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                                                                           Potential HDTV Adopters
 
 
 
Running head: POTENTIAL HDTV ADOPTERS
 
 
 
 
 
 
 
 
A Profile of Potential High-Definition Television Adopters in the United States
 
 
 
 
 
 
Michel Dupagne
School of Communication
University of Miami
P.O. Box 248127
Coral Gables, FL 33124-2030
Phone: (305) 284-3500
Fax: (305) 284-3648
E-mail: <a href="/cgi-bin/wa?LOGON=A3%3Dind9709C%26L%3DAEJMC%26E%3D7BIT%26P%3D2575198%26B%3D--%26T%3DTEXT%252FPLAIN%3B%2520charset%3DUS-ASCII" >[log in to unmask]</a>
 
 
 
 
 
 
 
Paper presented to the Media Management and Economics Division
 
at the annual convention of the Association for Education in Journalism and
 
Mass Communication, Chicago, IL
 
July 1997
 
 
Abstract
A telephone survey was conducted with 193 adults in a major U.S. metropolitan
area to assess consumer predispositions toward high-definition television (HDTV)
and profile potential adopters of this technology according to demographics,
mass media use, ownership of home entertainment products, and importance of
television attributes.  Based on diffusion theory and communication technology
adoption studies, this study hypothesized that male, younger, better educated,
and higher-income respondents who are more frequently exposed to mass media
channels and value television features more highly would be more aware of HDTV,
express a greater interest in HDTV, and be more likely to purchase an HDTV set.
Correlational analyses indicated that HDTV awareness was positively related to
education, income, gender (male), newspaper use, ownership of home entertainment
products, and picture sharpness; HDTV interest was negatively related to age and
positively related to income, gender (male), moviegoing, ownership of home
entertainment products, and picture sharpness; and HDTV purchase intention was
positively related to screen size.  Hierarchical regression analyses were also
run to determine the relative importance of demographics, mass media use,
ownership of home entertainment products, and television attributes in
predicting HDTV awareness, interest, and purchase intention.
 
 
 
