تاثیر حواس پرتی بر قابلیت استفاده و قصد استفاده از دستگاه های تلفن همراه برای خدمات داده های بی سیم

Abstract Mobile technology has quickly become ingrained in society due to the flexibility of anywhere/anytime usage. However, factors associated with and that impact mobility, mobile users, and mobile use of products and services are still poorly understood. For example, even though distractions are ever present during everyday use of mobile devices, the nature and extent to which user perceptions and performance are affected by their presence is unknown. An empirical study was undertaken to investigate the impact of distractions and confirmation of pre-trial expectations on usability and its subsequent effect on consumers’ behavioral intention toward using a mobile device for wireless data services. Distractions were simulated in this study in the form of either user motion or environmental noise (i.e. background auditory and visual stimuli). A Structural Equation Modelling (SEM) analysis confirmed the impacts of distractions on efficiency and effectiveness, and in turn the users’ satisfaction and behavioral intention to use a mobile device for wireless data services. Support was also obtained for a mediating effect of post-trial confirmation of expectations between perceived performance and satisfaction. Implications of these findings for theory, practice, and future research are outlined.

1. Introduction Mobile devices are becoming increasingly popular, having reached over 5.3 billion mobile subscribers worldwide by the end of 2010 (ITU, 2010 and PBC, 2008). Corresponding wireless data services that have emerged present an important evolution in information and communication technologies (ICTs) (Byoungsoo, Minnseok, & Ingoo, 2009). Coupled with continuous reduction in consumers’ technology fears and lower adoption costs, mobile devices have become “mainstream” around the developed world. Such devices propose increased value to consumers due to “anytime/anywhere” connectivity, communication, and data services. Although progress has been made in terms of technological innovations, many mobile subscribers are still concerned with the usability, reliability, and security of mobile applications and services (Coursaris & Hassanein, 2002). Key usability challenges include technology issues with respect to interface attributes, such as limited screen size, limited input methods, and navigation difficulties (Persson Waye, Bengtsson, Kjellberg, & Benton, 2001). Additionally, the mobile user has to share his or her attention between the task (application) and the surrounding environment. Furthermore, individual characteristics (e.g. age, culture) may be key factors in their ability and preferences to use a mobile device. The concept of context of use as it relates to usability emerged out of the work of several researchers (e.g., Baker and Holding, 1993, Bevan and Macleod, 1994, Coursaris and Kripintiris, 2012, Coursaris et al., 2008, Lee and Benbasat, 2003 and Tarasewich, 2003), who suggested that many variables beyond the immediate interface might impact usability. Although the definition of context may be slightly varied, the takeaway is that usability experiments need to consider various contextual factors ( Liu & Li, 2011). In particular when assessing the usability of mobile devices and services, the following factors should be considered (adapted from Hassanein & Head, 2003): • User (e.g. prior relevant/computing experience, age, education, culture, motion). • Environment (e.g. lighting, noise, visual distractions of other objects or people). • Task (e.g. complexity, interactivity). • Technology (e.g. interface design, input/output modes, device size, weight). The results of such contextual usability studies should guide the design of mobile devices and services resulting in better user satisfaction and consequently higher rates of adoption for such devices and services. Adherence to a rigorous research design would constrain most studies to the investigation of only one (or slightly more) of the aforementioned factors, e.g. user motion. Even though user motion is only one attribute of a potential human–computer interaction (HCI), its inherently dynamic effects on other HCI attributes (e.g. input mode) augment a user’s experience significantly from that of a desktop-based system use. With user motion comes the exposure to constantly changing visual and auditory stimuli. These stimuli effectively become distractions as users interact with mobile devices and their performance and experience with the services may be impacted significantly. Designing mobile interfaces and services should be informed so that they afford users greater capacity in this respect. Thus, this burgeoning research domain is guided by the need to explore the characteristics of mobility, develop new design principles for mobile systems, propose novel mobile usability evaluation techniques, and consequently to obtain a better understanding of, hence, improve mobile use (Biela et al., 2010 and Heoa et al., 2009). This paper explores the impact of context on the usability of mobile devices. Specifically, the paper empirically investigates the impact of distractions as well as the post-trial confirmation of users’ initial expectations of performance on the usability and the subsequent effect on consumers’ behavioral intention to use a mobile device for wireless data services. Distractions are ever present during everyday use of mobile devices, yet the nature and extent to which user perceptions and performance are affected by their presence remains unknown. Similarly, the relationship between pre-trial expectations from and post-trial perceptions of usability has received limited attention in the context of wireless data services. This study will contribute to theory through an extension of usability theory, by considering cognition and by additionally testing the applicability of the Expectancy-Confirmation Theory (EDT) in explaining a mobile user’s evaluative process of usability. Furthermore, this study contributes to practice by providing a better understanding of contextual usability factors that influence consumer adoption of mobile devices and wireless data services and hence can inform improved design of these devices and services.

