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This study examines the factorial structure of salient user beliefs associated with smart locks. We also examine the predictive value of the identified constructs on the smart lock adoption intention and we evaluate gender differences in the predictive value of the identified constructs.

The study assumes pragmatic epistemological stance and it leverages mixed-methods research design. The research progresses through three stages: belief elicitation, exploratory factor analysis and confirmatory factor analysis within a nomological network. New groups of participants were recruited for each stage of the study.

We find that while potential adopters express a broad range of perceived benefits and concerns associated with smart locks, only the perceived relative advantage of smart locks vis-à-vis conventional locks in providing safety and security is significantly correlated with adoption intention for both genders. We also find that perceived novel benefits are a significant predictor of the smart lock adoption intention for women, but not for men.

Our results indicate that perceived relative advantage can be the singular critical consideration in the adoption of smart home technologies that replace incumbent solutions. The results also demonstrate that gender-specific models can better capture gender effects that influence technology adoption and use.

Smart home technology vendors would need to convince prospective users that new technology is better than the incumbent solutions on the core affordances of the incumbent technology. Men and women differ in the consideration of novel benefits afforded by novel technologies.

This is among the first studies to examine salient beliefs that affect smart home technology adoption. The findings suggest that the traditional models (TAM, UTAUT) do not capture the key salient beliefs that can influence innovative smart home technology adoption. The study also suggests that gendered models are needed to understand technology adoption in contexts where technology adoption intersects with gender roles.

This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.

The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.

Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.

A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.

The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.

Cloud computing (CC) services have given a tremendous boost to the creation of efficient and effective solutions. With developing countries at a slow pace of adoption, this research aims to identify factors and their interrelationships influencing the adoption of CC in a developing country context. The developing countries are enjoying numerous benefits from CC services; however, its low adoption is still a question in developing economies; hence, the authors have selected the context of information and communication technology (ICT) firms in India.

The qualitative research method is used where experts from thirteen ICT firms in India are interviewed.

Sixteen factors, twenty-eight subfactors, and 25 interrelationships are revealed through content analysis. Further, causal loop diagrams are proposed to display the behavior of cause and effect of these factors from a system's perspective. This will help to understand the relationships among the factors in order to enhance the speed of CC adoption. Possible financial loss and resistance to change are found as the key barriers to adoption. The proposed interrelationships can guide both policymakers and service providers for designing effective CC policies.

This is the first scholarly work that identifies interrelationships among factors and subfactors, thereby providing a holistic picture to decision-makers while making a choice on whether to adopt cloud services or continue with on premise data centers and servers.

This study aims to investigate the factors influencing the adoption of online pharmacies in Qatar using the unified theory of acceptance and use of technology-2 (UTAUT-2) framework. Specifically, this study examines the impact of performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness of behavioral intention, which in turn affects the adoption of online pharmacies. Furthermore, this study explores the moderating role of word-of-mouth (WOM) recommendations on the relationship between behavioral intention and online pharmacy adaptation.

This study adopted a descriptive, quantitative approach to investigate the UTAUT-2 model in the context of consumers’ adoption of e-pharmacy in Qatar. Through convenience sampling, 455 responses were collected from regular customers accessing online pharmacy services. The data were analyzed using Smart-PLS 3.2 software to examine the hypothesized relationships.

The results showed that WOM recommendations significantly enhanced the relationship between behavioral intention and adopting online pharmacies in Qatar. This study identified the factors that may hinder or enable the adoption of online pharmacies, including performance expectancy, effort expectancy, social influence, hedonic motivation, habit, technology trust, perceived risk and users’ level of awareness.

This study contributes to the existing literature on technology acceptance by extending the UTAUT-2 model and recognizing three additional variables (perceived risk, technology trust and technology awareness). These need to be investigated against UTAUT-2 variables to detect the significance of their impact on adapting the e-health concept in Qatar. The potential for cultural change to accelerate the adoption of online pharmacies is highlighted. Future research should explore the role of moral and cultural factors in technology adoption.

The results underscore the economic and social significance of e-pharmacy adoption, particularly within the context of a developing country. Considering the positive intentions expressed by individuals toward e-pharmacy, it becomes crucial for managers and decision-makers to make strategic choices to address any challenges that may arise. Policymakers are encouraged to enhance their services and implement various development initiatives to expand e-pharmacy accessibility and availability.

This study builds upon previous research on e-commerce in the pharmaceutical industry and provides a comprehensive understanding of customers in developing countries. Extending the UTAUT-2 model and identifying additional variables contributes to the knowledge of e-health concepts in Qatar. The findings have practical implications for developing strategies to promote online pharmacy adoption in Qatar and other countries.

This study aims to identify the driving factors that influence blockchain technology adoption in the context of a supply chain (SC), considering three dimensions: technology, transactions and collaboration.