A Profile of Potential High-Definition Television Adopters in the United States
        On April 3, 1997, after 11 long, and often contentious, years (see Brinkley,
1997), the Federal Communications Commission (FCC) concluded its proceedings on
digital television (DTV).  First, on December 24, 1996, the Commission adopted a
standard for terrestrial DTV that will enable broadcasters to transmit programs
in high-definition television (HDTV) or standard-definition television (SDTV)
format (Federal Communications Commission [FCC], 1996).  Digital HDTV will offer
significantly better pictures than SDTV, which is essentially a digital version
of the existing NTSC television system, because it will use the entire 6 Mhz
bandwidth to deliver the signal.  It will provide three main technical
improvements over NTSC: (1) higher-picture resolution (1080 active lines versus
NTSC's 525 scanning lines) approaching 35 mm picture quality; (2) a wider aspect
ratio (16:9 versus NTSC's 4:3) approximating the movie theater experience; and
(3) distortion-free multichannel audio (digital 5.1 channel system versus NTSC's
analog stereophony) comparable to the sound quality of a compact disc (see Seel,
1996).
        Then on April 3, 1997, the Commission finalized the two remaining advanced
television (ATV) rulemakings--general service rules and channel assignments.  In
the Fifth Report and Order, the Commission completely reshuffled the
NTSC-to-HDTV transition schedule it had adopted in September 1992.  It required
that (1) the affiliates of ABC, CBS, Fox, and NBC in the top 10 markets (30% of
TV households) build their DTV facilities by May 1999 and those in the top 30
markets (53% of TV households) by November 1999; (2) all remaining commercial
stations construct their DTV facilities by May 2002; (3) all noncommercial
stations construct their DTV facilities by May 2003; and (4) DTV licensees
simulcast 50% of their analog video programming on the DTV channel by April
2003, 75% by April 2004, and 100% by April 2005. It also shortened the duration
of the transition period from 15 to 10 years by setting the target date for the
phase-out of NTSC service in 2006.  More surprisingly, and contrary to previous
actions, the FCC declined to mandate broadcasters to air a minimum amount of
HDTV programming and, instead, left this decision to the discretion of the
licensees (FCC, 1997a).
        In the Sixth Report and Order, the FCC adopted a Table of Allotments for
digital television based on use of channels 2-51.  Responding to comments, it
added channels 2-6 to channels 7-51, which was originally proposed as the DTV
core spectrum in the Sixth Further Notice of Proposed Rule Making of July 1996,
to determine DTV channel assignments.  Upon acceptability of the lower VHF
channels 2-6 for DTV use, the Commission might ultimately shift the core
spectrum from channels 7-51 to channels 2-46.  According to the Table, over 93%
of broadcasters would receive a DTV allotment that reaches at least 95% of their
existing NTSC service area (FCC, 1997b).
        With the completion of these proceedings, the HDTV debate is now shifting in
earnest from technology standardization and spectrum allocation to economic
considerations, primarily programming and station conversion.  Since the early
1990s, some U.S. broadcasters have expressed concerns, if not outright anger, at
the cost of converting their facilities from NTSC to HDTV, especially within the
FCC-prescribed transition window.   Vocal comments, such as "HDTV will bankrupt
stations" (McConnell, 1995, p.  103), were not uncommon a few years ago, though
now many broadcasters have resigned themselves to accept the inevitability of
HDTV by political and competitive necessity.  On February 2, 1997, NBC, in
cooperation with its owned-and-operated WRC-TV, became the first U.S. broadcast
television network to transmit live a program (Meet the Press) in HDTV format.
As of June 1997, seven stations were broadcasting experimental HDTV programs:
WRAL-HD, Raleigh, NC; WRC-HD, Washington, DC; KOMO-HD, Seattle, WA; and KCTS-HD,
Seattle, WA; KOPB-HD, Portland, OR; WETA-HD, Washington, DC; WCBS-HD, New York,
NY.  Conversion costs will depend heavily on station size and are difficult to
estimate, but are likely to range from $1 million or less for pass-through
equipment (i.e., to retransmit the network signal) to $10 million or more for
complete local production facilities (McConnell, 1997).
        Surprisingly, amidst all these preparations, one key factor remains overlooked:
the consumer (or demand) side.  First HDTV sets are slated to hit the stores by
Christmas 1998 at a price ranging from $5,000 to $11,000 (Dickson, 1997;
"Zenith's First Digital Sets," 1997). Broadcasters and consumer electronics
manufacturers have high expectations, but are American consumers ready for HDTV?
How will they react to it?  How aware of and interested are they in HDTV
receivers?  How will price influence the adoption of HDTV receivers and
associated hardware?  Early U.S. empirical studies, conducted in the late 1980s
and reviewed below, reveal lukewarm consumer reactions to HDTV instead of
unreserved responses that one would normally expect from a product that has been
heralded as revolutionary and unique.
        The purpose of this paper is to revisit the consumer issue by assessing HDTV
awareness, interest, and purchase intention in a major U.S. metropolitan area
and identifying the characteristics of potential HDTV adopters based on
demographics, mass media use, ownership of home entertainment products, and the
importance of television attributes.  Because previous studies were undertaken
in the late 1980s, and now that HDTV is just around the corner, it seems
particularly timely to reassess U.S. consumers' predispositions toward the
technology.  This study also offers theoretical insights, because, unlike past
research, it is grounded in the diffusion of innovations literature.  We would
expect potential HDTV adopters to exhibit characteristics similar to those of
earlier product adopters.  Furthermore, it advances our understanding of
diffusion theory by investigating the relative importance of demographics, mass
media use, ownership of home entertainment products, and television attributes
in explaining pre-adoption of a communication technology.  Before detailing the
hypotheses and the methodology, the paper will review three early HDTV consumer
studies and summarize the main elements of diffusion theory.
Early HDTV Consumer Studies in the United States
        Overall early consumer studies point to somewhat lukewarm predispositions
toward HDTV and its technical improvements.  John Abel, former Executive Vice
President of the National Association of Broadcasters, went so far as declaring
to a group of broadcasters that "You don't want HDTV.  And consumers say they
don't want it, either" (Andrews & Brinkley, 1995, p.  6).  But in fact, consumer
reactions are far from being negative except in the Home Box Office study.
        Neuman (1988) found that, when exposed to NTSC and HDTV material side by side
(dual stimulus test), 62% of the participants preferred HDTV.  With the
exception of age, viewers did not differ on the basis of demographics,
television use, or evaluations of picture characteristics (color, screen shape,
picture sharpness, picture brightness, sense of depth, and motion quality).  The
author also reported that only 6% of the subjects assigned to the HDTV condition
(single stimulus test) were willing to pay $500 on top of the price of their
current television set for an HDTV receiver.
        Another study, conducted in Seattle, Washington, suggests more enthusiastic
viewer responses to HDTV (Lupker, Allen, & Hearty, 1988).  In side-by-side
viewing, in which programming material was displayed alternatively, 73% of the
respondents reported that HDTV was better than NTSC in overall picture quality.
Respondents also preferred the HDTV set in terms of sense of depth (78%), screen
shape (74%), picture sharpness (72%), color quality (69%), picture brightness
(60%), and motion quality (57%).  Of the respondents, only 14% and 18% indicated
that they definitely or probably would buy an HDTV set like the one they were
shown for $2,500 and $1,500, respectively.
        Home Box Office (1988) conducted the third study in Danbury, Connecticut, and
found that only 39% of the respondents felt that HDTV was better than NTSC in
overall picture quality.  Respondents' preference for HDTV was also low in
regard to screen shape (46%), color quality (43%), sense of depth (43%), picture
sharpness (41%), picture brightness (41%), and motion quality (36%).  But 17%
and 23% of the respondents reported they definitely or probably would buy an
HDTV set like the one they were shown within the next two years if available at
$2,500 and $1,500, respectively.
Diffusion Theory
        Rogers (1995) defines "diffusion" as "the process by which an innovation is
communicated through certain channels over time among the members of a social
system [emphases added]" (p.  5).
        The first element of this definition presupposes the existence of an
innovation, which refers to an idea that is perceived as new by an individual.
People evaluate an innovation in terms of six main attributes: relative
advantage, compatibility, complexity, trialability, observability, and perceived
risk.  The sixth construct is not part of Rogers' set of perceived innovation
attributes and was originally conceptualized by Raymond Bauer (see Ostlund,
