Acceptance and use predictors of fitness wearable technology and intention to recommend. An empirical study

Date04 February 2019
Pages170-188
Published date04 February 2019
DOIhttps://doi.org/10.1108/IMDS-01-2018-0009
AuthorMd Shamim Talukder,Raymond Chiong,Yukun Bao,Babur Hayat Malik
Subject MatterInformation & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems
Acceptance and use predictors of
fitness wearable technology and
intention to recommend
An empirical study
Md Shamim Talukder
Center for Modern Information Management, School of Management,
Huazhong University of Science and Technology, Wuhan, China
Raymond Chiong
School of Electrical Engineering and Computing, The University of Newcastle,
Callaghan, Australia
Yukun Bao
Center for Modern Information Management, School of Management,
Huazhong University of Science and Technology, Wuhan, China, and
Babur Hayat Malik
Department of Computer Science and Information Technology,
University of Lahore, Gujrat Campus, Lahore, Pakistan
Abstract
Purpose The purpose of this paper is to identify the key facilitators and inhibitors of fitness wearable
technology (FWT) adoption and the intention to recommend this technology.
Design/methodology/approach An innovative and integrated research model was developed by
combining constructs from two well-established theoretical models, the extended unified theory of acceptance
and use of technology (UTAUT2) and diffusion of innovation (DOI). The proposed research model was
empirically validated using data collected from 392 respondents in China. The data was analyzed using the
partial least squares method, a statistical analysis technique based on structural equation modeling.
Findings The results indicate that performance expectancy, effort expectancy, social influence, habit,
compatibility and innovativeness have significant direct and indirect effects on FWT adoption and the
intention to recommend it. The significance of peoples intention to recommend FWT to others in social
networking sites (e.g. Facebook, Weibo, and WeChat) is also confirmed.
Practical implications The findings may facilitate the design and implementation of FWT products,
applications and functionalities that can achieve high consumer acceptance and positive recommendations in
social networks.
Originality/value This study is among the first to investigate FWT adoption from behavioral, social and
environmental perspectives. It also highlights the importance of social marketing campaigns and suggests
directions of future wearable technology adoption research.
Keywords Technology adoption, Diffusion of innovation, Intention to recommend,
Extended unified theory of acceptance and use of technology, Fitness wearable technology
Paper type Research paper
1. Introduction
The wide penetration of smartphones and wearable devices has enabled consumers to
monitor, store and transmit information about their physical activities, such as heart rate,
temperature, calories burned and time elapsed since their last physical activity. Fitness
wearables range from fitness trackers, electronic activity monitors, smart wristbands,
Fitbit, Jawbone and smart watches, among others. These devices provide visual
dashboards of usersactivities and can be added with other healthy lifestyle applications,
such as dietary tracking and medical follow-up. It has become an exciting area of
Industrial Management & Data
Systems
Vol. 119 No. 1, 2019
pp. 170-188
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-01-2018-0009
Received 6 January 2018
Revised 15 April 2018
Accepted 13 May 2018
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
170
IMDS
119,1
technology innovation that has received sufficient attention over the past few years, but a
reality check is necessary regarding user acceptability (Subramanian, 2014).
The global wearabletechnology market is expected to growfrom $750m in 2012 to $5.8bn
in 2018 (Research,2014). Despite this forecastedgrowth, Ledger and McCaffrey(2014) showed
that after initial purchases, continuous use of fitness wearables drops to 70 percent after six
months, and to about 55 percent after one year. Theoretical research on fitness wearable
technology (FWT) adoption is thus required to better understand reasons behind this.
To date, however,studies along this line of research have focusedpredominantly on accuracy
and reliability issues (Huang et al., 2016; Diaz et al., 2015; Byun et al., 2016), design and
implementation issues (Zheng et al.,2014;Markovicet al., 2013), as well as wearable device
market dynamics (Wuet al., 2017). In this study, we aim to bridge the gap by understanding
the effects of FWT adoption and explaining peoples intention to use fitness wearables.
The contributions of our study can be summarized as follows: Firstly, we investigated
the direct and indirect effects of antecedents of FWT adoption using an innovative and
integrated research model to increase understanding of the determinants of FWT adoption.
Specifically, we developed a conceptual model that combines the extended unified theory of
acceptance and use of technology (UTAUT2) (Venkatesh et al., 2012) and diffusion of
innovation (DOI) theory (Rogers, 2003) to reinforce the significance and predictability of the
results. Secondly, intention to recommend was introduced to evaluate the success of FWT
adoption within a social network context, which can be of huge market interest (Moe and
Schweidel, 2012), as consumers are increasingly keen to share their opinions about products,
services or technologies on social networks. We recognize the fact that FWT acceptance is
more than the decision of an individual, as social networks provide new directions for
significant diffusion of attitudes and behaviors (Miltgen et al., 2013). To the best of our
knowledge, this is the first time that intention to recommend has been considered in fitness
wearable-related research. This fills a significant research gap in the relevant literature, as
recommending a technology to others is a type of post-adoption behavior that is often
ignored by researchers due to an overwhelming emphasis on use itself (Miltgen et al., 2013).
2. Background
Smartphone use continues to grow at an unprecedented pace. As smartphone technology
continues to evolve, there has also been anincrease in the use of complementary information
technology (IT) and content, such as mobile applications and syncing devices (Nielsen, 2014).
In China, fitnesswearables had a market of $163min 2015, and it was expected to reachmore
than $900m in 2017 (CCTV, 2016). With the market for FWT devices continues to grow,
researchershave responded with a new wave of research,focusing mainly on demand aspects
of the technology.
Kim and Shin (2015) studied the psychological determinants of smart watch adoption.
Their findings indicated that effective quality and relative advantages are associated with
perceived usefulness, while mobility and availability lead to more significant perceived ease
of use. Jeong et al. (2017) explored the effects of product-possessing innovativeness and
information-possessing innovativeness on perceived attributes of wearable technology
(relative advantage, social image, aesthetics and novelty), which influence purchase
intention. Lunney et al. (2016) conducted a study on fitness wearable adoption with the
technology acceptance model (TAM). They found that FWT use is significantly related to
perceived health outcomes. Nasir and Yurder (2015) applied the TAM to investigate
perceptions of physicians and users about wearable health technologies. To validate the
constructs of perceived usefulness and perceived ease of use, they also identified perceived
risk and compatibility as essential factors of acceptance of FWT.
Adapa et al. (2018) took a qualitative approach rather than a quantitative one to explore
the determinants of using smart glasses with two user groups, namely, college students
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Acceptance
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FWT

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