Predicting User Acceptance of Mobile TV in Flanders
Tom Evens, Lieven De Marez
Research Group for Media & ICT (MICT-IBBT), Ghent University, Korte Meer 7-9-11, Gent, Belgium
Dimitri Schuurman
Research Group for Media & ICT (MICT-IBBT), Ghent University, Korte Meer 7-9-11, Gent, Belgium
Keywords: User research, adoption diffusion, use diffusion, mutual shaping, mobile TV.
Abstract: In the contemporary changing ICT environment, an increasing number of services and devices are being
developed and brought to end-user market. Unfortunately, this environment is also characterized by an
increasing number of failing innovations; confronting scholars, policy makers as well as industry with an
explicit need for more accurate user research. Such research must result in more accurate predictions and
forecasts of an innovation’s potential, as a basis for more efficient business planning and strategy
implementation. However, the success of a new technology is not only depending on the adoption decision
and the number of people actually buying it, but relies at least as much on its actual usage. Hence, the focus
of truly user-oriented acceptance or potential prediction should focus on predicting both adoption diffusion
and use diffusion. Within this paper, we illustrate the added value of such an interactionist approach for the
study of future adoption and usage of mobile TV by the assessment of both a large-scale intention survey
and qualitative techniques such as diary studies, focus group interviews, observational and ethnographic
In the contemporary changing ICT environment, an
increasing number of services and devices are being
developed and brought to end-user market.
Unfortunately, this environment is also characterized
by an increasing number of failing innovations;
confronting scholars, policy makers as well as
industry with an explicit need for more accurate user
research. Such research must result in more accurate
predictions and forecasts of an innovation’s
potential, as a basis for more efficient business
planning and strategy implementation.
In most cases however, this need for more
accurate user insight only gets translated in a cross-
sectional investigation of the innovation’s adoption
potential. However, the success of a new technology
or service is not only depending on the adoption
decision and the number of people actually buying
it. For example, many people may have bought or
adopted a mobile phone with GPRS, UMTS or
MMS without using the feature. The success of an
innovation is thus not only depending on its
adoption, but at least as much on its usage. Hence,
the focus of truly user-oriented acceptance or
potential prediction should not only be focussed on
predicting adoption diffusion, but also on predicting
use diffusion and potential usage. Evidently, the first
research question to answer remains up to which
degree the innovation has the potential to be
adopted. This should always be accompanied with
an answer to the question up to which degree the
innovation also has the potential to acquire a place in
people’s and household’s daily lives (in terms of
time and habits).
In terms of theoretical frameworks, the first
‘adoption diffusion’ question relies on the diffusion
paradigm, while the second ‘use diffusion’ question
relies on the ‘social shaping’ and ‘domestication’
paradigm. Too often however, the Social Shaping of
Technologies (SST) and Domestication perspective
is considered as the alternative to set off the lack of
attention for the user and his/her social usage
context in the diffusion theory. Traditionally, both
perspectives (and the research based on them) have
too much been considered as opposites; while they
Evens T., De Marez L. and Schuurman D. (2008).
ADOPTION VERSUS USE DIFFUSION - Predicting User Acceptance of Mobile TV in Flanders.
In Proceedings of the International Conference on e-Business, pages 124-130
DOI: 10.5220/0001907201240130
are perfectly complementary to each other. The
purpose of this paper is to illustrate this
complementariness and the enrichment of combining
the more quantitative generalizing research approach
of diffusionism with the more qualitative in-depth
SST research approach. Based on user research
conducted on mobile TV, we illustrate how this
combination of approaches and methods resulted in
a prediction of potential as well as usage of this new
technology. This way, we intend to illustrate the
theoretical, methodological, managerial as well as
policy relevance of this plea for a more mutual
shaping or interactionist approach on predicting user
acceptance (see Boczkowski, 2004: 255).
The oldest of the two theoretical frameworks is the
‘diffusion framework’, of which Everett M. Rogers
(1962) is assumed to be the founding father.
