Influential Authors in ADVT

8/10/2019 Influential Authors in ADVT

1/19

African Journal of Business Management Vol. 6(33), pp. 9399-9417, 22 August, 2012Available online at http://www.academicjournals.org/AJBMDOI: 10.5897/AJBM11.1513ISSN 1993-8233 2012 Academic Journals

Full Length Research Paper

Study of influential authors, works and researchnetwork of advertising research: 1998 to 2007

Pauline Pei-Ning Tu

Graduate School of Business and Operations Management, Chang Jung Christian University, Taiwan.E-mail: [email protected]. Tel: (886)62785123 ext. 2020. Fax: (886)62785170.

Accepted 11 June, 2012

Changes in citation patterns and in the advertising reflect the evolution of the field itself. This studyutilized author co-citation analysis, a bibliometric methodology and social network analysismethodology, to highlight the most influential authors, analyze citation relationships, revealcorrelations among publications, and show trends and patterns in the advertising field over twoconsecutive time periods, 1998 to 2002 and 2003 to 2007. In addition, factor analysis was used toexamine the breadth of the authors research areas. This study serves as a disciplinary review of thefield of advertising research.

Key words: Advertising, bibliometric analysis, author co-citation analysis, social network analysis, knowledge ofnetwork, Intellectual structure.

INTRODUCTION

How customers perceive the message from

advertisements will influence their purchasing intention.Many companies seek greater awareness of the power ofadvertising, which involves communicating a messagethat includes the name of the product or service and howthat product or service could potentially benefit theconsumer. In general, the goal of advertising is toincrease sales of these goods or services by catchingpeoples attention. Today, advertising is an elaborate toolenabling businesses to sufficiently educate people to beable to understand the nature and uses of their goods orservices. In other words, advertising is a form of masscommunication that typically attempts to persuadepotential customers to purchase more of a product orservice. Despite the dramatic growth of the internet inmodern times, television (TV) commercials are stillconsidered the most effective mass-market advertisingformat. Unfortunately, TV networks tend to charge highprices for commercial airtime during popular TV events.

As research in advertising has become increasinglypopular in recent decades, it is important to effectivelyidentify the most influential and representative collectionof research articles. As Walstrom and Leonard (2000)argued that because understanding such a large amountof information is time consuming and tedious, it isimportant for a researcher to focus on reading only the

best most relevant journal articles. While there are many

previous studies related to the field of advertising, it isextremely time consuming for researchers and scholarsto read all published journal articles. However, thisrequires that researchers have the means to identify theleading articles and authors in the field. There are manyways to trace advertising studies evolution over the pastdecade, from 1998 to 2007 this research adopts thewidely accepted bibliometric method of author co-citationanalysis (White and Giffith,1982; Culnan, 1986; Culnan,1987; McCain, 1990) to gain a knowledge network ofadvertising research and its shift in research focus aswell as to research the joint citations of key researchersin the advertising field and to examine the centraltheoretical and conceptual approaches in contemporaryadvertising research. The findings of this study build uponprevious studies investigating the patterns and evolutionin the advertising field.

LITERATURE REVIEW

Bibliometric methods

Bibliometric analysis is a widely adopted and establishedmethod for revealing the common research interests and


2/19

9400 Afr. J. Bus. Manage.

theoretical foundations within a particular researchdomain (Lievrouw, 1990; Pritchard, 1969). This methodinvolves counting and analyzing different kinds of writtencommunication (Pritchard, 1969), and it therefore consti-tutes a quantitative study of published or bibliographicunits (Broadus, 1987). Bibliometrics involves providing

proxies for quantifying the communication processes inwritten and published works which constitute theknowledge within a given network (Laudon and Laudon,1993). Bibliometrics encompasses citation and co-citationanalysis, both of which are commonly used tools formapping the intellectual structure of a particular researchfield (Small, 1973; Zuccala, 2006). By measuring andanalyzing written communication, such analyzes shedlight on the processes of communication and overallnature and development of a discipline (Borgman, 2000).According to Alan Pritchard (1969: 349) bibliometrics isthe application of mathematics and statistical methods tobooks and other media of communication, and itprovides a method for examining communication amongscholars in a field through their scholarly publication(Borgman, 1990). Also, Diodato (1994) points out that theterm bibliometrics refers to the mathematical andstatistical analysis of patterns that appear in thepublication and the use of documents. Bibliometricsutilizes quantitative analysis and statistics to describepatterns of publication within a certain field or body ofliterature. Researchers may thus use these methods toevaluate and determine a particular writers influence orexamine the relationship between two or more writers orworks. In general, bibliometrics utilizes quantitativeanalysis and statistics to describe patterns of publicationwithin a certain field or body of literature. In other words,bibliometrics is a set of methods used to study ormeasure texts and information. Generally speaking, theSocial Science Citation Index, the Science Citation Index,and the Arts and Humanities Citation Index are amongthe most commonly used methods to trace citations whenconducting bibliometric research. In this study, author co-citation analysis is used to map the changes in theintellectual structure of the advertising field over the pastten years. This analysis aims to detect shifts in scholarlyorientations within the discipline over one decadeencompassing the two five-year period, 1998 to 2002 and2003 to 2007.

Citation analysis

Citation analysis is the earliest and the most widely-usedas well as the most important method of bibliometrics.Citation analysis is a bibliometric technique thatconsiders the citation as the basic unit of analysis. Thistechnique goes beyond a simple counting of publicationsby analyzing which authors and papers are citedfrequently and are therefore most valuable and useful toother researchers (Pasadeos et al., 1998). Citation

analysis relies on theoretical and methodologicalapproaches developed by sociologists, revealing adisciplines structures and boundaries by identifyingwhich authors and publications are cited by other authorsand publications (Crane, 1972; de Solla Price, 1965,1970). Citation studies can show that links among

journals are important indicators of communicationbehavior (Reeves and Borgman, 1983).Through citation analysis, researchers are able to

identify the contributions of key authors in a specific field.This is achieved by combining descriptive analyses of themost widely published authors, the temporal profile ofarticles published, and the publication outlet pattern ofarticles published, with descriptive analysis of the most-cited first authors, most-cited texts (books and articles),temporal pattern of articles cited, and publication outletpatter of articles cited (Parvinen, 2003). According toGross and Gross (1927), the interlinked invisible nodescan be identified from the most influential publicationsand scholars throughout the citation analysis. Citationanalysis uses citations in scholarly works to establishlinks, and it is based on the notion that authors citepapers they consider to be most relevant and importantto the development of their research (Pilkington andTeichert, 2006). Thus, heavily cited articles are likely tohave exerted a greater influence on the subject thanthose less frequently cited (Sharplin and Mabry, 1985;Culnan, 1986; Ma et al., 2008).

