Relationship between acceptance of smartphones and its influence on users’ behavior among university’s students - Soo, Poh Lee (2016)
Smartphones have been the key drivers in shaping the consumer technology in the world of how human communicate, consume information, seeking leisure and entertainment and managing daily lives routine. It has become a perceived necessity in people’s daily lives nowadays and played an important role in many aspects of human daily activities that include home activities, personal, education, social networking and many others. However, spending too much time and excessive use on smartphone introduced some notable drawbacks. It becomes distractors and impacting users to be out of focus in delivering daily core activities. The main objective of this study is to examine the relationship between acceptance of smartphone towards it influence associated with smartphone stress, dependency and addiction on users’ behavior. As for the research methodology, the quantitative research method was employed to quantify the data and provide conclusive evidence. This was conducted through a set of questionnaires distributed by hand to 405 undergraduate students from both public and private higher education institutions in Selangor. Technology Acceptance Model (TAM) proposed by Davis (1989) was used as the theoretical framework for this study in order to determine the key determinants of smartphone acceptance while Pearson Correlation Analysis was used to determine the extent of associations between the independent variables and dependent variables. The overall results from this study evident that Perceived Usefulness (PU) and Perceived Ease of Use (PEU) significantly influence undergraduate students’ behavior on smartphone. The more useful and ease of use a technology is, the more it will accept by undergraduate students. This implies that PU and PEU influence the user’s behavior as well as associate the stress, dependency and addiction of smartphone usage. However, it was observed that the relationships on users’ behavior were weak based on Guilford’s Rule of Thumb. The implications of these findings warrant further future in-depth studies.