1974).  Rogers (1995) reports that his five attributes explain 49-87% of the
variance in rate of adoption.  Consistent with previous research, Holak and
Lehmann (1990) found that compatibility (.558) and relative advantage (.455)
were the perceived innovation characteristics most highly correlated with
purchase intention of entertainment items (e.g., consumer electronics products),
followed by perceived risk (-.160), communicability (i.e., observability)
(.158), complexity
(-.046), and divisibility (i.e., trialability) (.037).  So the two most relevant
perceived innovation attributes for communication technologies appear to be
compatibility, the degree of congruence with potential adopters' values and
needs, and relative advantage, the degree to which an innovative product is
perceived to be superior to previous ones (see also Holak, 1988; Lin, 1996).
        Communication channels, the second element of diffusion, involves both
interpersonal (e.g., word of mouth) and mass media (e.g., television) channels.
While mass media channels offer the most effective means to create awareness and
knowledge, that is, to inform the widest possible audience of individuals about
the existence of an innovation, interpersonal channels are best to persuade
potential adopters about the merits of an innovation.
        The third element is time, which is an important dimension in determining the
innovation-decision process and measuring adopters' degree of innovativeness.
The innovation-decision process is "the process through which an individual (or
other decision-making unit) passes from first knowledge of an innovation to
forming an attitude toward the innovation, to a decision to adopt or reject, to
implementation and use of the new idea, and to confirmation of this decision"
(p. 20).  Therefore, it contains five main steps: knowledge, persuasion,
decision, implementation, and confirmation.
        At the knowledge stage, the individual becomes aware of and gains basic
information about the innovation (e.g., how does it work).  Socioeconomic
qualities, personality traits, and communication behavior can affect the degree
of awareness and knowledge of an innovation.
Specifically, earlier knowers are more likely to have more formal education,
higher socioeconomic status, and greater exposure to mass media channels than
later kwowers (Rogers, 1995).  At the persuasion stage, individuals form
favorable or unfavorable attitudes toward the innovation.  They seek further
information about the new idea and evaluate its pros and cons, relying
particularly on interpersonal communication.  In so doing, potential adopters
develop a general perceptual map of the innovation primarily based on its
relative advantage, compatibility, and complexity.  At the decision stage, the
individual "engages in activities that lead to a choice to adopt or reject an
innovation" (p.  171).  Individuals express their intention to adopt or reject
the innovation (e.g., purchase intention and willingness to pay).  On repeated
occasions, marketing researchers have used purchase intention as a surrogate
measure of innovation adoption, because they have found that purchase intention
correlates with product trial (see Holak, 1988).
        The other two stages, implementation and confirmation, do not apply to this
study, because HDTV sets were not yet available on the consumer market at the
time of the survey.  So this research investigates pre-adoption or potential
adoption instead of actual adoption of HDTV.  Rogers (1995) defines "adoption"
as "a decision to make full use of an innovation as the best course of action
available" (p.  171).  He classified adopters into five groups according to
their level of innovativeness: innovators (2.5% of adopters), early adopters
(13.5%), early majority (34%), late majority (34%), and laggards (16%).
Innovativeness indicates how soon an individual decides to adopt a new idea.
Earlier adopters (innovators, early adopters, early majority) differ from later
adopters (late majority, laggards) in socioeconomic status, personality values,
and communication behavior.  Specifically, they are better educated, have higher
income, and use mass media channels more frequently than later adopters (Rogers,
1995).
        The fourth and final element of diffusion is the social system, which is "a set
of interrelated units that are engaged in joint problem-solving to accomplish a
common goal" (p.  23).  Members of a social system can be individuals, groups,
or organizations.
Hypotheses
        Four sets of hypotheses were formulated based on diffusion theory and adoption
studies for eight communication technologies (cable television, the video
cassette recorder [VCR], the home satellite dish [TVRO], the personal computer
[PC], videotex, audiotext, direct broadcast satellite [DBS], and the fax machine
(see Table 1).  A research question regarding the relative importance of these
sets of variables in predicting HDTV awareness, interest, and purchase intention
was also posed.  The first four hypotheses relate demographic variables to the
three dependent variables.
        H1.1: The younger respondents are, the more they will be aware of HDTV, express
an interest            in HDTV, and be likely to purchase an HDTV set.
        H1.2: The better educated respondents are, the more they will be aware of HDTV,
express an                     interest in HDTV, and be likely to purchase an HDTV
set.
        H1.3: The higher the income level of respondents is, the more they will be
aware of HDTV,                 express an interest in HDTV, and be likely to purchase
an HDTV set.
        H1.4: Male respondents will be as likely as female respondents to be aware of
HDTV, express an               interest in HDTV, and be likely to purchase an HDTV
set.
Rogers (1995) hypothesizes that "Earlier adopters are not different from later
adopters in age" (p. 269), although he is quick to point out the conflicting
empirical evidence about the relationship between age and innovativeness.  In a
majority of communication technology studies (Table 1; see also Lupker et al.,
1988), age was found to be negatively related to adoption.  Therefore,
Hypothesis 1.1 posits a negative relationship between age and the three
dependent variables.  Consistent with diffusion theory and most adoption
studies, we expected a positive relationship between level of education and
income and HDTV awareness, interest, and purchase intention.  Diffusion theory
is silent on the relationship between gender and innovativeness (or adoption),
but most empirical studies suggest that gender is unrelated to communication
technology adoption.  Consequently, it was hypothesized that there would no
difference between males and females in HDTV awareness, interest, and purchase
intention.
        The next block of four hypotheses deals with mass media exposure:
        H2.1: The more television respondents watch, the more they will be aware of
HDTV, express an               interest in HDTV, and be likely to purchase an HDTV
set.
        H2.2: The more radio respondents listen to, the more they will be aware of
HDTV, express an               interest in HDTV, and be likely to purchase an HDTV
set.
        H2.3: The more respondents read newspapers, the more they will be aware of
HDTV, express an               interest in HDTV, and be likely to purchase an HDTV
set.
        H2.4: The more respondents see movies in theaters, the more they will be aware
of HDTV,                       express an interest in HDTV, and be likely to purchase an
HDTV set.
Diffusion theory holds that earlier adopters will use mass media more frequently
than later adopters (Rogers 1995), but that generalization is rarely borne out
by empirical evidence for communication technology adopters (see Table 1).
Amount of television viewing is the only significant media use predictor common
to several adoption studies.  More often than not, mass media use is unrelated
to adoption of any of these eight communication technologies.  Nevertheless,
being theoretically grounded, this study hypothesizes that television use, radio
use, newspaper use, and frequency of moviegoing will all be positively
correlated with HDTV awareness, interest, and purchase intention.
        The third main hypothesis is a corollary of Hypothesis 1.3:
        H3: The greater the number of home entertainment products respondents own, the
     more they will          be aware of HDTV, express an interest in HDTV, and be
     likely to purchase an HDTV set.
Because earlier adopters generally have higher socioeconomic status than later
adopters (Rogers, 1995), it follows that they will also be more likely to own
consumer electronics items.  Empirical research has shown that home satellite
dish (TVRO), cable television, and personal computer adopters were more likely
to own related entertainment products (e.g., video games, VCR, PC) than
nonadopters (Danko & MacLachlan, 1983; Dickerson & Gentry, 1983; Lin, 1996;
Litman, Chan-Olmsted, & Thomas, 1991; Rothe, Harvey, & Michael, 1983; see also
Lupker et al., 1988).  Therefore, we hypothesize a positive relationship between
ownership of home entertainment products and HDTV awareness, interest, and
purchase intention.
        The last group of hypotheses examines consumer responses to television
technology attributes:
     H4.1: The higher respondents value the importance of picture sharpness, the
     more they will be          aware of HDTV, express an interest in HDTV, and
be
     likely to purchase an HDTV set.
 