Co-citation analysis

Since the simple citation counts show who cites whombut are not able to identify more detailed interconnectionsamong scholars, co-citation analysis is a method ofdocument coupling that measures the number ofdocuments that have cited any given pair of documents(Culnan, 1986) and is therefore able to detect theinterconnections among scholars. After all citations in agiven document are obtained, a co-citation network isconstructed by drawing a line connecting two documentsif they are both cited by other documents. Depending onthe number of sources that cite both documents, thestrength of co-citation can vary, and this varying strengthcan be represented by varying the number of lines linkingthe two documents (Tankard et al., 1984).

By identifying links among authors or published works,co-citation networks enable the assessment of a fieldsoverall tradition and evolution at the micro-level that ofthe individual author or published paper instead of themore macro-level of journal title (Culnan, 1986). Theseco-citation networks are essentially visual representationsof schools of thought, disciplinary paradigms, andinvisible colleges, informal communication relationsamong scientists or other scholars who share a commoninterest or goal (Lievrouw, 1989). These networks mayreveal consensus among authors views toward particular


3/19

works, especially if the co-citations always occur in thesame context (Small, 1980). Lastly, one of the benefits ofco-citations is in detecting shifts in group consensus overtime. Changes in co-citation networks occur lessfrequently and less rapidly than changes in simplecitation counts and therefore, represent major shifts in

research activity and the scholarly orientation within adiscipline (McCain, 1989; Usdiken and Pasadeos, 1995).In general, journals systematically chronicle authors

communication, both formal and informal. When workingon a certain research project, authors may cite otherauthors or draw on common source of knowledge.Moreover, it is likely that their works will be frequently co-cited by other studies focusing on intellectually similarthemes. This dissemination of knowledge establishes anintricate web of relationships between these works. Small(1973) stated that this web of relationships produces astructure or map for the discipline, which can beobserved as it changes and evolves over time; by clari-fying the complex patterns of associations betweenspecialties, co-citation makes it possible to monitor thedevelopment of scientific fields and identify relationshipsthat exist between specialties.

In order to evaluate the core knowledge of a field,citation and co-citation (Small, 1973; Marshakova, 1973;McCain, 1990; Pilkington and Teichery, 2006) as well asfactor analysis (McCain, 1990; Pilkington and Teichery,2006) are considered to be the fundamental researchtools. This study utilizes co-citation analysis to identifyinfluential authors or works and to display inter-relationships between authors or works. A way to identifythe influential authors or works is by counting thefrequency of citation as well as identifying authors orworks in the same discourse by analyzing how often theyare cited together at the same time. This study employsco-citation analysis to identify influential authors or worksand to examine the relationships between authors orworks. By counting the frequency of citation andanalyzing how often authors are cited together at thesame time, it is possible to identify the most influentialauthors or works. This study aims to fill a gap inadvertising research by providing researchers with anoverview of contemporary advertising studies in the pastone decade and by mapping the objective structure ofdifferent research topics in the development of theadvertising field.

Previous studies employing bibliometricmethodology

The bibliometric methodology is a tool used for screeningseveral social science disciplines. The following areexamples of studies that have used bibliometrictechniques to examine the intellectual structure ofscience specialties and explore the impact of theirrespective fields: tourism (Ma and Wang, 2007; Chou and

Tu 9401

Tseng, 2010), human resources management(Fernandez-Alles and Ramos-Rodriguez, 2009), internetadvertising (Kim and McMillan, 2008), strategicmanagement (Acedo et al., 2006; Nerur et al., 2008),family business (Casillas and Acedo, 2007), publicrelations (Pasadeos et al., 1999), inter-organizational

relationships (Oliver and Ebers, 1998; Parvinen, 2003),organization studies (Usdiken and Pasadeos, 1995),small enterprise research (Ratnatunga and Romano,1997), entrepreneurship research (Dery and Toulouse,1996), management information systems studies(Culnan, 1986), and research and development literature(Tijssen and van Raan, 1994).

Social network analysis (SNA)

Social network analysis is a powerful diagnostic methodused for analyzing the nature and pattern of relationshipsamong members of a particular domain (Krebs, 2002).Essentially, SNA is a method for visualizing our peopleand connection power, helping us to identify how we canbest interacts to share knowledge. SNA is an analyticaltool that reveals the number of interactions and thecloseness of relationships between nodes within anetwork. In the representation of the social network, thenodes are the people and groups, and the links showrelationships or flows between these nodes. SNA wasinitially developed for the purpose of analyzing networksin social science, computer networks, and communicationstudies. This method is useful because it mathematicallydefines certain characteristics of the actors and thenetwork itself. The characteristics defined include thepower of actors, range of influence, cohesion, equiva-lence, and brokerage (Bonacich, 1987; Burt, 1992) andthese characteristics are expressed in terms ofcorresponding network-structure parameters which arederived from the relationships among the actors.

According to Burt (1992), a social network is a group ofcollaborating entities that are related to one another.Mathematically, this is a graph in which each participantin the network is called an actor and depicted as a nodein the network. Actors can be people, organizations, orgroups, or other sets of related entities. Relationshipsbetween actors are depicted as links between thecorresponding nodes. A co-citation matrix is inherently

very similar to social networks as it essentially representsa network of linked authors (Pilkington and Teichert,2006; Pilkington and Chai, 2008). In the co-citationmatrix, the key nodes from one academic field can bediagrammed as a network with locations determinedusing Geodesic distances (Pilkington and Teichert, 2006;Pilkington and Chai, 2008). This study argues that SNAtechniques would facilitate researchers ability to examinenetworks of knowledge and detect correlations betweenthem. In this study, social network analysis tools are usedto graph the relationships in the co-citation matrix and


4/19


identify the strongest links and the core areas of interestin advertising.

METHODOLOGY

The data used for this bibliometric analysis were obtained from65,234 references from 2,975 articles found in the SSCI and SCIdatabases from 1998 to 2007. The intention of this study is todevelop a chronological perspective and an overview of theevolution of contemporary advertising research over the pastdecade, from 1998 to 2007. The research methods adopts citationanalysis, author co-citation analysis, factor analysis, andhierarchical clustering analysis to map and study changes in theintellectual structure of advertising research over the pastconsecutive ten years. This ten-year time frame is divided into twofive-year periods1998 to 2002 and 2003 to 2007for analysisand comparison, and in order to recognize a change or evolution inthe pattern of knowledge.

The results of this study are widely applicable and are not limitedto a single specific or area, which confirms the interdisciplinarynature of this emerging field.

This study utilizes co-citation analysis (Culnan, 1986; Sharplinand Mabry, 1985), a method which addresses the importance of journals and articles, based on the notion that the most frequentlycited journals and articles cited are the most important in the field.In addition, this study uses author co-citation analysis (Garfield,1963; Small, 1974; McCain, 1990), an approach based onanalyzing the frequency with which any work by an author is linkedto any work by another author and to a third and later work (Whiteand Griffith, 1981). Author co-citation analysis (ACA) is a set of datagathering, analytical, and graphic display techniques that can beused to produce empirical maps of prominent authors in variousareas of scholarship. Furthermore, ACA assumes that two authorsfrequency of co-citation and similarity in patterns of co-citations withothers are indicative of the closeness of the relationship betweenthem.

