Issue 3 / 2026 
Inner covers
Article: China’s textile export potential to South Asian countries and its determinants
Authors: DEVI LIQIN WEN, JIE XU, WENXUE ZOU, XUE LEI, SHENGLIN MA
Pages: 355–372
DOI: 10.35530/IT.077.03.202562
Published online: June 2026
Abstract
Against the backdrop of the Belt and Road Initiative and the restructuring of the global textile supply chain, this paper
analyses textile trade patterns between China and the seven South Asian countries, using China’s textile export data to
these countries from 2010 to 2023, with a focus on textile exports. It employs a stochastic frontier gravity model for
empirical analysis to assess the potential and influencing factors of textile trade between China and the seven South
Asian countries, and provides feasible suggestions for the development of textile trade between China and South Asian
nations. The study finds that the scale of textile trade between China and South Asian countries has been expanding,
with trade relations becoming increasingly close. However, the scale of imports and exports remains relatively small. In
terms of influencing factors, the study finds that China’s economic size has a significant inhibitory effect on textile
exports. In contrast, China’s population size, the economic development level and population size of South Asian
countries, as well as straight-line distance and whether they share a common border, have a positive impact on textile
exports. However, the influence of the Shanghai Cooperation Organisation on China’s textile exports is relatively weak,
with limited promotional effects; government efficiency indices, free trade agreements, currency flexibility, and economic
freedom scores all have a positive promotional effect on textile export efficiency. However, trade freedom has a negative
impact on trade efficiency; although China’s textile export trade efficiency with the seven South Asian countries remains
at a relatively low level, there is significant trade potential and room for expansion, with broad prospects for future
development.
Keywords: China, South Asia, textiles, stochastic frontier gravity model, export trade efficiency
Citation: Wen, L., Xu, J., Zou, W., Lei, X., Ma, S., China’s textile export potential to South Asian countries and its determinants, In: Industria Textila, 2026, 77, 3, 355–372, https://doi.org/10.35530/IT.077.03.202562
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Article: Enhancing textile industry efficiency using data mining and business intelligence for optimal supply chain management
Authors: P. VIJAYALAKSHMI, MANIMARAN S, KISHORE KUNAL, VAIRAVEL MADESHWAREN
Pages 373–381
DOI: 10.35530/IT.077.03.202554
Published online: June 2026
Abstract
In the modern textile industry, the integration of Business Intelligence (BI) through advanced Business Analytics (BA)
and Data Mining (DM) techniques is crucial for enhancing supply chain management, optimising production efficiency,
reducing operational costs and improving market responsiveness. By using data-driven decision-making techniques,
clothing manufacturers can improve their production planning, inventory control and demand forecasting. Nonetheless,
the textile industry frequently faces challenges such as unstructured data supply chain inefficiencies and unpredictable
market trends, which can lead to increased waste and production delays. This study’s main goal is to create a Pythonbased
analytical framework that makes use of data mining methods to improve business intelligence and optimise
production processes in the clothing industry. Over six months, production data quality control records and supply chain
information were collected from three textile manufacturing facilities located in Trippur from SouthIndia. The gathered
dataset was meticulously analysed using Python-based tools, including Pandas, Scikit-learn, and TensorFlow. Various
techniques, such as clustering classification, association rule mining and predictive analytics, were employed to extract
valuable insights. The research tested four key hypotheses that concentrated on production efficiency, demand
prediction, raw material utilisation, and inventory optimisation. Machine learning models were applied to identify
production bottlenecks, forecast sales trends and enhance inventory planning. The study’s conclusions offer practical
suggestions for raising operational effectiveness and profitability in the textile industry. Overall, this research highlights
the transformative potential of business analytics in revolutionising textile manufacturing, fostering data-driven growth
and strengthening competitiveness in the industry.