     H4.2: The higher respondents value the importance of sound quality, the
     more they will be aware         of HDTV, express an interest in HDTV, and
be
     likely to purchase an HDTV set.
     H4.3: The higher respondents value the importance of screen size, the more
     they will be aware         of HDTV, express an interest in HDTV, and be
likely
     to purchase an HDTV set.
These three television characteristics have often been touted as selling points
for HDTV technology.  Lupker et al. (1988) reported that motion quality, sense
of depth, picture sharpness, and set size were all significant predictors of
HDTV purchase intent at $1,500.  At the $2,500 price range, significant
predictors included motion quality and set size.  Therefore, we would expect
that the more respondents value picture sharpness, sound quality, and screen
size, the more they will be aware of HDTV, express an interest in HDTV, and be
likely to purchase an HDTV set.
        Finally, the following research question was posed:
     RQ: What is the relative influence of demographics, mass media use,
     ownership of home               entertainment products, and television
     attributes in predicting HDTV awareness, interest,         and purchase
     intention?
Despite the voluminous diffusion literature, little research has been conducted
to determine how blocks of variables such as those above compare to each other
in predicting adoption of communication technologies.  For instance, are
demographics better predictors of adoption than mass media exposure, or is it
the opposite?  Jeffres and Atkin (1996) found that "assessment of media quality"
and "media exposure" influenced people's likelihood to use new technologies for
consumer purposes to a greater extent than did "demographics."  Although a
formal prediction is difficult to state at this point, we would expect, based on
a number of empirical studies (see Danko & MacLachlan, 1983; Dickerson & Gentry,
1983; Litman, Chan-Olmsted, & Thomas, 1991; Lupker et al., 1988; Rothe, Harvey,
& Michael, 1983), that both demographics and ownership of home entertainment
products will play a significant role in determining HDTV awareness, interest,
and purchase intention.
Method
        A simple random sample of 613 phone numbers in the Miami, Florida, area were
called during the evening hours of March 3 to March 20, 1995.  Telephone numbers
were drawn from the most recent edition of the city telephone directory, by
first selecting randomly a page, then selecting randomly a column within the
page, and finally selecting randomly a name with a phone number within the
column.  The last digit of the suffixes was then increased by 1 to account for
unlisted phone subscribers.  Interviewers were trained undergraduate students
enrolled in a research methods class.  All calls were made from a central
location.  Excluding non-eligible respondents (e.g., younger than 18),
non-working numbers, and numbers that were never answered after six attempts,
the completion rate was 58% (N = 193).
        The questionnaire contained questions about five topics: (1) importance of
television attributes; (2) HDTV awareness, interest, and purchase intention; (3)
ownership of home entertainment products; (4) mass media use; and (5)
demographics.
        Television Attributes.  Respondents were asked to rate the importance of
picture sharpness, sound quality, and screen size on a 5-point scale ranging
from extremely important (1) to not important at all (5).
        HDTV Awareness, Interest, and Purchase Intention.  Next, they were asked to
report their HDTV awareness ("Have you ever heard about high-definition
television?").  Then, whether or not respondents were aware of HDTV,
interviewers briefly explained the three main characteristics of HDTV technology
(sharper pictures; high-fidelity sound; and larger and wider screen).
Afterwards, they asked respondents to evaluate their degree of interest in HDTV
("In keeping these characteristics in mind, can you tell me how interested you
would be in acquiring a high-definition television set"?) on a 4-point scale
from very interested (1) to not interested at all (4).  The third dependent
variable dealt with purchase intention.  The question was: "According to the
manufacturers, a high-definition television set will cost about $3,000 when
first introduced.  Suppose that you decide to buy a new television set in 1995.
How likely would it be that you would buy a high-definition television set at
this price." The response set ranged from very likely (1) to not likely at all
(4).
        Ownership of Home Entertainment Products.  Respondents were asked whether they
subscribed to cable television, and owned a VCR, a satellite dish, a video games
system, a compact disc player, and a personal computer at home.  These six
variables were categorical (1 = yes; 2 = no).
        Mass Media Use.  Fourth, respondents were asked about their television use ("On
average, about how many hours a day do you watch television?"), radio use ("On
average, about how many hours a day do you listen to radio?"), newspaper use
("How many days a week, if any, do you read a daily newspaper?"), and frequency
of moviegoing ("How many times did you go to see a movie last month?").  In
addition, respondents answered how often they watch wildlife documentaries and
sports on television on a 5-point scale, from about every day (1) to never (5).
        Demographics.  The questionnaire concluded with four demographic questions:
age, education, income, and gender.
        Because the calling area was bilingual, two versions of the same questionnaire,
one in English and one in Spanish, were prepared.
        Bivariate correlation analysis was used to test all hypotheses except the
relationship between HDTV awareness and gender (chi-square test).  Linear
hierarchical regression was used to determine the relative influence of
demographics, mass media use, ownership of home entertainment products, and
television attributes in predicting HDTV interest and purchase intention.
Logistic hierarchical regression, instead of linear regression, was used to
answer the awareness component of the research question, because HDTV awareness
was a categorical variable (see Hosmer & Lemeshow, 1989).  All categorical
variables were recoded as dummy variables (0 = no; 1 =yes).  Scales for
television attributes, viewing of documentaries, and viewing of sports were
recoded from 1-5 to 5-1; scales for HDTV interest and purchase intention were
recoded from 1-4 to 4-1.  To test Hypothesis 3, an index for home entertainment
products was created by aggregating responses to the six ownership variables
(cable subscription, VCR, satellite dish, video games system, compact disc
player, and personal computer).  The scale ranged from 0 to 6.  In the
regression analyses, two specific viewing measures, sports and documentaries
viewing, were added as predictors.  There has been some speculation whether
sports and wildlife documentaries might represent programming killer
applications for HDTV, because these types of television content might greatly
benefit from a wider aspect ratio (see Neuman, 1988).  The inclusion of these
variables in the media use block of the hierarchical regressions will allow us
to explore this possibility.
 
