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This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail.

The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM).

The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions.

To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR.

This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI.

The purpose of this study is to explore the potential and challenges of biogas utilization as an alternative and sustainable energy source in the Gurage zone of Southern Ethiopia, where traditional energy sources such as firewood and charcoal are widely used.

The study adopts a mixed-methods approach to collect and analyze data from different sources and perspectives. The research collects quantitative data from structured interviews with 200 rural households who use biogas or other energy sources, and qualitative data from key informant interviews and focus group discussions with biogas experts, local authorities and community leaders. Socioeconomic analysis is conducted to assess the importance of biogas in terms of income, expenditure, health and environmental benefits, and a multivariate probit model is used to identify the factors influencing biogas energy adoption among rural households.

The findings indicate that biogas users are more likely to substitute traditional energy sources with biogas for cooking, lighting and heating purposes. The model reveals that age, sex, education level, land size and livestock quantity influence biogas energy adoption, whereas income, distance to market and access to credit do not have a significant effect. The findings also show that biogas users have higher income, lower expenditure, better health and lower greenhouse gas emissions than nonusers.

The study concludes that the socioeconomic impact of biogas varies among households based on location and lifestyle. The study also highlights the need for further research on the technical, institutional and behavioral aspects of biogas utilization in different contexts.

To address the challenges faced by biogas users and their energy choices, such as lack of awareness, maintenance, quality control and affordability, the study suggests exploring biogas energy to meet the diverse needs of cattle owners in different regions. The study also recommends enhancing the capacity of local stakeholders, promoting public–private partnerships, and developing supportive policies and regulations for biogas development in Ethiopia.

The study implies that biogas utilization can contribute to social development by improving the living standards, health status and gender equality of rural households. The study also suggests that biogas utilization can foster social cohesion and empowerment by creating opportunities for collective action, knowledge sharing and income generation among biogas users and their communities.

The study provides a comprehensive and empirical analysis of the socioeconomic landscape of biogas utilization and the determinants of energy choice in the Gurage zone of Southern Ethiopia. The study also offers valuable insights and recommendations for policymakers, practitioners, researchers and other stakeholders involved in biogas development in Ethiopia and other developing countries.

This systematic literature review aims to explore the adoption, global acceptance and implementation of human resources (HR) analytics (HRA) by reviewing literature on the subject. HRA adoption can assist HR professionals in managing complex procedures and making strategic human resource management (SHRM) decisions more effectively. The study also aims to identify the applications of analytics in various disciplines of management.

The review is conducted using a domain-based structured literature review (SLR), emphasizing the diffusion of innovative thinking and the adoption process of HRA among early adopters. The philosophical stances are analyzed with the combination of research onion model and PRISMA protocol. Secondary data are gathered from published journals, books, case studies, conference proceedings, web pages and media stories as the primary source of information.

The study finds that skilled professionals and management assistance can significantly impact adoption intentions, enabling professionals to deal with analytics. The examples and analytical models provided by early adopters allow managers to manage complex processes and make SHRM decisions.

The study suggests that the lack of use of quantitative techniques is a key limitation and should be considered in future studies. Despite the rise in the number of research papers on HRA, its application in the workplace remains limited.

This research can assist managers in implementing HRA and help resolve complex and inefficient processes, making SHRM decisions.

This study adds to the existing body of knowledge on how HRA can aid a company's efficacy and performance and can be considered one of the first to link adoption and HRA.

This study aims to develop and test an original conceptual framework that examines the role of various factors borrowed from three theories (i.e. Institutional Theory, Resource-Based View and Diffusion of Innovation) in adopting Human Resource Analytics (HRA).

A new conceptual framework (research model) is developed based on previous research and coherent theoretical arguments. Its factors are classified using the Technology–Organization–Environment (TOE) framework. Research hypotheses are tested using primary data collected from 152 managers of Greek organizations. Empirical data are analyzed using the “Structural Equation Modelling” (SEM) technique.

The technological and organizational context proved extremely important in enhancing Organizational Analytics Maturity (OAM) and HRA adoption, while the environmental context did not. Relative advantage and top management support were found to significantly impact the adoption of HRA, while Information Technology (IT) infrastructure, human resource capabilities and top management support are crucial for increasing OAM. Overall, the latter is the most important factor in enhancing HRA adoption.