Keywords: textile industry, business intelligence, data mining, predictive analytics, Python, supply chain optimisation
Citation: Vijayalakshmi, P., Manimaran, S., Kunal, K., Madeshwaren, V., Enhancing textile industry efficiency using data mining and business intelligence for optimal supply chain management, In: Industria Textila, 2026, 77, 3, 373–381, https://doi.org/10.35530/IT.077.03.202554
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Article: Optimising ancient costume image generation using the stable diffusion model: a focus on dynastic characteristics
Authors: JIAN HUA, ZHI LI, rUIHONG CHEN, YU CHEN
Pages 382–389
DOI: 10.35530/IT.077.03.202570
Published online: June 2026
Abstract
The source of the generated images of ancient costumes is misplaced because the process of generating ancient
costume effect images cannot accurately capture the distinctive features of different dynasties. By leveraging the Stable
Diffusion model, this study organises costume characteristics across different dynasties into 163 textual prompts,
drawing on historical literature and classical scrolls. By matching these prompts with image feature vectors, a new token
embedding layer V* is introduced, which is optimised together with the cross-attention layer parameters Wk and Wv.
Then, the model was fine-tuned using the Low-Rank Adaptation (LoRA) model to reduce training costs while maintaining
historical fidelity. The results demonstrate that the optimised model can generate costume images that align with the
corresponding dynastic and ethnic characteristics based on textual prompts. Validation experiments across the Tang,
Song, and Ming dynasties show that the model achieves relatively low Kernel Inception Distance (KID) and Maximum
Mean Discrepancy (MMD) values, indicating its effectiveness in generating ancient costume images. This study not only
optimises the generation of ancient costume effect images but also holds reference value for the digital preservation and
protection of costume cultures from other dynasties and ethnic regions.
Keywords: ancient costumes, image generation, intelligent design, stable diffusion model, text-to-image
Citation: Hua, J., Li, Z., Chen, R., Che, Y., Optimising ancient costume image generation using the stable diffusion model: a focus on dynastic characteristics, In: Industria Textila, 2026, 77, 3, 382–389, https://doi.org/10.35530/IT.077.03.202570
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Article: Research on the recycling of sulfuric acid waste liquid in textile composition detection based on the ISO 1833-11 standard
Authors: GUANJIE CHEN, YU ZHANG, DAN ZOU, BEI CHENG, SHUANGYING ZHA, CHEN YANG
Pages 390–408
DOI: 10.35530/IT.077.03.2025119
Published online: June 2026
Abstract
In the field of textile quantitative component analysis, the 75 wt% sulfuric acid solution dissolution method, a globally
adopted standard, generates substantial acidic waste solution, imposing both environmental burden and economic
costs. To address this, this study selected white knitted fabric (cotton/polyester blended fabric) and red knitted fabric
(viscose/polyester blended fabric) as research subjects based on ISO 1833-11, conducting experiments with 0–8 cycles
of waste liquid recycling to compare dissolution efficiency, residual fibre morphology, and quantitative determination
results between fresh and recycled dissolution agents. Results indicated that within eight reuse cycles, the measurement
deviation between fresh and recycled acid remained minimal, with relative deviation generally below 2%, while microscopic
observation confirmed structurally intact polyester fibres in residues across all cycles, though minor surface
deposits emerged only after higher cycle counts without significantly affecting quantitative outcomes. Further assessment
revealed that this recycling strategy could reduce acid consumption and waste discharge by approximately 80%, offering
both environmental benefit and economic benefit, thereby validating the feasibility of multi-cycle waste liquid recycling
of concentrated sulfuric acid in textile detection and providing a practical foundation for green testing laboratories.
Keywords: textile detection, quantitative chemical analysis, sulfuric acid method, waste liquid recycling, sustainability
Citation: Chen, G., Zhang, Y., Zou, D., Cheng, B., Zha, S., Yang, C., Research on the recycling of sulfuric acid waste liquid in textile composition detection based on the ISO 1833-11 standard, In: Industria Textila, 2026, 77, 3, 390–408, https://doi.org/10.35530/IT.077.03.2025119
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Article: The impact of sales promotions on consumers’ purchasing behaviour in the clothing industry
Authors: SIMONA TRIPA, LUCIA ADRIANA PANTEA, FLORIN TRIPA
Pages 409–415
DOI: 10.35530/IT.077.03.202587
Published online: June 2026
Abstract
The fashion industry reflects global economic, technological, and cultural transformations, and consumer behaviour
regarding clothing purchases is strongly influenced by these dynamic forces. In today’s highly digitalised and competitive
market, consumers are more informed, more demanding, and increasingly aware of the social, environmental, and
economic implications of their purchasing decisions. They have access to an unprecedented variety of products, and
the rise of e-commerce has significantly shaped their preference for convenience, speed, and personalisation. A growing
number of consumers prefer quick, online purchases and are attracted to promotions and special offers that provide
value for money. In this context, promotional strategies and discount campaigns have become essential tools for fashion
retailers, helping them attract new customers, retain existing ones, and stimulate demand in an oversaturated market.
