodology: research design, independentand dependent variables, population and sample size,sampling method and techniques, data collection pro-cedures, psychometric measurements (validity andreliability), instrumentation, and statistical data analy-sis techniques (Baumgartner, Strong, & Hensley, 2002;Cozby, 1992; Greswell. 2003; DePoy & Gitlin, 1994).

This investigation focused on the latter component,statistical data analysis techniques.

The statistical data analysis for the current investiga-tion was adopted from research methodology and sta-tistics textbooks and classified into three distinctgroups: descriptive statistics, parametric statistics, andnonparametric statistics (DePoy & Gitlin, 1994; Gall etal., 2003; Hinkie, Wiersma, & Jurs, 1994; Howell, 1999;Leedy & Ormrod, 2001; McMillan & Schumacher,2001; Neuman 2003).

Descriptive statistics refer to techniques used todescribe and summarize data. Parametric and non-parametric statistics are used for making inferenceabout the characteristics of a pt)pulation itself or asample of such population known as inferential statis-tics. The distinction made between the two subsets isdetermined by the scales of measurements (e.g., nomi-nal, ordinal, interval, and/or ratio) when measuringthe study variables in a research investigation (Gall etal., 2003; Hinkie et al., 1994; Leedy & Ormrod, 2001;McMillan & Schumacher, 2001; Neuman, 2003). Table1 presents a summary of the three groups of statisticalmethods, their definitions, and related techniques asoperationalized in the current investigation.

"In 159 articles analyzed, there were 360 uses of sta-tistical techniques. Many of the articles used more

than one statistical technique; therefore, the numberof techniques exceeded the number of articles."

Literature Review

After a comprehensive literature search, the authorsdiscovered that an increasing number ot investigationsof this type have been conducted in several academicfields and disciplines, and that there are the beginningsof examination of sport management literature.Educational psychology surfaced as the first disciplineof which data were tabulated and classified based on thetypes of statistical techniques used in its scholarly jour-nals. Previous tabulations of statistical data analysistechniques have been found in such professional jour-nals as the American Psychologist (Edgington, 1974); theAmerican Educational Research Journal (AERJ; Wilson,1980); the Journal of Educational Psychology (Goodwin& Goodwin, 1985a); and the Educational Researcher(Elmore & Woeklke, 1988; Goodwin & Goodwin,1985b). Two of the latest studies have been conductedwithin the last 10 years. Baumberger and Bangert(1996) analyzed and coded the type of research designand statistical techniques published in the Journal ofLearning Disabilities (JLD) from 1989 through 1993.Based on their findings, more than one half (55%) ofall the statistical techniques used in the JLD were coded

Volume 14 • Number 4 • 2005 • Sport MarHeting Quarterly 229

Table 1A Summary of Statisticai Data Anaiysis Techniques and Procedures

Technique

Descriptive statistics

Parametric statistics

Nonparametric statistics

Definition

Techniques for describing, organizing,and summarizing numerical data{Gall, Gall, & Borg, 2003; Kirk, 1978;Runyon, Coleman, & Pittenger, 2000)

Inferential statistical techniques usedfor making inferences about apopulation itself or a sample of suchpopulation when data have beenmeasured on an interval or ratio scale(Conover, 1999; Gall, Gall, & Borg, 2003;Hinkle, Wiersma, & lurs, 1994; Howell,1999; McMillan & Schumacher, 2001;Neuman, 2003)

Inferential statistical techniques usedfor making inferences about apopulation itself or a sample of suchpopulation when data have beenmeasured on an nominal or ordinalscale (Conover, 1999; Gall, Gall, & Borg,2003; Hinkle, Wiersma. & Jurs, 1994;Howell. 1999; McMillan & Schumacher,2001; Neuman, 2003)

Example

Mean, mode, median, variance,standard deviation, range, percentage, frequency, and rank

t test, ANCWA, MANOVA,ANCOVA, MANCOVA,correlation, regression, trendanalysis, discriminant analysis.cluster analysis, multidimensionalanalysis, path anaiysis, structuralequation model, conjoint analysis.and Z score

Chi square, Mann-Whitney,Kruskal Wallis, and Spearman rankcorrelation

as primary. 32% as intermediate, and the remaining14% as advanced statistical techniques. ANOVA wasthe most frequently used technique. Kieffer, Reese, andThompson (2001) examined 756 articles published inthe AERf and in the Journal of Counseling Psychology(JCP) over a 10-year period. They found that certaintechniques (e.g., ANOVA and ANCOVA) were usedproportionately less frequently than previously foundin tbe earlier studies by Goodwin and Goodwin (1985a,1985b) and Wilson (1980).

