Textile & Leather Review 3 2019

TEXTILE & REVIEW LEATHER

3/2019 Volume 2 Issue 3 2019 textile-leather.com ISSN 2623-6257 (Print) ISSN 2623-6281 (Online)

TEXTILE & REVIEW LEATHER Editor-in-Chief

Dragana Kopitar, University of Zagreb, Faculty of Textile Technology, Croatia

Assistant Editor

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Managing Editor

Davor Jokić, University of Zagreb, Faculty of Textile Technology, Croatia

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Editorial Advisory Board

Emriye Perrin Akçakoca Kumbasar, Ege University, Faculty of Engineering, Turkey Tuba Bedez Üte, Ege University, Faculty of Engineering, Turkey Mirela Blaga, Gheorghe Asachi Technical University of Iasi, Faculty of Textiles, Leather and Industrial Management, Romania Andrej Demšar, University of Ljubljana, Faculty of Natural Sciences and Engineering, Slovenia Krste Dimitrovski, University of Ljubljana, Faculty of Natural Sciences and Engineering, Slovenia Ante Gavranović, Economic Analyst, Croatia Ana Marija Grancarić, University of Zagreb, Faculty of Textile Technology, Croatia Huseyin Kadoglu, Ege University, Faculty of Engineering, Turkey Fatma Kalaoglu, Istanbul Technical University, Faculty of Textile Technologies and Design, Turkey Hüseyin Ata Karavana, Ege University, Faculty of Engineering, Turkey Ilda Kazani, Polytechnic University of Tirana, Department of Textile and Fashion, Albania Vladan Končar, Gemtex – Textile Research Laboratory, Ensait, France Stana Kovačević, University of Zagreb, Faculty of Textile Technology, Croatia Aura Mihai, Gheorghe Asachi Technical University of Iasi, Faculty of Textiles, Leather and Industrial Management, Romania Jacek Mlynarek, CTT Group – Textiles, Geosynthetics & Flexibles Materials, Canada Abhijit Mujumdar, Indian Institute of Technology Delhi, India Monika Rom, University of Bielsko-Biala, Institute of Textile Engineering and Polymer Materials, Poland Venkatasubramanian Sivakumar – CSIR – Central Leather Research Institute, Chemical Engineering Department, India Pavla Těšinová, Technical university of Liberec, Faculty of Textile Engineering, Czech Republic Savvas Vassiliadis, Piraeus University of Applied Sciences, Department of Electronics Engineering, Greece

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Textile & Leather Review ‒ ISSN 2623-6257 (Print), ISSN 2623-6281 (Online) UDC 677+675 DOI: https://doi.org/10.31881/TLR Frequency: 4 Times/Year The annual subscription (4 issues).

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TEXTILE & LEATHER REVIEW ISSN 2623-6257 (Print)

ISSN 2623-6281 (Online) CROATIA

VOLUME 2

ISSUE 3

2019

p. 121-168

CONTENT ORIGINAL SCIENTIFIC ARTICLE 126-135

Washable embroidered textile electrodes for long-term electrocardiography monitoring Amale Ankhili, Shahood uz Zaman, Xuyuan Tao, Cédric Cochrane, Vladan Končar, David Coulon

136-144

The anisotropic structure of electro conductive leather studied by Van der Pauw method Aulon Shabani, Majlinda Hylli, Ilda Kazani, Pëllumb Berberi, Orion Zavalani, Genti Guxho

145-153

Field classification in Dimensions: A case study of textile technology Davor Jokić

154-161

Knowledge, attitudes and behavior of consumers towards sustainability and ecological fashion Özgür Ceylan

shoe.com GmbH & Co. KG Ferenc Vasadi . + 36 (0) 30 94 69 123 . ferenc.vasadi@soliver-shoes.com

ANKHILI A et al, Washable embroidered textile electrodes for long-term... TEXT LEATH REV 2 (3) 2019 126-135.

