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This study aims to examine how the theory of planned behaviour and technology acceptance theory can be used to understand the adoption of non-pharmaceutical interventions (NPIs). The relationships between attitudes, behavioural intentions towards using NPIs, actual use of NPIs and word-of-mouth (WOM) were examined and compared between early and late adopters.

A survey was conducted to test the hypotheses with partial least squares structural equation modelling (n = 278).

The results indicate that relationships between attitudes, intentions and behavioural intentions were positive and significant in the whole data set – and that there were differences between the early and late adopters. WOM had no substantial relationship with actual usage and early adopters’ behavioural intentions.

This research gives a better sense of how WOM impacts attitudes, behavioural intentions and actual usage among early and late adopters of NPIs and highlights the effectiveness of WOM, especially among late adopters of NPIs. Furthermore, using the TAM allows us to make specific recommendations regarding encouraging the use of NPIs. A new three-stage communications model is introduced that uses early adopters as influencers to reduce the NPI adoption time by late adopters.

This study aims to investigate how early and late adopters of Quality 4.0 (Q4.0) differ in terms of organizational performance.

The authors employed a grounded theory approach for interviewing 15 senior managers from diverse organizational contexts throughout the globe as part of their qualitative research methodology.

The research's findings were analyzed based on four types of performance: operational, financial, environmental and social. It was clear that early adopters of Q4.0 were sustaining superior performance in quality over time, even though their investment was significantly higher than that of late adopters. From a financial viewpoint, it was evident that early adopters had a competitive edge over their rivals compared to late adopters. Late adopters have utilized the notion of the circular economy (CE) more effectively than many early adopters in the context of environmental performance in order to establish a green economy and sustainable development.

Although the results of the interview indicate that Q4.0 is having some positive effects on social performance, in the authors' view, it is still least understood from an empirical standpoint.

The study's findings assist organizations in comprehending the performance differences between Q4.0 early adopters and late adopters.

The purpose of this paper is to offer a new analysis and understanding of the notion of deinstitutionalization. Deinstitutionalization of taken-for-granted practices as a natural consequence of ever-increasing entropy seems to directly contradict the major institutional thesis, namely, that over time isomorphic forces increase and, as a result, possibilities for deinstitutionalization decrease culminating in the impossibility of abandoning in highly institutionalized fields.

This paper is conceptual in nature. Oliver’s 1992 paper on deinstitutionalization is taken as a key text on the subject and as a starting point for building an alternative theory of deinstitutionalization. More broadly, institutional theory and organizational literature on diffusion/adoption are reviewed and synthesized.

The authors argue that possibilities for deinstitutionalization have been overestimated in institutional literature and offer a revisited account of deinstitutionalization vs institutional isomorphism and institutionalized vs highly diffusing-but-not-institutionalized practices. A freedom for choice between alternative practices exists during the pre-institutional stage but not when the field is already institutionalized. In contrast, institutionalized, taken-for-granted practices are immutable to any sort of functional and political pressures and they use to persist even when no technical value remains, thus deinstitutionalization on the basis of a functional dissatisfaction seems to be a paradox.

By revisiting the nature and patterns of deinstitutionalization, the paper offers a better conceptual classification and understanding of how organizations adopt, maintain and abandon organizational ideas and practices. An important task of this paper is to reduce the scope of application of deinstitutionalization theory to make it more focused and self-consistent. There is, however, still not enough volume of studies on institutional factors of practices’ abandonment in institutional literature. The authors, therefore, acknowledge that more studies are needed to further improve both the former deinstitutionalization theory and the framework.

The authors offer a solution to this theoretical inconsistency by distinguishing between truly institutionalized practices and currently popular practices (highly diffused but non-institutionalized). It is only the latter that are subject to the norms of progress that allow abandoning and replacing existing organizational activities. Deinstitutionalization theory is, thus can be applied to popular practices that are subject to reevaluation, abandonment and replacement with new optimal practices while institutions are immutable to these norms of progress. Institutions are immutable to deinstitutionalization and the deinstitutionalization of optimal practices is subject to the logic of isomorphic convergence in organizational fields. Finally, the authors revisit a traditional two-stage institutional diffusion model to explain the possibility and likelihood of abandonment during different stages of institutionalization.

