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This study aims to extend existing theories and fills research gaps regarding the acceptance and use of new technologies by consumers by exploring the adoption of app-cab services in India. Through the application and comparison of a unified theory of acceptance and use of technology (UTAUT) and UTAUT 2/expanded-UTAUT (E-UTAUT) models, this paper empirically tests the relationships between important constructs related to technology adoption, acceptance and utilization in India’s emerging economy.

In total, 612 responses to a questionnaire of active and regular users of app-cab services in India are examined. Path analysis and structural equation modeling presents interesting findings indicating that the expanded models have huge implications for the Indian app-cab industry.

This paper finds that the UTAUT 2/E-UTAUT models are a good fit for consumers and their behavior toward technology-based services. In particular, this study, one of the first of its kind, examines consumer acceptance and use behavior and identifies the factors that influence customer behavior with regard to new technology (app-cab services) in an emerging economy (India). Theoretical and practical implications are discussed.

Very few studies are available on app-cab adoption in emerging economies.

This study aims to investigate the factors influencing the adoption of online pharmacies in Qatar using the unified theory of acceptance and use of technology-2 (UTAUT-2) framework. Specifically, this study examines the impact of performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness of behavioral intention, which in turn affects the adoption of online pharmacies. Furthermore, this study explores the moderating role of word-of-mouth (WOM) recommendations on the relationship between behavioral intention and online pharmacy adaptation.

This study adopted a descriptive, quantitative approach to investigate the UTAUT-2 model in the context of consumers’ adoption of e-pharmacy in Qatar. Through convenience sampling, 455 responses were collected from regular customers accessing online pharmacy services. The data were analyzed using Smart-PLS 3.2 software to examine the hypothesized relationships.

The results showed that WOM recommendations significantly enhanced the relationship between behavioral intention and adopting online pharmacies in Qatar. This study identified the factors that may hinder or enable the adoption of online pharmacies, including performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness.

This study contributes to the existing literature on technology acceptance by extending the UTAUT-2 model and recognizing three additional variables (perceived risk, technology trust and technology awareness). These need to be investigated against UTAUT-2 variables to detect the significance of their impact on adapting the e-health concept in Qatar. The potential for cultural change to accelerate the adoption of online pharmacies is highlighted. Future research should explore the role of moral and cultural factors in technology adoption.

The results underscore the economic and social significance of e-pharmacy adoption, particularly within the context of a developing country. Considering the positive intentions expressed by individuals toward e-pharmacy, it becomes crucial for managers and decision-makers to make strategic choices to address any challenges that may arise. Policymakers are encouraged to enhance their services and implement various development initiatives to expand e-pharmacy accessibility and availability.

This study builds upon previous research on e-commerce in the pharmaceutical industry and provides a comprehensive understanding of customers in developing countries. Extending the UTAUT-2 model and identifying additional variables contributes to the knowledge of e-health concepts in Qatar. The findings have practical implications for developing strategies to promote online pharmacy adoption in Qatar and other countries.

Bicycle sharing offers a novel way to create smart and sustainable mobility solutions for the future. The purpose of this study is to draw on the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) framework for identifying the factors necessary to predict bike-sharing intention among users in India.

Data were collected through a questionnaire distributed across four major cities in India, and 515 responses were analyzed. A sequential approach was employed to analyze the data using Partial Least Square–Structural Equation Modeling (PLS-SEM) and Fuzzy-set Qualitative Comparative Analysis (fsQCA).

The findings from PLS analysis revealed that performance expectancy, effort expectancy, facilitating conditions, hedonic motivation and price value are the salient variables that affect users' intentions to participate in bike sharing. In addition, based on fsQCA, six configurations of causal conditions are presented as intermediate solutions that produce the same results. Although antecedent conditions, such as habit and social influence, had an insignificant effect on individuals' BSI, they create conditions sufficient to encourage users' participation in bike sharing in combination with other variables.

A few limitations of this research and the implications of the findings in terms of theory and policy implications are also discussed.

The reported study is one of the earliest to explain bike-sharing adoption in India using the UTAUT 2 model.

The research aims at examining educators’ perceptions, attitudes and behavioral intentions toward learning analytics (LA) and the role of self-instruction within the proposed model for LA adoption.

A quantitative approach is utilized in which a questionnaire is designed as a tool for data collection and partial least squares structural equation modeling (PLS-SEM) is used for data analysis and model testing.

Results show that performance expectancy and effort expectancy have a significant effect on educators’ attitudes, which in turn significantly affect educators’ behavioral intentions. Self-instruction mediates the relationship between educators’ attitudes and behavioral intentions. The attitude towards LA mediates the relationship between LA performance expectancy and educators’ self-instruction. The research model explains 54% of the variance in learning analysis adoption.

Findings open a path for research on pedagogical factors affecting LA adoption and guide education managers toward facilitating LA adoption. The tested model contributes to LA and teaching and learning literature by highlighting the role of educators’ self-instruction in LA adoption.

