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In view of the promising growth of FinTech in the Arab region, specifically in Egypt, this study identifies the significant factors likely to influence consumers’ acceptance intention toward e-payment products and services (mobile wallets, virtual-cards, mobile/online banking etc.).

Quantitative deductive research was used to investigate the extension of the unified theory of acceptance and use of technology (UTAUT) on consumers' e-payment acceptance intentions. Questionnaires were electronically administered through convenience sampling. Three hundred and ninety-nine questionnaires were analyzed through multiple regression to test the proposed hypotheses.

Performance expectance, facilitating condition, effort expectancy and social influence impact consumers' e-payment acceptance intentions. These factors contribute to the growing number of individuals using e-payments to the extent that e-payment eventually becomes a preferred medium for economic transactions. Hedonic motivation, price value and habit are insignificant in encouraging consumers' e-payment acceptance.

The study benefits to governments, policymakers, banking institutions, businesses involved in online transactions and software developers. They can utilize the findings to develop strategies aimed at increasing e-payment usage and overcoming cultural-resistance to changing traditional financial transaction methods. These methods align with the government’s goal of achieving a digital society.

This study presents information on the current state of e-payment acceptance. Its potential contribution lies in identifying the factors that influence the intention to e-payment among Arab consumers, thereby highlighting important considerations for the adoption of e-payment. Furthermore, this study supports UTAUT over UTAUT2 in the FinTech context. It suggests that individuals exhibit similar behavior and inspiration when using e-payment technology as they do when using technology in an organizational context.

Today the research area on technology acceptance is mainly dependent on the theory of technology acceptance model (TAM). The TAM was used in this study primarily for the purpose of providing a basis for determining the impact of various external variables on the adoption of edtech platforms. The TAM is a theory of information systems that suggests steps for learners to take as they adopt and use new technologies. The primary TAM variables for adoption of edtech platforms are evaluated in this study: perceived usefulness (PU) and perceived ease of use (PEOU) by using the factors – perceived enjoyment (PE), information quality, electronic-word of mouth (e-WOM), perceived compatibility, computer self-efficacy and objective usability. By analyzing and defining the relationship between the external variables with respect to the adoption of edtech platform among students, we hope to contextualize the TAM model. The end result provides a clearer understanding of TAM and its growth as a useful model for technology adoption studies and for clarifying the relationship between the uptake of edtech platforms and technological acceptability. The study employed a qualitative methodology and selected publications and research papers about the adoption of technology. These were then carefully assessed, analyzed and scrutinized for the terms of how students adopted edtech platforms. It was proposed that the adoption of an edtech platform may result from proper training in technology usage and its application to real-world scenarios.

The commonly used e-procurement systems still show unsatisfactory implementation outcomes because many organisations are still unable to effectively interpret the initial adoption decision. The e-procurement systems are generally developed at organisational level, but their usage is at individual level, by the employees particularly. This paper examined technology acceptance model’s (TAM) key antecedents, involving e-procurement systems usage by employees in their daily activities. This study aims to examine the impact of factors affecting e-procurement acceptance among users through the mediating role of users’ attitude. The commonly used e-procurement systems still show.

TAM was applied and expanded in this study, in exploring the factors impacting the employees’ e-procurement acceptance. This study used quantitative method, and questionnaires were distributed to 200 users in Jordanian public shareholding firms. The collected data were quantitatively analysed using PLS modelling.

Significant TAM relationships involving e-procurement were affirmed. The expanded TAM in the scrutiny of antecedents showed that content, processing and usability affected perceived usefulness, while perceived convenience did not affect the usefulness factor. Furthermore, it was noticed that perceived ease of use was affected by usability and training, while perceived connectedness was not affected by usability and training.

The results demonstrated the necessity of e-procurement training. Furthermore, at the start of the implementation stage, effective design on system navigation and system usability, and consistent support, could increase use effectiveness and acceptance. Also, expedient information and buyer–supplier product flows should be made available.

Most organizations invest a lot of time and money in installing e-procurement systems to deliver their goods at the right time and at the right price. However, many of these e-procurement systems have failed due to low acceptance among users. Thus, to the best of the authors’ knowledge, this is the first study that used TAM and theory of planned behaviour in examining the effects of perceived convenience, perceived connectedness, content, training, processing and usability factors, in Jordanian firms. Lastly, the focus of this study was on the individual employee’s acceptance, rather than on the organisational-level adoption, as the unit of analysis, to provide insight on how organisations can achieve maximally from e-procurement investments and from other comparable technologies of e-supply chain management.

This study identifies key facets leading to consumers' Internet of Things (IoT) adoption intention.

Applying four technology acceptance theories (theory of planned behavior, technology acceptance model, pleasure-arousal-dominance theory and technology readiness index), the author uses deductive quantitative research to develop a model, explaining IoT adoption intentions. Administrated questionnaires are distributed in Egypt among generation-Z and millennials in malls. A total of 400 questionnaires are used for hypotheses testing, applying structural equation modeling (SEM) path coefficient analysis.

Results of this study show that attitude, dominance, perceived usefulness, innovativeness and insecurity impact consumers' IoT adoption intentions; subjective norms, perceived behavior control, pleasure, arousal, perceived ease, optimism and discomfort hold insignificant impact on consumers' IoT adoption intentions.

Exploring IoT facets and how these facets impact consumers' adoption intentions, this study helps grasp technology acceptance in theory and practice, guiding scholar and practitioners (e.g. IoT developers, retailers, marketers and other field experts) to consider consumers' mindset when developing, improving and marketing IoT.

