The usability of passphrases for authentication: An empirical field study

In developing password policies, IT managers must strike a balance between security and memorability. Rules that improve structural integrity against attacks may also result in passwords that are difficult to remember. Recent technologies have relaxed the 8-character password constraint to permit the creation of longer pass-“phrases” consisting of multiple words. Longer passphrases are attractive because they can improve security by increasing the difficulty of brute-force attacks and they might also be easy to remember. Yet, no empirical evidence concerning the actual usability of passphrases exists. This paper presents the results of a 12-week experiment that examines users’ experience and satisfaction with passphrases. Results indicate that passphrase users experienced a rate of unsuccessful logins due to memory recall failure similar to that of users of self-generated simple passwords and stringent passwords. However, passphrase users had more failed login attempts due to typographical errors than did users of either simple or highly secure passwords. Moreover, although the typographical errors disappeared over time, passphrase users’ initial problems negatively affected their end-of-experiment perceptions.     

QoS-aware service selection via collaborative QoS evaluation

We present in this paper a novel collaborative filtering based scheme for evaluating the QoS of large scale Web services. The proposed scheme automates the process of assessing the QoS of a priori unknown service providers and thus facilitates service users in selecting services that best match their QoS requirements. Most existing service selection approaches ignore the great diversity in the service environment and assume that different users receive identical QoS from the same service provider. This may lead to inappropriate selection decisions as the assumed QoS may deviate significantly from the one actually received by the users. The collaborative filtering based approach addresses this issue by taking the diversity into account instead of uniformly applying the same QoS value to different users. They predict a user’s QoS on an unknown service by exploiting the historical QoS experience of similar users. Nevertheless, when only limited historical QoS data is available, these approaches either fail to make any predictions or make very poor ones. The cornerstone of the proposed QoS evaluation scheme is a Relational Clustering based Model (or RCM) that effectively addresses the data scarcity issue as stated above. Experimental results on both real and synthetic datasets demonstrate that the proposed scheme can more accurately predict the QoS on unknown service providers. The efficient performance also makes it applicable to QoS evaluation for large scale Web services.     

How and why do student teachers use ICT?

This paper examines how and why student teachers made use of information and communication technology (ICT) during a 1‐year initial teacher education programme from 2008 to 2009. This is a mixed methods study involving a survey (N = 340) of the entire cohort and a series of semi‐structured interviews with a sample of student teachers within the cohort (N = 21). The study explored several themes, including the nature of student teachers' use of ICT; variation in the use of ICT; support for, and constraints on, using ICT; attitudes to ICT and to teaching and learning more generally. It was found that nearly all teachers were receptive to using ICT – more so than their in‐service counterparts – and made frequent use of it during their placement (internship) experience. The Interactive Whiteboard (IWB) was central to nearly all student teachers' use of ICT, in good part, because it was already used by their mentors and was widely accessible. Student teachers' use of ICT was categorized in three levels. Routine users focused mostly on the use of the IWB for whole class teaching; extended users gave greater opportunities for pupils to use ICT for themselves; innovative student teachers used ICT in a greater range of contexts and made more effort to overcome barriers such as access. ICT use was seen as emerging from a mix of factors: chiefly student teachers' access to ICT; their feeling of ‘self‐efficacy’ when using ICT; and their belief that ICT had a positive impact on learning – in particular, the impact on pupils' behavioural and affective engagement. Factors which influenced ICT use included mentoring, training and support. Limitations on student teachers' use of ICT are explored and it is suggested that new teachers need to be supported in developing a more discerning use as they begin their teaching careers.     

Identification of Lead User Characteristics Driving the Quality of Service Innovation Ideas

Research indicates that creative ideas provide the seed for successful service innovations. However, little attention has been paid to understanding idea creation, especially for service innovations. Lead user analysis has been shown to provide the highest potential to create attractive innovation ideas. But which characteristics in lead users are important in this regard is still under‐researched. In the realm of an idea contest, we examine the impact of specific lead user characteristics in driving the quality of service innovation ideas. Our study broadens the understanding of which customers are suitable and should be activated for service innovation idea contests. Using the data of 120 ideas resulting from an idea contest for new online services of soccer clubs, our findings demonstrate that specific lead user characteristics affect the quality of service ideas generated. We find that dissatisfaction with existing services has the highest impact on idea quality. Thus, companies should make use of their complaint management database to invite dissatisfied users to participate in idea contests. The results also show that highly experienced users provide ideas of higher quality. Our findings imply that companies should design closed‐membership idea contests so that only people who show specific characteristics can be admitted.     

