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This paper aims to analyze the nature, magnitude and determinants of access to food among rural households in India during the COVID-19 pandemic.

The study is based on the World Bank’s Rural Impact Survey, which has documented the shocks of COVID-19 among 2,787 rural households across six states in India. The chi-square test and binary logistics regression have been used to analyze the data.

About 49.7 % of rural households have reported the incidence of food inaccessibility and shortage, and the majority of them reported a reduction in food intake during the COVID-19 outbreak. However, the magnitude of food accessibility varied across the states and the sociodemographic characteristics of the households. Furthermore, regression analysis indicates that family size, social category and occupation as sociodemographic variables and membership in self-help groups, wage employment under Mahatma Gandhi National Rural Employment Guarantee Act and Cash transfer under Pradhan Mantri Kisan Samman Nidhi and Pradhan Mantri Garib Kalyan Yojana as institutional support factors have a significant effect on access to food among rural households.

The findings of the study have far-reaching policy implications for developing an effective food distribution system in crisis situations like the COVID-19 outbreak. The study also provides directions for extending the research on determinants of access to food during crisis.

The study is based on a large survey data from the rural households in India and provides empirical evidence on access to food faced by rural communities during the COVID-19 lockdown.

This article aims at analysing the factors influencing the adoption of green economy practices across different sizes of firms in India.

This study is based on the World Bank Enterprise Survey 2022, covering 9,376 firms in India. The Poisson Count Regression Model has been used to analyse the factors affecting the adoption of green economy practices.

About 83 % of firms reported adopting at least one green practice in their business related to energy conservation, water management, pollution control and waste management and recycling. Research results reveal a significant association between the size of the firm and adoption of green economy practices. The impact of enterprise characteristics varies by firm size. For instance, female ownership positively affects adoption in large firms but negatively in small and medium-sized enterprises (SMEs). However, lean operations, research and development (R&D) spending and international quality certification positively influence green practices adoption for both SMEs and large firms. Perceived business obstacles show similar implications on green practices adoption by size of firms except access to finance, business licencing, tax rate and law and order affect SMEs while labour regulations, tax administration and political instability affect large firms.

This paper suggests implications for strengthening the adoption of green economy practices across firm sizes and provides opportunities for future research.

This study is based on a unique dataset derived from the World Bank Enterprise Survey 2022, which has included green economy indicators for the first time.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-11-2023-0918.

The purpose of this study is to establish Loratadine [LRD] quantification in purified and capsule formulations using a precise and specific Reversal Phase with a very high-performance liquid Chromatographic [RP-HPLC] technique. The approach was evaluated in agreement with the principles of the International Conference on Harmonization [ICH]. Arcus EP-C18 Ion Pac column, 5 m, 4.6 mm, 250 mm, mobile phase Methanol: Acetonitrile (60:40) v/v. Dibasic potassium phosphate buffer, pH 7.2, flow rate 1.0 ml/min.

The HPLC system used a 340 nm UV detector for testing. A 10-min run time was used for the analysis. At concentrations ranging from 2 to 10 g/ml, the technique was linear (R² = 0.9998), exact (intra-day and inter-day relative standard deviation [RSD] values 1.0%), accurate (range recovery = 96%–102%), exclusive and strong.

The detecting and quantitation limits were 0.92 g/ml and 2.15 g/ml, respectively.

The findings demonstrated that the proposed method could accurately determine LRD in bulk and pill dose formats quickly and accurately.

The primary objective of this research is to introduce a pioneering takaful model that provides both provision and protection to the aging population by combining the concept of cash waqf with takaful. This model is designed to align with Shariah principles, ensuring sustainability and enduring impact.

This research adopts a qualitative methodology, where a focus group discussion was conducted with six stakeholders. The participants consisted of takaful operators, legal experts and other industry players. The participants were presented with the proposed cash waqf takaful model and their feedback was recorded. Legal issues related to linking waqf with takaful were also identified and discussed.

