How Promotional Content Changes Ratings: The Impact of ...online.sfsu.edu › beca300 › eastmanca.pdfSusan Tyler Eastman, Gregory D. Newton, and Paul D. Bolls ABSTRACT This study

Journal of Applied Communication ResearchVol. 31, No. 3, August 2003, pp. 238–259

How Promotional ContentChanges Ratings:

The Impact of Appeals, Humor,and Presentation

Susan Tyler Eastman, Gregory D. Newton, and Paul D. Bolls

ABSTRACT This study assessed the impact of content—as opposed to structural—fac-tors on television program ratings, seeking to locate clusters of components that wouldidentify effective on-air promotion and allocate content a better-defined place withintheoretic models of media priming. Stepwise multiple regression analyses of 1,547 on-airpromos for 155 prime-time programs demonstrated that 5–9% of ratings variance wasaccounted for by content appeals, humor, and presentation in promos for comedyprograms. The influence of content variables was greater for familiar than unfamiliarcomedies, and humor and presentation in promos contributed to variance in ratings formid-rated but not high- or low-rated comedies.KEY WORDS: Comedy promotion, content appeals, humor, priming, program pro-motion, ratings

O n-air promotion’s importance to prime-time ratings has been beyond ques-tion for the last decade. Estimates are that the major broadcast networks

collectively air as many as 30,000 promos yearly (Ferguson, 2002), using upirreplaceable air time. Touting prime-time programs has become a big-budgetitem for the television industry, occupying more than $4 billion in air time thatotherwise could be sold for commercials and that necessitates high in-houseproduction costs (Eastman & Newton, 1998b). Competition from cable networksand the internet, hugely increased license fees for series programs, and prolifer-ating user technologies such as remote control devices, personal video recorders,and video-on-demand have made effective on-air promotion crucial to networkprogramming strategy. Nonetheless, scholarly research in this arena has beenlimited despite decades of industry practice—leaving questions about how andwhy on-air promotion impacts program ratings.

Only a few programs, such as the Super Bowls, Academy Awards, and

Susan Tyler Eastman is Professor in the Department of Telecommunications at Indiana University inBloomington, Indiana; Gregory D. Newton is Assistant Professor in the School of Telecommunicationsat Ohio University in Athens, Ohio; Paul D. Bolls is Assistant Professor in the Edward R. Murrow Schoolof Communication at Washington State University in Pullman, Washington. Direct correspondence tothe first author at the Department of Telecommunications, Indiana University, 1229 E. Seventh Street,Bloomington, IN 47405-5501 or [email protected].

Copyright 2003, National Communication AssociationDOI: 10.1080/0090988032000103458

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Olympics, are considered self-promoting, that is, able to attract a mass audiencewithout help from on-air spots (promos) or newspaper and program-guideadvertising.1 Most of the prime-time schedule depends on a steady stream ofpromotional announcements to elicit audience interest in watching shows aswell as to convey reminders of the day and time they appear. Capturing anaudience for a new series program is almost wholly dependent on having botha strong lead-in and extended on-air promotion, but continuing programs mustalso promote upcoming episodes, guests, and plot twists to maintain audiences(Eastman, 2000).

Investigating on-air promotion has importance for two reasons. First, promoscan be viewed as a form of high-stakes advertising. On-air promos are, inessence, advertisements for a television network’s own product, entertainmentprograms. As with advertisements, an effective on-air promo will present theproduct in a way that will make its target audience want to sample it. The degreeto which on-air promos are successful at advertising programs is presumed toaffect the programs’ ratings which, in turn, substantially impact the amount ofmoney the network can charge for advertising time during those programs.

Second, promos are among the factors that influence viewers’ evaluation ofprogram content; they affect viewer decision making. Promos entice viewers tosample unfamiliar shows and new episodes of familiar programs. Moreover,list-style promos and combined spots promoting multiple programs supply amemory framework for understanding an evening’s program schedule and thesequence of the individual programs within it which, in turn, influences tuningbehavior. Clearly, such factors as previous experiences with a program (or genreor even a particular network) and a viewer’s intended viewing situation (withfamily or friends, for example) may also impact viewers’ reactions to specificpromos. Nonetheless, previous studies—using thousands of promos and pro-grams over long periods of time—have demonstrated that promotion appears tohave a modest impact on viewing above and beyond those factors (Billings,Eastman, & Newton, 1998; Eastman & Newton, 1998b, 1999; Eastman, Newton, &Pack, 1996: Walker, 1993).

In on-air promotion, sets of appeals frame the value to viewers of watchingprograms, often called the benefits in industry jargon (Eastman, 2002). When aprogram is promoted as “very touching,” for example, the benefit is that theviewer gets to feel the tender emotion of poignancy and experience the betterside of human nature. Similarly, when a program is promoted as suspenseful, thebenefit is the enjoyable experience of being scared—within the wholly safecontext of a television program. Such appeals are equivalent to what researchersVakratsas and Ambler (1999) identify as affect in commercial messages. Thus,emotional appeals are shorthand for a program’s content, or at least for thatportion of the content picked up for inclusion in promos. Although contentappeals are related to the idea of program quality, the former are identifiable andmeasurable, whereas quality (or whatever makes programs popular) generally isnot. In practice, the appeals appearing in promos are selected by creativeproducers on a largely intuitive basis from the unwieldy mass of programcontent, often under pressure from tight deadlines (Ferguson, 2002). Isolatingappeals that significantly affect ratings should contribute to theoretical andpractical models of the process of building audience size. Viewer decisionmaking is, after all, the central concern in programming research.

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PROMOTIONAL CONTENT EASTMAN ET AL.

As previous research has focused almost exclusively on structural factors inpromotion affecting program ratings (such as location, associated clutter, length,and so on), this study distinguishes between content and structural componentsand separates their relative influences. The purpose of this study is to look forthe factors in promos having measurable impact on comedy viewing, as deter-mined by changes in Nielsen ratings. Another goal of this line of research is tolocate clusters of components that suggest empirically-derived guidelines foreffective promotion.