These strategies include seasonal sales, “buy two, get one free” offers, flash sales, discount coupons, and loyalty
programs. The study on the impact of promotions on consumer behaviour in the clothing sector highlighted aspects
related to consumer preferences based on place of residence, level of education, gender, and income. The key factors
influencing the decision to purchase clothing were identified, as well as the impact of discounts and special offers on
this decision – all of which provide valuable insights for marketing professionals operating in the fashion industry.
Keywords: promotions, consumers, clothing, fashion, marketing
Citation: Tripa, S., Pantea, L.A., Tripa, F., The impact of sales promotions on consumers’ purchasing behaviour in the clothing industry, In: Industria Textila, 2026, 77, 3, 409–415, https://doi.org/10.35530/IT.077.03.202587
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Article: Textile materials for transdermic therapy in neurocognitive disorders
Authors: DIANA ANDREEA PLACINTĂ, MIRELA BLAGA, ROMEO PETRU DOBRIN, ANA-RAMONA CIOBANU
Pages 416–423
DOI: 10.35530/IT.077.03.2025137
Published online: June 2026
Abstract
Neurocognitive disorders are a group of conditions that affect already developed cognitive abilities such as memory,
learning capacity, perception, attention, and language. Excluding delirium and amnestic disorders, dementia is currently
the seventh leading cause of death, with ten million new patients diagnosed annually. Patients with dementia, especially
those with Alzheimer’s disease, sooner or later develop neuropsychiatric symptoms that, along with the disease itself,
place a significant burden on caregivers and society. Developing alternative methods of drug administration compared
to traditional routes (oral, intravenous, intramuscular, inhalation) is essential to increase patient compliance and quality
of life. Transdermal drug delivery via patches has become a convenient alternative to other administration routes,
evolving from basic patches that simply store and release an active substance to smart and personalised patches that
can incorporate sensors and various technologies, allowing them to adjust drug release according to the patient’s needs
in real time. However, challenges related to precise drug release, adhesion stability, and uniform diffusion control still
remain. Unfortunately, for neurocognitive disorders, there are few patches available on the market, highlighting the need
for further research. This paper aims to analyse neurocognitive disorders, from symptoms to new approaches using
medical textiles in the form of medical patches for transdermal drug delivery.
Keywords: Alzheimer’s disease, dementia, medical textiles, transdermal patch
Citation: Plăcintă, D.A., Blaga, M., Dobrin, R.P., Ciobanu, A.R., Textile materials for transdermic therapy in neurocognitive disorders, In: Industria Textila, 2026, 77, 3, 416–423, https://doi.org/10.35530/IT.077.03.2025137
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Article: Equity structure, incentive and constraint mechanisms, and corporate agency costs: An empirical study of listed companies in China’s textile industry
Authors: GUANG CHEN, C.S NAJIB DAFIA, SONG KANG
Pages 424–431
DOI: 10.35530/IT.077.03.202540
Published online: June 2026
Abstract
Equity structure forms the basis of governance, while incentive and constraint mechanisms represent its core. Together,
they constitute a comprehensive corporate governance system. This study uses data from listed textile firms in China’s
Shanghai and Shenzhen A-share markets (2013–2024) to construct incentive and constraint mechanism indices via
principal component analysis. It explores how equity structure and these mechanisms affect agency costs and examines
their interrelationships. Results show that equity structure, incentive mechanisms, and constraint mechanisms all
significantly reduce agency costs, with incentives being the most effective. There are complementary effects between
equity structure and incentive mechanisms, and substitutability between equity structure and constraint mechanisms, as
well as between incentive and constraint mechanisms. Robustness checks confirm the reliability of these findings.
Based on these results, we recommend deepening equity-based incentive reforms, improving diversified monitoring
systems, and integrating governance mechanisms to maximise marginal governance efficiency. This study not only
provides a systematic theoretical foundation and actionable practical solutions for optimising corporate governance in
textile enterprises, but also offers a transferable analytical framework to inform governance practices in other sectors.
