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The present research identifies and prioritizes the critical success factors (CSFs) for Lean 4.0 (L4.0) implementation in small and medium enterprises (SMEs). L4.0 integrates Lean principles with Industry 4.0 (I4.0) technologies, for instance wireless networks, Internet of things (IoT), big data, cloud computing (CC), etc., offering significant opportunities to enhance operational efficiency by reducing non-value-adding activities.

This research adopts the “Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL)” methodology to examine and assess the connections between CSFs for L4.0 implementation. Data were gathered from SMEs using qualitative and quantitative approaches to ensure comprehensive insights into the critical enablers of L4.0 adoption.

The study identifies Top Management Support and Commitment, Employee Training and Financial Capabilities as the most important CSFs for L4.0 adoption in SMEs. These factors significantly impact the adoption process, providing actionable insights for SME leaders to overcome challenges and optimize implementation strategies.

This study contributes to the growing knowledge of L4.0 by highlighting key CSFs relevant to SMEs, a sector often constrained by resources but crucial for economic development. The findings provide a practical roadmap for SME entrepreneurs to achieve operational excellence and competitiveness through effective L4.0 adoption.

This study aims to develop a neurocomputational approach using the Levenberg–Marquardt artificial neural network (LM-ANN) to analyze flow and heat transfer characteristics in mixed convection involving radiative magnetohydrodynamic hybrid nanofluids. The focus is on the influence of morphological nanolayers at the fluid–nanoparticle interface, which significantly impacts coupled heat and mass transfer processes.

This research simplifies a complex system of higher-order nonlinear coupled partial differential equations governing the flow between orthogonal coaxially porous disks into ordinary differential equations via similarity transformations. These equations are solved using the shooting method, and parametric studies are conducted to observe the impact of varying important parameters. The resulting data sets are used to train, validate and test the LM-ANN model, which ensures high predictive accuracy. Machine learning and curve-fitting techniques further enhance the model’s capability to generate detailed visualizations.

The findings of this study indicate that increased nanolayer thickness (0.4–1.6) significantly improves thermal performance, while changes in the chemical reaction parameter (0.2–1) have a notable effect on enhancing the Sherwood number. These results highlight the critical role of morphological nanolayers in optimizing thermal and mass transfer efficiency in MHD nanofluids.

This research provides a novel neurocomputational framework for understanding the thermal and mass transfer dynamics in MHD nanofluids by incorporating the effects of interfacial nanolayers, an aspect often overlooked in conventional studies. The use of LM-ANN trained on computational data sets enables high-fidelity predictive analysis, offering new insights into the enhancement of thermal and mass transfer efficiency in hybrid nanofluid systems.

The main purpose of this review was to synthesize pre-service teachers' digital self-efficacy in the context of education 5.0 and to identify the elements that affect pre-service teacher's digital self-efficacy and preparedness for future technologies. A systematic review approach was employed to analyze the 22 articles about the pre-service teachers' digital self-efficacy of in the paradigm of education 5.0. The review was conducted from 2012 to 2022 following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. In this study, PICO model was used in framing research questions. The findings of the review revealed that limited study has been carried out in the context of digital self-efficacy in the context of education 5.0. It was found that previous studies were only focusing general digital self-efficacy through traditional ways. Moreover, findings revealed there is lack of research on digital self-efficacy pre-service teachers in the realm of education 5.0 paradigm in the literature. More specifically, the results revealed that implementation of education 5.0 into teacher preparation programmes faces numerous challenges, including a lack of technological approach, poor digital infrastructure, the digital divide, a paucity of professional training opportunities for teachers and a lack of importance in policies. This synthesis of the literature review has practical implications for pre-service teachers along with policymakers. Pre-service teachers are required to increase their digital skills for the reason that they could teach the advanced generation. The policymakers can revisit and update the curriculum to incorporate education 5.0 principles in the teacher education programmes. This comprehensive review helps to better understand the pre-service teachers' digital self-efficacy towards education 5.0 and contributes to the body of existing knowledge on digital self-efficacy. Moreover, this study gives valuable insights on the incorporation of education 5.0.

Purpose: The aim of this chapter is to find out the factors affecting female entrepreneurship in the case of the Corporate Social Responsibilities (CSR) in entrepreneurship.

Methodology: In this chapter, semi-structured interviews are conducted to reach the final findings of the study.

Findings: Findings entail different six factors that severely affect CSR activities in entrepreneurship in Pakistan. These six factors are the educational system and skills gap, Cultural Mindset and Risk Aversion, Limited Access to Finance, Regulatory and Bureaucratic Hurdles, Political Instability and Security Concerns, and Inadequate Infrastructure. Every factor has its intensity and influence on the entrepreneurial process.

Originality/value: This chapter can be useful for international and local NGOs, academic institutions, financial institutions, government agencies, and entrepreneurs.

The objective of this study is to investigate the barriers hindering the integration of lean manufacturing (LM) practices within the furniture industry of Bangladesh. The traditional operational paradigms in this sector have posed substantial challenges to the effective implementation of LM. In this study, the barriers of implementing LM in the furniture business are examined, aiming to provide a systematic understanding of the barriers that must be addressed for a successful transition.

The research reveals that “Fragmented Industry Structure,” “Resistance to Lean Practices” and “Inadequate Plant Layout and Maintenance”, emerged as the foremost barriers to LM implementation in the furniture industry. Additionally, “Insufficient Expert Management,” “Limited Technical Resources” and “Lack of Capital Investment” play significant roles.

