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Journal of Media Economics

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Attributes of movie distribution channels and consumer choice

a b
Robert LaRose & David Atkin
a
Assistant professor in the Department of Telecommunications , Michigan State University , East Lansing, MI, 48824
b
Assistant professor in the Department of Communication , Cleveland State University , Cleveland, OH, 44115
Published online: 24 Feb 2009.

To cite this article: Robert LaRose & David Atkin (1991) Attributes of movie distribution channels and consumer choice, Journal of Media Economics, 4:1, 3-17, DOI: 10.1080/08997769109358200

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 Spring 1991 3

Attributes of Movie Distribution

Channels and Consumer Choice
Robert LaRose and David Atkin
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The past decade has witnessed unparalleled changes in the variety of distribu-
tion channels for movie entertainment. Broadcast television remains the pri-
mary vehicle for reaching mass audiences, now available to 92 million U.S.
homes (Broadcasting, 1990). However, 1988 saw three cable services surpass two
of the three networks in profitability, as revenue per viewer surpassed that of
broadcasting (Electronic Media, 1989). Cable is now found in 56 percent of
television households in the United States (Broadcasting, 1990), over half of which
receive at least one pay channel (Cable World, 1989). VCRs are also in two-thirds
(66 percent) of U.S. TV homes, and now surpass pay TV and theater outlets in
annual revenue (Multichannel Nezvs,19S9). Movie theaters present yet another
viewing option, garnering one billion ticket sales in the U.S. each year (Guback,
1987). Pay-per-viewis a new cable-based technology that permits users to order
a one-time viewing of a program—usually a sports event, film, or concert—and
to pay only for the program they receive. The number of homes equipped to
receive pay-per-view services now exceeds 10 million and thisfigureis predicted
to reach 53.6 million by 1998, generating revenues of over eight dollars per
subscriber (Cable World, 1989).

literature
In considering relationships among these media, Henke and Donohue (1989)
suggest that the introduction of a new electronic medium tends to cause a
reorganization of the way consumers view established media. Their own
research indicated a functional displacement of traditional TV viewing by VCR
owners. This conception stems from the work of Laswell (1949), who correctly
predicted that TV would compete with radio for audiences, programming, and
advertising revenue in the decades to follow. New media may displace existing
media at a societal level because "they are able to deliver services, content and
entertainment more efficiently, attractively, or conveniently" (Henke and
 4 Journal of Media Economics

Donohue, 1989,p.l8)., but ultimately these displacements are the result of

individual consumer choices to favor one distribution modality over another.
How do consumers make choices among these many distribution channels
in today's complex environment? Descriptive information is widely available
from national rating services about the substitution of one modality for
another.Thus we read about the "erosion" of network television shares as
viewers turn to pay TV, basic cable, or home video (Atkin and Litman, 1986).
These technologies helped reduce network shares from 92 percent of American
television households in 1977,to 68 percent in 1989 (ElectronicMedia, 1989). There
are reports about the "cannibalization" of pay-per-channel pay television by
pay-per-view—the substitution of pay-per-view movies for subscriptions to
full-time pay channels like Home Box Office, for example (Moozakis, 1986).
One industry study of the impact of pay-per-view (Marks, 1986) estimated that
the rate of cannibalization (or pay disconnect) attributable to pay-per-view is 2
percent
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Other data indicate that seemingly competitive media may in fact comple-
ment one other. VCR ownership, for example, is positively related to both cable
subscribership (Rothe, Harvey, and Michael, 1983; LaRose and Atkin, 1988a)
and pay cable subscription (Harvey and Rothe, 1985).
A few studies haveexamined the general phenomenon of substituting "old
media" by "new media" (Crotta and Newsom, 1983; Becker, Dunwoody, and
Rafaeli, 1983; Webster, 1983,1986). These studies documented media substitu-
tions and their consequences among users, but generally did not examine the
factors that led to the choice of one medium over the other. They also focused
on pairs of media (for example, substitution of cable news for broadcast news)
rather than the full range of distribution modalities.
A more comprehensive approach was utilized in Childers and Krugman's
(1987) analysis of factors leading to choices among three distribution modali-
ties: VCRs, pay cable, and pay-per-view. The authors suggested that these
delivery systems are likely to compete for consumer dollars, audience viewing
time, programming, and product offerings/Their results indicated that VCR
owners regarded pay-per-view as a more convenient service and easier to
operate, relative to VCR rental. VCRs were thought to offer more control;
experience with VCRs reinforced feelings about their value. Perceptions of pay-
per-view did not vary among those currently subscribing to cable.
Reagan (1987) examined the adoption of four "new media" technologies:
cable, VCRs, videotext, and personal computers. Media use and demographic
variables were related to cable subscribership and VCR usage. There was no
explicit treatment of the factors that might lead individuals to choose one
medium over another in a particular situation, i.e., searching for a story on a
videotext data base rather than tuning in a news channel on cable TV.
Many studies of the adoption of new electronic media focus on the
demographic characteristics of early adopters. Much of this work has ad-
 Spring 1991 5