Applicable Theories

The industry invests billions of dollars annually—even in tight economictimes—in promoting television programs on the presumption that audience sizewill be affected. At the same time, explaining promotion’s impact on a theoreti-cal level necessitates accounting for three characteristics of promotional spots:(a) entertainment promos typically beget very low level, mundane reactionsrather than highly arousing experiences; (b) promos’ impacts on ratings aregenerally modest in size; and (c) promos’ impacts commonly occur in spite ofintervening activities and at substantial distances in time from the programsbeing promoted, thus any effects occur across hours, days, and weeks. The sizeof any collective impact from a large body of promos must necessarily be smallbecause of the nearly overwhelming impact of inherited viewing (lead-in ratings)and program popularity (carriage and promoted program ratings), and the ines-capable fact that most new programs have such low ratings that they will becanceled within a year. Moreover, most ratings are understood to containsignificant amounts of sampling and data collection error. Nonetheless, decadesof industry assumptions about the critical impact of promos have led to thewidespread and costly practice of extensive promotion of television shows inadvance of their airdates.

One problematic issue for research has been identifying the parts of promo-tional messages that contribute to their effects. A growing body of research ontelevision advertising addresses message effects from a cognitive and emotionalperspective (Hazlett & Hazlett, 1999; Lang, Bolls, Potter, & Kawahara, 1999;Nelson, Shavitt, Schennum, & Barkmeier, 1997; Rossiter & Silberstein, 2001;Yoon, Bolls, & Muehling, 1999). If promos are similar to ads, then cognitive andemotional processes probably act as the mechanisms underlying the effects ofpromotional messages. Two likely candidates for providing a theoretical linkbetween parts of promotional messages and their cognitive and emotional effectson viewers are excitation transfer and associative priming effects.

From a theoretical viewpoint, excitation transfer theory holds that content ableto stir viewers’ emotions may lend those emotions to subsequent viewing(Mundorf, Zillmann, & Drew, 1991; Zillmann & Weaver, 1999). Indeed, researchhas produced evidence of emotional effects transferring from programs to com-mercials as well as from commercials to adjacent programs. Mattes and Cantor(1982) showed that watching highly arousing programs led to higher levels ofenjoyment of commercials, and Mathur and Chadpadhyay (1991) showed thatprogram-induced moods transferred to reactions to commercials. Looking forhumor’s transference effects, Perry, Jenzowski, King, Hester, and Yi (1997) foundthat the presence of more humorous commercials in a show increased viewer

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enjoyment and the program’s perceived entertainment value, but found noinfluence in the opposite direction. In other words, humor in programs wasfound to have no influence on commercial enjoyment (Bjorna, Karsal, Vicary,Wagner, & Perry, 2001).

Nonetheless, a form of excitation transfer effect has been proposed as apossible explanation for how advertising works on a target audience. Associa-tional learning in consumer behavior occurs when a favorable response evokedby one stimulus is directed or transferred to another (Mullen & Johnson, 1990).Advertising that is successful at achieving associational learning evokes positiveemotions and thoughts that get transferred to the product itself. In the context ofon-air promotion, this means that emotions evoked during exposure to a promocould be transferred to the program and have some influence over viewingdecisions.

It is important to note that proposing excitation transfer as a possible cognitiveand emotional mechanism behind the effects of on-air promos requires a majorextension of the original theory. In studies of television content, excitationtransfer has only been demonstrated for very short lengths of time, and inlaboratory experiments arousal levels return to normal in seconds. This time-frame excludes promos’ apparent impact over much longer time periods. Apply-ing excitation transfer to the effects of promos would require the emotionsevoked by a promo either to (a) maintain some level of activation in workingmemory until a viewing decision is made, which could be several days afterexposure to the promo, or (b) reside in long-term memory where emotions areassociated with the program. Clearly, the low-level emotions evoked by promosare unlikely to remain intensely active over the course of days. Recent models ofhuman cognition, however, suggest that the emotional characteristics of stimuliget stored in memory in a manner that enables the activation of the sameemotions when a cue related to the original stimulus is encountered again, evendays later (Damasio, 1994). This means that emotions evoked by a promo couldmaintain some level of background activation, and be transferred to the pro-moted program when a viewer is cued to think about the program.

Zillmann (1971) has defined the excitation transfer effect as a matter ofincomplete decay of arousal, a definition that excludes promos’ apparent impactover much longer time periods. It seems, nonetheless, that the association ofemotions with a program during exposure to a promo may be explained as are-experiencing that occurs when a viewer is cued to think about a program.Thus, the process could constitute an incomplete decay of arousal that triggersanother excited state that is then transferred to the program. We have named thisthe secondary excitation transfer effect. While this notion goes beyond tra-ditional views of the excitation transfer effect, it seems premature to rule out amultistep excitation transfer process as the cognitive and emotional mechanismbehind the effects of promos until further experimental research can be conduc-ted.

Associative priming theory also provides part of the conceptual explanation ofthe promotional process. Research on associative priming, as Jo and Berkowitz(1994, p. 46) have pointed out, shows that “ideas having emotional significanceare linked associatively” to subsequent behavior. They also note that thinkingabout a behavior increases the likelihood of carrying out that behavior, and thatvisual stimuli such as video generate relatively high recall. Roskos-Ewoldsen,

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Roskos-Ewoldsen, and Carpentier (2002) summarize research showing that me-dia influence later behavior by priming aggression, stereotyping, and politicaljudgments, and thus, it follows that an arousing television promo that urgesviewers to tune in at a later time to experience a program might well have animpact on some viewers. While the content may be important because of itsarousing nature, however, any impact on viewing occurs long after particularjokes and plot moments are forgotten. It may be that secondary arousal transfersto behavior when the proper occasion (another promo or perhaps merely theright date and time) occurs. Nonetheless, the explanations falter inasmuch assituation comedy promos typically generate only the most modest of emotionalreactions of any kind, yet they apparently provoke subsequent viewing (by somepeople some of the time). Roskos-Ewoldsen et al. hold that “people have myriadmental models stored in long-term memory” (2002, p. 112) and that the mediacan prime these memories, meaning that media content will make these memor-ies readily accessible. Extending this mental model view of priming into promo-tional priming leads to the proposition that promos evoke viewers’ mentalmodels of television programs or, conversely, that the beginning of a program (orits title, music, teaser) evokes previously viewed promos that are stored inlong-term memory.

The model of promotional salience developed by Eastman and Newton (1998b,1999) adds another level of explanation to this discussion. Salience theoryproposes that on-air promos with specific attributes—those that make promosprominent in their environments—are more likely to have an impact on viewingthan promos with fewer of those attributes (or that have the attributes but in anon-salient condition). The idea is that certain conditions of variables—first orlast position in breaks, within-program location, little clutter in breaks, and adozen others—are structural factors that enhance attention to promos and conse-quently generate their impact on program ratings. By extension, salience theorysuggests that aspects of content, such as the appeals, humor, and presentation(execution in industry jargon) that are the focus of this study, can effectivelycreate expectations about programs under some conditions and, therefore, havean impact even without high levels of emotional arousal. Thus, associativepriming and secondary transference may together account for the relationshipbetween the promo and the program, while salience theory may identify theconditions of attributes creating the expectations.