Keywords: corporate agency costs, equity structure, constraint mechanism, incentive mechanism, China’s textile industry
Citation: Chen, G., Najib Dafia, C.S., Kang, S., Equity structure, incentive and constraint mechanisms, and corporate agency costs: An empirical study of listed companies in China’s textile industry, In: Industria Textila, 2026, 77, 3, 424–431, https://doi.org/10.35530/IT.077.03.202540
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Article: Research on an artificial intelligence (AI) cross-sectional quantitative analysis method for cotton and regenerated cellulose fibre blended fabrics
Authors: ZHENGHAI LI, YUJUE WANG, ZHENZHU ZHANG, GUANJIE CHEN, YONGFENG LI, CHEN YANG
Pages 432–444
DOI: 10.35530/IT.077.03.202589
Published online: June 2026
Abstract
This study addresses the technical bottlenecks in separating components in cotton and regenerated cellulose fibre (such
as viscose, modal, lyocell, etc.) blended fabrics using chemical methods. This study proposes a fibre cross-sectional
image segmentation and blending-ratio quantitative analysis method based on the U-Net (a U-shaped convolutional
neural network). By constructing a high-resolution image acquisition system, this study achieves automatic collection
and preprocessing of fibre cross-sectional images. Combined with the U-Net architecture, this study performs semantic
segmentation and contour extraction, allowing for the calculation of the cross-sectional area of individual fibres. Using
a density model, this study derives the mass percentage of each component. Comparative experiments were conducted
on 37 sets of cotton/regenerated cellulose fibre blended samples, showing that the average error of this AI system is
less than 2% compared to traditional manual methods and is highly consistent with the chemical dissolution method,
with a maximum error not exceeding 3%. Additionally, this method reduces the testing time for a single sample from the
traditional 60 minutes to 5 minutes, demonstrating excellent detection accuracy, efficiency, and practicality. The research
results provide a feasible path for rapid, non-destructive, and intelligent detection of fibre components, with potential for
application in textile testing laboratories and production lines.
Keywords: blending ratio, deep learning, fibre segmentation, microscopy, neural networks, U-Net
Citation: Li, Z., Wang, Y., Zhang, Z., Chen, G., Li, Y., Yang, C., Research on an artificial intelligence (AI) cross-sectional quantitative analysis method for cotton and regenerated cellulose fibre blended fabrics, In: Industria Textila, 2026, 77, 3, 432–444, https://doi.org/10.35530/IT.077.03.202589
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Article: Optimisation method for the quality of combed sliver
Authors: LI XINRONG, LIU RONGFANG, SHI SHUAIXING, WANG BIAO, LI LI
Pages 445–452
DOI: 10.35530/IT.077.03.202534
Published online: June 2026
Abstract
The quality of the sliver is a key parameter for assessing the technical level of spinning equipment. As a critical machine
in the spinning process, the sliver-quality optimisation system of the cotton comber is crucial for enhancing cotton sliver
quality. Based on the process characteristics of cotton combers, this paper proposes a new non-real-time optimisation
method for improving the evenness of combed slivers and verifies the feasibility of this method through experiments on
combed slivers. Firstly, the paper introduces a new method for optimizing sliver quality. Secondly, online sliver quality
data are collected and then processed through smoothing and correlation analysis to determine the periodic variations
in sliver quality. Next, according to the principle of sliver evenness and the open-loop control system, a model is
established between sliver quality variation and the middle roller speed. The periodic motion law of the middle roller is
then determined. Experimental results show that the method, after non-real-time processing of sliver data, reduces the
coefficient of variation (CV) of the sliver by 0.5%. Furthermore, a multi-stage speed control for the middle roller is
proposed to replace the continuously variable speed control. This reduces the requirements and cost of the control
system and still lowers the sliver CV by 0.38%. This proves that the method meets the combed sliver quality optimisation
requirements. Finally, the impact of open-loop system delay time on non-real-time processing time during actual
operation is analysed to further ensure the optimisation of roller speed regulation. This study provides a practical
technical solution and a theoretical basis for online sliver leveling in the combing process.
