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The COVID-19 pandemic has caused widespread disruptions to global industries, with the textile sector in South Asia being particularly hard hit. While previous studies have focused on the performance of textile sectors in individual countries, there is a gap in the literature on the comparative impact of the pandemic on the textile industry in South Asian nations. This study aims to fill this gap by investigating the performance of the textile sector in South Asian countries and identifying best practices for overcoming the pandemic’s adverse effects.

Using a comparative approach, this study analyzes the impact of COVID-19 on the performance of the textile sector in Pakistan, India and Bangladesh.

Our findings reveal that COVID-19 significantly negatively impacts the textile industry in Pakistan and India. However, Bangladesh has shown effective practices to support the textile industry and mitigate the pandemic’s adverse effects.

The findings of this study hold considerable implications for legislators, leaders, investors and supply chain management professionals operating within the South Asian textile sector. This research has the potential to inform policymakers in formulating strategies to facilitate the textile sector’s resilience during emergencies like the COVID-19 pandemic.

This paper provides significant theoretical additions to the current body of literature regarding the impact of COVID-19 on the textile sector in South Asia. The research uses the global value chain (GVC) theory as a theoretical framework to enhance understanding of the impact of global supply chains and interdependencies on the textile sector in the region.

This paper aims to examine and compare the export performance and competitiveness of Indian and Chinese textile and clothing industry in post-multifibre arrangement (MFA) era.

Balassa’s revealed comparative advantage Index is used to assess the competitiveness of Indian and Chinese textile and clothing exports.

The results indicate that China’s textiles and garments sector holds a greater proportion of the global market compared with India. India has a robust comparative advantage in silk, carpets and cotton post-MFA. Vegetable textile fibers, paper yarn and woven fabrics of paper yarn are also competitive. China had a strong comparative advantage in silk and fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery in 2005. China also recorded comparative advantage in silk, man-made filaments: strip and the like of man-made textile materials, fabrics; special woven fabrics, tafted textile fabrics, lace, tapestries, trimmings and embroidery and fabrics; knitted or crocheted in 2021.

This study’s results and recommendations could assist the Indian and Chinese Governments develop policies to upgrade their garment industries.

Though vast literature reviews are available for textile and apparel export performance in India and China separately, there are few studies on comparisons. This study is a significant attempt to evaluate India and China’s competitiveness in the global market.

Industry 4.0 has an inimitable potential to create competitive advantages for the apparel industry by enhancing productivity, production, profitability, efficiency and effectiveness. This study, thus, aims to assess the digitalisation level of the Tanzanian apparel industry through the Industry 4.0 perspectives.

A mixed-methods-based approach was deployed. This study deployed semi-structured interviews, document review and observation methods for the qualitative approach. For the quantitative approach, closed-ended questionnaires were used to ascertain the digitalisation levels and maturity level of the textiles and apparel (T&A) factories and small and medium-sized textile enterprises in Tanzania. The sample size was 110, with participants engaged through the purposive sampling technique.

Industry 4.0 frameworks evolved into practices mainly since 2011 in several service and manufacturing industries globally. For Tanzania, the findings indicate that the overall maturity level of the T&A industries is 2.5 out of 5.0, demonstrating a medium level of adoption. Thus, the apparel industries are not operating under the industry 4.0 framework; they are operating within the third industrial revolution – Industry 3.0 – framework. For such industries to operate within the fourth industrial revolution – Industry 4.0 – that is only possible if there is significantly well-developed industrial infrastructure, availability of engineering talent, stable commercial partnerships, demand from the marketplace and transactional relationship with customers.

This study’s limitations include: firstly, Industry 4.0 is an emerging area; this resulted in limited theoretical underpinnings in the Tanzanian perspectives. Secondly, the studied industries may not suffice the need to generalise the findings for the entire country, thus needing another study.

Although Industry 4.0 conceptual frameworks have been on trial in several industries since 2011, this is amongst the first empirical research on Industry 4.0 in the Tanzanian apparel industry that assesses the digitalisation levels.

