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writing multi-part question and need an explanation and answer to help me learn.
After reading the two articles (will be provided) answer the following questions only from
the readings without any references talk in a persons point of view it is a discussion. Short
Answers only, a paragraph or less.
How do new communication technologies affect television industries in Arab countries?
How are they changing audience habits and viewership?
How are affecting local cultures and societies?
Requirements: paragraph per question | .doc file
International Journal of Communication 13(2019), 653Ð673 1932Ð8036/20190005
Copyright © 2019 (Tamara Kharroub and Andrew J. Weaver). Licensed under the Creative
Commons Attribution Non-commercial No Derivatives (by-nc-nd). Available at
http://ijoc.org. Selective Exposure and Perceived Identification With Characters in
Transnational Arabic Television TAMARA KHARROUB Independent Researcher ANDREW
J. WEAVER Indiana University Bloomington, USA Given the transnational nature of the
Arabic satellite television industry and the cultural differences among Arab regions, this
experiment examined the role of social identity in Arab viewersÕ media choices and
perceived identification with characters. Overall, Arab viewers identified more with in-
group characters (gender and cultural region) and were more interested in watching
programs that feature in-group lead characters. The perceived intended audience of the
television program mediated the relationship between cultural identity on one hand and
perceived identification with characters and selective exposure on the other. The findings
show that social identity plays an important role in Arab viewersÕ media consumption, and
are discussed in light of social identity theory. Keywords: social identity, transnational
media, identification with characters, selective exposure, Arab television The Arabic
version of the TV reality show Big Brother (Al-RaÕis) received heavy criticisms and was
cancelled in 2004 only days after it started airing on Middle East Broadcasting
CorporationÕs satellite television channel (Kraidy, 2010). Meanwhile, the Arabic adaptation
of the Dutch music contest reality show Star Academy persisted to air on Lebanese
Broadcasting CorporationÕs satellite television channel for several years with the most
recent (11th) season airing its final episode in 2016. Both shows and other reality programs
on pan-Arab television were heavily criticized by ultraconservative Saudi clerics for their
gender dynamics, particularly for showing unmarried male and female contestants sharing
living spaces. Even though both Star Academy and Al-RaÕis generated controversies in
Saudi Arabia, Star Academy was based in Lebanon and hosted more participants from the
Levant Arab states, and Al-RaÕis was filmed in the Saudi neighbor Bahrain and hosted more
participants including women from the Arabian Gulf. This difference in the cultural settings
of the two programs may explain the shutdown of Al-RaÕis compared with that of Star
Academy. Tamara Kharroub: tamara.kh@gmail.com Andrew J.
Weaver: weaveraj@indiana.edu Date submitted: 2017‒01‒28
654 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) Whereas entertainment programming in the Arab world is usually produced in
the more liberal Lebanon or Egypt, sponsors of Al-RaÕis wanted to attract the wealthy
Saudi viewers by setting up the reality show in a cultural setting close to that of Saudi
Arabia (Kraidy, 2010). Because filming such programs in the Saudi kingdom itself is not
permitted, Bahrain was chosen. This decision was based on the belief that Saudi viewers
would be more likely to watch and identify with a show filmed in a country geographically
close and culturally similar to Saudi Arabia and that featured participants from the Arabian
Gulf similar to Saudi viewers. For the same reason, Saudi clerics believed that the cultural
similarity between the Saudi viewers and the show would lead to more favorable responses
toward the media personalities and thus greater influence by their behaviors and actions.
Although a complex combination of political, economic, and religious issues contributed to
the Al-RaÕis controversy, the role of social and cultural identity in this pan-Arab context
cannot be ignored. The cultural identity of Al-RaÕis was too close to home for the Saudi
clerics, and most likely led to its shutdown. In this particular case, BahrainÕs status as a
vassal state made it easier for Saudi Arabia to exert influence and pressure to close
production. As the above example demonstrates, the cultural proximity between the
participants in Al-RaÕis and the Saudi viewers triggered a more pronounced reaction to this
particular show than other television programs that feature non-Gulf Arab participants.
Although this example dates back to 2004, it is the most prominent instance revealing the
role of regional Arab cultural identity in the consumption of transnational Arab media
content. More recent examples point to similar patterns of identity-based phenomena. For
example, the popularity of Turkish television drama serials (dubbed into Arabic in Syrian
dialect) over the last decade has also raised controversy. Whereas American television
imports are subtitled into Arabic and the imported Mexican telenovelas are dubbed into
literary Arabic, thus maintaining a social distance between the characters and the viewers,
Turkish series are dubbed into colloquial Arabic and the charactersÕ names are Arabized
(Buccianti, 2010). This cultural proximity has generated public concern regarding the
potential effects of Turkish dramas on the Arab viewers. It is believed that such Arabized
context and the sharing of a religious identity (Turkish characters being Muslim) might
increase the degree to which viewers connect and engage with the characters. In the
context of the Arabic-language transnational satellite television industry, social identity
theory (Tajfel, 1978) suggests that a shared social identity between the viewers and the
media personalities (characters or participants) would lead to an increased desire to view
the programs and greater identification with media personalities. The present study
examined the role of social identity (cultural and gender) in Arab viewersÕ selective
exposure to in-group and out-group media content and their perceived identification with
in-group and out-group characters in the transnational Arab media context. The
Transnational Arab Television Industry Television development in the Arab world went
through several phases before evolving into the current transnational industry. Ayish
(2011) identifies three primary phases of development in the Arab television industry; the
formative phase between the 1950s and 1970s that ultimately led to government control of
the industry, the national expansion phase up to the 1990s of growth in production and
coverage, and the global phase following globalization trends during the 1990s including
technological
International Journal of Communication 13(2019) Selective Exposure and Identification
655 advancements, literacy, and privatization, which led to relaxed government control and
the launching of commercial operations. With the global trends and the advent of satellite
technology in the early 1990s, the Arabic television market achieved a transnational reach
beyond the limited national terrestrial radiuses, broke away from political control, and
evolved to include more diverse content. Globalization allowed marginalized and
oppositional groups to join the market, thus providing ideological variety as well as choice
and opportunity in Arabic television programming (Tawil-Souri, 2008). However, while
political elites loosened their grip on the media market, the economic elites took control of
the industry. With the commercialization aspect of globalization came the phenomenon of
what some call the ÒSaudi media empireÓ (Sakr, 2006). The structure of the new
transnational market gave advantage to the business elites in the region and the rich Gulf
states to launch media conglomerates. The dominant financial position of Gulf countries in
this industry gave them a majority of the market share and a greater sphere of influence in
the region. The rapidly growing Arab satellite television industry had reached 975 fully
functional free-to-air channels by the end of 2017 (Arab Advisors Group, 2017). Available in
all 22 Arab countries and serving a population of more than 406 million with at least 80%
television penetration rates (Kraidy & Khalil, 2009), satellite television remains the most
popular mass communication medium across the Arab world. Although more than 406
million inhabitants of the Arab world share a common language, they vary greatly in their
cultural tastes and sensibilities and their social, cultural, political, and legal systems
(Kalliny, Dagher, Minor, & De Los Santos, 2008). Some homogeneity among the Arab
countries does exist as a result of historical circumstances, but numerous differences among
the Arab nations exist especially with regard to wealth and economic standards, dialects of
Arabic language, cultural traditions, religion and religiosity, social conservativeness, and
gender norms (Kalliny et al., 2008; Kraidy & Khalil, 2009). For example, Saudi Arabia
operates under strict Islamic law, does not hold elections, and places severe restrictions on
womenÕs rights and freedoms. On the other hand, Arab countries in the Levant (e.g.,
Lebanon) are considered more liberal and have relatively more gender equality. Kalliny
and colleagues (2008) capture this diversity by placing Arab countries on a
liberalÐconservative continuum based on cultural differences. In general, they categorize
Arab countries into three cultural groups based on geographical locations: Asian non-Gulf
countries (Levant), Arabian Gulf countries, and African countries (Kalliny et al., 2008). They
propose that countries in the Levant region are on the liberal end, whereas Arab Gulf states
are the most conservative, and African Arab countries lie in the middle of the continuum.
This categorization demonstrates the existence of three distinct cultural regions within the
Arab world. Along similar lines, the three categories used by other media scholars to divide
the region are the Arab Maghreb, which includes the western Arab countries in North
Africa; the Arab Gulf; and the Arab Mashreq, which consists of the Arab Middle East nations
excluding the Gulf (e.g., Mellor, 2011). Most classifications place Egypt with the African Arab
countries in the middle of the liberalÐconservative spectrum.
