Search results

Successful adoption of building information modelling (BIM) by early adopters is crucial for its effective diffusion. The purpose of this study is to develop a framework of understanding that supports contextualized understanding of BIM adoption decisions in a BIM infant industry. The framework bridges the gap in current knowledge in terms of the absence of such a framework, which has hindered the structured understanding of the BIM decision of an adopter, curtailing the appropriate strategizing of their BIM adoption.

The study focuses on a BIM infant industry, where early adopters begin using BIM, allowing insights into this crucial initial stage of adoption. Identifying affordances as a versatile concept that could effectively represent not only what an adopter perceives and expects from BIM implementation, but also, what the adopter, in fact, can achieve from it, an affordance-led framework of understanding (AFU) was developed to comprehensively capture varying dynamics of BIM decision process. The study took a qualitative retroductive approach to theory with semi-structured interviews to gather necessary data from a sample of BIM adopters purposively selected to maximize the breadth and depth of data.

The study concludes by identifying and defining pertinent affordances as a new concept and a compulsory state for BIM adoption. Findings further demonstrate that existing theories can be linked to the AFU to strategically direct the affordances dynamics towards the pertinent state.

The AFU enables a deeper contextualizable view of innovation adoption that was absent in existing innovation studies. It significantly enhances the precision of strategizing BIM adoption compared to previous approaches, enabling adopters to plan and implement BIM in a manner that aligns well with their expectations and specific conditions.

Limited use of Internet of Things (IoT) technology on construction sites has restricted its value in the construction industry. To propel its widespread application, this paper explores the influencing factors and action paths of construction companies' IoT technology adoption behavior.

First, literature research, technology adoption theories, and semi-structured expert interviews were employed to build the adoption model. Second, a questionnaire survey was conducted among Chinese construction contractors to collect empirical data. Third, the structural equation model method and regression analysis were used to test the adoption model. Finally, the findings were further validated with interviews, case studies, and field observations.

External environmental pressure (EEP), perceived benefit (PB), top management support (TMS), company resource readiness (CRR), adoption intention (AI), and perceived compatibility (PCA) have a direct positive impact on adoption behavior (AB). In contrast, perceived cost (PC) and perceived complexity (PCL) exert a direct negative impact on AB. The EEP, PB, and PC are critical factors affecting AB, whereas AI is strongly affected by CRR and TMS. Besides, AI plays a part mediating role in the relationship between seven factors and AB. Company size and nature positively moderate AI's positive effect on AB.

This paper contributes to the knowledge of IoT technology adoption behavior in the construction sector by applying the technology adoption theories. Exploring the implementation barriers and drivers of IoT technology in construction sites from the perspective of organizational technology adoption behavior and introducing moderating variables to explain adoption behavior are innovations of this paper. The findings can help professionals better understand the IoT technology adoption barriers and enhance construction companies' adoption awareness, demand, and ability. This work also provides a reference for understanding the impact mechanism of the adoption behavior of other innovative technologies in construction.

The authors study how cloud adoption decision making unfolds in organizations and present the dynamic process leading to a decision to adopt or reject cloud computing. The authors thus complement earlier literature on factors that influence cloud adoption.

The authors adopt an interpretive epistemology to understand the process of cloud adoption decision making. Following an empirical investigation drawing on interviews with senior managers who led the cloud adoption decision making in organizations from across Europe. The authors outline a framework that shows how cloud adoptions follow multiple cycles in three broad phases.

The study findings demonstrate that cloud adoption decision making is a recursive process of learning about cloud through three broad phases: building perception about cloud possibilities, contextualizing cloud possibilities in terms of current computing resources and exposing the cloud proposition to others involved in making the decision. Building on these findings, the authors construct a framework of this process which can inform practitioners in making decisions on cloud adoption.

This work contributes to authors understanding of how cloud adoption decisions unfold and provides a framework for cloud adoption decisions that has theoretical and practical value. The study further demonstrates the role of the decision-leader, typically the CIO, in this process and identifies how other internal and external stakeholders are involved. It sheds light on the relevance of the phases of the cloud adoption decision-making process to different cloud adoption factors identified in the extant literature.