This study contributes to the limited published research on HRA adoption while at the same time it can be used as a guideline for future research. The novel findings offer insights into the factors impacting OAM and HRA adoption.

This study aims to examine the key antecedents influencing the private firm’s intention to adopt big data analytics (BDA) in developing economies. To do so, the study follows the sequential explanatory approach.

To test the hypothesized model that draws on the technology–organization–environment (TOE) framework paired with the diffusion of innovation (DOI) theory, a purposive sampling technique was applied to gather data from 156 IT and management domain experts from the private firms that intend to adopt BDA and operate in Pakistan’s service industry, including telecommunication, information technology, agriculture, and e-commerce. The data were analysed using the partial least squares structural equations modelling (PLS-SEM) technique and complemented with qualitative analysis of 10 semi-structured interviews in NVIVO 12 based on grounded theory.

The empirical findings revealed that the two constructs – perceived benefits and top management support – are the powerful drivers of a firm’s intention to adopt BDA in the private sector, whereas IT infrastructure, data quality, technological complexity and financial readiness, along with the moderators, BDA adoption of competitors and government policy and regulation, do not significantly influence the intention. In addition, the qualitative analysis validates and further complements the SEM findings.

Unlike the previous studies on technology adoption, this study proposed a unique research model with contextualized indicators to measure the constructs relevant to private firms, based on the TOE framework and DOI theory, to investigate the causal relationship between drivers and intention. Furthermore, the findings of PLS-SEM were complemented by qualitative analysis to validate the causation. The findings of this study have both theoretical and practical implications.

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.

Despite the critical role of the policy environment in facilitating the advancement of building information modeling (BIM) as a systemic innovation to reshape traditional facility design, construction and operation processes, scant scholarly attention has been paid to systematically investigating how and why complex BIM policies are concretely and gradually implemented in different regional contexts from a dynamic policy diffusion perspective. This study aims to empirically investigate how different types of BIM policy instruments are dynamically implemented in heterogeneous regions over time and how the diffusion of BIM policies across different regions is comprehensively impacted by both internal efficiency needs and external legitimacy pressures.

This study employed a positivist research paradigm in which BIM policy data from 182 prefecture-level and above cities in China during 2011–2022 were analyzed with quantitative approaches for theory verification. Based on the content analysis of the evolutionary characteristics of the adopted BIM policy instruments in heterogeneous regions over time, the event history analysis (EHA) method was then used to further examine the mechanisms underlying the diffusion of BIM policies across different regions.

The content analysis results show that while environmental instruments (such as technological integration and goal planning) are the primary policy instruments currently adopted in China, recent years have also witnessed increasing adoptions of supply-side instruments (such as fiscal support and information support) and demand-side instruments (such as demonstration projects and tax incentives). After controlling for the impacts of regional fiscal and technical resources, the EHA results illustrate that BIM policy adoption positively relates to regional construction industry scale but negatively relates to regional industry productivity and that compared with public pressures from industry participants, vertical pressures from the central government and horizontal pressures from neighboring regions are more substantial drivers for policy adoption.

As an exploratory effort of using a dynamic policy diffusion perspective to systematically investigate how BIM policies are adopted in heterogeneous regional contexts to facilitate BIM advancement, this study not only characterizes the complexity and dynamics of BIM policies but also provides deepened understandings of the mechanisms underlying policy adoption in the conservative construction industry. The findings hold implications for how multifarious policy instruments can be more effectively and dynamically adopted to facilitate the advancement of BIM and related technologies as innovative solutions in the construction domain.

This study aims to study the factors that drive non-users of digital banking services rendered by Islamic banks in Malaysia towards their adoption of digital services in the banking 4.0 era using the innovation diffusion theory (IDT), also known as the diffusion theory of innovation (DOI).

IDT theory and literature on intention to adopt digital bank services were reviewed in a bid to contribute to the factors that drive non-users to adopt digital banking.

The review suggests that the adoption of digital banking is determined not only by perceived relative advantage, and perceived compatibility but also by additional factors in IDT theory, which are technology self-efficacy and perceived expected benefits. On the contrary, perceived complexity does not turn out to be a factor of digital banking adoption.

Considering this paper in terms of the limited scope of the theory rendered and the context, it should be given proper attention when interpreting future outcomes when further investigations are brought into play in terms of population and sampling method.