656 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) In the transnational Arab television market with such high levels of diversity,
questions emerge regarding viewersÕ preferences and media consumption choices. In
terms of content diversity, media globalization has resulted in a paradox in Arab media. On
one hand, commercial and consumerist trends produced ÒWesternizedÓ Arabic programing
with images of seminude pop stars. On the other hand, there arose an ethnoreligious
populist reaction to globalization as a way to counter what is perceived as imperialist
influence, resulting in Islamic TV channels and religious and conservative content (Tawil-
Souri, 2008). To take womenÕs representation as an example, a content analysis of Arabic
drama serials (Kharroub & Weaver, 2014) revealed that Arab Gulf programs had more
female characters in female stereotypical roles and activities than programs from the more
liberal Levant countries. In this regard, the financial power of conservative Arab Gulf states
may translate into cultural influence through transnational television networks, and is
therefore worthy of investigation. AudienceÕs media choices and perceived identification
with characters in television programs are especially important as they have been shown to
play a role in the effects of media content on the viewersÕ attitudes and beliefs (e.g.,
Kaufman & Libby, 2012). In the pan-Arab television industry, media programs are produced
in several Arab countries and are consumed by viewers throughout the Arab world. The
transnational nature of this media market raises questions about the effects of media
content produced in one region and reflecting its cultural and social norms on the viewersÕ
attitudes and beliefs in other regions. Given the important role of identity in the processes
of identification and effects and the differences among the Arab countries, the present study
used the social identity framework to examine whether Arab viewers are interested in
watching television programs produced in different Arab cultural regions and whether they
identify with characters from Arab cultural regions different from their own. With much
attention given to media ownership and content, little is known about the viewersÕ media
choices in the Arab transnational television market. Surveys show a tendency by Arab
viewers to favor programs that feature their own country. Tunisian, Lebanese, Moroccan,
and Egyptian viewers prefer local programs produced in their own countries (Arab
Advisors Group, 2005, 2006, 2008, 2010b). In contrast, the majority of Jordanian TV
viewers prefer watching Syrian and Egyptian drama series than Jordanian dramas (Arab
Advisors Group, 2010a). These findings show some differences in media preferences among
viewers in different Arab countries, but they also suggest that local programming is still
preferred. However, not much is known about the processes that facilitate these
phenomena. Little work is available on audience-centered approaches to the study of Arab
media, and no empirical studies have examined the role of identity in media choices and
identification with characters among Arab TV audiences. The present study examined the
role of Arab viewersÕ cultural and gender identities in their media choices and their
perceived identification with media characters in the transnational Arab television
environment. Selective Exposure and Social Identity People are known to favor programs
that feature members of their social groups. For example, studies have shown that viewers
prefer programs produced in their home country (Waisbord, 2004) and programs that
feature characters that share their gender (Trepte, 2004) and race (Weaver, 2011b). Social
International Journal of Communication 13(2019) Selective Exposure and Identification
657 identity theory and self-categorization theory have been used to explain how media
choices can be determined by social group membership (Trepte, 2006). Social identity
theory (Tajfel, 1978) posits that people categorize themselves as belonging to different
social groups such that one part of the self is defined by belonging to one social group. Henri
Tajfel (1978) defines social identity as Òthat part of an individualÕs self-concept which
derives from his knowledge of his membership of a group together with the value and
emotional significance attached to that membershipÓ (p. 63). Interest in entertainment
content that features in-group members can be explained by the desire to learn about oneÕs
social group and define group norms (Hogg, 2010). As such, based on social identity theory,
we expected Arab viewers to show more interest in programs that feature characters that
share their social groups, particularly their gender and cultural background. In terms of
cultural background, although culture is a difficult term to delineate, it is commonly defined
as a set of interrelated qualities of observable artifacts, values, and underlying assumptions
(such as customs, morals, knowledge, etc.) that are shared by and specific to one social
group (e.g., Spencer-Oatey, 2012). Several cultural groups exist in the Arab world. For the
purpose of the present study and given the structure and financing of the transnational
Arab television industry, the regional cultural groups within the Arab world are most
relevant here. Based on the three regional cultural categories in the Arab world (Levant,
North Africa, and Gulf), we aimed to understand Arab viewersÕ media choices and
perceived identification with characters. In this context, StraubhaarÕs (2003) cultural
proximity concept can best explain media consumption choices. According to Straubhaar,
consumers and media audiences prefer products from ÒoneÕs own culture or the most
similar possible cultureÓ (p. 85). Selection and enjoyment of media content increase when
it exists in the same Òcultural linguisticÓ sphere as the viewers (Straubhaar, 2003). In
addition to language, other related factors such as dress, lifestyle, gestures, and traditions
have been discussed as determinants of cultural proximity (La Pastina & Straubhaar, 2005).
In the transnational Arab context, regional cultural categories (North Africa, Levant, and
Gulf) have been shown to exhibit distinct cultural cues that are visible in the media, such as
dialect, dress, traditions, and gestures. The media choices of Arab viewers in relation to the
three cultural groups are herein examined. Looking at quantitative studies of media
preference for programs that feature characters sharing the same cultural social group as
the viewers (in-group members), the findings are inconclusive. As shown earlier, studies of
Arab audiences show some preference for local programming along national lines, but
differences among Arab countries exist (Arab Advisors Group, 2005, 2006, 2008, 2010a,
2010b). Looking at other populations and national social groups, Trepte (2004) found no
difference in U.S. viewersÕ preference for German or American programs. Through two
international quasi-experimental studies conducted in the United States and Germany and
in Great Britain and Germany, Trepte and KrŠmer (2007) found no evidence for preference
of national media products, even when the participantsÕ national identity was made salient.
Trepte and KrŠmer suggest that, unlike sports, the salience of national categories in
entertainment programs is not high.
658 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) However, regional cultural identity in the Arab world is salient in entertainment
programs, especially through the observable cultural cues that distinguish among the three
Arab regional regions. Therefore, the present study examined Arab viewersÕ media choices
in relation to television programs produced in different Arab cultural regions. The following
research question guided this inquiry: RQ1: Do Arab viewers prefer TV programs
produced in their own cultural region over programs produced in other Arab cultural
regions? The second component of social identity examined in the present study was
gender. Studies have consistently found that females prefer female characters, whereas
males prefer male characters. For example, Trepte (2004) manipulated the gender of the
protagonist in a description of entertainment programs, and found that participants in both
Germany and the United States preferred television series that featured same-sex
protagonists. Similarly, the present study hypothesized that Arab viewers would prefer to
watch television programs of same-sex lead characters: H1a: Arab female viewers will
express more interest in watching programs that feature female lead characters than male
lead characters. H1b: Arab male viewers will express more interest in watching programs
that feature male lead characters than female lead characters. Perceived Identification With
Characters and Social Identity The second process influenced by social identity and
examined in the present study was identification with characters. The process of
identification is understood differently depending on the genre of the medium, such that
several concepts of viewersÕ reactions to media have been discussed as identification
including liking, similarity, empathy, wishful identification, fandom, and parasocial
interactions (Cohen, 2001; Hoffner & Buchanan, 2005; Hoffner & Cantor, 1991; Liebes &
Katz, 1990). Identification with characters in fictional narrative genres has been shown to
be an important element of narrative persuasion (De Graaf, Hoeken, Sanders, & Beentjes,
2011) and is therefore considered herein. As such, the present study examined Arab
viewersÕ identification with characters in Arabic fictional drama serials (Musalsalat).
Identification with characters is defined as a connection between an individual and another
person, Òsuch that the individual adopts traits, attitudes, or behaviors of the other person,
or incorporates the otherÕs characteristics into his or her sense of selfÓ (Hoffner &
Buchanan, 2005, p. 326). In his seminal paper, Cohen (2001) distinguishes between
identification and other responses to media content based on the internalization of media
messages. He defines identification with fictional media characters in narrative texts as an
Òimaginative processÓ (p. 253) that occurs in response to exposure to media characters; it
is a process of imagining oneself inside a textual reality where viewers feel with the
character rather than about the character.
International Journal of Communication 13(2019) Selective Exposure and Identification
659 In addition to the temporary process of identification described by Cohen (2001) and
others, Hoffner and Buchanan (2005) discuss the different yet equally important notion of
Òwishful identificationÓ: the desire to be like the characters in media texts. According to
Hoffner and Buchanan, wishful identification is similar to the durable process of Òlong-term
identificationÓ proposed by Rosengren, Windahl, Hakansson, and Johnsson-Smaragdi
(1976), which extends beyond the viewing situation. In the present study, CohenÕs
conceptualization of identification and the long-term process of wishful identification are
both relevant and were therefore investigated. Identification with media characters is a
central process in media consumption experiences, as it is believed to influence audience
responses to media texts (Hoffner & Buchanan, 2005) and the role of media in the
socialization process (Bandura, 1986). One of the factors that motivates viewers to identify
with certain media characters and emulate their behavior is perceived similarity (Bandura,
1986). Social cognitive theory predicts that people are more likely to pay attention to and
model behaviors performed by similar others (Bandura, 2001). Hoffner and Cantor (1991)
argue Òsome degree of similarity to media characters seems to promote a desire to be like
them, possibly because certain similarities signal that it is both possible and appropriate for
the viewer to become like the character in additional waysÓ (p. 87). Studies have found that
viewers feel similar to characters who are like themselves in terms of demographic
characteristics such as gender (e.g., Reeves & Miller, 1978) and race (e.g., Appiah, 2001).
This similarity based on social group membership leads to higher identification with the
media characters. For example, Kaufman and Libby (2012) found that identification with a
character (what they call Òexperience-takingÓ) is higher when the participant and the
character share a relevant group membership. Identification, in turn, increases the effects of
media on the viewers (e.g., Liebes & Katz, 1990). For example, Kaufman and Libby (2012)
found that 65% of participants in the character in-group condition reported intentions to
behave similarly to the character (e.g., going to vote), compared with only 29% of
participants in the character out-group condition. When considering gender as a social
identity, research on gender-based identification with media characters shows that viewers
identify more with same-sex characters than opposite-sex characters (Hoffner, 1996;
Reeves & Miller, 1978). In the present study, we hypothesized that Arab viewers would
identify more with programs that feature same-sex lead characters (i.e., when the viewer
and the character share the same sex group membership, or gender in-group): H2a: Arab
female viewers will identify more with female lead characters than with male lead
characters. H2b: Arab male viewers will identify more with male lead characters than with
female lead characters. Similarly, in terms of regional cultural groups, we predicted that
identification with media characters would be higher in programs from the same Arab
cultural region as the viewers (i.e., cultural in-group): H3: Arab viewers will identity more
with cultural in-group characters (from their cultural region) than with cultural out-group
characters (from other cultural regions).
660 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) Perceived Relevance and Intended Audience Several researchers have been
trying to understand the processes by which social identity affects media choices and the
level of connection with media personalities. Two distinct processes have been examined:
the perceived relevance of the plot to the viewersÕ lives and the perception of being part of
the intended audience of the program. The perception of the relevance of the storyline (i.e.,
events and issues) by the viewers has been found to influence interest in the program. For
example, viewers prefer films that have ethnic orientations (i.e., cultural traditions) that are
congruent with the viewersÕ ethnic background (Grier, Brumbaugh, & Thornton, 2006).
Similarly, Cohen and Ribak (2003) showed that women liked Ally McBeal and found it to be
more relevant than men did, because relevance (through realism) allows viewers to engage
with the text and lose themselves in the plot. Weaver (2011a) also found that perceived
relevance of a movie theme was related to the viewersÕ intent to see the movie. In
addition to influencing interest in the program, text relevance is also believed to impact
identification with the characters. For example, the relevance of the themes in the film
Thelma & Louise to women increased female audienceÕs identification with the female
protagonists (Cooper, 1999). The present study explored the role of plot relevance in
mediating the effect of social identity on interest in the show and on perceived identification
with the lead characters. With limited research literature on the topic, the current study
expands evidence of the role of plot relevance in media choices and consumption: RQ2a:
Will the perceived relevance of the plot account for the effect of social identity on media
choices? RQ2b: Will the perceived relevance of the plot account for the effect of social
identity on perceived identification with characters? Another factor that has been found to
influence interest in a media product and identification with characters is the perception of
the intended audience of a program. For example, consumer behavior research has shown
that people who perceive themselves to be part of the intended target audience of an
advertisement are more likely to show interest in watching and more likely to express
positive attitudes toward the ad (Grier & Brumbaugh, 1999). In films, Weaver (2011a)
found that shared social identity between the viewer and the character (race in this case)
influences perceptions of the intended audience of the film, which in turn is strongly related
to interest in the media product and intentions to see the film (r = .68). In fact, the
perception of the intended audience fully mediated the effect of actorÕs race on behavioral
intentions to see the film. Thus, in the present study, we investigated the applicability of this
phenomenon in the transnational Arab context, and examined Arab viewersÕ perceptions of
being part of the intended audience as a mediator of the effect of social identity on interest
in the show and on perceived identification with the lead characters: RQ3a: Will the
perception of the intended audience of the program account for the effect of social identity
on interest in the program?
