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The purpose of this paper is to investigate the efficient exploitation of bioactive compounds present in red, green and brown seaweeds to develop hygienic products.

To analyse the antioxidant properties and identification of significant bioactive compounds of green, red and brown seaweed treated cotton fabrics, total antioxidant activity, DPPH Free radical scavenging activity and gas chromatography-mass spectrometry analysis were used.

The experimental result specifies that the maximum antioxidant activity of 126.50 µg/ml and inhibition percentage of 76 ± 0.15 percent was achieved in the seaweed treated cotton fabrics. All six seaweed treated fabrics proved slightly lesser water vapour and air permeability compared with the untreated fabric.

The seaweed treated cotton materials are suitable for making wound dressing, surgical wear, face mask, sportswear, healthcare and hygienic applications.

The healthcare and hygiene textiles are gaining more importance for their eco-friendly and effective antimicrobial properties that have become essential to safeguard human beings from harmful microorganisms. The fabrics finished with chemical-based antimicrobial agents lead to environmental issues and are harmful to human beings. The paper aims to discuss these issues.

The present investigation is to develop a fabric with antioxidant and antimicrobial properties using the extracts of brown algae. Antimicrobial property has been imparted to the cotton fabric using microcapsules of brown seaweed extracts using the pad-dry-cure method. The presence of bioactive compounds and antioxidant activities of brown algae extracts was evaluated using gas chromatography-mass spectrometry and 2, 2-diphenyl-1-picrylhydrazyl radical scavenging technique, respectively. The total phenolic content of the seaweed extract was determined by the Folin-Ciocalteu method. The minimum bactericidal concentration and minimum inhibitory concentration methods were used to determine the antibacterial activity of the bacterial reduction percentage and parallel streak methods were used evaluate the antibacterial activity of seaweed-treated fabrics.

The methanol fraction of the treated fabric had the highest antioxidant activity (42.5+1.21 per cent), because the higher phenolic content traps the reactive oxygen species and develops the cells present in the skin. The results show that the lower inhibition (250 µg/mL) and bactericidal concentrations (1,000 µg/mL) possess higher antibacterial activity. The results also show that the treated fabric possess higher bacterial reduction of 96 per cent and higher zone of inhibition against Escherichia Coli and Staphylococcus Aureus which was about 35 mm and 40 mm. The air permeability, bending length and the wicking behaviour of the treated fabric were slightly reduced, but it has good bursting strength compared with the untreated fabric.

Such treated fabric is used for making wound dressing, surgical gowns, antibacterial socks and gauze bandage products in healthcare and hygiene textiles.

Medical textile is one aspect of technical textiles and it is classified according to performance and functional properties for hygienic and healthcare products. Seaweeds have curative powers for curing most degenerative diseases. The paper aims to discuss these issues.

The present study focusses on the extraction of dyes from five seaweeds such as Ulva reticulata, Ulva lactuca, Sargassum wightii, Padina tetrastomatica and Acanthophora spicefera. The presence of bioactive compounds, antioxidant and antimicrobial properties of dye extracted from seaweeds was analysed. The dye extracted from green seaweed was applied on cotton fabric to obtain antimicrobial and other properties used to make non- implantable materials.

A maximum antioxidant inhibition percentage of 86.48+2.84 and a maximum antibacterial activity of 27 mm inhibition zone were obtained on the fabric treated with the dye extract from the Ulva lactuca seaweed. The physical properties such as tensile strength and tearing strength did not show much significant difference in untreated and treated fabric. The air permeability, water absorbency and wicking behaviour of treated fabric were reduced compared with untreated fabric. The washing and rubbing properties of treated fabric were very good after repeated washing.

This bioactive fabric has been used for non-implantable materials such as wound healing, face mask, surgical gowns and hygienic textiles in recent years.

