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Deep learning (DL) is on the rise because it can make predictions and judgments based on data that is unseen. Blockchain technologies are being combined with DL frameworks in various industries to provide a safe and effective infrastructure. The review comprises literature that lists the most recent techniques used in the aforementioned application sectors. We examine the current research trends across several fields and evaluate the literature in terms of its advantages and disadvantages.

The integration of blockchain and DL has been explored in several application domains for the past five years (2018–2023). Our research is guided by five research questions, and based on these questions, we concentrate on key application domains such as the usage of Internet of Things (IoT) in several applications, healthcare and cryptocurrency price prediction. We have analyzed the main challenges and possibilities concerning blockchain technologies. We have discussed the methodologies used in the pertinent publications in these areas and contrasted the research trends during the previous five years. Additionally, we provide a comparison of the widely used blockchain frameworks that are used to create blockchain-based DL frameworks.

By responding to five research objectives, the study highlights and assesses the effectiveness of already published works using blockchain and DL. Our findings indicate that IoT applications, such as their use in smart cities and cars, healthcare and cryptocurrency, are the key areas of research. The primary focus of current research is the enhancement of existing systems, with data analysis, storage and sharing via decentralized systems being the main motivation for this integration. Amongst the various frameworks employed, Ethereum and Hyperledger are popular among researchers in the domain of IoT and healthcare, whereas Bitcoin is popular for research on cryptocurrency.

There is a lack of literature that summarizes the state-of-the-art methods incorporating blockchain and DL in popular domains such as healthcare, IoT and cryptocurrency price prediction. We analyze the existing research done in the past five years (2018–2023) to review the issues and emerging trends.

The purpose of this study is to investigate the role of blockchain technology in reducing online fraud among Gen Y and Gen Z.

This study uses a two-phase approach. Firstly, a systematic literature review is conducted to examine various aspects of blockchain technology and cyber security. Secondly, the Technology Adoption Model is used to study the adoption dynamics of blockchain-based platforms for online data exchange among 415 Gen Y and Z users.

The results indicate that efficiency and security, perceived ease of use, perceived usefulness, and trust have a positive effect on behavioral intention and attitude towards use. This is the first study to examine the role of blockchain technology to reduce fraud among Gen Y and Gen Z.

This study provides new insights into the adoption of blockchain-based platforms for online data exchange among Gen Y and Gen Z. The study highlights the critical areas of concern for the adoption of blockchain technology and provides managerial implications for fintech firms, banks, and e-commerce platforms. It is unique in its focus on the potential for blockchain technology to reduce fraud among Gen Y and Gen Z, which has not been previously explored in the literature.

Technology is the lifeline for the logistics industry, and it has been immensely disrupted by the emerging blockchain technology. This paper has two main objectives. The first is to explore how the current blockchain technology can be implemented in the logistics industry with the aim of improving logistic services amongst the network of logistics service providers (LSPs). The second is to propose the development of a blockchain model for the small and medium logistics service supply chain.

A prototype blockchain-based logistics system has been created and tested in a case study with a real logistics company. The primary technologies for developing a blockchain model on the Hyperledger platform as well as how the system is designed based on the logistics service flow are explained.

The study has resulted in the successful implementation of the proposed prototype blockchain-based logistics system. In particular, the case company has managed to fully utilise the developed tracking and tracing system. Whilst utilising the prototype, the participants have been able to fulfil their responsibilities in an effective manner. The performance of LSPs has improved following the World Bank Logistics Performance Index (LPI) criteria.

This paper contributes to current research in the application of blockchain technologies in the domain of logistics and the supply chain to progress LSPs towards Logistics 4.0. The current frameworks for Logistics 4.0 and how blockchain as a disruptive technology revolutionises logistic services are reviewed. In addition, this paper highlights the benefits of blockchain technology that LSPs can leverage to further improve their performance based on the LPI criteria.

Blockchain technology can potentially address the challenges of information storage, sharing and management and improve them further in an organization and sector as a whole. This study aims to investigate the effects of technology, organization and environment on the behavioral intention of employees to adopt blockchain in the Indian insurance sector and the mediating role of knowledge management practices.

A structured questionnaire was used to collect a sample size of 390 responses based on convenience sampling. Partial least square structural equation modeling was used to analyze the data.

The findings highlighted that organizational factors, followed by technological factors, significantly impact employees' behavioral intentions. The results established that the impact of environmental factors is insignificant on blockchain adoption intention. Knowledge management practices significantly mediate the relationship between organizational factors, technological factors and behavioral intention.

The results indicate that organizations must prioritize organizational factors (technological competence, top management support and financial readiness) and knowledge management practices (knowledge creation, sharing and retention) to positively impact employees' behavioral intentions and ensure successful and effective technology adoption.