Other scholars have also evaluated statistical dataanalysis methods and techniques in marketing research(Grazer & Stiff, 1987), tourism research (Dann, Nash,& Pearce, 1988; Reid & Andereck. 1989), clothingresearch (Kang-Park & Sieben, 1993), hospitality man-agement research (Baloglu & Assante, 1999), and recre-ational management research (Jamieson. Ross, &Swartz, 1994). In the latter study, Jamieson et al. (1994)conducted a content analysis of all articles published inthe National Intramural, Recreational Sport Association(NIRSA), the Journal of Sport Management, and pub-lished proceedings from the NIRSA annual conferencesbetween 1986 and 1993. A major result of this studysbowed that descriptive statistical tecbniques (i.e., the

measures of central tendency and variability) were mostfrequently u.sed by tbe researchers of NIRSA.

Baloglu and Assante (1999) analyzed 1,073 articles infive hospitality management journals over a seven-yearperiod from 1990 to 1996. Tbe findings revealed thatdescriptive statistics were used extensively across allpublications; however, multivariate or inferential sta-tistics showed an incremental increase over the periodstudied. Kang-Park and Sieben (1993) also identifiedtbe statistical techniques used by the authors in articleson the social psychological aspect of clothing between1970 and 1985. Tbey grouped tbe techniques into fourlevels: basic, intermediate, advanced, and nonparamet-ric procedures. The major findings of their studysbowed basic techniques were used by nearly one balf(48.3%) of tbe authors, intermediate techniques bynearly one fourth (23.3%), and advanced techniquesby less than one tenth (8.9%) of the authors.

When critically looking at tbe literature of the previ-ous studies, they all used an arbitrary process of classi-fying the statistical techniques by degree of complexityas basic, intermediate, or advanced. Tbis system wasrecommended by Goodwin and Goodwin (1985a.1985b). While tbis system corresponds to a course of

230 Volume 14 • Number 4 • 200S • Sport Marheting Quarterly

progression in statistics, the criteria for such classifica-tion became problematic when reporting and dis-cussing the results of major findings. Logically, thesystem may cause one to raise questions such as: Is thedegree of complexity based on the case of which a sta-tistic can be computed? or Is the degree of complexitybased on the simplicity or complexity of the outdateddue to technological advances for computing data atthe current time? For example, during the 1980s, factoror discriminant analyses may have been viewed asadvanced statistical analyses; however, currently suchtechniques may be considered as basic techniques. Outof such concerns, the authors of the present investiga-tion decided to use a different approach for classifyingthe statistical data analysis techniques. The conceptthat guided the current investigation was adopted fromresearch methodology textbooks; the techniques wereclassified as descriptive statistics, parametric statistics,and nonparametric statistics (see Table 1; DePoy &Gitlin. 1994; Gall et al., 2003; McMillan &Schumacher, 2001; Neuman, 2003).

In sport management, as previously mentioned, suchcritical review of the literature is just beginning. Indeed,perhaps critical examination of sport management liter-ature can be a new focus of research in the sport man-agement field. To date, five studies have beenconducted on specific sport management journals andbooks. This important research will help guide futureresearchers and sport management journal editors andeven publishers in determining the direction of andenhancing the state of the sport management literature.

Purpose and Significance of the StudyThe purpose of this study was to examine specific

aspects of one scholarly journal in sport marketing, theSport Marketing Quarterly. To date, this type ofresearch has not been conducted. Therefore, the resultsof such examination can significantly inform the stateof this journal based on the examined characteristics.This information is important to guide academics,practitioners, and scholars interested in sport manage-ment and specifically in addressing the needs of the lit-erature. For instance, the findings of such analysis ofthe state of the literature might (1) provide foundationdata from which future directions of the literature maybe considered; (2) provide information for course con-tent in graduate level research methods courses insport marketing; (3) provide information for a mini-mum level of knowledge and understanding of statisti-cal data analysis techniques used in sport marketingstudies; (4) provide research information for sportmarketing faculty development for those who teachstudents in research methods and statistics courses; (5)provide a basis for comparing sport marketing to other

fields regarding the comparative level of sophistication,development, and maturity of the sport marketing lit-erature; and, (6) provide information regarding theextent to which various statistical methods and tech-niques have been used.