dressed cable (Collins, Reagan, and Abel, 1983; Sparkes and Kang, 1986;LaRose
and Atkin, 1988b; Dutton, Rogers, and Jun, 1987) and pay cable (Ducey,
Krugman, and Eckrich, 1983; Webster, 1983), finding sets of demographic
characteristics that predict new media adoption. However, the significant
predictors vary from study to study, depending on media environment vari-
ables (Krugman, 1985; LaRose and Atkin, 1988a) — demographic differences
tend to fade over time (Sparkes and Kang, 1986). Only one of these studies
treated attitudes towards a competing medium—namely, broadcast television
(Ducey, Krugman, and Eckrich, 1983).
Of course, distribution channel choice is confounded by variations in
media content. For example, wrestling, one of the staples of pay-per-view, will
seldom be found in a movie theater. Sports and news are commonly seen in
broadcast television, but are seldom seen in other distribution channels.
Movies may be the key to understanding choice among entertainment
distribution modalities, because they are common to all distribution channels
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(Guback, 1987). They remain the staple of movie theaters and account for 15
percent to 29 percent of broadcast television viewing (Litman, 1979;Wackshlag
and Adams, 1985). Movies were also the engine that generated cable's growth
in the early 1980s, and they continue to be the primary reason for purchasing
pay cable (Krugman and Eckrich, 1982;Becker, Dunwoody, and Rafaelli, 1983)
and VCRs (Harvey and Rothe, 1985). It is estimated that 40 percent of pay-per-
view purchases involve movies as well (Marks, 1986). Thus, movies represent
the most widely utilized format through which to examine choices among
distribution modalities while "holding constant" the differing content of the
media.
Factors affecting the consumption of theatrical movies have been explored
from a uses and gratifications perspective (Palmgreen, et al., 1987). It wasfound
that college students attend movie theaters for a variety of social and informa-
tion-seeking reasons as well as for entertainment. However, no attempt was
made to relate these motivations to movie attendance behavior or to the
consumption of movies in other distribution channels.
Cohen, Levy, and Golden (1988), working from a uses and gratifications
perspective, charted the functional similarity of VCRs to broadcast television,
cinema, and four other mass media among a group of Israeli grade school
children. They found that VCRs and cinema relate to similar needs, which are
somewhat distinct from those gratified by broadcast television. Within the uses
and gratifications perspective, this suggests that individual consumption pat-
terns for VCRs and cinema should be complementary; therefore, exposure to
one might compete with exposure to the other. Likewise, if broadcast television
gratifies a differing set of needs, then television viewership should not compete
with usage of the other two media. However, their study did not examine
exposure as a variable.
Recently, attempts have been made to integrate the uses and gratifications
 6 Journal of Media Economics

approach with expectancy-value theory, in an effort to predict exposure to

telecommunications media (Galloway and Meek, 1981 ;Palmgreenand Rayburn,
1982; Babrow and Swanson, 1988; Babrow, 1989). Expectancy-value theory
(Fishbein and Ajzen, 1975), now known as the theory of reasoned action (Ajzen
and Fishbein, 1980), posits that behavioral intentions are determined by atti-
tudes toward the behavior. They are also conditioned by the expected conse-
quences of the behavior and the evaluations of those outcomes —and by
subjective norms—predicated on beliefs about whether social referents wish
the behavior to be performed and the motivation to comply with each referent.
Behavioral intentions are used to operationally define behavior, and a close
correspondence between the two is expected if care is taken to measure both
behavior and intentions in a consistent manner.
Within the theory of reasoned action, attitudes toward a behavior are
calculated according to the formula which follows.
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where b is the strength of the ith salient belief about the outcome of the behavior;
e is the evaluation of that belief, summed over all of the n salient beliefs about
the consequences of the behavior (Ajzen and Fishbein, 1980).
When combined with a parallel measure of perceived social norms, this
model has been very successful in predicting a wide variety of human behavior,
including behavior influenced by the media. Curiously, communications re-
searchers who have tried to integrate this theory with the uses and gratifications
approach have concluded that expectancy-value attitudes are not good be-
havioral predictors. They conclude that general attitudes toward media content,
which they find to be related to the gratifications sought from a medium, are
superior predictors of media exposure. One explanation offered for this puz-
zling non-result is that other media may provide functional alternatives for any
individual medium (Palmgreen and Rayburn, 1982). Another explanation is
that exposure to familiar media content—such as television soap operas—
produces well-known and stable consequences so that a general attitudinal
response to the content may influence behavior better than an expectancy-value
orientation (Babrow, 1989).
These results still leave open the possibility that an expectancy-value
formulation that explicitly treats the problem of competing, functionally
equivalent media channels and that covers a domain of behavior where the
consequences of behavior are not well-known and stable, might yet produce a
successful explanation of media behavior. When the behavior in question
represents a choice between two alternatives—such as candidates in a presi-
dential campaign—a differential attitude may be computed that provides a
 Spring 1991 7

