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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.

The apparel and textile sector poses a significant environmental challenge due to its substantial contribution to pollution in the form of air, water and soil pollution. To combat these issues, the adoption of sustainable practices is essential. This study aims to identify and analyse the barriers that hinder the progress of sustainability in the apparel and textile industry. By consulting experts in the field, critical barriers were identified and given special attention.

To achieve the research objective, an integrated approach involving Interpretive Structural Modelling (ISM) and fuzzy MICMAC decision-making techniques was employed. The results were further validated through the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method.

The findings highlight that barrier related to clothing disposal, inadequate adaptation to modern technology, challenges affecting sector efficiency and issues related to fashion design are crucial in influencing the remaining six barriers. Based on the outcomes of the DEMATEL method, a comprehensive cause-and-effect diagram was constructed to gain a deeper understanding of these challenges.

This research provides valuable insights for policymakers and stakeholders in the apparel and textile industry. It offers a strategic framework to address and overcome sustainability barriers, promoting the development of a more environmentally responsible and resilient sector.

The purpose of this research is to conduct an in-depth investigation of the barriers apparel and textile sectors. It is feasible that both the management team and the medical experts who provide direct patient care could benefit from this research.

This study is the maiden attempt to understand the effect of specific human resource practices (HRPs) on employee retention (ER) with the mediation of job satisfaction (JS) and moderation of work experience (WE) and job hopping (JH) in the context of the textile industry.

This study adopted a quantitative methodology and applied quota sampling to gather data from employees (n = 365) of leading textile companies in India. The conceptual model and hypotheses were tested with the help of Partial Least Squares-Structural Equation Modelling (PLS-SEM).

The findings of a path analysis revealed that compensation and performance appraisal (CPA) have the highest impact on JS followed by employee work participation (EWP). On the other hand, EWP had the highest impact on ER followed by grievance handling (GRH). The study revealed that JS significantly mediates between HRPs like CPA and ER. During Multi-group analysis (MGA) it was found that the importance of EWP and health and safety (HAS) was more in employee groups with higher WE, but it was the opposite in the case of CPA. In the case of JH behavior, the study observed that EWP leads to JS in loyal employees. Similarly, JS led to ER, and the effect was more pronounced for loyal employees.

In the context of the Indian textile industry, this work is the first attempt to comprehend how HRPs affect ER. Secondly, it confirmed that JS is not a guaranteed mediator between HRPs and ER, it could act as an insignificant, partial or full mediator. Additionally, this study establishes the moderating effects of WE and JH in the model through multigroup analysis.

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.

The case is written on the basis of published sources only.

Doodlage, a start-up incorporated in 2012 by Kriti Tula, Paras Arora and Vaibhav Kapoor, used discarded waste to create sustainable fashion products. It had a first-mover advantage in recycled fashion goods in the first 10 years of its existence. The company contributed to sustainable fashion by providing an alternative to fast fashion production, creating enormous clothing waste and environmental degradation. In the first quarter of 2022, it saved and reused 15,000 m of fabric waste. From 2018 to 2021, the company grew 150% annually, targeting the right customers and regions to expand its business. It ensured that postproduction industrial waste and postconsumption garments were used to produce clothes. It also confirmed that the waste generated in its fabric screening process was used to create stationery items and other valuable accessories.

However, the sustainable fashion model that gave the company a competitive advantage became obsolete in 2022 due to increasing competition in the industry as various players using unique ideas entered the market. The company is encountering operational and logistical challenges that are affecting its performance. The demand for its products was also subdued due to high prices of upcycled and recycled clothes and less consumer spending post-COVID pandemic. The competitors of Doodlage offered multiple products produced using environmentally friendly farming and manufacturing techniques, attracting sustainable purchasers. What should be the new portfolio of products for the company to explore future growth opportunities? Considering their vast price, can consumers be encouraged to buy upcycled clothes? How should the company ride the winds of change in the industry?

The instructor should initiate the class discussion by asking questions such as how frequently do you shop for clothes? Do you care about the fabric of your apparel? After you discard your clothes, do you think about where these goods finally end up? Data on the amount of total waste generated in the fashion industry should be communicated to students to connect it with the importance of the concept of circular economy. Post this, the instructor should introduce the business model of Doodlage to bring the discussion into the context of the fashion industry before going ahead to discuss the company’s dilemma.

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.