Medical textiles is a vibrant emerging field in the area of technical textiles and its category is based on its performance and biofunctional properties for hygienic and health care products. Biodegradable fabrics are widely used for medical textiles in recent years. Seaweeds provide a wide range of therapeutic possibilities for human beings both internally and externally due to the presence of bioactive compounds. The paper aims to discuss these issues.

This present study investigates the development of bioactive gauze fabric from Chaetomorpha linum seaweed/cotton blended fibres and also analysed the characteristics of Chaetomorpha linum seaweed/cotton blended gauze fabric and 100 per cent cotton gauze fabric. The effect of fibres on physical properties of fabric such as tensile strength, air permeability, wickability, water drop test and colour fastness properties were analysed. The antibacterial properties and antioxidant activity were assessed by DPPH radical scavenging, AATCC 100 and EN ISO 20645 test methods.

The experimental results indicate that the maximum antioxidant activity of 103.28±1.23 per cent inhibition was achieved at minimum concentration (500 µg/ml) of the blended fabric extract, and maximum antibacterial reduction of 95 per cent and zone of inhibition of about 26 mm were achieved in a blended fabric. The tensile strength, percentage of elongation and air permeability were more or less the same in both gauze fabrics. It is also found that Chaetomorpha linum seaweed/cotton blended gauze fabric exhibit better wickability and water absorbency properties than 100 per cent cotton gauze fabric. The colour fastness properties to washing and rubbing showed excellent results in the blended gauze fabric, and it is used for making wound dressing materials.

This bioactive gauze fabric was used for non-implantable materials such as wound healing, face mask, surgical gowns and hygienic textiles in recent years.

Introduction: The insurance industry has unprecedented growth, and the demand for insurance has outgrown in the recent past due to the prevailing pandemic. The companies have a large base of the data set at their disposal, and companies must appropriately handle these data to come out with valuable solutions. Data mining enables insurance companies to gain an insightful approach to map strategies and gain competitive advantage, thus strengthening the profits that will allow them to identify the effectiveness of back-propagation neural network (BPNN) and support vector machines (SVMs) for the companies considered under study. Data mining techniques are the data-driven extraction techniques of information from large data repositories, thus discovering useful patterns from the voluminous data (Weiss & Indurkya, 1998).

Purpose: The present study is performed to investigate the comparative performance of BPNNs and SVMs for the selected Indian insurance companies.

Methodology: The study is conducted by extracting daily data of Indian insurance companies listed on the CNX 500. The data were then transformed into technical indicators for predictive model building using BPNN and SVMs. The daily data of the selected insurance companies for four years, that is, 1 April 2017 to 21 March 2021, were used for this. The data were further transformed into 90 data sets for different periods by categorising them into biannual, annual, and two-year collective data sets. Additionally, the comparison was made for the models generated with the help of BPNNs and SVMs for the six Indian insurance companies selected under this study.

Findings: The findings of the study exhibited that the predictive performance of the BPNN and SVM models are significantly different from each other for SBI data, General Insurance Corporation of India (GICRE) data, HDFC data, New India Assurance Company Ltd. (NIACL) data, and ICICIPRULI data at a 5% level of significance.

Fabrics, which are one of the raw materials of the clothing industry, constitute approximately 40–45% of the total cost of an apparel product. Due to the labor-intensive nature of this industry and failure to apply scientific methods along with the manufacturing processes, the wastes in the raw materials, including fabrics, become higher. Besides, quality deficiencies are encountered due to the same reasons. This study aims to determine the optimum total fabric layer height based on the fabric type during the cutting process with a straight knife cutting machine, which provided a decrease in the cutting errors.

Frequently used fabric types in an enterprise operating in organic cotton knitwear were listed. During the cutting tests, the straight knife cutting machine was used as the cutting device. The weight and thickness values of the fabrics were obtained to provide a comparison basis. Two different algorithms were created to evaluate the defective pieces according to fabric type, cutting height and error placement. Cutting resistances of these fabrics were also determined to evaluate the defect reasons. In the end, optimum total fabric layer count and total cutting height suggestions were proposed for each fabric type for a minimum cutting error.

