Textile Supply Chain Research Articles

The role of marketing in sustainable textile supply chains

The role of marketing in sustainable textile supply chains

Energy consumption modeling in industrial sewing operations: A case study on carbon footprint measurement in the apparel industry

In the textile supply chain, the apparel manufacturing industry heavily relies on energy consumption (EC), contributing to greenhouse gas emissions. Understanding and optimizing energy usage in apparel manufacturing is crucial for sustainable and energy-efficient manufacturing. The EC in the industrial sewing operations is directly linked with sewing parameters, including fabric seam length, standard sewing speed, and stitching time. In general, the carbon footprint of an apparel industry is measured by considering the standard minute value (SMV) and specific energy consumption (SEC). However, these metrics include non-productive time and do not accurately measure actual EC or assess the industry’s carbon footprint. To address these limitations, this case study tackles this technical issue by calculating the stitching time of an industrial sewing machine based on its actual EC derived from the sewing machine’s motor power. This study employs EC modeling for industrial sewing parameters, including fabric seam length, standard sewing speed, and stitching time. This proposed model utilizes real-time data collected during the garment-making process, including fabric spreading, cutting, sewing, and ironing. The study allocates eleven sewing machines for a specific garment style to stitch a basic knit fabric t-shirt. The total EC for the entire garment-making (t-shirt) process at a single line is 0.1052 kWh, equivalent to 59.97 g of CO2 emissions (Bangladesh’s CO2/kWh emission factor). This study explores that a direct-drive servo motor consumes approximately five times less than its maximum motor load power, making it more energy-efficient than other sewing machines. Therefore, this study demonstrates the effectiveness of EC modeling by incorporating industrial sewing parameters and selecting energy-efficient sewing machines to reduce carbon footprints and enhance environmental sustainability in the apparel manufacturing industry.

Fuzzy Analytic Hierarchy Process (FAHP) Based Performance Assessment of Textile Industry in Tirupur

Abstract: This study explores the use of Fuzzy Analytic Hierarchy Process (FAHP) to evaluate and prioritize criteria in supply chain management within the textile industry of Tirupur district. Utilizing a detailed questionnaire reviewed by experts with over 30 years of industry experience, the study conducted pairwise comparisons of key criteria: cost (C1), quality (C2), time delivery (C3), and management and organization (C4). By applying FAHP, which effectively handles uncertainties in decision-making, the study determines the relative importance of these criteria. The findings provide a structured method for improving decisionmaking in textile supply chain operations, integrating fuzzy logic with the traditional AHP framework to enhance the management and optimization of supply chain processes.

Enhancing environmental sustainability in Asian textile supply chains: insights from agile practices and mediating variables

The current energy crisis has shown all states that energy from renewable sources can be a determining factor in the states’ sustainable development. Several papers have studied the relationship between renewable energy consumption and economic development, finding various situations, but there is no consensus. Thus, this study aims to first investigate the causal relationship between economic growth and total and sectoral renewable energy consumption (European Union and each Member State, for 2004–2020) by testing various linear and non-linear regressions to choose the fit model. Second, the investigation extends to analysing the impact of renewable energy consumption by sector on economic development. A hybrid approach is used, namely structural equation modelling and artificial neural networks. The study findings indicate the effect and the meaning (directly or inversely) exerted by the three sectoral components on economic growth, with different intensities from one country to another. There is a significant influence on the consumption of renewable energy in the heating and cooling sectors and transport on gross domestic product at the European Union level and for most member states. Based on the obtained results, a series of theoretical, practical, and political implications are provided.

