An e-Commerce framework for wearable devices

The main drawback of pervasive computing is the lack of infrastructure on which ubiquitous applications should be deployed on. The deployment of the resources required by pervasive computing require expensive hardware. These considerable disadvantages led to the area of wearable computing. In this poster we briefly describe our work in the area of wearable computing, were we apply some major concepts of ubiquitous commerce to achieve a generic e-commerce framework that can be used by any wearable device.peer-reviewe

Development of Innovation Acceptance Model for Wearable Computing: A Study of Users’ Technology Acceptance in Malaysia

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonWearable computing is becoming a phenomenon of emerging innovation which once started from the early era of personal computers. Since then, it has grown to sophisticated wearable smart devices which has promising prospects in this information age and is expected to become mainstream after the phenomena of the mass market adoption of smartphone usage, especially in Malaysia. However, in terms of users’ acceptance, wearable computing is still at its infancy stage. This research study examines the development of a conceptual framework to understand the influencing factors for users’ acceptance of wearable computing by utilising the integration of Technology Acceptance Model (TAM), the Diffusion of Innovation Theory (DOI) and related factors on mobility and pervasive computing. This research evaluates wearable computing from the potential users’ perspective about technological innovation acceptance. It is a challenging field to predict the factors that may drive potential users to accept this new emerging technology, thus expanding innovation diffusion. Data of 272 respondents were collected in the Malaysian region by employing the quantitative approach of a survey-based questionnaire as the dominant method and was analysed using IBM SPSS software (V.20). A qualitative approach was also conducted to support those quantitative findings. Empirical findings from regression analysis revealed the strongest and unique contribution of predicted factors were perceived usefulness; mobility linked with observability; perceived enjoyment linked factor with personalisation and facilitating conditions that may significantly influence the potential users to accept wearable computing. Conversely, perceived ease of use was not significantly influencing the users’ acceptance of wearable computing. The total variance explained by the model factor is 61 percent (R square=61%) of users’ acceptance of wearable computing. The findings and the development of this framework will give more insight and contribute to the body of knowledge in understanding the innovation of wearable computing, thus improving innovation diffusion