Understanding active and passive users: the effects of an active user using normal, hard and unreliable technologies on user assessment of trust in technology and co-user

The aim of this study was to understand how passive users perceive the trustworthiness of active users and technologies under varying technological conditions. An experimental study was designed to vary the functioning of technologies that active users interacted with, while passive users observed these interactions. Active and passive user ratings of technology and partner were collected. Exploratory data analysis suggests that passive users developed perceptions of technologies based on the functioning of the technology and how the active user interacted with the technology. Findings from this research have implications for the design of technologies in environments where active and passive users interact with technologies in different ways. Future work in this area should explore interventions that lead to enhanced affective engagement and trust calibration.     

How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust

Trust is generally assumed to be an important precondition for people’s adoption of electronic services. This paper provides an overview of the available research into the antecedents of trust in both commercial and non-commercial online transactions and services. A literature review was conducted covering empirical studies on people’s trust in and adoption of computer-mediated services. Results are described using a framework of three clusters of antecedents: customer/client-based, website-based, and company/organization-based antecedents. Results show that there are many possible antecedents of trust in electronic services. The majority of the research has been conducted in the context of e-commerce; only few studies are available in the domains of e-government and e-health. For many antecedents, some empirical support can be found, but the results are far from univocal. The research calls for more, and particularly more systematic, research attention for the antecedents of trust in electronic services. The review presented in this paper offers practitioners an overview of possibly relevant variables that may affect people’s trust in electronic services. It also gives a state-of-the-art overview of the empirical support for the relevance of these variables.     

Precursors of trust in virtual health communities: A hierarchical investigation

Lack of trust can have a negative influence on consumers’ willingness to share and adopt information in virtual health communities. However, not much is known about factors that influence the development of trust in such communities. This paper examined precursors of trust in virtual health communities. Data were collected from 361 users of virtual health community sites in South Africa. Structural equation modelling using version 23 of AMOS was used to analyse the data. The findings show that information usefulness, community responsiveness and shared vision have significant influence on consumers’ overall trust in health-related virtual communities. The findings, however, show differences in the extent to which precursor variables influence different dimensions of overall trust. The study provides insights that can help managers of such sites to effectively foster the development of trust in their communities.     

How and why trust matters in post-adoptive usage: The mediating roles of internal and external self-efficacy

Since the underutilization of technology often prevents organizations from reaping expected benefits from IT investments, an increasing body of literature studies how to elicit value-added, post-adoptive IT use behaviors. Such behaviors include extended and innovative feature use, both of which are exploratory in nature and can lead to improved work performance. Since these exploratory behaviors can be risky, research has directed attention to trust in technology as an antecedent to post-adoptive IT use. In parallel, research has examined how computer self-efficacy relates to post-adoptive IT use. While such research has found that both trust and efficacy can lead to value-added IT use and that they might do so interdependently, scant research has examined the interplay between these antecedents to post-adoptive IT use. Drawing on the Model of Proactive Work Behavior with a focus on its predictions about trust and efficacy, we develop a research model that integrates trust in technology and computer self-efficacy in the post-adoption context. Our model suggests that the two concepts are interdependent such that trust-related impacts on post-adoptive use behaviors unfold via computer-related self-efficacy beliefs. Contemporary tests of mediation on data from more than 350 respondents provided support for our model. Hence, our findings begin to open the black box by which trust-related impacts on post-adoptive behaviors unfold, revealing computer self-efficacy as an important mediating factor. In doing so, this study furthers understanding of how, and why, trust matters in post-adoptive usage, enabling strategic change management by elucidating the “fit” between technological characteristics and post-adoptive usage.     

I-TRUST: investigating trust between users and agents in a multi-agent portfolio management system

There is considerable research investigating trust among agents in multi-agent systems. However, the issue of trust between agents and users has rarely been reported in the literature. In this paper, we describe our experiences with I-TRUST, where trust is introduced as a relationship between clients and broker agents in terms of the amount of money clients are willing to give to these agents to invest on their behalf. The goals of broker agents are not only to maximize total revenue subject to clients’ risk preference, but also to reinforce trust with their clients. To achieve this, broker agents must first elicit user models both explicitly through questionnaires and implicitly through three games. Then based on the initial user models, a broker agent will learn to invest and later update user models when necessary. From the three experiments conducted in this study, we found that the controllability of a client towards the autonomous system plays a significant role for trust building.     