Environmental Sustainability Analysis of Rotary-Screen Printing and Digital Textile Printing

Worldwide concern regarding the need for more sustainable textile supply chain prompted emphasis on innovation in the coloration process, often considered the most problematic segment of the supply chain. Digital textile printing, an emerging coloration technology, has the potential to improve sustainability significantly. This study undertakes an environmental sustainability analysis that compares the impacts of rotary-screen printing, the traditional, more established printing method, and digital textile printing. Researchers partnered with Creditex S.A.A., a vertically integrated textile company from Peru, to perform the research in a realistic factory setting. Creditex printed a 16-color design for an order of 1000m cotton fabric with reactive dye occupying both rotary-screen printing and digital textile printing and collected environmental impact data throughout the production process, including consumption, usage, and wastage. The findings suggest that digital textile printing is favorable to rotary-screen printing in terms of environmental sustainability impacts within the research context.

Textile offshoring along global value chains (GVCs): Impacts on employment and gender wage gaps

Globalization has a significant impact on the international distribution of production, which in turn affects the global distribution of employment and income. Yet, previous studies have often overlooked the gender implications associated with the evolution of global value chains (GVCs). In this context, the textile sector is considered critical for explaining the most recent trends in female employment, particularly in developing countries.The main objective of this paper is to examine the impacts of textile offshoring on female participation in the labor market and on gender employment and wage gaps between 1991 and 2019. Specifically, it aims to understand prior premises as the expected increase in female workers due to the delocalization of the sector, the implications of these premises when countries begin to upgrade and their role in reducing gender inequalities.To achieve this, we devised a multi-sectoral and multi-regional input-output (MRIO) model with a high level of disaggregation of 189 countries and 26 sectors, expanded to include male and female jobs and wages by sector and country. We also conducted a structural decomposition analysis (SDA) on the forces driving the evolution of gender gaps.Our findings show that the gender employment gap grew in the global textile sector between 1991 and 2019, caused primarily by the role played by China and India in the textile supply chain. Gender wage gaps continue to linger, however, despite having narrowed in most of the countries analyzed.

Leveraging Lean and Green Supply Chain Practices for Sustainable Supply Chain Performance: The Moderating Role of Environmental Orientation

Abstract This study investigates the impact of lean and green supply chain practices on business process performance and sustainable supply chain performance. The research utilises the resource-based view (RBV) theory to construct a conceptual model wherein lean and green supply chain practices are employed to augment business processes and sustainable performance. Concurrently, dynamic capabilities theory is applied to signify an organisation’s capacity to adapt and evolve in response to internal and external pressures from customers and competitors. The conceptual model is validated using structural equation modelling with a sample of 170 supply chain practitioners from the apparel and textile supply chain in Jordan. Results indicate that lean practices exhibit no direct impact, whereas green practices significantly influence business process performance and indirectly affect sustainable supply chain performance. Business process performance does not mediate the relationship for lean practices, but it does so for green practices. Moreover, the environmental orientation of both competitors and customers negatively moderates the impact of green practices on business processes and sustainable supply chain performance. These findings contribute to existing literature and underscore the crucial role of green supply chain practices in enhancing sustainable supply chain performance in the apparel and textile industry.

Effluent wastewater technologies for textile industry: a review

Abstract The textile industry contributes significantly to the expansion of the world economy, however, it is also notorious for producing large amounts of trash and harming the environment. Effective waste management techniques depend on having a thorough understanding of the forms and makeup of waste from the textile sector. The objective of this paper is to study effluent wastewater technologies to efficiently treat and control the wastewater produced during textile production operations. It is well known that the textile industry generates vast amounts of wastewater, some of which may be contaminated with heavy metals, chemicals, dyes, and organic compounds. This effluent can have serious negative effects on the environment if it is not adequately treated, including contaminating soil and water sources, removing aquatic life, and possibly endangering human health. Due to the inclusion of dyes, heavy metals, and other chemicals, the discharge of untreated or improperly treated effluent from textile processes leads to water contamination. Textile waste can leak hazardous compounds into the environment and contaminate the soil, both of which have an impact on air quality. The environmental impact of the textile industry is further exacerbated by the energy and resource use involved in production. At several points in the textile supply chain, waste is generated. Fibre trimmings, fly waste, and yarn waste are produced during the fibre production, spinning, and weaving operations. There are numerous ways and technologies for treating wastewater, including advanced oxidation processes (AOPs), biological treatment systems, and membrane-based technologies. The formation of eco-friendly materials and advancements in recycling technology help to make the textile industry more closed-loop and sustainable. In conclusion, managing waste from the textile sector is a significant environmental concern that calls for creative solutions and environmentally friendly procedures.

