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This paper aims to examine the current technology acceptance model (TAM) in the field of mixed reality and digital twin (MRDT) and identify key factors affecting users' intentions to use MRDT. The factors are used as a set of key metrics for proposing a predictive model for virtual, augmented and mixed reality (MR) acceptance by users. This model is called the extended TAM for MRDT adoption in the architecture, engineering, construction and operations (AECO) industry.

An interpretivist philosophical lens was adopted to conduct an inductive systematic and bibliographical analysis of secondary data contained within published journal articles that focused upon MRDT acceptance modelling. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach to meta-analysis were adopted to ensure all key investigations were included in the final database set. Quantity indicators such as path coefficients, factor ranking, Cronbach’s alpha (a) and chi-square (b) test, coupled with content analysis, were used for examining the database constructed. The database included journal papers from 2010 to 2020.

The extant literature revealed that the most commonly used constructs of the MRDT–TAM included: subjective norm; social influence; perceived ease of use (PEOU); perceived security; perceived enjoyment; satisfaction; perceived usefulness (PU); attitude; and behavioural intention (BI). Using these identified constructs, the general extended TAM for MRDT in the AECO industry is developed. Other important factors such as “perceived immersion” could be added to the obtained model.

The decision to utilise a new technology is difficult and high risk in the construction project context, due to the complexity of MRDT technologies and dynamic construction environment. The outcome of the decision may affect employee performance, project productivity and on-site safety. The extended acceptance model offers a set of factors that assist managers or practitioners in making effective decisions for utilising any type of MRDT technology.

Several constraints are apparent due to the limited investigation of MRDT evaluation matrices and empirical studies. For example, the research only covers technologies which have been reported in the literature, relating to virtual reality (VR), augmented reality (AR), MR, DT and sensors, so newer technologies may not be included. Moreover, the review process could span a longer time period and thus embrace a fuller spectrum of technology development in these different areas.

The research provides a theoretical model for measuring and evaluating MRDT acceptance at the individual level in the AECO context and signposts future research related to MRDT adoption in the AECO industry, as well as providing managerial guidance for progressive AECO professionals who seek to expand their use of MRDT in the Fourth Industrial Revolution (4IR). A set of key factors affecting MRDT acceptance is identified which will help innovators to improve their technology to achieve a wider acceptance.

This study aims to develop a comprehensive adoption model that combines constructs from various theories and tests these theories against each other. The study combines a technology acceptance model, innovation diffusion theory and risk theory. It develops this model in a smart home applications context.

The study is based on an online survey consisting of 409 participants, and the data are analyzed using structural equation modeling.

Each theory provides unique insights into technology acceptance and numerous constructs are interrelated. Predictors from innovation diffusion and risk theory often display indirect effects through technology acceptance variables. The study identifies risk perception as a major inhibitor of use intention, mediated through perceived usefulness. Results reveal that the most important determinants of use intention are compatibility and usefulness of the application.

Studies which do not examine different theories together may not be able to detect the indirect effects of some predictors and could falsely conclude that these predictors do no matter. The findings emphasize the crucial role of compatibility, perceived usefulness and various risk facets associated with smart homes.

This study broadens the understanding about the necessity of combining acceptance and adoption drivers from several theories to better understand the usage of complex technological systems such as smart home applications.

This study aims to explore students' perceptions of a virtual reality simulation that enable nursing students to learn how to use a medical emergency crash cart.

The study was designed to explore how students' perceptions of ease of use and perceived usefulness from the technology acceptance model and the students' personal innovativeness in the domain of information technology explained their intentions to use the simulation. Six hypotheses were tested with a survey administered to 158 undergraduate nursing students at a midsized Southwestern university in the USA.

Data analysis based upon a structural equation modeling technique found support for all three research hypotheses based upon the technology acceptance model. Data analysis also found support for all three hypotheses drawn from the literature on personal innovativeness in the domain of information technology. Overall, the study's research model explained about 65 percent of the variance in intention to use the virtual reality simulation (R²=0.65).

This study suggests that future research should take into account the impact of an individual characteristic, personal innovativeness in the domain of information technology, in order to better predict users' intention to adopt an information technology innovation.

This study extends the knowledge of technology acceptance of a virtual reality simulation by incorporating the concept of personal innovativeness in the domain of information technology into the technology acceptance model.

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.

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.

The purpose of this study is to evaluate eTourism technology acceptance literature to illustrate current gaps in the field and suggest two alternative perspectives that could be adopted.

A review of academic literature in the field of eTourism technology acceptance was undertaken combining a systematic keyword-based search and snowballing techniques leading to the identification of relevant academic journal articles published since the year 2000.

While the field of eTourism technology acceptance research has grown substantially over the past few decades, this study highlights that the majority of this research seems to have been conducted within a narrow theoretical scope. The study suggests that this has led to contemporary theoretical and philosophical advancements in understanding the psychological, sociological and neuroscientific aspects of consumer behaviour not yet being mirrored in the eTourism technology acceptance research.