International Journal of Communication 13(2019) Selective Exposure and Identification
661 RQ3b: Will the perception of the intended audience of the program account for the
effect of social identity on perceived identification with the characters? Method
Participants Participants were college students recruited through universities in Palestine,
Egypt, and Syria and through student-centered Facebook pages. The participants (N = 123)
were between the ages of 18 and 31 years (M = 25.3 years). There were 80 women and 43
men, of which 84 were Palestinian, 13 were Syrian, 12 from Egypt, four from Lebanon, and
the remaining from other countries. However, only 83 participants completed the questions
about same-sex selective exposure and perceived identification with characters and were
included in this analysis, of whom 57 were women and 26 were men. Moreover, using the
three categories of Arab cultural regions, Palestinian, Syrian, and Lebanese participants only
were included in the within-subjects analyses for media choices and perceived
identification based on cultural identity (N = 70), as participants from these three countries
represent the same Arab Levant cultural region. Design and Procedure This experiment
used a 3 (producing country: Syria, Egypt, or Kuwait) ´ 2 (sex of lead character) within-
subjects design, resulting in six experimental conditions. The participants were sent the link
to a Web page where they were told that they would be participating in a study part of a
research project examining Òmedia use in different cultures.Ó Participants were then
randomly directed to a page containing all six conditions but employing different
combinations of story synopses. The participants were first asked to provide demographic
information including age, sex, and country of origin, followed by viewing six synopses of
Arab television fictional drama programs (one for each condition) and completing measures
for selective exposure, perceived identification with characters, plot relevance, and
perception of the intended audience for each condition. The introductory Web page and all
materials and measures were translated and presented to participants in Arabic. Materials
Twelve unique synopses of television drama serials (Musalsalat) were created based on
existing American and Arab television drama plots. Each synopsis consisted of the title and
a one-paragraph description of the plot. The producing country of the program (to delineate
regional cultural identity) and the sex of the lead character were manipulated to create six
conditions: Syria and female, Egypt and female, Kuwait and female, Syria and male, Egypt
and male, and Kuwait and male. These three countries were chosen because the majority of
drama shows on Arab television come from those countries (Chahine, El Sharkawy, &
Mahmoud, 2007) and because they represent different points on the Arab cultural spectrum
(Kalliny et al., 2008), where Syria (as part of the Levant regional cultural category) lies on
the moderate end, Kuwait (as part of the Gulf regional cultural category) on the
conservative end, and Egypt in the middle. The data were collected before the start of the
Syrian civil war. Twelve synopses were
662 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) used for the six conditions to increase generalizability. The synopses and
conditions were counterbalanced such that each synopsis was paired with each condition
an equal number of times, and every synopsisÐcondition combination was seen by an equal
number of participants. Measures Selective Exposure Three items adapted from Weaver
(2011b) were used to measure participantsÕ interest in watching the show: ÒBased on the
synopsis, how interested are you in watching this show on television?Ó; ÒBased on the
synopsis, how interested are you in watching this show on DVD?Ó; and ÒBased on the
synopsis, how interested are you in watching this show on the Internet?Ó The questions
were scored on a 5-point scale: 1 = not at all, 2 = a little, 3 = somewhat, 4 = very, and 5 = a
lot. The average of the responses to the three questions was used as a selective exposure
measure. CronbachÕs alphas for this scale for each of the six conditions ranged from .90 to
.94. Perceived Identification With Characters Because both identification and wishful
identification are relevant and important to assess the level of connection with characters in
this study, we used four items to assess the level of identification with the lead character in
each show, two of which were used by Cohen and Ribak (2003) to measure identification:
ÒI feel like I could identify with the characters in this programÓ and ÒI think there are
many points of similarity between the lead characters and myself,Ó and two measured the
wishful identification dimension (Hoffner, 1996; Rosengren et al., 1976): ÒI would like to do
the kinds of things the lead characters do in this programÓ and ÒI want to be like the
characters in this program.Ó As identification with characters was measured by asking
participants to report their identification and reactions to the characters, it was considered
a measure of perceived identification. Participants indicated their agreement with the four
statements using a 5-point scale: 1 = strongly disagree, 2 = disagree a little, 3 = neither
agree nor disagree, 4 = agree a little, and 5 = strongly agree. Scores were averaged to create
a measure of identification with the lead character. CronbachÕs alphas for this scale for
each of the six conditions ranged from .89 to .93. Relevance of the Plot Three items were
used by Cohen and Ribak (2003) to measure the perceived thematic relevance of the plot by
the participants, and were therefore used in the present study: ÒThe issues dealt with in the
plot are realistic,Ó ÒThe plot of this TV show is relevant to me,Ó and ÒThe plot of this TV
show reminds me of my life and the lives of those around me.Ó Participants indicated their
agreement with the statements using a 5-point scale: 1 = strongly disagree, 2 = disagree a
little, 3 = neither agree nor disagree, 4 = agree a little, and 5 = strongly agree. Scores were
averaged to create a measure of perceived relevance of the plot. CronbachÕs alphas for this
scale for each of the six conditions ranged from .76 to .84.
International Journal of Communication 13(2019) Selective Exposure and Identification
663 Perceived Intended Audience Three items, adapted from Weaver (2011a), were used
to measure the perceived intended audience of the program: ÒI believe I am part of the
intended audience for this TV show,Ó ÒI believe most of my friends would enjoy this TV
show,Ó and ÒI believe this TV show was made for me.Ó Participants indicated their
agreement with the statements using a 5-point scale: 1 = strongly disagree, 2 = disagree a
little, 3 = neither agree nor disagree, 4 = agree a little, and 5 = strongly agree. Scores were
averaged to create a measure of perceived intended audience. CronbachÕs alphas for this
scale for each of the six conditions ranged from .71 to .83. Statistical Power The G*Power
3.1 statistical program (Faul, Erdfelder, Lang, & Buchner, 2007) was used to calculate the
power for the analyses. For the within-subjects factors (F tests for repeated-measures
analysis of variance [ANOVA] within factors) with six within-subjects conditions (Syrian
male, Syrian female, Egyptian male, Egyptian female, Kuwaiti male, and Kuwaiti female) and
two between-subjects groups (male and female participants) and a sample size of N = 83,
the post hoc power to find a medium effect size (f = 0.25) and p = .05 was 0.99. For the
between-subjects factor (F tests for repeated-measures ANOVA between factors) with two
groups (male and female participants) and a sample size of N = 70, the post hoc power to
find a medium effect size (f = 0.25) and p = .05 was 0.84. For the withinÐbetween
interactions (F tests for repeated-measures ANOVA withinÐbetween interactions) and a
sample size of N = 70, the post hoc power to find a medium effect size (f = 0.25) and p = .05
was 0.99. Results The hypotheses and research questions were tested using repeated-
measures ANOVA. A 3 (country of the plot) ´ 2 (sex of lead character) ´ 2 (sex of participant)
factorial design was used, where sex of the participants was a between-subjects factor and
the plotÕs country and lead characterÕs sex were within-subjects factors. Selective
Exposure Hypothesis 1a predicted that female Arab viewers would express more interest
in shows that feature female lead characters than shows with male lead characters and
Hypothesis 1b predicted that male Arab viewers would express more interest in shows that
feature male lead characters than female lead characters. Sex of participants had a
significant main effect, F(1, 81) = 8.36, p < .01, partial ƞ2 = .09, where women expressed
more interest in the shows (M = 2.18) than men (M = 1.58). Hypothesis 1 was supported
because the gender of the lead characters interacted with the sex of participants and
significantly affected the desire to watch the show, F(1, 81) = 13.25, p < .001, partial ƞ2 =
.14. Table 1 shows the means and confidence intervals.
664 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) Table 1. ViewersÕ Selective Exposure to Television Programs. Male lead
characters Female lead characters Participant M 95% CI M 95% CI Male (n = 26) 1.67 [1.33,
2.01] 1.48 [1.10, 1.89] Female (n = 57) 2.03 [1.80, 2.26] 2.33 [2.07, 2.60] Note. p < .01.
Research Question 1 asked whether Arab viewers express more desire to watch programs
produced in the same cultural region as them (i.e., that feature cultural in-group lead
characters) than those with cultural out-group characters. The results show a significant
difference in the Levant viewersÕ preferences for Syrian, Egyptian, and Kuwaiti programs,
F(2, 67) = 14.62, p < .001, partial ƞ2 = .30. Bonferroni post hoc tests revealed that
participants who were from the Levant region in the Arab world (Palestine, Syria, and
Lebanon) were significantly more interested in watching Syrian shows (M = 2.20, 95% CI =
[1.93, 2.47]) than Kuwaiti shows (M = 1.69, 95% CI = [1.45, 1.94]), p < .001, and more
interested in watching Egyptian shows (M = 2.03, 95% CI = [1.78, 2.28]) than Kuwaiti shows
(M = 1.69, 95% CI = [1.45, 1.94]), p < .001. Arab Levant viewers expressed more interest in
watching Syrian programs over Egyptian programs; however, this finding was not
statistically significant (p = .18). Perceived Identification With Characters Hypothesis 2a
predicted that Arab female viewers would identify more with characters in shows that
feature female lead characters and Hypothesis 2b predicted that Arab male viewers would
identify more with characters in shows that feature male lead characters than female lead
characters. Hypothesis 2 was supported, as the gender of the lead characters interacted
with the sex of participants and significantly affected perceived identification with
characters in the show, F(1, 81) = 5.64, p < .05, partial ƞ2 = .07. Table 2 shows the means
and confidence intervals. There was no statistically significant difference in female (M =
1.76) and male (M = 1.75) participantsÕ perceived identification with characters in
programs featuring male lead characters. Moreover, there was no main effect of sex on
identification with characters overall (p = .28). Table 2. ViewersÕ Perceived Identification
With Characters. Male lead characters Female lead characters Participant M 95% CI M 95%
CI Male (n = 26) 1.75 [1.56, 2.04] 1.59 [1.29, 1.90] Female (n = 57) 1.67 [1.56, 1.96] 1.93
[1.73, 2.14] Note. p < .05 Hypothesis 3 predicted that Arab viewers would identify more
with cultural in-group lead characters than cultural out-group lead characters. There was a
significant difference in participantsÕ perceived identification with characters in Syrian,
Egyptian, and Kuwaiti programs, F(2, 67) = 9.22, p < .001, partial ƞ2 = .22. Bonferroni post
hoc tests revealed that participants from the Levant region in the Arab world identified
significantly more with the lead characters when they were told that the characters were
Syrian (M = 1.96, 95% CI = [1.74, 2.18]) than with the characters presented as Kuwaiti (M =
1.59,
International Journal of Communication 13(2019) Selective Exposure and Identification
665 95% CI = [1.39, 1.79]), p < .001, even though the synopses were exactly the same.