superior prediction of a differential intention to select one choice over another.

This model may be represented as follows:

n
I

In this case, a differential attitude is calculated by taking the difference

between the corresponding belief strengths in the outcomes of the two alterna-
tive behaviors (a and b). The differential attitude indeed improves the pre-
diction of choice behavior (Ajzen and Fishbein, 1980).
However, this approach becomes problematic when more than two alter-
natives are involved. How are reasoned actions formulated by judges under
such circumstances? Even with only two attributes, the task of weighing five
alternatives becomes formidable, requiring the judge to hold in mind 20
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different comparisons, then weigh them against evaluations of the beliefs. As

a rule of thumb, somewhere between five and nine attributes (Ajzen and
Fishbein, 1980, p.64) may determine an attitude, requiring between 50 and 70
separate simultaneous judgements. Clearly, some means of simplifying the
judgmental task must be invoked. The "functional displacement" explanation
for media substitution phenomena suggests a possible approach: that attitudes
toward functionally similar media alternatives may influence exposure. That
is, if a person believes that going to a theater to watch a movie is fun and that
staying home to watch a movie on commercial television is also fun, then the
attitude towards theatrical movies may also strengthen the intentions to use the
opposing alternatives. The attitudes towards the other alternatives may be
weighed in the model, as follows:
m n
I I

where there are m alternative choices. Using this model we have hypothesized:

HI: Expectancy-value attitudes toward pay-per-view mov-

ies will predict pay-per-view consumption behavior.

H2: Expectancy-value attitudes toward competing movie

distribution modalities will predict pay-per-view consump-
tion behavior

To maintain continuity with previous studies of new electronic media,

demographic variables were also included in the model. Because pay-per-view
is still a new technology in these areas studied, it was hypothesized that
 8 Journal of Media Economics

demographic predictors would parallel those found in the earliest studies of

cable and pay cable, that is:

H3: Pay-per-view users will be better educated, younger,

and have higher household incomes than nonusers.

Research Methods
The data were collected over a one-week period in three Midwestern commu-
nities during Fall 1987. In two of the communities, pay-per-view television was
available. In one of these communities orders were placed by making calls to
the cable system. The origin of the call was automatically recorded through
automatic number identification technology and the showing of the movie was
authorized for the corresponding location. In the other pay-per-view system,
orders were placed via auxiliary converter boxes (or "sidecars") attached to the
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television set. In the third community, introduction of pay-per-view was

planned for the following year.
Random digit dialing phone surveys were conducted in each community.
Random numbers were generated from listed numbers contained in local
telephone directories. Only cable subscribers were included in the sample. A
selection grid (Bryant, 1975) was used to select respondents from among adults
aged 18 or older in each household. The total number of respondents from all
three communities was 450.
Where pay-per-view was available, the dependent variable was the number
of pay-per-view movies that had been seen in the home. Those who said they
had never watched a movie in their home in this way scored zero. Intentions
to adopt pay-per-view were measured on an interest scale ranging from "very
interested" (scored 5) to "not at all interested" (scored 1), with neutral responses
scored at the midpoint of the scale. This item was evaluated for all respondents
regardless of whether they had ever used pay-per-view or had it available in
their area.
Several household and respondent characteristics were included. Sex of
respondent (1 if female, 0 if male), employment status (1 if employed, 0 if not),
and marital status (1 if married, Oifnot) were all dummy coded. Theageofthe
respondents was recorded in years (mean = 35.0). An ordinal education scale
was used with five levels (1 if less than high school, 2 if high school diploma,
3 if attended college without completing, 4 if college graduate, 5 if graduate
training). Household income was measured on a seven-level ordinal scale (1 if
$7500 or less, 2 if $7501 to $10,000,3 if $10,001 to $15,000,4 if $15,001 to $25,000,
5 if $25,001 to $35,000,6 if $35,001 to $50,000,7 if over $50,000). The number of
adults living in the household was also recorded.
Attributes of movie viewing across different media were also measured for
 Spring 1991 9

