The effects of design,size, and uniqueness of smartwatches: perspectives from current versus potential users

ABSTRACT

This study proposes design, uniqueness, and screen size as the key components of aesthetic appeal and investigates their role in influencing the use behaviour of current smartwatch users and purchase intentions of potential users. Hypotheses were tested using SmartPLS to analyze data collected from 377 current smartwatch users and 361 potential users. Design aesthetics was found to be the most important factor influencing the behavioural intentions of both user groups. Screen size and uniqueness had significant effects on current users’ use behaviour and potential users’ purchase intentions, respectively. Gender moderated the effect of design on the use behaviour of current smartwatch users, such that female users’ behaviour was more likely to be influenced than male users. A subsequent analysis on the moderating effect of brand revealed that the design aesthetics of smartwatches mattered more for Apple than Samsung in terms of promoting use behaviour.     

Personalized detection of user intentions

Interface agents are strategic software components for improving the quality of services to users. In order to be accepted by users, interface agents need to make useful suggestions always in the context of the user’s intention. The user’s intention should be detected as soon as possible so that the agent can define a way to collaborate with the user. Plan recognition can be applied to identify the user’s goal based on his or her actions in the environment. However, classical approaches to plan recognition fail in two main aspects that make them unsuitable for being used by interface agents: the lack of personalization and the lack of consideration of the transition between different goals pursued by the user. We propose an approach to capture intentions taking into account the variables involved in the application domain that represent the user preferences. Experimental evaluations show us that we have found a way for early detection of intentions.     

An evaluation method of outsourcing services for developing an elastic cloud platform

To gain and retain competitive advantages in a competitive business arena, a business cloud-computing platform should continuously strive to offer new services and remain competitive. Unfortunately, it becomes more and more recognized by the industry that a cloud-computing platform could not cover all aspects of IT layers engaged in infrastructure, platform and application. In practice, end users’ requests are nearly unlimited; while the services held by a cloud-computing platform is relatively limited, no matter in service category or in service capacity. In view of this challenge, an elastic cloud platform is investigated by recruited outside services that are absent from the cloud platform. Concretely, through dynamically hiring a qualified service on Internet to replace the absent service inside a cloud platform, an elastic cloud platform could nearly provide unlimited capabilities in an outsourcing service way, e.g., computing power, storage, application functions, etc. At last, the validity of the method is evaluated by a case study.     

Structural analysis of value creation in software service platforms

As software service platforms grow in number of users and variety of service offerings, it raises the question of how this phenomenon impacts the value obtained by users. This paper identifies system usability, service variety, and personal connectivity to be the major determinants that contribute to the value offered to users on mobile software service platforms. A structural equation model, which is based on utility theory, technology acceptance theory, and the theory of network externalities, has been constructed from seven observed constructs, reflecting the three determinants and the user value. The lower bound of user value is estimated through the user’s willingness-to-pay for services and the user’s willingness to spend time on using services. For the validation, a co-variance-based structural equation analysis has been conducted on online survey data of 210 users of mobile service platforms (e.g., Android, iOS). The results show that the number of services used and the number of active user connections were found to be the strongest constructs explaining user value. Perceived usefulness did not explain user value as much. In total, they can explain 49 % of the value that the user receives from the platform. The implication of this result is that users’ value from a software service platform cannot be explained by the technology acceptance model itself. Instead, an approach that, as used in this research, of integrating network externality theory, utility theory, and technology acceptance theory is necessary.     

Adoption Intention of Cloud Computing at the Firm Level

Cloud computing is an advanced technology that firms can use to reduce costs and increase efficiency. However, most firms hesitate to adopt cloud computing. This study investigates the perceived risk of cloud-computing adoption at the firm level and whether cloud-computing knowledge affects adoption intention and decreases risk perceptions. We demonstrate that the knowledge of cloud computing decreases perceived risk, positively affecting the intention of adopting these services. In addition, this study demonstrates that finance, security, technique, and user risks can negatively affect the adoption intention for cloud computing. Finally, this study provides academic and practical advice.     

ARREST: From work practices to redesign for usability

In this paper we discuss the redesign of a support management system deployed in a small and medium sized enterprise (SME) in the UK. The original system was not fulfilling its needs as it had not captured work practices in a way that was recognizable to the users. The advantages of the redesign included: improved usefulness; improved efficiency and productivity; reduced learning time; improved usability; and increased acceptance among users. The system is used to support complex and distributed cooperative activities taking place in an SME. We evaluated the current system and analysed work practices using a user-centred design and evaluation philosophy. In this paper we discuss how user needs are incorporated into the enhanced design of the support management system. The user-centred design techniques used in this research include interviews, questionnaires, observations and user tests. We present comparative evaluation results that show significant improvement in performance of user tasks using the redesigned support management system. The contribution of this paper is the presentation of a case study to show how a user-centred design and evaluation philosophy can lead to better requirements capture resulting in systems that more accurately capture the users’ conceptual models.     