The validity of ACA has been demonstrated by many

researchers, as described in the previous section Previous StudiesEmploying Biblometric Methodology. The following paragraphdescribes the methodology used in this study, which is adaptedfrom McCain (1990) and summarizes the steps that were used inthis study.

Data selection

This study adopts McCains (1990) ACA technique for datagathering, analysis, and graphic display to produce empirical mapsof prominent authors in various areas of scholarship. In thebeginning, this study utilized the key-word search strategy, whichinvolved searching for the keyword advertising and using thetopics of publications to identify the potential databases containingadvertising-related raw materials. In the on-line SCI and SSCIdatabases, 65,234 citations from 2,975 articles were found as citedreferences during the years 1998 through 2007. The data used inthis study includes books, journals, publication titles, author names,publication dates, and citation index. The citation counts weretabulated and filtered using Excel, and the collected data wereanalyzed and systematized by sorting, summing, sub-totaling,ranking, and screening based on the total citation counts eachreceived. Over the 10- year period, a total of 1,406 journals werepublished from 1998 to 2002 and 1,569 published journals from2003 to 2007. Among these journals in SSCI and SCI of ISI(Institute for Scientific Information), the most cited references for theearlier 5-year period were in 2002 followed by 1999, 2000, 1998,and 2001. The most cited references occurred in the year 2007

followed by 2005, 2006, 2003 and 2004 for the recent 5-yearperiod. They are used as the source to identify the most influentialscholars and documents in advertising studies. Thus, there was agreater number of advertising citations in the recent 5 years. Theadvertising literature has especially focused more attention in spiteof the large number of studies that have been done on advertisingin 2007 and 2002.

The next step is to collect two sets of data using 5 year each timeframes (1998 to 2002 and 2003 to 2007) in order to make temporalcomparisons. The data collected in this study indicate that five-yearperiods are more than adequate for constructing citation lists andco-citation networks and for making distinctions between the most-cited works in the two periods. Throughout the research, differentnumbers of publications and reference data are found: there are37,819 citations from 2003 to 2007 and 27,415 citations from 1998to 2002. The most cited publications for the earlier 5-year periodwere in 2002, followed by 1999, 2000, 1998 and 2001 and for therecent 5-year period were in 2007, followed by 2006, 2005, 2003and 2004. Thus, the most advertising citations occurred in therecent 5-year period. Over the entire 10 years, there is a total of1,569 published journals from 2003 to 2007 and 1,406 published

journals from 1998 to 2002. They are used as the source to identifythe most influential scholars and documents in advertising studies.

Thus, there is a slight increase in attention in spite of the largernumber of studies that have been done on advertising in the recent5 years.

Indentifying influential authors

Given the assumption that a heavily cited article or book must beconsidered important by a large number of scholars in a disciplineor across disciplines (Pasadeos et al., 1998), the citation analysisprovided by these authors is a logical source for influential works.Bibliographies and reading lists were used because they representboth scholarly and professional views of influence. Advertisingprinciples texts also represent logical sources for influential worksbecause of their focus on historical and fundamental topics, theirobjective of providing a conceptual foundation for students who willlikely pursue careers in advertising (Dunn et al., 1994), and theirnecessity for keeping up with change (Bergh and Katz, 1999).

The 30 most frequently cited authors in each 5-year time periodwere identified as the core authors in the field and further examinedwith co-citation analysis. A series of operations were conducted,through which it is possible to identify the key nodes in theintellectual structure of advertising research and develop thestructures.

Author co-citation matrix

By searching the SSCI database from 1998 to 2007, the 30 mostfrequently cited authors in each 5-year time period were identifiedas the core authors in the field and a raw co-citation matrix was

compiled. The author co-citation matrix was developed based onthese frequencies of author co-citation, and the diagonal data werecalculated. The matrix represents each authors profile of co-citationwith every other author on the list (White and Griffith 1981). Thedata is then converted into an Excel spreadsheet to develop a 30 X30 matrix for each 5-year period.

Data analysis

The data matrix was imported to UCINET 6.0 software (Borgatti etal., 2002) in order to perform the social network analysis (SNA),factor analysis, and cluster analysis (Pilkington and Tecichert,2006; Hair et al., 1998; Pilkington and Liston-Heyes, 1999). SNA is


5/19

increasingly used to analyze the nature and pattern of relationshipsamong individual scholars or articles in a certain discipline (Ma etal., 2008; Pilkington and Fitzgerald, 2006; Pilkington and Teichert,2006; Pilkington and Chai, 2008). The tools of social networkanalysis can be used to graph the relationships in the co-citationmatrix, thereby identifying the strongest links and the core areas ofinterest in the advertising field (Pilkington and Tecichert, 2006). Inorder to describe the knowledge distribution process in theadvertising research, the knowledge network of advertising ismapped by identifying the key nodes and developing the structure.The co-citation correlation matrix was factor analyzed using varimaxrotation a commonly used procedure which attempts to fit or loadsthe maximum number of authors on a minimum number of factors(McCain, 1990). These scholars can be said to collectively definethis field because they have the most influence in the developmentof the advertising research. The graphing programmer NETDRAW(Version 2.0 which comes with the social network software suiteUCINET) is used to generate the intellectual structure map ofauthor proximities (Borgatti et al., 2002). The advertising researchgraphs are shown in Figures 1 and 2, which show the links amongthe top 30 most-cited publications. These graphs only display thelinks with at least 15 citations for the sake of clarity and ease ofinterpretation.

The analysis reveals the most prevalent authors in the subfieldsand the extent of their influence (Nerur et al., 2008). Using thePearson-r correlation, author proximities are determined andpresented graphically as a hierarchical cluster (White and McCain,1998).

Finally, the last step of factor analysis is performed to groupthese authors according to the similarity of their research themesand focuses. By taking the co-citation matrix and grouping theauthors using factor analysis of the correlations between theentries, this study can determine which authors are groupedtogether as well as their common shared elements. The closenessof author points on such maps is algorithmically related to theirsimilarity as perceived by citers.