Keywords: non-real-time processing, open loop, comber, sliver, quality optimisation
Citation: Xinrong, L., Rongfang, L., Shuaixing, S., Biao, W., Li, L., Optimisation method for the quality of combed sliver, In: Industria Textila, 2026, 77, 3, 445–452, https://doi.org/10.35530/IT.077.03.202534
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Article: Influence of wet thermal treatment on the performance of three-dimensional weft-knitted fabrics intended for personal protective equipment applications
Authors: CRISTINA GROSU, MIRELA BLAGA, RODICA HARPA, DANIELA FARIMA, MIHAI PENCIUC, ANA RAMONA CIOBANU, MIHAELA PERDEVARA
Pages 453–460
DOI: 10.35530/IT.077.03.2025154
Published online: June 2026
Abstract
This study evaluates the influence of wet thermal treatments (washing and steaming) on the structural, comfort, and
functional properties of a set of twelve three-dimensional weft-knitted fabrics, all based on a sandwich configuration with
identical cotton outer layers and a polyester monofilament binding yarn. The experimental design considered three
machine set-up stitch cam divisions NP (13, 12, 11) corresponding to loose, medium and highly compact fabric
structures and four binding ratios of the monofilament yarn (1:1; 1:3; 1:7; 1:15). Mass, thickness, and stitch density were
measured before and after the wet thermal treatment, while air and water-vapour permeability, bursting strength,
abrasion resistance, and dimensional behaviour were determined on the finished fabrics, according to relevant
standards. Results showed that mass and stitch density increased, while thickness generally decreased after wet
thermal stabilisation. For the finished fabrics, abrasion resistance and bursting strength increased with the monofilament
binding ratio, reaching up to 15,000 cycles and 590 kPa, respectively, while air permeability showed an inverse trend,
decreasing to approximately 1,000 L/m2/s for the most compact variants. These findings highlight the role of the binding
ratio and stitch cam division of the knitting machine in defining the trade-off between comfort and protective
performance. Overall, the investigated fabrics exhibit a balanced structural and functional behaviour, indicating their
suitability as constituent layers for Category II PPE, such as gloves, workwear, jackets and vests, where mechanical
durability and breathability are required.
Keywords: sandwich knitted fabrics, wet thermal treatment, structural parameters, comfort, dimensional stability, workwear, PPE applications
Citation: Grosu, C., Blaga, M., Harpa, R., Fărîmă, D., Penciuc, M., Ciobanu, A.R., Perdevară, M., Influence of wet thermal treatment on the performance of three-dimensional weft-knitted fabrics intended for personal protective equipment applications, In: Industria Textila, 2026, 77, 3, 453–460, https://doi.org/10.35530/IT.077.03.2025154
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Article: Advancing the future of fashion: a bibliometric analysis of 3D technology in the apparel industry (2011–2024)
Authors: XIZHUO CHEN, ANDING LIU, YU HOU, BIN LI
Pages 461–475
DOI: 10.35530/IT.077.03.202544
Published online: June 2026
Abstract
The application of 3D technology in the apparel industry has accelerated significantly over the past decade, catalysing
innovations in digital design, virtual simulation, and sustainable manufacturing. This study conducts a comprehensive
bibliometric analysis of 1,079 publications (2011–2024) from the Web of Science using CiteSpace, mapping the field’s
temporal, spatial, and thematic evolution. To move beyond descriptive mapping and provide a critical interpretive lens,
we introduce a three-tier conceptual framework that structures the analysis around the Technical core layer (e.g., 3D
body scanning, virtual simulation, additive manufacturing), the Application and Integration layer (e.g., virtual try-on,
digital showrooms, Metaverse fashion), and the Macro-impact layer (e.g., sustainability, consumer behaviour, ethical
implications). Findings reveal China’s dominant role in both research output and influence, driven by its robust apparel
industry and national digitalisation policies. While significant progress has been made, persistent challenges remain,
including the fidelity-realizability gap in fabric simulation, algorithmic biases in AI-driven sizing, and interoperability
across digital platforms. Future research should prioritise enhancing simulation realism, developing standardised digital
formats, integrating multi-sensory feedback, and establishing ethical frameworks to support a more inclusive and
sustainable digital fashion ecosystem. This study offers a structured roadmap for scholars and practitioners aiming to
leverage 3D technologies for transformative impact in the global apparel industry.
