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This study aims to understand the learner behaviour of millennials for Massive Open Online Courses (MOOCs) in the post-adoption stage by extending the theory of Unified Theory of Acceptance and User Technology 2 (UTAUT2) with expectancy confirmation model (ECM) along with personal innovativeness as the exogenous, satisfaction as a mediating and continued intention as an endogenous construct.

This study applied a cross-sectional research design by using a survey method to collect primary data with a structured questionnaire. Convenience sampling was used to collect data from millennial MOOC users, and partial least square structural equation modelling method was applied for data analysis.

The results indicate that performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation influence satisfaction. Similarly, performance expectancy, hedonic motivation, personal innovativeness and satisfaction influence the continued intention for MOOCs.

In terms of limitations, the study applied a cross-sectional research design that could lead to data collection bias. Similarly, the study used convenience sampling as the authors did not have access to the participant list of users from MOOC platforms.

The research highlights various insights to all the stakeholders on improving MOOC satisfaction and enhance the continued intention for millennial learners.

The findings of this research bridge this gap by examining the post-adoption usage behaviour of MOOCs by extending the baseline model of UTAUT2 with personal innovativeness and integrating it with ECM.

The presented study aims to provide an understanding of the mechanism whereby foresight is accepted by Czech companies. The results of the study can offer insights into how to design an optimized corporate foresight tool.

The well-established framework of unified theory of acceptance and use of technology (UTAUT2) served as a baseline for research into key determinants of the behavioral intention to use the foresight. The proposed research model included independent variables of UTAUT2 relevant in the context of foresight. The additional variable of personal innovativeness was introduced as a potential predictor. Structural equation modeling (SmartPLS 2.0 software) was used to evaluate the data.

Performance expectancy regarding foresight was identified as the most substantial predictor of behavioral intention in line with the scientific literature. Surprisingly, the second strongest predictor was the construct of personal innovativeness, and social influence was also proven to affect behavioral intention. The results show that traditional determinants of effort expectancy, facilitating conditions, hedonic motivation and habit did not play a significant role in relation to behavioral intention to adopt the foresight.

The attributes of cost and intention to use could not be included in the research model, as the corporate foresight is not commonly implemented. Second, the tested sample included 103 interviewed organizations but only from Czech Republic.

The study primarily aims to enhance the corporate foresight theory. Secondarily, it extends the UTAUT2 theoretical framework by testing personal innovativeness as a variable explaining behavioral intention. The authors provide statistical evidence of factors impacting the adoption of corporate foresight by companies.

This paper investigates if the existing degree of students' acceptance and use of mobile or m-learning may face the online shift determined by SARS-CoV-2. Based on the extended unified theory of acceptance and use of technology (UTAUT2), a new comprehensive model, SD-UTAUT (social distancing-UTAUT), is developed to better understand relationships between the original constructs, plus personal innovativeness (PI) and information quality (IQ). It identifies the key factors affecting behavioral intention (BI) and use by examining the influence of revaluated hedonic motivation (HM) and learning value (LV) importance as mediators.

The paper opted for an exploratory study involving 311 learners, using partial least squares structural equation modeling (PLS-SEM).

SD-UTAUT can be a new m-learning model in higher education. It has high predictive power and confirmed 15 out of 16 hypotheses. The most powerful relationship is between performance expectancy (PE) and HM. IQ affected LV the most, since HM the behavioral use (BU). HM impacts the use behavior (UB) more than LV, but habit (HT) affects it the most.

Because of the pandemic context, output may lack generalizability and reproducibility.

To improve usage, staff must provide better support, course creators emphasize the objectives and competencies and developers integrate innovation. The joy and pleasure of m-learning use may stimulate the LV through interesting and interactive content, like incorporating gamification.

The model set-up and circumstances are previously unseen. SD-UTAUT confirms ten new hypotheses and introduces the student's grade point average (GPA) as a moderator.

The peer review history for this article is available at https://publons.com/publon/10.1108/OIR-01-2021-0017

This study aims to expand the Unified Theory of Acceptance and Use of Technology (UTAUT2) by exploring the effect of two new predictors: technological innovativeness and information quality, along with the learning value and the original determinants that influence faculty and students’ acceptance of the Moodle-Learning Management System. The modified model includes nine predictors: performance expectancy, effort expectancy, social influence, facilitating conditions, learning value, hedonic motivation, habit, technological innovativeness and information quality.