RESEARCH FINDINGS Most-cited advertising authors

The top 30 most-cited advertising authors in the periods1998 to 2002 and 2003 to 2007 are as shown in Tables 1and 2. The frequency of an authors citation by others isused to indicate the relative impact of specific author inthe advertising literature during each time period. Themost frequently cited authors between 1998 and 2002(the first five-year period) was Petty, followed byMackenzie, Machinnis, Nelson and Pollay. Also, thedatabase identified the most frequently cited scholarbetween 2003 and 2007 (the second five-year period) asMackenzie, followed by Bell, Nelson, Pollay, andRosenthal. According to this data, these scholars havethe most influence in the development of the advertisingarea and thus collectively define this field. It is interestingto see that Mackenzie moved from the second to the firstmost frequently cited scholar whereas Nelson and Pollayremained as the top 4 and 5 cited scholars, respectively,for both the first and second five-year periods. Also worthnoting is that Petty slid from first place to sixth place. Dueto the limitation of the SSCI online database, only thelead authors names are shown in the most frequently

Tu 9403

cited top 30 authors list in the periods 1998 to 2002 and2003 to 2007.

Most-cited advertising journals

The highest frequency of citation and the most influentialscholars were then identified from the citation samples,by counting their total citation count within the journalarticles. As shown in Table 3, among all the cited journalarticles, the most-cited advertising article titles between1998 and 2002 (1st five-year period) in the advertisingliterature are as follows: Journal of Advertising, Journal ofAdvertising Research, British Medical Journal, Advancesin Consumer Research, Graphics and Journalism andMass Communication. For the second five-year period,as shown in Table 4, the most frequently cited journalwas Journal of Advertising Research, which moved upfrom second place to first place. However, Journal of

Advertising dropped from first place to second place.There was a small change for Advances in ConsumerResearch, which climbed from fourth place to third place.It is surprising that International Journal of Advertisingshows up at fourth place in the second five-year period,whereas this journal did not appear in the list of mostfrequently cited journals in the advertising literature in thefirst five-year period. Another significant change is thatBritish Medical Journal slid from third to fifth place. These

journals and books were found by searching for the titleadvertising in the SSCI database.

Most-cited advertising articles

Based on the citation samples, the highest frequency ofcitation and the most influential scholars were thenidentified by their total count of citations within the journalarticles. As shown in Table 1, among all the cited journalarticles, the most-cited advertising article titles between1998 and 2002 (the 1st five-year period) are Pettyspaper (1986) The Elaboration on Likelihood Model ofPersuasion in Advanced in Experimental SocialPsychology, followed by Mackenzie and Lutz (1989) AnEmpirical-Examination of the Structural Antecedents ofAttitude Toward the Ad in an Advertising Pre-testingContext in Journal of Marketing, Maclnniss paper (1991)Enhancing and Measuring Consumers Motivation,Opportunity, and Ability to Process Brand InformationFrom Ads in the Journal of Marketing, and Nelsonspaper (1974) Advertising As Information in the Journal ofPolitical Economy. Based on Table 6, among all the citeddocuments, the most-cited advertising documentsbetween 2003 and 2007 are Mackenzies paper (1989)An Empirical Examination of the Structural Antecedentsof Attitude Toward the Ad in an Advertising Pre-testingContext in Journal of Marketing, followed by Bells paper(2000) Personality and Performance at the Beginning of


6/19


Figure 1. Core themes in advertising research: 1998 to 2002 (frequency > = 15).

Figure 2. Core themes in advertising research: 2003 to 2007 (Frequency > = 15).

the New Millennium: What Do We Know and Where DoWe Go Next? In the Journal of Family Practice, Nelsonspaper (1974) Advertising as Information in Journal ofPolitical Economy, Pollays paper (1993) heres The Beef

Factors, Determinants, and Segments in ConsumerCriticism of Advertising in the Journal of Marketing, andRosenthal et al. (2002) Promotion of Prescription Drugsto Consumers in the New England Journal of Medicine.

Co-citation networks

Social network analysis tools can be used to graph therelationships in the co-citation matrix and identify thestrongest links and the core areas of interest inadvertising (Pilkington and Teichert, 2006). The keynodes shown in Figures 1 and 2 were conducted by usingthe UCINET software (Borgatti et al., 2002) which showsgraphically the core areas of interest as well as the linksamong the top 30 most-cited publications. The differentshapes of the nodes result from performing a factionstudy of these authors. This method groups elements in anetwork based on the sharing of common links to eachother. The few authors centered in Figures 1 and 2 are

the leading figures in advertising research. Theirnumerous citations and extensive interlinks with eachother undoubtedly indicate their prestigious status inadvertising research. Their contributions and explorationsin advertising collectively define the future researchdirections of advertising studies. These two graphs onlydisplay the links with at least 15 co-citations for the sakeof clarity and ease of interpretation.

Factor analysis

Ding et al. (1999) stated that factor analysis is used toexamine the interrelationships among the originalvariables through the creation of some derived variablesor factors. In this study, to determine the common linksbetween authors, factor analysis was performed to mapthe intellectual structure of advertising studies. The mostinfluential scholars in the advertising studies between1998 and 2007 are grouped together. Six factors wereextracted from the data and together they explain over67.4% of the variance in the correction matrix for the firstfive years. As for the second five years, five factors wereextracted from the data, and together they explain over


7/19


8/19


Table 3. The most frequently cited journals in advertising literature: 1998 to 2002.

Journals (frequency > = 7) Number ofcitation Journals (frequency > = 7)

Journal of Advertising 84 Advertising Cons Journal of Advertising Research 78 Fortune British Medical Journal 45 IIC-International Review of Industrial Property and CoAdvances in Consumer Research 33 Journal of Business Ethics Graphics 26 Journal of Consumer Research Journalism and Mass Communication 26 International Journal of Industrial Organization American Journal of Agricultural Economics 24 Journal of Business Research Lancet 24 Review of Industrial Organization JAMA-Journal of the American Medical Association 22 International Journal of Market Research Tobacco Control 22 Journal of Academic Marketing Science Journal of Public Policy and Marketing 20 Journal of Marketing American Medical Association (AMA)-- Winter Education Conference 15 Journal of Consumer Psychology Psychology and Marketing 14 Library Journal Journal of Communication 12 American Journal of Health-System Pharmacy

Journal of Marketing Research 12 Business History Review

Table 4. The Most Frequently Cited Journals in Advertising Literature: 2003 to 2007.

Journals (frequency > = 7) Number of citation Journals (frequency > = 7) NumJournal of Advertising Research 78 Tobacco Control Journal of Advertising 78 International Marketing Review Advances in Consumer Research 36 Lecture Notes in computer Science International Journal of Advertising 34 Archives of Pediatrics and Adolescent Medicine British Medical Journal 30 Journal of Business Ethics Journalism and Mass communication 25 JAMA-Journal of the American Medical Association Journal of Consumer Research 19 Lancet Journal of Health Communication 17 Value In Health International Journal of Market Research 16 European Journal of Operational Research Canadian Medical Association Journal 15 Management Science Journal of Public Policy & Marketing 15 Alcoholism Clinical and Experimental Research Marketing Science 15 Journal of Consumer Psychology Advertising Cons 14 Journal of Marketing Research Journal of Business Research 14 Journal of Communication Psychology and Marketing 14 Journal of Economics & Management Strategy


9/19

38.2% of the variance in the correlation matrix. Tables 5and 6 illustrate the most important factors along with theauthors that had a factor loading of at least 0.4 (Whiteand Griffith, 1981). The names to the factors wereassigned on the basis of the interpretation of the authorswith high associated loadings. There are no attempts to

interpret the remaining factors on account of their relativesmall eigen values (


10/19


Table 5. The top 30 authors factor loadings (varimax rotation) at 0.4 or higher 1998 to 2002.