The study highlights the need for innovative financial solutions to support Malaysia's aging population. It proposes a cash waqf takaful model, leveraging crowd funding for sustainability. Legal hurdles and recommendations for overcoming them are discussed, along with suggestions for future research on quantitative validation and regulatory frameworks. Ultimately, the study emphasizes the holistic approach of the proposed model in addressing the well-being of Malaysia's senior citizens.

The proposed takaful model presents opportunities for takaful operators to integrate Islamic social finance into their operations, enabling easier access to takaful for the elderly community. By eliminating financial barriers, it can transform the takaful landscape, ensuring inclusivity and financial security for aging populations. Moreover, policymakers see it as a blueprint for sustainable financial solutions and social welfare enhancement globally.

The study introduces a novel cash waqf takaful model to support Malaysia's aging population, leveraging crowdfunding for sustainability. It addresses legal challenges unique to Malaysia and proposes collaboration with State Islamic Religious Authorities. Furthermore, it emphasizes the need for further research to validate the model's effectiveness and explores its potential global policy implications.

The purpose of this paper is to investigate, from a thorough review of the literature, the role of metaverse-based quality 4.0 (MV-based Q4.0) in achieving manufacturing resilience (MFGRES). Based on a categorization of MV-based Q4.0 enabler technologies and MFGRES antecedents, the paper provides a conceptual framework depicting the relationship between both areas while exploring existing knowledge in current literature.

The paper is structured as a comprehensive systematic literature review (SLR) at the intersection of MV-based Q4.0 and MFGRES fields. From the Scopus database up to 2023, a final sample of 182 papers is selected based on the inclusion/exclusion criteria that shape the knowledge base of the research.

In light of the classification of reviewed papers, the findings show that artificial intelligence is especially well-suited to enhancing MFGRES. Transparency and flexibility are the resilience enablers that gain most from the implementation of MV-based Q4.0. Through analysis and synthesis of the literature, the study reveals the lack of an integrated approach combining both MV-based Q4.0 and MFGRES. This is particularly clear during disruptions.

This study has a significant impact on managers and businesses. It also advances knowledge of the importance of MV-based Q4.0 in achieving MFGRES and gaining its full rewards.

This paper makes significant recommendations for academics, particularly those who are interested in the metaverse concept within MFGRES. The study also helps managers by illuminating a key area to concentrate on for the improvement of MFGRES within their organizations. In light of this, future research directions are suggested.

COVID-19 has been the subject of a number of inquiries recently. All country's capital market practices have been affected by the COVID-19 outbreak. Economic woes, along with the stock market crash, have hit emerging markets and developing economies in a variety of directions.

This study is an attempt to focus on the Indian economy to provide the gist of the situation and recovery mode of an economy with the help of growth indicators of the economy.

This study is based on secondary data. The researchers applied some econometric tools, viz, unit root test Augmented Dickey-Fuller (ADF), Panel Granger Causality, and Panel ARDL Bound Test were applied to examine the relationship of economic indicators and stock market benchmark in two periods: March 2020–June 2021 (during period) and July 2021 to March 2022 (post period).

The findings of this study explored the different causal relationships for the selected variables in both periods. The study discussed the reasons for ARDL (Auto Regressive Distributed Lag) bound for all selected factors. The study revealed the story of crude oil prices and Gold as trusted investment avenues during the crises.

As we know, the capital market's backlash is reflected in movements in stock prices and stock exchange volume, which are concerned with the economic effects of the pandemic and urged the segment to react. Investors can use the information in the event to make investment decisions.

This study aims to investigate the behavior of different types of stone columns, including the short and floating columns, as well as the ordinary and the geosynthetic encased stone columns (OSC and GESC). The effectiveness of the geosynthetic encasement and the impact of the installation using the lateral expansion method on the column performance is evaluated through a three-dimensional (3D) unit cell numerical analysis.

A full 3D numerical analysis is carried out using the explicit finite element code PLAXIS 3D to examine the installation influence on settlement reduction (ß), lateral displacement (U_x) and vertical displacement (U_z) relative to different values of lateral expansion of the column (0% to 15%).

