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Several disciplines and thousands of studies have used, developed and supported technology adoption theories to guide industry and support innovation. However, within the past decade, a paradigm shift referred to as the fourth industrial revolution (4IR) has resulted in new considerations affecting how models are used to guide emerging technology integration into business strategy. The purpose of this study is to determine which technology adoption model, or models are primarily used when assessing smart technologies in the 4IR construct. It is not to investigate the rigour of existing models or their theoretical underpinnings, as this has been proven.

To achieve this, a systematic literature review based on the preferred reporting items for systematic reviews and meta-analysis methodology is used. From 3,007 publications, 125 papers between 2015 and 2021 were deemed relevant for thematic analysis.

From the literature, five perspectives were extracted. As with other information and communication technology studies, the analysis confirms that the technology acceptance model remains the predominantly used model. However, 105 of the 125 models extended their theoretical underpinnings, indicating a lack of maturity. Furthermore, the countries of study and authors’ expertise are predominantly clustered in the European and Asian regions, despite the study noting expansion into 16 different subject areas, far beyond the smaller manufacturing scope of Industry 4.0.

This study contributes theoretically by providing a baseline to develop a generalisable 4IR model grounded on existing acceptance trends identified. Practically, these insights demonstrate the current trends for strategists and policymakers to understand technology adoption within the 4IR to direct efforts that support innovation development, an increasingly crucial factor for survival in the digital age. Future research can investigate the additional constructs that were impactful while considering the level of research they were applied to.

Today, a firm’s major concern is to know the way in which an innovation is adopted in the marketplace. The purpose of this paper is to focus on the two-stage nature of diffusion process in which the time lag between people being informed and their act of making final purchase is considered.

The paper discusses an approach based on the time lag for modeling awareness and adoption process as two separate and yet connected processes. Varying forms of time lag (constant, deterministic or random) have been considered while modeling the required framework. Furthermore, an equivalence approach has been shown between the present framework and the two well-known and established approaches of infinite queuing theory and hazard rate function.

The results are verified on sales data of two different consumer durables and it show good prediction capability of proposed models in capturing the real-life scenario. Further, the equivalence approach helps us to quantify such scenarios which were difficult to be modeled with any one particular approach. Further, the possibility of capturing different market scenarios by studying various distribution functions has been identified.

The proposed methodology is based on a two-stage adoption process. The same can be extended to a multi-stage adoption process as in today’s competitive environment. “Motivation” is one such factor that is highly important which can be considered in some later studies. In future, the authors wish to study the multi-stage adoption process considering the different forms of time lag function.

The equivalence approach discussed in the paper can help to cater the possibility of capturing different market scenarios by studying various distribution functions.

The proposed approach helps to cater the time lag between awareness and adoption process and develop different mean value functions to account for the manner in which sales are happening under different circumstances. The proposed methodical approach can also help decision makers in managing their available resources in a prudent manner.

This paper aims to examine mobile banking adoption in Islamic banks by integrating technology adoption model (TAM) and Religiosity-Behavioural Intention Model.

This study uses a sample of 300 mobile banking customers of Islamic banks from West Java Province, Indonesia. Partial least square was applied to assess the association between perceived usefulness, perceived ease-of-use, religiosity, satisfaction, and adoption.

The results of this study disclosed that the integration of TAM and Religiosity-Intention model provides a more complete explanation of Islamic bank consumers’ adoption of mobile banking. Besides perceived usefulness and perceived ease-of-use, the results of this study emphasise the importance of religiosity in mobile banking adoption.

This study offers an opportunity for Islamic bank managers to increase the adoption of their mobile banking services. To increase the adoption of mobile banking services, Islamic banks must not only provide an application that is useful and easy to use but also consider the customer’s religiosity. All of their mobile banking marketing strategies should focus on providing high-quality mobile service while ensuring the bank’s operations are compliant with the Islamic law.

This study is the first attempt to integrate TAM and Religiosity-Intention Model to assess mobile banking adoption.

The significance of cloud services in information technology (IT) is increasing as a means of achieving enhanced productivity, efficiency and cost reduction. Through cloud-based service, the reliability and scalability of an organization’s systems can be enhanced since organizations such as local governments are able to concentrate on their main business strategies. This research seeks to identify critical factors that may have an impact on the acceptance of cloud-based services, where the organizational context is based on local governments in Australia.

To formulate a more comprehensive IT innovation adoption model for cloud technology, factors from the technology-organizational-environment framework, desires framework and diffusion of innovation model were integrated. Data was obtained from 480 IT staff working in 47 local government organizations.

The research results show that the factors which had a statistically significant and positive impact on the adoption of cloud-based services in local governments were compatibility, complexity, cost, security concerns, expected benefits and organization size. It is likely that the outcomes from this research will provide insights to any organization seeking to make investment decisions on the adoption of cloud-based services.

Limitations include generalizability of the findings since the data is restricted to local government areas in Queensland, Australia. Further, the sample mostly included individuals with managerial positions and may not completely capture the cloud adoption factors relevant for front line IT employees. Another limitation is the possible omission of factors that may be relevant but not considered due to the selected theories. Lastly, this research did not differentiate between different types of cloud adoption such as private, public, community and hybrid models that are possible in this context.

The paper provides a combination framework of cloud-based service adoption based on a literature review on cloud adoption from an IS perspective. It adapts integrated model to establish a more comprehensive innovation adoption framework for cloud technology.

Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.

The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.

The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.

Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.

To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.

This study aims to establish an adoption model using Structural Equation Modeling (SEM) that examines the relationship between several key indicators that drive building information modeling (BIM) adoption.

