Acceptance and Use of E-Learning Based on Cloud Computing: The Role of Consumer Innovativeness

Cloud computing and E-learning are the inevitable trend of computational science in general, and information systems and technologies in specific.However, there are not many studies on the adoption of cloud-based E-learning systems. Moreover, while there are many papers on information system adoption as well as customer innovativeness, the innovativeness and adoption in the same model seems to be rare in the literature. The study combines the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) and consumer innovativeness on the adoption of E-learning systems based on cloud computing. A survey was conducted among 282 cloud-based E-learning participants and analyzed by structural equation modeling (SEM). The findings indicate that the adoption of cloud-based E-learning is influenced by performance expectancy, social influence, hedonic motivation, and habit. Interestingly, although innovativeness is not significant to use intention, it has a positive effect on E-learning usage which is relatively new in Vietnam

Examining the Determinants of Mobile Accounting App Acceptance Among Saudi Wholesalers: An Empirical Investigation Using the UTAUT2

Purpose: This research aims to identify the determinants of Mobile App Acceptance (MAA) intention and usage within the Saudi wholesaling sector.   Theoretical Framework: Drawing upon the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this study examines the factors that influence the acceptance and utilization of mobile apps among Saudi wholesalers.   Design/Methodology/Approach: The study employs a structured approach, analyzing data gathered from Saudi wholesalers. The research integrates the UTAUT2 model with an additional construct, trust, and employs Structural Equation Modelling (SEM) to test the hypothesized relationships.   Findings: The research results highlight the significance of various factors in shaping the behavioral intention towards MAA. Performance expectancy, effort expectancy, hedonic motivation, and trust play pivotal roles in influencing users' attitudes toward MAA. Furthermore, behavioral intention and facilitating conditions emerge as key predictors of MAA acceptance.   Research, Practical & Social implications: The findings contribute to both academic research and practical applications. MAA providers can leverage these insights to enhance user experience and build trust, thereby encouraging higher adoption rates. Additionally, the study provides valuable insights for the Saudi wholesaling sector to effectively incorporate MAA into their operations. &nbsp

The Relationship between Nonprofit Organizations and Cloud Adoption Concerns

Many leaders of nonprofit organizations (NPOs) in the United States do not have plans to adopt cloud computing. However, the factors accounting for their decisions is not known. This correlational study used the extended unified theory of acceptance and use of technology (UTAUT2) to examine whether performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit can predict behavioral intention (BI) and use behavior (UB) of NPO information technology (IT) managers towards adopting cloud computing within the Phoenix metropolitan area of Arizona of the U.S. An existing UTAUT2 survey instrument was used with a sample of IT managers (N = 106) from NPOs. A multiple regression analysis confirmed a positive statistically significant relationship between predictors and the dependent variables of BI and UB. The first model significantly predicted BI, F (7,99) =54.239, p -?¤ .001, R^2=.795. Performance expectancy (β = .295, p = .004), social influence (β = .148, p = .033), facilitating conditions (β = .246, p = .007), and habit (β = .245, p = .002) were statistically significant predictors of BI at the .05 level. The second model significantly predicted UB, F (3,103) = 37.845, p -?¤ .001, R^2 = .527. Habit (β = .430, p = .001) was a statistically significant predictor for UB at a .05 level. Using the study results, NPO IT managers may be able to develop strategies to improve the adoption of cloud computing within their organization. The implication for positive social change is that, by using the study results, NPO leaders may be able to improve their IT infrastructure and services for those in need, while also reducing their organization\u27s carbon footprint through use of shared data centers for processing

PERSEPSI MASYARAKAT PERKOTAAN TERHADAP LAYANAN SMART CITY: MODEL UTAUT2

In this study, we look at technology readiness related to performance expectancy and effort expectancy from UTAUT2 to analyze urban community perceptions of smart city services. Data is collected using a survey questionnaire. We use Partial Least Square Structural Equation Modeling (PLS-SEM) analysis. The questionnaire consists of 16 items on the Technology Readiness Index 2.0 scale to measure technological readiness and the UTAUT2 scale which has 29 items. The research of the study shows that optimism has a positive effect on performance expectancy and effort expectancy in using smart services. This means that respondents believe and have a sense of optimism that smart city service technology will be understood and used. Effort expectancy, facilitation conditions, and hedonic motivation have a positive effect on the intention to use smart services. It can be said that although some users are anxious about the new technology, it will not have an impact on the usability and ease of use of smart service technology