Participants also identified significantly more with characters when they were told that the
characters were Egyptian (M = 1.83, 95% CI = [1.63, 2.03]) than when they were told that
the characters were Kuwaiti (M = 1.59, 95% CI = [1.39, 1.79]), p < .05. Arab Levant viewers
identified more with characters when they were presented as Syrian than when they were
presented as Egyptian, but this difference was not statistically significant (p = .38).
Perceived Relevance and Intended Audience To test the role of perceived relevance and
perceived intended audience in mediating the effect of in-group/out-group dynamics on
selective exposure and identification, we used a path model analysis. For this purpose, the
data were rearranged such that every combination of participant and condition became a
unique row of data. Moreover, the cultural identity of the characters was transformed into a
cultural distance variable, where the higher value indicated greater cultural distance
between the Levant viewers and the characters (1 = Syrian characters, 2 = Egyptian
characters, 3 = Kuwaiti characters). Similarly, the combination of the sex of the character
and the sex of the participant was transformed into one variable with two levels, where the
same-sex condition was in-group and the opposite-sex condition was out-group (0 = in-
group, 1 = out-group). The path analyses were performed for the participants from the
Levant countries only (Palestine, Syria, and Lebanon). The model was tested using AMOS
7.0, with 200 bootstrap samples, 95% confidence interval. Model fit was evaluated using the
chi-square test, the comparative fit index (CFI), the normed fit index (NFI), and the root
mean square error of approximation (RMSEA), as recommended by Thompson (2004). For
the overall model, the chi square was not significant, c2(1, N = 419) = 0.016, p = .899. The
NFI was 1.000, the CFI was 1.000, and the RMSEA was 0.0000, all of which indicate an
acceptable goodness of fit. Using methods for model trimming recommended by Kline
(2004), we sequentially removed the nonsignificant paths from the model. A procedure of
removing the path with the smallest critical value and refitting the model was repeated until
no nonsignificant paths remained. The resulting model demonstrated good fit, c2(8, N =
419) = 9.115, p = .333. The NFI was 0.992, the CFI was 0.999, and the RMSEA was 0.018.
This model is shown in Figure 1.
666 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) Figure 1. Path model showing the significant relationships (standardized
regression weights) between social identity and selective exposure and identification with
characters, through plot relevance and perception of the intended audience. *p < .05. **p <
.01. ***p < .001. There were no significant direct effects of sex and regional cultural
identity on either selective exposure or perceived identification with characters.
Interestingly, regional cultural identity also did not directly affect the perceived relevance of
the plot, and sex identity did not directly affect the perception of the intended audience.
However, there were direct effects of cultural distance on the perception of being part of the
intended audience (r = −.21, p < .001) and of sex identity on perceived relevance of the plot
(r = .08, p < .05). See Figure 1 for all direct effects. Although sex and cultural identity did
not directly affect selective exposure and perceived identification, they had significant
indirect effects on both. In terms of regional cultural identity, increased cultural distance
between the viewers and the characters decreased interest in watching the programs, that
is, selective exposure (r = −.13, p < .01) and decreased the level of perceived identification
with characters (r = −.15, p < .05), via perceived relevance of the plot and the perception of
the intended audience. Moreover, there was a significant indirect effect of cultural distance
on perceived relevance of the plot (r = −.15, p < .01) via perception of the intended
audience. With regard to viewersÕ sharing the
International Journal of Communication 13(2019) Selective Exposure and Identification
667 same-sex identity with the characters, there were significant indirect effects of sex on
identification with characters (r = .05, p < .05) and on selective exposure (r = .03, p < .05)
via perceived relevance of the plot. These results, showing no significant direct effect when
the mediators were included but only indirect effects, indicate that relevance of the plot and
perception of the intended audience together mediated the effects of sex and cultural
identity on selective exposure to the programs and identification with characters.
Regarding Research Question 2, perceived relevance of the plot mediated the influence of
sex identity (but not the influence of cultural identity) on selective exposure to the
programs and perceived identification with characters. Regarding Research Question 3, the
perception of the intended audience mediated the influence of cultural identity (but not the
influence of sex identity) on selective exposure and perceived identification with characters.
However, the relationships between sex identity and the two dependent variables did not
follow the expected pattern when relevance of the plot was added to the model. The
charactersÕ out-group membership with regard to the viewersÕ sex identity increased
interest in the program and perceived identification with the character. In conclusion,
accounting for plot relevance and perception of the intended audience eliminated the direct
effects of identity on selective exposure and perceived identification with characters. In
particular, perceived relevance of the plot explained the effect of in-group sex identity on
selective exposure and perceived identification with characters, and perception of being
part of the intended audience explained the effect of cultural distance on selective exposure
and perceived identification with characters. Overall, the effects were stronger for cultural
identity than sex identity, and the strongest mediator for these effects was the perception of
being part of the intended audience. Discussion The present experiment provides an
empirical examination of Arab viewersÕ social identity as a driver of selective exposure to
media content and perceived identification with television characters in the transnational
Arabic media industry. The findings suggest that viewers in the Levant cultural region of the
Arab world are less interested and might identify less with characters in programs
produced in the more conservative Arabian Gulf, which are dominant in the television
industry. The findings may confirm the Saudi clericsÕ fear about Saudi viewersÕ interest in
and identification with the contestants in Al-RaÕis. Saudi viewers are expected to identify
more with characters from the Arabian Gulf cultural region and be more influenced by this
in-group content. In this study, consistent with existing findings (e.g., Hoffner, 1996;
Reeves & Miller, 1978; Trepte, 2004), female viewers expressed higher identification with
female characters and more interest in programs that feature female lead characters,
whereas male viewers identified more with male lead characters and were more interested
in watching programs with male lead characters. The findings regarding cultural identity
were also in line with these results. Participants from the Levant region in the Arab world
expressed most interest in watching television programs produced in Syria and least
interest in Kuwaiti programs. Similarly, the participants identified more with Syrian and
Egyptian characters than with Kuwaiti characters. These findings are particularly
compelling because the very subtle manipulations
668 Tamara Kharroub and Andrew J. Weaver International Journal of Communication
13(2019) (changing the gender of the lead character and the country name, while keeping
the exact same synopses) produced significant effects. The cultural identity findings give
credence to two of the three commonly referenced cultural regions (the Levant and the
Arabian Gulf), suggesting a salience of regional cultural differences in transnational Arab
media products (e.g., through visual cultural cues such as dialect and dress). However, the
results for Egypt were not significant. Participants did not express more interest in and did
not identify more with characters in Syrian programs than Egyptian programs. This is likely
because of EgyptÕs geography between the Levant and North Africa and the Arab viewersÕ
familiarity with Egyptian media products. The findings in general support social identity
theory (Tajfel, 1978), in that our Arab viewers favored programs that feature their gender
and cultural in-groups and identified more with characters that share their social identities.
These findings have important implications for media effects. Social cognitive theory
suggests that increased exposure and identification with media characters influence the
impact of media content on Arab viewers, where learning is directly related to the
observation of media models and behaviors (Bandura, 1988). Moreover, social cognitive
theory predicts that people are more likely to pay attention to and model behaviors
performed by similar others (Bandura, 2001). Therefore, the results suggest that Arab
viewers are more likely to be influenced by messages and model behaviors presented by in-
group characters (same-sex and proximate cultural identity). In addition, the study found
significant mediators of the relationships between identity and media choices, especially
with regard to cultural identity. Consistent with WeaverÕs (2011a) findings, perception of
being part of the intended audience explained the effect of cultural distance on interest in
watching the programs and perceived identification with characters. In the Arab context,
the results show that a shared cultural identity between the viewer and the character
influences perceptions of the intended audience, which in turn influences the viewersÕ
interest in television programs and their identification with media characters, that is, the
effect of cultural identity on selective exposure and identification is fully mediated by the
perception that the program was made for them. The unexpected findings for the
mediation analyses regarding sex identity might be due to differences between male and
female viewersÕ responses to the sex of the characters. The setup of the mediation path
model, in which sex identity was treated as in-group versus out-group, did not account for
gender differences. In fact, in the first part of the data analysis, we found that male and
female participants did not differ in their level of identification with male lead characters.