The contribution stems from the incorporation of various frameworks used to explain technology acceptance. By studying several theories jointly, the research extracts and identifies a significant set of facets (technical and psychological) to build a comprehensive theory of IoT acceptance, showing consumers' IoT adoption is not entirely similar to adoption of other past innovations. This understanding allows marketers to focus on content that needs to be promoted to boost consumers' IoT purchase plans. Future researchers could replicate the results to IoT categories (e.g. home appliances, cars, healthcare, education, sportswear, etc.) to improve external validity of the findings, among other future research opportunities.

The existing technology acceptance models have not yet investigated functional and motivational factors impacting trust in and use of conversational artificial intelligence (AI) by integrating the feedback and sequential updating mechanisms. This study challenged the existing models and constructed an integrated longitudinal model. Using a territory-wide two-wave survey of a representative sample, this new model examined the effects of hedonic motivation, social motivation, perceived ease of use, and perceived usefulness on continued trust, intended use, and actual use of conversational AI.

An autoregressive cross-lagged model was adopted to test the structural associations of the seven repeatedly measured constructs.

The results revealed that trust in conversational AI positively affected continued actual use, hedonic motivation increased continued intended use, and social motivation and perceived ease of use enhanced continued trust in conversational AI. While the original technology acceptance model was unable to explain the continued acceptance of conversational AI, the findings showed positive feedback effects of actual use on continued intended use. Except for trust, the sequential updating effects of all the measured factors were significant.

This study intended to contribute to the technology acceptance and human–AI interaction paradigms by developing a longitudinal model of continued acceptance of conversational AI. This new model adds to the literature by considering the feedback and sequential updating mechanisms in understanding continued conversational AI acceptance.

E-procurement has the advantage of improving the overall performance of construction project delivery. The purose of this study is to uncover the factors influencing e-procurement acceptance in the public sector of Ghana’s construction industry (GCI). Using an extended unified theory of acceptance and use of technology (UTAUT 2), variables that promote the acceptance of e-procurement in GCI were explored.

Data was collected using a mixed method strategy. In the first stage, a semi-structured interview was used to collect, assess and optimize the UTAUT2 model. Thematic analysis was used on the qualitative data, leading to modification of the proposed UTAUT2 model. The study subsequently used a questionnaire survey using the extended UTAUT2 model. Survey data was analyzed using structural equation modelling (SEM), leading to the identification and validation of factors that facilitate e-procurement acceptance in Ghanaian construction as well as the impact of these factors.

The findings of the study reveal that five independent constructs of the proposed UTAUT2 model significantly affects the behavioural intention of practitioners to accept and use e-procurement in the construction industry in Ghana.

The study will be of utility to government agencies, contracting organizations and other construction stakeholders in developing policy and programmes to support e-procurement acceptance within the sector.

This is a new extended UTAUT2 model that is applicable to technology acceptance within the public sector in sub-Saharan Africa.

Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.

Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.

The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.

Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.

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.

As a little research has been conducted to understand the factors influencing users’ intentions to adopt blockchain-based telemedicine (BBT), it is important to investigate BBT acceptance as incorporation of blockchain technology can solve telemedicine-related issues. Accordingly, this study aims to investigate the factors influencing behavioral intentions (BI) to adopt BBT.

An integrated model comprising the constructs taken from technology–organization–environment framework, technology acceptance model, unified theory of acceptance and use of technology and theory of planned behavior based on their relevance to the context and the objectives of the study has been used for this research. A quantitative approach has been used to test the hypotheses, for which the data was collected from 324 respondents through a self-administered questionnaire. Partial least squares structural equation modeling has been used to test the hypotheses.

The results of the study show that relative advantage, perceived usefulness, trust and perceived ease of use have a significant impact on BI to adopt BBT, whereas regulatory support, subjective norms and facilitating conditions do not have any significant impact on the same.

As the concept of BCT in Pakistan is at its nascent stage and literature regarding this technology’s adoption is also limited, researchers and scholars can apply it to several other fields in Pakistan. For example, this study can be extended to explore the factors influencing blockchain adoption in areas such as education, logistics, transportation, finances and management. This research only considers the direct effects of constructs on BI to adopt BBT and does not consider any mediation and moderations constructs. Future researchers can also study the influence of mediation and moderation constructs on BI to adopt BCT.

Although studies on the acceptance of telemedicine exist, there is a gap concerning the acceptance of BBT, which the current study helps to bridge. From a practical standpoint, the current study makes a highly valuable contribution toward understanding acceptance factors for BBT projects, leading to help policymakers devise policies to promote telemedicine.

By extending the service robot acceptance model (sRAM), this study aims to explore and enhance the acceptance of chatbots. The study considered functional, relational, social, user and gratification elements in determining the acceptance of chatbots.

By using the purposive sampling technique, data of 321 service customers, gathered from millennials through a questionnaire and subsequent PLS-SEM modeling, was applied for hypotheses testing.

Findings revealed that the functional elements, perceived usefulness and perceived ease of use affect acceptance of chatbots. However, in social elements, only perceived social interactivity affects the acceptance of chatbots. Moreover, both user and gratification elements (hedonic motivation and symbolic motivation) significantly influence the acceptance of chatbots. Lastly, trust is the only contributing factor for the acceptance of chatbots in the relational elements.

The study extends the literature related to chatbots and offers several guidelines to the service industry to effectively employ chatbots.

This is one of the first studies that used newly developed sRAM in determining chatbot acceptance. Moreover, the study extended the sRAM by adding user and gratification elements and privacy concerns as originally sRAM model was limited to functional, relational and social elements.