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Blockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships.

A three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score.

The findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group.

The outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains.

The research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.

This study aims to investigate causes of sustainability failures of ISO 9001 Quality Management Systems in Botswana.

The research employed qualitative and quantitative methods, including literature review and secondary data analysis to understand trends relating to Botswana, and a survey to identify gaps leading to certification sustainability failures, focusing on; motives for certification, causes of decertification and issues in the certification process.

ISO 9001 adoption in Botswana is slow, with low acceptance rate in the public sector at 13% compared to the private sector at 87%. Termination rates have been high at 55% over two decades. Manufacturing dominates certification with 45% of total certification. While micro and small companies struggle to sustain certification, often failing within 2 years, medium-sized companies demonstrate better sustainability, lasting beyond 6 years. Product/service quality and process improvement drive certification while decertification is influenced by management factors, financial constraints, and process management. The study recommends a model for effective integration of ISO 9001.

Integrated systems are crucial for consistent process performance and continual improvement in all sectors for sustainable organizational success. Although the ISO 9001 Quality Management System has shown positive impacts globally, the impact of its adoption in Botswana remains questionable with high failure rates post implementation. There appears to exist a significant gap in development, implementation, and maintenance of the QMS. The public domain has no evidence of any past investigation on causes of sustainability failures of ISO 9001 post certification. The current study sought to close that knowledge gap.

This paper aims to conduct a bibliometric analysis of studies focusing on green supply chain management (GSCM) within the context of the digital economy.

We utilize the Web of Science database to search and filter relevant documents spanning the years 2003–2022. This extensive dataset enables us to analyze the growth and cutting-edge developments in research pertaining to GSCM in the digital economy.

The paper finds a significant increase in research interest and output, particularly noticeable from 2016 onwards, indicating the growing relevance of integrating GSCM with digital technologies. It is found that the prominent contribution of countries like China, England and the USA, underscoring a strong geographical diversity in research outputs. China leads in the number of publications, which reflects its significant role in shaping the discourse around GSCM in the digital economy. However, when it comes to citations, the USA leads, suggesting a higher impact or quality of research emanating from this region. Collaborative dynamics outlined in the study demonstrate extensive international cooperation, primarily among leading research countries, which is facilitated by shared digital platforms enhancing the research’s reach and impact. The study also highlights a range of emerging themes such as the adoption of blockchain technology, Internet of Things (IoT) and the circular economy within GSCM, indicating dynamic areas for future research.

The findings of this study hold significant practical implications for researchers, practitioners and policymakers. They shed light on the current state of research in GSCM within the digital economy, highlighting areas where further investigation is needed and pointing to the emerging trends in this field. Understanding the distribution of research and influential authors can guide future collaborative efforts and inform decision-making processes in the pursuit of sustainable supply chain practices in the digital era.

This paper contributes to the existing body of knowledge by providing a comprehensive bibliometric analysis of the evolving landscape of GSCM in the digital economy. It offers valuable insights into the growth patterns, key contributors and geographical distribution of research in this domain. This information is crucial for researchers and stakeholders seeking to stay at the forefront of sustainable supply chain practices in an increasingly digital world.

The purpose of this paper is to provide a systematic literature review on Shariah governance and Islamic banks.

The literature was searched from Scopus and Web of Science using various queries related to Shariah governance and Islamic banks. Through a screening process, 93 articles were considered fit for the systematic literature review.

The paper provides a systematic review based on different themes, including measurement of Shariah governance in Islamic banks, disclosure of Shariah governance and its determinants, the impact of Shariah governance on performance, risk management and other outcomes of Islamic banks. Finally, issues and challenges of Shariah governance in Islamic banks are discussed, followed by conclusions and recommendations related to future research.

This study is the first of its kind, to the authors’ knowledge, to provide a comprehensive systematic literature on Shariah governance and Islamic banks by exploring different themes and highlighting multiple future avenues of research.

The study aims to critically review the Shariah governance framework for Islamic banking prevailing in Pakistan and provide a comparison with Accounting and Auditing Organization for Islamic Financial Institutions (AAOIFI).

It analyzes 16 circulars issued by the State Bank of Pakistan (SBP) since 2002, including three Shariah governance frameworks in 2014, 2015 and 2018. Additionally, the study compares the SBP and AAOIFI Shariah governance standards to evaluate the soundness of the SBP framework against international benchmarks.

Pakistan’s Shariah governance model is centralized, with the SBP’s Shariah board having ultimate authority. The SBP has provided a comprehensive Shariah framework, which includes among others, the criteria for the qualifications and conflict of interests of Shariah members. Both AAOIFI and SBP Shariah governance frameworks have similarities and differences in terms of the tenure of Shariah Supervisory Board (SSB) members, reporting line of SSB, number of SSB meetings, minimum experience of SSB members, primary duties of Shariah board, code of ethics and conduct for SSB and management and requirement of publication of SSB report in the annual report of Islamic banks. The frameworks differ in terms of the delegation of SSB powers, assessment and appraisal of SSB effectiveness and outsourcing of Shariah Compliance Department and Internal Shariah Audit Unit.

The study recommends expanding the qualification criteria for Shariah advisors to include additional degrees and qualifications, upholding stringent criteria for conflict of interests and promoting stakeholder consultation through exposure drafts.