The study is based on a cross-sectional survey design. The target population was faculty and students of the University of Kufa in Iraq. An online questionnaire was used to collect 228 responses from faculty and 553 from students.

Results of the Structural Equation Modeling (SEM) Partial Least Squares (PLS) analysis revealed that factors which influence faculty acceptance were social influence, facilitating conditions, hedonic motivation, habit, technological innovativeness and information quality, while factors which influence student acceptance were performance expectancy, facilitating conditions, learning value, hedonic motivation, habit, technological innovativeness and information quality.

The theoretical and practical contribution of the present study lies in the expansion of the UTAUT2 model through adding neoteric predictors, which are technological innovativeness and information quality. This study provides insights and further understanding of the effect of predictors (original and additive) on users’ acceptance of e-learning management system. In addition, the findings of the current study enable decision-makers and those interested in developing Moodle-LMS to obtain in-depth information on these indicators, especially in the Iraqi higher education environment.

Based on the unified theory of acceptance and use of technology (UTAUT2), the purpose of this study was to examine users’ continued usage intention of mobile event application (MEA) technology.

A self-administered online survey was used to collect the study data from 407 MEA users, and structural equation modeling was used to test the study’s hypotheses.

The study’s results revealed that users’ continued usage behavior was positively influenced by effort expectancy, performance expectancy, habit, facilitating condition and perceived security. The study’s results further indicated that personal innovativeness had a positive impact on effort expectancy and performance expectancy.

The findings of the current study deliver important practical implications for event organizers and event technology vendors for identifying factors affecting MEA users’ continued usage intention.

By extending UTAUT2, the current study is one of the first studies that examined users’ intention to continue to use MEA technology.

论影响参会人员继续使用移动会展App的因素

本论文基于UTAUT2模型, 旨在检验用户继续使用移动会展App（MEA）的影响因子。

本论文采用网上问卷的形式, 样本数据为407为MEA用户, 使用SEM来验证研究假设。

研究结果表明, 用户继续使用行为受到以下因子的正向影响：努力预期、效果预期、习惯、辅助条件、以及感知安全。本论文结果进一步表明个人创新对努力预期和效果预期有着积极影响。

本论文结果为会展组织者和会展科技商指出了影响MEA用户继续使用意图的影响因子, 提供了有价值的启示。

本论文拓展了UTAUT2模型, 是首批验证用户继续使用MEA科技的文章之一。

Notwithstanding the dynamics of digital transformation and its relevance for revenue generation in the entertainment industry, empirical research that focused on consumer behavior at the intersection of sport content and media technology acceptance is limited. Virtual reality (VR) is a re-emerging and nowadays commercially available technology that impacts sport consumed through media. The purpose of this paper is to investigate the consumer acceptance of VR technology and highlight the effects of content quality and flow experience as influencing factors of behavioral intention.

Based on a literature review, the authors constructed and empirically tested a model that extends the unified theory of acceptance and use of technology (UTAUT2) by considering additional antecedent factors. Participants (N=570) in the empirical study viewed sport content via VR technology (Sport VR) and completed a survey before and after viewing. The authors conducted factor analysis and structural equation modeling.

Three UTAUT2 influencing factors, i.e., performance expectancy, social influence and hedonic motivation, showed significant effects. Furthermore, flow and content quality had positive indirect effects. Thus, the quality of sport content and the state of flow that users experience when immersed in a VR environment are relevant factors that determine the performance expectations of consumers and their Sport VR usage intention.

This empirical study contributes to knowledge on consumer acceptance of a hedonic technology in a sport media context. Moreover, two factors extended the established UTAUT2 model.

The internet creates ample opportunities to start a mobile social commerce business. The literature confirms the issue of customer trust for social commerce businesses is a challenge that must be addressed. Hence, this study aims to examine the antecedents of trust in mobile social commerce by applying linear and non-linear relationships based on partial least squares structural equation modeling and artificial neural network model.

This study applied a non-linear artificial neural network approach to provide a further understanding of the determinants of trust in mobile social commerce based on a non-linear and non-compensatory model. Besides, a questionnaire was distributed to 340 social commerce customers in Malaysia.

The conceptual framework for investigating trust in mobile social commerce has various advantages and contributions to predicting consumer behavior. The results of the study showed there is a positive and significant relationship between social support, presence and unified theory of acceptance and use of technology2 (UTAUT2). In addition, UTAUT2 has fully mediated the relationship between social support, presence and trust in social commerce. Finally, the results concluded the relationship between UTAUT2 and trust in social commerce would be stronger when the diffusion of innovation and innovation resistance is high and low, respectively.