Based on the knowledge-attitude-behavior model, this study is aimed at investigating the influential mechanism underlying the purchase of green clothing by dividing this clothing category into green home-in wear and home-out wear within the context of green consumption. The mediating effects of perceived greenwashing (PG), perceived value (PV) and expected moral benefit (EMB) and the moderating effect of green clothing type (GCT) were examined.

The data for this study were collected from 366 valid samples through a between-subject design survey administered in China. Moderation analysis and mediation analysis using SPSS/PROCESS macro were applied to test the proposed hypotheses.

The results indicate that consumers' level of environmental knowledge (EKL) not only has a direct effect on purchase intention (PI) but also has an indirect effect through perceived value and expected moral benefit. However, perceived greenwashing did not play a mediating role in this relationship.

The study's findings show a moderating effect of green clothing type (green home-in wear vs green home-out wear). That is, compared to green home-out wear, the relationship between expected moral benefit and perceived greenwashing for green home-in wear had a weaker negative effect on purchase intentions.

Quality assessment of textile products is of prime concern to intimately meet consumer demands. The dilemma faced by textile producers is to figure out the stability among quality criteria and efficiently deal with target specifications. Hence, the basic devotion is to attain the optimum value product which entirely satisfies the views and perceptions of consumers. Selection of best fabric among several alternatives in the presence of contradictory measures is a disputing problem in multicriteria decision-making.

In the current study, the analytic hierarchy process (AHP) and preference ranking organization method for enrichment evaluation (PROMETHEE) are proficiently used to solve the problem in selection of branded woven shawls. AHP method verifies comparative weights of the criteria selection, while the ranking of fabric alternatives grounded on specific net-outranking flows is executed through PROMETHEE II method.

The collective AHP and PROMETHEE approaches are applied for the useful accomplishment of grading of branded shawls based on multicriteria weights, used for effective selection of fabric materials in the textile market.

In the apparel industry, fabric and garment manufacturers often rely on hit-and-trial methods, leading to significant wastage of valuable resources and time, in achieving the desirable fabric qualities. The implementation of the findings can assist apparel manufacturers in streamlining their fabric selection processes based on multiple criteria. By adopting this method, industry players can make informed decisions, ensuring a balance between quality standards and consumer expectations, thereby enhancing both product value and market competitiveness.

The methods of Visual PROMETHEE and AHP are assimilated to offer a complete method for the selection and grading of fabrics with reference to multiple selection criteria.

This article aims to clarify the impact of stock market liberalization on corporate green technology innovation, analyze its mechanism from the perspectives of financing constraints and environmental management level and explore heterogeneity.

Using the panel data of Chinese enterprises from 2010 to 2020, this article adopts the multi-point difference-in-difference (DID) method to test the impact of stock market liberalization on enterprise green technology innovation and its conduction pathway.

The outcomes demonstrate that stock market liberalization contributes to the furthering of green technology innovation. The heterogeneity test reveals that this promotion is more pronounced for private companies, small-scale companies and companies with high information transparency. The mediating effect test shows that stock market liberalization boosts green technology innovation by alleviating corporate financing constraints and improving corporate environmental management.

This article elucidates the impact path of stock market liberalization on corporate green innovation based on alleviating corporate financing constraints and improving corporate environmental management levels. From the perspective of corporate green technology innovation, this article provides evidence from emerging market countries for the economic effects of capital market opening, which helps to further improve the level of green innovation.

The purpose of this study is to investigate the role of consumers’ moral preferences between moral and economic benefits and consumers’ moral and rational behaviour intentions based on moral decision-making models of previous studies.

Respondents were asked to answer a questionnaire measuring moral and economic benefits, consumers’ moral preferences and moral and rational behaviour intention after reading a stimulus describing imaginary fashion brand A’s unethical activities.

Moral and economic benefits directly and significantly affect moral and rational behaviour intention. Homo economicus evoked by an economic benefit had a negative effect on moral behaviour intention.

This study focused only on a moral benefit and an economic benefit as factors evoking consumers’ moral preferences. This study was also conducted only in a Korean context and considered a specific industry. In future research, the results of this study should be extended to design the “possibility of punishment” to encourage moral behaviour by discouraging the effect of homo economicus. The results have implications for companies such as social enterprises and charities that want to promote consumers’ moral behaviour.