 
        Findings
Descriptive results
        The sample had a median age category of 30-39 and a median annual household
income category of $30,000-$45,000.  Of all respondents, 16.0% did not complete
high school, 18.8% were high school graduates, 29.8% had some college, 20.4%
were college graduates, and 14.9% pursued graduate work or received a graduate
degree.  In all, 65.1% had at least some college education.  Females comprised
50.8% of the sample.  Nationally, the median age was 34, the median annual
household income was $32,264 (1994),  51.2% of the population were female, and
47.7% had at least some college education (U.S. Bureau of Census, 1996).  So the
composition of the sample did not differ demographically from that of the
national population except in educational level.
        Respondents' ownership of home entertainment products also reflected national
trends (see Consumer Electronics Manufacturers Association, 1996; National Cable
Television Association, 1995).  Of the respondents, 67.7% subscribed to cable
television, 84.6% owned a VCR, 10.1% owned a satellite dish, 41.8% owned a video
games system, 62.4% owned a compact disc player, and 38.3% owned a personal
computer.  Nationally in 1995, 64% of all U.S. households subscribed to cable
television, 88% owned a VCR, 63% owned a compact disc player, and 40% owned a
personal computer.
        An overwhelming majority of respondents rated sound quality (82%) and picture
sharpness (77.8%) as either "very important" or "extremely important."  But only
45% felt that screen size was either "very important" or "extremely important."
On average, respondents watched about 3 hours and 4 minutes a day, listened to
radio for 2 hours and 47 minutes, read a daily newspaper four times a week, and
attended movies 1.67 times during the month preceding the survey.  In addition,
46.2% and 37.1% watched wildlife documentaries and sports programs at least a
few times a week, respectively.
        The study also revealed that 32.1% of the respondents were aware of HDTV.  A
majority (58.3%) expressed interest in acquiring an HDTV set based on the
specifications enunciated by the interviewers (somewhat interested: 25.3%; very
interested: 33%).  On the other hand, only 15.5% indicated that they would be
likely to purchase an HDTV receiver at a price tag of $3,000 (somewhat likely:
9.6%; very likely: 5.9%).
Hypotheses
        None of the hypotheses received full support for all three dependent
variables--HDTV awareness, interest, and purchase intention (Table 2).  However,
both Hypothesis 1.3 (income) and Hypothesis 4.1 (picture sharpness) came close
by correlating significantly with both HDTV awareness and interest.
Higher-income respondents and those who placed more importance on picture
sharpness were more aware of HDTV and expressed a greater interest in an HDTV
set than lower-income respondents and those who felt that picture sharpness was
less important.  As expected, age was negatively related to HDTV interest
(H1.1); education was positively related to HDTV awareness (H1.2); newspaper use
was positively related to HDTV awareness (H2.3); frequency of moviegoing was
positively related to HDTV interest (H2.4); and screen size was positively
related to HDTV purchase intention (H4.3).  Contrary to Hypothesis 1.4, gender
was significantly related to HDTV awareness (X2[1, N = 181] = 14.69, p < .001):
Male respondents were more aware of HDTV than their female counterparts.  Males
also expressed a greater interest in an HDTV set than females, although that
correlation coefficient (r = .14) was marginally significant (p = .060).
Finally, Hypothesis 3 (home entertainment products) was supported for HDTV
interest and marginally so for HDTV awareness (p = .069).  Those respondents who
owned more home entertainment products were more interested in HDTV than those
who owned fewer of these items (Table 2).
Research Question
        The research question examined the relative influence of demographics, mass
media use, ownership of home entertainment products, and television attributes
in predicting HDTV awareness, interest, and purchase intention.  Demographic
variables (age, education, income, and gender) were entered first, followed by
mass media use (television use, radio use, newspaper use, moviegoing,
documentaries viewing, and sports viewing), ownership of home entertainment
products, and importance of television attributes (picture sharpness, sound
quality, and screen size).  The logistic hierarchical regression reveals that
income, gender (male), and picture sharpness were significant positive
predictors of HDTV awareness (Table 3).  The Wald statistic, the equivalent of
the t test in linear regression, was used to determine the statistical
significance of the regression coefficients (see Norusis, 1994).  The
improvement chi-square (X2) test, which is comparable to an F-change test in
linear regression, tested the null hypothesis that coefficients for the
variables added at each step of the regression were 0.  The findings indicated
that the model with the demographic variables (block 1) constituted a
significant improvement in predicting HDTV awareness over the constant-only
model.  Importance of television attributes (block 4) contributed significantly
(p = .078) to improving the fit of the HDTV awareness model.
        In the first linear hierarchical regression (Table 4), age (negative), income,
moviegoing, sports viewing (p = .064), and picture sharpness (p = .088) were
found to be significant predictors of HDTV interest.  Independent variables
accounted for 25% of the variance in interest in acquiring an HDTV set.
Television attribute variables were more successful than mass media use and
ownership of entertainment products in explaining additional variance in HDTV
interest above that for the first block.
        In the second linear hierarchical regression (Table 5), the only major
predictor of HDTV purchase intention was screen size.  Independent variables
accounted for 11% of the variance in the HDTV purchase intention model.  Only
the R2 change for the block containing television attributes was significant.
Discussion and Conclusions
        While some hypotheses did not gain support, especially in regard to HDTV
purchase intention, those who did were almost always consistent with diffusion
theory and research.  Although it is difficult to profile HDTV potential
adopters with great precision because the technology is still in a pre-adoption
stage, certain characteristics clearly emerge.  Innovators and early adopters of
HDTV receivers will likely have higher income, be frequent moviegoers, watch
sports programs, and express a keen interest in large-screen televisions.
        This preliminary description is consistent with past research conducted outside
and in the United States.  For instance, Bouwman, Hammersam, and Peeters (1993)
also found that those Dutch respondents who desired a wider and larger screen as
a television improvement were more willing to buy an HDTV set for about ECU
2,200 (about $2,700).  In their Belgian study, Dupagne and Agostino (1991)
reported positive correlations between moviegoing and importance of having an
HDTV set at home.  The finding that sports viewing is a predictor of HDTV
interest substantiates some anecdotal evidence that content will matter in the
adoption of HDTV (see Neuman, 1988).  It may well be that sports programming
aired in HDTV could produce highly favorable attitudes among potential viewers,
which could in turn increase existing viewership.  Though insignificant in the
regression analysis, there was a significant positive relationship between the
number of home entertainment products owned and HDTV interest.  Again, this
result confirms previous HDTV audience research (see Lupker et al., 1988).
        The hierarchical regressions revealed that demographics and television
attributes were stronger predictors of HDTV awareness and interest than mass
media use and ownership of home entertainment products.  Jeffres and Atkin
(1996) noted "a diminished role for demographics" (p.  328) in their study of
technology use, but that observation was not supported in this study.  Future
diffusion research should evaluate whether the influence of demographics on
communication technology adoption depends on the nature or characteristics of
the technology.  From Table 1, it would appear that adoption of hardware-based
communication technologies, such as the VCR, TVRO, and the PC, is especially
contingent upon certain demographic variables.
        The perceived relevance of such television attributes as picture sharpness and
screen size for some prospective HDTV adopters contradicts the often-held view
(e.g., Negroponte, 1995) that television characteristics and improvements are
unimportant to the American public.  Other things being equal (e.g., price),
viewers prefer HDTV features to those of NTSC (Lupker et al., 1988).  A recent
HDTV-versus-NTSC comparative test, commissioned by Harris Corporation, further
corroborates this assertion.  Of the 104 respondents, 98% felt that digital HDTV
was superior to traditional NTSC television; 96% stated that they liked the
shape of the 16:9 receiver; and 97% reported that HDTV sound (5.1 channel
system) was superior to NTSC sound (stereophony) (Harris Corporation, 1997).  If
indeed these HDTV attributes truly matter, U.S. broadcasters would be well
inspired to transmit their programs in HDTV format, instead of delivering them
in lower-resolution SDTV.
        This study also has practical implications for consumer electronics
manufacturers.  The good news is that a majority of respondents (58.3%)
expressed an interest in HDTV and its features.  On the other hand, only 15.5%
of the sample reported a willingness to purchase an HDTV receiver at $3,000, an
expected low-end figure for the first HDTV sets that will be introduced in the
United States at the end of 1998.  This percentage is similar to the one (14%)
reported by Lupker et al. (1988) seven years earlier.  Not surprisingly, and
consistent with previous research (e.g., Dupagne & Agostino, 1991), an
overwhelming majority (93.1%) of the respondents were either somewhat or very
satisfied with their current television set.  To overcome the price objection,
which is likely to be acute in the initial diffusion of HDTV, consumer
electronics marketers should adopt pull promotion strategies by stimulating
interest and demand at the end-user level (instead of wholesalers and
retailers), that is, targeting directly the consumer with advertising messages.
Of particular importance, these campaigns should tout HDTV's relative
advantages, such as picture sharpness and screen size.  As discussed above,
relative advantage is a key determinant of an innovation's rate of adoption (see
Rogers, 1995).          Finally, this research is not without weaknesses.  The sample
size is limited even for an exploratory study.  It is also important to stress
that the results derive from a single market, not from a national survey,
although the sample composition was representative of the U.S. population at
large in terms of age, gender, income, and ownership of home entertainment
products.  Furthermore, it may be argued that respondents' HDTV interest and
purchase interest cannot be meaningfully measured without prior exposure to live
demonstrations of HDTV pictures.  A public demonstration would certainly have
enhanced the relevance of consumer reactions.  From this perspective, lack of
context is another limitation of this study.  On the other hand, unlike surveys
or experiments presenting NTSC-HDTV side-by-side comparisons (e.g., Lupker et
al., 1988; Neuman, 1988), this study has used a probabilistic procedure to
select respondents, allowing greater external validity.  Despite these
limitations, the results of this research offers some preliminary
diffusion-grounded insights into U.S. consumer awareness and interest in HDTV
prior to its market introduction in the United States.
 
