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Entrepreneurship represents a complex decision-making process capable of influencing the conditions of a socio-economic system. For this reason, stimulating entrepreneurship is a topic that has always fascinated scholars and attracted the attention of public policy makers. This study, from the perspective of the theory of planned behaviour (TPB), aims to contribute to the analysis of entrepreneurial intention (EI) in university students. Factors such as entrepreneurship education (EE), mediation of personal attitude (PA), perceived behavioural control (PBC), EI, regulatory support (RS) and opportunity recognition (OR) for university students.

Research data was collected using a questionnaire, and a cross-sectional sample was selected from senior business and engineering students who are most likely to participate in entrepreneurial activities. The survey was conducted in the Delhi NCR region. 240 students were interviewed. Partial least square structural equation modelling using SmartPLS-4 was used to test the explanatory and predictive power of the proposed model.

The results of this study offer interesting contributions to the academic debate. First, EE has a significant impact on PA, PBC and entrepreneurial intentionality. Second, PBC, recognition of opportunities and EI have a significant impact on entrepreneurial education. Finally, PA and PBC significantly mediate the “entrepreneurial education – entrepreneurial intention” relationship.

Interesting elements of originality are offered by this study. First, entrepreneurship is studied as a decision-making process influenced by intentions and not behaviours. Second, the authors limited the efforts to unraveling the effect of the five variables on the formation of EI. Finally, the large size of the sample allows the authors to obtain significant results, directing future studies to other territorial contexts. Additionally, incorporating some control variables, such as gender and family background, would explore the relationship between the model variables more meaningfully.

As a little research has been conducted to understand the factors influencing users’ intentions to adopt blockchain-based telemedicine (BBT), it is important to investigate BBT acceptance as incorporation of blockchain technology can solve telemedicine-related issues. Accordingly, this study aims to investigate the factors influencing behavioral intentions (BI) to adopt BBT.

An integrated model comprising the constructs taken from technology–organization–environment framework, technology acceptance model, unified theory of acceptance and use of technology and theory of planned behavior based on their relevance to the context and the objectives of the study has been used for this research. A quantitative approach has been used to test the hypotheses, for which the data was collected from 324 respondents through a self-administered questionnaire. Partial least squares structural equation modeling has been used to test the hypotheses.

The results of the study show that relative advantage, perceived usefulness, trust and perceived ease of use have a significant impact on BI to adopt BBT, whereas regulatory support, subjective norms and facilitating conditions do not have any significant impact on the same.

As the concept of BCT in Pakistan is at its nascent stage and literature regarding this technology’s adoption is also limited, researchers and scholars can apply it to several other fields in Pakistan. For example, this study can be extended to explore the factors influencing blockchain adoption in areas such as education, logistics, transportation, finances and management. This research only considers the direct effects of constructs on BI to adopt BBT and does not consider any mediation and moderations constructs. Future researchers can also study the influence of mediation and moderation constructs on BI to adopt BCT.

Although studies on the acceptance of telemedicine exist, there is a gap concerning the acceptance of BBT, which the current study helps to bridge. From a practical standpoint, the current study makes a highly valuable contribution toward understanding acceptance factors for BBT projects, leading to help policymakers devise policies to promote telemedicine.

The purpose of this study is to investigate the factors affecting the intention to adopt blockchain technology (BT) in operations and supply chain and to explore the moderating role of sustainability-oriented supplier development on the effects studied.

The authors developed a conceptual framework based on the integration of technology-organization-environment (TOE) framework and diffusion of innovation (DOI) theory along with several strands of the literature in supply chain management and information systems. Drawing on survey data from 412 supply firms, a novel model using partial least squares structural equation modeling (PLS-SEM) was empirically tested in the context of the apparel industry of Bangladesh – the world's second-largest apparel supplier nation.

The findings supported the theoretical framework developed. In particular, the findings suggested that supplier firms' intention to adopt blockchain in supply chains is influenced by relative advantage, compatibility, perceived trust, top management considerations, absorptive capacity, information sharing and collaborative culture, and trading partners' influence. However, regulatory support is yet to play a significant role in blockchain adoption behaviour. The findings also suggest that supplier development for sustainability significantly moderates the relationship between the several drivers' (e.g. relative advantage, compatibility, top management considerations and trading partners' influence) effects on blockchain adoption.