Everyday use of computer-mediated communication tools and its evolution over time: An ethnographical study with older people

Based on a 3-year ethnographical study, this paper discusses the prolonged use of computer-mediated communication (CMC) tools by approximately 400 older people in an adult education centre in Barcelona (Spain). Contrary to oversimplified views of older people as ICT users, this paper shows that they make a very rich use of CMC tools. Relevant elements of this use are their permanent desire to feel and be included, social, independent and competent ICT users. Despite the numerous interaction issues they face when using ICT, some are constant across different tools. Difficulties due to cognition limit their interactions more severely than those problems due to perceiving visual information or using the mouse. By examining the longitudinal aspect of the study, this paper addresses the evolution of technology use and whether the interaction issues that most of the current older people exhibit will be relevant when today’s more ICT literate young adults grow older. Interaction issues due to cognition are time-persistent, and independent of both experience and practice with ICT. Difficulties reading from the screen or using input devices are overcome with ICT experience. The strategies adopted by older people for coping with all these interaction issues are always targeted at feeling and being included, social, independent and competent ICT users. The results deepen current understanding of tools use in connecting older people with their social circles and the interaction issues most of them encounter when using ICT. The results also suggest that cognitive-related problems will be the most important ones in our work with the next generation of older people.     

Towards a model of consumer use of mobile information and communication technology in LDCs: the case of sub-Saharan Africa

Abstract. Using theories of technology acceptance and technology transfer, we identified factors affecting the use of mobile information and communication technology (mobile ICT) in the least developed countries (LDCs), specifically sub-Saharan Africa. From a literature review, we developed a research model to describe factors that impact mobile ICT use and formulated a series of hypotheses about them. We then surveyed mobile ICT users in Kenya and Nigeria and created a structural model to examine our hypothesized relationships. Our findings indicate that access to mobile ICT, and cultural influences on mobile ICT diffusion, strongly influence individuals' perceptions of the usefulness and ease of use of mobile ICT. Individuals' perceptions about the reliability of mobile ICT influence use of these technologies significantly. The results suggest that, although extensive ICT diffusion (high mobile ICT levels per capita) may be necessary for seeding commercial and economic initiatives that depend heavily on mobile ICT, such as m-commerce, it may not be sufficient. Firms conducting business in sub-Saharan Africa need to pay attention to the factors that explain individual mobile ICT use because these factors will most likely determine the optimal market segmentation, business development and customer service strategies for leveraging m-commerce operations in that region. For government units, the understanding of such factors would also be beneficial in aiding economic planning and commerce.     

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.     

iPad和iPhone数字阅读平台设计简介

随着苹果公司iPad和iPhone产品在全球的热销,在iPad和iPhone大行其道的形势下,如何结合这些新型高科技数码产品为用户提供更加优质的新闻阅读体验与操作体验,成为我们每个报业工作者的使命;该文概要介绍iPad和iPhone数字阅读平台设计背景,总体思路,技术方案与创新成果,实施效果,发现、发明及创新点,与当前国内外同类平台的综合比较。     

新通用顶级域名快速发展对互联网域名产业的影响分析

新通用顶级域名开放注册是互联网域名服务产业的一次重大创新,给产业带来了深刻变革。促进了产业链创新和繁荣,催生了新的细分行业。对互联网品牌用户尤其是广大企业用户而言,是其塑造企业全球品牌价值,开展业务创新的良好时机。     

Employee acceptance of disruptive service innovations at the frontline: The role of collective sensemaking processes

