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Green financial technology (FinTech) has received attention for promoting green finance investment and sustainable development. However, how consumer social responsibility and long-term orientation influence the continuance intention of green FinTech users remains unknown in the literature. To fill this gap, consumer social responsibility and long-term orientation are combined with the unified theory of acceptance and use of technology to develop a research model to investigate their moderating effects on the continuance intention of green FinTech users.

A random probability sampling method was adopted, and 377 valid responses were collected to verify the proposed model. Partial least squares structural equation modeling was employed for the data analysis.

Performance expectancy, effort expectancy, social influence and facilitating conditions have significant positive impacts on the continuance intentions of green FinTech users. Surprisingly, consumer social responsibility enhances the effects of performance expectancy and social influence on continuance intention but negatively moderates the effect of facilitating conditions on continuance intention. Moreover, a long-term orientation can increase the impact of facilitating conditions on continuance intention but decrease the impact of performance expectancy on continuance intention.

This paper proposes a research model that reveals how consumer social responsibility and long-term orientation moderate the relationship between the unified theory of acceptance and use of technology (UTAUT) and the continuance intention of green FinTech users to fill a gap in the literature.

This research aims to explore the factors influencing the adoption intention of eco-friendly smart home appliances among residents in densely populated urban areas of a developing country.

A quantitative research approach was employed to gather data from 348 respondents through purposive sampling. A comparative analysis strategy was then utilized to investigate the adoption of eco-friendly smart home appliances, combining both linear (PLS-SEM) and non-linear (fsQCA) approaches.

The results obtained from PLS-SEM highlight that performance expectancy, facilitating conditions, hedonic motivation, price value, and environmental knowledge significantly influence the adoption intention of eco-friendly smart home appliances. However, the findings suggest that effort expectancy, social influence, and habit are not significantly associated with customers' intention to adopt eco-friendly smart home appliances. On the other hand, the fsQCA results identified eight configurations of antecedents, offering valuable insights into interpreting the complex combined causal relationships among these factors that can generate (each combination) the adoption intention of eco-friendly smart home appliances among densely populated city dwellers.

This study offers crucial marketing insights for various stakeholders, including homeowners, technology developers and manufacturers, smart home service providers, real estate developers, and government entities. The findings provide guidance on how these stakeholders can effectively encourage customers to adopt eco-friendly smart home appliances, aligning with future environmental sustainability demands. The research implications underscore the significance of exploring the antecedents that influence customers' adoption intention of eco-friendly technologies, contributing to the attainment of future sustainability goals.

The environmental sustainability of smart homes, particularly in densely populated city settings in developing countries, has received limited attention in previous studies. Therefore, this study aims to address the pressing issue of global warming and make a meaningful contribution to future sustainability goals related to smart housing technologies. Therefore, this study employs a comprehensive approach, combining both PLS-SEM (linear) and fsQCA (non-linear) techniques to provide a more thorough examination of the factors influencing the adoption of environmentally sustainable smart home appliances.

This study aims to investigate the user’s behavior and intention to continue using e-health services by analyzing the factors influencing their decision. The stimuli–organism–behavior–consequence (SOBC) framework was used to assess how the risks and benefits of e-health influence both behavioral intention (BI) and continued use.

The hypotheses proposed for this study were tested with partial least square-based structural equation modeling. This study relied on the primary data collected from 572 respondents using convenient sampling.

This study examined the SOBC model’s four phases’ with the help of eight constructs. The conceptual model allowed the authors to examine 10 relationships to measure e-health adoption behavior in emerging nations like India. This study found that convenience, perceived risk and facilitating conditions are positively related to the effort and performance expectancy (PE) associated with e-health consultation. Only social influence is unrelated. This study also found a positive and substantial relationship between BI, effort and PE.

The study uses the unified theory of acceptance and use of technology and the SOBC paradigm to determine the factors influencing users’ intentions to use e-health. In addition to bringing new aspects to the existing literature on technology adoption and e-health consultation, the results of this study will aid e-health service providers in formulating strategies to promote the usage of e-health in emerging economies like India.

This research was motivated by the recognition that the use of mobile-based agricultural extension services (AES) applications has become increasingly popular among the bottom of the pyramid segment in recent years. However, users’ adoption is determined not only by their perception of the technology but also by its perceived wealth. In other words, even though a technology may be perceived as advanced, if it does not fit users’ wealth perception benefits, they may not adopt it. Using an extended unified theory of acceptance and use of technology (UTAUT) perspective, this study aims to explore potential predictors of behavioral intention toward AES such as effort expectancy, performance expectancy, customer wealth (CW), social influence and perceived characteristics of innovation.

Potential causal connections between key UTAUT factors and users’ intentions to use the services are hypothesized. An integrated theoretical model was developed and tested against the empirical data collected from 336 AES users. A measurement model and structural equation model were tested using AMOS 22.0 and confirmed all 14 hypothesized relationships.