theater, VCR, pay channel, and pay-per-view viewing. For each modality,
respondents were asked about the degree to which movie viewing meets the
following expectations:
(a) is fun, (b) is convenient, (c) gives good value for your money, (d) is
something you can do on the spur of the moment, (e) gives you a good selection
of movies to see, (e) is something you enjoy doing with your family and friends,
(g) lets you watch movies commercial free, (h) gives you a chance to go out, (i)
lets you see good quality movies.
Each of these beliefs was measured on a scale ranging from "strongly
agree" (scored 5) to "strongly disagree' (scored 1). Respondents were also
asked to evaluate how important each of these attributes was when deciding
among alternatives for movie entertainment on a scale ranging from "very
important" (scored 5) to "very unimportant" (scored 1). An expectancy-value
attitude measure was computed for each of the five modalities by first multiply-
ing each attribute by its importance rating and then summing these products
across all nine attributes for each modality. Confirmatory factor analyses
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(Hunter and Hamilton, 1986) were then conducted on the five sets of attitude
scales, and alpha coefficients were computed. Each of the five expectancy-
value scales had a satisfactory degree of internal consistency with Cronbach
alphas ranging between .63 and .74
Two separate stepwise multiple regression analyses were performed, one
with the behavioral measure of the number of pay-per-view movies ordered
and then other with intentions to use pay-per-view as the dependent variable.
The remaining variables were allowed to enter the equation as independent
variables. No a priori ordering was placed on the predictor variables. A
minimum F ratio of 1.0 was set for inclusion in the equation. Regression
analyses were performed using the PSTAT statistical package (PSTAT, 1989). A
total of 203 cases were included in the first analysis and 450 in the second.
Where missing data occurred for one of the independent variables, the popu-
lation mean was substituted for the missing observation. Prior to the initiation
of any regression runs, Pearson-product moment correlations were computed
to test for multicollinearity among the predictors. The highest intracorrelation
was that between VCR and pay TV attitudes (Pearson's r = .69);aside from that,
multicollinearity was not deemed a concern, as none of the other intracorrela-
tions exceeded 50.

Results
Table 1 summarizes beliefs about pay-per-view and the perceived importance
of each attribute. Those who scored above the midpoint on the respective scales
are reflected in the percentages shown in the table below.
The highest level of agreement was found for the commercial-free and
convenience aspects of viewing, with more than 80 percent of the respondents
 10 Journal of Media Economics

Table 1
Attribute of Pay-Per-View

Attribute % Agree % Important

Fun 7.3 88.2

Convenient 82.0 91.1
Value 51.9 93.1
Spur of the moment 635 775
Selection of movies 475 965
Do with family, friends 77.8 91.4
Commercial free 835 82.0
Chance to go out 85 52.0
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Quality movies 675 95.8

attributing these two characteristics to pay-per-view. Over 75 percent of the

respondents also perceived pay-per-view to be fun or something to do with
family or friends. Over half agreed that pay-per-view provides quality movies,
was something that could be done on the spur of the moment, and offered good
value. Sightly less than half perceived it as offering a good selection of movies.
Providing a chance to go out was the least commonly attributed belief about
pay-per-view.
With respect to the importance that respondents attached to each of these
attributes when considering how to obtain movie entertainment, movie selec-
tion, quality, value, convenience, and social activity were the most important
attributes. But, while commercial-free fare was commonly identified as a pay-
per-view attribute, viewers did not place it among the more important attrib-
utes. Commercial-free fare ranked only seventh on the attribute importance
list, followed by "gives you a chance to go out/'
The first regression analysis involved two communities with an operating
pay-per-view system. With the number of pay-per-view movies ordered as the
dependent variably a significant prediction equation was obtained (F 8,195 p <
.001, adjusted R2 = 2396). As hypothesized, the expectancy-value measure of
attitudes toward pay-per-view was a significant predictor (b = .46, F1,195= 24.7,
p < .01). The corresponding expectancy-value attitude toward obtaining
movies from pay television (b = -.20, F1,195 = 42, p < .05). was a significant
negative predictor. Household income was the only other predictor of pay-per-
view usage (b = .14, F 1,195 = p < .05), which was the hypothesized relationship.
Expectancy-value attitudes toward watching movies on commercial television
were negatively related to pay-per-view usage, while attitudes towards movie
 Spring 1991 11

theater consumption were negatively related, but neither of these results was
significant. Attitudes towards home video consumption did not meet the
minimum inclusion criterion.

