Issue 2 / 2025 
Inner covers
Article: Value chain analysis in technical textiles and composite materials sector: a regional case study
Authors: MEHMET KARAHAN, ALİ ARI, NEVİN KARAHAN
Pages: 147–159
DOI: 10.35530/IT.076.02.2024154
Published online: April 2025
Abstract
This study has been prepared as the value chain analysis for the Bursa Technical Textile and Composite Materials
Cluster. The study aims to identify key actors in the value chain, competencies, and areas to be developed in the cluster
ecosystem. The industrial scope of the study covers technical textiles and composite materials together, as, in many
ways, Bursa enjoys the presence of sophisticated companies and strong infrastructure to specialize further and be one
of the world’s leading centres for the industry. Industry-level value chain analysis detailed each value chain process in
terms of its main competencies and development areas. The value chain analysis reviewed the parameters of the
Diamond Model to form the basis of a strategic vision for the future. Based on the findings, the report has an early-stage
action plan for the cluster management team to undertake steps in the very short term, which can go hand in hand with
the strategic development stage.
Keywords: composite materials, technical textiles, value chain analysis, Bursa
Citation: Karahan, M., Ari, A., Karahan, N., Value chain analysis in technical textiles and composite materials sector: a regional case study, In: Industria Textila, 2025, 76, 2, 147–159, http://doi.org/10.35530/IT.076.02.2024154
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Article: Detection of garment manufacturing defects using CFPNet and deep belief network: an image-based approach
Authors: DENNISE MATHEW, N.C. BRINTHA
Pages 160–170
DOI: 10.35530/IT.076.02.2024140
Published online: April 2025
Abstract
The demand for high-quality items and the quickly shifting economic landscape increase the importance of ready-made
garment manufacturers in providing the correct quality product. It is difficult work in the textile industry since the efficacy
and efficiency of automatic flaw identification determine the quality and cost of every textile surface. In the past, the
textile industry used manual human efforts to find flaws in the manufacturing of clothing. The main downsides of the
manual garment fault identification technique include lack of concentration, human tiredness, and time requirements.
Applications based on digital image processing and computer vision can overcome the aforementioned restrictions and
shortcomings. In this article, we use intelligent algorithms like Channel-wise Feature Pyramid Network (CFPNet) based
on deep learning-based techniques with Deep Belief Network (DBN) to monitor the quality and predict any occurrences
of manufacturing problems in clothing. The suggested algorithm is mostly utilised in the textile industry to find flaws in
clothing while estimating client needs based on the environment and the economy to react quickly and meet business
objectives. The performance evaluation was used to determine the 12 kinds of garment faults, which included holes,
excessive margins, stains, cracks, inappropriate stitch balancing, needle breaks, ink stains, torn clothing, drop stitches,
soil content, and broken clothing. The suggested model obtains a 95.85% stain defect detection rate, a 97.33%
defect-free garment recognition rate, and a 97.16% hole defect recognition rate.
Keywords: garment industry, quality assurance, prediction classification parameter optimisation, digital image processing, deep belief network
Citation: Mathew, D., Brintha, N.C., Detection of garment manufacturing defects using CFPNet and deep belief network: an image-based approach, In: Industria Textila, 2025, 76, 2, 160–170, http://doi.org/10.35530/IT.076.02.2024140
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Article: Predictive power of newfangled GARCH models in assessing stock price volatility of Indian textile companies
Authors: BHARAT KUMAR MEHER, SANTOSH KUMAR, ZABHISHEK ANAND, RAMONA BIRAU, VIRGIL POPESCU, SUNIL KUMAR, PETRE VALERIU NINULESCU, MUHAMMAD AWAIS-E-YAZDAN
Pages 171–184
DOI: 10.35530/IT.076.02.2023138
Published online: April 2025
Abstract
This research endeavours to contribute to the existing body of knowledge by assessing the predictive power of various
GARCH models in the specific context of Indian textile companies listed on stock exchanges. The GARCH family
encompasses several models, each designed to address specific aspects of volatility dynamics. By evaluating the
performance of these models against historical stock price data, we aim to shed light on their efficacy in forecasting
volatility patterns and enhancing risk management strategies for investors in the Indian textile sector by applying
symmetric and asymmetric models, namely: FIGARCH, FIEGARCH, GJR-GACRH, EGARCH and GARCH (1.1). The
object of the study includes quantitative analysis, estimation and forecasting of daily volatility with Normal, Students-t
distributions and generalized error distribution constructs of various Indian textile market i.e. KPR Mill Limited
(NLKPRM), The Trident Group (NLTRIE), Page industry limited (NLPAGE), Welspun India Limited (NLWLSP) and, Alok
Industries Limited (NLALOK). The objective is to discern the impact of the global financial crisis on the linkages across
these textile markets. The sample data spans a long period from April 2013 to May 2023 and includes the COVID-19
pandemic, the war between Russia and Ukraine, Current conflicts in the Middle East and climate risk.
