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This study aims to ascertain the intentions of risk managers to use artificial intelligence in performing their tasks by examining the factors affecting their motivation.

The study employs an integrated theoretical framework that merges the third version of the technology acceptance model 3 (TAM3) and the unified theory of acceptance and use of technology (UTAUT) based on the application of the structural equation model with partial least squares structural equation modeling (PLS-SEM) estimation on data gathered through a Likert-based questionnaire disseminated among Italian risk managers. The survey reached 782 people working as risk professionals, but only 208 provided full responses. The final response rate was 26.59%.

The findings show that social influence, perception of external control and risk perception are the main predictors of risk professionals' intention to use artificial intelligence. Moreover, performance expectancy (PE) and effort expectancy (EE) of risk professionals in relation to technology implementation and use also appear to be reasonably reliable predictors.

Thus, the study offers a precious contribution to the debate on the impact of automation and disruptive technologies in the risk management domain. It complements extant studies by tapping into cultural issues surrounding risk management and focuses on the mostly overlooked dimension of individuals.

Yet, thanks to its quite novel theoretical approach; it also extends the field of studies on artificial intelligence acceptance by offering fresh insights into the perceptions of risk professionals and valuable practical and policymaking implications.

This study aims to propose a research model integrating technology acceptance model 3 (TAM3) constructs and human aspects of humanoid service robots (HSRs), measured by the Godspeed questionnaire series and tested across two hotel properties in Japan and the USA.

Potential participants were approached randomly by email invitation. A final sample size of 395 across two hotels, one in Japan and the other in the USA, was obtained, and the data were analysed using structural equation modelling.

The results confirm that perceived usefulness, driven by subjective norms and output quality, and perceived ease of use, driven by perceived enjoyment and absence of anxiety, are the immediate direct determinants of users’ re-patronage intentions for HSRs. Results also showed that users prefer anthropomorphism, perceived intelligence and the safety of an HSR for reusing it.

The findings have practical implications for the hospitality industry, suggesting multiple attributes of an HSRs that managers need to consider before deploying them in their properties.

The current study proposes an integrated model determining factors that affect the re-patronage of HSRs in hotels.

This paper aims to give broad insights into what components can significantly influence the adoption of Metaverse from the perspective of internal auditors and their firms in Indonesia.

This research used primary data from questionnaires. Relying on the empirical view of 202 internal auditors in Indonesia, this research’s framework is executed using structural equation model. Company’s intention in adopting the Metaverse technology intervenes in the influence of perception of external control and usefulness on the internal auditor’s intention to adopt that technology.

The perception of external control and perceived usefulness of Metaverse significantly influenced the adoption intention of Metaverse by internal auditors and their firms in Indonesia. This paper is helpful for practitioners who would like to know what factors are needed to make the internal auditors in Indonesia able to adopt Metaverse.

Results might be varied from country to country as each country has different technology development. Therefore, upcoming research can compare similar studies in another country. This paper can contribute to further empirical development for the theory of acceptance model of the third version. Many researchers use the theory to study advanced technology adoption intention.

The paper is also essential for future research and could enhance companies' knowledge about staying updated in the market with the advanced technology that keeps developing.

This paper contributes to an integrated view of the intention of internal auditors and firms in Indonesia to adopt Metaverse. To the best of the authors’ knowledge, this topic is relatively new in Indonesia.

The purpose of this study is to examine the effect of extrinsic aspects of the technology acceptance model, namely, information quality, functionality, accessibility, user interface design, system quality, functionality, facilitating conditions and computer playfulness as well as intrinsic aspects, namely, perceived self-efficacy, enjoyment and learning goals. orientation on perceived usefulness and perceived ease of use in the context of the learning management system (LMS) as a system to support employee learning and development. This study also analyzes the effect of perceived ease of use on perceived usefulness and analyzes the effect of these two variables on the intention to adopt a LMS. This study included 3,205 respondents who are employees of banking companies in Indonesia and who used the LMS for their learning and self-development needs during the COVID-19 pandemic.

This research is a quantitative study that uses online surveys to collect data and partial least squares statistical tools to analyze survey data.

The results showed that accessibility alone had no effect on perceived usefulness and perceived ease of use, while enjoyment had no effect on the intention to use LMS and perceived ease of use and functionality had no effect on the intention to use LMS.

This research focuses on the concept of technology acceptance with extrinsic and intrinsic aspects. This research context involves employees working in the banking sector with the adoption of the LMS.

LMS in banking companies can be optimized by providing online training and reducing the operational costs of employee training. By using LMS, companies can offer online courses to employees and track progress in distance learning, become a learning choice and information dissemination during the pandemic and also support future business continuity.

This study focuses on testing the technology adoption model on LMSs in the banking sector by adding extrinsic aspects, namely, system quality, facilitating conditioning, computer playfulness and user interface design, and combining intrinsic aspects, namely, perceived self-efficacy, enjoyment and learning goal orientation.

This paper aims to investigate the influence of health beliefs and trust by senior adults as associated with the perceived ease of use and perceived usefulness, for the acceptance of smart technology with a focus on smartwatch technology.