Acceptance of service innovation by frontline employees is a challenging issue, especially if such innovations have the potential to disrupt existing value creation models and individual competencies. Disruptive service innovations are often (1) characterized by a high degree of innovativeness related to significant changes in technology and in the market and (2) may be introduced by technology manufacturers as new service market entrants that cause a competitive threat to the existing service provision. We argue that such innovations challenge frontline employees' focus on routines and standardized service operating procedures. The perceived threat and resulting high levels of uncertainty may inhibit innovation acceptance. Our study follows a collective sensemaking perspective, paying special attention to investigating the moderating role of (1) the exchange of operational information within a workgroup and (2) a firm's entrepreneurial orientation. Whereas the former may increase frontline employees' preference for incremental improvements, the latter may help to increase the acceptance level of potentially more disruptive innovations. We test our theoretically derived hypotheses with an experimental vignette study of 671 frontline employees in the field of audiology, a health care market particularly affected by both more radical and market entrant innovations. Results show that a high degree of innovativeness has a negative effect on innovation acceptance. Frontline employees accept radical innovations less readily than incremental innovations. A competitive threat from new technology manufacturers in the supply chain does not lead to a lower innovation acceptance level. The moderation results indicate significant effects of both information exchange and entrepreneurial orientation. Intensive information exchange within the workgroup strengthens the negative relationship between the degree of innovativeness and innovation acceptance. In contrast, a high degree of entrepreneurial orientation weakens the negative relationship between a competitive threat and innovation acceptance.     

The role of attributional judgments when adopted computing technology fails: a comparison of Microsoft Windows PC user perceptions of Windows and Macs

The bulk of research to date on diffusion of innovations and the user acceptance of computing technology has focused on modelling the factors that lead to a user's decision to adopt and use a technology, instead of how individuals use technology and experience it after adoption. The current paper explores how users rationalise failures in their adopted innovations; their biases in the assessment of competing technologies; and the ultimate influence of these attributions on their interpersonal word of mouth communication with other users. The findings of the research point to the mechanisms of ego enhancement and innovativeness influencing users’ reactions to the failure of their adopted computing technology. Biases regarding competing technologies are, however, influenced by information presented in the mass media. Experienced users and users who are technologically innovative are more likely to exhibit biased optimism towards the technology they have adopted. When such users hear about the failure of the computing technology they have adopted, they are far more likely to blame other users for it. In contrast, less innovative, later adopters of a technology are far more likely to blame their adopted technology and consider it to be inferior.     

Web service reliability prediction based on machine learning

Web service reliability is an important mission that keeps web services running normally. Within web service, the web services invoked by users not only depend on the service itself, but also on web load condition (such as latency). Due to the features of web dynamics, traditional reliability methods have become inappropriate; at the same time, the web condition parameter sparsity problem will cause inaccurate reliability prediction. To address these new challenges, in this paper, we propose a new web service reliability prediction method based on machine learning considering user, web service and web condition. First we solve the web condition parameter sparsity problem, then we use the k-means clustering method to aggregate past invocation data, incorporate user, service, and web condition parameters to build a reliability feedback matrix, at last we predict web service reliability by considering specific web condition environments. The experiment shows that our machine learning method is able to solve the data sparsity problem and improve accurate web service reliability prediction, and we discuss how data sparsity and the number of feedback clusters to affect web service reliability prediction.     

Assessing cloud computing value in firms through socio-technical determinants

While cloud computing is touted as a promising information technology advancement, predictions of its value are inconclusive. This research investigates the impact of cloud computing within-firm and across-firm. Drawing on the resource-based view and sociotechnical theory, technical attributes and social attributes of cloud computing are identified to impact firm performance via primary and support use. Results from data collected from 513 firms show varying effects of technical and social attributes in primary use and support use, which help create value and better performance. Such effects also are found to differ between firms in service and manufacturing sectors.     

e-Learning continuance intention: Moderating effects of user e-learning experience

This study explores the determinants of the e-learning continuance intention of users with different levels of e-learning experience and examines the moderating effects of e-learning experience on the relationships among the determinants. The research hypotheses are empirically validated using the responses received from a survey of 256 users. The results reveal that negative critical incidents and attitude are the main determinants of the users’ intention to continue using the e-learning, irrespective of their level of e-learning experience. In addition, the findings show that the user’s experience of the e-learning service plays a moderating role. The impact of negative critical incidents on perceived ease of use is greater for less experienced users. By contrast, the impact of negative critical incidents on perceived usefulness is greater for more experienced users. Perceived ease of use has a more critical effect on the attitude and continuance intention of less experienced users, whereas perceived usefulness is found to be a stronger determinant of the attitude and behavioral intention of more experienced users. Moreover, the relationship between satisfaction and continuance intention is stronger for less experienced users than for more experienced users. The implications of the present findings for research and managerial practice are analyzed and discussed.     

