Earlier literature has shown that the implementation of FinTech innovations is not only determined by banks, financial institutions, or government support, but also by the perception and experiences of FinTech users. FinTech research has shown encouraging findings from scholars in developed countries. However, little is known about the users’ acceptance and use of FinTech in Jordan. The aim of this study is to investigate the determinants of users’ intentions and e-Loyalty toward FinTech adoption in Jordan post the COVID-19 era. A conceptual framework was developed by integrating the four original constructs of the unified theory of acceptance and use of technology (UTAUT), namely performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), with three additional factors: personal innovativeness (PI), financial literacy (FL), and uncertainty avoidance (UA). In addition, the proposed model considered the e-Loyalty of FinTech users as a consequence of having a good FinTech experience. A quantitative approach using a cross-sectional online questionnaire was applied to collect data from 423 FinTech users. Data were analyzed utilizing structural equation modeling (SEM) based on AMOS 26.0 software package. The findings revealed that UA has a moderating effect on the relationship between FC and users’ intentions. Also, PI has a significant impact on PE and EE. While PE, SI, and FC are factors that enhance behavioral intentions. In return, it builds users’ e-Loyalty toward FinTech services and is deemed a new normal behavior. This study may help FinTech service providers and policymakers better understand the, currently relatively low, usage rate of FinTech, and how it contributes to the development of strategies that boost the acceptance and e-Loyalty of FinTech by Jordanian users after the COVID-19 era, where FinTech is still considered an innovation.

Purpose: 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.Design/methodology/approach: 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.Findings: 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.Practical implications: 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.Originality/value: 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.

Purpose: This article aims to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) model to understand the factors affecting the usage behavior of Blockchain from accountants' and auditors’ perspectives and its impact on their performance.Design/methodology/approach: A quantitative research approach employing a web-based questionnaire was applied, and the empirical data were gathered from 329 potential and current users of Blockchain in the accounting and auditing profession in Jordan. The analytical model was based on structural equation modeling (SEM) using AMOS 25.0.Findings: The experimental findings of the structural path confirmed that performance expectancy (PE), social influence (SI), Blockchain transparency (BT) and Blockchain efficiency (BE) were significantly affecting individuals’ behavioral intention (BI) toward the use of Blockchain-based systems and helped to explain (0.67) of its variance. Also, BE has a positive significant impact on PE. Whereas, in contrast to what is anticipated, the influence of effort expectancy (EE) on BI was not supported. Additionally, users’ intentions were found to affect the actual usage (AU) behavior and helped to explain (0.69) of its variance. The outcome variables proposed in this study: knowledge acquisition (KACQ) and user satisfaction (USAT) were significantly influenced by the AU of Blockchain technology.Practical implications: This study outlines practical implications for government, policymakers, business leaders and Blockchain service providers aiming to exploit the advantages of Blockchain technology (BCT) in the accounting and auditing context.Originality/value: To the best of the authors’ knowledge, this article is one of the few studies that offer an evidence-based perspective to the discussions on the effect of disruptive and automated information and communication technologies (ICTs), on the accounting and auditing profession. It applies an innovative approach to analysis through the integration of UTAUT, contextual factors: BT and BE, besides two outcome factors: KACQ and USAT within its theoretical model. This study extends and complements the academic literature on information technology/information systems acceptance and use by providing novel insights into accountants' and auditors’ views.

The Metaverse technology (MVTECH) is an immersive virtual sphere where people interact with each other via avatars. The MVTECH promised to provide a number of potentials for various sectors including higher education. Despite the fact that MVTECH promotes virtual social interaction between people (e.g., university students), there is a lack of knowledge on what affects users’ perceptions regarding its social sustainability in HEIs, specifically in developing nations. Therefore, this research paper aims to determine the variables that affect the learners’ perceptions toward social sustainability (SS) of MVTECH in higher educational institutions (HEIs) in Jordan. A study model was formulated by integrating the core factors of the “unified theory of acceptance and use of technology” (UTAUT) (“performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC”) with “perceived curiosity” (PC) and “extraversion” (EXT) factors. Both PC and EXT were included as context-related variables that may possibly contribute to enhancing the applicability of UTAUT to a wide range of information technologies and settings. Data were collected from 422 students enrolled in Jordanian universities based on an online survey. The analysis of the “structural equation modeling” (SEM) found that students’ perceptions toward Metaverse were significantly influenced by PE, FC, and EXT. Furthermore, the PC construct significantly affected the EE construct. However, EE and SI were revealed to have no significant impact on SS. Drawing from these results, the study makes a number of theoretical advances and clarifies a number of practical implications for those involved in the development, design, and decision-making processes that support the use of the Metaverse in HEIs.