Factor 1: Attitude, brand attitude and contentanalysis in consumer research 33.0% variance

Factor 2: Informative advertising andproduct quality 14.0% variance

Factor 3: Cialcohol exp

Macinnis and Jaworski (1989) 0.896 Stigler G.J. (1961) 0.951 Pollay et Scott L.M. (1994) 0.883 Milgrom P. (1986) 0.931 Grube anKassarjian H.H. (1977) 0.869 Grossman and Shapiro (1984) 0.683 Baron R.MBrownand Stayman (1992) 0.850 Hoch and Ha (1986) 0.510Mitchell A.A. (1981) 0.841Greenwald, A.G. (1984) 0.822Batra R. (1986) 0.808

Edell and Burke (1987) 0.795 Factor 4: Pharmaceutical advertising anddirect-to customer 5.80%Factor 5: Coemotions an

Mackezie and Lutz (1989) 0.793 Marketing of Prescription Drug variance Content Baron R.M. (1986) 0.729 Hollon M.F. (1999) 0.961 GarramoHolbrook and Batra (1987) 0.691 Wilkes et al. (1992) 0.815 Petty andHoch and Ha (1986) 0.655 Holbrook a

Garramone G.M. (1990) 0.467

Factor 6: Direct-to-consumer prescription drugadvertising and drug information services 3.40% variance

Holmer and Alan (1999) 0.961Wilkes et al. (1992) 0.466

Table 6. The top 30 authors factor loadings (varimax rotation) at 0.4 or higher 2003 to 2007.

Factor 1: Attitudes and consumer 16.80% Factor 2: Advertising costs, advertising prices and product 7.40% Factor 3: Con

Behavior Variance Quality Variance Petty R.E. (1983) 0.932 Milgrom P. (1986) 0.885 Shavitt

Mackezie and Lutz (1989) 0.723 Nerlove and Arrow (1962) 0.759 Pollay Brown and Stayman (1992) 0.602 Butters G.R. (1977) 0.536 BarwiseVarkratsas D. (1999) 0.581 Grossman and Shapiro (1984) 0.472 Mittal BDucoffe R.H. (1996) 0.579 VarkratsaMueller B. (1987) 0.568Factor 4: Commercials, attitude, perceptions and beliefs 4.60% Factor 5: Advertising prices 3.70%and Positive Emotions Variance and Informative Advertising VariancePierce et al. (1998) 0.892 Nelson P. (1974) 0.904Mittal B. (1994) 0.510 Grossman and Shapiro (1984) 0.566

Butters G.R. (1977) 0.474


11/19

Tu 9409

Figure 3. Co-citation mapping the intellectual structure of advertising studies: 1998 to 2002.

Figure 4. Co-Citation Mapping the Intellectual Structure of Advertising Studies: 2003 to 2007.

(1987) demonstrates that feelings generated by the adare different conceptually from thoughts about the ad andboth are important and contribute uniquely to explainingthe effects of advertising. In general, the core of researchthemes in 1998 to 2002 mostly relates to the contentanalysis in consumer research, attitudes, cigaretteadvertising, alcohol expectancies, pharmaceutical adver-tising and brand attitudes.

Figures 1 and 3, Table 5 and Factor 1 showed that themain research focused on attitude, brand attitude andcontent analysis in consumer research. MacInnis andJaworski (1989) addressed that communication

effectiveness is in part driven by consumers motivation,opportunity and ability to process brand information froman ad. The brand attitudes research (Maclnnis, 1991;Brown and Stayman, 1992; Mitchell, 1981, Batra, 1986)suggested that anyone whom is able to gain the ideas ofan ad can be imported by any other market. Since marketresearch measures are based on the visual elements ofthe ad, such as flow of attention, flow of emotion andbranding moments provide insight into what is working inan ad in any country or region. Based on Table 5 andFactor 2 represented informative advertising and productquality; Stigler, Milgrom, Grossman and Hoch argued that

Co-citationsLines

WidthParis Co-citations Lines Width Paris

249+ 1 100 - 129 1

130 - 248 2 99 - 0 431

249

10 8

132

134 Nelson, P., 1974

Petty, R.E., 1986Baron, R.M., 1986

Bastra, R., 1986 Edell, J.A., 1987

Stigler, G.J., 1961 Milgrom, P., 1986


12/19


Figure 5. Hierarchical tree plot for the frequency of the two authors co-citations in advertising research: 1998 to 2002.

Figure 6. Hierarchical tree plot for the frequency of the two authors co-citations in advertising research: 2003 to 2007.

advertising had dramatic effects on perceptions of qualitywhen consumers saw ambiguous evidence; judgmentsand product inspection behavior protocols showed thatadvertising induced consumers to engage in confirmatoryhypothesis testing and search. In addition, advertisinginfluenced quality judgments by affecting the encoding ofthe physical evidence, while retrieval of ad-consistentevidence also appeared to occur, though to a lesserdegree. In Table 5 and Factor 3, Pollay et al. (1996)points out that sensitivity to cigarette advertising isapproximately three times larger among teenagers thanadults. Grube and Wallack (1994) research indicated that

awareness of television beer advertising is related tomore favorable beliefs about drinking than beer brands.Thus, the alcohol advertising may pre-dispose youngpeople to drinking. Therefore, in order to prevent drinkingand drinking problems among young people, it isnecessary to devote more attention to countering thepotential harmful effects of alcohol advertising. With theimpact of cigarette advertising, there is this commonclaim from cigarette manufacturers that cigaretteadvertising does not encourage people to smoke whowould not otherwise. In fact, studies show that cigaretteadvertising does not necessarily increase consumption.


13/19


14/19


Figure 7. The dominant research streams of advertising focus 1998 to 2002.

development of advertising theory and practice. Inconducting the present study, the author found changesin the focus of the advertising literature; a summary of thechanges over the past 10 years is provided in Figures 7and 8 and Tables 7 and 8. This study aims to provide anoverview of advertising studies and evaluate the changesof advertising literature in the past decade. Figures 7 and8 show the major focuses of advertising studies from1998 to 2002 and 2003 to 2007, respectively. The boxesabove the central line represent the areas that receivedgreater attention in the advertising literature relative tothe other 5-year period, whereas the boxes below thecenter line represent the areas that received equalattention in both 5-year periods. As these figures andtables illustrate the advertising field saw an expansion ofits core themes and a consolidation of its knowledgenetwork during this 10-year period.