The findings could help in developing an enabling environment for introducing blockchain-based apparel operations and supply chains.

The study contributes to and expands the embryonic research stream of sustainable supply chain management and BT. In particular, the paper provides neoteric evidence on how supplier development towards achieving sustainability moderates the effects of organizational, technological, and environmental drivers on the intention to adopt BT.

In recent years, technological advancement has played a crucial role in the growth of emerging economies. However, as with any novel technological development, there are often concerns and hesitations surrounding its implementation. This study aims to investigate the factors influencing blockchain adoption and usage. Thereby evaluating its impact on supply chain performance.

This is a deductive research based on the modified form unified theory of acceptance and use of technology, which is a persuasive model that has been used in numerous studies on the acceptance and usage of information technology systems. For this study, valid data was collected from 129 management-level supply chain professionals and policymakers working in diverse manufacturing industries. The collected data was used for testing hypotheses by deploying the structural equation modeling technique.

The findings of this study reveal that facilitating conditions and technology readiness highly are key influencers for organizations to implement this disruptive technology. Moreover, blockchain adoption and usage can significantly enhance supply chain performance.

Blockchain technology is a novel and promising disruptive technology that industries are looking forward to adopting and using. For the policymakers and supply chain strategists working in a developing country, this study offers a comprehensive viewpoint on the swift acceptance and usage of blockchain technology to facilitate supply chain operations.

The purpose of this paper is to investigate the determinants of cloud computing adoption (CCA) in a developing country context through the lens of the technology, organisation and environment (TOE) framework.

The study was carried out using the quantitative research methodology based on a survey of 305 organisations from different industries in Ghana. Based on the TOE framework, a conceptual model consisting of ten hypotheses were proposed and tested through a confirmatory factor analysis and logistic regression analysis.

The findings indicate that relative advantage, security concern, top management support, technology readiness, competitive pressure and trading partners’ pressure were the TOE factors found to be significant in CCA in a developing country context. Conversely, firm size, scope, compatibility and regulatory support were found to be insignificant.

This study provides insights into CCA across different industries in a developing country environment. The study is arguably the first kind of empirical research into CCA in a developing country context, specifically in Ghana. The findings from this study provide a foundation for other studies as well as constructive insights for the development of cloud computing, due to its infancy in the developing world.

Drawing on the technology-organization-environment (TOE) framework, this study aims to investigate determinants of performance of artificial intelligence (AI) adoption in hospitality industry during COVID-19 and identifies the relative importance of each determinant.

A two-stage approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) is used to analyze survey data from 290 managers in the hospitality industry.

The empirical results reveal that perceived AI risk, management support, innovativeness, competitive pressure and regulatory support significantly influence the performance of AI adoption. Additionally, the ANN results show that competitive pressure and management support are two of the strongest determinants.

This research offers guidelines for hospitality managers to enhance the performance of AI adoption and presents policy-making insights to promote and support organizations to benefit from the adoption of AI technology.

This study conceptualizes the performance of AI adoption from both process and firm levels and examines its determinants based on the TOE framework. By adopting an innovative approach combining PLS-SEM and ANN, the authors not only identify the essential performance determinants of AI adoption but also determine their relative importance.

Although prefabricated construction (PC) technology has attracted considerable attention worldwide because of its significant role in the global fight against COVID-19, market-driven adoption is still limited. The mechanisms for PC technology adoption have yet to be defined, which inhibits its diffusion in the construction market. This study aims to reveal the intrinsic motivation and action mechanism for PC technology adoption.

Drawing on the technology acceptance model (TAM), the study integrates characteristics from the diffusion of innovation theory to propose a multifaceted model for explaining practitioners’ PC technology adoption behavior from technology, organization and environment contexts. The proposed theoretical model was empirically examined via a survey of 234 professionals in mainland China using the partial least squares-structural equation modeling technique.

