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The new technology aspects of Industry 4.0 (I4.0), such as digital technologies including artificial intelligence (AI), block chain, big data analysis and the internet of things (IoT) as a digital cosmos, have the potential to fundamentally transform the future of business and supply chain management. By augmenting the functional components of the food supply chain (FSC), these technologies can transform it into an intelligent food supply chain (iFSC). The purpose of this study is to identify the I4.0 utilization for FSC to become an iFSC. Additionally, it suggests future research agendas to bridge the academic knowledge gaps.

This study utilizes the bibliometric analysis methodology to investigate the techno-functional components of iFSC in the context of I4.0. The study followed steps of bibliometric analysis to assess existing components’ knowledge in the area of intelligent food supply chain management. It further reviews the selected articles to explore the need for I4.0 technologies’ adoption as well as its barriers and challenges for iFSC.

This study examines the integration of emerging technologies in FSC and concludes that the main emphasis is on the adoption of blockchain and internet of things technology. To convert it into iFSC, it should be integrated with I4.0 and AI-driven FSC systems. In addition to traditional responsibilities, emerging technologies are acknowledged that are relatively uncommon but possess significant potential for implementation in FSC. This study further outlines the challenges and barriers to the adoption of new technologies and presents a comprehensive research plan or collection of topics for future investigations on the transition from FSC to iFSC. Utilizing artificial intelligence techniques to enhance performance, decision-making, risk evaluation, real-time safety, and quality analysis, and prioritizing the elimination of barriers for new technologies.

The uniqueness of this study lies in the provision of an up-to-date review of the food supply chain. In doing so, the authors have expanded the current knowledge base on the utilization of all I4.0 technologies in FSC. The review of designated publications yield a distinctive contribution by highlighting hurdles and challenges for iFSC. This information is valuable for operations managers and policymakers to consider.

This study aims to examine the transaction costs (TCs) involved in searching for a business case to adopt specific walling innovations by housing developers and the influence of these TCs on their adoption outcomes. This is against the backdrop that innovation adoption, like any new venture, is failure-prone but necessary for countries to reap the full benefits of technological innovation in residential developments, especially when these innovations are also green. Moreover, this issue is understudied.

The study uses a qualitative design and focuses on the early adopting developers in Ghana. The original theoretical framework integrates theories on entrepreneurial opportunity discovery and TC economics. The authors interviewed 12 developers and 13 industry stakeholders purposively identified. The authors analysed and triangulated the resulting transcripts using thematic analysis techniques.

The authors identified two types of early adopters who attempted eight types of walling innovations. Most efforts (71%) were partially successful or failed. The range of TCs identified differed by the adopter type, technology and knowledge coordination strategy. Although the common TCs that were consequential were associated with monitoring and supervision, construction, additional learning, acquiring specialised skills, design change and dispute resolutions, their influence on adoption outcomes is very nuanced.

To the best of the authors’ knowledge, this paper is among the first to link TCs with innovation adoption outcomes by housing developers in discovering profitable opportunities to adopt specific walling innovations. The findings and theoretical framework lay a foundation for in-depth analyses of the entrepreneurship of innovation adoption in residential real estate. The exploratory work will generate further interest in this area.

The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners.

Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses.

The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners’ intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners’ intentions to use IoT.

These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners’ intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field.

This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector.

Milk is a perishable food product, one of the primary sources of nutrition. Reports worldwide indicate numerous food frauds and foodborne diseases associated with adulterated milk products. These safety concerns highlight the importance of a visible milk supply chain, which can be achieved by cutting-edge technologies. However, these technologies come with high costs. So, this study aims to propose a framework that integrates blockchain, Internet of Things (IoT) and cloud to enhance visibility with reduced cost in an Australian milk supply chain (AMSC).

A design science research methodology is used, where a proof of concept is also developed at the retailer end to show how blockchain, IoT and cloud can improve visibility with reduced cost in an AMSC.

According to cost and visibility analysis, blockchain implementation in AMSC would generate a high return on investment (ROI). For the given case, ROI becomes positive for all stakeholders after 750 cycles. Integrating IoT, cloud and blockchain is more profitable than just using blockchain. Additionally, technology implementation may not benefit all stakeholders equally. For example, the retailer needs 10 cycles to benefit, but the transporter needs 50 in the given case.

The findings of this study assist milk industries in decision-making regarding technology implementation in their supply chain and motivate them to implement these technologies, resulting in improved trust and coordination among entities and consumers.

A cost and visibility analysis are performed to evaluate the impact of technology implementation on cost and visibility in an AMSC. A SOAR (Strength Opportunities Aspiration Results) analysis is also performed for the strategic planning framework.

Using AI to strengthen creativity and problem-solving capabilities of professionals involved in innovation management holds huge potential for improving organizational decision-making. However, there is a lack of research on the use of AI technologies by innovation managers. The study uses the theory of appropriation to explore how specific factors – agile leadership (AL), innovation orientation (IO) and individual creativity (IC) – impact innovation managers' use of generative AI tools, such as ChatGPT (CGA).

