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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.

In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.

This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.

Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.

This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

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.

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.

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.

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.

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.

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.

Problems such as information asymmetry and a lack of trust among construction practitioners damage the quality and progress of construction projects. The decentralization, transparency, traceability and temper-proof nature of blockchain technology (BCT) can provide solutions and facilitate multiparty cooperation. However, BCT acceptance in the construction industry is relatively low, and there are few pilot projects adopting BCT. Most relevant literature focuses on BCT acceptance at the industry and organizational levels, but the impact of non-managerial practitioners executing BCT or the traditional approach in day-to-day work tends to be disregarded. This study aims to establish a theoretical model of BCT acceptance, identify key influencing factors and paths of behavioral intention to adopt BCT and promote strategies to enhance BCT adoption.

A new BCT acceptance model for construction practitioners was proposed. A survey was performed with 203 construction practitioners in Shenzhen, China and post-survey interviews were conducted with four BCT experts for validation. Covariance-based structural equation modeling was used to examine the influence paths and moderating effect analysis was performed to check practitioners’ differential perceptions.

Performance expectancy, social influence, facilitating conditions and perceived behavioral control significantly and positively influence behavioral intention to accept BCT, while impacts from effort performance and risk are negative. Overcoming obstacles related to the effort required for BCT adoption and effective risk management will be essential to unlocking BCT’s transformative potential. Then, the moderating effects of respondents’ gender, degree and BCT knowledge as well as the project type involved were analyzed. Continued adoption of BCT in the construction industry has the potential to revolutionize project management, transparency and trust among stakeholders.

The findings of this research can help practitioners and government agencies understand crucial influencing factors and pathways of BCT acceptance. Targeted measures, such as increasing practitioners’ benefits and sense of BCT usefulness, conducting pilot projects and increasing publicity, were proposed for project leadership teams to enhance BCT adoption. This may lead to increased efficiency, reduced disputes and more streamlined and secure construction processes, ultimately enhancing the industry’s overall performance.

Few studies have explored BCT acceptance from the perspective of non-managerial construction practitioners. The BCT acceptance model proposed in this study is a novel adaptation of previous technology acceptance models, with new factors (risk and perceived behavioral control) and moderating variables (degree, BCT knowledge and project type) added for better understanding of non-managerial practitioners’ perceptions and differences.

Sharia-compliant financial technologies (Islamic fintech) are becoming increasingly popular among Muslims and non-Muslims. As the Islamic fintech landscape continues to grow and transform, it is crucial to understand the factors that influence the acceptance or adoption of Islamic fintech services from the past literature. Therefore, this paper aims to conduct a systematic literature review (SLR) to investigate and compile factors that could influence a user to adopt Islamic fintech.

The current study adopted the systematic literature review approach using Preferred Reporting Items for Systematic Reviews and Meta-Analyses technique to examine research on Islamic fintech adoption. A set of inclusion criteria was applied to filter out irrelevant documents and ensure the selection of only the most relevant ones. The criteria were limited to quantitative journals published in English between 2012 and 2022, as identified in Scopus outlets.

Despite the existence of various theoretical frameworks, the technology acceptance model and Unified Theory of Acceptance and Use of Technology 2 frameworks have gained prominence as the most frequently applied frameworks in examining Islamic fintech adoption. In addition, trust is the most important self-developed construct for the adoption of Islamic Fintech.

The current study does not segregate the intention, actual usage and retention, as the author is interested in understanding the overall adoption of Islamic fintech services. To obtain more specific analysis results, future research could potentially separate the three types of adoption exposure, i.e., consumer acceptance, intention and retention. Next, future studies can also expand their analysis and gain a better understanding of the research topic by exploring alternative data sources such as Web of Science, ERA or JSTOR.

To the best of the author’s knowledge, this study makes a significant contribution to the literature by providing the first systematic literature review of factors influencing fintech adoption from an Islamic perspective.

This chapter addresses research results regarding the past and current messages disseminated about Carbon Capture, Usage and Storage (CCUS) in Romania, as well as how new messages about CCUS are perceived by stakeholders. The research was conducted within the ACT ALIGN CCUS Project, funded by the European Commission to accelerate the demonstration and implementation of CCUS by addressing specific R&D gaps across the CCUS chain (act-ccs.eu/align). Media analysis and website analysis were conducted in Romania to identify the current and past core messages about CCUS used in society, while focus group research was conducted to test new core messages among citizens in Romania. The media analysis results show that media coverage and representations of CCUS for the time periods analysed were low in Romania, while the overall tone of the articles identified was relatively positive, as expressed by the division of arguments in favour of versus against CCUS. The CCUS topic is scarce on stakeholder websites in Romania. The results of the focus group study show that participants in the industrial area considered both environmental and economic benefits important, whereas participants in the non-industrial area considered environmental benefits more important. Most of the participants in the two focus groups expressed concerns about the safety of storage and transport, expressing the need to prevent further climate change. The CCUS messages testing shows the need for clarity, accessibility and appeal to citizens’ personal interests. This research was relevant for investigating the public debate on CCUS technologies in its early stages of development.

This paper aims to identify the relevant contributing constructs of readiness for the implementation of intelligent contracts (iContracts) in the construction industry. This study investigates the relationship between the personality dimensions of technology readiness index (TRI) and the system specific factors of technology acceptance model (TAM) within the context of iContracts.

Drawing insights from the extant literature and the author's previous qualitative investigations into iContract readiness constructs, a quantitative approach is used to operationalise the constructs by offering relevant statements to be measured and validated through a multiple-item scale against the users intent to accept the future iContract technology.

This study confirms and validates the relationship of the proposed iContract readiness index (iCRI) statements against the established TAM factors by offering 18 new constructs influencing technology readiness of the iContract technology. This study proves 9 of the 12 hypotheses highlighting key factors to be addressed for the successful development of the iContract technology.

This paper contributes to the body of knowledge by proposing a novel iCRI that informs an iContract technology readiness acceptance model (iCTRAM) for a trending technology. The iCTRAM can guide developers in producing an appropriate iContract solution and assess the readiness of users and organisations for the successful adoption of the iContract concept.

This study offers a unique theoretical framework, in an embryonic field, for predicting the success of iContract implementation within construction organisations. This study combines the established studies of TRI and TAM in producing a predictive iContract readiness assessment tool.

The study investigates the consumer’s attitude to using artificial intelligence (AI) devices in hospitality service settings considering social influence, hedonic motivation, anthropomorphism, effort expectancy, performance expectancy and emotions.

This study employed a quantitative methodology to collect data from Bangladeshi consumers who utilized AI-enabled technologies in the hospitality sector. A total of 343 data were collected using a purposive sampling method. The SmartPLS 4.0 software was used to determine the constructs' internal consistency, reliability and validity. This study also applied the partial least squares structural equation modeling (PLS-SEM) to test the research model and hypotheses.

The finding shows that consumer attitude toward AI is influenced by social influence, hedonic motivation, anthropomorphism, performance and effort expectancy and emotions. Specifically, hedonic motivation, social influence and anthropomorphism affect performance and effort expectations, affecting consumer emotion. Moreover, emotions ultimately influenced the perceptions of hotel customers' willingness to use AI devices.

This study provides a practical understanding of issues when adopting more stringent AI-enabled devices in the hospitality sector. Managers, practitioners and decision-makers will get helpful information discussed in this article.

This study investigates the perceptions of guests' attitudes toward the use of AI devices in hospitality services. This study emphasizes the cultural context of the hospitality industry in Bangladesh, but its findings may be reflected in other areas and regions.