Keywords: textile industry in India, volatility, GARCH models, long memory, leverage effect, COVID-19 pandemic
Citation: Meher, B.K., Kumar, S., Anand, A., Birau, R., Popescu, V., Kumar, S., Ninulescu, P.V., Awais-E-Yazdan, M., Predictive power of newfangled GARCH models in assessing stock price volatility of Indian textile companies, In: Industria Textila, 2025, 76, 2, 171–184, http://doi.org/10.35530/IT.076.02.2023138
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Article: Does supplier development matter for procurement performance in the textile industry? The moderating role of contract management difficulty
Authors: JORGE ALBERTO ESPONDA PÉREZ, REYNA ESPERANZA ZEA GORDILLO, ELIZABETH CÉSPEDES OCHOA, SARMAD EJAZ, KOMAL KAMRAN, MD BILLAL HOSSAIN, LÁSZLÓ VASA
Pages 185–193
DOI: 10.35530/IT.076.02.202438
Published online: April 2025
Abstract
The research aims to examine the impact of supplier development on procurement performance, taking into
consideration contract management difficulties as a moderating variable. The research method section of the study
employs a cross-sectional research design. In this survey technique, a questionnaire is employed to collect primary data
from 220 respondents from the purchasing department via Google Forms through an adopted questionnaire. The initial
step in our analysis was to clean and analyse the data using SPSS and SmartPLS 3 software, then incorporate structural
equation modelling (SEM) to conduct our analysis. The findings confirmed that supplier development affects
procurement performance. In addition to this, the contract management difficulties suggested a negative and significant
impact on procurement performance. Furthermore, the relationship between supplier development and procurement
performance is moderated by contract management difficulty. These unique findings highlight the importance of supplier
development and effective contract management in improving procurement performance in the textile industry. The
work’s implementation of transaction cost theory to analyse how supplier development impacts sourcing capability is
recognized as the primary theoretical contribution.
Keywords: supplier development, contract management difficulty, procurement performance
Citation: Pérez, J.A.E., Gordillo, R.E.Z., Ochoa, E.C., Ejaz, S., Kamran, K., B.Md Hossain, Vasa, L., Does supplier development matter for procurement performance in the textile industry? The moderating role of contract management difficulty, In: Industria Textila, 2025, 76, 2, 185–193, http://doi.org/10.35530/IT.076.02.202438
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Article: Development of a fitting-ensured men’s garment block pattern prediction model for people with convex belly (PWCB)
Authors: MENGSHU DING, TIANYU LUO, YAN HONG
Pages 194–210
DOI: 10.35530/IT.076.02.202487
Published online: April 2025
Abstract
The prevalence of People with a Convex Belly (PWCB) has been steadily increasing due to dietary and lifestyle
changes. Standard garments available in the market are unsuitable for individuals with visible belly protrusion. While
adapting patterns designed for individuals with normal morphology may be a potential solution, the design efficiency is
currently inadequate. The purpose of this study is to propose the development of a Garment Block Pattern Prediction
model to efficiently design fitting-ensured patterns for PWCB. This model aims to generate garment patterns that ensure
a proper fit based on morphological data specific to PWCB. To achieve this objective, we simulate the mapping
relationship between the body dimensions of PWCB and the dimensions of garment block patterns, which are adjusted
to ensure a proper fit. Firstly, we identify key morphological dimensions of PWCB’s bodies and determine the dimensions
of garment block patterns using traditional garment pattern formulas. Secondly, we develop 130 fitting-ensured garment
samples using CLO 3D software. Subsequently, we establish the mapping relationship using a linear regression model.