A first step in testing priming along with secondary transference as possiblecognitive and emotional mechanisms behind promotional effects is to find outwhether a relationship between promos’ content components and programratings can be isolated. However, programming scholars already know that thesingle biggest component of program ratings is viewing inherited from thepreceding program (Webster & Phalen, 1997).2 This study looks only at situationcomedies in order to include the component of humor in promos, but when airedin prime time, situation comedies are nearly always blocked in groups for thefirst hour or two. The consequence is that inheritance should be particularlystrong from comedy to comedy, irrespective of the amount and type of pro-motion received by the individual programs. While inheritance and other struc-tural characteristics of promos have previously been shown to affect programratings (see Eastman & Bolls, 2000 for a summary), this study provides the first

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direct test of the assumption that certain aspects of content also impact audiencesize.

H1: In addition to structural components, promos’ content components willsignificantly affect the ratings of promoted comedies.

Turning to the factor of program popularity as measured by Nielsen ratings,Eastman and Newton (1998a, 1998b) showed that promotion’s impact wasgreatest on the mid-rated shows, probably because the top-rated hits werealready about as high in audience size as they could go, and the bottom-ratedlosers would be promoted less and less until they were canceled. The Eastmanand Newton findings led to the practice of assessing promotion’s impact on thetwo mid quartiles (that is, the middle half) of programs as subdivided by theirratings. The consistency of previous findings for structural variables suggests asecond hypothesis.

H2: Content-related promotional variables will account for more variance in ratingsfor mid-rated comedies than for high-rated or low-rated comedies.

Practitioners concerned with the effects of advertising have been asking howads work for decades. Based on a meta-analysis of advertising studies, Vakratsasand Ambler (1999) proposed a three-dimensional model of advertising effective-ness with components of cognition, affect, and experience. They concluded thatthe cognitive aspects of ads were more important than their affective dimensionsfor high-involvement products, but that the affective aspects were more import-ant for low-involvement products; they also found that experience mattered mostfor mature, familiar products. Although their model was derived from studies ofads for consumer goods, it can be adapted to program promotion: If promos areindeed low-involvement messages, then they are most likely to be most effectivewhen they emphasize affect. Nevertheless, structural factors must be accountedfor, leading to this hypothesis:

H3: After the structural variables of lead-in ratings and carriage program ratings,appeals in comedy promos will contribute more to ratings variance thanpresentation or humor.

Walker (1993), however, showed that the familiarity of the program was key toeffective promotion, and that more frequent promotion of continuing (but notnew) programs was positively related to their ratings. Taking Vakratsas andAmbler’s (1999) and Walker’s conclusions a step further, when promos are forfamiliar programs, affect will be the crucial component, whereas in promos forunfamiliar programs, structural variables will dominate and, consequently, con-tent variables should have relatively little impact. The question then shifts backto the sources of affect in program promos. It may be that the appeals in on-airpromos, especially those alleging benefits for viewers, will most impact viewingof familiar programs. Paraphrased, these extensions lead to this hypothesis:

H4: The ratings for familiar comedy programs will be more affected than the ratingsfor unfamiliar comedies by the affective appeals contained within the promos.

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Prior Research About Humor

Another factor, related to appeals and likely to be crucial when evaluatingpromos for situation comedies, is comedy or humor—a widely-used indicator ofarousal. A reasonable presumption in most studies was that more humor impliesgreater likely impact. According to Speck (1990), scholars have identified severalbasic processes in humor, three of which apply to television commercials. Thefirst of these, arousal-safety (or Ahhh humor), is a mechanism that allows relieffrom strain or from the need to repress feelings. Laughter usually occurs whena person experiences increased arousal but evaluates the stimulus (typicallyanother person) as safe, cute, or inconsequential, as in much family humor. Thesecond type of humor, identified as incongruity-resolution (or Ah-Ha humor),occurs when two ideas cannot be assimilated using the same schema or, in otherwords, when the outcome of a story or event doesn’t fit with the audience’sexpectations, as occurs in puns, punch lines, comic reversals, understatement,and exaggeration. The third type of humor Speck calls humorous disparagement(or Ha-Ha humor), referring to censure, detraction, denunciation, or in present-day slang, dissing. Much hostile or aggressive humor falls into this category.Because writers and producers generally want the audience to feel good afterjokes or laugh at put-downs, they avoid getting mean or ugly in promos, andbecause clips are very rarely short (usually excerpted from the program) anddirected at broad audiences, promos are very subtle or witty. All three types ofhumor (and perhaps several others) probably appear within comedy programs,but only certain types will be selected by the producers or programming andpromotion executives to appear within promos. In preparation for this study, apreliminary survey of adult reactions to sitcom promos (Eastman & Bolls, 1999)showed that virtually all the humor in a large promo sample was identified byviewers as one of these three types. Because measuring the quantitative amountof humor proved unreliable in pilot studies, this analysis focuses on the type ofhumor and investigates the relationship between type and impact.

An additional factor is the presentation of the promo. Eastman and Bolls(2000) analyzed open-ended responses from nearly 2,000 adult television view-ers about why they might or might not watch a new program based solely onviewing a promo. Analysis showed that more than one-third of comments relatedto the promos (37%), rather than to the actors, storylines, or networks, andfocused on humor and presentation (music, effects) within the promo.

The advertising literature contains many studies of execution that look at theway commercials (and by extension promos, if considered as advertisements forprograms) are implemented. Some studies have examined how the viewer feelsabout the presentation of the product being pitched. Lang (1990), for example,has demonstrated that physiological responses to structural features of commer-cials are intensified by mild emotional content. Two feelings can be dis-tinguished: (a) how the viewer feels about the product based on purchase, use,price, quality, and so on, and (b) how the viewer feels the product is beingpresented in a commercial (Laskey, Fox, & Crask, 1994; Stewart & Furse, 1986).Although viewers’ feelings about television shows are part of the equationleading to ratings, this study focuses on the second meaning of presentation (orexecution) to assess that characteristic of on-air promos. Lang, Geiger, Strick-werda, and Sumner (1993) and Yoon, Bolls, and Lang (1998) examined aspects of

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presentation in advertising research that include pacing in terms of length andnumber of editing cuts, narrative structure, recognition of background scenes,and the degree to which the message informs users about the things they wantto know. When their findings are applied to promos, the use of quick cuts orrelatively slow-paced camera changes (apparent pacing) might be expected totransfer to viewers’ expectations about promoted programs and thus impactratings to some small degree. As Eastman (2002) points out, all measurableimpacts are likely to be small but significant because tiny shifts in ratings affectmillions of dollars in annual advertising revenue.