A meta-analysis of e-learning technology acceptance: The role of user types and e-learning technology types

Existing literature in the field of e-learning technology acceptance reflects a significant number of independent studies that primarily investigate the causal relationships proposed by technology acceptance theory, such as the technology acceptance model (TAM). To synthesize the existing knowledge in the field of e-learning technology acceptance, we have conducted a systematic literature review of 42 independent papers, mostly published in major journals. Furthermore, in order to view the research context by combining and analyzing the quantitative results of the reviewed research studies, a meta-analysis of the causal effect sizes between common TAM-related relationships was conducted. The main findings of this study, which is the first of its kind, are: (1) TAM is the most-used acceptance theory in e-learning acceptance research, and (2) the size of the causal effects between individual TAM-related factors depends on the type of user and the type of e-learning technology. The results of the meta-analysis demonstrated a moderating effect for user-related factors and technology-related factors for several evaluated causal paths. We have gathered proof that the perceived ease of use and the perceived usefulness tend to be the factors that can influence the attitudes of users toward using an e-learning technology in equal measure for different user types and types of e-learning technology settings.     

一种车载导航系统中磁盘共享的设计

本文提出了一种在车载嵌入式电子产品中,利用FPGA(Field-Programmable Gate Array)来实现多主机磁盘[HDD(HardDisk Drive)]共享的解决方案,阐述了整个方案的系统设计方法,介绍了FPGA子系统的各个主要模块设计原理。该方案可以有效降低高端车载导航系统的产品成本。     

Using structural technology acceptance models to segment intended users of a new technology: Propositions and an empirical illustration

This article aims to offer an alternative method to analyse technology acceptance models, namely a segment‐wise analysis. The empirical illustration of this method involves data that were collected during a company‐wide implementation of a Sales Force Automation technology in Europe. The data comprise a variety of commonly used technology‐related, context‐related, and person‐related variables. The segmentation procedure, which involved a finite mixture partial least squares estimation, provides more insight into the different ways in which people come to accept new technologies. Unlike other segmentation studies published in IS journals, the resulting segments are based on similarities and differences in the structure of the underlying theoretical models rather than (a collection of) individual variables. Further research or a re‐analysis of existing data should help establish robust “technology acceptance model”‐based segments as well as comprehensive profiles of the individuals in each segment.     

Churn prediction and social neighbour influences for different types of user groups in virtual worlds

In virtual worlds (VWs), users have more VW games alternatives, whereas VW companies consequently suffer from high customer turnover rate and low customer loyalty. Therefore, building a churn prediction model to facilitate subsequent churn management and customer retention is important. The churn behaviours and the impact of social neighbour influences to customer churn may be different for different types of users. Accordingly, we segment users into stable, unstable, and solitary user groups according to their social contact behaviours in VWs. Novel segmentation‐based churn prediction approaches are proposed for churn prediction in VWs by building prediction models for each type of user groups and considering the effect of social neighbour influences for different user groups. The proposed approaches are evaluated by conducting experiments with a dataset collected from a VW platform. The experimental results show different churn prediction performances under different user groups. The segmentation‐based churn prediction approaches perform better than do general approaches without considering user groups. Moreover, the results also reveal that social neighbour influences have a positive impact on stable and unstable users. The proposed work contributes to investigating the social neighbour influences on churn prediction for different types of user groups in VWs.     

User requirements of mobile technology: results from a content analysis of user reviews

Advanced mobile technology continues to shape professional environments. Smart cell phones, pocket computers and laptop computers reduce the need of users to remain close to a wired information system infrastructure and allow for task performance in many different contexts. Among the consequences are changes in technology requirements, such as the need to limit weight and size of the devices. In the current paper, we focus on the factors that users find important in mobile devices. Based on a content analysis of online user reviews that was followed by structural equation modeling, we found four factors to be significantly related with overall user evaluation, namely functionality, portability, performance, and usability. Besides the practical relevance for technology developers and managers, our research results contribute to the discussion about the extent to which previously established theories of technology adoption and use are applicable to mobile technology. We also discuss the methodological suitability of online user reviews for the assessment of user requirements, and the complementarity of automated and non-automated forms of content analysis.     