At the end of this study, the error-free layers were identified per fabric type. At the same time, the optimum cutting height was suggested for each fabric basis. For 40/1 single jersey fabrics, the cutting height should be between 2.10 cm and 10.40 cm; for 30/1 single jersey fabrics, between 1.65 cm and 5.70 cm; for 20/1 single jersey fabrics, between 1.83 cm and 6.70 cm; for two-thread fleece fabrics, between 2.13 cm and 4.70 cm; and for three-thread fleece fabrics, between 0 cm and 4.90 cm.

Within the scope of the study, since the products made of knitted fabric were produced more frequently and in large quantities, the study was carried out with 15 different types of knitted fabrics at 10 different layers. The same methods should be applied for woven, denim and nonwoven fabric types, which would shed light on the following studies.

Due to scarce research carried out on the cutting procedure of the clothing industry in regards to sustainability, this study aims to contribute to this area. The main difference between this study and the studies that mostly make mathematical predictions about the cutting procedure is that it is practice-oriented.

This study aims to examine the influence of collectivism, brand prestige and brand identification on green brand loyalty among Generation Z and older generation travellers in India. Loyal consumers are essential for the long-term success of hotels.

A single cross-sectional design is used in the study, with a total of 277 Generation Z and 299 Older generation travellers surveyed directly at three different tourist destinations in India. The PLS-SEM approach is used to analyse the data.

The study’s findings showed that among Generation Z travellers, factors such as collectivism, brand identification and brand prestige play a significant role in shaping green brand loyalty towards hotels. Furthermore, we noted that collectivism directly influences brand prestige and identification. Conversely, for the older generation, the study did not substantiate the impacts of collectivism on green brand loyalty nor the relationship between brand identification and green brand loyalty.

This study uniquely contributes to the literature by revealing generational differences in the influence of collectivism and brand factors on green brand loyalty within the Indian hotel industry.

本研究探讨了集体主义、品牌声望和品牌认同对印度 Z 世代和老一代旅行者绿色品牌忠诚度的影响。 忠诚的消费者对于酒店的长期成功至关重要。

该研究采用单一横断面设计, 直接在印度三个不同的旅游目的地对总共 277 名 Z 世代和 299 名老一代旅行者进行了调查。 PLS-SEM 方法用于分析数据。

研究结果表明, 在 Z 世代旅行者中, 集体主义、品牌认同和品牌声望等因素在塑造酒店绿色品牌忠诚度方面发挥着重要作用。 此外, 我们注意到集体主义直接影响品牌声誉和认同。 相反, 对于老一代人来说, 该研究没有证实集体主义对绿色品牌忠诚度的影响, 也没有证实品牌认同与绿色品牌忠诚度之间的关系。

这项研究揭示了集体主义和品牌因素对印度酒店业绿色品牌忠诚度影响的代际差异, 对文献做出了独特的贡献。

Este estudio examina la influencia del colectivismo, el prestigio de la marca y la identificación de la marca en la lealtad a la marca ecológica entre la Generación Z y los viajeros de la generación anterior en la India. Los consumidores leales son esenciales para el éxito a largo plazo de los hoteles.

En el estudio se utiliza un diseño transversal único, con un total de 277 viajeros de la Generación Z y 299 de la Generación Mayor fueron encuestados directamente en tres destinos turísticos diferentes en la India. El enfoque PLS-SEM se utiliza para analizar los datos.

Los hallazgos del estudio mostraron que entre los viajeros de la Generación Z, factores como el colectivismo, la identificación de marca y el prestigio de la marca juegan un papel importante en la configuración de la lealtad hacia las marcas ecológicas hacia los hoteles. Además, observamos que el colectivismo influye directamente en el prestigio y la identificación de la marca. Por el contrario, para la generación mayor, el estudio no corroboró los impactos del colectivismo en la lealtad a la marca verde, ni la relación entre la identificación de marca y la lealtad a la marca verde.