The focus of this study was not the appeals, humor, and presentation in theprograms themselves. Instead, it was expected that within 5-, 10-, 15- and30-second promos the inclusion of certain kinds of appeals or representations ofcertain kinds of humor might have close association with certain types ofpresentation and thus, as a group, affect ratings (in addition to the well-recog-nized elements of inherited viewing and the structural variables in promotionidentified in previous studies). If such combinations could be identified, theywould further refine the current models of advertising and promotional effective-ness and suggest empirically-based guides for industry practitioners. Because solittle research has been published about the role of content in on-air promotion,in addition to the four hypotheses already identified, this study posed one broadresearch question. It serves as a first step towards forming a model to guidepractitioners and subsequent research into promotion:

RQ1: Can combinations of certain kinds of presentation, specific appeals, and typesof humor be identified within promos that associate with significant increasesin comedy program ratings?

Method

Because prime time is the most watched daypart and because half-hourprograms maximized the number of programs in the database, this study lookedonly at prime-time promotion. It analyzed only on-air promos for half-hoursituation comedies (live or animated); humor was included and genre-relatedvariation excluded. The prime-time hours on all six broadcast networks werevideotaped by the researchers for six weeks: two weeks in October 1998, twoweeks in May 1998, and two weeks in April/May 1999.3 These purposivesamples encompass the highly-produced promos for new program introductions(October), where many programs would be unfamiliar, big-budget cliffhangerscomprising the culminating episodes of many series (April), and the end-of-sea-son program specials (May); they also avoid the extreme fluctuations in audiencesize occurring between winter and summer and reflect a mix of sweeps andnonsweeps months. Promotional messages of less than three seconds in lengthwere excluded, and no promos longer than 30 seconds were reported.

Coders

In addition to the three researchers, three classes of student coders worked onthis project. One class pretested the coding sheet in two iterations, resulting inthe rewording of confusing or redundant appeals, reducing the number of

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options for narrative structure, and eliminating measures of the quantity ordegree of humor because reliabilities were low. Two subsequent classes of 22and 31 students analyzed the videotaped promos, and all 218 tapes were codedat least twice, each time by different students. The first class analyzed the fourweeks of 1998 tapes; the second class reanalyzed the four weeks of 1998 as wellas the two weeks of 1999 tapes. The students undertook the coding for a gradeas part of an upper-division seminar in electronic media promotion, and theywere required to write a separately-graded paper about the research process. Twoclass periods were devoted to training each class of coders, focusing on distin-guishing promos for network sitcoms from local rerun sitcom spots, identifyingappeals and types of humor, utilizing the semantic-differential scales, andcounting shot changes. Stopwatches were supplied to measure promo length.

In the training and written instructions, coders were repeatedly directed togive their attention to the promo and its content and presentation, and not toconsider their reactions to whatever program was being promoted. Because theywere enrolled on a course specifically about media promotion and marketing, notprogramming, focusing on the promos was a reasonable expectation.

Coding Instrument

The coding sheets requested nine items of structural and sorting data, includ-ing (a) identification of the type (or absence) of humor, (b) an assessment of thepromoted program’s familiarity to the coder, (c) 14 ratings of specific appeals,and (d) four measures of presentation of the promo’s content. Followingspecification of the network, date and time, and name of the program containingthe promo (the carriage program), coders were asked to code the name, date andtime of the sitcom being promoted, the construction of the spot (operationalizedas the number of named programs included in the promo), and the distancebetween the promo and its program (operationalized as the next show; latertonight; tomorrow night; later in the same week; next week—between seven and14 days away; and much later—with space to supply a date if one was given).

Coders classified the predominant type of humor used in the promo bychoosing one of three options: relief/cute (followed by a definition and the words“arousal-safety or Ahhh!”), surprise/mismatch (definition and “unexpected in-congruity or Ah-Ha!”), and put-down/sarcasm (definition and “dissing and satireor Ha-Ha!”). Pretesting using promos not in the sample had demonstrated thatthe coders could consistently distinguish between types of humor and identifyone dominant type even when more than one type appeared in 30-second spots.In a few cases, promos for sitcoms had no humor component, which wasrecorded.

The coding instrument listed 14 appeals to rate on a nine-step semanticdifferential, anchored by not very or weak on the low end and very orstrong on the high end. Following the heading question “How does the promomake the show seem to look?” were seven phrases anchored from negative topositive, as in not very funny to very funny, along with not very realistic, notvery new, not very uplifting, not very hip/trendy, not very critically acclaimed,and not very suspenseful. Following the heading question “What does the promomake the show seem to have?” were seven more appeals: a not very puzzlingsituation (to a very puzzling situation, and so on), weak star appeal, weak sex

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appeal, characters not easy to identify with, not very realistic characters, a notvery intriguing situation, and no network popularity.

Presentation was operationalized in four ways: as background scene, narrativestructure, informational value, and the pacing of the promo. For the primarybackground scene, the options were bar/restaurant, workplace, school, home/family, singles’ apartment, and other. Based on the results of pretesting, threeoptions for the promo’s narrative structure were provided: clip, with or withouta voice over (a short scene from the show with dialogue); announcement (a castmember speaking directly to the audience, sometimes accompanied by a briefvoiceover); and other. The informational value of each promo was assessed withthe question: “How informative was this promo?” Coders responded from not atall informative to very informative on a nine-step semantic differential.

Pacing was assessed in two ways. Coders were asked to count the number ofcuts (shot changes) in a promo (or in a segment dealing with one program duringa spot promoting multiple shows) and to record the clock length in seconds ofthe promo (or individual segment). Pacing was then calculated as the number ofcuts divided by length. Coders also made their own assessment of the pacing ona five-step semantic differential, ranging from very slow to very fast. Finally, forsorting purposes, a global measure of the coder’s familiarity with the promotedprogram was also obtained using a nine-step semantic differential anchored bythe terms not very familiar and very familiar.