Using the Technology-Organization-Environment framework, the study tests the conceptual model, showing the relationship between technological, organizational and environmental factors, behavioral intention and knowledge management practices. The role of knowledge management practices in technology adoption within organizations has been scarcely explored. This study adds significant and novel contributions in this area.

This study aims to comprehensively inspect the impact of blockchain technology in the context of globalization, focusing on the most influential research works, scientific production by countries, commonly used keywords, trending topics and the conceptual and intellectual structure of this field.

A bibliometric analysis was conducted in R Studio, involving the review and scrutiny of 194 research papers indexed in the Scopus database. This analytical approach allowed for a systematic examination of the literature and the identification of key patterns and trends in blockchain and globalization research.

The analysis revealed the most influential research contributions, highlighted countries with significant scientific production, identified frequently used keywords and unveiled emerging trends and areas of focus in the field of blockchain and digitization. Additionally, the study explores prospective research directions.

This research provides insights into the current state of blockchain and globalization research, offering valuable information for scholars, policymakers and industry professionals. The recognized themes provide a systematic structure for upcoming inquiries, directing studies toward vital domains like supply chain management and sustainable development. Moreover, the analysis emphasizes the significance of interdisciplinary collaboration and provides practical insights, enabling businesses and policymakers to enhance transparency, counteract fraud and adjust to the digital era for societal and economic advancement.

The study contributes to the prevailing literature by steering a comprehensive analysis of the interplay between blockchain technology and globalization, shedding light on influential works and emerging trends. It adds value by providing a structured overview of the field's intellectual landscape.

To address the absence of Lean in transportation logistics in the digital era, this study aims to investigate the application of Lean transportation (LT) tools to reduce waste and facilitate the digital transformation of dedicated road transportation in the offshore industry.

The study adopts action research with a multimethod approach, including a scoping review, focus groups (FG) and participant observation. The research is conducted within the offshore supply chain of a major oil and gas company.

Implementing LT’s continuous improvement tools, particularly value stream mapping (VSM), reduces offshore transportation waste and provides empirical evidence about the intersection of Lean and digital technologies. Applying techniques drawn from organisational learning theory (OLT), stakeholders involved in VSM mapping and FGs engage in problem-solving and develop action plans, driving digital transformation. Waste reduction in loading and unloading stages leads to control actions, automation and process improvements, significantly reducing downtime. This results in an annual monetary gain of US$1.3m. The study also identifies waste related to human effort and underutilised digital resources.

This study contributes to theory and practice by using action research and LT techniques in a real intervention case. From the lens of OLT, it highlights the potential of LT tools for digital transformation and demonstrates the convergence of waste reduction through Lean and Industry 4.0 technologies in the offshore supply chain. Practical outputs, including a benchmarking questionnaire and a plan-do-check-act cycle, are provided for other companies in the same industry segment.

This study presents a systematic framework for maintenance strategy development of manufacturing process machinery. The framework is developed based on the reliability-centred maintenance (RCM) approach to minimise the high downtime of a production line, thus increasing its reliability and availability. A case study of a production line from the ghee and soap manufacturing industry in Taiz, Yemen, is presented for framework validation purposes. The framework provides a systematic process to identify the critical system(s) and guide further investigation for functional significant items (FSIs) based on quantitative and qualitative analyses before recommending appropriate maintenance strategies and specific tasks.

The proposed framework integrates conventional RCM procedure with the fuzzy computational process to improve FSIs criticality estimation, which is the main part of failure mode effect criticality analysis (FMECA) applications. The framework consists of four main implementation stages: identification of the critical system(s), technical analysis, Fuzzy-FMECA application for FSIs criticality estimation and maintenance strategy selection. Each stage has its objective(s) and related scientific techniques that are applied to systematically guide the framework implementation.

The proposed framework validation is summarised as follows. The first stage results demonstrate that the seaming system (top and bottom systems) caused 50% of the total production line downtime, indicating it is a critical system that requires further analysis. The outcomes of the second stage provide significant technical information on the subject (seaming system), helping team members to identify and understand the structure and functional complexities of the seaming system. This stage also provides a better understanding of how the seaming system functions and how it can fail. In stage 3, the application of FMECA with the fuzzy computation integration process presents a systematic way to analyse the failure mode, effect and cause of items (components of the seaming system). This stage also includes items’ criticality estimation and ranking assessment. Finally, stage four guides team members in recommending the appropriate countermeasures (maintenance strategies and task selection) based on their priority level.

This paper proposes an original maintenance strategies development framework based on the RCM approach for production system equipment. Specifically, it considers a fuzzy computational process based on the Gaussian function in the third stage of the proposed framework. Adopting the fuzzy computational process improves the risk priority number (RPN) estimation, resulting in better criticality ranking determination. Another significant contribution is introducing an extended item criticality ranking assessment process to provide maximum levels of criticality item ranking. Finally, the proposed RCM framework also provides detailed guidance on maintenance strategy selection based on criticality levels, unique functionality and failure characteristics of each FSI.