According to this framework, the diffusion of
innovations in a social system always follows a bell-
shaped normal distribution, in which there can be
successively distinguished between Innovators
(2.5%), Early Adopters (13.5%), Early Majority
(34%), Late Majority (34%) and Laggards (16%). A
person’s innovativeness is assumed to be determined
by the perception of the following set of innovation
characteristics: relative advantage, complexity,
compatibility, trialability and observability (Rogers,
2003). Since the early 60’s the theory’s assumptions
on segment sizes, diffusion pattern and determinants
have been a basis for different types of (mostly)
quantitative research such as econometric diffusion
modelling or innovation scales (Goldsmith &
Hofacker, 1991; Meade & Islam, 2006; Moore &
Benbasat, 1991; Parasuraman & Colby, 2001;
Venkatsh, Morris, Davis & Davis, 2003).
Since the mid 80’s however, questions about its
technological determinism and lack of attention to
the user and usage of the innovation have induced
Rogers to adjust his approach to the adoption
decision process, but have also led to the rise of new
paradigms such as domestication focussing on the
‘way the use in households is being socially
negotiated and becomes meaningful, within the
social context of class, gender, culture or lifestyle’
(Van Den Broeck, Pierson, Pauwels, 2004: 103;
Haddon, 2007; Silverstone & Haddon, 1996) or ‘the
process of taming and house training ‘wild’
technological objects, by adapting them to the
routines and rituals of the household and thus giving
them a more or less natural and taken-for-granted
place within the microsocial context of that
household’ (Frissen, 2000: 67; Jankowski & Van
Selm, 2001: 37). Domestication thus refers to
integration of new technologies in the daily patterns,
structures and values of users, relying on a more
social determinism (Bouwman, Van Dijk, Van den
Hooff & van den Wijngaert, 2002).
Methodologically, the SST and domestication
paradigm relies more on a qualitative tradition of
methods such as in-depth interviews, ethnographic
observation and diary studies.
In the past, these two major paradigms have
mostly been regarded as opposite and competing,
with convinced advocates from the two sides
engaging in vicious debates. However, with
diffusionism as the more quantitative tradition with
the focus on acceptance and adoption decisions and
the domestication tradition as more qualitative with
a focus on the use and appropriation of technologies,
both paradigms are clearly complementary (Punie,
2000). Or, as Boczkowski (2004: 255) states, ‘two
sides of the same innovation coin’. To date a
dialectical approach, which considers the
development and diffusion of ICT innovations as
‘joint processes of technological construction and
societal adoption’ (Boczkowski, 2004: 257), gains
ground. Instead of thinking in terms of diffusionism
or social shaping, the mutual shaping or
interactionism approach (Boczkowski, 2004;
Lievrouw & Livingstone, 2006; Trott, 2003)
appeared in the late 90’s as a dynamic middle path
between the two previous linear deterministic
predecessors. By integrating both quantitative and
qualitative research outcomes within this paper, we
aim to illustrate the enrichment of such an
interactionist approach for the development and roll-
out of mobile TV in Flanders, the northern and
Dutch-speaking part of Belgium.
Relying on the difference between ‘adoption
diffusion’ and ‘use diffusion’ (Shih & Venkatesh,
2004), we believe that the prediction of ‘adoption
diffusion’ should rely on (1) a quantitative diffusion
approach by means of (intention) surveys and
modelling to gain insight in the innovation’s
potential in terms of percentage of the target market,
penetration pattern and profiles of the different
adopter segments; and (2) the prediction of ‘use
diffusion’, based on more qualitative techniques
such as diary studies, focus group interviews,
observational and ethnographic techniques (if
possible in a field trial or living lab setting).
ADOPTION VERSUS USE DIFFUSION - Predicting User Acceptance of Mobile TV in Flanders
The empirical findings are based on the two-year
MADUF project which studied the possibilities of
mobile TV using DVB-H in Flanders. In first
instance, a large-scale user survey (n: 575) was set
up in order to forecast the market potential, or to
predict the ‘adoption diffusion’ potential for mobile
TV in Flanders. By applying the Product Specific
Adoption Potential (PSAP) scale, we were able to
map the size and nature of the future mobile TV
market in Flanders. The PSAP scale is an intention
based survey method in which respondents are
allocated to Innovator, Early Adopter, Majority and
Laggard segments based on the stated intentions on
a general intention question and on respondent-
specific formulated questions gauging for their
intention for ‘optimal’ and ‘suboptimal’ product
offerings (De Marez & Verleye, 2004; Verleye & De
Marez, 2005). The scale was compared on its
reliability with five other adoption models and has
been applied to and validated for a diversity of ICT
innovations such as digital TV, 3G, mobile TV and
mobile news (De Marez, 2006; De Marez, Vyncke,
Berte, Schuurman & De Moor, 2008).