Acceptance of blended learning in executive education

This article evaluates the factors involved in the acceptance of Blended Learning (BL) with executives based on the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model in executive education. The empirical analysis uses data from 307 responses to an online questionnaire by senior and middle-ranking managers. The confirmatory factor analysis and structural equation modeling demonstrated the applicability of the UTAUT2 model in BL in executive education. The results showed that hedonic motivation, performance expectancy, and effort expectancy predict the intention to adopt BL. Results also prove no significant effect on social influence and habits. The relevance of this article is to contribute to the understanding of the factors that influence the intention to adopt BL in a group not typically considered in higher education research

FACTORS INFLUENCING THE ACCEPTANCE OF BLENDED LEARNING BY EARLY CHILDHOOD UNDERGRADUATE STUDENTS

The mixed-method research approach was applied to explore early childhood major students' levels of acceptance and attitudes towards blended learning based on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) and College and University Classroom Environment Inventory (CUCEI). Three hundred sixty-three undergraduate early childhood major students in China participated in the study. The Structural Equation Modeling (SEM) analysis was used to determine which variables in the UTAUT2 and CUCEI significantly impacted blended learning acceptance. The interview data supplemented the findings of the quantitative data. It was found that social influence and classroom environment significantly impacted blended learning acceptance. Results also indicated that blended learning is more likely to be accepted and used because of the ease of its use and the convenience it offers, as well as promoting a better social and classroom environment. However, the blended learning acceptance was not correlated with performance expectancy, effort expectancy, hedonic motivation, facilitating condition, and price value. Based on these findings, the researcher provided suggestions for decision-makers regarding using and accepting blended learning in their institutions. Administrators and educators can use this study's findings to guide their implementation and improvement of blended learning

Fatores que afetam a adoção de análises de Big Data em empresas

With the total quantity of data doubling every two years, the low price of computing and data storage, make Big Data analytics (BDA) adoption desirable for companies, as a tool to get competitive advantage. Given the availability of free software, why have some companies failed to adopt these techniques? To answer this question, we extend the unified theory of technology adoption and use of technology model (UTAUT) adapted for the BDA context, adding two variables: resistance to use and perceived risk. We used the level of implementation of these techniques to divide companies into users and non-users of BDA. The structural models were evaluated by partial least squares (PLS). The results show the importance of good infrastructure exceeds the difficulties companies face in implementing it. While companies planning to use Big Data expect strong results, current users are more skeptical about its performance.Con la cantidad total de datos duplicándose cada dos años, el bajo precio de la informática y del almacenamiento de datos, la adopción del análisis Big Data (BDA) es altamente deseable para las empresas, como un instrumento para conseguir una ventaja competitiva. Dada la disponibilidad de software libre, ¿por qué algunas empresas no han adoptado estas técnicas? Para responder a esta pregunta, ampliamos la teoría unificada de la adopción y uso de tecnología (UTAUT) adaptado para el contexto BDA, agregando dos variables: resistencia al uso y riesgo percibido. Utilizamos el grado de implantación de estas técnicas para dividir las empresas entre: usuarias y no usuarias de BDA. Los modelos estructurales fueron evaluados con partial least squres (PLS). Los resultados muestran que la importancia de una buena infraestructura excede las dificultades que enfrentan las empresas para implementarla. Mientras que las compañías que planean usar BDA esperan muy buenos resultados, las usuarias actuales son más escépticos sobre su rendimiento.Com a quantidade total de dados duplicando a cada dois anos, o baixo preço da computação e do armazenamento de dados tornam a adoção de análises de Big Data (BDA) desejável para as empresas, como aquelas que obterão uma vantagem competitiva. Dada a disponibilidade de software livre, por que algumas empresas não adotaram essas técnicas? Para responder a essa pergunta, estendemos a teoria unificada de adoção e uso de tecnologia (UTAUT) adaptado para o contexto do BDA, adicionando duas variáveis: resistência ao uso e risco percebido. Usamos a nível da implementação da tecnologia para dividir as empresas em usuários e não usuários de técnicas de BDA. Os modelos estruturais foram avaliados por partial least squares (PLS). Os resultados mostram que a importância de uma boa infraestrutura excede as dificuldades que as empresas enfrentam para implementá-la. Enquanto as empresas que planejam usar Big Data esperam resultados fortes, os usuários atuais são mais céticos em relação ao seu desempenho

Evaluation of ERP Oracle Netsuite System for Purchasing Management Module at PT PQR using UTAUT2 Method