Unravelling the critical success factors for resilient supply chains – insights from the textile industry of Pakistan

This study focuses on developing a theoretical framework for the Resilient Supply Chain for analysing the various types of resilience and the role-play of different managerial levels in developing them effectively. Data is collected from the textile sector of Pakistan with the aid of semi-structured interviews, which were done with employees from different managerial levels. Analytical Hierarchy Process (AHP) was used to define the importance of the multiple Critical Success Factors (CSFs) which were derived from an extensive literature review. The identified CSFs are categorized into Ecological, Engineering, Evolutionary, and Technological resilience. The weight of each criterion and their cause- effect relationships are determined. The findings reveal that the Use of Modern Technology holds the highest weightage at 24.1%, followed by the Development of Effective SCM Strategy (14.6%) and Reliable Supplier Development (9.6%). Additionally, the study establishes connections between the CSFs and different managerial levels (Tactical, Strategic, and Operational), facilitating employee understanding of their roles in mitigating disruptions and fostering resilient supply chains. Overall, this research offers a comprehensive framework for enhancing Textile Supply Chain resilience, providing practical insights for improving operational performance and addressing industry challenges.

Accounting information sharing within buyer-supplier collaborations: Insights from a developing country

Background: The significance of the context, or the environment, is pivotal in influencing the practices of management accounting.Objectives: This article aims to explore the significance, methods and challenges of accounting information exchange in buyer–supplier collaborations.Method: In buyer–supplier collaborations, data are gathered from 13 semi-structured interviews and 250 questionnaires. The analysis is conducted using SPSS version 25, employing non-parametric Kruskal–Wallis test and content analysis techniques.Results: Respondents recognise its benefits but prefer informal communication. Challenges such as diverse systems and mistrust hinder formal sharing. Despite obstacles, informal channels remain effective, although concerns about data leakage persist, leading to a conservative approach.Conclusion: In the Egyptian textile supply chain, members prioritise individual goals over collective ones. Informal methods, such as backdoor access, facilitate accounting information sharing among buyer–supplier partnerships. Formal sharing protocols are lacking, with limited one-way technical data exchange. Trust issues and data security concerns persist. Despite the absence of formal disclosure, cost estimations remain feasible. The company adopts a conservative approach, limiting access to records in most cases.Contribution: In essence, the article not only sheds light on the complexities and nuances surrounding accounting information sharing in the textile supply chain but also emphasises the resilience of informal communication channels in overcoming challenges. As the industry navigates these dynamics, recognising the importance of relational ties and informal exchanges could be pivotal in fostering a more efficient and collaborative supply chain ecosystem.

A Smart Manufacturing Process for Textile Industry Automation under Uncertainties