Management and applications of trust in Wireless Sensor Networks: A survey

Wireless Sensors Networks (WSNs) are susceptible to many security threats, and because of communication, computation and delay constraints of WSNs, traditional security mechanisms cannot be used. Trust management models have been recently suggested as an effective security mechanism for WSNs. Considerable research has been done on modeling and managing trust. In this paper, we present a detailed survey on various trust models that are geared towards WSNs. Then, we analyze various applications of trust models. They are malicious attack detection, secure routing, secure data aggregation, secure localization and secure node selection. In addition, we categorize various types of malicious attacks against trust models and analyze whether the existing trust models can resist these attacks or not. Finally, based on all the analysis and comparisons, we list several trust best practices that are essential for developing a robust trust model for WSNs.     

Gen Y customer loyalty in online shopping: An integrated model of trust,user experience and branding

Generational theory posits that generational cohorts develop similar attitudes and beliefs. Gen Y, Millennials, will become the largest customer segment for hotels worldwide. This group likes to travel and prefers to spend money on experiences rather than materialistic items. Their responses to online marketing is expected to be different as they process website information five times faster than older generations and are the most emotional and least loyal customers compared to all other generations. The aim of this research is to develop and test a comprehensive model that explains how Gen Y develops loyalty to a hotel booking website. To test the research model, an online survey was distributed to a systematic random sample of 2500 Gen Yers. Findings highlight that trust is the most important antecedent of e-loyalty in online shopping for Gen Y customers. Brand equity is also a key precursor of e-loyalty. Finally, a positive online experience (flow), is also a significant precursor of e-loyalty for this cohort.     

How students and instructors using a virtual learning environment perceive the fit between technology and task

Abstract   Virtual learning environments (VLEs) are widespread in higher education today, typically used to deliver instructional materials and facilitate communication within a course. This study aimed to investigate the task–technology fit of VLEs for their two main groups of users: instructors and students, using the VLE WebCT. Task–technology fit, user satisfaction, attitude towards use and anticipated consequences of use were found to be significantly higher for students than for instructors. Instructors were found to have higher perceptions of social norms and higher perceptions of facilitating conditions than students. However, there was no difference between the instructors and students in level of utilization of the VLE. Students perceived that the VLE had higher impacts on their learning compared with instructors' perceptions regarding their teaching. These results suggest that despite high levels of support acknowledged by instructors, they may still be unsure about the contribution of VLEs to their teaching.     

A survey of trust in computer science and the Semantic Web

Trust is an integral component in many kinds of human interaction, allowing people to act under uncertainty and with the risk of negative consequences. For example, exchanging money for a service, giving access to your property, and choosing between conflicting sources of information all may utilize some form of trust. In computer science, trust is a widely used term whose definition differs among researchers and application areas. Trust is an essential component of the vision for the Semantic Web, where both new problems and new applications of trust are being studied. This paper gives an overview of existing trust research in computer science and the Semantic Web.     

SemPI: A semantic framework for the collaborative construction and maintenance of a shared dictionary of performance indicators

Collaboration at strategic level entails the sharing of Performance Indicators (PIs) to measure the achievement of common objectives and evaluate performances. PIs are synthetic measures calculated starting from transactional data. Given their compound nature, it is difficult to achieve an agreement on their definitions and heterogeneities arise that make sharing and exchange a difficult task. Semantic techniques can help to address these challenges by providing a common layer of formal definitions and automatic reasoning tools to maintain its consistency. In this paper, we present a novel semantic framework for representing Performance Indicators that supports the construction and maintenance of a minimal and consistent dictionary. The distinctive feature of the approach is the logical representation of formulas defining PIs, allowing to make algebraic relationships among indicators explicit, and to reason over these relationships to derive PI identity and equivalence and to enforce the overall consistency of the dictionary. We also present a web application implementing the framework for collaborative construction and maintenance of the dictionary. We provide experimental evidence of the efficiency and effectiveness of the approach on synthetic and real data.     