The present study explored the determinants influencing students’ intentions towards utilizing digital learning technologies (DLTs). It proposes a holistic view model for students’ utilization of digital learning technologies by integrating social support theory and the “Technology Acceptance Model” (TAM). Data were gathered from 262 students of the University of Ha’il through utilizing a questionnaire. Two steps in SEM were applied for data analysis: CFA was employed to develop the model measurement, and SEM was conducted to analyze the relationships between constructs. The results revealed that “Educational Support” (EDS) significantly affected students’ “behavior intention” (BI) to utilize digital learning technologies through perceived usefulness (PU) (EDS→PU: β = 0.338, p < 0.05). Furthermore, “Emotional support” (EMS) significantly affected behavioral intention through both “perceived ease of use” (PEU) and PU (EMS→PEU: β = 0.635, p < 0.05; EMS→PU: β = 0.310, p < 0.05). Surprisingly, students’ “perceived ease of use” (PEU) did not affect digital learning technologies’ “perceived usefulness” (PU) (PEU→PU: β = 0.195, p > 0.05). The present study contributes to a refined understanding of how educational and emotional support influence students’ receptivity towards and engagement with learning technologies. Thus, institutions and universities should enhance their students’ educational and emotional support to facilitate the successful utilization of digital learning technologies. Furthermore, the study revealed that PU and PEU affected students’ intentions to utilize DLTs. Thus, PU and PEU can enhance the utilization of digital learning technologies. This study provides practical implications that educational institutions and universities could apply to achieve successful usage of these digital learning technologies.

Purpose: In this research, we seek to understand the effects of artificial intelligence (AI) and knowledge management (KM) processes in enhancing proactive green innovation (PGI) within oil and gas organizations. It also aims to investigate the moderator role of trust and sustainability in these relationships.Design/methodology/approach: This paper employs a quantitative analysis. Surveys have been gathered from the middle-line managers of twenty-four oil and gas government organizations to evaluate the perceptions of the managers towards AI, KM processes, trust, sustainability measures and proactive measures toward green innovation. Analytical and statistical tools that were employed in this study, including structural equation modeling with SmartPLSv3.9, have been used to analyze the data and to examine the measurement and structural models of this study.Findings: The study results reveal a significant and positive impact of AI utilization, KM processes and PGI within oil and gas organizations. Furthermore, trust and sustainability turn out to be viable moderators affecting, and influencing the strength and direction of AI, KM and PGI relationships. In particular, higher levels of trust and more substantial sustainability commitments enhance the positive impact of AI and KM on green innovation outcomes.Practical implications: Understanding the impact of AI, KM, trust and sustainability offers valuable insights for organizational leaders and policymakers seeking to promote proactive green innovation within the oil and gas industry. Thus, organizations can increase the efficiency of sustainable product development, process improvement and environmental management by using robust AI technologies and effective KM systems. Furthermore, fostering trust among stakeholders and embedding sustainability principles into organizational culture can amplify the effectiveness of AI and KM initiatives in driving green innovation outcomes.Originality/value: This study extends the current knowledge by assessing the effect of AI and KM on proactive green innovation while accounting for trust and sustainability as moderators. Utilizing quantitative methods offers a nuanced understanding of the complex interactions between these variables, thereby advancing theoretical knowledge in the fields of innovation management, sustainability and organizational behavior. Additionally, the identification of specific mechanisms and contextual factors enriches practical insights for organizational practitioners striving for a practical understanding of the dynamics of the complexities of sustainable innovation in an AI-driven era.