The study was carried out using quantitative approaches through the Delphi method and questionnaire survey. A total of 272 completed responses were collected and analyzed through the SEM technique using SPSS 25 and AMOS software.

The structural model shows that “environment” and partially “people” indicators are the leading indicators driving BIM adoption with path coefficient values of 0.280 and 0.332, respectively.

It is expected that these conclusions will lead the Bahraini construction industry stakeholders to raise the level of BIM adoption.

This study aims to undertake a contextual analysis of project-level building information modelling (BIM) adoption in Nigeria and demonstrate how BIM is applied across different projects in Nigeria.

This research generates contextual and holistic understandings of multiple project-level cases of BIM adoption through an interpretive paradigm guided by relativist ontology and subjectivist epistemology. Two models of project-level BIM adoption (ten-factor theory of BIM adoption and strategic-contingent model of BIM adoption) were merged to formulate the BIM adoption assessment scale (BIM-AAS). A qualitative-oriented case study protocol was developed to extract valid and reliable data from external and internal project data based on BIM-AAS features. The extracted data were analysed using the pattern-matching technique and cross-case analysis.

The results indicate that there was substantial use of BIM tools and technologies in the projects. All the projects adopted collaborative procurement and team and developed integrated building information models. The use of BIM tools, technologies and processes in the projects was found to be above average. The complexities and expectations levels of the projects compliment the nature of BIM adoption in the projects.

The BIM-AAS adopted in this research is an excellent example of a project-level BIM adoption analytical tool. It can be assumed in future research. Also, this research contributes to the theory that the level of project complexity and expectations must align with the level of BIM adoption in projects. The study’s findings ratify BIM tools, technologies and processes as the elements of project-level BIM adoption.

This research substantiates the actual nature and structure of BIM adoption in Nigeria, thereby simplifying the development of initiatives towards BIM adoption in projects and determining the appropriate strategies for BIM implementation and innovation in the Nigerian construction industry. The most important initiative that the Nigerian government can make to drive BIM implementation is the automating of code checking for building rules and regulations in Nigeria.

Previous studies have only reported cases of project-level BIM adoption using surveys and without a standardised project-level BIM adoption model to guide the analysis. This study is the first to formulate and use BIM adoption models for a uniform, critical and contextual analysis of project-level BIM adoption.

Off-site construction (OSC) has been regarded as a clean and efficient production approach to help the construction industry towards sustainability. Different levels of OSC technologies vary greatly in their implementations and adoptions. Compared to low OSC level technologies have been applied widely, the adoption of high OSC level technologies (HOSCLTs) in practice remains limited. The adoption mechanism for HOSCLTs by firms has not been clear, hindering their promotion. This study aims to explore the mechanism combining subjective and objective adoption for HOSCLTs.

This study developed an integrated model illustrating mechanism for HOSCLTs adoption based on the technology acceptance model (TAM), which has strong capacity to explain potential adopters' subjective intentions to adoption, and the task-technology fit (TTF) theory, which well describes the linkages between the task, technology and performance in technology adoption. The proposed model was then empirically evaluated through a survey of 232 practitioners in the Chinese OSC industry using partial least squares structural equation modeling.

The results indicate that both task characteristics (TAC) and technology characteristics (TEC) positively affect TTF of HOSCLTs. TAC, TTF, firm conditions and stakeholder influence have significant positive effects on perceived usefulness (PU), which further positively influence attitude towards adoption. TEC and firm conditions are significantly related to perceived ease of use (PEU). TTF, PEU and attitude towards adoption are good predictors of behavior intention to HOSCLTs adoption. PEU only significantly influences adoption intention and is not observed to influence attitudes and PU, unlike prior research on common OSC adoption.

This study contributes to the body of knowledge by exploring HOSCLTs adoption in the industry based on distinguishing the levels of OSC technologies and supplementing an integrated model for explaining the mechanism with the combination of subjective and objective adoption. The study also provides useful insights into understanding and promoting HOSCLTs adoption for policy makers and stakeholders actively involved in the OSC field.

The purpose of this research is to develop a comprehensive model to better understand competitive dynamics between mobile payment providers in a multi-sided market featuring customers and merchants. This is undertaken by modeling customers performing financial transactions with merchants while two mobile payment systems (MPS) providers deploy different strategies to compete for market share.

The authors developed an agent-based simulation model using the NetLogo environment. The simulation featured two competing platform providers, 1,000 customer agents and 50 merchant agents. Past research, interviews and surveys were conducted to accurately model the behavior of the agents. Each simulation run lasted for 50 time periods. A total of 1,024 experimental conditions were designed to model different competitive environments, and 50 replications were conducted for a total of 51,200 experiments.

The simulation model provides insight into MPS platform providers’ competitive strategies by simultaneously modelling socioeconomic interactions between customers, merchants and MPS.

From a methodological perspective, the paper contributes a comprehensive model that can be used to study competitive dynamics between competing platforms in a multi-sided market. From the perspective of competitive strategies, the results show that pricing alone is not sufficient to influence MPS diffusion. Interactions between pricing, customers’ risk perception, perceived security and ease of use of the platform create unexpected same-side and cross-side network effects, which affect MPS diffusion.

While pricing remains a crucial lever for MPS to compete for market share, they should focus on enhancing customers’ and merchants’ trust and reduce their risk perception. This can be done through the improvement of the user experience of their platform, development of educational materials and marketing campaigns that address concerns around security, data breaches and perceived risk.

The paper is a direct response to a recent call for action on studying competition between MPS platforms by simultaneously modelling the socio-economic behavior of heterogeneous consumers and merchants. The proposed agent-based simulation model can be used to provide insights into competitive strategies and as a building block for subsequent research in this area.

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.