The authors aim to study a conceptual model based on behavioural theories (UTAUT-3 model) to evaluate the adoption, usage and recommendation for neobanking services in India.

The authors propose this model based on the UTAUT-3 integrated with perceived risk constructs. Hypotheses were developed to determine the relationships and empirically validated using the PLSs-SEM method. Using the survey method, 680 Delhi NCR respondents participated in the survey.

Empirical results suggested that behavioural intention (BI) to usage, adoption and recommendation affects neobanking adoption positively. The research observed that performance expectancy (PE), effort expectancy (EE), perceived privacy risk (PYR) and perceived performance risk (PPR) are the essential constructs influencing the adoption of neobanking services.

Limited by geographic and Covid-19 constraints, a cross-sectional study was conducted. It highlights the BI of neobanking users tested using the UTAUT-3 model during the Covid-19 period.

The study's outcome offers valuable insights into Indian Neobanking services that researchers have not studied earlier. These insights will help bank managers, risk professionals, IT Developers, regulators, financial intermediaries and Fintech companies planning to invest or develop similar neobanking services. Additionally, this research provides significant insight into how perceived risk determinants may impact adoption independently for the neobanking service.

The purpose of this study is to reveal both the adaptations of information computer technology (ICT) teachers teaching the information technologies and software (ITS) course online during the pandemic and the factors that affect this adaptation process. Teachers’ endeavours to conduct their courses online, the support they take during their endeavours, and their relationships with such basic components as the environment, content and students during this adaptation process will be revealed within the framework of unified theory of acceptance and use of technology (UTAUT).

In this study, a sequential transformative mixed model was used in which firstly quantitative and then qualitative data were collected and analysed. The sample of this study consists of 307 ICT teachers employed and serving at public and private school in 2020–21. A proper sampling technique is used in the study. In this study, a sequential transformative mixed model was used in which firstly quantitative and then qualitative data were collected and analysed ( Creswell, 2009). The sample of this study consists of 307 ICT teachers employed and serving at public and private school in 2020–21. A proper sampling technique is used in the study.

The ICT teachers’ adaptations to the online courses have developed positively over the sub-dimensions of UTAUT, which are performance expectancy (PE), effort expectancy (EE), social influence (SE), facilitating conditions (FC) and behavioural intention (BI). The ICT teachers’ adaptations to the online instruction process have a significant effect on PE, FC and BI on the basis of gender, and on PE and EE on the basis of course content quality. In the process whereby the ICT teachers carry out the ITS course online, the sub-dimensions of PE, SE and FC are significantly predictive of the BI.

UTAUT has been taken as a guiding framework in explaining and discussing the adaptations. Similarly, in other studies focussing on adaptation, this model could be employed in planning the research process. In addition, this study has followed a method in which qualitative data are mostly used to explain the quantitative data. Further studies may adopt a process whereby qualitative data are largely used to describe the way ITS course is conducted in online environments and this process may be used to develop a model.

Examining the students’ BIs in online courses overlaps with the sub-dimension of PE in this study, which stresses that PE, EE and motivation are significantly and directly effective on the students’ intentions of using the online courses, while there is a difference between these two studies in terms of the dimension of EE. The factors such learning outcome, curriculum, attendance to the course, use of materials and tools, interaction and technological substructure appear to be affected by this dimension, so they could be taken as important in that they reveal the importance of the study.

This study may provide clues for the online instruction practices that it reveals teachers’ adaptations to online learning environments at secondary schools. On the other hand, software, hardware, coding and robotics take place in the subjects like product designing, developing and programming that are within the content of ITS course for secondary schools. Even though there is a curriculum prepared for these subjects, a lot of different instruction techniques can be used for the teaching of these subjects. This can allow some inferences about the environments and methods suitable for the online instruction of the related subjects.

This paper aims to examine the factors that influence bank customers’ acceptance towards FinTech using the unified theory of acceptance and use of technology (UTAUT) model.

A survey was carried out, and a judgemental sampling method was used. Moreover, over 200 responses were gathered from individuals that were bank account holders. Besides, the literature on the factors that influence an individual acceptance towards FinTech using the UTAUT model was also reviewed as an effort to contribute towards the factors that are significant in predicting the acceptance of FinTech services.

The results of the study revealed that performance expectancy and effort expectancy are the main factors in determining the acceptance of FinTech services. Moreover, consumer innovativeness plays an important role in the acceptance of FinTech by bank users. In contrast, social influence and facilitating conditions were not the determinants of FinTech acceptance in Pakistan.

This study not only contributed to the theoretical extensions but also to practical implications, which would benefit the community of FinTech service providers in Pakistan.

The limitations of this study were two but are not limited to, firstly, the respondents which were taken among bank customers in Pakistan, confining its contribution to the narrowed perspective of Pakistan. Besides, this study also considers its contributions towards the use of the UTAUT in which the factors examined were specific, which may elucidate that the generalization of the findings only includes FinTech, where the UTAUT comes into play. This study is an eye-opener for the merging perspective of both the UTAUT and FinTech.