The results were consistent with the recent literature on mobile technology acceptance, confirming an unmoderated relationship between CW and the adoption of mobile-based AES. This research proposes a mobile AES user adoption model by integrating CW with the unified theory of acceptance and usage of technology (UTAUT).

This study establishes CW as an outcome of various relationships.

The Metaverse is an immersive virtual world where individuals interact with each other using an avatar. The Metaverse is promised to offer several potentials for different sectors. While the Metaverse promotes innovative interaction between individuals (e.g. learners), there is a scarcity of knowledge on what influences its acceptance and use in higher educational institutions (HEIs), particularly in developing countries. Thus, this paper aims to identify the factors that affect the users' intentions toward Metaverse technology for educational purposes in the HEIs in Jordan.

A study model was created by incorporating variables from the unified theory of acceptance and use of technology (UTAUT) (performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC) and information system success (ISS) model (user satisfaction, SAT; system quality, SQ; service quality, SVQ and information quality, IQ) with perceived curiosity (PC) and hedonic gratification (HG) constructs. Both PC and HG were added as context-related factors that could contribute to improving the applicability of UTAUT and ISS to a wide range of technology use contexts. Data were gathered from 441 Jordanian university students using an online questionnaire.

The analysis of the structural model revealed that users' behavioural intentions toward using Metaverse were significantly affected by user satisfaction (SAT), performance expectancy (PE), facilitating conditions (FC) and hedonic gratification (HG). Also, information quality (IQ) and services quality (SVQ) were revealed to have a significant influence on user satisfaction. Likewise, the results illustrated a significant impact of systems quality (SQ), information quality (IQ) and service quality (SVQ) on PE. Lastly, a significant effect of PC on the EE factor was found.

This study will shed light on a number of practical implications for developers, designers, service providers and decision-makers supporting the acceptance and adoption of the Metaverse technology in the educational context. Also, it will contribute to developing the right strategies, and Metaverse content which will draw the attention of learners.

As per the surveyed literature and the researcher's prior knowledge, this is one of the first studies that integrate the UTAUT model, ISS model and two contextual factors (PC and HG) besides testing the proposed model in a developing country (Jordan). This paper is one of the few in which the individuals' acceptance behaviour of Metaverse technology was examined in the HEIs context.

This study aims to examine the mediating role of social influence on the relationship between key predictors of E-pharmacy adoption among young consumers based on the unified theory of adoption and use of technology (UTAUT).

This study employs a quantitative correlational research design. Based on cluster sampling, data was collected from 306 university students from three public universities in southwestern Nigeria. Data was analysed using partial least square structural equation modeling.

The primary determinant driving the adoption of e-pharmacy is performance expectancy. Social influence plays a partial mediating role in linking performance expectancy to e-pharmacy adoption. In contrast, it fully mediates the relationship between effort expectancy, facilitating conditions and the adoption of e-pharmacy services.

This study provides theoretical clarity on recent issues within the UTAUT framework. Findings highlight the complexity of how social factors interact with individual beliefs and external conditions in determining technology acceptance.

Research includes information relevant to access the impact of e-pharmacy services on healthcare accessibility, affordability and quality in developing countries.

The findings extend the adoption of technology literature in healthcare and offer a new understanding of adoption dynamics. The results emphasize the importance of performance expectancy in driving e-pharmacy adoption, providing a clear direction for stakeholders to enhance service quality and user experience of e-pharmacy. Additionally, the mediating effect of social influence highlights the significance of peer recommendations, celebrity endorsements and social media campaigns in shaping consumer adoption of e-pharmacies among young people.

The purpose of this study is to analyze the combined effect of eight factors – performance expectancy (PE), effort expectancy (EE), hedonic motivation (HM), system quality (SQ), information quality (IQ), service quality (SEQ), digital literacy (DL) and computer anxiety (CA) on learners’ behavioral intention (BI) toward the adoption of e-learning in higher education institutions (HEIs) in India.

The study used factors from two theoretical models, the extended Unified Theory of Acceptance and Use of Technology and the DeLone and McLean Information Systems Success model. The study also considered DL and CA as additional factors because they could affect a learner’s intention in a developing country like India. Data were collected from three HEIs in Southern India and analyzed using fuzzy qualitative and comparative analysis (fsQCA).

The results of the study emphasize the importance of considering both individual and technological factors in e-learning adoption and provide evidence for the significance of integrating multiple theories in understanding the complex relationship between factors and learners’ BI. Four different configurations of the eight factors: EE*HM*SQ*IQ*SEQ*DL*∼CA; PE*EE*HM*SQ*IQ*DL*CA; PE*EE*HM*IQ*SEQ*DL*CA; and PE*EE*SQ*IQ*SEQ*DL*CA found to be sufficient to cause learners’ BI to use e-learning.

This study explores the complex relationship between different factors and learners’ intention to adopt e-learning using the fsQCA method. These findings may need further validation in HEIs across different geographical locations.

This study provides practical insights for HEIs in India and other developing countries on how different factors combine and interact to determine e-learning adoption in multiple contexts.