Table 2
regression or Atntuainai ana uemogra pmc vanaoie5
on Pay-Per-View Usage
Change Final F Pearsoi
Variable inR 2 beta to Delete r

PPV Attitude .110 .4656 24.721** 3317

Household Income .015 .1391 4.079* .0840
Move Theater Attitude .016 -.1285 3321 .0078
Sex of Respondent .014 -.1175 3.104 -.1059
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Pay TV Attitude .012 -.1960 4.253* .1580

Education .009 -.1291 3.314 -.1340
Employment Status .011 .1112 2562 .1407
Commercial TV Attitude .008 .1009 1.929 .1564
F * 195 - 5.917, p < .001. Adjusted R* » .1623
•p<.05

The relationship between education and pay-per-view usage was in the

opposite direction of the one hypothesized, although this was not a significant
effect after taking into account the effects of the other independent variables.
Age, household size, and marital status were unrelated to usage. Males and
unemployed persons tend to use pay-per-view more than females or employed
persons, although these were not statistically significant predictors i n the final
regression equation.
A significant prediction equation was also obtained for intentions to use
pay-per-view (F 6,443 = 24.856, p<.001, adjusted R2 = 2396). Once again the
expectancy value measure of attitudes toward pay-per-view was the first
predictor entered into the equation (b = 50, F 1,433 = 785, p<.01). Attitudes
toward movie theater attendance (b =.13, F 1,443 = 85, p<.01) and attitudes to-
ward obtaining movies from commercial television (b = -.10, F 1,443 = 4.6, p<.05)
were both significant negative predictors. Attitudes toward pay cable movie
consumption were positively related to intentions to use pay-per-view, but this
result failed to reach statistical significance. Expectancy-value attitudes toward
the use of home video (that is, VCR) did not enter the equation.
 12 Journal of Media Economics

Table 3
Regression of Attitudinal and Demographic Variables
on Pay-Per-View Use Intentions

Change Final F Pearson

Variable inR* beta to Delete r

PPV Attitude 210 .4994 78556" .4586

Movie Theater Attitude .011 -.1449 8554** .1348
Age of Respondent .013 -.1342 8.952" -.1668
Household Income .007 .0824 3.626 -.0028
Commercial TV Attitude .005 -.1013 4595* .0789
Pay Cable Attitude .004 .0849 2.224 3078
F k 443 - 2458* p < .001. Adjusted R*-.2396i
•p<.05
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Age had the hypothesized relationship (b » -.14, F 1,443 » 8.9, p<01), with
younger respondents indicating stronger intentions to consume pay-per-view
movies than older respondents. The relationship with household income was
also in the hypothesized direction, although not significant. Education, marital
status, sex, and household size did not meet the minimum inclusion criterion.

Discussion
The hypothesis that expectancy-value attitudes would predict behavior was
supported both for a measure of behavioral intentions and for a direct measure
of behavior. Bothrelationshipswere moderately strong, leading us to conclude
that expectancy-value attitudes are indeed powerful predictors of media be-
havior, just as the theory of reasoned action would project. It appears that the
dynamic range of choices available in the home video environment calls for
reasoned decisions, in the absence of stable generalized attitudes towards the
various distribution channels in question. In contrast, previous studies that
found that expectancy-value attitudes did not predict behavioral intentions
(Babrow, 1989; Palmgreen and Rayburn, 1982) may have focused on media
behaviors whose consequences are predictable and that are not subjected to
well-reasoned decisions. It is also possible that the previous null findings
concerning expectancy-value attitudes were the result of the introduction of
extraneous concepts horn the uses and gratifications paradigm (for example
gratifications sought) or from earlier conceptualizations of the theory of rea-
soned action (for example, attitudes toward an object) that have subsequently
been discarded (Ajzen and Fishbein, 1980). Hopefully, this issue will be
revisited in future research.
 Spring 1991 13