In second instance, a representative panel of test
users was randomly selected from the 575 survey
respondents to experiment with mobile television
devices in a ‘living lab’ setting during two weeks.
Due to practical reasons (the DVB-H network was
operational in the city of Ghent only, so the panel
contained people exclusively living but not
especially working in Ghent) and because of the
rather explorative nature of this field trial, the
amount of test users was limited to 30. With this
field trial, we aimed at achieving a first realistic
view of how future users will integrate mobile TV in
their everyday practices. Users were asked to
document their experiences in diaries while logging
their activities, noting their comments and taking
pictures of their usage situations.
Next to these data, we also gained insight in their
personal evaluation of the trial phase by means of a
post-measurement. Comparing these results with the
findings of the market forecast before testing the
device allowed us to see whether user attitudes
towards mobile television had changed as a result of
the trial. In this manner, we aimed to measure the
effect of trialability, the degree to which an
innovation may be experimented with on a limited
basis (Rogers, 2003: 266). Explanations for possible
shifts between the pre- and the post-measurements
can be found in the usage diaries and two organised
focus groups. Figure 1 illustrates this interactionist
approach combining both quantitative user attitude
research and qualitative ethnographic techniques.
Figure 1: Interactionist research design.
By applying the PSAP scale to 575 rich cases, we
obtained a reliable view on the size and nature of the
various adoption segments for mobile TV in
Flanders in the following segmentation forecast.
While traditional fixed segment sized methods are
reflected by the black line (in this case Rogers’
Diffusions of Innovations), the red line represents
the adoption potential for mobile TV. The latter is
contrasted to the potential of 3G (De Marez, 2006),
which allows TV programmes to be received over a
unicast architecture network. Figure 2 clearly shows
that there is little demand for mobile TV over DVB-
H compared to Rogers’ full market approach and
even compared to the take-up of 3G services. Due to
the lack of substantial innovative segments
(Innovators and Early Adopters), we would
recommend a partial market approach or even a
niche strategy for the introduction of mobile TV in
Flanders. This implies a specific introduction
strategy for a limited market potential to serve the
chosen segments in an optimal manner (about a 20%
market penetration). Since the Late Majority and
Laggard segment are clearly not willing to pay for
this mobile service, we will define the maximal
target group as Innovators, Early Adopters and Early
Majority promising a 16,7% segmentation forecast.
Figure 2: Segmentation forecast mobile TV.
In general, we witnessed a rather dual profile
within the innovative segments with on the one hand
well-earning, older executives (little time, potential
ICE-B 2008 - International Conference on e-Business
for snacking) and on the other hand low educated
young couples without children (much time,
complementary to heavy TV viewing behaviour).
Although especially executives are facing a shortage
of time, most of them seem to be heavy television
viewers, watching both entertainment and
information programs. Especially Innovators and
Early Adopters (joint for statistical reasons) possess
advanced mobile phones (with camera, MMS, WAP,
MP3, FM radio…), which they use in an innovative
manner (e.g. sending e-mails on mobile phone, see
Figure 3). Generally, these people show the highest
willingness to pay for mobile TV while most of
them consider a mobile TV device (with integrated
mobile phone) as a substitute for their current
mobile phone.
Figure 3: Sending e-mails on mobile phone
Clearly, such quantitative research may provide
reliable estimations of the adoption potential and
diffusion (in this case of mobile TV in Flanders), but
does not provide us with in-depth information
regarding the domestication and potential use
diffusion of mobile TV. What place will it take in
the lives of the consumers, how and when will it be
To answer the latter questions, one needs a more
qualitative ‘use diffusion’ and domestication
oriented research framework. In the case of mobile
television a combination of diaries, focus group
discussions, pre-post test comparisons and photo
elicitation within the boundaries of a living lab
setting was used to get further insight in people’s
usage patterns of mobile TV. Although we are aware
these results are not statistically representative due
to the very limited sample of 30 test users, they
nevertheless allow us to identify some explorative
usage patterns for mobile TV amongst our field trial
On average, people watched approximately
eleven times via their mobile television device
during the two-week test period. However, it is
possible that people being part of a panel within a
test environment felt obliged to experiment more
with the devices than they would do within a more
natural context. Although we cannot ignore this trial
effect, it plays a less important role within this
research set-up because we aim to generate
explorative rather than statistically representative
findings. In terms of this usage frequency pattern,
we can distinguish three kinds of viewers: light
viewers watching less than 10 times (n: 15), medium
viewers watching between 10 and 20 times (n: 13)
and heavy viewers watching more than 20 times (n:
2). These two heavy viewers were identified as
Innovator and Early Adopter within our large-scale
Within our user panel, we only found two heavy
viewers while the rest of the panel was about equally
divided among medium and light viewers. One
important finding during our test period is that the
different types of viewers used the mobile TV
device in a different way. Figure 4 represents all
watching moments and divides them amongst the
periods people watched mobile TV. In terms of the
moments people watched mobile TV, we identified
six different time slots: night (0-6h), morning (6-
12h), noon (12-14h), afternoon (14-18h), evening
(18-22h) and late evening (22-24h). When analysing
the figure, we see that, except for the light viewers,
trial participants are not inclined to watch mobile
TV while having breakfast. This is probably due to
the strong position in the morning of the medium
radio, which is ‘together with the water and the
stove, the first thing that is turned on in the morning’
(Winocur, 2005: 325). Light viewers are also more
likely to watch mobile television at noon while
having dinner.