The findings demonstrate the superior performance of GESC, particularly short columns outperforming floating counterparts. This enhanced performance is attributed to the combined effects of geosynthetic encasement and increased lateral expansion. Notably, these strategies contribute significantly to decreasing lateral displacement (U_x) at the column’s edge and reducing vertical displacement (U_z) under the rigid footing.

In contrast to previous studies that examined the installation effect of OSC contexts, this paper presents a comprehensive investigation into the effect of geosynthetic encasement and the installation effects using the lateral expansion method in very soft soil, using 3D numerical simulation. The study emphasizes the significance of the consideration of geosynthetic encasement and lateral expansion of the column during the design process to enhance column performance.

The apparel industry of Bangladesh is rethinking lean manufacturing (LM) deployment because of the challenges imposed by the COVID-19 pandemic. Due to COVID-19, LM implementation in the apparel industry has become more difficult. Thus, the purpose of this study is to explore the barriers to implementing LM practices in the apparel industry of Bangladesh in the context of COVID-19 pandemic.

For evaluating the barriers, an integrated framework that combines the Delphi method and fuzzy total interpretive structural modeling (TISM) has been designed. The application of fuzzy TISM has resulted in a structured hierarchical relationship model of the barriers with driving and driven power.

The findings reveal that “lack of synchronization of lean planning with strategic planning”, “lack of proper understanding of lean concept” and “low priority from the top management” are the three top most important barriers of LM implementation in apparel industry.

These findings will help the apparel industry to formulate strategy for implementing the LM practices successfully. The proposed model is expected to contribute to the sustainable development goals (SDGs) such as Responsible Consumption and Production (SDG 12); Decent Work and Economic Growth (SDG 8); Industry, Innovation and Infrastructure (SDG 9) via resilient strategies.

This study is one of few initial efforts to investigate LM implementation barriers during the COVID-19 epidemic in a real-world setting.

During the coronavirus disease 2019 (COVID-19) pandemic, ubiquitous social media has become a primary channel for information dissemination, social interactions and recreational activities. However, it remains unclear how social media usage influences nonpharmaceutical preventive behavior of individuals in response to the pandemic. This paper aims to explore the impacts of social media on COVID-19 preventive behaviors based on the theoretical lens of empowerment.

In this paper, survey data has been collected from 739 social media users in China to conduct structural equation modeling (SEM) analysis.

The results indicate that social media empowers individuals in terms of knowledge seeking, knowledge sharing, socializing and entertainment to promote preventive behaviors at the individual level by increasing each person's perception of collective efficacy and social cohesion. Meanwhile, social cohesion negatively impacts the relationship between collective efficacy and individual preventive behavior.

This study provides insights regarding the role of social media in crisis response and examines the role of collective beliefs in the influencing mechanism of social media. The results presented herein can be used to guide government agencies seeking to control the COVID-19 pandemic.

Nanotechnology (NT) advancements in personal protective textiles (PPT) or personal protective equipment (PPE) have alleviated spread and transmission of this highly contagious viral disease, and enabled enhancement of PPE, thereby fortifying antiviral behavior.

Review of a series of state of the art research papers on the subject matter.

This paper expounds on novel nanotechnological advancements in polymeric textile composites, emerging applications and fight against COVID-19 pandemic.

As a panacea to “public droplet prevention,” textiles have proven to be potentially effective as environmental droplet barriers (EDBs).

PPT in form of healthcare materials including surgical face masks (SFMs), gloves, goggles, respirators, gowns, uniforms, scrub-suits and other apparels play critical role in hindering the spreading of COVID-19 and other “oral-respiratory droplet contamination” both within and outside hospitals.

When used as double-layers, textiles display effectiveness as SFMs or surgical-fabrics, which reduces droplet transmission to <10 cm, within circumference of ∼0.3%.

NT advancements in textiles through nanoparticles, and sensor integration within textile materials have enhanced versatile sensory capabilities, robotics, flame retardancy, self-cleaning, electrical conductivity, flexibility and comfort, thereby availing it for health, medical, sporting, advanced engineering, pharmaceuticals, aerospace, military, automobile, food and agricultural applications, and more. Therefore, this paper expounds on recently emerging trends in nanotechnological influence in textiles for engineering and fight against COVID-19 pandemic.