The proposed prediction model in this study successfully enables the realization of personalized fitting-ensured garment
block patterns for PWCB. This research significantly enhances the efficiency of pattern-making for PWCB and
establishes a foundation for the automation and intelligence of garment pattern-making specifically tailored to PWCB’s
needs.
Keywords: prediction model, convex belly, garment block pattern, pattern-making
Citation: Ding, M., Luo, T., Hong, Y., Development of a fitting-ensured men’s garment block pattern prediction model for people with convex belly (PWCB), In: Industria Textila, 2025, 76, 2, 194–210, http://doi.org/10.35530/IT.076.02.202487
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Article: The utilisation of polydopamine interlayer to add silver nanoparticles (AgNPs) to PET fabrics
Author: ABDURRAHMAN TELLI
Pages 211–219
DOI: 10.35530/IT.076.02.2024104
Published online: April 2025
Abstract
Silver nanoparticles are structures used in many areas such as antibacterial materials, increasing conductivity,
wastewater treatment, etc. In recent years, demand for their use in textile products has been increasing. Starting from
this point, this study aimed to produce silver nanoparticles on the surface of PET fabric to meet the different properties
expected from silver. For this purpose, polydopamine coating was applied to PET fabric by in situ polymerization. Then,
fabric structures containing polydopamine and silver nanoparticles were obtained with a reduction reaction of three
different molarity silver nitrate salts. The after-washing condition of the fabric with the highest produced amount of silver
nanoparticles was examined. Spectrophotometric colour measurement, FT-IR, SEM and EDX techniques were
performed. The best results were obtained on the fabric where silver nitrate was applied at 50 mM. The amount of silver
nanoparticles in this fabric was measured as 1.35% after washing.
Keywords: polyethyleneterephthalate, polydopamine, silver, silver nitrate, nano-coating
Citation: Telli, A., The utilisation of polydopamine interlayer to add silver nanoparticles (AgNPs) to PET fabrics, In: Industria Textila, 2025, 76, 2, 211–219, http://doi.org/10.35530/IT.076.02.2024104
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Article: Impact of production methods on waste minimization in v-bed flat knitting: a case study
Authors: NADIIA BUKHONKA, OLENA KYZYMCHUK, MARIJA PESIC, INETA NEMESA, JOVAN RADISIC
Pages 220–229
DOI: 10.35530/IT.076.02.2024123
Published online: April 2025
Abstract
Sustainable development in the textile industry is challenging due to growing demand and urgent environmental impact.
Waste minimization at every production stage is a promising way toward sustainability. Knitting is the most flexible textile
technology for zero-waste production.
This study aims to investigate the impact of production methods on production efficiency and waste minimization using
the V-bed flat knitting machine and the men`s cardigan as an example. The comparative analysis of yarn consumption
and production time for different production methods (part cut and fully fashioned) was used.
Research results of men`s cardigan manufacturing by four distinct methods derived from part-cut and fully fashioned
methods highlight their significant effect on yarn consumption, duration of production cycle, and cardigan performance.
The fully fashioned method minimizes yarn consumption by 16.5%, with 3.9% waste compared to the part-cut method.
The advanced fully fashioned method using a front knitted part with integrated cardigan pockets decreases yarn
consumption by 2.6% more and incurs only 3.0% waste. This method produces the highest cardigan performance
compared to the other methods due to its linking stitching and integrated knitted pockets. Within the part-cut method,
using the part-shaped panel instead of the rectangular panel for sleeves leads to a 9.7 % decrease in yarn consumption
and a 2.6% reduction in waste. It also leads to better product performance because of minimizing the overlocking
seams. These findings underscore the importance of selecting appropriate production methods to enhance efficiency
and reduce waste in knitwear manufacturing. Embracing waste reduction measures, mainly through natural yarn, holds
promise for environmentally friendly garment production. This research emphasizes the need for ongoing exploration of
eco-conscious manufacturing processes to promote sustainable knitwear production.