Using fsQCA as a novel and rigorous method, this study uncovers the complex and nonlinear causal relationships among various factors that affect e-learning adoption. This study provides a holistic and contextualized understanding of e-learning adoption in a developing country’s scenario. This study can inform educators and policymakers on how to design and implement effective e-learning strategies that suit different learner profiles and contexts.

This study delves into the behavioural intentions of educators within medical colleges at Mosul Universities concerning the adoption of Knowledge Management-Driven Metaverse technology (KM-D-MT). Rooted in an adapted Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model, the research aims to enrich the understanding of Metaverse adoption factors, exploring correlations among key constructs such as performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value, hedonic motivation and interaction. Furthermore, the study investigates the mediating roles of knowledge generation and knowledge sharing in the relationship between interaction and behavioural intention.

The research employs a quantitative approach, gathering 278 responses from educators in medical colleges. Structural Equation Modelling-Partial Least Squares (SEM-PLS) is used to analyse the data, rigorously examining the reliability and validity of research instruments. The investigation involves an extensive evaluation of various factors influencing educators’ intentions to adopt KM-D-MT, using a cross-sectional design.

The study reveals significant positive impacts of performance expectancy, effort expectancy, social influence, facilitating conditions, perceived value and hedonic motivation on behavioural intention to adopt KM-D-MT. Interaction is identified as a key factor positively influencing knowledge sharing and knowledge generation. Furthermore, knowledge sharing and knowledge generation exhibit positive correlations with behavioural intention. Interaction indirectly impacts behavioural intention through the mediating roles of knowledge generation and knowledge sharing, highlighting the transformative potential of Metaverse technology in reshaping knowledge processes.

The findings of this study hold practical implications for educators, institutions and policymakers. The adoption of KM-D-MT can enhance educational experiences, facilitate global collaboration and contribute to the continuous professional development of educators in medical colleges. Institutions are encouraged to strengthen technological and organisational infrastructure to support effective Metaverse implementation. Furthermore, promoting positive social norms, providing technical support and offering training programs can contribute to overcoming barriers and fostering a conducive environment for Metaverse adoption in medical education.

This research significantly contributes to theoretical perspectives by advancing Metaverse research and addressing the call for extensive studies covering theoretical, conceptual and empirical elements. It extends current UTAUT2 frameworks, exploring correlations in the context of medical education and contributes to knowledge management paradigms. The study’s originality lies in its exploration of Metaverse acceptance in higher education institutions, specifically in medical colleges in Iraq, providing valuable insights for further research and practical applications globally.

This paper aims to examine employees’ online learning continuation intentions (OLCI), exploring factors such as performance expectancy (PE), effort expectancy (EE), social influence (SI), perceived benefits (PB) and management support (MS) influencing their commitment to online learning engagement.

The Unified Theory of Acceptance and Use of Technology (UTAUT) model was expanded to include PB and MS constructs. This study used a quantitative research approach using purposive sampling techniques. Three hundred and eighty-six responses from Indian information technology (IT) professionals at various levels were analysed using Statistical Package for the Social Sciences-Analysis of Moments Structures tool.

This study found a strong positive influence of PE, EE, PB and MS on OLCI in the context of post-pandemic. Workplace learning rapidly generates outcomes if employees associate it with their career growth. However, the authors found that SI does not significantly affect OLCI.

This research is unique work in the area of workplace learning by evaluating the OLCI of IT professionals using the extended UTAUT model in a new normal. Moreover, this study contributes to online learning literature with a combined study of technology usage, continuance intention and organization learning and development.

Building on technology acceptance and learning transfer theories, this study aims to evaluate the integration of mobile augmented reality (MAR) in omnichannel retailing touchpoints for Generation Z (or Gen Z)'s apparel shopping, assessing how habitual augmented reality (AR) use in nonretailing contexts impacts Gen Z's motivations, acceptance and use of MAR shopping apps.

A total of 562 participants downloaded a footwear MAR app and completed a survey. Data were analyzed using confirmatory factor analysis and multivariate regression to explore moderated mediation effects.

The study reveals a paradigm shift: Gen Z's habitual use of AR in social media (e.g. Snapchat and TikTok face filters) significantly influences their intent to use MAR in shopping, overshadowing hedonic motivations. This marks a transition from AR as a gimmick to a practical utility in omnichannel touchpoints, with performance expectancy emerging as a critical mediator in adopting MAR for utilitarian purposes.

This study highlights how Gen Z consumers’ tech habits influence their pragmatic view of MAR, urging re-exploration of the main constructs of the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model.

Findings suggest Gen Z values practicality over fun in MAR shopping apps, guiding marketers to emphasize tangible benefits for this demographic.

This research underscores the evolving perception of AR in retail among mobile natives, highlighting the shift from novelty to habitual utility. It offers strategic insights for integrating AR into omnichannel strategies, catering to the utilitarian expectations of Gen Z in the digital retail landscape.