Most textile manufacturing companies in the world heavily rely on manual labor, particularly in the fabric inspection section, especially for cotton fabric. Establishing smart manufacturing systems like industrial automation in the textile industry for cotton fabric inspection is important for error-free inspection. The proposed make-to-order (MTO) inventory model focuses on the strategic development of a supply chain network under fuzzy uncertainty. The distinctiveness of this research lies in integrating a methodology that involves human and machine interaction, along with allocating resources to investment in smart manufacturing. This article presents a case study of the Jagatjit Cotton Textiles (JCT) manufacturing company in Punjab, India, as an example to validate the model and check the performance of SMT in the fabric inspection process in cotton TC mills. This paper contributes by developing four distinct textile supply chain models with industrial automation under triangular and trapezoidal fuzzy demand. A numerical analysis is conducted to verify the effectiveness of installing automated fabric inspection machines in the cotton plant. This article proposes an iterative solution algorithm (KDPMG) to obtain the global optimum for the proposed model. A comparative study of the proposed algorithm, KDPMG, and the genetic algorithm (GA) is presented in this study to verify the credibility of the obtained results. It is observed that KDPMG provides more appropriate solutions to the problem compared to the GA. Moreover, the computational time of KDPMG is significantly less than that of the GA. The rigorous analysis reveals that maximum profit can be achieved under trapezoidal fuzzy demand with fully automated fabric inspection technology. Using a triangular fuzzy demand pattern, the model with fully automated smart manufacturing achieves an 8.62% higher profit compared to a traditional system. Similarly, in the case of a trapezoidal fuzzy demand pattern, the adoption of automation in cotton plants can achieve an 8.69% higher profit. Hence, the implementation of smart manufacturing systems in the mending section of the cotton textile industry proves to be more profitable compared to the traditional inspection process.

Digitalization in logistics for textiles – possible fields of application for the Blockchain technology

The globalized supply chains of textiles and clothes involve multiple parties from different countries. Flows of goods, information and finances are coordinated through logistic processes, but offer potential for optimization in terms of digitalization and transparency. Incidents of the past prove that fundamental human rights standards and occupational safety are not met in global production countries yet. Legal regulations like the Act on Corporate Due Diligence Obligations for the Prevention of Human Rights Violations in Supply Chains (LkSG) shall help to improve the situation since 2023. Especially small and medium sized enterprises (SME) in Germany, to which the law applies indirectly through private-sector contracts from their non-SME consignees, struggle to control their global supply chain, to provide all necessary data and to ensure a traceable, fraud-resistant and manageable flow of information. Hence, the Center Textile Logistics investigated the potential of the Blockchain technology and its application possibilities for textile supply chains. The Blockchain technology offer chances in terms of securing clothing trademarks, proofing that standards of seals and certificates are met, proofing that political and legal regulations are met and in terms of controlling global processes that involve international suppliers and partners. However, the current state of the art of digitalization is often too low to directly apply the Blockchain technology and has to be improved first. The cost-benefit ratio has to be evaluated individually but the Blockchain technology offers great potential to rise transparency, ease communication and critical data exchange along textile supply chains.

Atmospheric plasma technology for sustainable wet processing of textiles

Nowadays, the preservation of the environment is one of the top priorities of scientists and researchers which drives them to innovate and develop eco-friendly methods and processes. The textile industry is considered one of the most water consumption industries due to the water they need for preparation and finishing operations. The wet processing of textiles is a complex and resource-intensive stage in the textile supply chain. While it allows for the creation of vibrant and functional textiles, it has associated environmental challenges, such as water pollution, chemical usage, and high energy consumption. In response to these challenges, sustainable alternatives like atmospheric plasma technology are being explored to reduce the environmental impact of wet processing in the textile industry. For textile fields of application, fundamentally only 'cold plasma' and in particular the corona and glow discharge are of interest. Plasma treatment generally takes place in dry conditions; thus, the fibres are not swollen. The changes in properties induced by plasma treatment are therefore restricted to the surface only.This review aims to highlight the effects of plasma treatment technology on textiles and the potentiality of considering it as an alternative to conventional wet processing (desizing, bleaching, etc.). Types of plasma, techniques, applications, advantages, and disadvantages are mentioned. The water consumption and the environmental impact are discussed.Plasma modification of textiles saves large quantities of water, chemicals, and electrical energy, which is made possible since the plasma process does not produce large volumes of waste or toxic by-products.