Research QuestionsThis investigation examined the frequency and possi-

ble changes of statistical data analysis techniques used inquantitative data based studies appearing in SMQ from1992 to 2004. Three research questions were examinedwith respect to the quantitative studies in SMQ:

1. What were the most frequently used quantitativestatistical data analysis techniques that were pri-mary to the research purposes, questions, and/orhypotheses appearing in SMQ from 1992 to 2004?

2. What were the most frequently used quantitativestatistical analysis techniques that were primaryto the research questions or hypotheses appearingin SMQ from 1992 to 2004 when classified asdescriptive, parametric inferential, and nonpara-metric inferential statistics?

3. What were the trends in the use of statistical dataanalysis techniques used in SMQ from 1992 to2004?

MethodThis research is part of a major ongoing research

effort to better understand statistical data analysismethods and techniques that are unique to sport man-agement and sport marketing studies. For this investi-gation, 251 articles published in SMQ during its first13 years, from 1992 to 2004, were classified as concep-tual, quantitative data based, or qualitative data based.Conceptual articles were defined as those that describedor discussed concepts and did not employ a statisticalanalysis. Qualitative data based articles were defined asarticles of which no numerical values were collectedand analyzed. Quantitative data based articles weredefined as articles of which numerical values were col-lected and analyzed that represented an amount orcount. Quantitative data based articles accounted fornearly two thirds (159 or 63.3%) of the articles pub-lished in SMQ. Qualitative data based articles account-ed for less than one tenth (6.4%) ot the articles, andconceptual articles accounted for nearly one third(29.5%) of such publications. Only quantitative databased articles (e.g., articles tor which numerical valueswere collected and analyzed that represented anamount or count) were included in the current investi-gation. A summary of the levels and types of tech-niques is presented in Table 2. Of the 159 articlesinvestigated, two of the studies used mixed methods,

Volume 14 • Number 4 • 2005 • Sport MarHeting Quarterly 231

Table 2A Descriptive and Numerical Summary of Manuscripts Pubiished in the Sport Mariieting Quarterly: 1992 to 2004

Type of article

Quantitative data based article

Qualitative data based article

Both quantitative andqualitative data based article

Conceptual article

Total

Definition

A data ba.sed article for which numerical valueswere collected and analyzed that represented anamount or a count

A data based article for which nonnumericvalues were collected and analyzed that representeda class or category

A data based article that employed both quantitativeand qualitative values

An article for which data were not collected where thewriter presented a discussion or some significant idea,concept, theory, issue, or program related to the fieldof sport management

No.

159

16

2

74

251

%

63.35

6.37

0.80

29.48

100.00

including both quantitative and qualitative data analy-sis techniques. 'Ihe majority ot the articles containedmultiple descriptive and inferential statistical dataanalysis techniques.

Conceptualization and Validation of the Data AnalysisCategories

Content validity was used to determine the type ofitems to adequately measure the construct of dataanalysis techniques from studies in educational psy-chology (Edgington, 1974; Wilson, 1980), educationalresearch (Goodwin & Goodwin, 1985a, 1985b), learn-ing disabilities (Baumberger Sc Bangert, 1996), recre-ational sport (Jamieson et al., I994)> management(Kieffer et al., 2001), and leisure studies (Riddick et al.,1984). In these studies, the data analysis techniqueswere listed by categories and divided by levels.Drawing from the works of DePoy and Gitlin (1994),Gall et al., (2003), McMillan and Schumacher (2001),and Neuman (2003), 28 common statistical techniqueswere identified and classified among the three majorcategories of statistical techniques: descriptive, para-metric, and nonparametric statistics (see examples inTable 1, Column 3).