UTAUT is extended in the context of FinTech. Consumer innovativeness is incorporated in the context of the UTAUT model. Consumer innovativeness is yet to be tested and for that this study is a useful reference for academicians, policymakers and future researchers.

This paper aims to analyse the adoption of fitness wearables by using the unified theory of acceptance and use of technology (UTAUT). The study analyses the relative weights and causal combinations of antecedent variables on use and intention to use fitness wearables.

The study design involves two stages: first, from the perspective of variable-oriented analysis, a structural equation model is tested using partial least squares (PLS) technique on a sample of 176 adopters and a second sample of 187 non-adopters. Second, from the perspective of case-oriented analysis, a fuzzy set qualitative comparative analysis (fsQCA) identifies causal combinations of variables that lead to use of wearables by adopters and intention to use by non-adopters.

PLS results show that performance expectancy and effort expectancy have high net effects on use and intention to use for adopters. FsQCA analysis shows that current users follow a streamlined path to adoption. High beliefs on performance expectancy and effort expectancy are the main influences of intention to use a fitness wearable for non-adopters. In contrast to adopters, non-adopters may follow a number of paths to intention to use through performance expectancy, effort expectancy or facilitating conditions. This insight was apparent only after analysing the data sets by using fsQCA.

For sake of parsimony, this paper tested UTAUT model instead of the more complex unified theory of acceptance and use of technology 2.

Marketers in the fitness category can enhance use and intention to use by utilising not one but a combination of causal factors such as performance expectancy, effort expectancy and facilitating conditions. Wide societal deployment of wearables depends on performance and expectations.

The widespread use of mobile devices depends on performance expectancy and effort expectancy. To transit to a real knowledge economy, co-creation should occur at early stages of product development so that these expectations are shared and better products be developed.

This paper offers a nuanced understanding of fitness wearable adoption by analysing adopters and non-adopters through variable- and case-oriented techniques. It complements the one-linear-path perspective with a number of alternative causal combinations of variables that lead to use and intention to use fitness wearables. While the causal path for adopters is unique, there are a number of causal combinations of antecedents that lead to high intention to use in potential adopters.

This study aims to integrate extant research on eWallet adoption to better understand the key antecedents to eWallet use intention and examine whether the relationships differ across multiple moderators.

To integrate eWallet adoption findings, the unified theory of acceptance and use of technology (UTAUT) and its extensions were utilized. Meta-analyses estimated the relationships between eWallet use intention and seven antecedents and the intercorrelations between antecedents. A total of 28 effects were calculated, utilizing 48 studies and 444 individual effect sizes, using 14,802 subjects. Using meta-analytically derived values, regression and relative weight analysis then determined each antecedent's relative utility. Furthermore, moderator analyses examined whether eight theoretically based moderators influenced the relationships between the antecedents and eWallet use intention.

Price value, hedonic motivation, facilitating conditions and social influence had the strongest relationships with the intention to use eWallets, accounting for virtually all the unique variance. The three weakest antecedents, however, still explained a large percentage of variance. No relationships were significantly moderated.

Due to the lack of data in primary studies, some UTAUT moderators could not be analyzed. Also, common method variance may impact the findings because the primary studies used cross-sectional surveys.

This study provides guidance regarding how companies can increase eWallet adoption rates, which have lagged in certain countries. These recommendations include specific techniques for tailoring messages and emphasizing features and benefits.

To the best of the authors’ knowledge, this is the first integrative meta-analysis conducted on eWallet use. Combining meta-analysis, regression and relative weight analysis, this study provides an integration of what is currently known about eWallet use intentions.

The purpose of this paper is to identify a model that provides explanations for normative behavior in information technology (IT) use, and to test the model across two different types of normative behavior (i.e. green information technology (GIT), and digital piracy (DP)).

The proposed model is based on the norm activation model (NAM) and the unified theory of acceptance and use of technology model (UTAUT). A total of 374 and 360 usable responses were obtained for GIT and DP, respectively. The authors use the SEM technique in order to test the proposed model on the two sub-samples.

Findings from the proposed model show that DP users’ personal norm (PN) negatively impacts behavioral intention and actual behavior. These findings indicate that users of IT who indulge in DP understand that use of pirated software may not be a socially approved behavior but they still indulge in it because their PNs are not aligned with social expectations. GIT users’ PN positively impacts behavioral intention and actual behavior, and the relationship is stronger for behavioral intention than for actual behavior.

The sample consists of college students and working professionals based in India who may be savvy with respect to internet use. Future work may evaluate whether the pattern of results that the authors report for normative behavior does hold across other types of normative behavior.

These findings hint at a gap between the moral compass and the final “action” taken by DP users. What managers need to do is to create awareness among their customers about the implementation of DP/GIT and help users engage in normative behavior.

This research contributes to the literature by integrating the UTAUT and the NAM to explain normative behavior of IT use. The authors propose and test a model that identifies cognitive as well as social-psychological motivations to explain normative behavior in IT use, which have been sparingly studied in extant literature, and provides a holistic understanding of the phenomenon. As such, this research contributes to the existing knowledge of understanding of normative IT behavior.