Subsequent to coding, four additional kinds of information were added to thedatabase by the researchers. The frequency of promotion of each program wascalculated from the database, and the published ratings for each carriage andpromoted program were added, in the latter case utilizing only the rating for theepisode closest in time to the promo’s appearance. To account for the impact ofinheritance, the rating for the lead-in program was also entered. When unavail-able because the sitcom was scheduled as a prime-time lead-off, the mean of alllead-ins in that two-week period was substituted for the missing data, thusmaintaining sample size and utilizing all identified promos and situation come-dies.4

Ratings Analysis

For the analyses dealing only with mid-rated comedies, researchers identifiedthe range of high to low ratings separately for each network because the range ofratings varies even within the “Big Three” (ABC, CBS, NBC) and widely outsidethem (Fox, UPN, WB). One network’s ratings, for example, might have a high of17.5 and low of 5.5, while another has a high of only 4.9 and a low of 1.9. Themiddle half of each network’s ratings was calculated independent of the othernetworks by computer subroutine.

Coding Reliability

The researchers looked for coding errors at five stages in the research process.During an initial examination of completed coding sheets, they discarded thosewith blank or off-scale responses, and scheduled the tapes for recoding. Inaddition, absence on a training day, and in-class responses or project papersshowing misunderstandings of the protocols, triggered recoding of a student’s

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tapes. After the second tentatively approved coding, the two analyses werecompared on administrative items and factual items about the carriage andpromoted programs, spot construction, distance, pacing, length, backgroundscene, and narrative structure. Any discrepancies in these items led to a third (orfourth) coding. During data entry by the researchers, the coding sheets wereagain examined for missing or inconsistent data. Whenever the ratings of the 14appeals and one scaled information item differed by more than two steps on thenine-step scales, a recoding was undertaken (blind to the original evaluations).Because the number of students in the second participating class was not anexact multiple of the number of tapes to be coded, students were available forrepeated recodings for class credit. In addition, one student was hired to recodethe promos in 16 of the 218 tapes. When two codings of the appeals agreedwithin two degrees (within two steps on each of the 15 items) and on all otherfactual items, one of the codings, selected at random, was subsequently retainedin the database. Finally, during statistical analysis, high measures of inconsis-tency on some appeals flagged two students’ work and led to recoding of all fourof their tapes. As a final check, comparisons were made of 12 randomly selectedpairs of final coding sheets. Following Holsti’s (1969) method, calculationsshowed 93% reliability on the 14 appeals (in other words, an average of five ofthe 126 decision steps differed by up to two degrees per pair).

Results

Altogether, 1,547 promos for 155 different situation comedies (for more than300 different episodes) were located. Results showed that two-thirds (68%) ofthe promos were multiple spots promoting more than one program (in thepatterns of two to four sitcoms together), leaving just one-third as single spots(32%). More than one third of the promos (37%) were for programs scheduledlater the same week; 20% were for the same night; 17% for the next night; and23% for the following week (generally the next episode); only 3% were for aprogram more than one week away. The promos’ narrative structure was similarfrom program to program as well as from network to network because of thecurrent style of using a clip from the program with a voice-over narration,although occasionally, a star spoke directly to the audience (LL Cool J of In theHouse, and Wayans Brothers). Thus, lacking variance, no distinctions in impactcould emerge for the narrative aspect of promo presentation. About one third(34%) of the comedy promos had a home or family situation as the primarysituation, the second most frequent location was the workplace (31%), with amix of bars/restaurants (15%), singles’ apartments (9%), and mixed other loca-tions (11%) having progressively smaller proportions of promo backgrounds.

The number of cuts in the promos varied from less than three (33%), four tofive (26%), six to eight (21%), to more than eight (20%). In general, codersassessed the promos’ pacing as fast (36%) or in the middle (36%), rather thanvery fast (15%) or slow or very slow (13%). The three kinds of humor were fairlywell distributed across the sample, with 38% using cute type, 36% usingsurprise, 24% using sarcasm, and just 2% not funny.

The variable of promo length was measured as the total clock time (in seconds)devoted to a single program. A 30-second multiple spot might have portions ofdiffering lengths devoted to its programs. The distribution of lengths was as

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follows: 27% were of 5 seconds or less, 39% were of 6–10 seconds, 15% wereof 11–15 seconds, 10% were of 16–20 seconds, and 9% were of 21–30 seconds.5

Promo Content to Program Impact

The first and most important question driving this study was whether reac-tions to content significantly impacted program ratings, and as Tables 1 to 3show, they certainly appeared to do so. Although multiple regression analysesrevealed that the well-established inheritance and structural variables related topromotion predicted the greatest amounts of variance in most analyses, severalcontent-related variables also appeared to contribute significantly to subsequentprogram ratings. For example, Table 1 reports the analysis of the 1,547 promosfor the total database of all 155 programs airing in 1998 and 1999.

In the overall analysis, the combination of inheritance, structural variables(carriage program rating, number of promos aired), and five appeal and presen-tation variables accounted for 78% of the variance in program ratings (adj.R2 � .781). The content variables—fostering character identification, surprisehumor, (not) seeming new, suspenseful, and promo length—produced changesin R2 totaling .062, a relatively small but still significant contribution to the totaltarget program ratings in a business where tenths of a ratings point are treated asimportant because they are financially valuable. This result supports the firsthypothesis—that content matters significantly, in addition to structure, in com-edy promotion.

Program Popularity

The second hypothesis posited a greater impact of content-related promotionalvariables for mid-rated comedies compared to high-rated or low-rated comedies.Table 2 shows the results of a stepwise regression analysis for the two middlequartiles of promoted programs, containing 85 mid-rated programs and 837promos. Table 3 reports the results of a similar analysis of the 70 programs and710 promos in the high- and low-rated quartiles. The overall difference betweenthe two groups was substantial, as 7% more variance was explained for themid-rated programs (adj. R2 � .840) than for the high- and low-rated shows (adj.R2 � .762). Moreover, more content variables, including the elements of humorand presentation, were significant factors in the mid-quartile ratings than in theextreme quartiles. However, contrary to Hypothesis 2, the content variablesalone accounted for more of the ratings variance for the high- and low-ratedshows (9% came from relating to characters, suspenseful, and seems new) whilepredicting less for the mid-quartile programs (just 6% came from star appeal,hip, cute humor, and length). Thus, Hypothesis 2 was not supported.