Keywords: 3D technology, virtual simulation, body scanning, digital fashion, sustainability, bibliometric analysis, conceptual framework
Citation: Chen, X., Liu, A., Hou, Y., Li, B., Advancing the future of fashion: a bibliometric analysis of 3D technology in the apparel industry (2011–2024), In: Industria Textila, 2026, 77, 3, 461–475, https://doi.org/10.35530/IT.077.03.202544
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Article: Effects of elasticity distribution of sports bras on breast support and pressure comfort performance for senior females
Authors: XIAOFANG LIU, YUE SUN, XIAOFEN JI
Pages 476–484
DOI: 10.35530/IT.077.03.2025101
Published online: June 2026
Abstract
Sports bras efficient in the reduction of breast displacement (RBD) were always rated low in pressure comfort
performance. Elasticity distribution was found to be influential in RBD and pressure distribution in the under-band;
however, the effects of other parts have yet to be studied. This study aimed to investigate the effects of elasticity
distribution on RBD and pressure comfort for the optimisation of these two performances for senior females. Five sports
bras with different elasticity distribution in 5 parts (front strap, back strap, cup, back panel, and under-band) were
developed to compare with the one without elasticity distribution. 20 senior female participants were involved, and the
RBD, dynamic peak pressure and compressive feelings at four test points were measured and analysed by ANOVA. The
results indicated that Bra A, C, and E significantly improved RBD in all three directions (P<0.001), Bra D enhanced RBD
in direction Z (P<0.001), while Bra B showed no significant effect in any direction. The effect on pressure varied with the
specific placement of the test point relative to the high-Young’s modulus part of the sports bra, and the compressive
feelings of Bra A and E were below 3 at all four test points. Comprehensively, the elasticity distributions of applying
high-Young’s modulus in the front straps (Bra A) and under-band (Bra E) were ideal and typical, which significantly
enhanced RBD without inducing discomfort, and provided novel information in optimising RBD and pressure comfort for
the sports bras industry and the exercising senior females.
Keywords: senior females, sports bra, elasticity distribution, breast displacement, pressure comfort
Citation: Liu, X., Sun, Y., Ji, X., Effects of elasticity distribution of sports bras on breast support and pressure comfort performance for senior females, In: Industria Textila, 2026, 77, 3, 476–484, https://doi.org/10.35530/IT.077.03.2025101
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Article: Innovative application of batik patterns in Cheongsam design
Authors: ZHANG YU JUN, JUNG JUNG HO
Pages 485–496
DOI: 10.35530/IT.077.03.202541
Published online: June 2026
Abstract
To explore the sensory imagery differences in Cheongsam styling resulting from the combination of various batik pattern
themes, this study selected four different thematic categories of batik patterns and used commonly worn Cheongsams
as the research carrier. By integrating these elements, 24 Cheongsam research samples were developed, along with
six pairs of Kansei words forming the semantic space for evaluation. A survey questionnaire was designed to collect
consumers’ sensory evaluation of the Cheongsam samples. Subsequently, data analysis was conducted using SPSS
26.0. The results indicate that two primary Kansei factors influence the appearance of batik-patterned Cheongsams,
which were identified as the style factor and the temperament factor based on their characteristics. Different batik pattern
themes combined with Cheongsam exhibit distinct sensory imagery in their appearance. Cluster analysis further
revealed that Cheongsam samples within different clusters possess unique sensory evaluation characteristics, while
those within the same cluster show a high level of consistency in overall sensory evaluation of appearance. This study
proposes design methods and recommendations for the integration of batik patterns with traditional Cheongsam,
expanding the development path for the application of batik patterns in traditional garment design. It contributes to the
preservation and development of batik culture from the perspective of intangible cultural heritage and provides insights
into the innovative design of traditional handicrafts.