 
 
References
        Andrews, E. L., & Brinkley, J. (1995, January 22). The fight for digital TV's
future. The New York Times, sec. 3, p. 1.
        Bouwman, H., Hammersam, M., & Peeters, A. (1993, May). The demand for a better
television and acceptance of HDTV. Paper presented at the annual meeting of the
International Communication Association, Washington, DC.
        Brinkley, J. (1997). Defining vision: The battle for the future of television.
New York: Harcourt Brace.
        Bruce, I. (1996, August). Information, attitude and the early adoption of
innovation: The case of direct broadcast satellite. Paper presented at the
annual meeting of the Association of Education in Journalism and Mass
Communication, Anaheim, CA.
        Collins, J., Reagan, J., & Abel, J. D. (1983). Predicting cable subscribership:
Local factors. Journal of Broadcasting, 27, 177-183.
        Consumer Electronics Manufacturers Association. (1996). The year in consumer
electronics 1995. Arlington, VA: Author.
        Danko, W. D., & MacLachlan, J. M. (1983). Research to accelerate the diffusion
of a new invention: The case of personal computers. Journal of Advertising
Research, 23(3), 39-43.
        Dickerson, M. D., & Gentry, J. W. (1983). Characteristics of adopters and
non-adopters of home computers. Journal of Consumer Research, 10, 225-234.
        Dickson, G. (1997, May 19). Cutting edge. Broadcasting & Cable, p. 61.
        Dupagne, M., & Agostino, D. E. (1991). High-definition television: A survey of
potential adopters in Belgium. Telematics and Informatics, 8, 9-30.
        Ettema, J. S. (1984). Three phases in the creation of information inequities:
An empirical assessment of a prototype videotex system. Journal of Broadcasting,
28, 383-395.
        Federal Communications Commission. (1996, December 24). Advanced Television
Systems and Their Impact Upon the Existing Television Broadcast Service (Fourth
Report and Order), 11 FCC Rcd. 17771.
        Federal Communications Commission. (1997a, April 3). Advanced Television
Systems and Their Impact Upon the Existing Television Broadcast Service (Fifth
Report and Order), MM Docket No. 87-268.
        Federal Communications Commission. (1997b, April 3). Advanced Television
Systems and Their Impact Upon the Existing Television Broadcast Service (Sixth
Report and Order), MM Docket No. 87-268.
        Harris Corporation. (1997). Consumer DTV screening survey. Melbourne, FL:
Author.
        Holak, S. L. (1988). Determinants of innovative durables adoption: An empirical
study with implications for early product screening. Journal of Product
Innovation Management, 5, 50-69.
        Holak, S. L., & Lehmann, D. R. (1990). Purchase intentions and the dimensions
of innovation: An exploratory model. Journal of Product Innovation Management,
7, 59-73.
        Home Box Office. (1988). Consumer response to high definition television. New
York: Author.
        Hosmer, D. W., Jr., & Lemeshow, S. (1989). Applied logistic regression. New
York: John Wiley.
 