Content validity was established by the use of a panelof experts to review each of the categories and levels ofdata analysis techniques. Two graduate faculty mem-bers and three doctoral students who were not a partof the research team were asked to examine each of thecategories and to judge how well the categories related

to the purpose of the investigation. Both faculty andstudents were identified as knowledgeable and activelyinvolved in statistical procedures. Feedback from thepanel resulted in slight modification of the categoriesand instrument for content validity and editorial con-cerns. Comments were solicited by the t1rst authorthrough the use of individual conferences with eachmember of the review panel.

Data Coding ProceduresTwo of the co-authors were graduate students and

were trained by the primary author as reviewers for thedata analysis techniques employed in the articles. Thereviewers were in the doctoral program in sport man-agement at a major research institution. Each reviewerindependently read and coded each of the techniquesin 159 articles. Coding procedures were based on a sys-tematic categorization scheme employed in earlierstudies (Baumberger Sc Bangert, 1996; Goodwin &Goodwin, 1985a, 1985b).

The coding scheme involved locating every statisticaltechnique used in a study and then classifying tbe tech-nique as being either primary or secondary. A statisti-cal technique was considered primary when it was usedto directly answer a study's research purpose, ques-tions, and/or hypotheses. When a technique wasjudged as primary, it was marked a y (meaning yes) onthe coding form. A technique was considered second-ary wben it was reported as a means of supplementinga higher level statistic. When a technique was consid-

232 Volume 14 • Number 4 • 2005 • Sport MarHeting Quarterly

ered preliminary to a major analysis {e.g., factor analy-sis) or a supplement to the major analysis (e.g., meansand standard deviation reported in conjunction withANOVA, etc.), it was not coded. This approach wassimilar to those used in earlier studies (Baumberger &Bangert, 1996; Goodwin & Goodwin, 1985a, 1985b).The distribution of techniques that were consideredprimary to the research purpose, questions, and/orhypotheses of each study is outlined in Figures 2through 4 and Table 3.

Year to year Percentage Use Indices (PUIs) werecomputed for each of the .statistical data analysis tech-niques. In the current investigation, the PUIs reproducethe percentage of statistical data analysis techniquesused in a given year and can range from 0 to 100%. Inusing this computation procedure the frequent use of agiven type of statistical data analysis technique wasdivided by the number of total techniques that emergedfor each year and the quotient was multiplied by 100(Stone-Romero, Weaver, & Glenar, 1995). For example,shown in Figure 5, the PUIs for inferential statistics anddescriptive statistics in 2004 were (16/23) x 100 = 70%and (6/23) x 100 = 26%. respectively.

Reliability of the Coding ProcessIn order to assure validity of the coding process, two

individuals were selected who had a formal educationalbackground in statistics. They were experienced coderswho participated in a series of systematic training ses-sions and content analyses of statistical techniques insport related journals. Initially, the coders were trainedthrough two practice sessions. The practice was on thearticles (e.g., 5-year period and 15-year period) fromsport management and sport marketing related journals.In each training session, the coders located every statisti-cal technique related the research purpose, hypothesis,or question and then classified the techniques. Whenthere was a disagreement, the coders discussed disagree-ment with statistical experts to make sure the statisticaltechnique and its relationship to the research purpose,hypothesis, or question was accurate. The purpose ofsuch practices was to eliminate disagreements betweencoders for validation of this study. This approach hasbeen one of the most appropriate ways to reconcile cod-ing disagreements (Gerstner Sc Day, 1997; Scandura &Williams, 2000). In addition, this process was followedthroughout the entire research study where coderschecked each other for the disagreements.

Rater agreement levels between the coders were 82 to96 percent. Reliability coefficients of 80 percents havebeen interpreted as adequate for this type of research(DePoy & Gitlin 1994; Gall, Gall, & Borg 2003;Neuman 2003; Nunnally 1967).

ResultsThe quantitative statistical data analysis methods and

techniques that were primary to the research purposes,questions, and/or hypotheses appearing in SMQ from1992 to 2004 are shown in Figures 1 through 5 andTable 3.

Figure IA summary of the statistical data analysis methodsused in the Sport MarHeting Quarterly. 1992 to 2004

Nonparametric,8.06%

Parametric,41.94%

Descriptive,50.00%

Figure 1 and Table 3 show the total number ot usesof the statistical methods and techniques used by SMQresearchers during its tlrst 13 years. In 159 articles ana-lyzed, there were 360 uses of statistical techniques.Many of the articles used more than one statisticaltechnique; therefore, the number of techniques exceed-ed the number of articles.