Keywords: knitting waste, production cycle, fully fashioned method, part-cut method, product performance, sustainability, integrated pocket, zero-waste technology
Citation: Bukhonka, N., Kyzymchuk, O., Pesic, M., Nemesa, I., Radisic, J., Impact of production methods on waste minimization in v-bed flat knitting: a case study, In: Industria Textila, 2025, 76, 2, 220–229, http://doi.org/10.35530/IT.076.02.2024123
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Article: A segmentation method for virtual clothing effect images
Authors: RUIHONG CHEN, KAIJIE YU, YU CHEN, ZENGBO XU
Pages 230–236
DOI: 10.35530/IT.076.02.2024111
Published online: April 2025
Abstract
Based on Efficient Channel Attention (ECA) mechanism, multi-level feature fusion and multi-scale channel attention
mechanism, this paper proposes an improved VGG16-UNet clothing effect image segmentation method, commanded
as EF-UNet, which aims to address the problems of insufficient semantic labels, poor local segmentation accuracy, and
rough segmentation edges in clothing effect images. For this purpose, an ECA mechanism is first added to the fifth layer
of the VGG16-UNet to assign greater weight and better extract target feature information to enhance the segmentation
ability for clothing data. Subsequently, a multi-level feature fusion approach is adopted in a decoder to extract these
features of various scales more efficiently and improve segmentation results. Finally, a multi-scale channel attention
module is added to the skip connection to extract spatial information from multi-scale feature maps and to enable
cross-dimensional interaction of salient visual features. Experimental findings show that the improved segmentation
model has higher training indicators and better segmentation outcomes than similar networks such as FCN, U-Net,
SegNet, PSPNet, DeepLabv3+, and VGG16-UNet semantic segmentation models. Compared with the original
VGG16-UNet, the improved network has recorded an increase of 4.91% in the Mean Intersection over Union (MIoU),
an increase of 4.98% in Mean Pixel Accuracy (MPA), and an increase of 0.43% in Accuracy, respectively.
Keywords: clothing image, Efficient Channel Attention (ECA) mechanism, Multi-Level Feature Fusion, Multi-Scale Channel Attention, semantic segmentation, VGG16-UNet network
Citation: Chen, R., Yu, J., Chen, Y., Xu, Z., A segmentation method for virtual clothing effect images, In: Industria Textila, 2025, 76, 2, 230–236, http://doi.org/10.35530/IT.076.02.2024111
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Article: From Hardship to Hope: the role of Cultural Intelligence to promote workplace harmony in the Indian garment industry
Authors: AALIYA ASHRAF, NANCY SAHNI, RAMONA BIRAU, DANIEL FRANK, GOKARNA VIDYA BAI, SUHAN MENDON, LUCIA PALIU-POPA, GABRIEL NICOLAE PRICINĂ, COSMIN MIHAI PRICINĂ
Pages 237–248
DOI: 10.35530/IT.076.02.202482
Published online: April 2025
Abstract
Migrants often encounter circumstances that call for the use of cultural intelligence (CQ), or the ability to communicate
effectively with people from different cultural backgrounds. Empirical evidence suggests that developing cultural
intelligence improves migrant workers’ general well-being and aids in their adjustment to new environments. The
purpose of this research endeavour is to explore the impact of cultural intelligence variables like cultural intelligence
strategy, knowledge, motivation and behaviour with a mediating role of multicultural workforce on workplace harmony.
The study employed a cross-sectional research design and implemented a convenience-sampling technique to collect
primary data through nine months from March 2023 to November 2023 through a well-structured questionnaire, which
was circulated among 358 migrant women workers from readymade garment industries in the Indian states of Karnataka
and Punjab. Data was collected through a structured questionnaire and analysed using Partial Least Squares-Structural
Equation Model. Hypothesis shows that cultural intelligence and multicultural workforce have a significant influence on
workplace harmony. The results of IPMA and PLS-MGA analysis show the similarity in the results of total effect and path
relationships. This study provides theoretical foundations and empirical findings on conceptualizing the antecedents of
workplace harmony. The outcomes of this research serve as significant input to policymakers and readymade garment
industries to facilitate the enhancement multicultural workforce to achieve workplace harmony.
