Partner influences on ICT use variety among middle-aged and older adults: The role of need for cognition

Media Richness and Continuance Intention to Online Learning Platforms: The Mediating Role of Social Presence and the Moderating Role of Need for Cognition

Continuance intention to online learning platforms has received increased attention in recent years, and media richness has been found to be an important antecedent influencing user retention. However, there is insufficient research on the mediating and moderating mechanism underlying this relation. The purpose of this article is to investigate (a) the positive association between three dimensions of media richness and user continuance intention, (b) the mediating role of social presence in the relationship between three dimensions of media richness and continuance intention, and (c) the moderating role of need for cognition in the relationship between three dimensions of media richness and social presence. We conduct a survey questionnaire with a sample of 368 users from online learning platforms and use structural equation modeling. The results indicate that the model proposed has a high explanatory power of continuance intention to online learning platforms and give support to the moderating role of the need for cognition. The study highlights the crucial role these technological-environment-related variables (media richness) have in relation to virtual user experience (social presence) and their continuance intention. Furthermore, this study shows the significance of differentiated online course design to foster users’ social presence according to user types.

Investigating Factors Influencing Nurses' Behavioral Intention to Use Mobile Learning: Using a Modified Unified Theory of Acceptance and Use of Technology Model

The purpose of this study was to develop and empirically test a model for predicting the key factors affecting nurses' behavioral intention to use mobile learning (m-learning). We explored behavioral intention from users' perspectives by applying an extended unified theory of acceptance and use of technology (UTAUT) model with the addition of information quality, system quality, technostress, and satisfaction. We conducted a survey of the district and regional hospitals in central Taiwan. Data were derived from 434 respondents. Structural equation modeling was applied to analyze the causal effects of 15 hypothesized predictive factors. We determined that satisfaction, social influence, performance expectancy, facilitating conditions, and effort expectancy positively impacted nurses' behavioral intention to use m-learning. In addition, technostress was a negative antecedent of effort expectancy. Information quality and system quality had significantly positive effects on satisfaction, performance expectancy, and effort expectancy. This study provides hospital managers with a reference when assessing future developments and informs approaches to promote m-learning.