Descriptive statistical techniques were most frequent-ly used, accounting for one half (50.00%) of ali tech-niques used. Among descriptive statistical techniques,percentage (21.94%), frequency (15.28%), and mean(6.67%) were most commonly used.

Parametric inferential statistical techniques were thesecond most frequently coded techniques (41.94%). Inaddition to the 16 techniques used in JSM, conjointanalysis and multidimensional scaling were included inthe parametric inferential statistical techniques. Ofthese techniques, one-way ANOVA (7.50%), regression(6.39%), and t test (5.28%) were most commonly used.

Nonparametric inferential statistical techniques wereleast frequently coded (8.06%) as primary to answeringthe research purposes, questions, and/or hypothesesproposed by SMQ researchers. Nonparametric inferen-tial statistics included Mann-Whitney as well as chi-square. Spearman rank correlation, and Kruskal Wallis.Of the four techniques, chi-square (6.39%) was themost frequent technique to be coded; each of the othertechniques accounted for less than 1% of total non-parametric inferential statistical techniques.

Figure 2 summarizes the types of descriptive statisticsused by the researchers in SMQ between 1992 and2004. Seven types of descriptive statistical techniques

Volume 14 • Number 4 • 2005 • Sport MarHeting Quarterly 233

Table 3Frequencies and Percentages of m^or statistical tech-niques used in tiie Sport MarHeting Quarteriy, 1992 to2004

Number of Quantitative Articles (n)Number of Statistical Techniques (n)Average Technique per Article

DESCRIPTIVE STATISTICSPercentagesErequencyMeanRank

Standard DeviationMedianRangeTotal

1992-2004N

159.03602.3

79552411821

!80

INEERENTIAL STATISTICS: PARAMETRICOne-way ANOVARegressionT-testPost-hoc Multiple ComparisonsPearson Product Moment CorrelationEactor AnalysisOne-way MANOVA/MANCOVAEactorial ANOVAZ-SCO resDiscriminant AnalysisFactorial MANOVA/MANCOVAStructural Equation ModelLogistic RegressionFactorial ANCOVA

Cluster AnalysisPath AnalysisMultidimensional ScalingConioint AnalysisTotal

272319191412106443

32I

1111

151

%

21.9415.286.673.062.220.560.28

50.00

7.506.395.285.283.893.332.781.671.11l . l l0.830.830.560.28

0.280.280.280.28

41.94

INFERENTIAL STATISTICS: NONPARAMETRICChi SquareMann- WhitneyKruskal WallisSpearman Rank CorrelationFisher's Exact TestWilcoxon Signed Rank TestTotal

23

21111

29

6.39

0.560.280.280.280.288.06

were identified that were directly related to answeringthe research purposes, questions, and/or hypotheses.Of this amount, three (percentage, frequency, andmean) accounted for nearly all (87.78%) of such tech-niques. Percentage was the most dominant statistical

Figure 2A summary of descriptive statistics used in the SportMarHeting Quarteriy, 1992 to 2004

Mean,13.33%

Others,12.22%

Frequency,30.56%

Percentage,43.89%

technique to emerge, accounting for 43.89% of thedescriptive statistical techniques used in SMQ.

Of 18 parametric statistical techniques, five account-ed for nearly two thirds (67.55%) of such techniques(see Figure 3). One-way ANOVA was the single mostdominant technique, accounting for 17.88% of thetechniques. Regression analysis was the second mostpredominant technique (15.23%). The t test, post-hocmultiple comparisons and Pearson product momentcorrelation accounted for 12.58%, 12.58%, and 9.27%of the techniques, respectively. The remaining 13 sta-tistical techniques accounted for less than 7.00% each.Figure 4 shows that chi-square was the most frequentlyused nonparametric technique used in SMQ by itsresearchers between 1992 and 2004.