Keywords: batik, Cheongsam, factor, Kansei engineering, sensory imagery, SPSS
Citation: Jun, Z.Y., Ho, J.J., Innovative application of batik patterns in Cheongsam design, In: Industria Textila, 2026, 77, 3, 485–496, https://doi.org/10.35530/IT.077.03.202541
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Article: Performance analysis of sustainable fabrics inspired by Ottoman caftan motifs
Authors: GENCAL OZTURK RUKIYE ZEYNEP, SUNTER EROGLU NILSEN, KOCAK EMINE DILARA
Pages 497–505
DOI: 10.35530/IT.077.03.2025131
Published online: June 2026
Abstract
In this study, sustainable fabrics were developed by taking inspiration from tulips, pomegranate and carnation motifs in
the caftan patterns used in the 16th – 17th century Ottoman Empire. In fabric production, sustainable raw materials such
as PET and rPET were used for warp yarns. In contrast, polyviscose, Tencel, RO (recycled olefin), organic cotton, and
bamboo were used for weft yarns. Yarn counts, yarn strength, elongation and twist properties were analysed. After fabric
production, seam opening test, breaking strength, breaking elongation, abrasion, light fastness, abrasion resistance and
air permeability tests were performed. The structural characterisation, comfort and durability properties of the fabrics
were evaluated. The breaking strength, breaking elongation, and seam opening strength results of the RO-containing
K2 are better than those of the natural raw material-containing K1, K3, K4, and K5 fabrics. In tests on fabrics containing
natural fibres, it was observed that the K5-coded organic cotton fabric was advantageous in terms of breaking strength,
breaking elongation, abrasion resistance, and air permeability. The study revealed that K5 organic cotton fabrics
exhibited superior tensile strength, elongation, abrasion resistance, and air permeability, whereas K2 fabrics containing
RO showed better seam strength but lower abrasion resistance. All fabrics were transformed into clothing, and modern
caftan designs were made. It was concluded that many products could be developed from the patterns of caftan fabrics
by considering their usage performance with sustainable materials, and that their applicability in modern textile design
and production in different areas would become widespread.
Keywords: sustainability, pattern design, environmentally friendly, woven fabrics, caftan patterns
Citation: Öztürk Rukiye Zeynep, G., Sünter, E.N., Koçak, E.D., Performance analysis of sustainable fabrics inspired by Ottoman caftan motifs, In: Industria Textila, 2026, 77, 3, 497–505, https://doi.org/10.35530/IT.077.03.2025131
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Article: How digital factors lead to sustainability through circular economy practices: empirical evidence from the textile sector
Authors: KUN HU, WANHUA KUANG, QUANDE QIN, JIANUO WANG, MD BILLAL HOSSAIN
Pages 506–518
DOI: 10.35530/IT.077.03.202586
Published online: June 2026
Abstract
The transition toward sustainable manufacturing requires integrating digital innovation with environmental responsibility.
In the textile sector, the adoption of Industry 4.0 technologies has become essential for achieving circular and
sustainable operations. However, the mechanisms linking digitalisation to sustainability remain underexplored. This
study examines how five Industry 4.0 technologies, Big Data (BD), Smart Factory (SF), Cyber-Physical Systems (CPS),
Internet of Things (IoT), and Interoperability (IP) influence sustainability performance in China’s textile industry, with
Circular Economy Practices (CEP) acting as a mediating factor.
Adopting a quantitative, cross-sectional design, data were collected through structured questionnaires distributed to 523
professionals in textile manufacturing firms across mainland China. Using purposive sampling, firms that have either
adopted or shown interest in adopting 4.0 technologies or circular practices are selected.
The analysis conducted using Structural Equation Modelling (SEM) reveals that BD and CPS exert significant direct
effects on sustainability performance, while SF and IoT contribute indirectly through CEP. Interoperability shows no
significant impact, indicating that integration does not lead to sustainability gains unless strategically aligned with circular
principles. The results confirm that circular practices act as a key mechanism transforming digital capabilities into
environmental benefits. These outcomes highlight the strategic role of digital technologies, guided by the
Resource-Based View (RBV), in enabling a sustainable and circular transformation of China’s textile industry.
Keywords: Smart Factory, Big Data, IoT, Cyber-Physical Systems, Interoperability, Industry 4.0, circular economy, sustainability
Citation: Hu, K., Kuang, W., Qin, Q., Wang, J., Hossain, Md.B., How digital factors lead to sustainability through circular economy practices: empirical evidence from the textile sector, In: Industria Textila, 2026, 77, 3, 506–518, https://doi.org/10.35530/IT.077.03.202586
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