A Model of Green Acceptance and Intentions to Use Bike-Sharing: YouBike Users in Taiwan

With the emphasis on sustainability in transportation, bike-sharing systems are gaining popularity. This paper investigates the attitudes of users of a bike-sharing system with the aim of identifying their priorities, thus allowing local governments to focus their efforts most effectively on enhancing users’ intentions to use such systems. The relationships among green perceived usefulness (the extent to which individuals believe that a bike-sharing system will improve the environmental performance of some part of their life within a specific context), user attitude and perceived ease of use with green intentions, and the mediation effect of user attitude towards bike-sharing are explored. The focus of the study is on how to enhance green intentions via perceived usefulness, perceived ease of use and user attitude of the green technology acceptance model (green TAM) (Davis 1989). The two-step approach of structural equation modeling was applied to analyze the empirical results, which indicated that green perceived usefulness and user attitude have positive influences on the green intentions of 262 users and 262 non-users from ten sampled bike-sharing sites around the central administrative districts of Taipei. However, user attitude has the highest mediation effect on green intentions, and perceived ease of use does not have a significant effect on intentions for either users or non-users. Therefore, governmental institutions can strive to improve the attitudes of bike-sharing users and non-users, their green perceived usefulness, and perceived ease of use to strengthen their intentions to use this mode of sustainable transportation.     

Prediction of individual learning curves across information visualizations

Confident usage of information visualizations is thought to be influenced by cognitive aspects as well as amount of exposure and training. To support the development of individual competency in visualization processing, it is important to ascertain if we can track users’ progress or difficulties they might have while working with a given visualization. In this paper, we extend previous work on predicting in real time a user’s learning curve—a mathematical model that can represent a user’s skill acquisition ability—when working with a visualization. First, we investigate whether results we previously obtained in predicting users’ learning curves during visualization processing generalize to a different visualization. Second, we study to what extent we can make predictions on a user’s learning curve without information on the visualization being used. Our models leverage various data sources, including a user’s gaze behavior, pupil dilation, and cognitive abilities. We show that these models outperform a baseline that leverages knowledge on user task performance so far. Our best performing model achieves good accuracies in predicting users’ learning curves even after observing users’ performance on a few tasks only. These results represent an important step toward understanding how to support users in learning a new visualization.     

Modeling context-aware and intention-aware in-car infotainment systems

It is fundamental to understand users’ intentions to support them when operating a computer system with a dynamically varying set of functions, e.g., within an in-car infotainment system. The system needs to have sufficient information about its own and the user’s context to predict those intentions. Although the development of current in-car infotainment systems is already model-based, explicitly gathering and modeling contextual information and user intentions is currently not supported. However, manually creating software that understands the current context and predicts user intentions is complex, error-prone and expensive. Model-based development can help in overcoming these issues. In this paper, we present an approach for modeling a user’s intention based on Bayesian networks. We support developers of in-car infotainment systems by providing means to model possible user intentions according to the current context. We further allow modeling of user preferences and show how the modeled intentions may change during run-time as a result of the user’s behavior. We demonstrate feasibility of our approach using an industrial case study of an intention-aware in-car infotainment system. Finally, we show how modeling of contextual information and modeling user intentions can be combined by using model transformation.     

基于高斯过程分类器的三维模型多粒度语义检索

为解决三维模型语义检索中用户检索意图不一致问题,建立多粒度语义检索框架,使学习模型能够有效地适应用户的不同检索意图。首先对模型分类知识进行层次划分,形成语义概念的多粒度结构。然后提取一种多视图特征来描述三维模型的形状特性,并采用高斯过程分类器建立不同粒度层次上的学习模型,实现低层特征和查询概念之间的语义一致性描述。和已有研究相比,多粒度语义检索框架使用户可通过语义粒度级别变化进行检索意图设置,从而检索结果尽可能符合用户语义。在实验部分,采用三维模型基准数据库对框架进行算法性能测试。结果表明,检索准确率要明显提高,并且符合人类思维特点。     

Investigating users’ perspectives on e-learning: An integration of TAM and IS success model

The purpose of this paper is to examine an integrated model of TAM and D&M to explore the effects of quality features, perceived ease of use, perceived usefulness on users’ intentions and satisfaction, alongside the mediating effect of usability towards use of e-learning in Iran. Based on the e-learning user data collected through a survey, structural equations modeling (SEM) and path analysis were employed to test the research model. The results revealed that “intention” and “user satisfaction” both had positive effects on actual use of e-learning. “System quality” and “information quality” were found to be the primary factors driving users’ intentions and satisfaction towards use of e-learning. At last, “perceived usefulness” mediated the relationship between ease of use and users’ intentions. The sample consisted of e-learning users of four public universities in Iran. Past studies have seldom examined an integrated model in the context of e-learning in developing countries. Moreover, this paper tries to provide a literature review of recent published studies in the field of e-learning.     