Wool Agro-Waste Biomass and Spruce Sawdust: Pellets as an Organic Soil Amendment

The production of wool is an economic burden and an issue for sheep breeders in many countries of the European Union because shorn greasy wool is defined as an animal byproduct (category 3) and must be sent to landfill as a special waste if not addressed in the textile supply chain. Nevertheless, wool is an important source of nitrogen, with high potential as agricultural renewable and sustainable organic fertilizer. To apply wool to soil, any contamination from harmful bacteria (e.g., Listeria monocytogenes and Salmonella spp.) should be excluded. In this study, we developed sheep wool pellets to test their suitability for use as an organic fertilizer. Wool was rich in N (12% of dry material) and was mixed to spruce sawdust at sawdust: wool ratios of at 2:1; 1:1 (v/v) to increase soil organic carbon. Despite the different mix of wool and sawdust, pellets were similar in size (diameter and length), and the content of the elements suited the requirements of fertilizers and did not present harmful bacteria after pelletization. Therefore, wool pellets may represent a feasible solution to provide sheep wool with an added value, introducing it in a circular economy process. However, further study is needed to test the effects of the produced fertilizing pellets in real cropping systems.

Input–output analysis as guidance for the Brazilian textile supply chain

Input–output analysis as guidance for the Brazilian textile supply chain

Navigating Sustainability through Greenhouse Gas Emission Inventory: ESG Practices and Energy Shift in Bangladesh’s Textile and Readymade Garment Industries

As the world's demand for textiles and clothing rapidly increases, this industry's greenhouse gas (GHG) emissions are becoming a major environmental concern. Bangladesh, a key player in the global textile supply chain and one of the top producers, contributes significantly to these emissions. However, accessible data on activity and GHG emissions, crucial for researchers, the private sector, and policymakers in decision-making, is scarce. To address this gap, this study combines a detailed field survey with expert interviews to establish a comprehensive emission inventory. This inventory aims to identify hotspots and facilitate the adoption of effective mitigation strategies. Focusing on a prominent industrial zone's textile and readymade garments (RMG) industries, the research employs a mix of top-down and bottom-up approaches and follows the IPCC guidelines to develop a GHG emission inventory for 2022. The study evaluates various emission sources, including scope 1 (onsite fuel combustions), scope 2 (grid electricity usage), and scope 3 (waste and wastewater treatment). In the total emissions (6043.5 Gg CO2eq.), textile and RMG industries contribute 67.8% and 32.2%, respectively, with scope 1 emissions dominating at 85%. Notably, scope 2 emissions exhibit significant uncertainty (−10.4% to +11.9%), largely due to variations in national grid emission factors. This study forecasts GHG emissions until 2030, considering current trends (26 thousand Gg CO2 eq.). It also explores various energy mix scenarios, factoring in the depletion of existing natural gas reserves (ranging from 8 thousand to 33 thousand Gg CO2 eq.). This study delves into the impact of the Environmental, Social, and Governance (ESG) system on industries' GHG emissions. Besides improving worldwide emission databases and identifying hotspots, this research aims to promote a sustainable transition in both Bangladesh and other developing textile manufacturing nations across the globe.

Determine the impact of COVID-19 on the textile supply chain management

The textile supply chain is also affected by the COVID-19 epidemic, as thousands of supply chains worldwide. The textile industry is labour-intensive in structure and interconnected globally. The COVID-19 epidemic resulted in order cancellation and delays in manufacturing orders in the textile supply chain. The shortage of raw materials is another issue due to the closing of international seas and airports. During this epidemic, the textile industry became less important for the world's people as their 1st priority was to survive by purchasing only essential items. Data was collected from employees and industries primarily related to the textile industry. Data analysis was done using factor analysis and regression models. It was also found that most organizations and businesses faced the radical consequences of COVID-19 on textile supply chain management, including working capital, customer demand, and future marketing drives to pursue new customer orders. However, most companies have adopted digitalized systems to run out of production and purchasing.