Washable embroidered textile electrodes for long-term electrocardiography monitoring Amale ANKHILI1,2,3,*, Shahood uz ZAMAN1,2, Xuyuan TAO1,2, Cédric COCHRANE1,2, Vladan KONCAR1,2, David COULON3 École Nationale Supérieure des Arts et Industries Textiles / Génie et Matériaux Textiles laboratoire (ENSAIT/GEMTEX), 2 Allée Louis et Victor Champier, F-59100 Roubaix, France; shahood-uz.zaman@ensait.fr; xuyuan.tao@ensait.fr; cedric. cochrane@ensait.fr; vladan.koncar@ensait.fr 2 GEMTEX, University of Lille, Cité Scientifique, F-59650 Villeneuve d’Ascq, France 3 @HEALTH, Europarc de Pichaury, 1330 Rue Jean René Guillibert Gauthier de la Lauzière, F-13290 Aix-en-Provence, France; dcoulon@healthcardionexion.com * Corresponding author: amale.ankhili@ensait.fr 1

Original scientific article UDC 677.076.6+616.12-073.7 DOI: 10.31881/TLR.2019.27 Received 24 December 2018; Accepted 4 February 2019; Published Online 13 March 2019

ABSTRACT The improvement of human health condition is an important objective that remains relevant since the origin of human being. Currently, cardiovascular diseases are the first cause of death worldwide. For this reason, permanent real-time monitoring of heart activity (Electrocardiogram: ECG), its analysis and alerting of concerned person is a solution to decrease the death toll provoked by heart diseases. ECG signal of medical quality is necessary for permanent monitoring and accurate heart examining. It can be obtained from instrumented underwear only if it is equipped with high quality, flexible textile based electrodes guaranteeing low contact resistance between the skin and them. This work is therefore devoted to the design and test of wearable textile embroidered bands following defined protocol for ECG long-term monitoring. These bands were investigated in three configurations: band without any adding layer to protect lines between electrodes and the connector, band with lines protected by simple yarn, band with lines protected with thermoplastic polyurethane (TPU).

Bands were worn around chest by healthy subjects in a sitting position and ECG signals were acquired by an Arduino-based device and assessed. Washability tests of connected underwear were carried out over 50 washing cycles in a domestic machine and by using a commercial detergent. Influence of encapsulation process on the electrical properties of textile electrodes during repetitive washing process has also been investigated and analyzed. All the ECG signals acquired and recorded have been reviewed by a cardiologist in order to validate their quality required for accurate diagnosis.

KEYWORDS Embroidery, textile electrodes, washability, electrocardiography, signal quality

INTRODUCTION Over the past few decades, there has been an exponential increase of wearable sensors that have revolutionized smart textile industry since the industry of electronic integration into garments has been grown [1,2]. With the increase in the general awareness of people regarding the use of smart textiles in health monitoring, more efforts are being involved to overcome problems related to their reliability and washa126 www.textile-leather.com

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bility [3,4]to respond and adapt behaviour to them in an intelligent way and present a challenge in several fields today such as health, sport, automotive and aerospace. Electrically conductive textiles include conductive fibres, yarns, fabrics, and final products made from them. Often they are prerequisite to functioning smart textiles, and their quality determines durability, launderability, reusability and fibrous performances of smart textiles. Important part in smart textiles development has conductive polymers which are defined as organic polymers able to conduct electricity. They combine some of the mechanical features of plastics with the electrical properties typical for metals. The most attractive in a group of these polymers are polyaniline (PANI. Especially that the treatment of a wide critical diseases is not portable and require medically trained experts for their implementation [5]and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene.

Currently, lots of works have been done for the usage of smart textiles in medical industry for real time health monitoring and sports industry [6,7]. Health sector is still one of the big players in smart textile industry and reliability of the products used in this field is under discussion to make them acceptable for the market. These products, in future, will be used to integrate the routine checkup and comfortability of users with centralized data base [6]. Cardiovascular diseases are the first cause of lethal issues worldwide. To deal with this issue, real time heart monitoring and usage of smart textiles in inner garments got attraction [5]and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene.

ECG electrodes can be prepared by different techniques including conductive polymer, inkjet, screen printing and weaving / knitting etc [8–10]we unite graphene with ordinary textiles and report the development of graphene-clad, conductive textile electrodes for biosignal acquisition specifically in cardiac monitoring. The proposed electrode was prepared by dipping nylon fabric in reduced graphene oxide (rGO. But embroidering of electrodes were preferred because it is easy and less time consuming to produce embroidered electrodes and secondly, they are produced with same conductive threads used as connection yarns. Hence if conductive yarns are reliable and washable, both connection threads and electrodes will be reliable.