The outcomes of this study provide valuable insights into the furniture industry, enabling the development of strategies for effective LM implementation. One notable challenge in lean implementation is the tendency to revert to established practices when confronted with barriers. Therefore, this transition necessitates informed guidance and leadership. In addition to addressing these internal challenges, the scope of lean implementation should be broadened.

This study represents one of the initial efforts to systematically identify and assess the barriers to LM implementation within the furniture industry of Bangladesh, contributing to the emerging body of knowledge in this area.

Purpose: In this study, monolith analysis methods, microservice identification, and decomposition methods proposed for the transition to microservice architectures that enable the development of appropriate solutions by adapting to the complex demands that will shape the technological infrastructure of the future are evaluated.

Need for the study: Decomposition from monolithic architectures to microservices has become a popular approach in organizations and companies with Industry 5.0. This transformation of Industry 5.0 enables businesses to gain a competitive advantage and can provide a quick solution to personalized problems such as personal service systems.

Methodology: The study, decomposition from monolith to microservice, initially includes monolith analysis, followed by microservice decomposition review. Various classification methods have been proposed for microservice identification and decomposition and are aligned with Industry 5.0 principles, focusing on artificial intelligence (AI)-based approaches, especially human-centered AI.

Findings: Four analysis methods (domain, static, dynamic, and version) are identified for monolith analysis, with static and dynamic being the most common. Version analysis is not typically used alone. In the decomposition phase, clustering-based methods are prevalent due to the uncertain dimensions of microservices. Rule-based and unsupervised methods are identified for decomposition, with AI algorithms like affinity propagation, Kmeans clustering, hierarchical clustering, Hungarian algorithm, genetic algorithm, latent Dirichlet allocation (LDA), and minimum spanning tree (MST) being employed.

Practical implications: Microservice architecture enables flexibility, scalability, and resilience compared to monolithic structures. Decomposing large-scale monolith projects into microservices is challenging, requiring selection of appropriate monolith analysis methods based on project details (e.g., domain analysis for detailed Unified Modelling Language (UML) diagrams) before proceeding with decomposition. This transformation improves deployment, maintenance, fault isolation, and scalability, while allowing for diverse service-specific databases and programming languages.

This chapter examines the relationship between media consumption during COVID-19 and its effect on trust in experts. Successful crisis management requires risk assessment and rapid decisions, and decision-making in the crisis is often based on multidimensional and conflicting information, which highlights the importance of trust. Here, the aim is to examine how daily media consumption is associated with trust in experts and satisfaction with government response during the pandemic. Media consumption was defined by how many different media platforms respondents used daily, grouped into three broad categories: (1) broadcast media, including television and radio; (2) journalistic media, including newspapers and periodicals; and (3) social media, including social network sites and discussion forums. The results of the analyses show that trust in experts strengthened as the crisis progressed, but satisfaction with the government declined. Omnivorous media consumption – those who consumed several different forms of media – increased trust in experts as well as satisfaction with the government. Particularly, one-sided and social media-based media consumption was related to declined trust. That is, those who used only one form of media and those who relied heavily on social media alone expressed lower levels of trust in experts. The mediation analysis showed that the association between media consumption and government satisfaction was partly indirect through trust in experts. Overall, the study reinforces the importance of media as a moderator of messages during crisis management.

Supply chains need to be made viable in this volatile and competitive market, which could be possible through digitalization. This study is an attempt to explore the role of Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business performance from the lens of natural resource-based view.

The study tests the proposed model using a covariance-based structural equation modelling and further investigates the ranking of each construct using the artificial neural networks approach in AMOS and SPSS respectively. A total of 234 respondents selected using purposive sampling aided in capturing the industry practices across supply chains in the UK. The full collinearity test was carried out to study the common method bias and the content validity was carried out using the item content validity index and scale content validity index. The convergent and discriminant validity of the constructs and mediation study was carried out in SPSS and AMOS V.23.

The results are overtly inferring the significant impact of Industry 4.0 practices on creating smart and ultimately sustainable supply chains. A partial relationship is established between Industry 4.0 and supply chain agility through a smart supply chain. This work empirically reinstates the combined significance of green practices, Industry 4.0, smart supply chain, supply chain agility and supply chain resilience on sustainable business value. The study also uses the ANN approach to determine the relative importance of each significant variable found in SEM analysis. ANN determines the ranking among the significant variables, i.e. supply chain resilience > green practices > Industry 4.0> smart supply chain > supply chain agility presented in descending order.

This study is a novel attempt to establish the role of digitalization in SCs for attaining sustainable business value, providing empirical support to the mediating role of supply chain agility, supply chain resilience and smart supply chain and manifests a significant integrated framework. This work reinforces the integrated model that combines all the constructs dealt with in silos so far in prior literature.

The service sector has witnessed an important transformation due to technological disruption. The widespread adoption of digital technologies has enabled service providers to automate various tasks and processes. Blockchain technology, for instance, has transformed payments, remittances, and financial transactions in the financial services sector by providing greater transparency and security. The travel and hospitality industry has also seen changes through online booking platforms, review aggregators, and AI-driven recommendations. Other activities like entertainment, education, logistics, and transportation as well as retail have been disrupted by technologies leading to increased accessibility and efficiency and shaping the service economy into a customer-centric business model. This literature survey reviews the technological disruption in the services sector, including the health, education, financial, transport, tourism, and communications sectors. Across the subsectors reviewed, an average of 30 articles were reviewed and analyzed during the period 2000–2023.