Some evidence was found to support a reformulated expectancy-value

model suitable for n-way choice situations. Attitudes toward both comple-
mentary and competing distribution modalities were found to contribute to the
prediction of the usage of pay-per-view. The directionality of these relation-
ships changed in two instances depending upon whether actual pay-per-view
ordering behavior or intentions to use pay-per-view was the dependent vari-
able. Because the latter analyses included a sizeable number of respondents
living in an area where pay-per-view was not yet available, a likely explanation
is that experience with a new distribution modality may change beliefs about
its most salient attributes, causing a shift in the pattern of attitudes. In this case,
it appears that experience with pay-per-view may cause users to distinguish it
more from conventional pay television programming, altering the overall
pattern of relationships among the distribution modalities. The failure of
expectancy-value attitudes toward VCR movies to predict pay-per-view use is
probably attributable to multicollinearity between VCR and pay TV attitudes,
noted earlier.
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Other information processing methods that consumers may use to make

reasoned choices between multiple media options should also be explored. The
confirmatory factor analyses used to construct the expectancy-value attitude
scales contained a substantial number of violations in scale identities. That is,
there were many instances in which items assigned to one of the expectancy-
value attitude scales on theoretical grounds (for example, the product of the
attributed belief about the good selection of movies available on pay TV and of
the overall importanceof good selection in making movie distribution modality
choices) had a higher loading on one of the other scales (for example, attitudes
toward pay-per-view) than on its own (that is, attitudes toward pay TV).
Violations of this sort occurred about 15 percent of the time, suggesting that an
alternate underlying structure may exist that would provide a better explana-
tion of the relationships between the expectancy-value components than the
hypothesized one. One possibility that could be explored in future research is
that consumers organize their decisions within attributes (perhaps by ranking
modalities within each of several different attributes) instead of across attrib-
utes within modalities. Another approach would be to narrow down the
attributes to a smaller set until the total number of intermodality comparisons
becomes more manageable.
It seems attitudinal models based on expectancy-value theory hold some
promise for understanding choices between distribution modalities in a com-
plex media environment. In fact, the amount of variance explained was consid-
erably greater than that explained by similar models when used to predict other
media behaviors (typically less than 10 percent; see Swanson, 1987). The
amount of variance explained was still considerably less than that observed in
other behavioral domains, where R_squares of .6 or more are common (Ajzen
and Fishbein, 1980).
 14 Journal of Media Economics

Several improvements in the present study might improve the power of

behavioral predictions. One possibility would be to sharpen the correspon-
dence between the attitude measure and the behavioral criterion, such as by
focusing on the choice of modality or even a particular movie to be viewed in
a specific time frame. The present study also focused exclusively on the
attitudinal components of media choice behavior. Perceived sodal norms—
perceptions about the wishes of significant others with respect to the behavior
in question, weighed by the motivation to comply with them—might be
significant as well. This might be especially true in comparing pay-per-view
with theatrical movies, where an individual consumer might not value the
opportunity afforded to leave the home, but a spouse or other loved one might
apply pressure to "go out on the town/' The current research also deviated from
the commonly accepted operational definition of belief evaluations, asking
respondents how important each attribute was in making modality choices
rather than obtaining evaluations of each on a "good-bad" scale. Closer
conformance to the recommended practice might yield better results. Finally,
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the attribute set included in the study was based on attributes listed in other
studies and on concepts elicited from a very small group of graduate students
and colleagues working with investigators. An elicitation of the perceived
consequences of movie choice behavior involving a larger sample more repre-
sentative of the general adult population to which the questionnaire was
administered would probably yield a better correspondence between expec-
tancy-value attitudes and behavior.
In comparison with attitudinal variables, demographics explained a rela-
tively small degree of variance. Hypothesized relationships between age,
income, and education and pay-per-view adoption were not consistently
significant between the two sets of analyses. The relatively modest role for
demographic variables may perhaps indicate that they are proxies for charac-
teristic patterns of perception of the various distribution modalities that char-
acterize certain demographic groups by virtue of common reinforcement
histories. For example, a moderate negative correlation was found between
both age and education and the "good selection" component of the attitudinal
model. That is, older and more highly educated people tended not to be much
influenced by the selection of pay-per-view movies available to them. This
poses an important alternative to the diffusion of innovations position, which
has focused on the development of demographic profiles of early adopters
(Dutton, Rogers and Jun, 1987).
Thus, the present research illustrates the potential value of extending the
expectancy value approach to the study of the adoption of new electronic
distribution modalities through explicit consideration of competing media
alternatives. The perceived attributes of new media like pay-per-view and
those of competing modalities can be used to predict the adoption of new home
entertainment technologies.
 Spring 1991 15

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