As a result, the advertising research in the period 1998to 2002 was focused on brand attitude, cigaretteadvertising, alcohol advertising, pharmaceutical adver-tising, consumption-related emotions and advertisingcontent and attitudes. The findings indicate that a relative

shift occurred during the period 2003 to 2007, when thedominant research stream changed; there is apredominance of research focus on attitudes, consumerbehavior, and consumer criticism of advertising,perception of commercials, beliefs, positive emotions,advertising prices, product quality, and informativeadvertising research. In conclusion, this paper hasprovided an opportunity to recognize the historical andongoing inputs and output of advertising research asrepresented in the work published in the SSCI and SCIdatabases from 1998 to 2007. There have been changesin the dominant research streams, and advertisingstudies now place emphasis on different themes than inthe past.

Contributions to scholarship

By examining most frequently cited authors and papers,and by analyzing co-citation patterns, it is possible toconstruct a general picture of the field. This lays afoundation of knowledge that will help future scholars

Demandand supplyof priceinformation;

Optimaladvertisingpolicy

The duration ofadvertising effect on sale;Aggregate advertisingmodelsContent analysis inconsumer research;

Advertising informationfunction;Brand Advertisement;

Product quality;Equilibrium distributions;

Optimaladvertising;Optimalquality

Audienceinvolvement;Price attributebeliefs;TV commercials;ELM;

Product attributebeliefs;

Brand attitudes;InformativeAdvertising;Differentiatedproducts;Price & advertisingsignals;Ad. attitudes

Negative politicaladvertising effects;MOA;Print advertising;Advertisingcompletive strategy;Pharmaceuticaladvertising;

Brand attitudes;TV commercials ;Tobacco

advertising;DTC ofprescription drugsadvertising

M a j or a r e a s of a d v e r t i n gf o c u s

1950 s 1960 s 1970 s 1980 s 1990 s


15/19

Tu 9413

Figure 8. The dominant research streams of advertising focus 2003 to 2007.

better understand the shift in advertising research overtime. This study provides insights to effectively identifythe most influential authors and the important articlesfrom the database, which will ultimately enable academiaand practitioners to have a better understanding ofcontemporary advertising studies.

Applied implications

This paper aims to provide valuable research direction forfuture research in advertising while also proposing anobjective means of establishing the relative importance ofdifferent knowledge nodes in the recent development ofthe advertising field.

LIMITATIONS AND FUTURE RESEARCH DIRECTION

This research offers valuable insights into the intellectualstructure of advertising studies; however, it is important toalso acknowledge the limitations of this study. First, itsimportant of objectivity is crucial to a study such as this,yet in choosing the number of authors to be included inthis study, a certain degree of subjectivity is inevitable.Certain judgment calls needed to be made to balancethese contrasting considerations (McCain 1990); with theresulting possibility that certain worthwhile papers maynot have been included. Second, the selection of samplearticles was limited to the period 1998 to 2007, whichmay affect the generalization of this study. Moreover, theresearch method used by this paper was unable to

Advertisingsinformationfunction;Brandadvertising;Product quality;Equilibriumdistributions

Persuasioncommunicationinvolvement;

Product quality;Advertising attitudes;Advertising appeals;

Product attributebeliefs;Brand attitudes;Informative advertising;

Differentiated products;Price and advertisingsignals;Ad. attitudes

Optimaladvertising

policy

Informative ad.;Price attributebeliefs;Advertising

attitudes;Consumercriticism ofadvertising;Optimal control;Alcoholadvertising;

Internetadvertising;

Brand attitudes ;TV commercials ;Print advertising ;

Tobaccoadvertising;

DTC prescriptiondrugs advertising

DTC ofprescriptiondrugsadvertising;Permission-based mobileadvertising

M a j or a r e a s of a d v e r t i n gf o c u

s

1960 s 1970 s 1980 s 1990 s 2000 s


16/19


17/19


18/19


Professor Yender McLee for lecturing on the invisiblenetwork knowledge and for his insightfulinformation in class.

REFERENCES

Acedo FJ, Barroso C, Galan JL (2006). The resource-based theory:Dissemination and main trends. Strat. Manage. J. 27:621-636.

Baron RM, Kenny DA (1986). The moderator-mediator variabledistinction in social psychological research: Conceptual, strategic,and statistical Considerations. J. Personal. Soc. Psychol. 51(6):1173-1182.

Barwise P, Strong C (2002). Permission-based mobile advertising. J.Interact. Mark. 16(1):14.

Batra R, Ray ML (1986). Affective responses mediating acceptance ofadvertising. J. Consum. Res. 13(2):234-249.

Bell RA, Kravitz RL, Wilkes MS (2000). Direct-to-consumer prescriptiondrug advertising, 19891998: A content analysis of conditions,targets, inducements and appeals. J. Fam. Pract. 49:329-335.

Bonacich P (1987). Power and centrality: A family of measures. Am. J.Sociol. 92:1170-1182.

Borgatti SP, Everett MG, Freeman LC (2002). Uncient 6 for windows:

Software for social network analysis. Harvard M.A.: AnalyticTechnologies.Borgman CL (1990). Scholarly communication and bibliometrics.

Newbury Park, CA: Sage.Borgman, C. (2000). Scholarly communication and bibliometrics

revisited. In Cronin B, Atkins HB (Eds.). The web of knowledgeMedfird, NJ: Information Today. pp. 143-162.

Briggs R, Hollis N (1997). Advertising on the web: Is there responsebefore click-through? J. Advert. Res. 37:33-46.

Broadus RN (1987). Toward a definition of Bibliometrics. Scientometrics12(5-6):373-379.

Brown SP, Stayman DM (1992). Antecedents and consequences ofattitude toward the ad A metaanalysis. J. Consum. Res. 19(1):34-51.

Burt RS (1992). Structural holes: the social structure of competition. Cambridge, Harvard University Press.

Butters GR (1997). Equilibrium distributions of sales and advertisingprices. The Review of Economic Studies, 44(3):465-491.

Calfee J (2002). Public policy issues in direct-to-consumer advertisingof prescription drugs. J. Pubic. Policy. Mark., 21(3):174-193.

Casillas J, Acedo F (2007). Evolution of the Intellectual Structure ofFamily Business Literature: A Bibliometric Study of FBR. Fam. Bus.Rev. 20:141-162.

Chintangunta P, Vilcassim NJ (1992). An empirical investigationofadvertising strategies in a dynamic duopoly. Manage. Sci.38(9):1230-1244.

Chou L, Tseng H (2010). Exploring the intellectual structure ofcontemporary tourism studies. J. Qual. 17(2):159-178.

Clarke D (1976). Econometric measurement of the duration ofadvertising effect on sales. J. Mark. Res. 13:345-357.