        Jeffres, L., & Atkin, D. (1996). Predicting use of technologies for
communication and consumer needs. Journal of Broadcasting & Electronic Media,
40, 318-330.
        LaRose, R., & Atkin, D. (1992). Audiotext and the re-invention of the telephone
as a mass medium. Journalism Quarterly, 69, 413-421.
        Lin, C. A. (1996, August). Personal computer adoption and internet use. Paper
presented at the annual meeting of the Association of Education in Journalism
and Mass Communication, Anaheim, CA.
        Litman, B., Chan-Olmsted, S., & Thomas, L. (1991). Estimating the demand for
backyard satellite dishes: The U.S. experience. Telematics and Informatics, 8,
59-69.
        Lupker, S. J., Allen, N. J., & Hearty, P. J. (1988). The North American high
definition television demonstrations to the public: The detailed survey results.
Montreal, Canada: Committee for the North American High Definition Television
Demonstrations to the Public.
        McConnell, C. (1995, January 16). More, not less, time needed for HDTV switch.
Broadcasting & Cable, p. 103.
        McConnell, C. (1997, January 20). Digital TV at doable price. Broadcasting &
Cable, pp. 60-61.
        National Cable Television Association. (1995, Spring). Cable television
developments. Washington, DC: Author.
        Negroponte, N. (1995). Being digital. New York: Alfred A. Knopf.
        Neuendorf, K. A., Atkin, D., & Jeffres, L. W. (1996, August). Understanding
adopters of audio information services. Paper presented at the annual meeting of
the Association of Education in Journalism and Mass Communication, Anaheim, CA.
        Neuman, W. R. (1988, April). The mass audience looks at HDTV: An early
experiment. Paper presented at the annual meeting of the National Association of
Broadcasters, Las Vegas, NV.
        Norusis, M. J. (1994). SPSS advanced statistics 6.1. Chicago: SPSS Inc.
        Ostlund, L. E. (1974). Perceived innovation attributes as predictors of
innovativeness. Journal of Consumer Research, 1, 23-29.
        Reagan, J. (1987). Classifying adoptors and nonadoptors of four technologies
using political activity, media use and demographic variables. Telematics and
Informatics, 4, 3-16.
        Reagan, J., Ducey, R. V., & Bernstein, J. (1985). Local predictors of basic and
pay cable subscribership. Journalism Quarterly, 62, 397-400.
        Reese, S. D. (1988). New communication technologies and the information worker:
The influence of occupation. Journal of Communication, 38(2), 59-70.
        Rogers, E. M. (1995). Diffusion of innovations (4th ed.). New York: The Free
Press.
        Rothe, J. T., Harvey, M. G., & Michael, G. C. (1983). The impact of cable
television on subscriber and nonsubscriber behavior. Journal of Advertising
Research, 23(4), 15-23.
        Scherer, C. W. (1989). The videocassette recorder and information inequity.
Journal of Communication, 39(3), 94-103.
        Seel, P. B. (1996). High-definition and advanced television. In A. E. Grant
(Ed.), Communication technology update (5th ed.) (pp. 101-113). Boston, MA:
Focal Press.
        U.S. Bureau of Census. (1996). Statistical abstract of the United States: 1996
(115th ed.). Washington, DC: Author.
        Zenith's first digital sets won't do cable HDTV. (1997, May 19). Broadcasting &
Cable, p. 15.
Table 1
Predictors of Communication Technology Adoption According to Demographic and
Media Use Variables
 
