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This paper investigated the extent to which the predictive power of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) was robust against cultural variations and to what extent its predictive power could be improved by including face-valid individual differences (i.e. perceived risk and personal innovativeness) and cultural factors (i.e. individualism and uncertainty avoidance).

Data were collected from web surveys of Chinese, American and Belgian mobile Internet users (total n = 1,068).

The authors found that the UTAUT2 model was less predictive in the country where the adoption of mobile payment service (MPS) is high (i.e. China). In contrast, the UTAUT2 model was more predictive in countries where the adoption of MPS is lower (i.e. the United States and Belgium). The authors did not find additional variance explained by individual differences. Regarding the cultural variables, the authors found that individualism moderated the effect of social influence on behavioral intention to use MPS, such that the effect was more substantial among people with individualistic cultural traits. However, the authors found no moderation effect of uncertainty avoidance.

This research contributes to existing work on technology acceptance by exploring whether it is helpful to introduce individual and cultural factors into the UTAUT2 model when predicting technology adoption in different cultures. This research further examines the moderating role of cultural factors in predicting the adoption of MPS. The authors conclude that the UTAUT2 model is generally robust and appears to capture the predictive of face-valid individual and cultural factors.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

With the increasing mobile activity of the Generation Z market (born after 1994), marketers’ interest in this social group is rising. This research paper aims to uncover the relatively unknown attitudes and behaviour of the youth market in an emerging market, South Africa, towards branded mobile applications (apps). Previous studies on mobile marketing have focused on Generation X and Generation Y and generally with a quantitative focus.

This study is based on the theoretical framework of the unified theory of acceptance and use of technology model 2. The study used a qualitative framework with stratified focus groups, aged between 18 and 21 years old at a private tertiary institution in South Africa.

The findings indicate that these South African Gen Z participants mainly used WhatsApp, Instagram, Facebook, Uber and Snapchat. The participants had more positive than negative attitudes towards mobile apps. The findings also showed that privacy was a major concern for the participant’s attitudes and behaviour towards mobile apps. The findings supported the UTAUT2 model, but also discovered new themes. As a recommendation, the issue of privacy and its effect on mobile app adoption is a factor to be researched in the future. The research also provides recommendations for marketers and app developers.

This study was of a qualitative nature, and thus, the sample size was smaller than that of a quantitative study. Future research could add to this study by increasing the sample size and adding a quantitative method such as surveys.

Marketers of mobile apps targeted towards the Gen Z market should aim to be convenient for their users, as well as be entertaining, functional, time-efficient while avoiding excessive in-app adverts, being honest upfront about their pricing strategy, incorporate an element of connectivity into the app and respect their privacy. This paper also provides practical recommendations for mobile app developers (targeted towards Gen Z users) including minimising notifications and updates within the app, developing a mobile app that requires less usage of data (due to the high expense of data in South Africa for the price-conscious Gen Z market) as well as less usage of memory space on the phone and incorporating universal symbols within the mobile app.

This study supported the UTAUT2 model effects of performance and effort expectancy, social influence, facilitating conditions, hedonic motivation, price value and habit on the behavioural intention of users towards a new technology, i.e. GenZ students’ attitudes and behaviour towards branded mobile apps in South Africa. However, an additional condition was discovered in this study, i.e. privacy and its impact on the attitudes and behaviour of GenZ mobile app users. Therefore, this study extends the UTAUT2 model framework. Furthermore, this study uses a qualitative design, which has not been used in previous studies, with a focus on the under-researched Gen Z market, and in particular in an emerging market, such as South Africa.

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.

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

Since the advent of augmented reality (AR) technology, “Smart Retailing” has become the dominant business model in the retail sector. Therefore, comprehending the dynamics of AR adoption is essential if retailers are to successfully encourage customers to embrace this extremely innovative form of technology. As a result, the authors propose and evaluate a more comprehensive model, consisting of the task-technology fit (TTF) and unified theory of acceptance and use of technology (UTUAT2) models, for use in low-income countries.

The present research uses variance-based partial least squares structural equation modeling (PLS-SEM) using WarpPLS.7 to examine 398 responses from Egyptian retail consumers.

TTF, performance expectancy (PE), effort expectancy (EE), social influence (SI), facilitating condition (FC), hedonic motivation (HM) and customer innovativeness (CI) positively affect shoppers' behavioral intentions (BI) to adopt AR Apps in retail, while perceived risk (PR) negatively affects BI.

The current study is the first to investigate the determinants of shoppers' BI toward AR Apps adoption in the retail context using UTAUT2 and TTF models.

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.

This study aims to determine the factors that influence the actual behavior of Islamic digital banking customers based on the users’ perspectives during the recovery from the COVID-19 pandemic crisis.

This study used a causal exploratory method with quantitative and qualitative approaches presented in two parts. The first study (Study 1) was empirical testing of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) used WARP-partial least square by modifying the variables of customer trust and satisfaction. A. Hayes’s PROCESS procedures were applied to examine the moderating effects of age, gender and experience. The second study (Study 2) explored the obstacles and solutions to improve digital banking services. The survey was conducted on 897 Islamic bank customers throughout Indonesia.

The results showed that all the hypotheses about the direct effect of the modification of the UTAUT2 model were supported empirically except for the effect of price value and hedonic motivation on behavioral intention, and there was just one moderating effect in this study. The other results show that 35 factors became obstacles to using digital banking.

This study had limited qualitative data collection techniques that were less deep and comprehensive. This happened because respondents were given complete confidence to fill in the open questions without any follow-up to customer answers. For further research, an in-depth interview method can be added to crucial information from the customer and expert side to get in-depth and complementary data regarding constraints and solutions. This study only used a sample of customers of Islamic banks; further research is expected to use customers of Islamic banks and conventional banks to compare their preferences for digital banking.

This study offered seven strategies that could encourage increased digital banking transactions to accelerate crisis management, mitigate cybercrime and communicate the positive impact of digital banking effectively and efficiently.

This study offered seven strategies that could encourage increased transactions using digital banking to accelerate crisis management, mitigate cybercrime and communicate the positive impact of digital banking effectively and efficiently.

Most of the existing studies focused on the modification model of the UTAUT2 model. The study is unique because it has proposed the obstacle and solution to improve digital banking service in Islamic Bank in Indonesia.

The objective of this study is to investigate the key determinants affecting the acceptance and utilization of Blackboard as a Computer-Assisted Language Learning (CALL) platform among Saudi university students pursuing English as a foreign language (EFL) courses.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

The study's findings indicate that performance expectancy, social influence, effort expectancy and price value significantly affect the attitudes of EFL students toward using CALL. The habit factor was the most robust predictor of behavioral intention and technology use, indicating that CALL usage can become automatic for students and improve their engagement in EFL learning. The study highlights the importance of providing better technical and organizational support to EFL students who want to use CALL more effectively. The theoretical and practical implications of the study's findings are thoroughly discussed.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the UTAUT2 by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

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.