The outcomes indicated that relative advantage, corporate social responsibility and market demand are significantly positively related to practitioners’ perceived usefulness from PC technology. Regulatory support and trading partner support have noticeable positive effects on practitioners’ perceived ease of use from PC technology. Perceived ease of use is found to positively influence perceived usefulness, and both of them have a positive influence on the attitude toward adopting PC technology. Attitude is further confirmed as an important predictor of adoption intention, which would lead to actual PC technology adoption behavior.

To the best of the authors’ knowledge, this paper is the first attempt to explore industry perceptions toward PC technology adoption, providing valuable guidance for the effective diffusion of PC technology and laying a reliable foundation for research on other construction innovation adoption in post-COVID-19.

This study aims to blockchain facilitate information sharing among different players in the food industry, such as farmers, food suppliers and investors, enabling an effective decision-making process where the information about goods is traceable without any inherent risk. Although blockchain technology is emerging, its use in the food industry needs to be explored from different angles, such as organizations’ policy, adoption strategies and potential technology innovations which could positively impact business processes.

For this purpose, the authors survey 84 organizations in the food industry. Further, the authors conducted in-depth- interviews with three organizations that applied blockchain technology in the production phase to address the pros and cons of this adaption and discuss how the technology could be improved based on the challenges they faced. Moreover, an overview of current and potential digital transformation uses cases of blockchain technology in the food industry has been provided.

The results suggested that perceived efficiency, transparency, standardization and platform development and traceability factors positively influenced intention to use (ITU).

The adoption of the blockchain cloud solution is neither time-consuming nor expensive; organizations may attempt to predict how regulations or standards will be developed to create a blockchain solution compatible with them.

This study is among the primary studies investigating the role of blockchain technology in the food sector from the organizations’ viewpoint, highlighting the factors influencing the ITU.

Though Blockchain has been studied in numerous contexts, the understanding of the impacts of Blockchain in achieving competitive advantages remains unexplored. Many industries, organizations and firms are still in a “wait and see” mode. This study aims at examining the effects of the technological, organizational and environmental factors drawn from the TOE framework in generating competitive advantage.

A dual-staged deep learning structural equation modeling artificial neural network analysis was conducted on 211 samples of small and medium enterprises. Four neural network models were engaged to rank the normalized importance of each of the predictor variables.

The research model can expound 57.99 and 47.33% of the variance in Blockchain adoption and competitive advantage correspondingly. The study successfully identified nonlinear relationships. The theoretical and managerial contributions are useful to scholars and practitioners such as industrial players, investors, chief executive officers (CEOs), managers, decision-makers and other stakeholders that intend to use Blockchain technology.

Unlike the existing technological–organizational–environmental (TOE) framework that uses a linear model and theoretically assumes that all relationships are linear, this has been the first study, which has successfully validated that there exist nonlinear relationships in the TOE framework. Further, very little has been theorized on the impacts of Blockchain adoption on competitive advantage, especially in the context of SMEs. Therefore, this study is the first one to provide the necessary theoretical foundation that may further extend the current knowledge of Blockchain technology adoption and its impacts.

The purpose of this paper is to examine the determinants of cloud computing adoption in small and medium enterprises (SMEs), further, to measure the effect of cloud computing adoption on cloud-supported firm performance through enhancing organisational agility.

The research model is developed by combining two popular theoretical models, namely, the unified theory of acceptance and use of technology (UTAUT) and the technology–organisation–environment (TOE) framework. Data are collected from 372 SMEs to test the model. The strengths of widely used structural equation modelling (SEM) are applied to analyse the data.

This study reveals that the significant predictors of cloud computing adoption are performance expectancy; effort expectancy; absorptive capacity; data security and privacy; and perceived trust. Also, cloud computing adoption positively influences firm performance directly and through organisational agility. The results of importance–performance map analysis indicate that effort expectancy falls in the critical zone, which needs to be improved.

This research is one of few that blends the strengths of UTAUT and TOE framework. The research outcomes yield noteworthy suggestions to cloud providers, managers and government policymakers on ways of motivating the spread of cloud computing in developing countries.