The use of technology in 4th industrial revolution is at its peak. Industries are trying to reduce the consumption of resources by effectively utilizing information and technology to connect different functioning agents of the manufacturing industry. Without digitization “Industry 4.0” will be a virtual reality. The present survey-based study explores the factual status of digital manufacturing in the Northern India.

After an extensive literature review, a questionnaire was designed to gather different viewpoints of Indian industrial practitioners. The first half contains questions related to north Indian demographic factors which may affect digitalization of India. The latter half includes the queries concerned with various operational factors (or drivers) driving the digital revolution without ignoring Indian constraints.

The focus of this survey was to understand the current level of digital revolution under the ongoing push by the Indian government focused upon digital movement. The analysis included non-parametric testing of the various demographic and functional factors impacting the digital echoes, specifically in Northern India. Findings such as technological upgradations were independent of type of industry, the turnover or the location. About 10 key operational factors were thoughtfully grouped into three major categories—internal Research and Development (R&D), the capability of the supply chain and the capacity to adapt to the market. These factors were then examined to understand how they contribute to digital manufacturing, utilizing an appropriate ordinal logistic regression. The resulting predictive analysis provides seldom-seen insights and valuable suggestions for the most effective deployment of digitalization in Indian industries.

The country-specific Industry 4.0 literature is quite limited. The survey mainly focuses on the National Capital Region. The number of demographic and functional factors can further be incorporated. Moreover, an addition of factors related to ecology, environment and society can make the study more insightful.

The present work provides valuable insights about the current status of digitization and expects to facilitate public or private policymakers to implement digital technologies in India with less efforts and the least resistance. It empowers India towards Industry 4.0 based tools and techniques and creates new socio-economic dimensions for the sustainable development.

The quantitative nature of the study and its statistical predictions (data-based) are novel. The clubbing of similar success factors to avoid inter-collinearity and complexity is seldom seen. The predictive analytics provided in this study is quite elusive as it provides directions with logic. It will help the Indian Government and industrial strategists to plan and perform their interventions accordingly.

This study aims to examine individual-specific market orientation as an innovative approach and its relationship with marketing skills among artisan entrepreneurs in India.

The study adopted an in-depth interview to explore variables, a questionnaire survey to understand their latent dimensions through exploratory factor analysis and structural equation modeling to test the relationship between constructs under study.

The interview result indicates that 20 variables explain factors affecting individual-specific market orientation with four latent dimensions: customer orientation, competitor orientation, external coordination orientation and personal selling orientation. There is a significant and positive relationship between customer orientation and personal selling orientation with the marketing skills of artisan entrepreneurs in India.

The study is confined to three southern states of India and weaving villages known for their endemic product specifications.

The study found significance in orienting artisan entrepreneurs of developing countries and equipping them with desired skills to meet the changing dynamics of the market and meet their livelihood needs. The study further supports policymaking in strengthening the capability of artisans to enter the market without mediators.

The model provides insight into other unorganized sectors to formulate innovative approaches to strengthen marketing skills and entrepreneurial ability.

As an exploratory study, examining individual-level market orientation as an innovative approach and their relationship with marketing skills among artisan entrepreneurs was unexplored in several unorganized sectors, including handlooms.

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.

This study aims to identify and prioritize barriers to corporate social responsibility (CSR) in the construction sector.

A literature review was first conducted to identify barriers to CSR performance. After that, construction professionals were invited to validate the appropriateness of the obstacles. The discussion allowed the establishment of a list of barriers to CSR performance and their corresponding categories. Data collected from the survey were then analyzed to prioritize the importance of these barriers by the fuzzy DEMATEL-based ANP (DANP) technique.

The findings presented 16 barriers to CSR, which were categorized into four clusters. The fuzzy DANP analysis showed that strategic vision is the most crucial cluster, followed by the measurement system, stakeholder perspective and scarce resources. Among the sixteen barriers examined, lack of awareness, knowledge and information of CSR; low priority of CSR; lack of metrics to quantify CSR benefits; lack of guidelines and coherent strategies; and lack of CSR enforcement mechanism are the five most crucial barriers.

This study is one of the first that proposes a comprehensive model to prioritize barriers to CSR performance of contractors considering their interrelationships. It provides construction stakeholders with a framework for understanding the linkage between the barriers and CSR framework under the umbrella of stakeholder theory. Thus, the findings might assist construction practitioners and academics in fostering the success of CSR implementation.