Integrating TTF and IDT to evaluate user intention of big data analytics in mobile cloud healthcare system

ABSTRACT

With the rapid development of mobile technology and cloud computing, observers have recognised the vast potential for mobile cloud healthcare systems in individualised preventive healthcare. Using a mobile cloud healthcare system and big data analysis, this study aids young users in preventive healthcare against diabetes. It also integrates the Task-Technology Fit (TTF) and Innovation Diffusion Theory (IDT) models to evaluate user intentions to use the system, and tests this model using data collected from 423 young people. Results show that task-technology fit is significantly affected by task characteristics and technology characteristics, and also user intention of using the mobile cloud healthcare system is affected by task-technology fit, complexity, and relative benefits. However, observability has no significant effect on user intentions of using the mobile cloud healthcare system. These findings provide some interesting theoretical insights into the usage of the mobile cloud healthcare system. The direct effects of TTF and IDT on young users′ intention of using the mobile cloud healthcare system are shown. This study thus makes an important contribution by highlighting the role that TTF and IDT may have in affecting use of the mobile cloud healthcare system.     

Extending the engineering trade-off analysis by integrating user preferences in conjoint analysis

The ongoing technical improvements in architecture design with improved features of mobile or smartphones do not automatically guarantee user acceptance, because technical and commercial aspects primarily drive the development of mobile communication systems and devices. Especially in early stages of technology development, user preferences and values are not adequately considered, which might even have a negative impact on acceptance issues. The aim of this study was the implementation of a quantified understanding of user needs in terms of values into the system design process of cell-phone processors. Moreover, we aimed for an extension of the engineering’s trade-off analysis by using conjoint analysis in order to investigate trade-offs between specific device characteristics. Finally, our aim was the evaluation of empirically based user-oriented research methods.Results of the first study revealed that battery life, speech quality, signal quality and data-transmission rate are the most important device characteristics. Results from conjoint analysis indicated a clear trade-off between battery life and the three other characteristics. Moreover, this research demonstrated that technology acceptance research benefits considerably from an interdisciplinary and multi-method approach. Besides, implementing the users’ preferences into early stages of the product development process offers several advantages concerning effectiveness as well as economic aspects of development.     

The puzzle of experience vs. memory: Peak-end theory and strategic gamification design in M-commerce

As businesses increasingly use gamified mobile marketing campaign (GMMC) systems to engage mobile shoppers, gamification in m-commerce systems warrants more attention in both IS research and design practices. Inspired by peak-end theory, this study focused on the puzzling differences between user experience vs. memory and empirically examined the impact of different experience orders of cognitive load on user perceptions and behavioral intentions. Overall, the outcomes of this research suggest that appropriate applications of the peak-end effect, moderated via users’ regulatory focus styles, can alleviate the negative mental utility imagery of users, reducing their perceived uncertainties and opt-out intentions from the GMMC. Important implications for research and practice are then discussed.     

The changing nature of user attitudes toward virtual world technology: A longitudinal study

Virtual world technologies have been utilized in gaming for a number of years but only recently have they been applied as a serious tool for business. Many business applications have been identified, including the use of virtual worlds for team collaboration, training, and education, but a question remains about whether users will accept the premise that virtual worlds represent useful environments for engaging in business functions. We address this question by examining user reactions to virtual worlds. The first study looks at attitudes of users of the virtual world Second Life during three time periods (i.e., before exposure to the environment, after an information session and discussion of Second Life, and after use of the environment). Two variables, user acceptance of virtual world technologies and user self-efficacy, were examined as the primary dependent measures. Results show that while self-efficacy increases over time, user acceptance decreases in a highly correlated pattern. A second study investigates the underlying causes of the observed pattern of user acceptance using a content analysis of written reflections of user experiences. Both studies paint a detailed picture of user intentions and some of the reasons these intentions developed after use. The paper concludes with a discussion of the implications of these results for business managers and researchers.     