To the best of the authors’ knowledge, this is the first of its kind which critically review and compare the Shariah governance framework prevailing in Pakistan.

This research aims to analyses the structural model of customers’ intention towards reputable and accountable Islamic finance, explained through Meta-Analysis Structural Equation Modelling (MASEM) with the Theory of Planned Behaviour approach and extended variables.

This study used MASEM to examine the factors systematically influencing behavioural intentions within Islamic finance. By synthesising 89 existing studies, the study identified key variables and their relationships, providing a comprehensive understanding of the underlying mechanisms. A rigorous methodology involving article selection, data extraction and statistical analysis enabled the development of a robust conceptual framework.

This study underscores the significant impact of subjective norms and perceived behavioural control on the intention to adopt Islamic finance, mediated by customer attitude. Religiosity, customer awareness and knowledge influence the intention to adopt Islamic finance products, with the Islamic financial institution's reputation and customer attitude serving as mediating variables.

This research novelty examines Islamic finance accounting, reporting and financial accountability, primarily focusing on customers’ perceived intentions towards Islamic financial practices.

This study aims to investigate the impact of augmented reality (AR) training modules on knowledge retention in corporate settings, focusing on the context of the United Arab Emirates (UAE). Drawing on the Technology Acceptance Model (TAM) and existing literature, the study examines the relationships between AR training modules, employees’ engagement, interactive learning environments and knowledge retention.

This study uses a quantitative technique by using a structured survey to collect data from participants in service sectors in the UAE. The survey gathers information on their attitudes, views and behaviors toward using AR in business training. This study used a stratified random selection to guarantee representation across several service sectors in the UAE, including hospitality, tourism, retail and finance. A SEM analysis tool was used to test the relationship that exists between the construct under investigation, that is, employees’ engagements (EE), AR training modules (ARTM), interactive learning environment (ILE), Fintech training content (FTC), the moderating role of technological aptitude (TA) on knowledge retention (KR).

Findings reveal a significant positive correlation between AR training modules and knowledge retention, emphasizing the potential of immersive technologies in enhancing learning outcomes. Moreover, the study underscores the importance of engaged employees, customized training materials and technological proficiency in shaping knowledge retention. Limitations and avenues for further research are also discussed.

Overall, this study contributes to understanding the factors influencing knowledge retention in corporate training contexts and provides practical insights for organizations seeking to optimize their training programs.

This study examines how structured procedures and psychological safety can enhance six sigma processes’ effectiveness and foster individual creativity within an organization.

This study employs a novel methodological approach, combining structural equation modeling (SEM) and multi-value qualitative comparative analysis (mvQCA).This combination gave us a unique lens through which to view the complex connections between the constructs that were the subject of the investigation.

The results substantiate that a well-structured six sigma approach, paired with a psychologically safe environment, fosters knowledge exploration and exploitation as well as triggering conducive learning behaviors. These elements, in turn, augment individual creativity, which is found to be instrumental in boosting six sigma performance.

This study is one of the first to combine mvQCA and SEM to investigate the complex interplay between structured methods, psychological safety and individual creativity in enhancing six sigma performance. This research highlights the importance of fostering creativity in strategic management processes and the unrealized potential of combining these methods.

The purpose of this article is to analyze the existing studies on the application of artificial intelligence (AI) in lean construction management (LCM). Further, this study offers a classification scheme that specifies different categories of AI tools, as applied to the field of LCM to support various principles of LCM.

This research adopts the systematic literature review (SLR) process, which consists of five consecutive steps: planning, searching, screening, extraction and synthesis and reporting. As a supplement to SLR, a bibliometric analysis is performed to examine the quantity and citation impact of the reviewed papers.

In this paper, seven key areas related to the principles of LCM for which AI tools have been used are identified. The findings of this research clarify how AI can assist in bolstering the practice of LCM. Further, this article presents directions for the future evolution of AI tools in LCM based on the current emerging trends.

This paper advances the LCM systems by offering a lens through which construction managers can better understand key concepts in the linkage of AI to LCM.

This research offers a new classification scheme that allows researchers to properly recall, identify and group various applications of AI categories in the construction industry based on various principles of LCM. In addition, this study provides a source of references for researchers in the LCM discipline, which advances knowledge and facilitates theory development in the field.

The unitized curtain wall system (UCWS), a symbol of modern architecture, is gaining popularity among prefabricated components. Previous studies have focused on both construction technology advances and material selection strategies to facilitate the UCWS. However, the topic of client satisfaction, which drives industry development by targeting clients' demands, has gone unnoticed. Therefore, the current study aims to investigate client satisfaction with UCWS products in Hong Kong by finding its influential factors.

A systematic review was employed to first identify the influential factors. A semi-structured interview was employed to validate the reliability of the extracted factors. The machine learning algorithm Extreme Gradient Boosting (XGBoost) and the Pearson correlation were then employed to rank the importance and correlation of factors based on the 1–5 Likert scale scores obtained through a questionnaire survey.

The findings revealed that “reduction in construction time” and “reduction in construction waste” are the most important factors and have a strong positive influence on client satisfaction.

Unlike previous studies, the present study focused on a novel research topic and introduces an objective analysis process using machine learning algorithms. The findings contribute to narrowing the knowledge gap regarding client preference for UCWS products from both individual and collaborative perspectives, providing decision-makers with an objective, quantitative and thorough reference before making investments in the curtain wall management development.