Keywords: migrants, well-being, strategy, multicultural workforce, empirical evidence, cultural intelligence
Citation: Ashraf, A., Sahni, N., Birau, R., Frank, D., Bai, G.V., Mendon, S., Paliu-Popa, L., Pricină, G.N., Pricină, C.M., From Hardship to Hope: the role of Cultural Intelligence to promote workplace harmony in the Indian garment industry, In: Industria Textila, 2025, 76, 2, 237–248, http://doi.org/10.35530/IT.076.02.202482
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Article: Does ESG performance have an impact on firm value? Evidence from the Chinese textile and garment industry
Authors: YIBING SHAO, MENGLIN ZHENG, XIN XU, XIAOFEN JI
Pages 249–256
DOI: 10.35530/IT.076.02.2023126
Published online: April 2025
Abstract
The effect of ESG performance has recently become a challenge, attracting controversy. This study investigates the
relationship between ESG performance and firm value in textile and garment companies; moreover, it examines the role
of green innovation in the relationship between ESG performance and firm value. We used 673 annual samples of
Chinese Shanghai and Shenzhen A-share textile and garment listed companies from 2012 to 2022. Correlation and
panel regression analyses were carried out to evaluate possible links between ESG performance as determined by the
ESG rating data published by the Sino-Securities Index Information Service (Shanghai) Co., Ltd and market-based
measures of firm value. Our main finding reveals that the ESG performance has a significant positive relationship with
textile and garment company value; ESG performance can promote firm value by increasing green innovation, and
green innovation has a partial intermediary role between ESG performance and firm value. We conducted multiple
sensitivity analyses, and our findings are robust, which can provide useful recommendations for firms, investors, and
policymakers.
Keywords: environmental, social responsibility and corporate governance (ESG), circular economy, sustainability, textile industry, garment industry
Citation: Shao, Y., Zheng, M., Xu, X., Ji, X., Does ESG performance have an impact on firm value? Evidence from the Chinese textile and garment industry, In: Industria Textila, 2025, 76, 2, 249–256, http://doi.org/10.35530/IT.076.02.2023126
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Article: Study on the adaptability of cellulose diacetate tow for tobacco to the type of curling machine
Authors: LI ZHANG, HAOXUAN SHI, ZONG CHEN, JIANXING HUANG, JIAHUI GAO, YIQUN LI
Pages 257–264
DOI: 10.35530/IT.076.02.202446
Published online: April 2025
Abstract
The raw material of cigarette filters is cellulose diacetate slurry, and potentially harmful substances such as acetone are
used during production. To improve cigarette filters’ filtering effectiveness, increase cellulose diacetate filaments’
utilisation rate, and reduce environmental pollution during production, this study aims to investigate the effects of
cellulose diacetate tow specifications and crimping machine models on tow formation quality. In this paper, the
correlation between the specification of cellulose acetate tow, crimping machine models, and the resulting tow quality is
determined to guide the selection of crimping machines for practical production. To tackle the challenges of large sample
sizes and high experimental costs, a multidimensional sampling method is developed. Utilizing a learning-based
approach, we identify a robust nonlinear relationship among these three factors and validate the relationship by using
historical production data. Our findings reveal a significant nonlinear correlation between the crimping machine model
and both single and total deniers. Through two regression adjustments, a reasonable degree of regression fitting for the
relationships among the three factors is achieved. The experimental results indicate that the selection of the crimping
machine is positively correlated with the number of filaments in the bundle and the pressure on the rollers, while it is
negatively correlated with the cross-sectional area of the filaments. Additionally, a production guidance model, which
relates the crimping machine model to the specifications of cellulose acetate tow, is established.