The study aims to explore the digital fashion trend within the Metaverse, characterized by non-fungible tokens (NFTs), across Twitter networks. Integrating theories of diffusion of innovation, two-step flow of communication and self-efficacy, the authors aimed to uncover the diffusion structure and the influencer's social roles undertaken by social entities in fostering communication and collaboration for the advancement of Metaverse fashion.

Social network analysis examined the critical graph metrics to profile, visualize, and cluster the unstructured network data. The authors used the NodeXL program to analyze two hashtag keyword networks, “#metaverse fashion” and “#metawear,” using Twitter API data. Cluster, semantic, and time series analyses were performed to visualize the contents and contexts of communication and collaboration in the diffusion of Metaverse fashion.

The results unraveled the “broadcast network” structure and the influencers' social roles of opinion leaders and market mavens within Twitter's “#metaverse fashion” diffusion. The roles of innovators and early adopters among influencers were comparable in collaborating within the competition venues, promoting awareness and participation in digital fashion diffusion during specific “fad” periods, particularly when digital fashion NFTs and cryptocurrencies became intertwined with the competition in the Metaverse.

The study contributed to theory building by integrating three theories, emphasizing effective communication and collaboration among influencers, organizations, and competition venues in broadcasting digital fashion within shared networks. The validation of multi-faceted Social Network Analysis was crucial for timely insights, highlighting the critical digital fashion equity in capturing consumers' attention and driving engagement and ownership of Metaverse fashion.

With the rise of cryptocurrency and its influence on the financial industry, this paper aims to explore cryptocurrency affordances that lead to approach–avoidance behavioral intentions for non-users (potential) and the intention to continue use for users (actual), drawing upon affordance theory and chasm theory.

The authors collected data from 480 potential and actual users in Germany and used maximum likelihood structural equation modeling (ML-SEM) to analyze it. In particular, the data consisted of 301 cryptocurrency users in Germany\ the authors used ML-SEM to test the post-adoption model. Additionally, logistic regression was utilized to determine the dominant actual usage method (store of value or medium of exchange) for various cryptocurrency coins.

According to the study's results, the perceived value benefits have a positive impact on the behavioral intention of potential users to adopt cryptocurrency, and they influence the intention of actual users to continue using it. However, both perceived volatility and financial risk tolerance are the most crucial factors hindering cryptocurrency adoption, whether in the pre-adoption or the post-adoption stage.

This is the first study to reveal cryptocurrency affordances and examine their effect on behavioral intentions toward cryptocurrency adoption based on the differences between non-users (potential) and users (actual). Furthermore, the authors explore how cryptocurrency holders perceive and invest in different coins (e.g. NFTs), which sheds light on factors such as financial risk tolerance that affect their decision making.

Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance. As innovation adoption is vital to achieving success and remaining competitive, it is important to measure and understand factors that impact innovation diffusion. Building on a survey of a national sample of 654 clinicians, our study measures the extent of diffusion of value-enhancing care delivery innovations (i.e., technologies that not only improve quality of care but has potential to reduce care cost by diminishing waste, Faems et al., 2010) for 13 clinical specialties and identifies healthcare-specific individual characteristics such as: professional purview, supervisory responsibility, financial incentive, and clinical tenure associated with innovation diffusion. We also examine the association of innovation diffusion with perceived value of one type of care delivery innovation – artificial intelligence (AI) – for assisting clinicians in their clinical work. Responses indicate that less than two-thirds of clinicians were knowledgeable about and aware of relevant value-enhancing care delivery innovations. Clinicians with broader professional purview, more supervisory responsibility, and stronger financial incentives had higher innovation diffusion scores, indicating greater knowledge and awareness of value-enhancing, care delivery innovations. Higher levels of knowledge of the innovations and awareness of their implementation were associated with higher perceptions of the value of AI-based technology. Our study contributes to our knowledge of diffusion of innovation in healthcare delivery and highlights potential mechanisms for speeding innovation diffusion.

Although social media has gained prominence as a communication and marketing tool in various sectors, its adoption and utilization within the construction industry remain relatively underexplored. Therefore, this study fills this gap by evaluating the level of awareness and the extent of adoption of social media within the Nigerian construction industry, shedding light on its current status and potential impact.