Figure 3A summary of parametric statistics used in the SportMarHeting Quarteriy, 1992 to 2004

Others, 32.45% One-way ANOVA, 17.88%

Correlation,9.27% Post-hoc

Comparisons,12.58%

T-test,12.58%

Regression,15.23%

The percentage usage (PUIs) values of the techniquesare plotted in Figure 5. As illustrated in the figure, thePUI for descriptive statistics have gradually decreasedfrom the initial issues of SMQ in 1992 to the issues of2004. The mean rate of such PUIs were 53.9% andranged from 86% (1992) to 26% (2004). Unlikedescriptive statistics, the PUIs for parametric statisticaldata analysis techniques have gradually increased from1992 to 2004 in SMQ. The mean rate for such PUIs

234 Volume 14 • Number 4 • 2005 • 5port Marheting Quarteriy

was 38.4% and ranged from 14% in 1992 to 70% in2004. Interestingly, the mean PUIs percentage rate fornonparametric statistics was 7.3% and ranged from 0%to 12%.

Figure 4A summary of non parametric statistics used In theSport MarHeting Quarterly, 1992 to 2004

Kruskal Wallis,13.79%

Mann-Whitney,

6.90%Chi Square, 79.31%

DiscussionThe tlndings of this investigation can be attributed to

the nature and scope of descriptive and inferential sta-tistics. Descriptive and inferential strategies are two dis-tinctive and complementary statistical techniques,however, both are necessary for analysis of data in thefield of sport marketing. In the current investigation, itis not intended to make a case that descriptive statisticsare better than inferential statistics. More importantly

was that the researchers utilized statistical data analysistechniques that were appropriate to a given researchpurpose(s), question(s), and/or hypothesis(es). Bothdescriptive and inferential statistics contribute toadvancement of the body of knowledge of the field insport marketing when they are effectively articulatedand designed. The purpose of descriptive statistics is tocondense, summarize, or describe a given set of data(Gall, Gall, & Borg, 2003; Kirk, 1978; Neuman, 2003;Runyon, Coleman, & Pittenger, 2000). They are used todescribe exploratory base findings and may be used toprovide fundamental knowledge for further interpreta-tion of inferential statistics. Descriptive statistics areused to describe what currently exists or what peoplebelieve by measures of central tendency (i.e., mean,mode, median, etc.), measures of condense data (i.e.,frequency counts and percentages) and/or measures ofvariability (i.e., range, standard deviations, and otherstatistics).

Unlike descriptive statistics, inferential statistics canbe thought of as a group of techniques or proceduresthat enable a researcher to generalize findings obtainedby measuring a variable in a certain number of subjectsto the larger group (population) from which the sam-ple was chosen. Inferential statistics are used for mak-ing assumptions about a population itself and to finddifferences, relationships, associations, and/or predic-tions of variables of interest. Inferential statistics areconsidered to be more sophisticated for analyzing data

Figure 5Trends In the Use of Statistical Data Analysis Techniques used In Sport MarHeting Quarterly, 1992 to 2004

100

^ so

S-§ *̂'

40

20

(86%)• (79%)

[14%)

(10%)(5%) ^ ..(

92 93 94 95 96 97 98 99 00 01 02 03 04

Year

" Descriptive Parametric • " Nonparametric

Volume 14 • Number 4 • 2005 • Sport MarHeting Quarterly 235

than descriptive statistics. For example whenresearchers want to test hypotheses, or decide whetherdifferences in results exist between the mean scores oftwo or more groups they use inferential statistics.(Conover, 1999; Gall, Gall, & Borg, 2003; Hinkle,Wiersma, & Jurs, 1994; Howell, 1999; McMillan &Schumacher, 2001; Neuman, 2003). Based on suchanalogy, our findings show that there has been a devel-oping sophistication in terms of statistical data analysistechniques employed in SMQ between 1992 and 2004.As illustrated in Figure 5, the plot shows that descrip-tive statistics have gradually decreased in use by SMQresearchers however, inferential parametric statisticshave gradually increased from 1992 to 2004. For exam-ple, parametric statistics accounted for 70% of the dataanalysis techniques used in SMQ in 2004. Unlikedescriptive and parametric statistics, the PUIs forinferential nonparametric statistics did not vary andwere generally below 12% for the entire period.