Crane D (1972). Invisible colleges: diffusion of knowledge in scientificcommunities. Chicago, IL: University of Chicago Press.

Culnan JM (1986). The intellectual development of managementinformation systems, 1972-1982: A co-citation analysis. Manage. Sci.32(2):156-172.

Culnan JM (1987). Mapping the intellectual structure of MIS, 1980-1985: A co-citation analysis. MIS Q. (9):341-350.

Dery R, Toulouse JM (1996). Social structuration of the field ofentrepreneurship: a case study. Canadian J. Adm. Sci. 13(4):285 305.

de Solla Price DJ (1965). Networks of scientific papers. Science149(3683):510515.

de Solla Price DJ (1970). Citation measures of hard science, softscience, technology, and nonscience, In: Nelson, C.E. and Pollock,D.K. (Eds.) Communication Among Scientists and Engineers, pp. 3 22. Lexington, MA, USA: D.C. Heath and Company.

Ding Y, Chowdhury G, Foo S (1999). Mapping intellectual structure ofinformation retrieval: An author cocitaton analysis, 1987-1997. J.

Inform. Sci. 25(1):67-78.Diodato V (1994). Dictionary of bibliometrics. The Haworth Press.

Binghamton, New York.Dorfman K, Steiner PO (1954). Optimal advertising and optimal quality.

Am. Econ. Rev. 12:831.Ducoffe RH (1996). Advertising value and advertising on the web. J.

Advert. Res. 36(5):21-35.Dunn SW, Barban AM, Krugman DM, Reid, LN (1994). Advertising: Its

role in modern marketing, 8th

ed., Chicago: The Dryden press.Edell JA, Burke MC (1987). The power of feelings in understanding

advertising effects. J. Consumer Res. 14(3):421-433.Feichtinger G, Hartl RF, Sethi, SP (1994). Dynamic optimal control

models in advertising: Recent developments. Manage. Sci. 40:195-226.

Fernandez-Alles M, Ramos-Rodriguez A (2009). Intellectual structure ofhuman resources management research: A bibliometric analysis ofthe journal human resource management 1985-2005. J. Am. Soc. Inf.Sci. Technol. 60(1):161-175.

Garfield E (1963). Citation indexes in sociological and historicalresearch. Am. Doc. 14:289-291.

Garramone GM (1990). Effects of negative political advertising on thepolitical process. J. Broadcast. Electronic. Med. 34(3):299-311.

Gorn GJ (1982). The effects of music in advertising on choice behavior:A classical conditioning approach. J. Mark. 46(3):94-101.

Greenwald AG, Leavitt C (1984). Audience involvement in advertising:Four levels. J. Consum. Res. 11(1):581-592.

Gross PLK, Gross EM (1927). College libraries and chemical education.Sci. 66:385-389.

Grossman GM, Shapiro C (1984). Informative advertising withdifferentiated products. Rev. Econ. Stud. 51(1):63-81.

Grube JW, Wallack L (1994). Television beer advertising and drinkingknowledge, beliefs, and intentions among school children. Am. J.Public Health. 84:254259.

Hair JF, Anderson RE, Tatham RL (1998). Multivariate data analysis(5th ed.). Prentice-Hall. Upper Saddle River, NJ.

Hoch SJ, Ha YW (1986). Consumer learning: Advertising and theambiguity of product experience. J. Consum. Res. 13:221-233.

Holbrook MB, Batra R (1987). Assessing the role emotions asmediators of consumer responses to advertising. J. Consum. Res.16(3):404-420

Hollon MF (1999). Direct-to-consumer marketing of prescription drugs:

Creating consumer demand. J. Am. Med. Assoc. 281(4):382-384.Holmer JD, Alan F (1999). Direct-to-consumer prescription drugadvertising builds bridges between patients and physicians. J. Am.Med. Assoc. 281(4):380-382.

Kassarjian HH (1977). Content analysis in consumer research. J.Consum. Res. 4(1):8-18.

Kim J, McMillan S (2008). Evaluation of internet advertising research: Abibliometric analysis of citations from key sources. J. Advert.37(1):99-112.

Krebs V (2002). Mapping networks of terrorist cells. Connections24(3):43-52.

Kravitz RL, Epstein RM, Feldman MD, Franz CE, Azari R, Wilkes MS,Hinton L, Franks P (2005). Influence of patients requests for direct-to-consumer advertised antidepressants: A randomized controlledtrial. JAMA 293(16):1995-2002.

Laudon KC, Laudon JP (1993). Business information system: Aproblem-solving approach (2 nd ed). The Dryden Press. Orlando, FL.

Lievrouw LA (1990). Communication and the social representation ofscientific knowledge. Crit. Stud. Mass Comm. 7(1):1-10.

Lievrouw LA (1989). The invisible college reconsidered: Bibliomertricsand the development of scientific communication theory. Commun.Res. 16(5):615-628.

Little JDC (1979). Aggregate advertising models: The state of the art.Oper. Res. 27(4):629-667.

Lutz RJ, Mackenzie SB, Belch GE (1983). Attitude toward the ad as amediator of advertising effectiveness: Determinants andconsequences. Advances in consumer research. ed. Bagozzi R,Tybout A. Assoc. Consum. Res. Ann Arbor, MI. 10:532-539.

Ma Z, Lee Y, Yu K (2008). Ten years of conflict management studies:Themes, concepts, and relationships. Int. J. Confl. Manage.19(3):234-248.


19/19

Ma Z, Wang Y (2007). An invisible network of knowledge production: 12years of tourism management studies (1994-2005). Paper presentedat the annual meeting of the administrative sciences association ofCanada (ASAC).Ottawa, ON, Canada.

MacInnis DJ, Moorman C, Jaworski BJ (1991). Enhancing consumers'motivation, ability and opportunity to process brand information fromads: Conceptual framework and managerial implications. J. Mark.55:32-53.

MacInnis DJ, Jaworski BJ (1989). Information Processing fromAdvertisements: Toward an Integrative Framework. J. Mark. 53:1-23.

Mackenzie SB, Lutz RJ (1989). An empirical examination of thestructural antecedents of attitude toward and ad in an advertising pre-testing context. J. Mark. 53(2):48-65.

Marshakova IV (1973). A system of document connection based onreferences. Scientific and Technical Information Serial of VINITI. 6(2):3-8.

McCain KW (1990). Mapping authors in intellectual space: A technicaloverview. J. Am. Soc. Inform. Sci. 41(6):433-443.

McCain KW (1989). Descriptor and citation retrieval in the medicalbehavioral science literature: Retrieval overlaps and noveltydistribution. J. Am. Soc. Inform. Sci. 40(1989):110-114.

Milgrom P, Roberts J (1986). Price and advertising signals of productquality. J. Polit. Econ. 94(4):796-821.

