Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model

Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors

Ease of use and usefulness are believed to be fundamental in determining the acceptance and use of various, corporate ITs. These beliefs, however, may not explain the user’s behavior toward newly emerging ITs, such as the World-Wide-Web (WWW). In this study, we introduce playfulness as a new factor that reflects the user’s intrinsic belief in WWW acceptance. Using it as an intrinsic motivation factor, we extend and empirically validate the Technology Acceptance Model (TAM) for the WWW context. # 2001 Elsevier Science B.V. All rights reserved.

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Beyond the Usefulness and Ease of Use : Extending the TAM for a World - Wide - Web Context

Investigating the influence of the most commonly used external variables of TAM on students' Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios

The purpose of this study was to investigate how to facilitate learners' engagement and persistence in massive open online courses (MOOCs). Specifically, this study used structural equation modeling to examine the structural relationships among academic self-efficacy, teaching presence, perceived usefulness, and perceived ease of use, learning engagement, and learning persistence in MOOCs. For the data analysis, we selected as the research subjects 306 learners who were taking MOOCs in South Korea. The results indicated that academic self-efficacy, teaching presence, and perceived usefulness had significant direct effects on learning engagement. Furthermore, teaching presence and perceived ease of use had direct effects on learning persistence. Finally, learning engagement had indirect effects on the relationships between academic self-efficacy, teaching presence, perceived usefulness, and learning persistence. These findings suggest implications for designing and developing effective instructional and learning strategies in MOOCs in terms of learners’ perceptions of themselves, instructors, and learning support systems.

Learning Engagement and Persistence in Massive Open Online Courses (MOOCS)

Although E-Learning 2.0 has played a significant role in training and development within the organisational environment, after an initial acceptance, its use is frequently discontinued. Prior studies offered insights into participation in E-Learning; however, there is limited research on continuance intention towards E-Learning 2.0 systems in organisational contexts. Furthermore, the most widely used research models, such as technology acceptance model (TAM), neglect the interactive social processes in E-Learning 2.0. Therefore, this study proposes a unified model integrating the TAM, the information system success model and social motivation theories to investigate continuance intentions towards E-Learning 2.0 in an organisational context. A sample of 284 participants from companies in China that have already implemented E-Learning 2.0 systems took part in this study. Structural equation modelling was conducted to test the research hypotheses. The results show that the unified model provides a more compr...

Empirical study on continuance intentions towards E-Learning 2.0 systems

Background: In practice, online health communities have passed the adoption stage and reached the diffusion phase of development. In this phase, patients equipped with knowledge regarding the issues involved in health care are capable of switching between different communities to maximize their online health community activities. Online health communities employ doctors to answer patient questions, and high quality online health communities are more likely to be acknowledged by patients. Therefore, the factors that motivate patients to maintain ongoing relationships with online health communities must be addressed. However, this has received limited scholarly attention. Objective: The purpose of this study was to identify the factors that drive patients to continue their use of online health communities where doctor-patient communication occurs. This was achieved by integrating the information system success model with online health community features. Methods: A Web spider was used to download and extract data from one of the most authoritative Chinese online health communities in which communication occurs between doctors and patients. The time span analyzed in this study was from January 2017 to March 2017. A sample of 469 valid anonymous patients with 9667 posts was obtained (the equivalent of 469 respondents in survey research). A combination of Web mining and structural equation modeling was then conducted to test the research hypotheses. Results: The results show that the research framework for integrating the information system success model and online health community features contributes to our understanding of the factors that drive patients' relationships with online health communities. The primary findings are as follows: (1) perceived usefulness is found to be significantly determined by three exogenous variables (ie, social support, information quality, and service quality; R2=0.88). These variables explain 87.6% of the variance in perceived usefulness of online health communities; (2) similarly, patient satisfaction was found to be significantly determined by the three variables listed above (R2=0.69). These variables explain 69.3% of the variance seen in patient satisfaction; (3) continuance use (dependent variable) is significantly influenced by perceived usefulness and patient satisfaction (R2=0.93). That is, the combined effects of perceived usefulness and patient satisfaction explain 93.4% of the variance seen in continuance use; and (4) unexpectedly, individual literacy had no influence on perceived usefulness and satisfaction of patients using online health communities. Conclusions: First, this study contributes to the existing literature on the continuance use of online health communities using an empirical approach. Second, an appropriate metric was developed to assess constructs related to the proposed research model. Additionally, a Web spider enabled us to acquire objective data relatively easily and frequently, thereby overcoming a major limitation of survey techniques. [J Med Internet Res 2018;20(4):e126]

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Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication.