The current study provides a novel perspective on how customers can trust social m-commerce to provide real solutions to managers of encouraging e-marketing among consumers.

This paper shows how businesses can develop trust in social m-commerce in Malaysian markets. The findings of this study probably could be extended to other businesses in Asia or other countries. Because trust in social e-commerce has a dynamic role in consumer behavior and intention to purchase.

This study provided a new perspective on mobile social commerce and paid more attention to an investigation of such emerging commerce. The originality of this study is embodied by investigating an integrated model that included different theories that presented new directions of trust in mobile social commerce through social and behavioral determinants.

The substantial benefits of e-procurement to organizations and institutions have, over the past two decades, become central to supply chain management. This study aims to identify the factors that facilitate the adoption of e-procurement system using modified Unified Theory of Acceptance and Use of Technology (UTAUT2).

Using a quantitative approach, the factors identified in the UTAUT2 are operationalized and examined carefully. The investigation has been conducted using a survey questionnaire. The data set has been obtained from 205 construction professionals in Ghana.

The research evinced that the decision by individuals to adopt e-procurement is mainly influenced by performance expectancy and social influence. By implication, the study found out that the respondents are more likely to adopt e-procurement if it is seen to be user-friendly and useful, and when they have a community of people supporting its use. Overall, the findings suggest that the model can stimulate a high adoption and intention to use e-procurement technologies, given its good predictive potential and robustness.

The structures uncovered in the study show that not all UTAUT2 factors are applicable within the study area. The findings provide a good backdrop in the development of policy and a roadmap for e-procurement implementation in Ghana. This is particularly useful for system development and implementation purposes for government agencies, contracting organizations, professionals and users of e-procurement technologies.

The original contribution and value of the paper is the use of UTAUT2 to provide evidence on their significance to e-procurement adoption among construction professionals.

This study aims to explain the factors affecting students’ acceptance and usage of a lecture capture system (LCS) – ReWIND – in a Malaysian university based on the extended unified theory of acceptance and use of technology (UTAUT2) model. Technological advances have become an important feature of universities’ plans to improve the flexibility and accessibility in a learning and teaching environment. For private universities, which are market-driven, it is vital to assess if these technologies influence the perceptions and behaviour of their target beneficiaries.

The study is designed using a causal research design to examine the cause–effect relationship between the study variables. The study sample consists of 398 students selected via purposive sampling. Data are collected using a five-point Likert scale covering UTAUT2’s factors and variables featuring ReWIND’s acceptance and usage. Partial least squares-based structural equation modelling is used to analyse the data.

The findings show that performance expectancy, effort expectancy, social influence, facilitating conditions, price–value, hedonic motivation and habit have significant influence on students’ acceptance and usage of ReWIND.

This research examines the factors affecting students’ acceptance and usage of ReWIND in a Malaysian university. The main limitation of this study is that it focuses only on the factors highlighted in the UTAUT2 model.

The results provide a useful framework to the universities for the successful implementation of student-friendly technologies such as ReWIND to enhance their learning experience.

Responding to the need of studies validating the UTAUT2 model in the adoption and use of different technologies, this study contributes to the literature by extending the UTAUT2 into the context of LCS at a private university in a developing country.

In keeping with global developments rendering online shopping as an emerging trend among consumers, the present study extends the unified theory of use and acceptance of technology (UTAUT2) comprising the digital payment mode (DPM) as a new driver of online shopping and with the mediation of attitudes toward technology (ATTs) to gauge a better and deeper understanding of behavioral intention (BI).

This study used a survey instrument with snowball sampling from 600 consumers in northern India. Partial least squares structural equation modeling was used to find the association between drivers using UTUAT2, along with DPM and ATTs. The data were divided into a test group (20%) and validated through a training group (80%).

DPM was shown to be directly associated with BI. The mediation of ATTs was also validated through the model. The predictability of the model was 67.5% for the test group (20%) and 69.6% for the training group (80%). The results also indicated that facilitating conditions is a critical driver of BI.

This study enhances the understanding of the roles that DPM and ATTs play in BI during online shopping, suggesting that Indian managers need to adopt DPM as a support service to make online shopping a worthwhile experience.