Exploring the Factors Influencing an Organisation in Thailand To Adopt Cloud Computing Platforms

This research is aimed to explore the factors influencing organizations in Thailand to adopt to cloud computing platforms.  The study was conducted utilizing the theory of planned behavior (attitude toward the behavior, subjective norms, perceived behavioral control) with an additional factor known as the perceived usefulness, perceived ease of use, and satisfaction to predict companies' intention to adopt to cloud.  The research was conducted as a quantitative analysis with descriptive and inferential research with a sample size of 284 respondents who have had some experience with cloud computing services.  The results of this research were analyzed using simple and multiple linear regression.  The finding shows most of the variables have significantly influenced cloud adoption intention.  Interestingly, technology impacts perceived usefulness, Perceived ease of use as well as satisfaction.  There is a need for proper knowledge sharing, training for Thailand people to use cloud computing platforms

Investigating Continuance Intention to Use E-Learning of Female Students Majoring in Music in Chengdu

Purpose: Remote learning is expected to become a normal tool after the epidemic’s end and is an important means to promote the digital development of education. This study investigates the impact of system quality, subjective norms, interactivity, course content quality, perceived usefulness, and satisfaction on the continuance intention to use e-learning of music major college students in Chengdu, China. Research design, data, and methodology: The population is 500 female students at Sichuan University using three selected e-learning platforms: DingDing, Tencent meeting, and WeLink. The sample techniques are judgmental, stratified random, and convenience sampling. The Item Objective Congruence (IOC) Index and the pilot test (n=50) by Cronbach’s Alpha were approved before the data collection. The data was analyzed through Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM). Results: The findings reveal that system quality and subjective norms significantly impact perceived usefulness. Interactivity and course content quality significantly impact satisfaction. Continuance intention is impacted by perceived usefulness and satisfaction. On the opposite, perceived usefulness has no significant impact on satisfaction. Conclusions: Educational institutions and the Chinese government can exploit the findings in this study to improve accessibility with the highest-performance online learning infrastructure for the country

Drivers of Undergradute Students’ Perceived Usefulness and Satisfaction with Online Learning in Chengdu, China

Purpose: The purpose of the study is to deeply explore the factors influencing perceived usefulness and satisfaction of undergraduates towards online learning experiences in China. In constructing the research framework, we selected seven latent variables: perceived ease of use, system quality, information quality, service quality, perceived usefulness, confirmation, and satisfaction. Research design, data, and methodology: This study applied quantitative approach, distributing questionnaire to 500 undergraduate students at three universities in Chengdu, Sichuan, China. Before the data collection, Item-Objective Congruence (IOC) and a pilot test of Cronbach's Alpha were adopted to test the content validity and reliability. In data analysis, the researcher used confirmatory factor analysis (CFA) and structural equation modeling (SEM) for statistical analysis to assess key indicators such as validity, reliability, model fits, and path coefficient. Results: The results show that perceived ease of use and service quality significantly influence perceived usefulness. The relationship among confirmation, perceived usefulness and satisfaction is supported. Additionally, perceived usefulness significantly influences satisfaction. Nevertheless, system quality and information quality have no significant influence on perceived usefulness. Conclusions: This research aims to gain a deeper understanding of the online learning experience to provide useful insights into the field of education

Switching Intention and Intention to Use Personal Cloud Storage Services Among Chinese Undergraduates

Purpose: As one of the emerging Internet technologies, cloud technology may be broadly categorized as cloud computing and cloud storage. Personal Cloud Storage Service (PCSS) is an important part of cloud technology. Thus, this study investigates the factors influencing Hangzhou undergraduates' switching intentions and intention to use personal cloud storage services. Research design, data, and methodology: The data were collected from 515 undergraduates at Zhejiang University, Zhejiang Gongshang University, and Zhejiang University of Technology. The sampling techniques are judgmental sampling, stratified random sampling, and snowball sampling. The item-objective congruence (IOC) and Cronbach's Alpha of the pilot test were approved before the data collection. Afterwards, this study applied confirmatory factor analysis (CFA) and structural equation modeling (SEM). Results: The findings indicate that perceived ease of use has a significant impact on perceived usefulness. Perceived usefulness, perceived ease of use and attitude significantly affect intention to use. Perceived risk significantly affected the switching intention. Finally, switching cost and perceived usefulness significantly affect the switching intention. Conclusion: Personal cloud storage service providers should enhance the security and should continue to improve its PCSS products and optimize the membership price model, enabling free users to use the service by sending them advertisements

Psychological and Agentic Effects of Human-Bot Delegation in Open-Source Software Development (OSSD) Communities: An Empirical Investigation of Information Systems Delegation Framework

Bots are agentic AI that automatically interact with software developers, also known as contributors, to coordinate work in open-source software development (OSSD). The proliferation of bots in OSSD communities like Kubernetes led them to become the disruptive new teammates central to the coordinating mechanisms for implementing source code changes using pull requests. These bots provide procedural rationality and enhance predictability in OSSD communities akin to clerks and managers in traditional organizations. However, despite acknowledging the criticality of the bots’ agentic role in coordinating the OSSD, research on the OSSD dynamics in the Information Systems literature has failed to reveal the role of bots on contributors’ behavioral outcomes. Bot-driven OSSD communities serve as an excellent example of successful new forms of organizing that necessitate theoretical modeling of the human-bot collaboration, the central mechanism, enhancing contribution patterns, and the overall sustainability of the OSSD community. Using 289 survey responses from Kubernetes contributors, we empirically tested the model and identified the factors enabling contributors’ fit appraisal of collaborating with the bots. Contributors appraised adaptive and reliable bots that offered explainable feedback. Our findings highlight the role of contributors’ self-efficacy and their instrumentality in the project as the predictors of their fit appraisal. More importantly, the empirical results revealed the role of agentic coordination as the enabler of contributors’ satisfaction via explicit and implicit coordination mechanisms. Furthermore, we find that contributors intend to continue contributing if satisfied with their contribution experience, leading to their commitment to the OSSD community. The model offers a more nuanced perspective of the human-bot collaboration in OSSD communities. A profound understanding of the dyadic delegation patterns, leading to contributor satisfaction, could inform researchers and practitioners in designing bots and OSSD platforms that ultimately enhance the contribution experiences, leading to their willingness to continue contributing to the OSSD community. Our results and discussion of findings offer actionable insights to enable bot design for optimal utilization in OSSD and other similar knowledge-intensive voluntary communities. The study findings offer implications for the future forms of organizing, the design of human-bot collaborative environments, and the sustainability and success of OSSD communities