Elsevier

Computers in Human Behavior

Volume 63, October 2016, Pages 899-905
Computers in Human Behavior

Consumer valuation of the wearables: The case of smartwatches

https://doi.org/10.1016/j.chb.2016.06.040Get rights and content

Highlights

  • Consumers’ recognition of smartwatches, one type of wearable, is increasing.

  • Smartwatch functions are more important to users than brand and price.

  • Display shape and standalone communication are more critical functions.

  • A curved display shape is most preferred.

Abstract

Wearable devices indicate objects encompassing both mobile computing and fashion characteristics. Although the combination of the two characteristics is relatively new, consumers’ recognition of smartwatches, one type of wearable, is increasing. However, despite the heightened interest in smartwatches, sales are growing more slowly than expected. In order to comprehend this, we should understand potential consumers’ perceptions of smartwatches. This study explored how much potential consumers value various smartwatch attributes by examining their preference structure of the wearable. The preference structure was generated from a conjoint analysis including five smartwatch attributes: brand, price, standalone communication, display shape, and display size. We also compared findings by user group (current wristwatch users vs. non-users). Results showed that display shape and standalone communication are more critical factors influencing respondents’ smartwatch choices than brand and price for both types of users. Results also revealed that a curved display shape is most preferred.

Introduction

Since personal computers (PCs) were introduced a few decades ago, computers have become closer to human beings, both physically and psychologically. In the early stages of PCs, computers were mainly used for operational purposes in organizations. After penetrating into homes and being used in daily life, PCs became more familiar to people. Advances in mobile systems and information technology (IT) led to the diffusion of smaller, lighter, and networked computers, and now, most individuals have their own personal devices (i.e., smartphones). For example, over 90 percent of the world’s population owns a mobile phone device, and approximately half of the world’s population uses mobile broadband services (ITU, 2015). Furthermore, wearable computing devices, which are closer to our bodies than mobile phones or notepad computers, have undergone experimentation and have recently begun to be diffused. With wearable computing, sensors and transmission chips are embedded into ordinary objects that are then put on the body (e.g., smart clothing, smart glasses) (Mann, 1997). Wearable devices are distinctive from mobile phones or portable computers, in that wearables work without interruption and are more inextricably intertwined with the human body than prior personal devices (Mann, 2014). Now, as wearable devices are becoming popularized, computers are physically closer to users than ever before.

As the smartphone market is maturing, IT vendors are trying to create new demand for mobile devices, and much of their attention is directed to wearable computing devices. Although experiments on wearables have been conducted since the early 1980s (Mann, 1996), wearables have only recently come into their own as a device for general users. While other types of wearables (e.g., smart clothing, smart glasses, and smart accessories) have not become very popular, the smartwatch is regarded as the first commercialized wearable device for consumers. Smartwatches have been called the next big thing in consumer technology (Sangani, 2013). Leading IT industry players, such as Samsung Electronics, Sony, and Apple, have released diverse styles of smartwatches. Consumers bought 3.6 million smartwatches in 2014, and it is predicted that the purchase volume will grow to 36 million in 2015 and reach 101 million in 2020 (IHS Technology, 2015).

The wide diffusion of the smartwatch is important for the future of wearable computing, in that it is the first step toward commercialized wearables. Furthermore, the success of the smartwatch would spur the IT industry, which is facing a slowdown of growth (Ribeiro, 2014). Nevertheless, skeptical views on the future of smartwatches have been presented. Some analysts maintain that smartwatches do not replace wristwatches or smartphones but are rather an accessory for smartphones (Kendrick, 2013). According to the results of a survey conducted by Harris Interactive (2013), while most U.S. adults have an interest in owning a smartwatch, nearly half of respondents said that smartwatches are just a fad that may not become common. Consumers’ curiosity about this novel product does not seem to negate their doubts about the necessity of smartwatches. The full boom of smartwatches can be achieved through the diffusion beyond the current early adopters to general or potential consumers. In this study, we attempt to explore which smartwatch attributes affect potential consumers’ choice of smartwatches. Specifically, we focus on the effect of five key smartwatch attributes (i.e., standalone communication, display shape, display size, brand, and price) on users’ choices. By providing information about the relative importance of these attributes, the study enables us to understand potential consumers’ assessments of smartwatches, the device currently leading wearable computing.

Section snippets

Key smartwatch attributes

The notion of wristwatches equipped with computing technologies is not new, in that those types of devices appeared in science fiction several decades ago. Although initial computer-based wristwatches (e.g., the Fossil wrist PDA, IBM/Citizen WatchPad, Microsoft’s STOP Watch) were released in the early 2000s, their functional limitations prevented their success (Rawassizadeh, Price, & Petre, 2015). Computer-based watches were not widely adopted until the Pebble watch was successful in 2012.

Conjoint design

Conjoint analysis is a decompositional method that has been widely used to investigate the structure of a consumer’s preference for a multi-attributed product (Green & Srinivasan, 1990). Under the assumption that consumer choice of a product is based on an evaluation of its separate characteristics, conjoint analysis assesses their preference of alternatives, each of which combines levels of attributes. Conjoint analysis has been widely used to investigate consumer preference structure (Chen,

Findings of conjoint analysis

The data were analyzed using SPSS 19 Conjoint. To evaluate the model’s goodness-of-fit, we used Kendall’s tau indicating the correlation between the predicted ranks, which are based on the estimated part-worths, and the actual ranks (Hair et al., 2006). Kendall’s tau was 0.800 (p < 0.000), implying a high goodness-of-fit. Table 3 presents the part-worths of the attributes’ levels and the relative importances of these attributes.

In terms of the relative importances of attributes1

Discussion

Smartwatches have come to the forefront as not only the next killer product following smartphones but also the first popularized wearable device. However, compared to expectations and the degree of consumers’ recognition of smartwatches, the dissemination of smartwatches is being delayed. This study provided knowledge of potential consumers’ perceptions by examining how smartwatch attributes affect their choices. Our findings implied that functional factors, which enhance the independence of

Acknowledgements

This research was supported by the MSIP(Ministry of Science, ICT and Future Planning), Korea, under the CPRC(Communication Policy Research Center) support program (IITP-2015-H8201-15-1003) supervised by the IITP(Institute for Information & communications Technology Promotion). This work was also supported by the National Research Foundation (NRF) of South Korea grant funded by the Korean government (NRF-2013S1A3A2043357).

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