Decarbonization practices in the textile supply chain: Towards an integrated conceptual framework

The textile industry is a significant source of global greenhouse gas emissions; therefore, it is crucial to implement decarbonization measures throughout the supply chain (SC) to reduce carbon emissions and achieve sustainable development. However, there exists a lack of systematic review regarding decarbonization in textile SCs. The objective of this review is to identify themes related to decarbonization in textile SCs, address research gaps, and propose an integrated framework. To do this, we conducted a systematic literature review of 68 identified papers discussing decarbonization in textile SCs. Based on descriptive and thematic findings, we have developed a comprehensive conceptual framework that synthesizes antecedents, decarbonization practices, influential factors, and outcomes within the context of textile SCs. Furthermore, our review highlights current research gaps and recommends future directions for studying decarbonization in textile SCs. By providing the first comprehensive framework for addressing decarbonization across all stages of the textile SC process, this review contributes significantly to the existing literature.

A conceptual framework for the operations planning of the textile supply chains: Insights for sustainable and smart planning in uncertain and dynamic contexts

Recent practices in textile supply chains (SC) show a growing concern for sustainability not only in its economic dimension, but fundamentally in its environmental and social ones. One of the key management processes that affect sustainability is the SC operations planning since its fundamental role in achieving a balance between supply and demand in a sustainable manner. Moreover, in an uncertain and dynamic environment such as the textile sector, it is necessary to provide a certain learning capability to the operations planning techniques used to increase the speed and quality of response of the textile SC to unexpected situations. In this context, mathematical programming models, heuristics and artificial intelligence techniques have proven their validity to achieve sustainable, robust and smart supply chains. Despite their potential, neither a conceptual framework (CF) nor a literature review have been detected to support the development and study of such models in the textile supply chain operations planning. In view of these gaps, this paper proposes a CF for supporting the sustainable and smart operations planning of the textile supply chains in a dynamic and uncertain context based on a set of dimensions, categories and elements that reflect the specific characteristics of the textile sector. Firstly, a tentative CF is predefined based on other generic works on SC operations planning in uncertain context and the own authors’ knowledge. Secondly, a structured literature review based on this CF has been made resulting, at the same time, in the updating of some of its dimensions, categories and elements to reflect some textile specific characteristics. Consequently, the CF is not only predefined but also logically derived from the literature analysis. The results of the literature review show that there is a great opportunity to contribute to making textile supply chains more sustainable, smart, flexible, robust and resilient in dynamic and uncertain environments.

A new mathematical model integrating the carbon tax and horizon planning to optimize the textile and clothing industry supply chain

Energy costs have surged significantly in recent years across various regions of the world. This inflation has a direct impact on households and businesses, by increasing production costs. It risks slowing the global economic recovery by reducing purchasing power and consumption. This study presents a new mixed-integer non-linear programming (MINLP) model with the objective of cost minimization within the direct supply chain of the textile and clothing industry. To consider different aspects in our study, the cost function is decomposed to the supply, production, energy, transportation, storage, and carbon tax emissions costs. It deals also with the management of multiple energy sources (specifically, electricity for production and fuel for transportation). This model simultaneously incorporates several critical factors, including life cycle assessment, carbon tax emissions, and planning horizon. To do this, a product’s carbon emissions are quantified from raw material extraction through to the finished product, and three different planning horizons as long term t=∞, medium term t=3 month, and short term t=1 month are considered to evaluate their impacts on the costs and emissions values. A shorter planning horizon leads to increased costs and reduced emissions reductions compared to a medium or long-term planning horizon. Additionally, the study introduces a new benchmark based on real-world data available in the literature, which serves as a valuable tool for evaluating strategic and tactical planning issues within textile supply chains. To evaluate the performance of our proposed model, we defined three different size of the problem by changing the number of factories, suppliers, production sites, warehouses and customers.The study’s findings reveal that, over a medium and long-term planning horizon, there is an average cost increase of about 2% for different problem sizes, when considering a carbon tax ranging from 44.6€ to 86.2€ per tonne of emissions. When a higher carbon tax is applied, the total cost increases, while the carbone emissions and subcontracting activities will be decrease.