Weder et al. [11] have developed an embroidered textile electrode from polyethylene terephthalate yarn plasma coated with silver and ultra-thin titanium layer on top for passivation. Those electrodes were embedded into a breast belt. However, they had to be moisturized with a very low amount of water vapor from an integrated reservoir. In our opinion, this moisturizing will be an issue for long-term use, because the reservoir has to be filled up regularly. The advantage of this approach is that the monitoring is possible at rest, as well as when the subject is moving.

The current challenge faced in developing wearable ECG sensors is washability. Our previous works [4,5,9] and an accurate heart examination can be obtained from instrumented underwear only if it is equipped with high-quality, flexible, textile-based electrodes guaranteeing low contact resistance with the skin. The main objective of this article is to develop reliable and washable ECG monitoring underwear able to record www.textile-leather.com 127

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and wirelessly send an ECG signal in real time to a smart phone and further to a cloud. The article focuses on textile electrode design and production guaranteeing optimal contact impedance. Therefore, different types of textile fabrics were coated with modified poly(3,4-ethylenedioxythiophene explain the washability and reliability of textile electrodes by analyzing the performance of ECG signals after 50 washing cycles. In other research [12] different conductive threads behavior after washing was analyzed and concluded that washing have some severe effect on the conductivity of connection threads due to some mechanical forces acting during the washing process. In continuity with the previous work, this study is conducted to evaluate the performance of two different silver plated polyamide conductive yarns. Wearable textile bands for ECG long-term monitoring were produced by embroidering these conductive threads to make three electrodes with lines and connectors. Different protective methods of lines, that connect electrodes to connectors, were assessed and compared in order to determine the best one that can withstand in washing process. These methods include protection with a thermoplastic polyurethane film (TPU) and protection by a nonconductive yarn (simple yarn) and without any protective treatment. Washability tests of connected underwear were carried out over 50 washing cycles in a domestic machine and by using a commercial detergent. Influence of encapsulation process on the electrical properties of textile electrodes during repetitive washing process has also been investigated and analyzed by (i) calculating the resistances of lines that connect electrodes to connectors, (ii) computing of signal-to-noise ratio (SNR) and spectral power densities of ECG signals.

EXPERIMENTAL Materials and Methods The patterns of electrodes and lines were designed on the software BASE PAC8 provided by SZK Company (Germany) as shown in Figure 1.

Figure 1. The pattern of electrodes

Two type of silver plated polyamide conductive threads were used: Statex-Shieldex 117f17 2-ply HC+B and Madeira HC-40 to embroider bands on a plain cotton fabric by using embroidery machine (ZSK, Germany).

Embroidery machine was preferred to normal stitching machine due to better stitch quality and availability of vast range of design possibilities. Conductive lines between ECG electrode and connector were assessed up to 50 washing cycles, prototected by nonconductive yarn embroidered on the of the top of conductive lines (Figure 2), without any protection (Figure 3), protected by a thermoplastic polyurethane film (TPU) (Figure 4). The TPU protection film (BEMIS, United Kingdom) was attached by using a heated press at 140°C for 20 seconds.

The washing process was carried out with a commercial detergent (X.TRA Total, Roubaix, France) in a domestic washing machine (Miele, Paris, France). Each washing cycle comprised 35 min at 40 °C with 30 mL of detergent and a total machine load of 2.5 kg. The drying spinning speed was 600 rpm. Household washing machine was preferred on laboratory washing machine because if these products will be commercialized, ultimately they will be washed in available washing machines.

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Samples were dried in controlled conditions (20 ±2 °C and 65 ± 5 % R.H) for 24 hours before each measurement. Change in resistance (Ri/Ro) in conductive lines was measured after washing. Digital multi meter was used for measurements.

ECG measurements were performed by a SHIELD-EKG-EMG card from OLIMEX. The OLIMEX card was configured using an Arduino, and data analysis was processed using MATLAB (R2013a). Signals were filtered by a Butterworth passband filter (0.05–100 Hz) and Notch filter at 50 Hz to remove, respectively, motion artifacts and power line noises. The recording was carried out for around 40 s with subjects wearing bands around chest and sitting to avoid motion artifacts. Measurements were carried out without any skin preparation at the electrodes sites, and performed immediately after installing the bands.

