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This study aims to examine the research pattern and growth trends of published research on a unified theory of acceptance and use of technology 2 (UTAUT2) from 2012 to 2019. The study also examines the research scope of UTAUT2 for future researchers.

This study has adopted a bibliometric approach followed by a structured literature review analysis to synthesize the research on UTAUT2 since 2012. In total, 163 documents were analyzed for type of studies, theories and frameworks, methodologies, author wise collaboration, organizations that contributed to the body of knowledge in the UTAUT2 research and journals that published studies in this domain. VOSviewer and Tableau were used for the data visualization, whereas TCCM, which means theory (T), context (C), characteristics (C) and methodology (M) framework is used to propose the future research directions.

The findings reveal research on UTAUT2 is growing. The structured literature analysis of the top 15 cited articles further analyzed the parsimony of new models in detail. In addition, the study highlights the inception by and promoters of UTAUT2 in a separate section. The data for this study was collected by searching the title, abstract and keywords of documents in the Scopus database.

This study is based on research papers, published in the UTAUT2 research area, that have been extracted from the Scopus database by keywords only. Future studies can also perform a meta-analysis of various clusters generated by bibliometric analysis.

This study is useful for practitioners to devise strategies for increasing technology acceptance, adoption and utilization in the times to come.

To the best of the authors’ knowledge, this study is one of the very few and early studies, which examined patterns and growth trends of the UTAUT2 studies with the TCCM framework, to suggest scope for future research studies.

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.

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 research empirically studies consumers' continued intention to use mobile food delivery applications (apps) during the post-pandemic era in Saudi Arabia.

Using the unified theory of adoption and use of technology 2 (UTAUT2) as a theoretical model, this study collected data from a survey of 304 Saudi Arabian consumers. Structural equation modelling (SEM) was used to examine the proposed model and its hypotheses.

Social influence and performance expectancy (PE) had the strongest effects on the intention to continue using mobile food delivery apps in the post-pandemic era. In addition, effort expectancy (EE) significantly influenced PE regarding the adoption of food delivery apps. Meanwhile, EE was not an important predictor of the continued intention to use mobile food delivery apps in Saudi Arabia.

This study enriches the literature on consumers' continued intention to use food delivery apps in the post-pandemic era, a subject that has rarely been studied. In addition, this study expands the theoretical potential of the UTAUT2 model by examining the role of trust in continued intention and the effect of PE on EE in the adoption of food delivery apps during the post-pandemic era in Saudi Arabia.

This study examines the main factors influencing banking customers' behavior toward smart banking services (SBS) adoption in Pakistan. This study extends the unified theory of acceptance and use of technology (UTAUT2) by integrating information privacy concern and big brother effect into an overarching conceptualization.

This study adopts theoretical constructs from the related literature and develops hypotheses. An analysis of 385 banking customers was performed using partial least squares structural equation modeling (PLS-SEM).

The results show that most predictors of behavioral intention, including facilitating conditions, effort expectancy, habit, performance expectancy, hedonic motivation (except for social influence and price value), big brother effect and perceived information privacy concern are significant. Indeed, all predictors of use behavior are also significant. Gender and age differences between individuals further moderate the relationship between UTAUT2 constructs. Moreover, information privacy concern mediates the relationship between big brother effect and behavioral intention.

This cross-sectional study focused only on Pakistan as a developing country, which limits the generalizability of the results.

The roles of social influence and price value must be strengthened by employing marketing strategies and personalized communication. Banks should offer incentives and rewards to customers who recommend SBS to friends and family members. In addition, banks must consider the price factor when offering these services to increase their market share.

This study contributes to the field of technology adoption by providing a unique perspective of SBS adoption in Pakistan. This empirical study is the first to extend the UTAUT2 model by integrating information privacy concern and big brother effect to assess SBS acceptance and use behavior. This study examines SBS adoption issues at the national level, especially in Pakistan.

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 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.