This paper serves as a guide to ensure the better planning of non-users’ adoption factors related to Islamic bank customers in both theory and practice.

DOI is extended in the context of digital banking, as evidenced by empirical results, and literature shows that IDT integrated with the technology self-efficacy model is yet to be proposed in the digital banking adoption by Islamic bank customers. Additionally, variables, namely, perceived expected benefits and technology self-efficacy, are proposed in IDT’s existing model. Current findings will therefore serve as a relevant reference for digital technology specialists, policymakers, Islamic banks’ IT managers, academicians and future researchers.

Technological innovations provide huge opportunities to expand and revolutionize the scope of products and services offered. This is particularly true for tourism, which is undergoing significant changes due to the development of new technologies. The level of technology diffusion depends on several factors like the exchange of information among peers, and the attitude and shared perception among the contributors. The aim of the study is to explore the diffusion of technology in tourism with a specific focus on the social media discourse around new technologies. Thus, the paper investigates the level of interest in these new technologies analysing the information exchange occurring between individuals on Twitter in order to explore the influence of reciprocal networking.

To capture the attitudes expressed in the industry, the study analyses the ongoing discourse on Twitter as a proxy for the participants “interest in new technologies. Through a social network analysis of the tweets and retweets conducted over a period of nine months, the research maps the level of information exchange about the diffusion of new technologies. Moreover, the sentiment analysis provides an interesting overview of the individuals” attitudes towards the awareness or the adoption of new technologies.

Our analysis has provided several insights: (1) the information network on blockchain in tourism consists of participants who change very quickly over time (high turnover of accounts); (2) some contributors have an extremely important role in influencing the flow of information in the system (information centralization), they can have a generalist (discussing several topics) or a specialist (focusing on a specific topic) behaviour and this strategic choice influences their network's structure; (3) these central nodes also have an impact on the definition of positive and negative sentiment towards a topic (sentiment influencer).

The paper contributes to the literature on technology diffusion, by focusing on one of the preconditions of diffusion that is the shared positive attitude towards technological innovation. More specifically, we adopt a network-based approach, which is useful to explain the level of information exchange and the public discourse that can impact the shared perception and attitude towards technological innovation. The study also highlights the role of knowledge brokers in influencing this public discourse. Future studies can deepen the association between positive perception, higher levels of information exchange and increasing usage of specific technologies. Our results also suggest further exploring the opportunity to combine social media data and other sources of information to shed more light on the technological innovation diffusion processes.

This paper shows how practitioners can benefit from the analysis of information exchange about new technologies in tourism adopting a network perspective with the aim of understanding the level of influence among contributors. Moreover, the increasing interest in blockchain technology and the potential combination between social media data and other sources of information can offer promising insights.

The present study explores the level of technology diffusion through the analysis of information exchange on social media (Twitter). Furthermore, the dynamics of individual user behaviour offers a better understanding about media effects.

While previous research is focused on the users' perception towards the development of new technologies in tourism, the aim of this study is to investigate the dynamics behind the level of diffusion of information and awareness about these new technologies, which still represents an unexplored area of research.

Insufficient intra-organizational diffusion of prefabricated construction (PC) technology hinders its implementation benefits. More research on intra-organizational diffusion of PC technology is required to improve organizational performance in PC implementation. This study aims to explore the antecedents and consequence of intra-organizational diffusion of PC technology.

This study established an antecedent and consequence model of intra-organizational diffusion of PC technology from the perspective of contingency theory. The model was empirically tested by 91 valid questionnaires using partial least squares-structural equation modeling (PLS-SEM).

The results indicate that organizational support (OSU), organizational climate (OC) and mechanistic organizational structure (OST) positively influence intra-organizational diffusion of PC technology, which further positively influences organizational performance. The relationship between OC and intra-organizational diffusion of PC technology is mediated by OSU. Technological turbulence negatively moderates the relationship between OSU and intra-organizational diffusion.

This is the first paper to study the antecedents and consequence of intra-organizational diffusion of PC technology and an expansion of contingency theory in the research field of PC technology. This study helps to theoretically stimulate future research on intra-organizational diffusion and practically promote intra-organizational diffusion of PC technology along with improving organizational performance in its implementation.