Technology
Diffusion
Theory
Cable
Cable (pay)
Cable
Cable
VCR
VCR
VCR
TVRO
Demographics
 Age
 Education
 Income
 Gender (male)
 
ns
+
+
 
ns
ns
-
ns
 
-
ns
+
ns
 
ns
ns
ns
ns
 
-
ns
+
ns
 
ns
+
+
ns
 
-
ns
+
ns
 
-
+
+
 
-
ns
+
Mass Media Use
 Television use
 Radio use
 Newspaper use
 Moviegoing
+
 
-
ns
ns
ns
 
ns
ns
ns
ns
 
+
ns
ns
ns
 
+
+
ns
ns
 
+a
 
ns
 
ns
ns
ns
ns
Study
Rogers, 1995
Collins
et al., 1983
Reagan et al.,
1985
Reagan, 1987
Reese, 1988
Reagan, 1987
Reese, 1988
Scherer, 1989
Litman et al., 1991
Note. ns = nonsignificant; + = positive predictor; - = negative predictor;
anon-news.
 
 
Technology
Diffusion Theory
PC
PC
PC
PC
Videotex
Videotex
Audiotext
DBS
Fax
Demographics
 Age
 Education
 Income
 Gender (male)
 
ns
+
+
 
+
+
+
 
-
+
ns
 
-
ns
+
ns
 
-
+
+
ns
 
-
+
ns
 
-
ns
ns
-
 
ns
+
ns
-
 
ns
ns
ns
+
 
-
ns
+
ns
Mass Media Use
 Television use
 Radio use
 Newspaper use
 Moviegoing
+
 
-
 
ns
-
-
+
 
 
 
ns
 
-
ns
ns
ns
 
ns
 
ns
ns
ns
+
Study
Rogers, 1995
Dickerson & Gentry, 1983
Danko & MacLachlan, 1983
Reagan, 1987
Reese, 1988
Ettema, 1984
Reagan, 1987
LaRose & Atkin, 1992
Bruce, 1996
Neuendorf et al., 1996
Note. ns = nonsignificant; + = positive predictor; - = negative predictor.
 
 
Table 2
 
Zero-Order Correlations of Demographics, Mass Media Exposure, Ownership of Home
Entertainment Products, and Television Attributes with HDTV Awareness, Interest,
and Purchase Intention
 
Dependent Variable
 
Independent Variable
HDTV Awareness
HDTV Interest
HDTV Purchase
Intention
Demographics
 Age
 Education
 Income
 Gendera
 
 -.06
  .26**
  .42**
   --
 
-.27**
 .12
 .25**
 .14 (p = .060)
 
   .01
  -.03
   .07
   .10
Mass Media Use
 Television use
 Radio use
 Newspaper use
 Moviegoing
 
 -.12
  .04
  .21**
  .03
 
-.12
 .12
 .04
 .25**
 
   .01
   .01
   .03
  -.06
Home Entertainment Products
  .13 (p = .069)
 .16*
   .01
Television Attributes
 Picture sharpness
 Sound quality
 Screen size
 
  .14*
 -.06
  .06
 
 .17*
 .10
 .09
 
   .01
   .10
   .24**
Note. agender: 0 = female; 1 = male; *p < .05; **p < .01.
 
 
 
Table 3
 
Logistic Hierarchical Regression of Demographics, Mass Media Exposure, Ownership
of Home Entertainment Products, and Television Attributes on HDTV Awareness
 
Block of Variables
Coefficient (B)
Improvement X2 Test
-2 Log Likelihood
1. Demographics
 Age
 Education
 Income
 Gender (male)
 
  -.12
   .13
   .51**
  1.18*
36.77***
153.86
2. Mass Media Use
 Television use
 Radio use
 Newspaper use
 Moviegoing
 Wildlife documentaries
 Sports
 
  -.20
   .05
   .04
   .08
   .19
   .01
4.09
149.77
3. Home Entertainment Products
  -.29
1.62
148.15
4. Television Attributes
 Picture sharpness
 Sound quality
 Screen size
 
   .63*
  -.57 (p = .095)
   .18
6.81 (p = .078)
141.34
*p < .05; **p < .01; ***p < .001.
 
 
 
Table 4
 
Linear Hierarchical Regression of Demographics, Mass Media Exposure, Ownership
of Home Entertainment Products, and Television Attributes on HDTV Interest
 
Block of Variables
Beta
R2 Change
R2
 Adjusted R2
1. Demographics
 Age
 Education
 Income
 Gender (male)
 
  -.18*
  -.03
   .21*
   .01
.14***
.14***
.11
2. Mass Media Use
 Television use
 Radio use
 Newspaper use
 Moviegoing
 Wildlife documentaries
 Sports
 
  -.14
   .02
  -.04
   .19*
  -.02
   .16 (p = .064)
.06
.19**
.13
3. Home Entertainment Products
   .01
.00
.19**
.13
4. Television Attributes
 Picture sharpness
 Sound quality
 Screen size
 
  .15 (p = .088)
  .05
  .13
.06*
.25***
.17
*p < .05; **p < .01; ***p < .001.
 
Table 5
 
Linear Hierarchical Regression of Demographics, Mass Media Exposure, Ownership
of Home Entertainment Products, and Television Attributes on HDTV Purchase
Intention
 
Block of Variables
Beta
R2 Change
R2
 Adjusted R2
1. Demographics
 Age
 Education
 Income
 Gender (male)
 
   .01
   .02
   .02
  -.01
.02
.02
 -.01
2. Mass Media Use
 Television use
 Radio use
 Newspaper use
 Moviegoing
 Wildlife documentaries
 Sports
 
  -.07
   .03
   .10
  -.05
   .06
   .14
.04
.06
 -.01
3. Home Entertainment Products
  -.02
.00
.06
 -.02
4. Television Attributes
 Picture sharpness
 Sound quality
 Screen size
 
  -.01
   .02
   .24*
.06*
.11
  .02
*p < .05.