This pattern is consistent with existing research (Hoffner, 1996; Reeves & Miller, 1978),
which found that boys identify more with same-sex characters than girls. Overall, the
present study reveals important findings about the role of social identity in the processes of
media consumption among Arab viewers. Consistent with other findings (Kaufman & Libby,
2012; Trepte, 2004), the study shows that Arab viewers are more interested in in-group
content and are more likely to identify more with characters similar to themselves,
suggesting that such in-group media content might reinforce their existing attitudes and
beliefs, especially about gender roles. Moreover, even
International Journal of Communication 13(2019) Selective Exposure and Identification
669 when Arab viewers do consume out-group media programs, the impact of out-group
content on their attitudes and beliefs may be lessened. Although it provides a replication
and expansion of the research on social identity and identification to the Arab media
industry and delivers important empirical data of Arab viewersÕ media choices and
exposure in transnational contexts, the present study is not without limitations. The
relatively small sample, the majority of which was female, and the focus of the study on
Levant participants present the primary limitations to the study. This limitation is due to
the extreme difficulty in collecting data from Arab viewers in different countries. A second
limitation is presented by the measure of perceived identification with characters through
reading a synopsis, which is also due to logistical challenges in data collection from this
understudied population. However, this method of examining identification with characters
using textual narratives has been used in several studies (e.g., De Graaf et al., 2011; Weaver,
2011b). Despite these limitations, the study provides important contributions to this area of
research and evidence of media choices in the Arab context. Future research should
provide comparison with participants from the Arabian Gulf (e.g., Kuwait and Saudi Arabia)
and North Africa. For example, viewers from conservative countries in the Gulf might be
interested in programs from more liberal Arab countries as a way of escapism, which would
be an additional interesting interaction with characters to explore. Moreover, as previous
research has found that identification with media characters can increase the effects of
media content on the viewersÕ attitudes and beliefs (e.g., Kaufman & Libby, 2012), this
impact should also be directly investigated in the Arab context. Examination of regional
conflicts and political polarization in Arab responses to media messages and message
source, including on social media, would be important to assess in the current political
climate. Finally, further investigation of the nature and salience of cultural identity in
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PrevalenceofBusinessModelsinGlobalOTTVideoServices:AClusterAnalysisEun-
AParkWesternColoradoUniversity,USAABSTRACTThispaperisanempiricalanalysisoftheprev
alenceofbusi-nessmodelsintheOverTheTop(OTT)videocontentdistribu-
tionsector.FromareviewoftheliteratureontaxonomiesofOTTbusinessmodels,itidentifiesfivea
ttributesofanOTTcontentdistributionplatform:ownership,verticalintegrationwithcontentpro
ducers,platform/multiplatformcompatibility,servicetype,andrevenuemodel.Applyingcluster
analysistoSNLKagan’sglobaldatabaseof798OTTdistributionnetworks,themostfivecommonly
occurringcombinationsofattributesareidentified.Thepaperconcludesbydiscussingthecharac-
teristicsofthesebusinessmodels.ARTICLEHISTORYReceived18February2019Revised21Augu
st2019Accepted10November2019IntroductionTheincreasingbandwidthofbroadbandnetwo
rkshascreatedopportunitiesforOTTservicestoenteranderodetraditionalbroadcastingmarket
s.IntheUnitedStates,subscriptionstotraditionalcabletelevisionserviceshaveshrunkto94millio
nhouseholdsin2018(or74%oftheestimated127millionUShouse-
holds)(Spangler,2018).Thistrendisespeciallystrongamongtheyoungergen-eration(18–
34),whoaremuchmorelikelytooptforalternativevideodeliveryservices.InEurope,nationalpay-
TVpenetrationlevelsvarybetween24and97percent,anddeclineshavenotreachedthedramatic
USlevels:however,mostnewrevenuegrowthiscomingfromnon-
traditionalSubscriptionVideoonDemand(SVOD)services(Ene,2019).Asthetraditionalcabletel
evisionproviderscontinuetolosecustomers,thefutureseemsbrightforOTTvideoproviders.Sen
singopportunityintheOTTvideoservicesmarket,anumberofdifferententities,includingtraditio
nalbroadcasters,newcontentproviders,andtelecomcompanieshavedeployedavarietyofcomp
etitiveofferings.ThegrowthinOTTvideoservicesisexemplifiedbytheriseofNetflixintheUnitedS
tates.InitiallylaunchedasaDVDmailingservice,itlauncheditsOTTvideostreamingservicein200
7(Voigt,Buliga,&Michl,2016).By2010,Netflixwasdrawingalargershareofsubscribershipandre
venuefromonlinestreamingCONTACTEun-
AParkepark@western.eduCommunicationArts,Language&Literature,WesternColoradoUniv
ersity,1WesternWay,Gunnison,CO81231,USAINTERNATIONALJOURNALONMEDIAMANAGE
MENT2019,VOL.21,NOS.3–4,177–
192https://doi.org/10.1080/14241277.2019.1695257©2019InstituteforMediaandCommu
nicationsManagement
(Netflix,2010),demonstratingtheviabilityofanOTT-
basedbusinessstrategy.Sincethen,Netflixhasincreaseditssubscriberbaseandexpandedinterna
tionally,reachinganoverallsubscribercountof104millioninthesecondquarterof2017(Statista,
2017).Yet,NetflixislargelyanexceptionintheglobalOTTmarket,wheremostnewentrantsarestr
ugglingtofindtraction(Agnese,2016),andevenforNetflix,subscribergrowthmighthavealready
plateauedinitsmajormarkets(Newman,2016),andrevenuesarenolongergrowingexponentiall
y(Kim,2016).Datashowthat,asoflate2016,thereweremorethan800OTTvideoprovidersworld
wide(SNLKagan,2017).Theemergenceoftheseprovidershasshakenupthecomplexverticallyint
egratedbroadcasttelevisionandcableindustriesinmanycountries(Skot,2014),andledtopheno
menasuchas“cord-cutting,”and“cord-
shaving”(Arolovitch,2015;Banerjee,Rappoport,&Alleman,2014).1Duetotheseparadigmshifts
,scholarlystudieshaveexaminedthebusinessmodelsandstrategicpositioningofTVplayers(Abr
eu,Nogueira,Becker,&Cardoso,2017;Aidietal.,2013;Ross&Erasmus,2013).Otherinsightsarepr
ovidedbyconsultingfirmreportsorthetradepress(ABIResearch,2014;Song,2013,2014).These
scholarlystudiesandindustryreportspointtoadiversityofbusinessmodelsthathavebeendeploy
ed,includingsubscription-basedmodels,advertis-ing-
supportedmodels,andmultiscreenstrategies.Butnoneofthesemodelshaveprovedtobeconsiste
ntperformersregardingrevenuegenerationandprofitability.Thus,despitethepromiseofOTTse
rvicesandthethreattheyposetotraditionalbroadcasters,thereisnosingledominantbusinessmo
delintheOTTvideodistributionsector.Instead,awidediversityofoptionsexistwithineachattribu
teofanOTTplatform:forexample,platformcapability(PC/Mac,smartphone,tablet,connectedTV
,gameconsole,Internetstreamingplayers,pay-TVset-topbox),revenuemodels(free/ad-
supported,transactional,subscription,appfee,premiumcontentcost),etc.Therefore,theobjecti
veofthispaperistoinvestigatethemostcommonlyoccurringattributesoftheOTTbusinessmodel
s.ItseekstofindoutiftherearecommonfeaturesorattributestoOTTbusinessmodels,andifyes,wh
attheirrelativefrequenciesareandhowcorrelatedtheyarewithotherfeatures/attributes.Finall
y,itaskswhatcombinationsofattributesaremostcommonamongbusinessmodelsinOTTvideose
rvice.Thispaperproceedsasfollows.Inthenextsection,anoverviewoftheliteratureonOTTbusin
essmodelsisprovided,focusingonthefeaturesorattributesofmodelsthathavebeenthefocusofst
udies.Wethenexplicatetheconceptofa“businessmodel”andusetheliteraturetoidentifythekeya
ttributesofOTTvideoservicebusinessmodels,tobeinvestigatedinthedataanalysis.Wethenpres
entourdataanddescribeourmethodol-
ogy.Thethirdsectionpresentstheanalysis,whichleadstotheconcludingchapter.178E.-A.PARK
LiteraturereviewWiththerisingpopularityofOTTservices,providershaveexperimentedwitha
widevarietyofplatforms,contentsources,revenuemodels,andmultiscreenstrategies(Qin&Wei,
2014).Ad-supportedmodelslikeYouTubehavecapitalizedonsignificantamountsofuser-
generatedcontent,whilesubscription-
basedservicessuchasNetflixandAmazonPrimeVideohaveinvestedaggressivelyinoriginalcont
ent(Castillo,2016).Facebook’svideodistributionisgrowing,andAppleisplanningtoaddvideotoi
tsmusicservice.Traditionalvideoprovidershaveaddedmorefeaturestotheirservicepackagetoc
ompetewithOTT:forexample,CBSdistributesoriginalTVseriesexclusivelyoverSVODnetworks.
SatelliteTVoperatorsaretransform-
ingthemselvesintointernetMVPDs,suchasViasattoViaplay,andDISHtoSling.Platformsforthedi
stributionofcontentareproliferating:personalvideorecorders,transactionVOD,andsubscriptio
nVOD,andset-
topboxesaredeployingmanynewcapabilitiessuchasRokuTVthatcanpauseandcatchuplivebroa
dcasts.GiventhewidediversityofOTTmodelsavailable,researchershavepro-
posedvarioustaxonomicclassifications(Abreuetal.,2017;Crawford,2015).Abreuetal.(2017)su
rveyedvideocontentofferingsfrom62countriesandproposedaclassificationbasedona2×2matr
ix,withtheprovider(managedoperatornetworkorOTT)asonedimensionandtypeofcontent(lin
earornon-
linear)astheotherdimension.Therefore,thefourcategoriesofviewingarelinearofferingsfromm
anagedoperatornetworks(traditionaltelevision),non-
linearofferingsfrommanagedoperatornetworks(time-
shiftedandVideoonDemand,VODservices),linearOTTservices(streamingcontentfromtraditio
nalTVstations)andthemarket-disruptingnon-
linearOTTservices(Netflixetal.).Abreuetal.(2017)organizebusinessmodelsofTVviewing(time
-shiftedTV,VOD,personalvideorecorders,catch-upTV,subscriptionVOD,app-
baseddistribution,etc.)alongwiththis2×2classification.2Theresultsshowthat34countrieshad
oneormoreoperatorsofferingCatch-upTVservices.MostoperatorswithCatch-
UpTVservicesalsoofferedshortandlong-
formonlineTV.Videorevenueismadeupofsubscriptionfeesandadvertisingrevenue,aswellasele
ctronicsell-throughretailandon-
demandrevenuefromonlineservicesdeliveringTVandvideocontent.Similarly,Crawford(2015)
dividedOTTvideodistributorsintofourcategories:OTTaggregatorsoforiginalandlicensedconte
nt;3traditionalpay-TVdistributorsdeployingmultiscreen,online-
offline,“TVeverywhere”strategies;individualcon-
tentowners,especiallysportsleagues(MLB,NBA);anddevicemanufacturerswhodistributecont
enteitherontheirownorinpartnershipwithothergroups.4WhileAbreuetal.focusprimarilyonth
eproviderandthetypeofviewingexperienceoffered,othersfocusontherevenuemodels(Martíne
z,Navio-Marco,&Perez-
Leal,2017;Waterman&Sherman,2016).Martínezetal.INTERNATIONALJOURNALONMEDIAM
ANAGEMENT179
(2017)differentiatebetweenthreemodels:fixedpayments,pay-per-
view,andsubscription.WatermanandSherman(2016),intheiranalysisoftheeconomicsofonline
video,focusmoreontherevenuemodels.Theyidentifyfivebasiconlinevideorevenuemodels:àlac
arterentalsandpurchases,orVOD;subscription;ad-supportedprofessionalcontent;ad-
supporteduser-generatedcontent;andverification-
dependent,bundledcontent.VODsystemsallowuserstoselectandviewfromamenuofchoiceson
aperplaybasis,whilesubscriptionserviceschargeaperiodic(monthly,annual,etc.)flatfeeforacce
sstoanentirelibraryofcontent.Ad-supportednetworks,whetherbasedonprofessionaloruser-
generatedcontent,donotchargetheuserdirectlyforaccessbutfinancethemselvesthroughadvert
ising.Hybridmodels,involvingbothsubscriptionandadvertising,or“freemium”modelsinwhich
userswillingtopayafeeareexposedtonoorlessadvertisingarealsopossible.Finally,verification-
dependent,bundledcontentmodelshavebeenusedbytraditionalbroadcasterswhoallowauthen
ticatedofflinesubscriberstoaccessstreamedcontentonline.Thisiscommonwithbroadcasters’m
ultiscreen,“TVeverywhere”strategies(Waterman&Sherman,2016).Severalauthorshavealsofo
cusedonthecontentofOTTvideo(Martínezetal.,2017).Aprimarydifferentiationisbetweenshort
-formandlong-formcontent.Theshort-
formvideo,roughlylessthan10minutesinlength,includesmuchuser-
generatedcontent,aswellasexcerptsfromtelevisionshows,musicvideos,trailers,andteasers.Th
elong-formvideoincludesprogrammingsuchasfull-
lengthtelevisionshows,documentaries,andmovies.Thereisanassociationbetweenthetypeofvi
deoandrevenuemodels,withtheshort-formvideobeingpredominantlyadvertising-
supported,andlong-formcontentdistributedthroughsubscription-
basedmodels.AuthorshavealsofocusedonlesscommonlyobservedattributesofOTTplatforms.