The prevention of mental health issues at work represents a significant challenge for organizations. The transformation of workplaces whose future promises to be virtual or hybrid can make the anticipation and prevention of these health issues more challenging, considering the potential distance that it may create between employees and their employers. The recent health crisis undermined individual mental health but also highlighted the importance of new technologies which greatly paved the way for the future of workplaces. This paper aims to examine these new technologies, specifically the use of blockchain technologies in organizations to predict and prevent mental health issues at work, specifically psychological distress, in times of crisis, and beyond. It addresses the main challenges and opportunities and presents research avenues as well as insights for human resource management (HRM) practitioners.

This paper is a viewpoint that addresses the use of blockchain technology in the prevention of employees’ mental health at work in times of crisis and beyond. Literature was used to support this viewpoint and highlight the importance of addressing mental health issues at work and preventing their occurrence in the future.

Blockchain is one of the disruptive new technologies that can be used as a strategic tool for organizations to prevent mental health issues among employees in the workplace in times of crisis, and beyond. It facilitates the collaboration between employees, their organization, healthcare and employee assistance program (EPA) providers, as well as insurance companies. In this context, a specific type of blockchain should be used to support this type of collaboration.

Blockchain can generate both opportunities and challenges for the prevention of mental issues at work. It can transform the future of workplaces and help organizations as well as healthcare and EPA providers to anticipate potential employees’ mental health issues in 2019. Organizations need to address their readiness to implement this new technology and the possible reluctance of their employees to use it. This paper presents insights for managers and HRM practitioners.

The studies that have addressed the use of blockchain in organizations to prevent employees’ mental health issues are sparse. This paper is an attempt to address this gap and examine the challenges as well as the opportunities associated with the use of this disruptive new technology that can significantly reshape the future of workplaces.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.

In today’s business world, adopting social commerce for day-to-day operations has increasingly become an important phenomenon. Several factors have been identified by previous researchers regarding the adoption of social commerce, but academic research is scarce on the relationship between the factors influencing social commerce adoption and small and medium-sized enterprises (SMEs) in the post-COVID-19 situation. This study aims to identify the impact of technological, environmental and entrepreneurial factors on the adoption of social commerce by SMEs in Sri Lanka.

A quantitative study utilised the deductive approach and collected data through a field survey by distributing a five-point Likert scale questionnaire to conveniently selected respondents from Sri Lankan SMEs. Structural equation modelling (SEM) was used for the analysis of 384 responses.

The results revealed that technological factors [technology availability (TA) and cost-effectiveness (CE)], environmental factors [bandwagon effect (BE)] and entrepreneurial factors [attitude (AT), innovativeness (IN) and IT knowledge (IK)] have a significant impact on the social commerce adoption of SMEs in Sri Lanka. This study, as the first of its type, offers insightful information on the influence of variables on the adoption of social commerce after the COVID-19 pandemic.

Similar to any research, this study also has inherent limitations. Due to time and financial restrictions, the study’s convenience sampling method was adopted. The study’s possible limitation is its narrow focus, which could mean that it only examines a select few social media (SM) networks. The study’s conclusions might be less generalised since it focused on the western province of Sri Lanka. Future studies should take a cross-cultural strategy to explore the influence of social commerce adoption to improve the generalisability of research findings.

This study provides an in-depth assessment of critical factors, facilitating policymakers, owners, leaders and managers (decision-makers) to gain insight into the real influencing factors on social commerce adoption and the significance of SM. The study helps them comprehend how outstanding governance and knowledge of influencing factors can boost SME success in various ways. For example, research reveals that various factors have a major influence on social commerce adoption.

There has been limited research conducted on social commerce adoption after the COVID-19 pandemic period; thus, this study looked at the variables influencing it amongst SMEs in a South Asian developing country like Sri Lanka after the pandemic lasted for two years. By placing a strong emphasis on the role of entrepreneurial characteristics and the available technology within one single framework in the context of SMEs and their involvement with social commerce adoption, this study contributes to the past literature by emphasising the role of several significant factors in SMEs' adoption of social commerce. Whilst previous studies looked at multiple factors influencing the adoption of social commerce globally, this study focussed on how these factors have a significant impact on SMEs in Sri Lanka.

This study developed a multi-perspective framework combining technological, environmental and entrepreneurial factors influencing SMEs to adopt social commerce. The study provides a contribution to the literature on social commerce adoption from the perspective of SMEs in a developing country like Sri Lanka after COVID-19. Exclusively, it examines the impact of entrepreneur-related factors on social commerce adoption.