What drives smartwatch adoption intention? Comparing Apple and non-Apple watches

DOIhttps://doi.org/10.1108/LHT-09-2016-0105
Date20 March 2017
Published date20 March 2017
Pages186-206
AuthorKuo-Lun Hsiao
Subject MatterLibrary & information science,Librarianship/library management,Library technology,Information behaviour & retrieval,Information user studies,Metadata,Information & knowledge management,Information & communications technology,Internet
What drives smartwatch adoption
intention? Comparing Apple and
non-Apple watches
Kuo-Lun Hsiao
Department of Information Management,
National Taichung University of Science and Technology, Taichung, Taiwan
Abstract
Purpose The purpose of this study is twofold. First, an integrated model will be developed based on task-
technology fit, innovation diffusion theory and the new product adoption model in order to explore the factors
that affect smartwatch adoption. Second, the differences in the factors that affect usersintention to adopt the
Apple Watch and other smartwatches will be examined.
Design/methodology/approach The data for this study were collected via an online survey
questionnaire. The responses of 341 potential adopters of smartwatches were used to test the hypotheses in
the research model. The casual model was assessed using partial least squares techniques.
Findings The model can account for more than 50 percent of the variance in adoption intention.
The research results affirm prior findings that perceived product attributes have relatively strong influence
on adoption intention. Among these attributes, relative advantage has the strongest effect. Moreover, this
study revealed differences between the antecedents of Apple watches and those of non-Apple watches.
Practical implications The insights provided by this study can help smartwatch providers formulate
better growth strategies. The findings also provide some directions for further development.
Originality/value This study provides a better understanding of how the factors in the theories influence
the adoption intentions of Apple watches and non-Apple watches.
Keywords Task-technology fit, Apple watch, Innovation diffusion theory, New product adoption,
Openness to experience, Smartwatches
Paper type Research paper
Introduction
With the development of the Internet of Things, wearable devices have become one of the
most popular technology products. According to a 2014 survey by the Nielsen Corporation,
70 percent of Americans are familiar with the concept of wearable devices. Smartwatches
are particularly popular (Nielsen, 2014). Annual shipments of wearable devices are predicted
to increase 500 million units by 2020 (Gartner, 2015).
Smartwatches can connect with smartphones and receive a lot of information, such as time,
text messages, schedules, and GPS data. While it can perform basic data and communications
tasks, it is also capable of running mobile applications. Users can download and install the
various applications they need via the smartwatchs operating system. Two of the most popular
operating systems are Googles Android Wear and Apples watchOS. The users of Googlesand
Apples operating systems have been shown to be different. According to a survey by
American business magazine Forbes (2014), Apple device users are typically businesspersons
and have a higher level of education and income than the users of the Android system.
Therefore, the factors that influence the users to adopt one of these two operating systems are
expected to be different. Smart device manufacturers have a strong interest in understanding
these factors and exploring ways to increase usersintention to adopt smartwatches.
As the popularity of smartwatches has increased, so as the number of people adopting
these products. Rogers (1995) indicated that product attributes are key factors that influence
Library Hi Tech
Vol. 35 No. 1, 2017
pp. 186-206
© Emerald PublishingLimited
0737-8831
DOI 10.1108/LHT-09-2016-0105
Received 27 September 2016
Revised 15 October 2016
Accepted 26 October 2016
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0737-8831.htm
The author would like to thank the Ministry of Science and Technology of the Republic of China for
supporting this study financially (Contract No. 105-2410-H-025 -009).
186
LHT
35,1
usersadoption of a product. Adventurous and creative consumers are more likely to adopt
new technologies or innovative products. Past research has typically adopted innovation
diffusion theory (IDT) and the new product adoption (NPA) model to explore the adoption
factors. Holak (1988) found that the intention to adopt is affected by NPA model variables,
such as product attributes, consumerspersonality traits, and the environment. Yoon and
Steege (2013) also found that the personality trait of openness has a positive effect on the
intention to use online banking. Moreover, Islam (2016) found that the compatibility of a
learning management system will influence studentslearning performance and usage
intention, in accordance with IDT.
Since smartwatches can receive data and install mobile applications to facilitate daily
tasks, the task-technology fit (TTF) model can be used to explain the reasons behind
smartwatch usage (Chung et al., 2015). Several recent studies have explored the
motivations for adopting smartwatches from a variety of perspectives, such as the
technology acceptance model and system qualities (e.g. Kim and Shin, 2015; Tam and
Oliveira, 2016). However, few of these studies have integrated TTF, IDT and the NPA
model to examine the possible factors affectingsmartwatchusage.Therefore,thepurpose
of this study is twofold: first, an integrated model will be developed based on TTF, IDT
and the NPA model in order to explore the factors that affect smartwatch usage and
second, the differences in the factors that affect usersintention to adopt the Apple Watch
and other smartwatches will be examined.
Literature review
IDT
IDT notes five key characteristics of innovations: relative advantage, complexity,
trialability, compatibility, and observability (Rogers, 1995). Relative advantage refers to the
perceived benefits gained by an innovative product as compared to its precursor.
Complexity refers to the extent to which the innovative technology is difficult to learn.
Compatibility refers to the degree to which an innovation is perceived as being accordant
with existing tools, and the needs and past experiences of potential adopters. Trialability is
the degree to which an innovation can be explored or tested on a limited basis. Observability
is the degree to which the outcomes of an innovation are visible to potential adopters.
These five characteristics have been widely used by recent studies to explore the
adoption of innovative products. For example, Shim et al. (2016) found that observability,
relative advantage, compatibility and complexity affect e-reader adoption in different
decision-making stages. Agag and El-Masry (2016) indicated that the relative advantage,
compatibility and complexity are positively related to consumersintention to purchase
travel online. Li (2014) found that the relative advantage and compatibility positively
influence usersadoption of tablet and laptop personal computers, respectively.
In particular, the relative advantage, complexity and compatibility have been found to be
the most important innovation characteristics of information systems (Kim and Ammeter,
2014). Busselle et al. (1999) pointed out that a combination of lower complexity and a greater
relative advantage increases usersintention to adopt new technology. Liao et al. (1999)
found that the compatibility and a greater relative advantage increases userspositive
attitude regarding the usage of a new technology. Therefore, we integrated these three
characteristics into our research model.
NPA model
Holaks (1988) NPA model proposes that consumersadoption intention is affected by
perceived product attributes, consumer traits, and environmental variables. The term
product attributesrefers to specific product design or promotional features. Consumer traits
include demograph ic and psychological traits, such as e ducation and openness to experience.
187
Comparing
Apple and non-
Apple watches

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