The research model is tested through a large-scale survey of 222 Italian innovation managers. Data have been analyzed using structural equation modeling following a two-step approach. First, the measurement model was assessed to ensure the constructs reliability. Subsequently, the structural model was analyzed to draw the conclusions on theorized model relationships and their statistical significance.

The research findings reveal positive associations between IO and IC with CGA, demonstrating that innovation managers who exhibit strong innovation orientations and higher Individual Creativity are more likely to adopt and personalize ChatGPT. However, the study did not confirm a significant association between AL and CGA.

Our findings have important implications for organizations seeking to maximize the potential of generative AI in innovation management. Understanding the factors that drive the adoption and customization of generative AI tools can inform strategies for better integration into the innovation process, thereby leading to enhanced innovation outcomes and improved decision-making processes.

This study synthesises the self-determination theory (SDT), expectation-confirmation model (ECM), and protection motivation theory (PMT) to formulate an integrated theoretical framework that elucidates the process of shaping the intention to continue using facial recognition payment (FRP) under the conditional impact of perceived technology security.

Data from 667 Beijing Winter Olympics visitors with FRP experience were collected through an online survey and analysed using variance based-structural equation modelling (VB-SEM).

This study reveals that the intention to continue using FRP evolves through three key stages. Initially, in the expectation stage, the multidimensional concept of artificial autonomy (sensing, thought, and action), which is underpinned by self-determination, is pivotal, strongly influencing perceptions of service enhancement and fostering trust in FRP. Subsequently, the confirmation stage underscores the importance of perceived service enhancement and trust as vital drivers in maintaining FRP usage, while also contributing to subjective well-being. Crucially, perceived technology security emerges as a key moderating factor, enhancing positive perceptions and intentions towards FRP, thus influencing its sustained adoption.

This study stands out by revealing the nuanced interplay between artificial autonomy and user perceptions, particularly concerning service enhancement, technology security, and trust, as they influence well-being and the continued adoption of FRP. Robustly grounded in the integrated theoretical framework of SDT, ECM, and PMT, the study’s findings are critical for comprehending the core elements and specific drivers that promote sustained FRP use, especially as we consider its potential widespread implementation. Therefore, this study not only advances theoretical understanding but also offers practical guidance for optimising FRP deployment strategies in a rapidly evolving technological landscape.

The rapid global use of Financial Technology (FinTech), an innovative and advanced technology, is leading to the replacement of traditional financial services. Despite this, consumers in the United Arab Emirates are still not accepting FinTech services as anticipated. This study aims to investigate the barriers preventing consumers from using FinTech services in the banking industry based on the technology-organisation-environment (TOE) framework and anchored by the unified theory of acceptance and use of technology (UTAUT).

The current study used an exploratory sequential mixed-method design. A purposive sample was used to conduct preliminary semi-structured interviews with ten banking practitioners. These interviews aimed to explore the obstacles that hinder consumers from adopting FinTech services. To provide further empirical validation, the conceptual model has been systematically examined through a quantitative cross-sectional online survey encompassing a sample of 332 bank customers.

The qualitative investigation highlighted six new barriers to the usage of FinTech based on TOE’s model attributes. Through quantitative data analysis, the preliminary qualitative findings were primarily verified. It was discovered that self-efficacy, electronic word-of-mouth, system quality and bank image substantially influence consumers to use FinTech services, in addition to performance expectancy and facilitating conditions. Meanwhile, IT features and governmental support were found to have insignificant effects. Yet, government support was found to have a positive moderating role in strengthening social influence and system quality towards customer use of FinTech. Thus, the research supports the UTAUT and TOE models’ fitness for explaining FinTech usage with high predictive relevance.

This study is the authors’ pioneering effort to propose a comprehensive research framework that integrates the UTAUT and TOE models to tackle the limited adoption of FinTech services among consumers. Moreover, the study specifically examined the moderating influence of government support to propose an integrated model. Remarkably, this study is one of the initial attempts to investigate the adoption of FinTech using a mixed-methodology approach by incorporating quantitative and qualitative methods within a single inquiry to yield more comprehensive and insightful findings than research that relies on a single method.

This article aims to extend the Unified Theory of Acceptance and Use of Technology (UTAUT) model to understand the factors affecting the usage behavior of Blockchain from accountants' and auditors’ perspectives and its impact on their performance.

A quantitative research approach employing a web-based questionnaire was applied, and the empirical data were gathered from 329 potential and current users of Blockchain in the accounting and auditing profession in Jordan. The analytical model was based on structural equation modeling (SEM) using AMOS 25.0.

The experimental findings of the structural path confirmed that performance expectancy (PE), social influence (SI), Blockchain transparency (BT) and Blockchain efficiency (BE) were significantly affecting individuals’ behavioral intention (BI) toward the use of Blockchain-based systems and helped to explain (0.67) of its variance. Also, BE has a positive significant impact on PE. Whereas, in contrast to what is anticipated, the influence of effort expectancy (EE) on BI was not supported. Additionally, users’ intentions were found to affect the actual usage (AU) behavior and helped to explain (0.69) of its variance. The outcome variables proposed in this study: knowledge acquisition (KACQ) and user satisfaction (USAT) were significantly influenced by the AU of Blockchain technology.