Kim,Kim,Hwang,Kim,andKim(2017)identifiedrecommenda-
tionsystems,resolution,andviewingoptionsasessentialproductattributesofOTT.Intheircompa
risonofChineseandKoreanOTTusers,theyfoundthatChineseconsumersweremostpersuadedb
yresolution,followedbytherecommendationsystemandviewingoptions;Koreanconsumersra
nkedtherecommendationsystemasthemostvaluableattribute,followedbyviewingoptionsandr
esolution.Thoughthesecharacteristicsareimportantinacompetitivesenseandinfluenceuserad
optionofOTTservices,thereislessattentionpaidtothemintheliterature.BusinessmodelsMuchof
theliteraturediscussedaboveonthetaxonomyofOTTvideoprovidersfocusonidentifyingdistinc
tivequalitiesofeachserviceprovider;specifically,theliteraturehasfocusedonidentifyingbusine
ssmodelsforOTTvideoservices,asacombinationofthesedistinctivequalities.Simply180E.-
A.PARK
put,abusinessmodelrepresentsthe“underlyingeconomiclogicthatexplainshowwecandeliverv
aluetocustomersatanappropriatecost”(Magretta,2002,online).Anotherdefinitionstatesthata
businessmodelis“a“coherentframeworkthattakestechnologicalcharacteristicsandpoten-
tialsasinputsandconvertsthemintocustomersandmarketsintoeconomicoutputs”(Chesbrough
&Rosenbloom,2002,quotedinGhezzi,Cortimiglia,&Frank,2015,p.348).Essentially,abusinessm
odelcombinesthedistinctbutinterrelatedactivitiesofproducingagoodorservice(innovatingthe
product,obtainingrawmaterials,componentsorparts,manufacturing,etc.)anddistributingit(id
entifyingandreachingcustomers,marketinganddis-
tributingthegoodorserviceanddeliveringafter-
saleservice).Ghezzietal.(2015)identifyfourdimensionsofbusinessmodels:valueproposi-
tion,valuecreation,valuedelivery,andvalueappropriation.Thevaluepropositionistheuniquepr
oductorservicethatcreatesvalueforthecustomer;inthecaseofOTT,thisistheaudiovisualsoftwar
e,withtheaddedfunctionalitiesoftime-
flexibleviewing,alternativescreen,ormultiscreencapability,ormobileportabilitydifferentiatin
gitfromtraditionalvideoofferings.Thevaluecreationreferstotheorganizationalcharacteristics
oftheproviderandincludesthesupplychains,resources,andproductionmodesenablingthecreat
ionofthevalueproposition.Thevaluedeliveryimplicatesthekeypartnerships,distributionchann
elsandcustomerrelationshipstrategiesthatconveytheproductorservicetothecusto-
mer.Finally,valueappropriationreferstotherevenuegeneration,pricingandsharingmechanism
sthatenabletherealizationofprofitanditsallocationtovariouspartnersalongthevaluechain.Stef
fanandRichard(2014)havecomprehensivelyreviewedclassificationschemesforbusinessmode
lsbyfocusingontheirattributes.Commonlyusedfactorstodifferentiatebusinessmodelsincluder
evenueschemes(salesversusrentalversuslicensing),relationshipswithcustomers(salesperso
nnelversusself-
serviceversusautomateddelivery),distributionchannels(retailoutletsversusonline),etc.(seeT
able3,p.25forafulllistingofbusinessmodelattributes).ToidentifythebusinessmodelsforOTTvid
eoservices,wefirstcon-
sultedtheliteraturetolocatethemostcommonlyusedattributesofOTTvideoservices.Fromtheta
xonomiesofOTTvideoservicereviewedinthesectionabove,threeattributesmaybeidentified:or
ganizationalmode(contentoriginators,aggregators,redistributors,etc.),distributionchannels(
wired/mobile,devices),andrevenuemodels(advertising-funded,subscrip-
tion,hybrid,etc.).However,severalauthorsalsohighlightedtheimpor-
tanceofthefirm’sorganizationalstructure(Crawford,2015;Waterman&Sherman,2016).Accor
dingly,weaddtwomoreattributestothislist:ownership(broadcasters,telecommunicationscom
panies,Internet-basedcompanies)andverticalintegration(integratedornon-
integrated).“Verticalintegration”referstothecombinationofproductionactivitiesatdifferentst
agesofthechainofproductionwithinonecompany.VerticalINTERNATIONALJOURNALONMEDI
AMANAGEMENT181
integrationwithaprogramproductioncompanymayenableanOTTvideoprovidertohaveeasyac
cesstoalibraryofcontent.However,currentresearchhasnotexaminedhowprevalenteachtypeis
withinanattribute(e.g.,whatpercentageofOTTvideoprovidersareadvertisingfunded?),andho
wtheattributesrelatetoeachother(e.g.,whatisthemostcommonrevenuemodelassociatedwith
mobilecontentdelivery?).Thesectionsbelowattempttoanswerthesequestions,butfirst,wedesc
ribeourdata.DataanalysisTheprimarydataforthisanalysisisSNLKagan’sGlobalOTTproviderda
tabase.SNLKaganisaleadingfirmthatprovidesdataandanalysisservicesforthemedia,entertain
ment,andcommunicationsindustries.Itwascreatedthroughthe2007acquisitionofKaganResea
rch,5aMonterey,CA-basedmediaresearchfirmfoundedin1969,byCharlottesville,VA-
basedSNLFinancial,abusinessintelligenceprovider(Qualtrough,2007).SNLKaganprovidesacc
esstoabroadrangeofinformationanddatabasesonthemediaandentertainmentindustriestoitsc
lients,includinguniversities.SNLKagan’sGlobalOTTproviderdatabaselists798OTTprovidersfr
om71differentcountries,andseveraloftheirattributes,includingplatformcapabil-
ities,revenuemodels,andprogrammingsources.ThedatabaseidentifiesthenameoftheOTTservi
ce,theservice“parent”(theorganizationofferingtheservice),thegeographicalregionwithinwhic
htheserviceisoffered(e.g.,Asia,WesternEuropeetc.),thenationalmarketsinwhichtheserviceisa
vailable,theservicetype(OTTaggregator,TVeverywhere,catch-upTV,etc.),thedistribu-
tiondevicessupported(connectedTV,gameconsole,smartphone,tablet,etc.),therevenuemodel
s(advertising,authenticated,rental),notestorevenuemodels,andsizeofthearchive.Forthedataa
nalysis,eachOTTservicewascodedalongseveraldimensions.First,theservice“parent”wascode
dintosixcategories,basedontheirprimarybusiness:telecommunicationscompany(TEL),broad
caster(BRO),pay-TVpro-
vider(PAYTV),mediacontentproducer(MEDIA),webcompany(WEB),andotherorunclassified(
OTHER).Toaidtheclassification,additionalinformationaboutcompanieswascollectedfromthei
rwebsiteswhenneeded.Thecategoriza-
tionwasexclusive:eachservice“parent”wasassignedonlytoonecategory.Second,theservicetyp
ewascodedasreportedbySNLKagan:asacontentaggregator(AGGRE),TVeverywhere(TV_EVER
Y),andcatch-
upTV(CATCHUP).Servicetypestoowerecodedexclusively.Insomecases,itwasobservedthatOT
Tservicesofferedbythesamecompany,butwithdifferentservicetypeswerebrandedwithdiffere
ntnames;eachname,there-
fore,canbeassociatedexclusivelywithaservicetype.ItmaybenotedthatitisnottheownerofanOT
Tservicethatiscoded,buttheOTTserviceitself.SNLKagan’sdataincludesmultipleofferingsfromt
hesameparentcompany,182E.-A.PARK
withseparatecodesforeachoftheOTTservices.Therefore,forexample,multipleofferingsfromDi
sney,suchasHuluandESPN+areseparatelycodedforthebusinessmodelfollowedbyeach.Third,t
heplatformsonwhichtheserviceisdistributedwascoded.Whilelistingallplatformsexhaustively,
sevenplatformscouldbeidentified:con-nectedTV;gameconsole;Internetstreamingplayer;pay-
TVset-
topbox;PC/Mac;smartphone;andtablet.Sincemanyserviceswereavailableformultipleplatfor
ms,thecodingfor“platform”wasdonenon-
exclusively.Fourth,therevenuemodelwascodedasreportedbySNLKaganintofivecategories:ad
vertising,authenticated,rental,subscription,andpurchase.Fifthandfinally,avariable“verticalin
tegration”wasdefinedaspresentiftheparentcompanyoftheOTTvideoservicewasalsoacontent
producer:informa-
tionabouttheparentcompanywasresearchedonlinetocodeforthisvariable.Thepercentagedistr
ibutionofattributesforallthecategoriesisprovidedinTable1.Forexample,theparentcompanyof
18percentofallOTTvideoserviceswasatelecommunicationscompany,andbroadcastersowned
23per-
cent.Notethatthepercentagedistributionbytheplatformismorethan100percent,since‘platfor
ms’wascodednon-
exclusively:anOTTvideoservicemaybemadeavailabletomultipleplatforms.Areviewofthedatai
nTable1providesusefulinsightsintotheresearchobjectivesofthispaper.Worldwide,webcompa
niesaretheentitiesmostoftendeployingOTTvideo,with26percent,followedbybroadcasters(23
%)andtelecomcompanies(18%).Only44percentofallOTTvideoprovidersareverticallyintegrat
edwithcontentproducers:therestaggregatecontentfromavarietyofsources(56%).Verticallyin
tegratedcompaniesaremorelikelytooffermultiscreenTVeverywherestrategies(25%ofallOTTs
ervices,or57%ofverticallyintegratedOTTservices),while19percentofallOTTservicespursueac
atch-
upTVstrategy(43%ofverticallyintegratedOTTs).AnoverwhelmingmajorityofOTTservicesare
accessibleoverPC/MACplatforms(96%),tablets(90%),andsmartphones(89%).Alittleoverhalf
(53%)ofallOTTservicesareaccessibleonconnectedTVsets,whilestream-
ingmediaplayers(35%)andgameconsoles(29%)arealsopopular.Perhapsnotsurprisingly,only
11percentofallOTTservicesareaccessibleoverpay-TVset-
topboxes,sincethesedevicesarecontrolledbycable/broadbandproviders,whosevideoservices
competewithOTTservices.Intermsofrevenuemodels,OTTservicesaresplitalmostevenlybetwe
enauthenticatedcontentproviders,subscriptionservices,andadvertising-
basedmodels,witheachaccountingforaquarteroftheglobalmarket.TheremainingOTTvideoser
vicesfollowarentalorpurchasebasedmodel.Toinvestigatefurthertherelationshipsamongtheva
riables,bivariatecorrela-
tionswerecalculatedandreportedinTable2.Significantcorrelationswereobservedbetweensev
eralofthevariables:telecomproviderswerelikelytodeployTVEverywherestrategiesusinganaut
henticatedcontentrevenuemodel.INTERNATIONALJOURNALONMEDIAMANAGEMENT183
BroadcasterswerestronglylikelytodeployOTTserviceslikecatch-
upTV,whichwasalsolikelytobeadvertisingsupported.Meanwhile,webcompaniesdidnotdispla
yaclearpatternregardingrevenuemodels,thoughtheyweresomewhatmorelikelytousesubscri
ption-
based,rentalorpurchasemodels,andsomewhatlesslikelytouseauthenticatedcontentmodels.A
potentialproblemwastheperfectnegativecorrelationbetweenverticalintegrationandanaggreg
ationservicetype:thisisexaminedmoreintheclusteranalysissectionbelow.Interestingpatterns
werealsoobservedintermsofdevices.Thestrongestcorrelationwasobservedbetweensmartpho
nesandtablets:OTTservicesavailableoveronewerealmostcertainlyavailableovertheotherasw
ell.WeakerpositivecorrelationswerealsoobservedbetweenconnectedTVs,streamingmediapla
yers,andgameconsoles.Tofurtherinvestigatethesepatterns,clusteranalysiswasconducted.Clu
steranalysisToidentifythevariousOTTbusinessmodels,ahierarchicalclusteranalysisfollowedb
yak-
meansanalysiswasperformedusingSPSS.Eachsubject’srelativestandingoneachofthevariables
wasestimatedbycomputingfactorTable1.Percentagedistributionbycategory.VariableIDPerce
ntageOwnershipTelecomcompanyTEL.18BroadcastersBRO.23PayTVprovidersPAYTV.14Me
diacompaniesMEDIA.17WebcompaniesWEB.26OthersOTHERS.03VerticalIntegrationVERTI
CAL.44ServiceTypeAggregatorsAGGRE.56TVEverywhereTV_EVERY.25CatchupTVCATCHUP.
