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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.

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.

Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC.

To examine the behavioural intention of employees in the retail SC, the research uses three theories – the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis.

This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector.

This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only.

This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC.

The aim of this paper is to research the acceptance mechanism of building information modeling (BIM) technology and to explore the differences among Architecture/Engineering/Construction (A/E/C) professionals with different individual characteristics. The proposed acceptance mechanism of BIM technology is intended to be used by industry stakeholders to propose decisions and measures, and improve the degree of BIM adoption.

Traditional hypothesis testing is adopted by the current study to empirically research the specific mechanism of A/E/C professionals accepting BIM technologies. In the one phase, a conceptual model based on technology acceptance model (TAM) and technology organization environment (TOE) theory was established and a large-scale questionnaire survey was conducted. In the other phase, structural equation modeling (SEM) was used to analyze acquired sample data, so as to empirically test the validity of the proposed linkage.

The results show first that perceived ease of use has no significant influence on perceived usefulness, and perceived usefulness has no significant effect on behavior intention as well. Second, BIM technical features and government BIM policies have positive effects on perceived usefulness, BIM technical features and organization supports have positive effects on perceived ease of use. Third, the BIM acceptance mechanism of A/E/C professionals is diverse from respondents with different characteristics, e.g. regions and working time.

The authors highlight the large sample size, as well as the nationwide context, of the questionnaire survey. Meanwhile, acceptance differences among A/E/C professionals with different demographic characteristics have been clarified using profound data and t-test. The findings of this study enrich the research on the acceptance mechanism of BIM technology, and contribute to relevant stakeholders taking targeted measures to promote the effective application of BIM technology nationwide.

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.

The evolution of e-health technologies presents promising alternatives for health-care excellence. Despite the benefits arising from mobile e-health (m-health) and wearables technologies, the literature stands many contradictories signs regarding how users accept and engage in using these technologies. This study aims to synthesize the estimations about m-health user acceptance technologies.

A meta-analytic structural equation modeling was carried out using the 778 relationships estimated by 100 previous research. The estimations follow the relations and constructs proposed in the UTAUT2 technological acceptance model.

The results indicate the performance expectancy, effort expectancy, social influence and habit constructs are most important for predicting the behavioral intention of use of m-health technologies. The Latin American users of e-health technologies are still underestimated in the literature.

The study presents a guide to understanding the acceptance process of m-health technologies and delivers a general orientation for developing new m-health devices considering their acceptance by users.

The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.

A structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.

The findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.

The paper will help decision-makers to adopt and use m-learning in higher educational institutions.

This paper is the first to explore the readiness and acceptance of m-learning in higher education in India.

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.

This paper aims to create a conceptual model that connects learning organizations, service innovation and technology acceptance.

The importance of the interaction of variables benefiting both individuals and organizations has been comprehensively explained by combining two well-known theories – learning organizational theory and service innovation theory – with the technology acceptance model. In the first part of the study, conceptual model has been constructed and then applied to the hospitality industry of which results have been presented in the second part of this paper.

It is hypothesized that learning organization, service innovation and technology acceptance have significant relationships. It is also suggested that the learning organization plays an intermediary role in the relationship between technology acceptance and service innovation. Empirical results in this regard have been presented in the second part of the paper.

The relations have been established and tested in the hospitality industry in Antalya. However, the model can be applied and established relations tested in other industries.

This research contributes to our knowledge of the intricate linkages that exist between learning organizations, technology acceptance and service innovation. Originality of the paper is related to the novel multilayered model illustrating three-way interactions between the three dimensions of learning organization, technology acceptance and service innovation.

This study aims to examine hotel guests’ acceptance of technology agency – the extent to which they would let artificial intelligence (AI)-based systems make decisions for them when staying in hotels. The examination was conducted through the prism of several antecedents of acceptance of technology agency, including perceived ethics, benefits, risks and convenience orientation.

A thorough literature review provided the foundation of the structural model, which was tested using confirmatory factor analysis, followed by structural equation modeling. Data were collected from 400 US hotel guests.

The most important determinant of acceptance of technology agency was perceived ethics, followed by benefits. Risks of using AI-based systems to make decisions for consumers had a negative impact on acceptance of technology agency. In addition, perceived loss of competence and unpredictability had relatively strong impacts on risks.

The results provide a conceptual foundation for research on systems that make decisions for consumers. As AI is increasingly incorporated in the business models of hotel companies to make decisions, ensuring that the decisions are perceived as ethical and beneficial for consumers is critical to increase the utilization of such systems.

Most research on AI in hospitality is either conceptual or focuses on consumers’ intentions to stay in hotels that may be equipped with AI technologies. Occupying a unique position within the literature, this study discusses the first time AI-based systems that make decisions for consumers. The value of this study stems from the examination of the main concept of technology agency, which was never examined in hospitality.