Elsevier

Computers in Human Behavior

Volume 70, May 2017, Pages 131-142
Computers in Human Behavior

Full length article
Identifying design feature factors critical to acceptance and usage behavior of smartphones

https://doi.org/10.1016/j.chb.2016.12.073Get rights and content

Highlights

  • Nine factors were extracted as critical design features of users' preference for smartphones.

  • PEOU was significantly related to Smartphone characteristics, Touch feedback, and Display screen.

  • PU was significantly related to Smartphone characteristics, Application and PEOU.

  • The intention to use was significantly related to Smartphone characteristics, PEOU and PU.

  • The proposed measurement model could explain 76.5% of variance in the usage behavior of smartphones.

Abstract

Smartphones are increasingly used all over the world. However, the effects of smartphone design features on smartphone acceptance and usage behavior are not well known. Thus, in this study, a questionnaire was constructed to identify design feature factors that are critical to the acceptance and usage behavior of smartphones. A total of 842 participants completed the questionnaire. Acceptance was measured on the basis of perceived ease of use (PEOU), perceived usefulness (PU), and intention to use (IU). Results of exploratory factor analysis indicated that users’ preference for smartphones consisted of the following nine factors: Interface element design, Smartphone characteristics, Physical characteristics, Touch feedback, Operation design, Display screen, Connectivity, Button, and Application. Results of hierarchical regression analysis indicated that Smartphone characteristics, Touch feedback, and Display screen significantly influenced PEOU. PU was significantly related to Smartphone characteristics, Application, and PEOU. IU was significantly associated with Smartphone characteristics, PEOU, and PU. The usage behavior of smartphones was significantly related to Connectivity, Interface element design, PEOU, PU, and IU. The proposed model comprising demographic variables, design features, and acceptance-related variables could explain 76.5% of the variance in the usage behavior of smartphones.

Introduction

A growing number of people around the world have been using smartphones. In 2015, sales of smartphones to end users reached 1.4 billion (Statista, 2016). Nearly half of worldwide mobile-phone users are expected to use smartphones by 2017 (Srivastava, 2014). Smartphones have unique characteristics that make them suitable communication devices and powerful tools to process multimedia information (Westlund, 2010). The following are typical characteristics that distinguish smartphones from traditional mobile phones: smartphones have an advanced operating system (OS) and can run various applications (Middleton, 2010), they are usually equipped with a touch screen (Henze, Rukzio, & Boll, 2011), and they always enable users to access the Internet (Kim, Briley, & Ocepek, 2015).

Smartphones are becoming an integral part of modern life (Oulasvirta, Rattenbury, Ma, & Raita, 2012). As smartphones have advanced features such as Internet connection and installation of third-party applications, the usage behavior of smartphones presents two new patterns that are different from the usage behavior of traditional mobile phones. First, users spend more time on the Internet through smartphones than through personal computers. Based on a survey by Nielsen (2014), adults in the United States spend an average of 34 h per month using the Internet on smartphones, whereas they only spend around 27 h using the Internet on PCs. Second, applications consume most time spent using smartphones, especially applications in social, communication, and entertainment categories (Nielsen, 2014). However, with the increasing penetration of smartphones, researchers have found that excessive use of smartphones may lead to the issue of nomophobia. Nomophobia refers to the discomfort or anxiety caused by the non-availability of a smartphone, computer or any another communication device (King et al., 2013). Not being able to communicate, losing connectedness, not being able to access information, and giving up convenience are four dimensions of nomophobia (Yildirim & Correia, 2015).

Acceptance of smartphones is primarily a result of the unique features provided by the devices (Fazal-e-Amin, 2014). To satisfy users' requirements and differentiate their products from those of competitors, manufacturers have been adding more features to smartphones (Head & Ziolkowski, 2012). As an integrated platform that can provide advanced utilities, smartphones provide users with the opportunity to enjoy several new additional features at a low cost. Meanwhile, the value-added features of smartphones increase the product feature complexity (Zhang, Rau, & Salvendy, 2010), requiring greater user-decision effort and making the product more difficult to use. Moreover, excessive features can make a product overwhelming and reduce user satisfaction (Head & Ziolkowski, 2012). To find a tradeoff between two sides, designers must understand the features that satisfy users' preference for smartphones. With this knowledge, smartphone manufacturers could exert additional effort to improve users’ preferred features in smartphone design, while providing less attention to less preferred features, thereby producing smartphones more accepted by users.