Structural equation modeling is used to conceptualize the model using survey data collected from 243 randomly selected senior adults 60+ years of age.

This paper presents that perceived usefulness, perceived ease of use, trust and health belief are direct and indirect predictors of senior adults’ technology acceptance and intention to use smartwatch technology.

The study reveals the moderator effect of social influence on relation between perceived usefulness, perceived ease of use and intention to use. The authors highlight the effect of health belief and trust on perceived usefulness and perceived ease of use and the role of intention to use smartwatch technology.

The authors contribute bridging developers of health technologists and senior adults as end-user perspectives. For marketing of health-care technology products, specifically smartwatch, to seniors, a focus on health beliefs and trust is essential to build, maintain and improve perceived usefulness and perceived ease of use.

The present study contributes empirical evidence to the literature on factors affecting the acceptance of the smartwatch technology by senior adults.

This study aims to scrutinize existing end-user comprehension regarding e-wallet technology through an examination of apparent usefulness, ease of use and levels of trust, and how these factors may influence a consumer’s attitudes toward the adoption of this new payment method.

The quota sampling method was used, and residents over the age of 22 years were targeted in online and offline questionnaires, and partial least squares-structural equation modeling was used to analyze the data.

This study indicates that existing consumer mindsets and intentions to adopt new technology, such as the e-wallet, are greatly influenced by their perception of the practicality of the product, its ease of use and their levels of trust in the technology to protect their online safety, privacy and economic affairs. Contrastingly, those participants who were offered deferred reimbursements and those given no information were demonstrably less likely to adopt the new service.

The study sample was from a developing nation – Saudi Arabia. Similar cohorts from developing and developed countries could provide a unique cross-nation comparison.

This study stresses the importance of thoroughly explaining and demonstrating an innovative technology to customers while simultaneously promoting the product. Consumers can be encouraged to use and evaluate the new technology by providing inducements, such as effective reimbursement policies.

This paper contributes to literature by critically reflecting on the question: What are the factors influencing customer intentions to adopt the e-wallet, and how do the guarantee of reimbursement and the time frame following unauthorized use influence consumer adoption intentions when deciding to use the new payment technology?

Food SMEs is the backbone of local and world economy. Even while food SMEs are aware of the potential advantages of implementing supply chain analytics (SCA), only a small number of companies use data-based decision-making. This is because of technophobia. In light of this, the purpose of this study is to investigate the factors that have an impact on SCA adoption which in turn influence the sustainable performance of firms.

The data were collected from 221 managers working in food-related SMEs in China by using a questionnaire-based survey. The framework of this study was validated using a rigorous statistical procedure using the technique, namely, partial least squares structural equation modelling.

The findings of this study suggest that all modified UTAUT components (i.e. performance expectancy, effort expectancy, social influence, facilitating conditions and technophobia) significantly influence SCA adoption. Moreover, the existing study highlights and confirms the significance of adopting SCA to improve sustainable performance.

This research is novel, as it extends and investigates the theoretical framework based on UTAUT theory in SCA context and its impact on sustainable organizational performance. In addition, the factor of technophobia is tested in SCA context. This study has several contributory managerial implications for food SMEs.

This study aims to apply the service robot acceptance model (sRAM) to examine how attitude toward human–robot interaction (HRI) and engagement influence consumer acceptance of service robots in a frontline setting.

Data was collected from 255 visitors who interacted with a robotic tour guide at a city museum. The data was analyzed using smart PLS 4.0.

The findings show the positive effects of subjective norms, appearance, perceived trust and positive emotion on both attitude toward HRI and engagement. In addition, social capability impacted attitude toward HRI, whereas perceived usefulness affected engagement.

To deliver engaging museum experiences that bring about positive word-of-mouth and intention to visit, managers need to incorporate the sRAM dimensions in the design and deployment of service robots.

This research uses field data to empirically validate the sRAM in the context of service robot acceptance. It introduces engagement as a novel mediating variable, enriching current understanding of human-like qualities in HRIs.

This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail.

The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM).

The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions.

To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR.

This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI.

Generative pretrained transformers (GPTs), soaring to one million users at lightning speed, outpaced social media giants (15 times faster) (Buchholz, 2023). Despite this, scant research explored GPT’s impact on the digital entrepreneurial intentions (EIs) of students and tech-savvy generations. This study aims to pioneer a fusion of the technology acceptance model (TAM) and the theory of planned behavior (TPB), bridging the gap in research.

In this bold quantitative quest, business administration students became fearless participants, engaging in a survey of profound significance. Guided by the mighty powers of G*Power and Stata’s structural equation modeling builder, the intricate relationships within a robust sample of (n = 400) were unraveled.

The mediating power of GPT usefulness and GPT ease of use part of the TAM emerges, paving the way for a future brimming with digital entrepreneurship (DE) boundless possibilities. Predictably, the study found that TPB constructs also affect the EI of students.

This groundbreaking study brings together the powerful combination of TAM and TPB, while pioneering the exploration of GPT models’ mediating role. Its findings offer invaluable contributions to the field of DE and policymakers.