This study provides evidence on why ethical consumers do not always make ethical decisions by confirming that homo economicus has a significant influence on not only rational behaviour intention but also moral behaviour intention.

Manufacturing small and medium-sized enterprises (SMEs) are heading towards smart manufacturing despite growing challenges caused by globalisation and rapid technological advancement. These SMEs, particularly textile SMEs of Bangladesh, also face challenges in implementing sustainability and organisational ambidexterity (OA) due to resource constraints and limitations of conventional leadership styles. Adopting paradoxical leadership (PL) and entrepreneurial bricolage (EB) is important to overcome the challenges. However, these dynamics are less explored in academia, especially in the Bangladeshi textile SMEs context. Hence, the purpose of this study is to investigate the influence of the adoption of smart technologies (ASTs), PL and OA, EB on sustainable performance (SP) of textile SMEs in Bangladesh.

A cross-sectional and primary quantitative survey was conducted. Data from 361 textile SMEs were collected using a structured self-administrated questionnaire and analysed by partial least square structural equation modelling (PLS-SEM).

The statistical outcome confirms that ASTs and PL significantly influence SP and OA. OA plays a significant mediating role for PL and is insignificant for ASTs, and EB significantly moderates among ASTs, PL and SP.

As this study is cross-sectional and focussed on a single city (Dhaka, Bangladesh), conducting longitudinal studies and considering other parts of the country can provide exciting findings.

This research provides valuable insights for policymakers, management and textile SMEs in developing and developed countries. By adopting unique and innovative OA, PL and EB approaches, manufacturing SMEs, especially textile companies, can be more sustainable.

This study has a novel, pioneering contribution, as it empirically validates the role of multiple constructs such as AST, PL, OA and EB towards SP in the context of textile SMEs in a developing country like Bangladesh.

Non-profit organizations (NPOs) are exposed to a highly competitive environment in which they are forced to grow their commercial activity to acquire additional financial resources. This study aims to create an understanding of how NPOs involved in textile reuse as a revenue-generating programme manage their reverse supply chains (RSC).

The research involves an embedded single-case study of NPOs in Finland involved in post-use textile collection. The main data sources are semi-structured interviews and participant observations.

This study is inspired by the microfoundations movement and identifies the underlying microfoundations of the NPOs’ capabilities for managing RSC for textile reuse. The study contributes to the literature by demonstrating NPOs’ lower-level, granular practices and their adaptations for achieving quality outcomes in textile reuse.

The findings have context sensitivity and apply to the NPOs which operate in a context similar to Finland, such as in other Nordic countries.

This study continues the discussion on the adoption of “business-like” practices in the NPOs’ pursuit of additional revenue streams to finance humanitarian work. The findings of this study can also be transferred to the growing area of domestic textile circularity.

Using the case of NPOs in textile reuse, the study illustrates how RSC management can serve a social, non-profit cause and transform unwanted textile products into a source of fundraising for humanitarian work.

This enriches the understanding of NPOs’ practices within the scope of revenue-generating programmes by examining one of them – textile reuse through charity shops from an RSC perspective.

This research tries to find the blockchain-based resilience strategies that can help the supply chains of micro, small, and medium-sized enterprises (MSMEs) to recover from the disruptions and work effectively in a resource-based view perspective.

Eight broad strategies and 32 sub-strategies are identified from the literature review. Delphi study was carried out, and detailed discussion with 16 experts helped in finalizing these strategies. Further, the best-worst method (BWM) prioritized these strategies.

The findings suggests that “building social capital,” improving “coordination capabilities,” “sensitivity towards market,” “flexibility in process and production,” “reduction in process and lead time,”and “having a resource efficiency and redundancy” are the top strategies on which the top management should focus to overcome the situations of disruptions and enhance performance of MSMEs.

The blockchain-based strategies will enable the companies in tracing the products from the company to customers. Further, the customers will be able to identify their manufacturers, the raw materials used in manufacturing, and the life and quality of raw used materials. Altogether the textile industry will become more sensitive toward environmental practices.

The previous research has not identified and evaluated the blockchain-based resilience strategies, and therefore this study tries to fill this gap. This study used a smaller sample from the experts, so the results may vary if the larger data set is used and hypothesis testing can be done.