Several models, such as theory of reasoned action (TRA) (Fishbein & Ajzen, 1975), theory of planned behavior (TPB) (Ajzen, 1991), technology acceptance model (TAM) (Davis, Bagozzi, & Warshaw, 1989), diffusion of innovation (Rogers, 1995), and unified theory of acceptance and use of technology (UTAUT) (Venkatesh, Morris, Davis, & Davis, 2003), have been used to explain people's acceptance and usage behavior of technology. Among the aforementioned models, TAM has been confirmed to be robust and powerful in evaluating technology acceptance. Most previous studies that used TAM focused on the influences of psychological factors (e.g., self-efficacy, anxiety, and innovativeness) on the acceptance and usage behavior of smartphones (Chen and Chan, 2014, Kim et al., 2010, Park et al., 2013). Aside from users' self-cognition and perception, the interaction devices themselves, especially the design features (e.g. the interface design and physical parameters) can influence their perceived usability (Zhang et al., 2010), which can also affect acceptance and usage behavior. However, few studies have examined the influence of design features on the acceptance and usage behavior of smartphones.

In short, the present study has three objectives. The first objective is to identify critical design feature factors that could explain users' preference for smartphones; second, to investigate the influences of design feature factors on smartphone acceptance as measured by PEOU, PU, and intention to use (IU); and third, to examine the relationships between design feature factors, acceptance, and usage behavior of smartphones and to construct a theoretical model explaining the usage behavior of smartphones. The results will help practitioners gain a systematic understanding of users’ preference for smartphones and place significant emphasis on the critical design feature factors in smartphone design.

Section snippets

Technology acceptance theories and usage behavior of smartphones

The technology acceptance and usage is a complex, inherently social, developmental process and individuals' perceptions of technology can influence the usage process (Straub, 2009). Theoretical models such as TRA (Fishbein & Ajzen, 1975), TPB (Ajzen, 1991), TAM (Davis et al., 1989), diffusion of innovation (Rogers, 1995), and UTAUT (Venkatesh et al., 2003) are often used to explain people's acceptance and usage behavior of technology. Among all models and theories related to technology

Questionnaire construction

The questionnaire consisted of four parts, i.e., demographic information, users' preference for the design features of smartphones, users' acceptance of smartphones, and users’ usage behavior of smartphones.

Descriptive statistics

The demographic information of the 842 participants was summarized in Table 2. Among the 842 participants, 378 were males and 464 were females. Their age ranged from 20 to 51 years old (M = 31.6, SD = 6.7). The questions, “Choose the operating systems you are currently using” and “Choose the ways you connect to mobile Internet through smartphones” were two multiple-choice questions. The mean smartphone usage experience of these participants was four years. The participants used smartphones for

Relationships among design features, acceptance, and usage behavior of smartphones

The present study showed that users' preference for smartphones consisted of nine design feature factors: Smartphone characteristics, Connectivity, Touch feedback, Application, Interface element design, Operation design, Display screen, Button, and Physical characteristics. These factors accounted for 65.6% of the total variance in users’ preference for smartphones. The study also examined the relationships between design feature factors, acceptance, and usage behavior of smartphones. Results

Conclusions

A nine-factor model was constructed to describe users' preference for smartphones. The model comprised the following factors: Interface element design, Smartphone characteristics, Physical characteristics, Touch feedback, Operation design, Display screen, Connectivity, Button, and Application. The nine-factor model explained 65.6% of the total variance in users' preference for smartphones. Hierarchical multiple linear regression results showed that the design feature factors critical to the

Acknowledgements

This work was supported by one grant from the Natural Science Foundation of China [project number 71471098] and one grant from National Key Technology R&D Program of the Ministry of Science and Technology [project number 2014BAK01B03].

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