The purpose of the study was to evaluate the acceptance, use, and behavior of users towards the use of ERP Oracle NetSuite systems in the Purchasing Management module by analyzing how UTAUT2’s variables affected the user acceptances towards ERP Oracle NetSuite. The research method used is the UTAUT2 method, by conducting field studies to obtain information related to PT PQR and literature studies to support the theoretical data collection and analysis method to measure the user acceptance of ERP in the Oracle NetSuite Purchasing Management module system. In this study, 52 samples were collected using the saturated sample technique questionnaires. The data was analyzed using SEM-PLS with SmartPLS 3.0. The conclusion obtained from the results of this study is to focus more on improving performance expectancy, habit, and behavioral intention in using Oracle NetSuite ERP

Examining the Influence of Perceived Risk on the Selection of Internet Access in the U.S. Intelligence Community

Information technology security policies are designed explicitly to protect IT systems. However, overly restrictive information security policies may be inadvertently creating an unforeseen information risk by encouraging users to bypass protected systems in favor of personal devices, where the potential loss of organizational intellectual property is greater. Current models regarding the acceptance and use of technology, Technology Acceptance Model Version 3 (TAM3) and the Unified Theory of Acceptance and Use of Technology Version 2 (UTAUT2), address the use of technology in organizations and by consumers, but little research has been done to identify an appropriate model to begin to understand what factors would influence users that can choose between using their own personal device and using organizational IT assets, separate and distinct from “bring your own device” constructs. There are few organizations with radical demarcations between organizational assets and personal devices. One such organization, the United States Intelligence Community (USIC), provides a controlled environment where personal devices are expressly forbidden in workspaces and therefore provides a uniquely situated organizational milieu in that the use of personal devices would have to occur outside of the organizational environment. This research aims to bridge the divide between these choices by identifying the factors that influence users to select their own devices to overcome organizational restrictions in order to conduct open-source research. The research model was amalgamated from the two primary theoretical frameworks, TAM3 and UTAUT2, and is the first to integrate these theories as they relate to the intention to use personal or organizational systems to address the choices employees make when choosing between personal and organizational assets to accomplish work related tasks. Using survey data collected from a sample of 240 employees of the USIC, Partial Least Squares Structural Equation Modeling (PLS-SEM) statistical techniques were used to evaluate and test the model, estimate the path relationships, and provide reliability and validity checks. The results indicated that the Perception of Risk in the Enterprise (PoRE) significantly increased the Intention to Use Private Internet and decreased the Intention to Use Enterprise devices, as well as increasing the Perceived Ease of Use of Private Internet (PEUPI). The results of this study provide support to the concept that organizations must do more to balance threats to information systems with threats to information security. The imposition of safeguards to protect networks and systems, as well as employee misuse of information technology resources, may unwittingly incentivize users to use their own Internet and devices instead, where enterprise safeguards and protections are absent. This incentive is particularly pronounced when organizations increase the perceived threat of risk to users, whether intentional or inadvertent, and when the perception of the ease of use and usefulness of private Internet devices is high

Universidad inteligente: una visión de la adopción de la tecnología

Smart University is an emerging concept, strongly anchored to smart technologies and considered by different authors in the literature. Organizations, including universities, need to incorporate smart technologies to take advantage of their capabilities to transform their processes and drive them toward new organizational models. A Smart University focuses on improving its technological infrastructure for achieving its quality educational goals. This paper presents the integration of the key factors for adopting four smart technologies: Cloud Computing, Big Data, Artificial Intelligence, and the Internet of Things. This characterization and integration allow us to conclude on the need to align digital technologies with the organization's processes, requiring greater interaction with the company’s senior management.Universidad inteligente es un concepto emergente, fuertemente anclado a las tecnologías inteligentes, y considerado por diferentes autores en la literatura. Las organizaciones, incluidas las universidades, necesitan incorporar las tecnologías inteligentes para aprovechar las capacidades que proporcionan para transformar sus procesos e impulsarlas hacia nuevos modelos organizativos. Una universidad inteligente se centra en la mejora de su infraestructura tecnológica para lograr sus objetivos educativos de calidad. Este trabajo presenta la integración de los factores clave para la adopción de cuatro tecnologías inteligentes: Computación en la nube, Big Data, Inteligencia Artificial, e Internet de las Cosas. Esta caracterización e integración nos permite concluir sobre la necesidad de alineación de las tecnologías digitales con los procesos de la organización, exigiendo una mayor interacción con la alta dirección de la empresa