This investigation has been one of the first of criticalself-analysis of the research conducted in the field ofsport marketing. In order for a field or discipline togrow and improve it must periodically allow for selfevaluation (Riddick, DeSchriver, & Weissinger, 1984).One way to measure progress and credibility in a rela-tively new and emerging field is to periodically conducta comprehensive critical self-examination of the aca-demic literature, such as research topics, methodology,and statistical techniques used in the new and emerg-ing field (Crawford-Welch & McCleary, 1992; Reid &Andereck, 1989; Riddick, DeShriver, & Weissinger,1984). Critical self-analysis is a motivating factor and ishealthy for the field of sport marketing. This type ofanalysis informs us of where we have been and wherewe are currently.

Furthermore, as sport marketing educators we are apart of a relatively small group of scholars within thelarger higher education academic enterprise and, assuch, must have an investment in the future develop-ment of our chosen field, sport marketing studies. Inorder for research to progress and develop the neces-sary degree of sophistication, it is important to engagein periodic objective critical self-evaluation as we haveattempted to do in the current investigation.

This investigation posits nothing with respect to thequality of the research published in SMQ. Instead, itprovides us with a summary of the state of the mostfrequently used statistical techniques in this one jour-nal in the Held. The extent of familiarity a reader haswith such techniques will determine to what extent thereader can critically profit from the results of empiricalinvestigations in SMQ.

The authors hope that the findings of this study willbe examined alongside other studies on the sport man-

agement literature. Together, the studies can bringlight to the state of various aspects of the literature.When all of the literature has been examined, this willserve as a basis for developing and enhancing allaspects of the literature.

Implications of the StudyThe findings of this study reveal the state of some

aspects of the literature published in the journal SportMarketing Quarterly. From this information, academi-cians may ascertain strengths and weaknesses found inthese particular aspects of this journal and begin toaddress them. (As the authors of this study, we do notwant to dictate such action or direction—we believethat should be left to sport marketing scholars andresearchers.)

Also, the findings of the current investigation shouldbe of special interest to students and faculty of gradu-ate level programs in research methods and statisticscourses in sport marketing studies. Specifically, in ref-erence to the current investigation, the fmdings shouldeliminate some of the fear about statistics.

It is recommended that this investigation be replicat-ed and extended using all sport management journalsand that multiple indicators will be used for assessingthe state of the literature. Critical self-examination fol-lowed with improvement and enhancement will posi-tively influence the credibility and acceptance of sportmarketing as a field of study.

Future investigations should be replicated using thestudies published in other sport marketing journals(i.e.. International Journal of Sports Marketing andSponsorship). Similar reviews for other sport marketingjournals are important. With such important informa-tion, sport marketing academicians can begin toaddress these issues and enhance the body of literaturefor the advancement of the field. Moreover, assess-ments of the body of literature in sport marketingshould include sport marketing papers published injournals other than sport marketing journals, sportmarketing literature published in conference proceed-ings, and material published in academic books andtextbooks. Assessment of the entire body of knowledgewill offer a more exbaustive and thus accurate analysisof the body of literature.

It is also suggested that studies be extended toinclude a wider variety of research methodology andtechniques other than what was used in the currentinvestigation. The use ot statistical data analysis tech-niques is only one indicator of research direction andthe sophistication of methodology. In future studies,the analyses of other categories should be included.such as (a) the type of research hypotheses (directionalor nondirectional); (b) sampling procedures (e.g., sim-

236 Volume 14 • Number 4 • 2005 • Sport Marheting Quarterly

pie random sampling and stratified sampling, etc.); (c)population and sample size; (d) psychometric meas-urement (validity and reliability); and (e) researchdesign (experimental and nonexperimental design).These are categories selected from some of the earlierstudies ((jrazer & Stiff, 1987; Swanson 8c Alford, 1987).Such categories were also defined and summarized inseveral research methodology and statistics textbooks(DePoy & Gitlin, 1994; Gal! et al., 2003; Hinkie et al.,1994; Howell, 1999; Leedy & Ormrod, 2001; McMillan& Schumacher, 2001; Neuman, 2003).

Lastly, it is hoped that the current investigation willinspire discussion among students and faculty, as wellas practitioners concerning the state of the literature insport marketing. Moreover, we hope that these discus-sions will lead to ideas that will address all aspects ofthe literature and will eventually extend to researchand other scholarly activity to continue the contribu-tion to the expansion and enhancement of the litera-ture as it continues its path to maturity.

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