5. Conclusions This paper proposed a new model to further understanding of mobile usability. Specifically, distractions and user expectations were examined for their potential impacts on usability dimensions and, ultimately, on behavioral intention to use mobile services. Implications for both theory and practice are described next. 5.1. Implications for theory From a theoretical point of view, this work contributes to usability research by providing a better understanding of the impacts of auditory, visual and motion distractions on the use of mobile devices for wireless data services. We found that such distractions do have a significant negative impact on the perceived efficiency and effectiveness of mobile device use, a finding that is consistent with research findings regarding the negative effect of distractions on driving performance (Ljungberg et al., 2004). While controlled laboratory studies help to ensure experimental rigor, academics must remember that usability may be greatly affected by context of use. This is particularly true for mobile devices, where distractions are more likely to occur while users are ‘on the move’ in the environment. Our experimental design attempted to approximate real-world scenarios for the tested product and services, while upholding a rigorous methodology, and can serve as an example for future empirical research on mobile usability. With respect to ECT, and in alignment with (Babakus & Boller, 1992) who studied satisfaction with utility services, we observed performance as a stronger predictor of satisfaction than the confirmation of pre-trial expectations was, this time in the context of a mobile device for wireless data services. This study also reinforces the positive relationship between usability and satisfaction previously validated in screen web experiences and website loyalty (Casaló et al., 2008) this time supported in the context of wireless data services. 5.2. Implications for practice For practice, this study’s results have direct implications for designers and retailers of mobile devices. By decomposing satisfaction we offer relevant insight as to which performance dimension (i.e. efficiency) becomes critical in personal use decisions for a mobile device. Learnability, ease of use, and time required to complete a task are prevalent dimensions in the decision making process of using a mobile device for wireless data services, while successful task completion seems to be less relevant. Thus, complex interfaces that offer enhanced capabilities while having a toll on the efficiency of a mobile device may deter a consumer from using it. This observation is in agreement with the findings of Rust, Thompson, and Hamilton (2006), who also call upon device developers to avoid “feature fatigue”, i.e. overwhelming users by adding device functionality that leads to increased use complexity and product dissatisfaction. Such dissatisfaction often leads to product returns, customer attrition, and/or negative effects on brand equity. If repeat business, i.e. increasing the life-time value of the customer, is the goal, manufacturers are better off producing a device that is simple and easy to use than a “powerful” all-in-one device (Marcus, 2003). Additionally, strong beta coefficients and corresponding t-values indicate that women may be affected more by distractions than men, which is in agreement with the results of Bruni’s (2004) work, who examined the impact of instant messaging on task performance. If women are less robust to distractions than men in the context of using a mobile device for wireless data services, it is likely that such applications, both professional and leisurely, will not be as popular with women. Hence, manufacturers could arguably capture a market opportunity by designing different interfaces or offering special tools/accessories for mobile devices geared towards increasing usability for women. Similarly, usability and accessibility become imperative design considerations for devices aimed at older users, who were found to be more susceptible to distractions. Furthermore, the differences found in this study among user groups in terms of performance, satisfaction, and intention to use wireless data services highlight the importance of targeted marketing communications, thereby creating realistic product expectations for each user group. In addition, businesses providing decision aids, such as recommendation agents that help identify a user’s real needs, may help increase the prominent importance of usability in the purchase decision (Chin, 1998, Chin and Gopal, 1995 and Rust et al., 2006). Additionally, closing the gap between pre- and post-use consumer preferences may lead to higher product satisfaction, repeat business, and favorable effects on brand equity. 5.3. Limitations As with all experimental studies, there are limitations for this study, which can prompt future research in this area. First, the study’s tasks were simulated in a laboratory setting. Thus, any sense of urgency or other contextual responses that a user may experience in a real-setting may not arise here, other than those triggered by mobility, the visual and auditory environment. While this is a limitation in terms of the realism of the study, it is a means of controlling for additional variables that could not be otherwise measured during the experiment. Second, the experiment was carried out using one particular mobile device (RIM’s Blackberry) with one particular interface input mode (QWERTY keyboard). Results from this study should be validated across multiple mobile devices and interface input modes. Third, the experiment was conducted in a Canadian context and should not be generalized to other cultures before further validation. 5.4. Future research Given the interdisciplinary nature of this study, several opportunities emerge for future research. First, a study could collect both device- and self-reported data regarding the efficiency and effectiveness of mobile devices at the task level. This study would then compare these data sets so that conclusions could be drawn for each task (or application) independently. Thus, a closer attention between the measurement of perceived (self-reported) and objective (device) data is needed. A more focused investigation for performance-related attributes (e.g. time, learnability, error rate, success rate, etc.) is also warranted. By conducting mobile usability studies that triangulate between self-reported, observed, and device data, analyses would be richer and with greater external validity (i.e. closer to the ‘real world’). From the finding that gender influences the perceived effectiveness of a mobile device for wireless data services, future research could further explore the impact of gender on expectations of mobile devices. If women have lower initial expectations than men do, then the differences found here in terms of perceived effectiveness would be further supported. Beyond gender, studies could explore the effects of cultural traits on the motivations, adoption, and user experience with wireless data services, as was the recent effort by Lee, Kim, Choi, and Hong (2010) with a focus on the mobile Web. Marketing practices would be better informed through the results of such studies, guiding the gender-specific and culturally-appropriate tailoring of marketing communication messages for wireless data services.