19PlatformsConnectedTVCONNECTV.53GameConsolesGAMECONS.29Screamingmediaplaye
rsSTREAMIN.35PayTVsettopboxSETTOP.11PC/MACPCMAC.96SmartphoneSMARTP.89Tabl
etsTABLET.90RevenueModelAuthenticatedAUTHEN.25SubscriptionSUBSCR.26Advertising
ADVERT.25RentalRENTAL.15PurchasePURCHA.09Note:N=798forownership,verticalintegra
tion,servicetype,andplatform;N=797forrevenuemodel(1missingdata)184E.-A.PARK
Table2.Correlations.TELBROPAY_TVMEDIAWEBOTHERSVERTICALAGGRETV_EVERYCATC
HUPCONNECTVGAMECONSSTREAMINSETTOPPCMACSMARTPTABLETAUTHENSUBSCRAD
VERTRENTALOWNERSHIPTEL1BRO-.257**1PAY_TV-.191**-.218**1MEDIA-.204**-.242**-
.180**1WEB-.280**-.319**-.237**-.264**1OTHERS-.076*-.087*-0.064-.072*-
.095**1VERTICAL.269**.322**.300**-.261**-.511**-.142**1SERVICEAGGRE-.269**-.322**-
.300**.261**.511**.142**-1.000**1TV_EVERY.514**-.307**.484**-.198**-.336**-
.093**.655**-.655**1CATCHUP-.229**.750**-.156**-.112**-.276**-.077*.543**-.543**-
.279**1PLATFORMCONNECTV-.213**-0.03-.166**-0.037.349**.087*-.359**.359**-.339**-
.080*1GAMECONS-.194**-0.028-0.029-0.045.235**.072*-.207**.207**-.179**-
0.065.454**1STREAMIN-.237**-0.057-.200**0.02.365**.116**-.388**.388**-.346**-
.109**.430**.418**1SETTOP-.098**.166**-.086*0.064-.084*.070*-.092**.092**-
.207**.112**.193**.265**.125**1PCMAC-.103**.087*-0.061-0.0240.0660.031-.092**.092**-
.187**.092**.148**.093**.099**0.0681SMARTP0.0060.0320.006-.117**.084*-0.0440.021-
0.0210.0150.009.101**.109**.173**-.148**-0.0031TABLET0.0140.0280.03-.090*0.042-
0.05-0.0040.004-0.001-0.004.156**.148**.184**-
.112**0.024.891**1REVMODELAUTHEN.511**-.307**.486**-.197**-.335**-.093**.654**-
.654**1.000**-.279**-.337**-.178**-.345**-.207**-.188**0.0210.0051SUBSCR-.162**0.014-
.090*0.034.173**-0.004-.392**.392**-.343**-
.117**.144**.182**.188**.087*0.035.083*0.069-.343**1ADVERT-.210**.439**-.185**-
0.045-0.036-0.057.173**-.173**-.338**.595**0.001-0.043-0.0430.0460.065-0.012-0.039-
.338**-.346**1RENTAL-.089*-.109**-.158**.171**.139**0.068-.349**.349**-.242**-
.175**.168**0.015.079*.084*0.061-.086*-0.02-.242**-.248**-.245**1PURCHA-.098**-.091*-
.123**.104**.127**.152**-.225**.225**-.177**-.090*.080*0.039.205**0.0050.058-0.034-
0.03-.177**-.181**-.179**-.128****Correlationissignificantatthe0.01level(2-
tailed).*Correlationissignificantatthe0.05level(2-
tailed).INTERNATIONALJOURNALONMEDIAMANAGEMENT185
Table3.Meansandstandarddeviationsofvariablesbyclustergroup.OwnershipServiceTypeClus
terNTELBROPAYTVMEDIAWEBOTHERSAGGRETV_EVERYCATCHUP1429.08(.27).10(.31).0
4(.20).26(.44).48(.50).04(.19)1.00(.07).00(.00).00(.07)2199.53(.50).01(.07).43(.50).04(.20
).00(.00).00(.00).00(.00)1.00(.00).00(.00)3146.00(.00).88(.32).02(.14).08(.30).01(.08).00(.
00).01(.08).00(.00).99(.08)411.73(.47).00(.00).27(.47).00(.00).00(.00).00(.00)1.00(.00).00
(.00).00(.00)54.00(.00)1.00(.00).00(.00).00(.00).00(.00).00(.00)1.00(.00).00(.00).00(.00)Pl
atformsRevenuemodelClusterNCONNECTVGAMECONSSTREAMINSETTOPPCMACSMARTPT
ABLETAUTHENSUBSCRADVERTRENTALPURCHAS1429.70(.46).38(.49).53(.50).13(.34).98(
.14).88(.32).90(.30).00(.00).43(.50).17(.38).26(.44).14(.35)2199.24(.43).16(.36).07(.25).00
(.00).90(.30).90(.30).90(.30)1.00(.00).00(.00).00(.00).00(.00).00(.00)3146.45(.50).23(.42).
25(.44).18(.39)1.00(.00).90(.29).90(.30).00(.00).14(.35).82(.39).00(.00).04(.20)411.09(.30
).09(.30).00(.00).18(.41).91(.30)1.00(.00)1.00(.00).00(.00).00(.00)1.00(.00).00(.00).00(.00
)541.00(.00)1.00(.00).75(.50).75(.50)1.00(.00).75(.50)1.00(.00).00(.00).00(.00).00(.00)1.0
0(.00).00(.00)186E.-A.PARK
scores,whichwerethenusedasinputvariablesforclustering(Cook,2005).Themorestronglythev
alues(i.e.,factorscores)aresituatedinthenegativerange,themorethecompany’sfactorsarebelo
wtheclusteraverage,whilepositivevaluesindicatearatingabovetheclusteraverage.Distancesbe
tweentheclusterswerecalculatedwiththeEuclideandistancemeasure,andaggre-
gationofclusterswasperformedwithWard’sprocedure.Toreflectthetruestructureofthedataset
,theelbowcriterionwasusedtodecideonthenumberofclusters,whichresultedinchoosingafive-
clustersolutionasthemostappropriaterepresentationofthedata(Yim&Ramdeen,2015).Apote
ntialproblemwiththeclusteringprocedurewastheperfectnegativecorrelationbetweenverticali
ntegrationandanaggregationservicetype.Ifthereisastrongcorrelationbetweenvariables,theya
renotsufficientlyuniquetoidentifydistinctsegments.Ifhighlycorrelatedvariablesareusedforclu
steranalysis,specificaspectsaddressedbythesevariableswillbeoverrepresentedintheclusterin
gsolution.Inthisregard,absolutecorrela-
tionsabove0.90arealwaysproblematic(Sarstedt&Mooi,2014).Thus,theverticalintegrationvari
able(VERTICAL)wasdroppedbecauseitwashighlycorrelatedwiththeaggregatorservicetype.M
eansandstandarddeviationsofeachvariableforthefiveclustergroupsarepresentedinTable3.To
detectdifferencesinscoresacrossthedifferentvariablesbetweenthedifferentclusters,ANOVAw
asperformedfollowedbyaTukeytest.Below,theattributesofthefiveclustersarediscussed.Cluste
r1(N=429).Thisclusterismostlycomprisedofwebcompanies,thoughsomemediacompaniesare
alsorepresented.Regardingcontent,theseOTTprovidersareexclusivelyaggregators,andthepri
maryrevenuemodelissubscriptions,thoughamajoritydoesnotfavorit.Asubstantialpercentage
alsouserentalmodels,advertising,andpurchase.TheprimarydistributionplatformsarePC/Mac,
smartphones,andtablets,thoughconnectedTVandstreamingmediaarealsoused.Intermsoftheo
perationsoftheirbusinessmodel,companiesinthisgrouparenon-
traditionalvideoproviderswithoutaccesstoin-
houseprogramproductionfacilitiesorbusinessallianceswithprogramproviders.Therefore,thei
rservicetypeisaggregation–
puttingtogetherarosterofprogrammingfromdiversesources.Also,asnewentrants,companiesi
nthisgroupopportunisticallychooserevenuemodelswithsome–
thosewithamoreextensiveaudiencebase–
favoringadvertisingandothersoptingforrentalorsubscriptionmodels.Finally,thesecompanies
withoutaccesstoowneddistributionplatformssuchascablebroad-
bandorDSLnetworkshavetotargetnewvideoconsumptiondevicessuchascomputers,smartpho
nes,andtablets.Cluster2(N=199).Thisclusterisdominatedbytelecomandpay-
TVcompanieswithverylittleparticipationbyothertypesofowners.Thegroupisdefinedbyitsexcl
usiveuseof“TVeverywhere”strategiesandauthenticatedINTERNATIONALJOURNALONMEDIA
MANAGEMENT187
content.ThemodelreliesstronglyondistributionviaPC/Mac,smartphones,andtablets,witheven
lessuseofconnectedTVandothermodesthanCluster1.Alargepartofthisclusteriscomprisedofno
n-
traditionalvideoproviders(telecomcompanies)who,however,havethebenefitofaccesstoDSLin
fra-structures.Asecondcategoryispay-
TVcompaniesformerlyaffiliatedwithcable/broadbandnetworks.Bothgroupshaveseentheirau
diencesunderattackduetocord-cuttingandfallingpay-
TVsubscriptionrates.Therefore,bothgroupsappeartoaimwitha“TVeverywhere”businessmod
eltomigratewiththeircustomerstonewviewingplatformssuchasPC/Mac,smartphonesandtabl
ets.Cluster3(N=146).Thisgroupiscomprisedoverwhelminglyofbroad-
casters,thoughsomemediacompaniesarealsorepresented.Theservicetypeisalmostexclusively
“catch-
upTV,”fundedprimarilythroughadvertising,withalittlesubscription.Asinthecaseoftheothercl
usters,Cluster3tootendstodistributeoverPC/Mac,smartphones,andtablets,thoughitalsohasas
ubstantialpresenceonothermedia,includingconnectedTV,gamingconsoles,andstreamingmed
iaplayers.Themajorstrengthofcompaniesinthiscluster,primarilycomprisedofbroadcasters,ise
