Introduction
Technology use is one of the most important behaviours for increasing the quality of life for people from
different backgrounds [
1
]. Nowadays, Smart wearable technologies are promisingly evolving and
becoming essential in our lives. The growing popularity of mobile technologies has led to emergence
of wearable technologies [
2
]. The recent technological progress in the worldwide cause to boost
popularity of wearable devices such as smart watch and fitness wristband, which have been granted
anywhere-anytime accessibility to information. The meaning of “mobility” is evolving from exclusively
portable to seamlessly wearable technology, advancing the ubiquity of personal communication to the
next level [
3
]. Wearable technologies are fully functional, self-contained electronic devices that can be
worn, attached to the body, allowing the user access information anytime and anywhere [
4
].
Wearable technologies are still in its early stage and mostly being used as a tracking health and fitness
activities. In particular, smart watches (e.g. Samsung Galaxy Gear, Pebble E-Paper Watch) have been
highly hyped in the information and communications technology (ICT) industry for a multi-functionality
that appeals to a broad range of user interests, including not only fitness, health monitoring, and location
tracking but also extended communication and “smart” features [
5
]. Recent polls on smart watch
adoption forecast that the market will continue to grow at an exponential rate: 15 million units are
expected to be sold globally in 2014, 91.6 million by 2018, and 373 million by 2020 [6].
Markets for smartwatches and other wearables are growing. IDC (2015a) predict the worldwide market
for wearables to reach more than 111 million units in 2016, which is an increase of 44% compared to
2015. More than eighty percent of these devices will be wrist-worn devices – i.e., smartwatches or smart
wristbands. A Google trend-analysis also reflects a tremendous increase in searches for ‘smartwatch’
and related terms, supporting the results of the market research. Although forecasts vary with regard
to forecasted numbers and definitions, immense growth rates are consistently identified for the near
future [
7, 8
]. As the smart wearable technologies are growing rapidly, it is vital to understand the human
interaction with these new devices. However, although reports present increased demand for
smartwatches in the future, current sales estimates are still relatively low [7]. Little is known about what
impacts this difference in forecasts and sales and subsequently research is needed to more
comprehensively understand this gap of technology that is still in the beginning stages of its product
lifecycle. In particular, the question of what drives the adoption of smartwatches remain unanswered
between different segments of technology and market.
Therefore, focusing on the current phase of market, analyzing person’s psychographics should be the
best strategy and tactics for reaping the reward of this mainstream market. According to the model of
“ Technology Adoption Life Cycle” (TALC), making commutation and marketing shift between any two
adoption sections can be extremely hard due to adopt a new strategies and recognize all the differences
for the each segment [
9
]. One of the biggest problem during this transfer period is the gap from following
to use the group on the left part of the model (TALC) as a reference to penetrate the segment on the
right. The biggest gap between the all adoption groups are belong to visionaries (Early adopters) and
pragmatics (early majority). Penetrating to market segment can be tough challenge due to differences
between new target customers based on psychographic profile [
9, 10
]. Therefore, in order to fill this
chasm, those characteristics of visionaries that alienate pragmatists need to be observed and
considered.
In addition, as wearable technology is becoming more commercialized, it is necessary to investigate
how previous research regarding the factors of acceptance theory can be used in the context of
wearable technologies. Consequently, it is crucial to examine factors influencing consumers’
acceptance of smart devices among early and mainstream customers’ profiles. This study thereby
attempt to create a research model enabling a prediction of smart watch usage, with implications for
the adoption of future mainstream market according to chasm theory. The resulting analysis offers a
number of contributions to research and managerial implications. First, few studies have offered
analysis of smart wearable technologies from initial adoption to successful diffusion in the market.
Therefore, we aim to contribute to smart wearables research by providing insights into the adoption
processes and conditions that make such technology overcome the initial pilot stages. Second, we aim
to challenge existing boundaries of diffusion of innovation research, between innovators and
mainstream market consumers in particular by crossing the chasm, identifying those factors that
mainstream market face in seeking to diffuse the technology to a broader market. Finally, we provide
insights on which are the key drivers crossed the chasm by building a customized model based on
UTAUT2 in order to test psychographics profile of each segments of consumers.
Related work
Despite the wide use of technology adoption’s theories to investigate new technologies, limited research
has applied for analysis of consumers’ adoption in the area of smart wearable devices such as smart
watch and smart wristbands. Nevertheless, this section presents a brief summary of the fragmented
research on the smart wearable technologies.
Bodin and Gemperle [
14
] presented one of the first study in the topic of smart wearables. Their research
described that functionality plays a key factor in the perceived comfort of consumers. Later, Ko, Sung,
& Yun [
15
] examined the effect of perceived risks and benefits on attitudes and purchase intentions for
smart jacket and shoes. The study showed that attitude towards purchase intention is positively
influenced by compatibility and is negatively affected by devices’ perceived complexity. Another study
by Turhan [
16
] tested TAM and TPB theories for the smart bra and t-shirt adoptions by Turkish students.
The study found that perceived usefulness and behavioural control have an indirect effect on purchase
intention while subjective norms and perceived behavioural have a direct influence on attitude and
purchase intention. In addition, subjective norms, perceived usefulness, attitude and perceived
behavioural control appear to be shown by a set of salient beliefs for the both products. In the study by
Wang et al [
17
], an extended technology acceptance model in the context of wearable technologies is
used. The model proved that perceived usefulness is the most significant variable that affects
consumers’ attitudes towards wearable technologies acceptance while Nasir and Yurder [
18
] identified
that perceived benefits and perceived risk play an important role in the adoption wearable healthcare
devices by consumers.
Kim and Shin [
3
] carried out one of the extensive research in smart watch. The research replicates
basic TAM and clarified subcultural appeal and costs of the device. Moreover, the authors identified
various antecedents to perceived usefulness and perceived ease of use. Rauschnabel et al [
11
] run
two different research regarding google glass according to “big five theory” and TAM. The first study
showed descriptive norms and expected functionality influence on adoption intention and the second
study indicated that functional benefits, ease of use and brand drive the attitudes towards using smart
glasses. Jee and Sohn [
19
] found that concerning wearable devices some factors such as low to middle
priced with aesthetic character needs to be observed by firms in order to successfully targeting
segmented consumers. The study by Yang and his colleagues [
20
] presented that perceived
usefulness, social image and enjoyment seems to have influence on perceived benefits of consumers
for wearable devices. Finally, Gu et al [
21
] explored factors that impact on trust of consumers for
accepting wearable commerce by UTAUT2. This research clearly showed that performance
expectancy, hedonic motivation and facilitating condition impact in initial trust of consumers while
privacy concerns has a negative impact on it.
[6] IDC (2015a). IDC forecasts worldwide shipments of wearables to surpass 200 million in 2019, driven by strong
smartwatch growth <https://www.idc.com/getdoc.jsp?containerId=prUS40846515>.
[7]Lamkin, P. (2015). Just how big can wearable tech
<http://www.forbes.com/sites/paullamkin/2015/03/31/just-how-big-can-wearable-techget/#
2715e4857a0b7a2ea43b7812>.
get?
Forbes