一种基于用户情境的QoS预测方法

完整的QoS信息有利于更准确的服务推荐,但是现实中往往很难得到。文章提出了一种基于用户情境的QoS预测方法,对于老用户,根据他们原来的QoS选择,考虑QoS类型区别和时间衰减情况,预测新的QoS取值;对于新用户,按照用户分类信息,根据同类用户的服务选择情况,预测他们的QoS取值。实验证明,该方法有助于提高服务推荐的性能。     

Usability,quality, value and e-learning continuance decisions

Previous research suggests that an eventual information technology (IT) success depend on both its initial adoption (acceptance) and subsequent continued usage (continuance). Expectancy disconfirmation theory (EDT) has been successfully used to predict users’ intention to continue using information technologies. This study proposed a decomposed EDT model to examine cognitive beliefs and affect that influence users’ continuance decision in the context of e-learning service. The proposed model extended EDT by decomposing the perceived performance component into usability, quality, and value. Research hypotheses derived from this model are empirically validated using the responses to a survey on e-learning usage among 183 users. The results suggest that users’ continuance intention is determined by satisfaction, which in turn is jointly determined by perceived usability, perceived quality, perceived value, and usability disconfirmation.     

Learning to Predict by the Methods of Temporal Differences

This article introduces a class of incremental learning procedures specialized for prediction – that is, for using past experience with an incompletely known system to predict its future behavior. Whereas conventional prediction-learning methods assign credit by means of the difference between predicted and actual outcomes, the new methods assign credit by means of the difference between temporally successive predictions. Although such temporal-difference methods have been used in Samuel's checker player, Holland's bucket brigade, and the author's Adaptive Heuristic Critic, they have remained poorly understood. Here we prove their convergence and optimality for special cases and relate them to supervised-learning methods. For most real-world prediction problems, temporal-difference methods require less memory and less peak computation than conventional methods and they produce more accurate predictions. We argue that most problems to which supervised learning is currently applied are really prediction problems of the sort to which temporal-difference methods can be applied to advantage.     

Maximizing business information security's educational value

A business information security course's goals and objectives are quite different from most traditional security courses, which focus on designing and developing new security technologies. Business information security primarily concerns the strategic, tactical, and operational management issues surrounding the planning, analysis, design, implementation, and maintenance of an organization's information security program. Core issues include asset valuation, auditing, business continuity planning, disaster recovery planning, ethics, organizational communication, policy development, project planning, risk management, security awareness education and training, and various legal issues such as liability and regulatory compliance. Because businesses can't afford to mitigate all security risks, students must learn methods to identify and justify the optimal amount of expenditures to ensure that their information assets are sufficiently protected. Students should also understand the technical components of security so they can appreciate the problems experienced by the people they manage. This paper describes my experiences in developing a business information security course that provides students the knowledge arid experience to succeed in today's competitive information-intensive corporate environment.     

基于社会网络动态反馈的Web服务信任度计算

在当前服务计算背景下,针对用户难以获得满足需求的可信服务问题,提出基于社会网络动态反馈的Web服务信任度模型.基于用户使用经验设计服务直接信任度算法,对服务交易情况进行动态跟踪和监测.当用户缺乏使用某服务的直接经验时,基于社会网络中服务使用者信任度,聚合其他服务使用者对服务的直接信任度,计算该服务的间接信任度.采用修正因子进行修正,以提高社会网络节点及关联服务可信性.算法分析表明,该方法是可行和有效的.     

The critical aspects of co‐creating and co‐capturing sustainable value in service business models

Numerous researchers and practitioners emphasize the potential to create value through sustainable business models (SBMs). However, little attention has been paid to how sustainable value is proposed, created, delivered, and captured in the organization, and how customers perceive sustainable value in service. The aim of this paper is to explore this research gap empirically through a case study of sustainable value (co‐)creation through SBMs of sustainable service innovations as experienced among two hotels' managers, employees and customers. The contributions of the study relate to the development of SBMs in service, where the value processes happen simultaneously and where the element value perception has to be added to the extant SBM literature, which is closely related to the creation and delivery of physical goods as in product‐oriented industries. The study also contributes through the dual perspective (providers and customers) on sustainable value proposition, value creation and value capture. The findings reveal different key aspects in creating and capturing sustainable value through SBMs and sustainable service innovation. The managerial implications for creating and implementing SBM in service stress the need for employee engagement, customer involvement and targeted and personal communication educating internal and external sustainability ambassadors.