Looking at the content variables, however, reveals some interesting differencesbetween mid-rated programs and (1) those much more or much less successfuland (2) as compared with the overall analysis reported in Table 1. Fewer separatecontent variables were significant predictors for the high- and low-rated shows,but one appears to be particularly important. Fostering identification withcharacters explains more than 4% of the variance for those programs, nearlytwice as much as any other content variable in any of the regressions. The

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TABLE 1

Hierarchical (Stepwise) Regression Analysis of Appeal, Presentation,and Humor Variables for All Programs

Variable B SE B B �R2 Adj. R2

Step 1 .661 .658Lead-in rating .948 .055 .813*

Step 2 .044 .700Lead-in rating .810 .059 .694*Carriage program rating .257 .054 .240*

Step 3 .019 .717Lead-in rating .799 .057 .685*Carriage program rating .250 .053 .233*Relate to characters .399 .125 .137**

Step 4 .014 .729Lead-in rating .761 .058 .652*Carriage program rating .237 .052 .221*Relate to characters .358 .123 .123**n of promos 6.788E-02 .024 .124**

Step 5 .014 .742Lead-in rating .745 .057 .639*Carriage program rating .238 .051 .222*Relate to characters .332 .121 .114**n of promos 7.344E-02 .024 .134**Surprise humor 1.061 .370 .119**

Step 6 .009 .749Lead-in rating .746 .056 .640*Carriage program rating .219 .051 .204*Relate to characters .377 .121 .130**n of promos 6.864E-02 .024 .126**Surprise humor 1.074 .365 .120**Program seems new � .282 .123 � .096***

Step 7 .011 .759Lead-in rating .743 .055 .638*Carriage program rating .210 .050 .196*Relate to characters .280 .124 .096***n of promos 7.474E-02 .023 .137**Surprise humor .913 .362 .102***Program seems new � .343 .122 � .117**Program seems suspenseful .326 .121 .116**

Step 8 .009 .768Lead-in rating .758 .054 .650*Carriage program rating .172 .051 .160*Relate to characters .266 .122 .091***n of promos 8.328E-02 .023 .152*Surprise humor .822 .358 .092***Program seems new � .382 .121 � .130**Program seems suspenseful .335 .119 .119**Promo length .550 .220 .104***

Note: n of programs � 155; n of promos � 1,547; *p � .001; **p � .01; ***p � .05

negative coefficients for both appeals to hipness and cute humor suggest thatcontemporary audiences (at least younger ones, the avowed target audiences formost comedies) may respond best to spots with some edge but not to overtmessages such as “look how cool this show is.”

The results also provide some support for Hypothesis 3, which predicted thatappeals would matter more than presentation or type of humor. Based on eitherthe number of times appeals appear in the analyses, or on total predictive power,certain appeals (especially fostering character identification) explain more vari-

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TABLE 2

Hierarchical (Stepwise) Regression Analysis of Appeal, Presentation,and Humor Variables for Mid-Rated Programs



Step 2 .130 .765Lead-in rating .623 .070 .564*Carriage program rating .257 .038 .431*

Step 3 .025 .788Lead-in rating .544 .071 .493*Carriage program rating .255 .036 .428*n of promos 7.44E-02 .024 .174**

Step 4 .016 .802Lead-in rating .561 .069 .509*Carriage program rating .228 .036 .383*n of promos 6.809E-02 .023 .159**Star appeal .212 .082 .132***

Step 5 .017 .817Lead-in rating .531 .067 .481*Carriage program rating .204 .036 .342*n of promos 6.3551E-02 .022 .149**Star appeal .288 .084 .179*Program seems hip � .331 .120 � .146**

Step 6 .014 .830Lead-in rating .539 .065 .488*Carriage program rating .179 .036 .300*n of promos 5.871E-02 .021 .137**Star appeal .379 .088 .236*Program seems hip � .392 .118 � .173*Cute humor � .776 .292 � .131**

Step 7 .011 .840Lead-in rating .562 .063 .510*Carriage program rating .152 .036 .256*n of promos 6.107E-02 .021 .143*Star appeal .366 .085 .288*Program seems hip � .387 .114 � .171*Cute humor � .719 .284 � .122***Length .434 .180 .113***

Note: n of programs � 85; n of promos � 837; *p � .001; **p � .01; ***p � .05

ance than the type of humor employed or the presentation (where only lengthmay be significant). Nonetheless, humor and presentation did contributesignificantly to the variance in promos for mid-rated program ratings but not tothe promos for highly popular or unpopular programs.

Impact of Familiarity

The fourth hypothesis predicted that appeals would impact the ratings forfamiliar comedies more than for unfamiliar comedies. Using familiarity as abinary (familiar/unfamiliar) sorting variable, the results reported in Table 4 andTable 5 indicate that although all of the variables accounted for nearly 20% morevariance in the ratings for familiar (adj. R2 � .927) than for unfamiliar (adj.R2 � .759) programs, the contributions made by appeals were very similar.However, the effective appeals were very different for the two categories ofprograms: Structural variables and appeals contributed most significantly to the

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TABLE 3

Hierarchical (Stepwise) Regression Analysis of Appeal, Presentation,and Humor Variables for High-and Low-Rated Programs



Step 2 .046 .690Lead-in rating .911 .082 .761*Relate to characters .760 .239 .219*

Step 3 .027 .713Lead-in rating .767 .097 .641*Relate to characters .680 .232 .196**Carriage program rating .394 .156 .207***

Step 4 .017 .727Lead-in rating .746 .096 .623*Relate to characters .610 .229 .175**Carriage program rating .426 .153 .224**Program seems suspenseful .422 .203 .133***

Step 5 .026 .750Lead-in rating .735 .091 .614*Relate to characters .628 .218 .181**Carriage program rating .420 .146 .221**Program seems suspenseful .554 .200 .175**Program seems new � .615 .229 .167**

Step 6 .014 .762Lead-in rating .707 .090 .591*Relate to characters .544 .218 .157***Carriage program rating .394 .143 .207**Program seems suspenseful .601 .197 .190**Program seems new � .604 .223 � .164**n of promos 7.583E-02 .038 .127***

Note: n of programs � 70; n of promos � 710; *p � .001; **p � .01; ***p � .05

ratings for familiar programs. Presentation (length) was a factor only for unfam-iliar shows, whereas type of humor (surprise) was significant only for familiarshow ratings.

