Determinants of the intention to use non-medical insertable digital devices: The case of Chile and Colombia

In the past, thinking of carrying electronic devices inside our bodies was only posed by non-real scenarios. The emergence of insertable devices has changed this. Since this technology is still in its initial development stages, few studies have investigated factors that influence its acceptance. This paper analyzes the predictors of the intention to use non-medical insertable devices in two Latin American contexts. We used partial least squares structural equation modeling to examine whether six constructs predicted intention to use insertable devices. A questionnaire was administered to undergraduate students located in Colombia and Chile (n = 672). We also examined whether these predictors influenced intention differently for both of them. Four common constructs significantly and positively influenced both Chilean and Colombian respondents to use insertable devices (hedonic motivation, habit, performance expectancy, and social influence). Also, the habit has a complementary mediating effect on the relationship between social influence and behavioral intention. By contrast, effort expectations were a positive and significant predictor, but only among Chilean respondents. Findings suggest that when technologies are emerging, well-known predictors of intention (e.g., performance and effort expectations) are less influential than predictors related to self-efficacy (e.g., habit and hedonic motivation). The use of insertable devices has a significant impact on society. Thus, a better understanding of what motivates their use has implications for both academia and industry.     

Compensation paradox: the influence of monetary rewards on user behaviour

Many e-commerce companies collect users’ personal data for marketing purposes despite privacy concerns. Information-collecting companies often offer a monetary reward to users to alleviate privacy concerns and ease the collection of personal information. This study focused on the negative effects of monetary rewards on both information privacy concerns (IPC) and information disclosure. A survey approach was used to collect data and 370 final responses were analysed using a two-way analysis of variance and a binomial logistic regression model. The results show that monetary rewards increase IPC when an information-collecting company requires sensitive information. Additional results indicate that building trust is a more effective way of collecting personal data. This study identifies how organisations can best execute information-collection activities and contributes additional insights for academia and practitioners.     

Surveying instructor and learner attitudes toward e-learning

The trend of using e-learning as a learning and/or teaching tool is now rapidly expanding into education. Although e-learning environments are popular, there is minimal research on instructors’ and learners’ attitudes toward these kinds of learning environments. The purpose of this study is to explore instructors’ and learners’ attitudes toward e-learning usage. Accordingly, 30 instructors and 168 college students are asked to answer two different questionnaires for investigating their perceptions. After statistical analysis, the results demonstrate that instructors have very positive perceptions toward using e-learning as a teaching assisted tool. Furthermore, behavioral intention to use e-learning is influenced by perceived usefulness and self-efficacy. Regarding to learners’ attitudes, self-paced, teacher-led, and multimedia instruction are major factors to affect learners’ attitudes toward e-learning as an effective learning tool. Based on the findings, this research proposes guidelines for developing e-learning environments.     

A motivational model of rural students' intentions to persist in, versus drop out of, high school.

Using self-determination theory, the authors tested a motivational model to explain the conditions under which rural students formulate their intentions to persist in, versus drop out of, high school. The model argues that motivational variables underlie students' intentions to drop out and that students' motivation can be either supported in the classroom by autonomy-supportive teachers or frustrated by controlling teachers. LISREL analyses of questionnaire data from 483 rural high school students showed that the provision of autonomy support within classrooms predicted students' self-determined motivation and perceived competence. These motivational resources, in turn, predicted students' intentions to persist, versus drop out, and they did so even after controlling for the effect of achievement. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A connectionist implementation of the theory of planned behavior: Association of beliefs with exercise intention.