Figure 4: Usage patterns (per time slot).
Heavy viewers are most likely to watch mobile
during the afternoon, while most of the other types
of viewers only switch their device on in the evening
after coming home from work or school (see Figure
4). While light and medium viewers are watching
mobile TV in the evening, we notice a remarkable
ADOPTION VERSUS USE DIFFUSION - Predicting User Acceptance of Mobile TV in Flanders
decline in viewing of the heavy viewer-segment
during this time slot (see red line). Nevertheless, we
see that this segment starts watching again in the late
evening, the moment where the other segments
switch their device off. This results in peaked
watching patterns that differ quite much between the
three user segments. While light and medium users
show one viewing peak during the evening, heavy
viewers have two peaks: one in the afternoon and
one in the late evening. The latter two-peaked
pattern is rather complementary with traditional TV,
as its peak time comes right in between the mobile
peak times. We can conclude that heavy viewers
used mobile TV complementary to their regular
television and therefore watched the device in a
manner it was meant to be watched: on the move. In
contrast, light and medium viewers watched mobile
TV at home as a substitute for regular television.
The previous findings are supported by the usage
locations indicated in the diaries. Light and medium
viewers especially watched mobile TV at home.
Undoubtedly, the most popular place was the living
room where people are used to watch regular
television while relaxing in their sofa. This also
seemed the case for mobile TV: most people
watched television in their natural habitat. Instead of
watching the large screen, our test users watched
mobile TV, albeit for a rather short period. After
having tested the mobile device, they switched to the
large screen again to enjoy their favourite programs.
Here, we witnessed a substitution
of the classical
screen at traditional peak times with mobile TV was
considered a second TV (see also Schuurman et al.,
2008). This was especially the case for the light and
medium users in our sample. This does explain the
similarities between peak times for mobile and
regular TV for these groups.
Another popular location for watching mobile
TV was the kitchen. People seem to enjoy watching
mobile TV while eating in the kitchen, where most
of the time no TV set is at hand. We also witnessed
that a lot of people used the mobile device while
working at their desk or sitting behind the computer.
These people used mobile TV rather as a
medium or as tertiary activity (see
Jacobs, Lievens, Vangenck, Vanhengel & Pierson,
2008). When they heard something interesting, they
switched attention from their work to the mobile
device. Although they watched mobile television,
these people considered the mobile television device
often as a radio, which is in most cases also used as
a background medium. Here mobile TV was clearly
used in combination with other activities such as
doing the dishes or working (multitasking).
Especially heavy viewers made use of the
complementary function
of mobile TV and
considered it as an extra supply next to their regular
television. This is illustrated by the fact that heavy
viewers watched significantly more in public space
and on the move. We found that watching in the car
is a rather popular activity to kill time, sometimes as
fellow passenger but also as driver. These people
driving to their work and back, spend a lot of time in
their car and have to suffer traffic jams. It is hardly
surprising that in such cases mobile television is
seen as a simple time killer although the radio can
serve this purpose as well. Other persons preferred
watching mobile TV while waiting for or travelling
with public transport services (bus, metro and train).
Taking into account the massive success of the iPod,
mobile TV devices can be the next big thing to
spend time while commuting.