This study outlines practical implications for government, policymakers, business leaders and Blockchain service providers aiming to exploit the advantages of Blockchain technology (BCT) in the accounting and auditing context.

To the best of the authors’ knowledge, this article is one of the few studies that offer an evidence-based perspective to the discussions on the effect of disruptive and automated information and communication technologies (ICTs), on the accounting and auditing profession. It applies an innovative approach to analysis through the integration of UTAUT, contextual factors: BT and BE, besides two outcome factors: KACQ and USAT within its theoretical model. This study extends and complements the academic literature on information technology/information systems acceptance and use by providing novel insights into accountants' and auditors’ views.

The purpose of this study is to investigate the antecedents of metaverse adoption intention amongst Muslim students by expanding the technology acceptance model (TAM) to incorporate factors viz. perceived cyber risk (PCR), perceived enjoyment (PE), personal innovativeness in IT (PIT), self-efficacy (SE), trust (TR) and religiosity (RL).

An online survey was circulated using a Google questionnaire to gather information on the study constructs. Purposive and snowball sampling techniques were adopted to reach the targeted students. The proposed associations were examined through the application of structural equation modelling with the use of AMOS software.

The findings suggest that the empirical results derived from the study present a compelling and effective model, and the model is designed to elucidate the intentions of Indian Muslim students regarding their willingness to embrace or adopt the metaverse. The research has identified and showcased a robust conceptual framework that provides insights into the factors influencing the metaverse adoption intentions among Muslim students.

This research adds value to the existing literature by expanding the understanding of metaverse adoption amongst Muslim students. This thorough framework offers an intricate comprehension of metaverse adoption, offering a theoretical framework beyond traditional technological determinants. This study provides important insights that can assist educationists, administrators and policymakers in various ways in chalking out essential strategies, policies and programmes related to metaverse adoption amongst Muslim students.

This study is unique as the six additional constructs, viz. PCR, PE, PIT, SE, TR and RL, are included in the original TAM model, thus filling the literature gap. It also augments the comprehension of the metaverse and unfolds the antecedents of metaverse adoption intention amongst Muslim societies through the lens of students.

The study aims to identify a model of commercializing entrepreneurial ideas in information and communication technology (ICT) knowledge-based companies.

A mixed method has been used in the research. The participants of the qualitative part were 15 key informants selected by sampling method purposefully and theoretically, while a sample of 205 experts was randomly chosen for the quantitative part. Data collection was completed through a semistructured interview in the qualitative part and by a researcher-made questionnaire in the quantitative part. The reliability of the research was confirmed by Cronbach’s alpha. The validity of the qualitative and quantitative parts was approved, respectively, by the criteria of Corbin and Strauss (2008) and by the content validity. Data analysis was done in the qualitative part through open, axial and selective coding, while in the quantitative part through partial least squares structural equation modeling (PLS-SEM) and adaptive neuro-fuzzy inference systems (ANFIS).

The commercialization model of ICT entrepreneurial ideas was depicted by the paradigmatic version of Corbin and Strauss (2008). The model has been consisted of six sectors as follows: causal conditions (including stimuli of science and technology parks, interests and motivation of managers of ICT knowledge-based company and environmental stimuli), contextual conditions (including skills and abilities of managers of ICT knowledge-based company, status of ICT knowledge-based company and enabling and facilitating legal framework), intervening conditions (including the complex nature of the ICT industry, science and technology parks’ support of companies, facilities and equipment for commercialization of ICT entrepreneurial ideas and economic system stability), strategies (including marketing research, planning and feasibility study of ICT entrepreneurial idea, design and production of ICT product and release and supply of ICT product), consequences (successful commercialization of ICT entrepreneurial ideas in the post-COVID-19 era) and the central phenomenon (ICT entrepreneurial ideas: commercialization in the post-COVID-19 era). Then, the main factors were confirmed through PLS-SEM and ANFIS. Among the factors, interests and motivation of managers of ICT knowledge-based companies, status of ICT knowledge-based companies, facilities and equipment for commercialization of ICT entrepreneurial ideas and release and supply of ICT products were identified as the most influential factors.

The model can help solve the challenges of managers and policymakers to commercialize ICT entrepreneurial ideas. Therefore, innovative production will increase, value will be created for the beneficiaries and economic, social and political growth will occur in the post-Corona era.

Commercialization of ICT entrepreneurial ideas has the potential to affect many aspects of economic and societal activities in the society such as GDP growth, employment, productivity, poverty alleviation, quality of life and education.

The research includes innovation in presenting a multidimensional commercialization model based on an entrepreneurial perspective in the special field of ICT with a mixed approach including grounded theory, PLS-SEM and ANFIS in ICT knowledge-based companies. But the most important innovation of the study is related to the findings. The main categories, subcategories and concepts of the research have been presented in the form of a theory entitled “ICT entrepreneurial ideas: commercialization in the post-COVID-19 era.”