An integrative systematic literature review of previous studies was conducted. Using three main dimensions: technology, transactions and SC collaboration, supported by the unified theory of acceptance and use of technology, transaction cost economics (TCE) and concepts of SC collaboration, the authors categorized factors that contributed to blockchain technology in SC in the extant literature and proposed a theoretical model that covers these three dimensions.

The findings reveal that the information sharing category – related to the SC collaboration dimension – is the category with the greatest number of motivating factors for blockchain adoption in the SC context, followed by performance expectancy and behavioral uncertainty.

The review considers papers published until 2021 obtained from a specific database.

This study focuses on filling the research gap concerning technology adoption as it considers the interconnection formed by two organizations, interorganizational transactions and SC collaboration, using complementary theories to explain the phenomenon.

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 evaluate the role of personality in digital library systems (DLS) adoption intention among Generation Z (Gen-Z) students. The study uses the unified theory of acceptance and use of technology-2 and the five-factor model to investigate personality’s influence on Gen-Z’s DLS adoption intention.

The study is a descriptive causal investigation based on primary data collected through a self-administered survey using pre-validated tools. The study uses structural equation modeling to investigate personality dimensions’ direct and moderating effect on the dependent, independent variables and their relation.

The study results indicate that personality has no significant influence on Gen-Z’s DLS adoption, suggesting the ubiquity and inevitability of technology in current times. Also, only performance expectancy had a considerable impact on DLS adoption among Gen-Z going to college – a deviation from past studies where multiple independent variables have influenced DLS adoption when examined from different technology adoption model angles.

The current research is done on Gen-Z, and thus the results are ideographic to the cohort.

The results of the study can be used to effectively design and communicate technology-enabled information solutions among the Cohort.

The results of the study help better understand the factors affecting the technology adoption intentions of Gen-Z. Such understanding can help in better design and implementation of technology-enabled solutions for the cohort, maximizing such system adoption and its effective and efficient utilization.

The study explores the impact of personality on DLS adoption intentions, hitherto unexplored. The research also focuses on Gen-Z – a cohort born in a technology-enabled world whose attitude and preferences towards technology might differ. The study’s findings will help understand the influence of personality on DLS adoption among the Gen-Z and can be used to design, promote and evaluate such systems.

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.

The present study aims to understand small retailers' current use of various low-cost technologies and the factors responsible for small retailers' adoption. Furthermore, these factors of adoption were mapped back to beliefs within the theory of planned behaviour (TPB), and an attempt was made to understand if some of the beliefs dominated over the others and their implications.

The study takes a qualitative approach comprising in-depth semi-structured interviews and direct observation. The qualitative data were analysed through a thematic analysis to identify technology adoption factors.

Amongst the various technologies (mobile apps), payment and procurement apps were the most widely used. The authors identified eight factors influencing technology adoption: the top being customer demand for payment apps and convenience and cost-saving for procurement apps. The study also highlights the role of the dominant beliefs in technology adoption, which managers could use to improve adoption rates.

The current study is a cross-sectional study and the sample was predominantly of grocery retailers, limiting the generalisability of the results.

Small retailers face stiff competition from organised retail and e-commerce platforms which threatens small retailers' existence. Small retailers' survival is vital as many people depend on the small retail sector for livelihood. Increased use of technology seems the only way for them to stay competitive and increase profitability. The study's outcome could help increase technology adoption amongst small retailers and increase small retailers' competitiveness.

Despite the widespread presence of small retailers in emerging economies, few studies have examined technology adoption amongst them. This study is also the first to use the TPB theory in the small retailer technology adoption context.

Existing literature suggests that construction worker safety could be optimized using emerging technologies. However, the application of safety technologies in the construction industry is limited. One reason for the constrained adoption of safety technologies is the lack of empirical information for mitigating the risk of a failed adoption. The purpose of this paper is to fill the research gap through identifying key factors that predict successful adoption of safety technologies.

In total, 26 key technology adoption predictors were identified and classified using a combination of literature review and an expert panel. The level of influence for each identified safety technology adoption predictor was assessed and ranked using the Relative Importance Index. Analysis of variance was performed as well to assess the potential difference in perceived level of importance for the predictors when the study participants were clustered according to work experience and company size.

Statistical analysis indicates that 12 out of the 26 predictors identified are highly influential regarding technology adoption decision-making in construction. Technology reliability, effectiveness and durability were ranked as the most influential predictors. The participants who work for small companies and who had less than ten years of experience rated individual- and technology-related predictors significantly lower than the experienced participants working for medium and large companies.

The present study provides construction researchers and practitioners with valuable information regarding safety technology predictors and their magnitude, both of which are essential elements of a successful safety technology adoption process. Improved technology adoption can enhance workplace safety and minimize worker injuries, providing substantial benefits to the construction industry.

This study contributes to technology adoption knowledge by identifying and quantifying the influential predictors of safety technologies in relation to different organizational contexts. The study informs the need to develop an integrated conceptual model for safety technology adoption.