Table 4 shows that for the 45 familiar programs promoted in 492 promos, twostructural variables (inheritance and carriage program rating) accounted for

TABLE 4

Summaries of Hierarchical (Stepwise) Regression Analysis of Appeal,Presentation, and Humor Variables for Familiar Programs

Variable B SE B B

Lead-in rating .729 .053 .668*Carriage program rating .102 .025 .203*Network popularity .329 .075 .194*Surprise humor 1.050 .224 .195*Program seems hip � .405 .109 � .174*Star appeal .189 .075 .114***

�R2 � .773 for Step 1; .079 for Step 2; .024 for Step 3; .031 for Step 4; .021for Step 5; and .011 for Step 6.Adjusted R2 � .767 for Step 1; .844 for Step 2; .866 for Step 3; .897 for Step4; .917 for Step 5; and .927 for Step 6.Note: n of programs � 45; n of promos � 492; *p � .001; **p � .01;***p � .05

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TABLE 5

Summaries of Hierarchical (Stepwise) Regression Analysis of Appeal,Presentation, and Humor Variables for Unfamiliar Programs

Variable B SE B B

Lead-in rating .720 .071 .610*Carriage program rating .289 .087 .204*Identify with characters .376 .159 .120***Program seems suspenseful .461 .154 .152**Program seems new � .432 .160 � .134**N of promos 7.943E-02 .030 .137**Length of promo .625 .280 .108***

�R2 � .654 for Step 1; .043 for Step 2; .026 for Step 3; .012 for Step 4; .016for Step 5; .012 for Step 6; and .011 for Step 7.Adjusted R2 � .651 for Step 1; .692 for Step 2; .716 for Step 3; .725 for Step4; .739 for Step 5; .749 for Step 6; and .759 for Step 7.Note: n of programs � 110; n of promos � 1,055; *p � .001; **p � .01;***p � .05

approximately 84% of the ratings variance. Three appeals (network popularity,seeming hip, and star power) added an additional 5%. The remainder (3%) wasattributed to the use of surprise humor.

In contrast, Table 5 shows that the conventional structural variables accountfor only 70% of the ratings variance for the 110 unfamiliar programs, andpresentation (length) adds an additional 1%. The significant appeals for unfam-iliar shows were identifying with characters, suspense, and (negatively) seemingnew, which collectively added 5%. Thus, Hypothesis 4 was not supportedbecause the size of variance accounted for by the appeals was identical for bothfamiliar and unfamiliar program ratings. The differences lay in the contributionsof humor and presentation. Nonetheless, appeals and humor together accountedfor 8% for familiar programs, whereas appeals and presentation accounted forjust 6% for unfamiliar programs.

Discussion

First, and most important, these findings strongly support the presumptionthat promos have a significant and measurable impact on program ratings.Second, the content—not just the structure—of promos was demonstrated toimpact program ratings in this study. Third, affective appeals contributed sub-stantially more to promotional impact than the forms of humor or execution inthe promos. Fourth, the impact of promo content was greater for familiar thanunfamiliar programs. Fifth, the impact of humor and presentation were greaterfor promos promoting mid-rated than for top- or bottom-rated comedies. At thesame time, the results also confirm the expected powerful impact of inheritedviewing on program ratings and the influential role of scheduling of promotionalmessages to reach a wide audience. The consistency of such findings with thelong tradition of programming research adds credence to these results.

Particularly new in this study was the identification of some of the specificappeals that made a difference. For television comedies, the key content ele-ments appear to be: having characters that can be identified with; havingdramatic suspense and realism; using big stars; avoiding self-identified trendi-

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ness and newness in appeals; and avoiding cute humor. While these results maynot generalize to other program genres, and some key appeals may have beenomitted, these findings provide the first examination of promotional contentoutside the boundaries of sexual and violent content. The importance of foster-ing identification with characters in hit programs will be no surprise to programproducers and writers, but what emerges here is its importance to successfulpromotion. The ability of audiences to relate to characters, and to feel someelement of suspense related to the program episode, appear to be significantfactors in the effectiveness of promotion for both high-rated and low-ratedprograms. Successful promotion of mid-rated shows, in contrast, seems to bedriven to a greater degree by structural factors, by appealing to the star power ofthe actors, and by allotting sufficient time to the spots (or to the individualprograms in a multiple spot) to get the promotional message across (promolength). Further, these findings offer preliminary evidence that the content withwhich programs are promoted affects viewing decisions. This significant rela-tionship should give experimental researchers the confidence to test suchspecific mechanisms as excitation transfer and priming that could be behind therelationship.

On the theoretical level, these findings add strength to the presumption thateven the very modest interest stirred by on-air promotion measurably primesbehavior related to program ratings. This occurs despite the low level ofarousal—if that is the appropriate word for such a mundane effect—created bypromos. It occurs despite the regular presence of intervening activities includingother programming and the extended time lapse between the airing of promosand the airing of promoted programs. For familiar shows in particular, theaffective and humor components are effective (and more important), probablybecause they aid viewers’ recall of positive experiences and build anticipationthrough their desire for subsequent similar experiences. To be maximally effec-tive, then, promos should contain cognitive and emotional elements that triggerviewer recall of previous experiences with a program and emphasize the success-ful nature of the show. As examples, one might point to the very successful“must-see-TV” theme and the widespread use of variants of “Last Sunday, 30million Americans saw. . . .”

Limitations and Future Research

As previously mentioned, executional (presentational) variables are commonlyused in laboratory and marketing studies. Their infrequent appearance in theseanalyses may be measurement artifacts or may represent real differences betweenadvertising and promotional messages. The variable of promo length, an aspectof pacing, becomes of particular interest because it was the only presentationalvariable to show up in the overall and mid-quartile regression analyses as asignificant factor in promos’ impact on program ratings.

Another qualification is that the regression method employed lacks the rigor oflaboratory experimentation for deducing causal explanations, while simul-taneously being too demanding for situations where the variance is small (as inthe smaller networks’ ratings). Nonetheless, while more extended tests ofspecific findings are highly desirable, along with using evaluators (coders)reflecting a wider range of demographics, these results have remarkable simi-

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larity to the findings of some previous studies of structural variables in pro-motion (Eastman & Newton, 1998a, 1998b). Thus, despite limitations, thefindings confirm some general outlines that should be expected to continue tohold up in subsequent research into promotion.