开源云计算平台研究

Eucalyptus、OpenNebula和Enomaly弹性云计算平台是3个主要的开源云计算软件平台。这些系统的基本功能是为了提供云基础设施服务来管理虚拟机的配置。这些不同的开源项目对那些不希望使用商业提供云的用户提供了一个重要选择。本文对这些系统进行比较详尽的比较和分析,特别分析了反映这些项目各自不同目标的不同特点,以方便用户的选择。     

A parameterized model to select discriminating features on keystroke dynamics authentication on smartphones

Nowadays, smartphones work not only as personal devices, but also as distributed IoT edge devices uploading information to a cloud. Their secure authentications become more crucial as information from them can spread wider. Keystroke dynamics is one of prominent candidates for authentications factors. Combined with PIN/pattern authentications, keystroke dynamics provide a user-friendly multi-factor authentication for smartphones and other IoT devices equipped with keypads and touch screens. There have been many studies and researches on keystroke dynamics authentication with various features and machine-learning classification methods. However, most of researches extract the same features for the entire user and the features used to learn and authenticate the user’s keystroke dynamics pattern. Since the same feature is used for all users, it may include features that express the users’ keystroke dynamics well and those that do not. The authentication performance may be deteriorated because only the discriminative feature capable of expressing the keystroke dynamics pattern of the user is not selected. In this paper, we propose a parameterized model that can select the most discriminating features for each user. The proposed technique can select feature types that better represent the user’s keystroke dynamics pattern using only the normal user’s collected samples. In addition, performance evaluation in previous studies focuses on average EER(equal error rate) for all users. EER is the value at the midpoint between the FAR(false acceptance rate) and FRR(false rejection rate), FAR is the measure of security, and FRR is the measure of usability. The lower the FAR, the higher the authentication strength of keystroke dynamics. Therefore, the performance evaluation is based on the FAR. Experimental results show that the FRR of the proposed scheme is improved by at least 10.791% from the maximum of 31.221% compared with the other schemes.     

Understanding the behavior changes in belief and attitude among experienced and inexperienced learning object users

Prior empirical studies in the implementation of general information technologies (IT) have revealed that IT adoption and usage were determined by user beliefs and attitudes. However, little is known about how user beliefs and attitudes form and change over time. To address these issues, this paper reports a study of 481 inexperienced and 120 experienced potential users on learning objects. Technology acceptance model’s constructs were used to conduct a longitudinal study across three phases (introduction, training and direct-use experience) to examine the formation and the changes in users’ beliefs and behavioral intention to use learning objects over time. The results showed that the rates of changes in users’ beliefs and behavioral intention toward learning objects usage were time-variant and were more predominant during the early stage (introduction to training) of learning objects usage than in the later stages (training to direct-use experience). The study confirmed that initial exposure through introduction and training was effective in improving inexperienced users’ beliefs and intentions to use learning objects. It also helped to reduce the belief and intention gaps that existed between experienced and inexperienced users. In addition, the influence of initial introduction and training on users’ beliefs and perceptions was sustained over time, thus further indicating their importance.     

Do I have to learn something new? Mental models and the acceptance of replacement technologies

Few studies in technology acceptance have explicitly addressed the acceptance of replacement technologies, technologies that replace legacy ones that have been in use. This article explores this issue through the theoretical lens of mental models. We contend that accepting replacement technologies entails both mental model maintenance and mental model building: mental model maintenance enables users to apply their knowledge of the legacy technologies, and mental model building helps users acquire new knowledge and reform their understanding to use replacement technologies. Both processes affect user perceptions about replacement technologies, which in turn affect user intentions to use them. In addition, this study explores how perceived compatibility between replacement and legacy technologies affects both mental model processes. A research model was developed and empirically tested with survey data. The results in general support our arguments. Based on the findings, we offer a few suggestions that can promote user acceptance of replacement technologies.     

Two-channel user authentication by using USB on Cloud

According to parallel computing technology, Cloud service is popular, and it is easy to use Cloud service at everywhere. Cloud means involving application systems that are executed within the cloud and operated via the internet enabled devices. Cloud computing does not rely on the use of cloud storage as it will be removed upon users download action. Clouds can be classified as public, private and hybrid. Cloud service comes up with Ubiquitous; Cloud service users can use their service at anywhere at any time. It is convenient. However, there is a tradeoff. If user’s username and password are compromised, user’s cloud system is in danger, and their confidential information will be in jeopardy. At anywhere and anytime with any device, Cloud user’s credential could be in jeopardy. Security concerns in Cloud play a major role. It is the biggest obstacle to developing in Cloud. However, Cloud is still popular and vulnerability for hacking because of one channel user authentication. Therefore, this research proposes two-channel user authentication by using USB to emphasise security.