User acceptance of wearable devices: An extended perspective of perceived value
Introduction
As information technology (IT) continues to develop, mobile devices are getting smarter and have become essential tools for communication (Wang et al., 2014). Mobile device types are diversifying into classes such as smartphones, tablet PCs, and wearable devices. Wearable devices are attracting much attention as the next generation of portable electronics. Nine out of ten smartphone vendors have already entered the wearable device market or are about to ship their first product, whereas, two years ago, only two vendors were at that stage (Gartner, 2014). The global wearable device market is expected to grow by 78% each year, from 19 million units in 2014 to 112 million in 2018 (IDC, 2014).
Wearable devices are used external to the body, either attached as an accessory or embedded in clothes (Raskovic et al., 2004). They can be used in various applications equipped with sensors, internet connections, processors, and operating systems as well as user-friendly interfaces with touch pads/screens. Watch-type wearable device users can receive e-mail, text messages, and phone notifications on their wrists without having to pull out their cellphones. Wristband or necklace-type wearable devices are mainly used to track the user’s health and fitness status in real time. Head-mount display-type wearable devices are suitable for virtual reality content and 3D games.
Despite the positive prospects and functionality of wearable devices, little research has been done on user acceptance and behaviors concerning them because they are still in the very early stage of commercialization. This study focuses on customers’ perceived value of wearable devices as well as its determinants. Its research model is developed based upon previous research that has studied perceived value by incorporating perceived usefulness, perceived enjoyment, and social image. This study examines users’ perceived value of wearable devices to investigate the impact of each component of perceived benefit and risk on perceived value and to explore how the attributes of wearable devices affect customers’ perceived benefit. This study divides users into potential users and actual users to compare the significant factors influencing perceived value.
Section snippets
Perceived value
Schechter (1984) explained that perceived value is composed of qualitative and quantitative as well as objective and subjective factors that jointly form a buyer’s experience. Dodds et al. (1991) defined perceived value as the ratio of perceived benefit relative to perceived sacrifice. Woodruff and Gardial (1996) described perceived value as a trade-off between desirable attributes and sacrifice attributes. The most widely accepted definition of perceived value is that in Zeithaml (1988), who
Research model and hypotheses development
This study develops the research model shown in Fig. 1. It proposes a comprehensive framework for examining the factors of perceived value for wearable devices. In particular, the proposed model includes four antecedents (i.e., functionality, compatibility, visual attractiveness, and brand name) that reflect the characteristics of wearable devices as high-tech electronic devices and fashion items. This study defined each construct and developed a theoretical rationale for the model’s causal
Data
An online survey was conducted and validated for two weeks in June 2015 before it was used to test the research model and hypotheses. A total of 375 samples (273 potential and 102 actual users) were retained for study after samples with missing or erroneous data were removed. Detailed descriptive statistics for the respondents’ demographic characteristics are presented in Table 1. The samples’ demographic characteristics resemble the Korean Population Statistics collected for Koreans from 10 to
Measurement model
This study employed the partial least squares (PLS) method to test the proposed model and corresponding hypotheses using Smart PLS 2.0, an appropriate method given the sample size, the focus on each path coefficient, and the focus on variance explained rather than overall model fit (Chin et al., 2003).
Confirmatory factor analysis was conducted to investigate the convergent validity of each construct. Table 3 shows the cross-loadings of all items, indicating that they load highest on their
Discussion
This research offers a number of findings. Perceived value had a significant influence on both potential and actual customers’ intention to use, supporting the generally accepted belief that perceived value is a very important factor in consumers’ decision to adopt new products or services (Chen and Dubinsky, 2003, Dodds et al., 1991, Zeithaml, 1988). Therefore, customers must be made to perceive value fully in order to ensure that they will adopt and continuously use wearable devices.
This
Conclusions
This research makes several theoretical contributions. This is the first empirical study to examine the user acceptance of wearable devices, which are at an early stage of diffusion. Most IT adoption studies based on perceived value address mobile service adoption, satisfaction, and loyalty or continuance intention (Kim et al., 2007, Turel et al., 2010). This study extends the application of perceived value to the convergence IT device domain by developing a theoretical model based on customer
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