In addition, given that the affective appeals and content pacing were rated bycollege students and were necessarily somewhat subjective (or at least, timebound), generalization from these findings to a wider range of age groups is notwarranted. While the specific appeals probably differ for demographic groupsother than young adults, these finding do provide the first steps toward isolatingthe powerful content elements in promos. Moreover, college students are part ofthe demographic groups that programmers want to attract as viewers (adults18–34 and 18–49) and are an ideal target for building loyalty (bonding) tospecific programs, one of the other key goals of promotion.

While the collective contribution of the content variables to the varianceaccounted for in this study remains small, it must be kept in mind that theend-of-season differences in ratings from the number one to number two networkmay be as small as one-tenth of a ratings point. This was indeed the case in May1999, the end of that year’s 36-week season. CBS was ahead by one-tenth of aratings point (9.0 to 8.9, season-to-date) and was equal in share points (at 15), asituation that was unchanged for much of the year. ABC, the third-rankednetwork, was usually less than one ratings point behind throughout that year.Thus, the amount of variance available to be found is small but vital to theindustry because it represents millions of dollars in advertising revenue, andimportant to scholars in demonstrating the applicability of priming and saliencetheories.

Future applied research needs to assess the kinds of content factors salient toappeals in promos for other genres of programs, as well as the ideal andmaximum distance of promos from various genres of programs. It can bereasonably expected, for example, that effects would occur over greater lengthsof time for specials and movies but only over relatively shorter lengths of timefor episodic promos for series. Future theoretical research in laboratory experi-ments needs to pinpoint the exact mechanism that accounts for the secondaryexcitation transfer effect or priming effect.

Practical Applications

The importance of on-air promotion when assessing the sources of prime-timeratings lends practical value to this study. The findings have implications forboth television programming executives and scholars interested in teaching andresearching program promotion because they provide empirical evidence toguide the design of effective comedy promos. First, the results illustrate howsimilar program promotion is to product advertising. As in advertising, the typeof appeal used matters a great deal. Another similarity is that, as in productadvertising, brand (or program) familiarity and popularity impact the roles ofappeals in determining promotion’s effectiveness. The pattern of results in thisstudy should give television executives added confidence in drawing on theknowledge gained from advertising research when designing effective strategiesfor program promotion. Second, the study shows the need to distinguish pro-grams by their ranking in the ratings when creating promos and probably to

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focus on promoting the mid-rated programs. The findings imply that televisionexecutives may want to allocate proportionally more air time to promos formid-rated than for hit shows.

On the content side, in addition to identification, suspense and realism appearto be robust elements in many sitcom promos. Suspense is created by showingonly a tiny portion of a sequence, while a voice-over implies what might happenin the promoted episode but leaves the outcome problematic. Realism may berelated to the ability to identify with characters or situations, with the absenceof trendiness, and with some kinds of humor. In combination, these seem amongthe most important factors in creating effective sitcom promos. Also, theseresults confirm the important of promoting identification with characters whileavoiding touting a program’s coolness or its newness. Further, when targetingyoung adults, promos for comedies probably should not incorporate cute humor.It seems likely that sarcasm and surprise humor are more effective in makingcomedy promos appealing to young adults.

Moreover, because situation comedies occupy about one-quarter of the weeklyprime-time schedule each year (27% in 1998–99),6 these results probablyreflect the dominant patterns within prime-time promotion. Analysis ofpromos for dramas, movies, sports, and news programs may necessitate theintroduction of appeals unimportant to comedy programming, but the generalfactors identifying salient promo content have been suggested by this andprevious studies.

Finally, although not reported in tables here because of length, analysesshowed that the individual networks utilized significantly different promotionalpractices, although those of the Big Three networks seemed to be more like eachother than like those of Fox and the two newer networks. Nonetheless, the BigThree differed substantially between themselves in some promotional practices,in ways that were not necessarily related to the popularity of their programs.Analyses by network suggested two possibilities: that the kinds of appealsincluded in this study better describe the types of promotion employed by ABC,CBS, and NBC, and less accurately describe promos on Fox, UPN, and WB, or,more likely, given their shorter evening schedules, that the amount of variancewithin the ratings of the latter three networks is too small to examine via suchrigorous tests as hierarchical multiple regression.

Conclusion

Although these results are derived from a sample that represents a relativelynarrow picture of current industry practice, subsequent studies should enablescholars and practitioners to track changes in the industry over time. Moreover,the model for analysis used in this study may help other scholars interested inprogramming and promotion compare the differences between promos for situ-ation comedies and other genres of prime time, daytime, late night, or weekendprogramming. This demonstration of the impact of content as well as structurebrings home the aggregate importance of on-air promotion in assessing thesources of prime-time program ratings.

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Endnotes

1. Although special events such as the Olympics are promoted in advance on television, thispromotion tends to be aimed primarily at building network prestige and credibility rather thanaudience size.

2. The findings for inheritance generally do not apply to live sports events, which are largelyviewed by appointment on the broadcast networks (Eastman, 2000). In most studies of prime time,inherited viewing accounts for about 50% of the variance in the next program’s ratings, meaning—ina practical sense—that about half the second program’s audience also watched the precedingprogram. However, the amount of inherited viewing has been shown to vary considerably by daypart,by program genre, and by the popularity of the program (Webster & Phalen, 1997).

3. The prime-time hours were 8–11 Monday to Saturday, 7–11 Sunday for ABC, CBS, and NBC;8–10 for six nights and 7–10 on Sundays for Fox; 8–10 for three weeknights in 1998 and fourweeknights in 1999 for UPN; and 8–10 for two weeknights in 1998 and four weeknights in 1999, plus7–10 on Sundays for both years, for WB. Four hours in 1998 were lost due to technical error. Thenumber of hours programmed each week increased by six hours on UPN and WB from May 1998 toMay 1999, bringing the total weekly hours of prime time from 96 to 102.

4. Because sitcoms are often used as the lead-off programs at 8 p.m. on about half of networkevenings, elimination of all those programs would have substantially reduced the database, and thefocus of this research was not the exact size of the lead-in effect.

5. If the length categories are treated as interval level data, the differences between the networksare not statistically meaningful (eta2 � .167, very low), but nonetheless, a few characteristics standout. While 10-second spots (or 6–10 second chunks of multiple spots) have become the industrynorm, and were the biggest category for every network, the younger networks were even more likelyto use them than the Big Three.

6. See Adams & Eastman (2002). The percentage of sitcoms in the 1998–99 schedule resulted froma program by program count of the Nielsen prime-time ratings for the 32 weeks of that year’s season,as published in Broadcasting & Cable.

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Received December 10, 2001Final revision received May 24, 2002Accepted August 1, 2002

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