Keywords: curling machine, cellulose diacetate, orthogonal experimental design, Latin hypercube sampling, logistic regression
Citation: Zhang, L., Shi, H., Chen, Z., Huang, J., Gao, J., Li, Y., Study on the adaptability of cellulose diacetate tow for tobacco to the type of curling machine, In: Industria Textila, 2025, 76, 2, 257–264, http://doi.org/10.35530/IT.076.02.202446
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Article: Methylene blue removal capabilities of activated carbon doped nanofibres
Authors: GAMZE D. TETIK, RAGIPHAN OZTURAN, MURAT ERCAN
Pages 265–274
DOI: 10.35530/IT.076.02.202457
Published online: April 2025
Abstract
The importance of adsorbents in wastewater treatment is related to their pollutant removal efficiency. The performance
in the treatment process depends on the surface area, morphology, and chemical structure of the adsorbents. Since
these properties can be controlled in both nanofibres and activated carbon, activated carbon (AC) doped nanofibres
were used to remove methylene blue (MB) from the aqueous medium in this study. For this purpose, AC was
synthesized from human hair by chemical activation and characterized. By this means, AC possessing 561 m2/g
Brunauer-Emmet-Teller (BET) surface area and 6.5% ash content was obtained. Thermogravimetric analysis of the AC
showed that approximately. 50% of the initial weight decomposed at 750°C. The synthesized AC was doped into the silk
fibroin (SF) electrospinning solution at the ratios of 1% and 5% (w/v). Scanning electron microscope and energy
dispersive X-ray analyses, and BET surface area measurements were conducted for characterization. Finally, batch
adsorption tests were performed under different conditions, assisted with an ultrasonic bath. According to the test
results, 5% AC-doped nanofibre web with 15 mg of adsorbent amount exhibited the best performance among nanofibre
webs with an adsorption amount of 262.3 mg/g. This value was achieved at pH 12, 50°C, and an ultrasonic bath-assisted
process duration of 10 min. The overall results showed that the AC synthesized from human hair-doped SF nanofibre
webs has the potential to remove MB from textile wastewater.
Keywords: activated carbon, adsorption, electrospinning, nanofibre, methylene blue, wastewater
Citation: Tetik, G.D., Ozturan, R., Ercan, M., Methylene blue removal capabilities of activated carbon doped nanofibers, In: Industria Textila, 2025, 76, 2, 265–274, http://doi.org/10.35530/IT.076.02.202457
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Article: Investigation of electrical and surface properties of spunbond nonwoven fabrics coated with graphene oxide and formed PVDF nano fibres via electrospinning on IT
Authors: GUL OZKAN, MUSTAFA SABRI OZEN, GULTEKIN NERGIS DEMIREL
Pages 275–285
DOI: 10.35530/IT.076.02.202456
Published online: April 2025
Abstract
Graphene oxide (GO) and Polyvinylidene fluoride (PVDF) are among the primary materials constituting the basis of
conductivity and sensor research. In this study, PVDF and GO-filled PVDF nanofibers were formed by the
electrospinning method on the polyester spunbond nonwoven fabric coated with aqueous graphene oxide dispersion via
the dip coating method. The graphene oxide dip-coated spunbond nonwoven fabric as a substrate was used. Then,
nanofiber surfaces with PVDF and GO-filled PVDF were formed by the electrospinning method onto GO-coated and
reduced nonwoven fabrics. Polymer solutions were prepared as pure PVDF with 0.5 wt% – 1 wt% – 2 wt% GO. The
chemical reduction operation by using Vitamin C and rosehip extract powder to nonwoven spunbond fabric coated with
graphene oxide and forming GO-filled PVDF nanofibers on it, was processed. Characterization analyses of nonwoven
spunbond fabric samples were performed by using XRD, FTIR, and SEM. To determine the functional properties,
electrical resistance, water contact angle, and mechanical strength measurement results were evaluated. The use of
nature- and human-friendly reducing agents in the present study is in alignment with the principle of sustainability.
