Explicating Consumers’ Adoption of Wearable Technologies

This research aims to determine the key antecedent factors in consumers’ adoption of and their intention to recommend smartwatch wearable technology. The proposed research model combines the current technology acceptance and innovation diffusion theories with perceived aesthetic and perceived privacy risk to explain individuals’ smartwatch adoption and subsequent recommendation to other people. Based on a sample of 299 completed individual online surveys, the research employed partial least squares (a variance-based analysis method) for the model and hypotheses testing. The results showed some similarities as well as differences from the previous literature. The study found that performance expectancy, habit, and perceived aesthetic were the main predictors of smartwatch adoption. Compatibility was the antecedent factor of performance expectancy, and innovativeness directly influenced user adoption and effort expectancy. Consequently, user smartwatch adoption usually led to recommendation.

Using Depth Cameras for Recognition and Segmentation of Hand Gestures

In recent years, in combination with technological advances, new paradigms of interaction with the user have emerged. This has motivated the industry to create increasingly powerful and accessible natural user interface devices. In particular, depth cameras have achieved high levels of user adoption. These devices include the Microsoft Kinect, the Intel RealSense, and the Leap Motion Controller. This type of device facilitates the acquisition of data in human activity recognition. Hand gestures can be static or dynamic, depending on whether they present movement in the image sequences. Hand gesture recognition enables human-computer interaction (HCI) system developers to create more immersive, natural, and intuitive experiences and interactions. However, this task is not easy. That is why, in the academy, this problem has been addressed using machine learning techniques. The experiments carried out have shown very encouraging results indicating that the choice of this type of architecture allows obtaining an excellent efficiency of parameters and prediction times. It should be noted that the tests are carried out on a set of relevant data from the area. Based on this, the performance of this proposal is analysed about different scenarios such as lighting variation or camera movement, different types of gestures, and sensitivity or bias by people, among others. In this article, we will look at how infrared camera images can be used to segment, classify, and recognise one-handed gestures in a variety of lighting conditions. A standard webcam was modified, and an infrared filter was added to the lens to create the infrared camera. The scene was illuminated by additional infrared LED structures, allowing it to be used in various lighting conditions.

Evaluating the user perceived usefulness of Enterprise Social Networking

<p>This paper aims to identify user perceived usefulness of enterprise social networking within the public and private sector of Wellington NZ. It aims at determining the specific factors that appeal to enterprise social networking users. This paper first outlines the global trend towards enterprise social networking based on academia and IT industry papers. It draws parallels between ESN and KM to better understand the unique attributes of ESN. In particular it brings to focus the social nature of ESN and the use of modern technologies that facilitate ease of use. It also highlights the community nature of ESN and its importance in managing knowledge security, quality, trust and sense of sharing. These dimensions help form the basis on which the interview questions are based. Anti- positivism philosophical approach is used to peer into user perceptions and make sense of the research findings. Qualitative data shall be gathered through interviews. 7 participants will be involved in the interviews. Participants will be a mixture of MIM students and IT professionals employed within the private and public sector. The outcome of this study is to better understand contemporary views on the topic and shape future direction in better dissemination of enterprise social networking in the local industry. The focus on what the user perceived usefulness of social networking within wellington will give insights into user adoption strategies for enterprise social networking.</p>

Evaluating the user perceived usefulness of Enterprise Social Networking

<p>This paper aims to identify user perceived usefulness of enterprise social networking within the public and private sector of Wellington NZ. It aims at determining the specific factors that appeal to enterprise social networking users. This paper first outlines the global trend towards enterprise social networking based on academia and IT industry papers. It draws parallels between ESN and KM to better understand the unique attributes of ESN. In particular it brings to focus the social nature of ESN and the use of modern technologies that facilitate ease of use. It also highlights the community nature of ESN and its importance in managing knowledge security, quality, trust and sense of sharing. These dimensions help form the basis on which the interview questions are based. Anti- positivism philosophical approach is used to peer into user perceptions and make sense of the research findings. Qualitative data shall be gathered through interviews. 7 participants will be involved in the interviews. Participants will be a mixture of MIM students and IT professionals employed within the private and public sector. The outcome of this study is to better understand contemporary views on the topic and shape future direction in better dissemination of enterprise social networking in the local industry. The focus on what the user perceived usefulness of social networking within wellington will give insights into user adoption strategies for enterprise social networking.</p>

Using Performance Predictions to Evaluate Two-factor Authentication Setup Processes

Low user adoption due to usability issues during setup is one of the primary challenges facing two-factor authentication implementations. A method which could quickly provide performance predictions for two-factor authentication setup processes would help create opportunities for iterative improvements during the design phase. These improvements can lead to increased human performance in the two-factor authentication setup processes once implemented and may help address some of the usability challenges that plague two-factor authentication user adoption efforts. Various software-based prediction tools can help simulate human performance and analyze underlying usability issues. The challenge is to evaluate human performance quickly and iteratively in two-factor authentication setup processes to help improve the usability of the processes during the design phase. We demonstrate rapid software-based performance predictions for three two-factor authentication setup processes and compare them to previously published human performance data for insights.

User Needs of Smart Home Services

Technological advances have improved the functionality of smart home systems and services, enabling consumers to automate some of in-home tasks, enhance their safety and security, and save energy. Despite improved functionality, user adoption of many available products and services remains low. This phenomenon suggests that smart home technologies may not be meeting the needs of potential users. Furthermore, continued technological advancement combined with changes in people’s lifestyle and attitudes towards in-home technologies require updated investigations to gain a clear view of current user needs. This study presents findings from a set of semi-structured interviews and card-sorting activities with eleven participants from different socio-demographic backgrounds, with a focus on describing ten challenges commonly experienced in the home environment. Possible technological solutions are discussed from the existing unmet needs within the scope of smart and connected homes.