After the trial period, we asked our 30 test users
to fill out the same questionnaire they had
previously taken. Based on the combined results of
both pre- and post-trial measurement, we were able
to compare the findings and see whether user
expectations and attitudes had changed during the
mobile TV field trial. The findings from the
qualitative part of this research project (i.e. focus
groups and ethnographic methods such as usage
diaries) enabled us to explain possible shifts.
General interest for mobile TV slightly increased
during the field trial. However, persons who
originally intended to purchase a mobile TV device
soon, now preferred to wait a bit longer. On the
other hand, the amount of people certainly not
willing to purchase a mobile TV device declined as
well. A slightly increased average score (from 3,70
to 3,80) suggests that overall attitude towards mobile
TV became a little bit more positive. Also the
average price people are willing to pay increased
from €233 to €294. But it is striking that we witness
a converging shift towards a non-decisive average.
Convinced believers start to doubt while disbelievers
might have seen some possibilities after all due to
the trial.
In other words, less people are showing an
innovative attitude towards mobile TV, but many
others shifted from ‘never’ to ‘maybe’. It thus seems
that the field trial has raised awareness of mobile TV
and that a lot of people do not consider the medium
as a luxurious product any longer, making it less
appealing to the more innovative but more likely to
consider for the less innovative. Although these
people are not likely to purchase mobile TV soon,
they are not longer against mobile TV since they
have experienced it as a handy medium to catch up
television content quickly. Innovators and early
adopters on the other hand were somehow
disappointed by the lack of interactive and
ICE-B 2008 - International Conference on e-Business
interesting content, resulting in their downgrade.
Despite the shift towards a more positive attitude,
the potential for mobile television remains
dramatically low, as the sample does not contain any
Innovators or Early Adopters anymore and that the
least innovative segments (Late Majority and
Laggards) remain largely overrepresented.
With this paper, we intended to reconcile two
opposing traditions: adoption diffusion and use
diffusion. Within the MADUF-project, we combined
research techniques from both traditions in an
interactionist way in order to get a more holistic
view on the possible success of mobile TV in
Flanders. By means of a PSAP-estimation, it became
clear that mobile TV is not ready yet for total market
acceptance so that a partial market or even niche
strategy was suggested. By means of a diary study,
combined with a pre-test and post-test survey during
a mobile TV-trial in a living lab environment, we
were able to get a better understanding of the
possible use diffusion of mobile TV. We found that
for most test persons traditional television remains
the reference point for evaluating mobile TV.
Television undoubtedly is one of the most
domesticated technologies within the home and
became so dominant that people often schedule their
behaviour in function of the TV-set. We found that
light and medium mobile viewers used the device at
home as a second TV with watching behaviour in
line with traditional TV. Heavy users on the contrary
watched mobile TV in a truly mobile and much
more complementary way with traditional television.
This resulted in mobile peak times coinciding with
regular TV for the former two groups, while for the
latter mobile TV allowed to extend the regular TV
viewing peak with two mobile peaks: one before and
after the regular peak. Finally, we witnessed the
(modest) overall positive effect of trialability
through a slightly increased general attitude towards
mobile TV during the field trial.
By combining these two paradigms, we were
able to draw a clearer picture of the potential success
of mobile TV and the different factors influencing
this success. While a quantitative potential
estimation can identify adoption segments and
describe them for targeting purposes, the qualitative
usage diffusion-research provides input for the fine-
tuning of the technology in terms of usage patterns,
features and content. We believe this methodological
plea for more interactionist research designs has
theoretical as well as industry and policy relevance
for the prediction of ICT user acceptance. For
instance, in the current debate of digital dividend
such predictions could help policymakers to get
insight in the feasibility of new communication
technologies and for which new technologies they
should preserve space in the future radio spectrum.
These estimations also allow marketing managers to
decide in which market segments they should invest
and with what offer these segments should be
targeted. Finally, for researchers we hope this paper
gives some food for thought about the added value
of an interactionist approach and inspires them to
work out more creative innovations research designs
in the future.
The MADUF-project (Maximize DVB Usage in
Flanders) was supported by grants from the research
centre IBBT (Interdisciplinary Institute for
Broadband Technology) and a consortium of both
broadcasters and network solution companies. The
MADUF project aimed to maximize the social and
economic valorisation of DVB-H for the Flemish
citizen, government and industry (broadcasters,
operators and constructors) through the development
of a technological and regulatory consensus model
(pax mobilis).
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