This study invites researchers to adapt alternative theoretical perspectives to create a more in-depth understanding of aspects of technology acceptance behaviour that have yet to be understood. Two distinct alternative perspectives, NeuroIS and interpretivism, are suggested.

This study assists researchers in developing alternative research agendas and diversifying the theoretical foundations of eTourism technology acceptance research.

eTourism technology acceptance research risks being left behind if it does not begin to think beyond current theoretical conceptions of consumer behaviour research. This study contributes to the wider literature by highlighting how eTourism literature is falling behind and by suggesting two innovative alternatives that allow eTourism research an exciting way forward.

本论文旨在审视eTourism技术接受研究文献, 以指出当前文献的不足, 并且提出两个未来可能研究方向。

研究样本为关于eTourism技术接受研究的文献, 文献搜集方法采用系统关键词搜索和雪球搜索技术, 共74篇相关研究文献, 发表年代为2000年至今。

eTourism技术接受研究自过去几十年的发展, 其研究成果已经显著增长。本论文强调这方面研究大多数局限在一个狭小理论领域中。本论文建议此方面的研究可以扩展到心理学 社会学 神经科学等消费者行为的领域,提高eTourism技术接受研究的现代理论和哲学进步,而这些方面在eTourism技术接受研究领域中, 还未涉足。

本论文邀请学者采用其他理论角度来增强技术接受行为的深入理解。两个显著研究方向包括NeuroIS和解释主义。

本论文启示学者在eTourism技术接受研究方面的开发新的研究征程, 以及丰富其相关理论基础。

eTourism技术接受研究将被落下, 如果学者不扩展当前关于消费者行为方面的理论基础。本论文拓宽了对eTourism文献的论述, 并且就其如何可能研究落后以及建议两个创新性方向, 使得eTourism研究将有一个崭新前进。

技术接受、电子旅游、技术接受模型(TAM)、神经资讯系统(NeuroIS)、 神经科学旅游(Neurotourism)、解释主义

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.

With recent advances in internet technologies, internet of things (IoT) technology is having an increasing impact on our daily lives, and beginning to offer interesting and advantageous new services. The current research aims to develop and test an integrative model of factors determining consumers' acceptance of IoT technology.

Based on technology acceptance model (TAM), the authors proposed an IoT acceptance model that consists of three technology factors (perceived usefulness, perceived ease of use, and trust); one social context factor (social influence); and two individual user characteristics (perceived enjoyment and perceived behavioral control). Data from 368 Chinese consumers were used to test the research model through the use of structural equation modeling.

The results showed particularly strong support for the effects of perceived usefulness, perceived ease of use, social influence, perceived enjoyment, and perceived behavioral control. However, trust played an insignificant role in predicting the intention. In addition, perceived ease of use and trust were found to affect perceived usefulness. Compared with the individual TAM model, the integrated model provides more explanation on user behavioral intention toward IoT usage.

The integrated model explores the driving factors of individuals' willingness to use IoT technology from the perspectives of the technology itself, social context and individual user characteristic. It links the constructs of social influence, enjoyment, and perceived behavioral control to the TAM and successfully extends TAM in the IoT technology context.

This paper aims to determine the entrepreneur's intention to accept artificial intelligence (AI) and provide advancement in the domain of digital entrepreneurship.

Extensive literature review and theories have been considered in the area of technology adoption/acceptance and digital entrepreneurship to identify the factors affecting the intention of entrepreneurs with respect to accept AI for digital entrepreneurship. Further, a model, artificial intelligence acceptance and digital entrepreneurship (AIADE) is theorized after formulating some hypotheses. The theorized model has been validated with 476 useable responses.

The findings revealed that performance expectancy, openness, social influence, hedonic motivations and generativity have a positive impact on entrepreneur's acceptance intention of AI. Additionally, affordance has no direct relationship with AI acceptance intention, but it affects AI acceptance intention through attitude. Inconvenience has a significant negative relationship with the intention to accept AI, while uncertainty was found to be positively affecting the AI acceptance intention. Effort expectancy did not confirm any significant relationship.

By considering existing theoretical models and concepts the authors contribute to the AI's theoretical progress, specifically in the domain of entrepreneurship. The authors complement and extend existing technology adoption/acceptance theories and digital entrepreneurship theories by developing a theoretical model, AIADE, explaining the entrepreneur's intention to accept AI.

The practical implications of the study show that performance expectancy (positive), openness (positive), social influence (positive), hedonic motivations (positive), generativity (positive), affordance through attitude (positive), uncertainty (positive), effort expectancy (negative) and inconvenience (negative) are the antecedents for the entrepreneurs to accept AI for digital entrepreneurship. The authors suggest that intentional improvement planning is developed by increasing entrepreneur's positive perceptions of AI affordance and explanation of its generativity and openness, and improving their attitude of using AI for digital entrepreneurship.

This is the first study that reveals the critical antecedents of entrepreneur's intention to accept AI for digital entrepreneurship. Relevant theoretical background, discussion, implications, limitations and future research recommendations are discussed.

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.