xpertiseintheproductionoforiginalprogrammingandaccesstolargeprogramminglibraries.Ho
wever,thesecompanieshaveseenasteadyerosionoftheirliveaudienceratings,especiallyintheU
nitedStates,butalsoinmanyleadingmarkets,withnegativeconsequencesforadvertisingrevenu
es.Launchinga“catch-upTV”businessmodelmayfulfilltwoobjec-
tives:one,toincreasetheappealoftheirprogrammingbycombiningitwithofferingsfrommultiple
broadcaststations;andtwo,toincreasetotalview-
ershipandstanchtheerosionofadvertisingrevenue.Cluster4(N=11).Arelativelysmallclusterisc
omprisedoftelecomcompaniesandsomepay-
TVcompanies,asinthecaseofCluster2.Itmay,therefore,beconsideredanalternativebusinessmo
delfortelecomandpay-
TVcompanies,mainlydifferentiatedfromthelatterbyitsrelianceonanaggregationservicemodel
(whereasCluster2useda“TVeverywhere”strat-egy)andanadvertising-
basedrevenuemodel(contrastedwithCluster2’srelianceonauthenticatedcontent).Asinthecase
ofallclusters,Cluster4reliesondistributionoverPC/Mac,smartphone,andtablet,butunlikeClust
er2,thereispracticallynopresenceonanyotherplatform.ThecontrastbetweenClusters2and4hi
ntsatthedifferentstrategiesadoptedbytelecomcompanies,thatformalargepartofbothclusters,
astheypursuevideoaudiences.Telecomcompaniesarenottraditionalvideodis-
tributors,buthaveoverthepastexpertiseandexperienceinvideoprogramdeliverythroughacqui
sitionsand/ormarketparticipation.However,thosethathaveacquiredgreaterexpertiseinvideo
programmingappeartofollowa“TVeverywhere”strategy,whilethosethathavenothaveoptedfo
ranaggregationstrategy.188E.-A.PARK
Cluster5(N=4).Thesmallestcluster,itiscomprisedexclusivelyofbroadcasters;itmaybeanaltern
ativemodelforthebroadcastersinCluster3.Theseaggregatorsrelyexclusivelyonarentalbasedre
venuemodel.Ofalltheclusters,theyarethemost“platformagnostic,”equallypresentonalldistrib
utionplatforms:connectedTV,gameconsoles,streamingmedia,pay-TVset-
topboxes,PC/MAC,smartphonesandtablets.Butuniquelyamongtheclusters,Cluster5usesset-
topboxesheavily,butperhapsthisisanartifactofsmallnumbers.Inthenextsection,wereturntoou
rresearchquestionsandpresentourconclusions.DiscussionandconclusionWhilenumerousstu
dieshaveexaminedbusinessmodelsinthenewOTTvideoservicessector,fewquantitativeanalys
eshavebeenaimedatanalyzingtherelativeprevalenceofbusinessmodels,ortheelucidationofthe
mostcommonattributesofthesebusinessmodels.Tofillthisgapintheliterature,theobjectiveofth
ispaperwastoinvestigatewhethertherearecommonfeaturesorattributestoOTTbusinessmodel
s,andifyes,whattheirrelativefrequenciesareandhowcorrelatedtheyarewithotherfeatures/att
ributes.Finally,itaskswhatcombinationsofattributesaremostcommonamongbusinessmodelsi
nOTTvideoservice.UsingSNLKagan’sglobaldatabaseofOTTvideoserviceproviders,thispaperc
odedfiveattributesofbusinessmodelsidentifiedbasedontheliterature:ownership,servicetype,
verticalintegration,platforms,andrev-
enuemodelsandcomparedtheirrelativefrequenciesandcorrelationsacrossdimensions.Cluster
analysiswasperformedtoidentifythemostcommoncombinationsofattributesinbusinessmodel
sforOTTvideoservices.Thefirsttakeawayfromtheclusteranalysisisthatownershipisnotfullycoi
ncidentalwithbusinessmodels.Thoughclustersaredominatedbyoneortheotherformofowners
hip,diverseownersarerepresentedwithineachcluster.Mediacompaniesaresplitbetweensubsc
ription-basedaggregators(Cluster1)andadvertising-fundedcatch-
upTV(Cluster3).Similarly,tele-comandpay-
TVcompaniesfavoreitherTVeverywherewithauthenticatedcontent(Cluster2)oradvertising-
basedaggregators(Cluster4).Broadcastersaremostlyadvertising-funded“catch-
upTVproviders(Cluster3),thoughrentalbasedaggregationmightbeanalternativebusinessmod
elforthem.Inotherwords,telecommunicationscompanies,broadcasters,mediafirms,andwebb
usinessesofferOTTvideoservicesusingbusinessmodelsnotcommonwithintheirownershipcate
gory.Asecondtakeawayfromtheclusteranalysiswasthatservicetypesandrevenuemodelsarem
oretightlycoupledthanownershiptypes.Dependingontheservicetype,specificrevenuemodelsa
ppeartobepreferred:TVINTERNATIONALJOURNALONMEDIAMANAGEMENT189
everywhereisprovidedexclusivelywithauthenticatedcontent,whilecatch-
upTVispredominantlyadvertising-
funded.Aggregators,however,maybesubscription,advertisingorrentalbased.Third,regarding
devices,allrevenuemodelsandservicetypesrelyonPC/Mac,smartphones,andtabletsasthemain
stayoftheirdistributionplatforms.However,otherdeliveryplatformsareutilizedtooindifferent
proportionswithintheotherclusters.OTTvideoprovidersseemtohavesuccessfullynegotiatedto
secureplacementevenondevicesdedicatedtoanonaffiliatedorcompetingservice,suchasaset-
topbox,gamingconsole,orsmartphone.Thoughthisstudyaimedtoanalyzethecharacteristicsofb
usinessmodelscomprehensively,itsuffersfromseveraldrawbacksthatmayberemediedthroug
hfutureresearch.First,duetolimitationsofdata,thetypeofcontentcouldnotbestudied(user-
generatedversusprofessional,etc.).ItislikelythatthetypeofcontentprovidedbyanOTTservicew
illhaveabearingontherevenuemodelsused.Second,itisrelevanttoconsidertheprevalenceofdiff
erentbusinessmodelattributeswithinspecifictypesofmarkets(developedversusdeveloping,an
dthosewithadominantpublicservicebroadcasterversuspriva-
tizedsystems).Consideringsuchvariables,too,couldnotbeimplementedinthecurrentstudyduet
olimitationsofdata.Third,thedataarecross-
sectional,andthepapercannotaddressthetimefactorinthemodel.Accordingly,weareunabletod
etermineifthereisconvergenceinbusinessmodelsinOTTvideoservice.Theirrevenueandaffiliat
edservicescanchangeovertime,andfutureresearchmayinquire,astimegoesby,howtheirOTTbu
sinessmodelswillevolve.Finally,thestudyusedarelativelysimplecodingforownershipthatdidn
otaccountforthemixofservicesofferedwithinamediaortelecommunica-
tionsconglomerate.Futureresearchshouldaddresstheselimitations.Notes1.“Cord-
cutting”referstothediscontinuationoftraditionalcableservicebycustomerswithaccesstostrea
mingvideoservicesovertheInternet,while“cord-
shaving”referstoreductionofcableservicetolower-
pricedservicetiers(forexample,frompremiumchannelstobasicservice)bythosecustomers.2.“C
atch-
upTV”referstoTVservicethatcaptureslivebroadcasts,fromthepastcoupleofhourstoasmuchas3
0days,fromdozensofTVstations,andmakesthemavailableoverVOD(Abreuetal.,2017).3.“Aggre
gators”arenon-
traditionalornewvideoprogramproviders,thatprimarilyacquirevideocontentfromthirdpartie
sfordistributiontotheirusers.4.“TVeverywhere”isapayTVservicegenerallyofferedbyTVbroad
castersthatenablesauthenticatedsubscribers(passwordprotected)toaccessstreamingvideoco
ntentflexiblyonmultipleplatforms(InternetenabledTVsets,tablets,mobiledevices,etc.)oftheus
er’schoice.“Authentication”isaprocessofuniquelyidentifyingasubscriberaccount(whichmayh
avemultipleusers)usingpasswordprotection,encryption,orothertechnologies.190E.-A.PARK
5.SeeprofileofKaganResearchfounderandCableHallofFameinducteePaulKaganathttps://ww
w.cablecenter.org/2011-honorees/paul-f-
kagan.html.ReferencesABIResearch.(2014).Overthetop(OTT)andmultiscreenvideoservices.
Retrievedfromhttps://www.abiresearch.com/market-research/product/1016143-over-
the-top-ott-and-multiscreen-video-
ser/Abreu,J.,Nogueira,J.,Becker,V.,&Cardoso,B.(2017).Surveyofcatch-upTVandothertime-
shiftservices:Acomprehensiveanalysisandtaxonomyoflinearandnonlineartelevision.Telecom
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