This study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.

The study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.

Study results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.

Study findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.

This study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

This study aimed to investigate and analyze the level of awareness and adoption of distributed ledger technologies (DLTs) within the Nigerian construction industry. The focus was on addressing the current state of DLT utilization, identifying challenges and opportunities and proposing strategies to enhance the integration of DLTs into the construction processes and practices of Nigerian professionals and organizations.

The research was underpinned by a robust theoretical and conceptual framework, drawing from established theories of technology adoption. A comprehensive literature review guided the identification of various DLT types. This informed the development of a well-structured questionnaire, which was then distributed to Nigerian construction professionals. The collected data underwent analysis using percentages, frequencies, mean scores, the Kruskal–Wallis H-test and the Shapiro–Wilk test.

A significant finding of this study reveals a generally low awareness and implementation of DLT among construction professionals in Nigeria. These findings emphasize the urgent need for comprehensive strategies to bridge the gap between awareness and adoption of DLT within the Nigerian construction industry.

Industry associations, regulatory bodies and educational institutions can collaborate to develop specialized programs aimed at familiarizing professionals with the benefits and applications of DLTs. Additionally, technology providers and policymakers can leverage these findings to design user-friendly interfaces and guidelines for seamless DLT integration into construction processes.

This study contributes to the existing body of knowledge by providing a comprehensive assessment of the awareness and adoption of DLTs specifically within the Nigerian construction industry. While the global recognition of DLT’s potential in construction is acknowledged, this research delves into a regional context, shedding light on the specific opportunities within Nigeria. Furthermore, the study’s identification of a gap between awareness and implementation highlights a critical area for future exploration and development in the field of construction technology adoption.

Ambient-assisted living (AAL) is one solution to the challenges of healthcare systems in an aging population. Using the “ecosystem adoption of practices over time” (EAPT) as a theoretical lens, this study explores and describes three elements of AAL adoption: (1) the AAL practices in which the technology is embedded (i.e. object of adoption), (2) the older adult's adoption ecosystem (i.e. subject of adoption) and (3) the change of adoption practices over time (i.e. temporality of adoption).

Qualitative interviews with three actor groups in the ecosystem: clients, relatives and home nurses.

The study identifies six categories of AAL practices. Clients, relatives and nurses interact and integrate their resources in carrying out these practices. Some of the practices have developed, or are expected to develop, over time.

The study applies a novel theoretical perspective on how AAL technology is embedded in practices performed by different actors in the adoption ecosystem. This broadens the conceptualization of what is being adopted compared to traditional adoption research.

The purpose of our study was two-fold: (1) to examine the effect of perceived value derived from perceived benefits and sacrifices in the adoption of artificial intelligence (AI) in talent acquisition and (2) to investigate the moderating role of human resource (HR) readiness in the association between perceived value and AI adoption intention.

A structured questionnaire was administered to 198 talent acquisition executives and HR professionals of Indian IT companies based on a purposive sampling technique. Partial least squares structural equation modeling (PLS-SEM) was used on the Smart PLS 2.0 platform to analyse the data and test the model.

Results revealed that perceived benefits and sacrifices significantly predict perceived value which significantly affects the HR professional’s AI adoption intention. The study further found that HR readiness moderates the link between perceived value and the intention of HR professionals to adopt AI in the talent acquisition process in the Indian IT industry.

IT companies are advised to continuously monitor and evaluate the performance of AI tools to ensure that they are meeting the recruitment process needs to leverage AI’s benefits in talent acquisition. This study seeks to provide the impetus for a planned AI adoption in talent acquisition.

This research provides ample evidence for the existing technology adoption theories. It explored the predictors of adoption by validating the value-based adoption model in the Indian context. It provides valuable insights into the practice of acquiring talents in the IT sector using artificial intelligence.