New technology in personnel selection: How recruiter characteristics affect the adoption of new selection technology

The aim of the present field study is to expand the understanding of how characteristics of recruiters relate to their adoption of new selection technology. In two studies, among 198 recruiters, we used the Technology Acceptance Model (TAM), together with two measures of personality (i.e., openness to experience and neuroticism), two information technology specific individual differences (i.e., personal innovativeness in information technology and computer self-efficacy), and reactions to and actual usage of new technology. Both studies showed that all recruiter characteristics (except openness to experience) relate to perceptions of usefulness and ease of use, and that these perceptions relate to intentions to use new selection technologies. Study 2 showed that recruiter characteristics predict perceptions of usefulness and ease of use over and above established predictors of the TAM. Perceptions of usefulness and ease of use were better predictors of intentions to use new technology than perceptions of face validity, predictive validity, and fairness. Thus, when it comes to the adoption of new selection technology, recruiter characteristics, and perceptions of usefulness and ease of use play an important role.     

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.     

Continuance intention of blog users: the impact of perceived enjoyment,habit, user involvement and blogging time

The purpose of this study is to understand factors that affect continuance intention of a popular hedonic information system, blogs. The expectation-confirmation theory (ECT) is adapted with perceived enjoyment, habit and user involvement. Data was collected via an online survey. A total of 430 valid responses were collected. The research model was assessed by structural equation modelling (SEM). The results show that continuance intention of blog use was predicted collectively by user involvement, satisfaction and perceived enjoyment. Habit, however, exhibited no strong relationship with satisfaction and use intention. Users' satisfaction with blog use was predicted primarily by perceived enjoyment, followed by users' confirmation of expectation and user involvement. Perceived enjoyment was predicted by users' involvement and users' confirmation of expectation. Blogging time significantly moderates the effect of habit on perceived enjoyment, but not on satisfaction and continuance intention. The integrated model explains 65% of the satisfaction and 57% of continuance intention. The results suggest that integrating perceived enjoyment and user involvement into the ECT provides better insights into continuous use in the blog context.     

Exploring interactive style and user experience design for social web of things of Chinese users: A case study in Beijing

This study designed an interactive IoT (Internet of Things) service on mobile devices based upon the concept of Social Web of Things (SWoT), with which users can interact with IoT in the same way they use the social network services. In order to integrate IoT into Chinese daily use, this study also investigated how Chinese users interact with things and IoT technologies. A four-phase study among users living in Beijing was conducted with a lifecycle of user-centered design. Results revealed that SWoT could activate users׳ intuitive understanding of social network services, and make the interaction with SWoT natural in their own ways. Users living in Beijing tended to be utility-oriented and highly emphasized efficiency; they were distinctive in uncertainty avoidance and preference of hierarchical way of managing things. Our results suggested implications for the design of user-centered IoT systems in China, and shed light on improvements for the performance of IoT systems and balance of requirements between users and system design.     

Antecedents and consequences of trust in a social media brand: A cross-cultural study of Twitter

This study extends brand relationship theory to the context of the microblogging platform Twitter. The authors investigate the impact of Twitter trust on users’ intentions to continue using the platform and to “follow” brands that are hosted on Twitter (the trust transfer phenomenon). They also explore the role of perceived self-Twitter personality match in strengthening trust towards the Twitter brand. A cross-cultural American–Ukrainian sample allows to identify potential culture-based differences in brand personality and brand trust concepts. The results show that the positive effect of trust in Twitter on its users’ patronage intentions is robust across two cultures with diverse history and ideology. An important novel finding is the influence of trust in Twitter on patronage intentions towards the businesses hosted on Twitter. However, this relationship reaches statistical significance only in the Ukrainian sample, signaling potential differences in the trust transfer processes in different cultures. The study confirms the role of similarity in personality traits between Twitter users and the Twitter brand in engendering trust in Twitter. The salience of different personality traits in the “personality match – Twitter trust” link for different cultures suggests important implications for global marketers.