Mitchell AA, Olson JC (1981). Are product attribute beliefs the onlymediator of advertising effects on brand attitude? J. Mark. Res.18(3):318-332.

Mittal B (1994). Public assessment of TV-advertising-faint praise andharsh criticism. J. Advert. Res. 34(1):35-53.

Mueller B (1987). Reflections of culture-an analysis of Japanese andAmerican: Advertising Appeals. J. Adv. Res. 27(3):51-59.

Nelson P (1974). Advertising as Information. J. Polit. Econ. 82(4):729-754.

Nerlove M, Arrow K (1962). Optimal advertising. Policy under DynamicConditions. Econ. 29:129-142.

Nerur SP, Rasheed AA, Natarajan V (2008). The intellectual structure ofthe strategic management field: An author co-citation analysis. Strat.Manag. J. 29(3):319-336.

Oliver AL, Ebers M (1998). Networking network studies: An analysis ofconceptual configurations in the study of inter-organizationalrelationships. Organ. Stud. 19(4):549-583.

Parvinen P (2003). Towards a governance perspective to mergers and

acquisitions. Doctoral Dissertation. Espoo, Helsinki University ofTechnology.Pasadeos Y, Phelps J, Kim BH (1998). Disciplinary impact of

advertising scholars: temporal comparisons of influential authors,works and research networks. J. Advertising 27(4):53-70.

Pasadeos Y, Renfro RB, Hanily ML (1999). Influential authors andworks of the public relations scholarly literature: A network of recentresearch. J. Public Relat. Res. 11(1):29-52.

Petty RE (1983). Central and peripheral routes to advertisingeffectiveness: The moderating role of involvement. J. Consum. Res.10:135-146.

Petty RE, Cacioppo JT (1986). The elaboration likelihood model ofpersuasion. Adv. Exp. Soc. Psychol. 19:123-205.

Pierce JP, Choi WS, Gilpin EA, Farkas AJ, Berry CC (1998). Tobaccoindustry promotion cigarettes and adolescent smoking. Jama-J. Am. Med. Assoc. 279(7):511-515.

Pilkington A, Chai KH (2008). Research themes, concepts andrelationships: A study of international journal of service industrymanagement (1990-2005). Int. J. Serv. Ind Manage.19:83-110.

Pilkington A, Fitzgerald R (2006). Operations management themes,concepts and relationships: A forward retrospective of IJOPM. Int. J.Oper. Prod. Manage. 26:1255-1275.

Pilkington A, Teichert T (2006). Management of technology: Themes,concepts and relationship. Technovation 26:288-299.

Pilkington A, Liston-Heyes C (1999). Is production and operationsmanagement A discipline? A citation / co-citation study. Int. J. Oper.Prod. Manage. 19:7-20.

Pollay RW, Mittal B (1993). Heres the beef Factors, determinants,and segments in consumer criticism of advertising. J. Mark. 57(3):99-114.

Tu 9417

Pollay RW, Siddarth S, Siegel M, Haddix A, Merritt RK, Giovino GA,Eriksen MP (1996). The last straw? Cigarette advertising and realizedmarket shares among youths and adults. J. Mark. 60(2):1-16.

Pritchard A (1969). Statistical bibliography or bibliometrics? J. Doc.24(4):348-349.

Ratnatunga J, Romano C (1997). A citation classics analysis of articlesin contemporary small enterprise research. J. Bus. Venturing 12:197-212.

Reeves B, Borgman C (1983). A bibliometric evaluation of core journalsin communication research. Hum. Commun. Res. 10:119-136.

Rosenthal MB, Berndt ER, Donohue JM, Frank RG, Epstein AM (2002).Promotion of prescription drugs to consumers. New. England. J. Med.346(7):498-505.

Scott LM (1994). Images in advertising- The need for a theory of visualrhetoric. J. Consum. Res. 21(2):252-273.

Sharplin A, Marby RB (1985). The relative importance of journals usedin management research: An alternative ranking. Hum. Relat. 38:139-149.

Shavitt S, Lowrey P, Haefner J (1998). Public attitudes towardadvertising: More favorable than you might think. J. Advert. Res.38(4):7-22.

Small H (1973). Co-citation in the scientific literature: A newmeasurement of the relationship between two documents. J. Am.Soc. Inform. Sci. 24(4):265-269.

Small HG (1974). Multiple citation patterns in scientific literature: Thecircle and hill models. Inform. Storage. Retr. 10:393-402.

Small HG (1980). Co-citation context analysis and the structure ofparadigms. J. Documentations. 36(3):183-196.

Stigler GJ (1961). The economics of information. J. Polit. Econ.69(2):213-215.

Tankard JW, Chang TK, Tsang KJ (1984). Citation networks asindicators of Journalism Research Activity. J. Q. 61(124):89-96.

Tijssen RJW, Van Raan AJJ (1984). Mapping changes in science andtechnology: Bobliometric co-occurrence analysis of the R & Dliterature. Eval. Rev. 18(1):98-115.

Usdiken B, Pasadeos Y (1995). Organizational analysis in NorthAmerica and Europe: A comparison of co-citation networks. Organ.Stud. 16(3):503-526.

Varkratsas D, Ambler T (1999). How advertising works: What do wereally know? J. Mark. 63(1):26-43.

Walstrom KA, Leonard L (2000). Citation classics from the information

systems literature. Inform. Manag. 38:59-72.White HD (1990).Author co-citation analysis: Overview and defense.Bibliometrics and Scholarly Communication, C. Borgman, (ed.).Sage. Newbury Park, CA. pp. 84-106.

White HD, McCain KW (1998). Visualizing a discipline: An author co-citation analysis of information science, 1972-1995. J. Am. Soc.Inform. Sci. 49(4):327-355.

White HD, Griffith BC (1981). Author co-citation: A literature measure ofintellectual structure. J. Am. Soc. Inform. Sci. 32(3):163-171.

White DH, Griffith BC (1982). Authors as markers of intellectual space:Co-citation in studies of science, technology and society. J. Doc.38:255-272.

Wilkes MS, Bell RA, Kravitz RL (2000). Consumer-directed prescriptiondrug advertising: Trends, impact, and implications. Health Affair19:110128.

Wilkes MS, Doblin BH, Shapiro MF (1992). Pharmaceuticaladvertisements in leading medical journals - Experts assessments.Ann. Int. Med. 116(11):912-919.

Wolfe S (2002). Direct-to-consumer advertising Education or emotionpromotion? New. England. J. Med. 346(7):524.

Woloshin S, Schwartz LM, Tremmel J, Welch HG (2001). Direct-to-consumer advertisements for prescription drugs: What are Americansbeing sold? Lancet. 358:1141-1146.

Zuccala A (2006). Modeling the invisible college. J. Am. Soc. Inform.Sci. Technol. 57(2):152-168.

Documents

Influential Authors in ADVT