There is a growing awareness in today's organizations of the gap between existing digital technologies and those arising from digital innovation that contribute to reducing work exhaustion. However, no comprehensive framework has been proposed for the importance of adopting digital innovation in reducing work exhaustion. The purpose of this paper is to provide a holistic view by proposing a model for the importance of adopting digital innovation technologies and their role in reducing work exhaustion in Iraq as a developing country, and the model was proposed based on the theory of technology-organization-environment and diffusion of innovation.

To collect data, an electronic questionnaire was designed for a survey conducted on 183 Iraqi firms in the industrial sector. For data analysis, the structured equation model was used through the (AMOS. 26) program.

The results revealed the importance and significance of the study model in adopting the cloud of things (CoT) as one of the techniques of digital innovation in reducing work exhaustion.

The authors can conclude that the adoption of the CoT in small and medium enterprises (SMEs) can have a positive impact on the performance of the employees. The adoption of the CoT may provide SME managers with an opportunity to effectively manage various roles and responsibilities. While there were many limitations that this study faced, the authors focused on one type of digital innovation dynamics, which is the CoT, as they must focus on other technologies.

To the best of the authors’ knowledge, this study is one of the first studies in Iraq as a developing country that explains how emerging digital innovation can be leveraged to create innovative digital products and services as a CoT technology and subsequently lead to the reduction of work exhaustion. It also fills the literature gaps related to adoption factors of digital innovation and their role in reducing work exhaustion.

This study aims to construct an appropriate framework by incorporating essential components from the most renowned theories to investigate the variables that impact behavioural intentions towards embracing cashless transactions (CLT).

A survey was conducted to ascertain the users’ intention to adopt CLT in Chennai, Tamil Nadu, India. Further, this study used a “partial least squares-based structural equation modelling” technique to analyse the relationships between latent factors.

The results of the proposed model revealed that 11 independent variables together explain the intention to use CLT with a 60.5% explanatory power. Further, perceived usefulness is the most influential factor in predicting users’ willingness to adopt CLT, followed by social influence, perceived costs, attitude, trust and device barriers. Finally, the findings of moderator effects indicate that income and experience interact positively and strongly with behavioural intention to adopt CLT. It indicates that high-income, experienced users are more likely to convert their intentions into actions.

This study integrated critical elements from the major theories, such as Theory of Reasoned Action, Technology Acceptance Model, Decomposed Theory of Planned Behaviour, the unified theory of acceptance and use of technology (UTAUT) model and UTAUT2, to investigate the adoption of CLT. As a result, 11 crucial factors were identified from the existing literature that impacts CLT adoption without overlapping. Consequently, the model presented in this study provides a more profound understanding than previous research regarding why individuals adopt CLT systems. Accordingly, these results could aid policymakers in addressing people’s concerns and facilitating a seamless transition to a cashless society.

The sharing economy is changing the way people use products and services, and the success of sharing-based apps like bicycle and automobile sharing has drawn a lot of interest across the world. The purpose of this research is to investigate the factors affecting the consumer's adoption of ride-sharing services.

With this aim, the current study integrates the Technology Acceptance Model (TAM) and Expectancy Confirmation Model (ECM) with a further extension of consumer trust and social norms. Using a survey-based research design, data were collected from 558 respondents using multi-stage convenience sampling on 5 point Likert scale. Confirmatory factor analysis is conducted followed by structural equation modelling using IBM AMOS-22.

The findings of the study report crucial determinants for the consumer's continuance intention and actual use of these services. Perceived usefulness, consumer satisfaction, trust and subjective norms were found positively associated with the continuous intention to use ride-sharing services, whereas perceived ease of use was found to be insignificant. This study also highlights antecedents for the consumer's trust towards these services and found reputation, propensity to trust as a significant contributor whereas structural assurance was found insignificant to establish the trust among the users.

The research on consumer adoption towards ride-sharing services are meagre and this study adds the value to the field by integrating TAM and ECM model with further extension of consumer trust and social norms and empirically test the proposed model.