Este estudio contribuye de manera única a la literatura al revelar diferencias generacionales en la influencia del colectivismo y los factores de marca en la lealtad a las marcas ecológicas dentro de la industria hotelera india.

The purpose of this research is to investigate the change in the relationship of cognitive destination image, affective destination image, destination psychological commitment and destination psychological ownership with intention to visit destination because of COVID-19 pandemic.

The research followed a longitudinal design with 424 samples collected in two phases (t1 – before COVID-19; t2 – during COVID-19). The hypotheses were analysed using structural equation modelling, and the difference between the models (before and during COVID-19) was estimated using multi-group analysis.

The results indicate that destination psychological ownership and affective destination image share higher significant relationships with intention to visit destination even during COVID-19.

The results have indicated the role of destination psychological ownership in building a sustainable campaign towards the visit intention even during a crisis.

The study contributes to understanding the difference of tourists intention to visit destination before and during COVID-19 from the lens of various theories such as psychological ownership, psychological commitment and destination image.

The study attempts to estimate farm subsidies the governments can save by transitioning to a millet-based production system, replacing GHG emission-intensive crops.

It updates a 131 × 131 commodity input–output (IO) table of the year 2015–16 into 2021–22 using the RAS procedure and simulates the economy-wide impacts of replacing rice and wheat with pearl millet and sorghum using consumption and production approaches. It then quantifies fertilizer, electricity and credit subsidy expenses the government can save through this intervention. It also estimates the potential reduction in GHG emissions that the transition could bring about. India is taken as a case.

Results show pearl millet expansion brings greater benefits to the government. It is estimated that when households return to their pearl millet consumption rates that prevailed in the early-reform period, this could save the Indian government Rs. 622 crores (USD 75 m). The savings shall be reinvested in agriculture to finance climate adaptation/mitigation efforts, contributing to a sustainable food system. Net GHG emissions also decline by 3.3–3.6 MMT CO2e.

Indian government has been actively aiming to bring down paddy areas since 2013–14 through the Crop Diversification Program and promoting millets (and pulses and oilseeds) on these farms. The prime reason is to check rapidly declining groundwater irrigation in Green Revolution states. Regulations in the past in these states have not brought the intended results. Meanwhile, electricity and fertilizers are heavily subsidized for agriculture. A slight shift in the cropping system can help conserve these resources. Meanwhile, GHG emissions could also be brought down and subsidies could well be saved. The results of the study indicate the same.

A less warm society is what governments and nongovernment organizations across the world are aiming for at present. Financial implications affect actions against climate change to a greater extent, apart from technological innovations. The effects of policy strategies discussed in the study, taking a large country as a case, when implemented appropriately around the regions, could help move a step closer to action against climate change.

The paper addresses a key but rarely explored research issue – that how a climate-sensitive crop choice will help reduce the government’s fiscal burden to finance climate adaption/mitigation. It also offers a mechanism to estimate the benefits within an economy-wide framework.

The study examines the influence of various congruity factors (economic, safety and Health, hedonic, and functional) on tourists' satisfaction with sharing economy-based services.

A single cross-sectional design is used in the study, with 513 travellers surveyed directly at three different tourist destinations in India. The partial least squares-structural equation modelling approach is used to analyse the data.

The research shows that congruity factors significantly influence tourists' satisfaction with sharing economy-based services. Moreover, satisfaction is strongly associated with recommendation intention for these services and customer loyalty. Additionally, the intention to recommend directly leads to increased customer loyalty.

The results offer pertinent insights for stakeholders in the sharing economy, including tourism marketers, policymakers and corporations. Aligning services with the identified congruity factors can enhance user satisfaction, boost recommendation rates and foster long-standing customer loyalty.

This study stands out for its thorough investigation into how congruity factors influence tourist satisfaction within the context of the sharing economy. Additionally, by focusing on specific demographic differentiators, such as age (gen Z or old gen) and gender (male or female), the study provides a nuanced understanding that enriches the existing body of knowledge.