Open innovation communities (OICs) can help enterprises make full use of external knowledge resources from users, but problems such as low user participation and low conversion rate of creative ideas impact the efficiency of OICs. Most studies on this topic employ qualitative or empirical methods from a static perspective, but ignore the effect of interaction between enterprises and users as well as the cumulative effect of time. A discussion on the dynamic evolution process of open innovation is lacking. Based on a review of the literature on OICs, innovation performance, and system dynamics, this study proposes a conceptual model of innovation performance impact, which comprises the knowledge management, governance mechanism, and user behavior subsystems. Xiaomi’s OIC in China was selected as the research object, and relevant data were collected through a web spider. According to the system dynamics modeling method, a causal relationship analysis was carried out on the three aforementioned interrelated subsystems. Then, a stock flow chart with 32 variables was constructed to determine the initial values and calculation equations for each variable. Finally, the model was constructed and verified using Vensim PLE software. The simulation results were as follows. (1) The number of product releases in the Xiaomi OIC was positively correlated with the number of posts, comments, and views. Compared with user interaction behavior (i.e., commenting and viewing), the impact of user innovation behavior (i.e., posting) on enterprise innovation performance (i.e., number of patents) is clearer. Specifically, regarding interaction behavior, the impact of the users’ commenting behavior on innovation performance (i.e., number of product releases) was relatively clearer than that of their viewing behavior. (2) Governance mechanism (i.e., R&D investment and management expense), which comprises technical and organizational mechanisms, positively affected the innovation performance of enterprises. Compared with the organizational mechanism (i.e., management expense), the impact of the technical mechanism (i.e., R&D investment) on the innovation performance was clearer. (3) Governance mechanism helped to increase the number of users in the OIC, and, in turn, affected the user innovation and interaction behavior. (4) The technical mechanism positively affected knowledge application capability, which, in turn, had a positive impact on the innovation performance of enterprises. Based on these findings, management strategies are proposed for the establishment and development of OICs.

https://www.mdpi.com/2071-1050/11/17/4794/pdf

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

As the E-Learning 2.0 system is a tool to help members manage knowledge in an effective way, this study attempts to verify the constructs of knowledge creation self-efficacy, subjective norms, perceived usefulness, organizational climate, attitudes toward knowledge sharing and the intention to engage in knowledge sharing. A sample of 284 participants from companies in China that have already implemented E-Learning 2.0 systems participated in this study. Structural equation modeling is conducted to test the research hypotheses. Research results show that 1 Knowledge creation self-efficacy, perceived usefulness and organizational climates are found to have positive effects on the intentions toward knowledge sharing in E-Learning 2.0 systems; 2 Meanwhile, system success factors of communication quality and service quality are suggested to influence the perceived usefulness of E-Learning 2.0 systems; 3 As we expected, the intentions toward knowledge sharing in E-Learning 2.0 have positive effects on knowledge-sharing behavior. Therefore, by highlighting the role of the organizational climate, the findings of current research provide practical insights for understanding how organizations should reinforce fairness, innovativeness and affiliation to create a climate of reciprocity.

Bing Wu

Papers

Continuance intention to use MOOCs: Integrating the technology acceptance model (TAM) and task technology fit (TTF) model

Empirical study on continuance intentions towards E-Learning 2.0 systems

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication.

Impact of Open Innovation Communities on Enterprise Innovation Performance: A System Dynamics Perspective

Identifying the Influential Factors of Knowledge Sharing in E-Learning 2.0 Systems