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Lean Manufacturing Systems (LMS) gained popularity among manufacturers globally. However, their efficacy in developing and least-developed countries remained noticeably understudied. Motivated by this research gap, the researchers of this study designed a quantitative study with a structured survey technique to investigate its context-specific impact on the apparel industry of a developing country. Hence, this study aimed to examine the relationship between LMS and elimination of waste (EOW) and operational performance (OP) and comprehend how the EOW mediates the relationship between an LMS and OP within the apparel industry of a developing economy.

The researchers collected data from 227 garment companies in Bangladesh. These organization-level data were then analyzed using the structural equation modeling approach with AMOS 20.0 software to examine the direct and indirect effects among EOW, LMS and OP.

The findings of this study suggest that EOW has a direct and significant effect on OP. This research also revealed that EOW has a partial mediating effect on the relationship between LMS and OP.

This research focused on a single industry administering self-reported data and cross-sectional design, limiting generalizability and causal inference.

LMS and directing efforts towards EOW can significantly improve the operational performance of apparel companies by reducing lead times and costs, improving quality and increasing productivity.

These findings can provide useful insight to managers, practitioners and future researchers to understand the relationship between EOW, LMS and OP to optimize their production processes and improve OP in the apparel industry.

This chapter proposes a new architecture to address challenges to security and the privacy in e-healthcare under Industry 5.0. With the growing needs for high-quality medical treatment and the continuously growing costs of treating global medical problems, systems and web-based medical care are regarded as innovative solutions. In particular, the new progress in Internet of Things (IoT) has led to the development of Internet of Medical Things (IoMT). The patient history data is handled and processed remotely in real-time rather than visiting any clinic and then having that data transferred for subsequent use to third parties, such as data that gets saved in the cloud. This patient data faced security threats and it is observed as major limitations of using such systems in Industry 5.0. This chapter analyzes the security and secrecy challenges, together with the necessities, the danger involved and proposed secured blockchain-based framework which is capable of future research scope in Industry 5.0. The study has described an Eye Hospital case study that stores the eye donors’ details. With such critical scenario, this study addresses healthcare scenario with poverty-led agenda and social developmental features.

The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.

Revenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.

The empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.

As per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.

This paper aims to present a numerical study that investigates the flow of MgO-Al₂O₃/water hybrid nanofluid inside a porous elliptical-shaped cavity, in which we aim to examine the performance of this thermal system when exposed to a magnetic field via heat transfer features and entropy generation.

The configuration consists of the hybrid nanofluid out layered by a cold ellipse while it surrounds a non-square heated obstacle; the thermal structure is under the influence of a horizontal magnetic field. This problem is implemented in COMSOL multiphysics, which solves the related equations described by the “Darcy-Forchheimer-Brinkman” model through the finite element method.

The results illustrated as streamlines, isotherms and average Nusselt number, along with the entropy production, are given as functions of: the volume fraction, and shape factor to assess the behaviour of the properties of the nanoparticles. Darcy number and porosity to designate the impact of the porous features of the enclosure, and finally the strength of the magnetic induction described as Hartmann number. The outcomes show the increased pattern of the thermal and dynamical behaviour of the hybrid nanofluid when augmenting the concentration, shape factor, porosity and Darcy number; however, it also engenders increased formations of irreversibilities in the system that were revealed to enhance with the permeability and the great properties of the nanofluid. Nevertheless, this thermal enhanced pattern is shown to degrade with strong Hartmann values, which also reduced both thermal and viscous entropies. Therefore, it is advised to minimize the magnetic influence to promote better heat exchange.

The investigation of irreversibilities in nanofluids heat transfer is an important topic of research with practical implications for the design and optimization of heat transfer systems. The study’s findings can help improve the performance and efficiency of these systems, as well as contribute to the development of sustainable energy technologies. The study also offers an intriguing approach that evaluates entropy growth in this unusual configuration with several parameters, which has the potential to transform our understanding of complicated fluid dynamics and thermodynamic processes, and at the end obtain the best thermal configuration possible.

The study explores the current research trends within the responsible leadership (RL) domain and proposes a future research agenda by conducting an extensive review of past research. The study aims to understand recent developments in theories, constructs and contexts in RL literature.

Scopus database is used for the data collection on RL and patterns from 1998–2022. In total, 138 articles were covered for a systematic literature review (SLR) of RL behaviors. Further, the search was extended, and 109 more articles were included for bibliometric analysis of RL using R software. In total, 247 papers were reviewed.

The results present the consequences and antecedents of RL behaviors with external and internal stakeholders. Literature also indicates that researchers are more attentive to empirical studies with internal stakeholders, such as responsible leaders' impact on employee outcomes. Among theories, stakeholder theory's normative integrative and instrumental perspectives are used with RL.

The first limitation of the study is that this study collected data only from the Scopus database and the choice of language was English. Future studies may use other databases, languages and keywords. Instrumental and integrative RL behavioral styles would help balance organizations' financial and social goals.

This research enhances the literature on RL by combining content and bibliometric analysis to develop a more systematic and comprehensive understanding of integrative and instrumental leadership behaviors.

This paper investigates the ways digital media applications in rural areas have transformed the influence of social networks (SN) on farmers' adoption of various climate change mitigation measures (CCMM), and explores the key mechanisms behind this transformation.

The study analyzes data from 1,002 farmers’ surveys. First, a logit model is used to measure the impact of SN on the adoption of different types of CCMM. Then, the interaction term between digital media usage (DMU) and SN is introduced to analyze the moderating effect of digital media on the impact of SN. Finally, a conditional process model is used to explore the mediating mechanism of agricultural socialization services (ASS) and the validity of information acquisition (VIA).

The results reveal that: (1) SN significantly promotes the adoption of CCMM and the marginal effect of this impact varies with different kinds of technologies. (2) DMU reinforces the effectiveness of SN in promoting farmers' adoption of CCMM. (3) The key mechanisms of the process in (2) are the ASS and the VIA.

This study shows that in the context of DMU, SN’s promotion effect on farmers' adoption of CCMM is strengthened.