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The purpose of this study is to identify the risks that exist in halal meat supply chain activities and to carry out a risk assessment using the fuzzy best-worst method (FBWM) along with mitigating risks using the risk mitigation number (RMN).

The method used is to collect several literature reviews related to the halal meat supply chain, which has information relevant to the risks of the meat industry in Indonesia. Then, a focus group discussion was held with several experts who play a role in the meat industry in Indonesia, and 33 identified risks were identified in halal meat supply chain activities. The proposed methodology uses FBWM and RMN in conducting risk assessment and mitigation in the meat industry in Indonesia.

The analysis reveals that priority risk is obtained by using the global weight value on the FBWM, and then risk mitigation is carried out with RMN. Priority mitigation strategies can mitigate some of the risks to the meat industry in Indonesia. The proposed mitigation strategy is designed to be more effective and efficient in preventing risks that can interfere with product halalness in halal meat supply chain activities in the Indonesian meat industry.

The implications of this study highlight the need for collaboration among stakeholders, improved risk assessment methodologies and the expansion of research into other halal supply chains. By addressing these implications, the halal industry can enhance its integrity, consumer confidence and overall contribution to the global market.

This research provides an integrated approach to identifying, analyzing, assessing and mitigating risks to the meat industry in Indonesia.

This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been prioritized and modeled based on an extensive literature search and professional views.

An integrated multi-criteria decision-making approach has been used in two phases. Best worst method (BWM) is used in the first phase to prioritize the challenges with sensitivity analysis to validate the findings and eliminate a few challenges. In the second phase, interpretive structural modeling is applied to the remaining 15 challenges to obtain relative relationships among them with cross-impact matrix multiplication applied to classification analysis for their categorization.

The study’s results reveal that limited knowledge and expertise, cost and risk involved, technical issues, lack of clear regulations, resistance to change and lack of top management support are the top-ranked or high-intensity challenges according to the BWM. Interpretive structural modelling findings suggest that the lack of government initiatives has been driving other challenges with the highest driving power.

This work has been conducted in the Indian context, so careful generalization of the results is needed.

This work will give health-care stakeholders a better perspective regarding blockchain’s adoption. It will help health-care stakeholders, service providers, researchers and policymakers get a glimpse of the strategies for eradicating mentioned challenges. The analysis will help reduce the challenges’ impact on blockchain’s adoption in the Indian health-care sector.

The adoption of BT is a novel concept, especially in developing countries such as India. This is one of the few works addressing the challenges to BT adoption in the Indian health-care sector.

In the textile dyeing industry, the foam dyeing has been recognized as a significantly sustainable alternative for the cotton fabrics. However, this efficient technology undergoes the many issues related to the foam generation, foam optimization and the required performance of the resultant fabrics. The purpose of this paper is to address these issues through the development and optimization of the novel reactive foam dyeing recipes for the cotton fabrics.

The foam dyeing recipes were generated and optimized using the different stabilizers, foaming agents and three primary colors of reactive dyes. The different recipes were applied onto the cotton fabric using laboratory scale foam coating machine. The performance of the foam coated and padded fabrics was evaluated using different criteria including the shade depth, rubbing fastness, air permeability, washing fastness, perspiration fastness, light fastness and tear strength. Then, a complex decision-making approach, namely, analytic hierarchy process (AHP), was applied for the ranking of the key recipes based on the main criteria.

The newly optimized foam dyeing recipes were found very competitive with the conventional pad dyeing process with respect to the shade-depth and the other performance properties. The optimization of foaming parameters and addition of stabilizers have advanced the foam dyeing process, which would accelerate the implementation of foam dyeing methods in the textile industry. Furthermore, significant water and energy savings would be achieved as compared to the conventional foam dyeing. AHP model offered a comprehensive and rational way to identify the most important recipes amongst the selected recipes.

In this research, novel foam dyeing recipes have been developed for the cotton fabrics through the optimization of the different stabilizers, foaming agents and the three primary colors of reactive dyes. Until now, the exiting literature has not reported the combination of these stabilizers with the different foaming agents and three primary reactive dyes for the improvement of sustainable foam cotton dyeing process.