The theory of planned behavior suggests attitudes are a product of salient beliefs. This study examined whether aggregating salient beliefs was plausible within a more biologically centered information-processing environment. A neural network was used to examine associations among beliefs relating to exercise intention. Data on intentions and behavioral, normative, and control beliefs from 114 respondents were used to train (by error backpropagation) a neural network to associate beliefs with intention. The R2 between the network's estimated and self-reported intention was .66. The network's representation comprised 6 belief profiles associated with high, moderate, or low behavioral intention. The neural network accommodated complex relationships among beliefs and belief-intention associations and indicated how high-level constructs such as attitudes may be viewed as the best fit (compromise state) between aroused beliefs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Driving intention recognition and behaviour prediction based on a double-layer hidden Markov model

We propose a model structure with a double-layer hidden Markov model (HMM) to recognise driving intention and predict driving behaviour. The upper-layer multi-dimensional discrete HMM (MDHMM) in the double-layer HMM represents driving intention in a combined working case, constructed according to the driving behaviours in certain single working cases in the lower-layer multi-dimensional Gaussian HMM (MGHMM). The driving behaviours are recognised by manoeuvring the signals of the driver and vehicle state information, and the recognised results are sent to the upper-layer HMM to recognise driving intentions. Also, driving behaviours in the near future are predicted using the likelihood-maximum method. A real-time driving simulator test on the combined working cases showed that the double-layer HMM can recognise driving intention and predict driving behaviour accurately and efficiently. As a result, the model provides the basis for pre-warning and intervention of danger and improving comfort performance.     

基于样本熵与时频分析的手部抓握运动意图预测

针对上肢外骨骼控制信号产生与外部设备响应存在时间滞后导致脑机接口(BCI)系统实时性差的问题,采集被试手部自主抓握前运动相关皮质电位(MRCP) ,提出基于非线性复杂度特征样本熵 (SampEn)与线性幅值特征融合算法的手部运动意图预测方法. 从时频、神经复杂度分析不同大脑状态之间存在的差异,通过特征融合实现对手部抓握运动意图的预测. 基于特征融合意图离线预测准确率最高可达88.46%,可以在人体手部自主运动发生时刻?1 400 ms实现对手部运动预测. 与平静时期手部静止状态相比,被试产生手部抓握运动意图时脑电信号的功率谱与复杂度均产生明显变化,为基于手部运动意图预测提前驱动机器人实现人机协同提供控制策略.     

Examining the role of perceived value in virtual communities continuance: its antecedents and the influence of experience

Although perceived value has long been recognised as an influential means of affecting continuance intention in information systems (IS), little attention has been devoted to explore its antecedents, which constitutes an important research issue. This study, building on prior literature on continued usage in IS as well as the resource-based view, proposed a model to address this gap. Our model suggests that perceived value, a major driving force for members’ satisfaction and continuance intention, is affected by four kinds of resources embedded in virtual communities, which are relationship resources, technology infrastructure, knowledge resources and human resources. To provide additional insights on the pivotal role of perceived value, we also postulate that experience moderates the link between perceived value and its antecedents. Data collected from 235 members of a professional virtual community provide strong support for the research model. It was found that perceived value exerts a great effect on both satisfaction and continuance intention. In addition, when different levels of experience are taken into consideration, relationship resources, knowledge resources and human resources were found to be more salient to high-experience members, whereas technology infrastructure was found to be more salient to low-experience members. Finally, this study discusses the implications of these findings and offers direction for future research.     

潜在网络购物者与有经验者购买意愿比较研究*

感知风险和信任缺失被认为是阻碍网络购物发展的主要因素。以技术接受模型为理论基础,将感知风险和信任引入模型,把消费者分为潜在网络购物者和有经验网络购物者两大类,采用结构方程模型方法对影响我国消费者网络购物意愿的因素进行实证对比研究。实证结果表明：消费者感知网络购物有用性对其购买意愿的影响路径系数高于信任和风险因子对购买意愿的路径系数;感知风险对网络购买意愿有直接的负向影响;对于潜在消费者群体,信任显著影响其网络购物意愿,但对有购物经验的消费者群体信任却对网络购买意愿没有显著影响。     

知识型员工工作态度与离职倾向关系的实证研究

采用实证法研究了知识型员工工作态度总体水平及各维度与离职倾向的关系,并建立了关系模型。研究结果表明：工作态度及其维度均与离职倾向显著负相关,且组织承诺对离职倾向的影响大于工作满意度;规范承诺、内在满意度、情感承诺、外在满意度、持续承诺依次成为影响知识型员工离职倾向的主要因素,均负相关。