Keywords: graphene oxide, polyvinylidene fluoride, electrospinning, spunbond nonwoven fabric, sensor
Citation: Ozkan, G., Ozen, M.S., Demirel, G.N., Investigation of electrical and surface properties of spunbond nonwoven fabrics coated with graphene oxide and formed PVDF nano fibres via electrospinning on IT, In: Industria Textila, 2025, 76, 2, 275–285, http://doi.org/10.35530/IT.076.02.202456/a>
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Article: Determinants of foreign direct investment in the textile sector: a research with IT2 Fuzzy TOPSIS methodology
Authors: RECEP UĞURCAN ŞAHİN, NALBANT KEMAL GÖKHAN, ABDULKADİR KESKİN, YAVUZ ÖZDEMİR, ABDURRAHMAN KESKİN
Pages 286–292
DOI: 10.35530/IT.076.02.2024116
Published online: April 2025
Abstract
This study aims to identify the determinants of foreign direct investment (FDI) in the textile sectors in Poland, Romania,
Hungary, Slovakia, Czechia and Türkiye. The study assesses these criteria through paired comparisons conducted by
experts who have a minimum of 10 years of professional experience in the field and analyses them using the IT2 Fuzzy
Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) technique. According to the findings, the
criteria with the highest degree of importance are national security, inflation rate, patent and trademark protection,
transportation networks and market size. On a country-by-country basis, Poland has a higher investment attraction
potential compared to other countries according to the criteria of openness, corruption, legal regulations and
privatization policies, import and export quotas, education and professional status, renewable energy resources,
sustainability, intellectual property protection, patent and trademark protection and national security. Hungary scores
highest on import and export quotas and tax rates, while Slovakia stands out on import and export quotas and waste
management/environmental regulations. Romania scores highest on profitability and debt financing, labour costs and
import and export quotas. Czechia scores highest on inflation rate, political stability, legal regulations and privatization
policies, economic incentives, general trade policies, import and export quotas and cultural situation and lifestyle.
Türkiye scores the highest in terms of market size, GDP growth rate, access to raw materials and markets, technological
infrastructure and innovation, transport networks, production sites, energy production, import and export quotas and
business-friendly approaches.
Keywords: foreign direct investment, textile industry, textile investment, IT2 Fuzzy TOPSIS
Citation: Şahin, R.U., Gökhan, N.K., Keskin, A., Özdemir, Y., Keskin, A., Determinants of foreign direct investment in the textile sector: a research with IT2 Fuzzy TOPSIS methodology, In: Industria Textila, 2025, 76, 2, 286–292, http://doi.org/10.35530/IT.076.02.2024116
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Article: Analysis of the dual network relationship and its evolutionary characteristics of global textile new material technology cooperation R&D in the 21st century
Authors: PENGFEI WANG, HUA CHENG
Pages 293–304
DOI: 10.35530/IT.076.02.202491
Published online: April 2025
Abstract
Vigorously developing new materials technology is of great significance to improving the high-tech level of the textile
industry, enhancing the transformation and upgrading of the textile industry, promoting the sustainable development of
the industry and enhancing the comprehensive national strength. In this paper, the data of 6982 invention patents
created by global textile new material technology cooperation are chosen as the research object, and the patent
technology network analysis method is used to examine the dual network relationship and its evolution features. The
results suggest that the core subjects represented by multinational corporations, well-known universities and scientific
research institutes integrate resources to conduct technology cooperation research, and the cooperation network’s
innovation activities in this field tend to be stable, but there is no relatively stable collaborative relationship between
innovation organizations. Furthermore, technology nodes, technology subgroups, spillover effects between
technologies, diffusion and fusion, and technology correlation strength have greatly improved. At the same time,
reasonable division of labor and coordination of the collaborative activities among nodes in the core, middle, and edge
layers of the network are crucial, and the division of labor and cooperation within the network are of great significance
for improving collaborative innovation efficiency. This study is useful to determine the innovation subjects, network
structure and technological evolution of global textile new material technology cooperation research and development,
but there is no analysis of the relationship between organizational cooperation network and technological network and
its evolution characteristics in this field. As a result, this article tries to supplement existing research in terms of both
research object and research content, to fill the gaps in the existing research.
Keywords: textile, new materials, technology R&D, network structure, patentometrics, evolution characteristics
Citation: Wang, P., Cheng, H., Analysis of the dual network relationship and its evolutionary characteristics of global textile new material technology cooperation R&D in the 21st century, In: Industria Textila, 2025, 76, 2, 293–304, http://doi.org/10.35530/IT.076.02.202491
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