This objective was attained via a quantitative research approach that utilized a structured questionnaire to obtain responses from construction professionals such as architects, builders, engineers, quantity surveyors and estate managers. Frequencies and percentages and the mean item score (MIS) were used to analyze the questionnaire responses and assess the overall awareness and adoption of social media among construction professionals. Additionally, the Kruskal–Wallis H-test provided valuable insights into the variations in social media adoption levels among different professional categories within the construction industry.

The results indicate that construction professionals possess a generally high level of awareness regarding various social media platforms. However, despite this awareness, the extent of adoption does not align with the level of awareness, suggesting that adoption rates are not as widespread as anticipated.

The findings of this study underscore the importance of not just awareness but also effective adoption and utilization of social media platforms. While awareness is a crucial first step, construction firms should focus on implementing strategies to encourage greater adoption and integration of these platforms into their daily operations. This can go a long way in bridging the awareness – adoption gap which was revealed in this study.

While the limited existing research on social media in the construction industry has predominantly concentrated on areas such as marketing, addressing the root causes of fatalities, data environment tools and business branding, none have undertaken a thorough evaluation of social media awareness and adoption within the sector. This study fills a critical gap by narrowing its focus to the adoption dynamics and the technology’s potential impact on communication, collaboration and knowledge sharing among construction professionals.

This study aims to explore and ranks the factors that might determine attitudes and intentions toward using autonomous vehicles (AVs).

The “technology acceptance model” (TAM) was extended by assessing the moderating influences of personal-related factors. Data were collected from 378 Vietnamese and analysed using a combination of “partial least squares” and the “adaptive neuro-fuzzy inference system” (ANFIS) technique.

The findings demonstrated the power of TAM in explaining the attitude and intention to use AVs. ANFIS enables ranking the importance of determinants and predicting the outcomes. Perceived ease of use and attitude were the most crucial drivers of attitude and intention to use AVs, respectively. Personal innovativeness negatively moderates the influence of perceived ease of use on attitude. Data privacy concerns moderate positively the impact of perceived usefulness on attitude. The moderating effect of price sensitivity was not supported.

These findings provide insights for policymakers and automobile companies' managers, designers and marketers on driving factors in making decisions to adopt AVs.

The study extends the AVs literature by illustrating the importance of personal-related factors, ranking the determinants of attitude and intention, illustrating the inter-relationships among AVs adoption factors and predicting individuals' attitudes and behaviours towards using AVs.

User-generated content (UGC) refers to semantic and behavioral traces created by users on various social media platforms. While several waves of platforms have come and gone, the long-term sustainability of UGC activities has become a critical question that bears significance for theoretical understanding and social media practices.

Based on a large and lengthy dataset of both blogging and microblogging activities of the same set of users, a multistate survival analysis was applied to explore the patterns of users' staying, switching and multiplatforming behaviors, as well as the underlying driving factors.

UGC activities are generally unsustainable in the long run, and natural attrition is the primary reason, rather than competitive switching to new platforms. The availability of leisure time, expected gratification and previous experiences drive users' sustainability.

The authors adopted actual behavioral data from two generations of platforms instead of survey data on users' switching intentions. Four types of users are defined: loyal, switcher, multiplatformer and dropout. As measured by the transitions among the four states, the different sustainability behaviors are thereby studied via an integrated framework. These two originalities bridge gaps in the literature and offer new insights into exploring user sustainability in social media.

Despite the existing gaps in the use of technology in East Africa, the region is among the fastest-growing mobile data users on the continent. This progress is partially attributed to local initiatives to develop and adapt homegrown technologies to local contexts to increase their accessibility and use even in the remotest areas. In this chapter we identify a few of these innovations in Kenya, Rwanda and Uganda and examine how they have been indigenised to fit local contexts as well as the processes of their diffusion, adoption, affordability and accessibility among users and their everyday gratifications from the innovations. The socio-technological assemblage theory, which illuminates the influences of, and the connections between various types of actors and their roles, visions, ideas, concepts and the technological products, informs our inquiry. Other related concepts including ‘innovation’, ‘indigenisation’ and ‘diffusion’ are discussed to understand the homegrown technology innovations and their adaptability. Discussions with both innovators and users/beneficiaries reveal rigorous proactiveness and responsiveness of innovation creators and users in the three countries – reflected in numerous attestations of life transformation. Nevertheless, there is a paradigm shift in the diffusion of innovations amongst users – contrary to the discourse around its early precepts.