The signal recorded is obtained from the Lead I corresponding to the voltage between the left arm (LA) electrode and the right arm (RA) electrode. The quality of ECG signals was assessed by calculating signalto-noise-ratio (SNR) which is the ratio between filtered signal and the original noisy signal [13].

Figure 2. Band with lines protected by nonconductive yarn (red yarn)

Figure 3. Band without any protection

Figure 4. Band with lines protected TPU film

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RESULTS AND DISCUSSION Figures 5 and 6, illustrate variations of Ri/Ro during 50 washing cycles for both silver-plated yarns (Shieldex and Madeira), where Ro is the resistance of conductive lines before washing and Ri is the resistance after the i-th washing cycle. For all yarns, the resistance increases linearly as a function of the number of washing cycles, but with different slopes. For Madeira conductive yarn (Figure 5), protective coating with simple yarn seemed to save it from mechanical stresses during washing process. When we compare Ri/Ro while using TPU film and without any coating, the results are almost same, meaning that TPU film indeed is not protecting the conductive yarn layer. Moreover, whatever the type of protection, Ri/Ro increases slowly and with low standard deviations that means that Madeira yarn is homogenous and stable compared to Shieldex conductive yarn (Figure 6). The same as for Madeira yarn, simple yarn protection is proved to be the best one to protect the Shieldex conductive lines from damages exerted in the washing machine. However, TPU protection seemed to damage Shieldex yarn. In fact, Shieldex yarn has conductive silver plate coating on the outer side of yarn plies only. But in Madeira yarn, each filament in the ply is separately coated with silver. Consequently, for Shieldex yarn, the protruding fibers on its surface are more damaged during the application of TPU film at high temperature (140°C for 20 s) and hence resistance increased after repetitive washing cycles.

Figure 5. Madeira

Figure 6. Shieldex

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In order to determine the effect of the difference protections on the quality of washed bands, ECG signals were recorded before and after 50 washing cycles. High quality signal means that there is no missing P, Q, R, S and T waves. They provide useful information for cardiologists to interpret. Figures 7, 8 and Figure 9, show electrocardiograms before and after washing recorded by bands without any protection, protected

by TPU film and those protected by nonconductive yarn. For all ECG signals recorded by the two types of conductive yarns (Shieldex and Madeira), cardiac waves were clearly identified: P wave which correspond to atrial depolarization, QRS complex corresponding to ventricle depolarization and T wave corresponding to the repolarization of the ventricle. After 50 washing, ECG signals were contaminated by noise, especially for bands protected with TPU film (Table 1).

In fact, before washing the bands with TPU film had the best SNR, as the heated press increased the contact between fibers. However, these bands are more sensitive to washing process because of the high set-up temperature of TPU installation (140°C). Moreover, according to Table 1, protection with simple yarn seemed

Figure 7. ECG signlas of bands without protection

Figure 8. ECG signlas of bands protected by TPU layer

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Figure 9. ECG signlas of bands protected by nonconductive yarn

to be the best solution for Madeira yarn since the SNR kept the same value after 50 washing cycles. For all types of bands made by Shieldex yarn, the SNR decreased strongly after repetitive washing meaning that Shieldex is more sensitive to washing than Madeira. Which again justify the fact that Shieldex yarn has conductive silver plate coating on the outer side of yarn plies only in contrast to Madeira yarn that has each filament separately coated with silver.

Table 1. Signal to-noise-ratio obtained by bands

SNR (dB) Shieldex

SNR (dB) Madeira

Before washing

After washing

Before washing

After washing

Band without protection

37,7734 ± 2.6112

23,8203± 2.5025

35,1584 ± 3.2544

34,2087 ± 2.2285

Band with TPU protection

40,1633 ± 1.0169

20,2333 ± 6.0148

38.0609 ± 1.3876

35,0674 ± 1.2070

Band with nonconductive yarn protection

39,4139 ± 1.9619

21,2734 ± 2.6165

34,2131± 1.4018

34,1637 ± 1.4645

In order to confirm the influence of washing on ECG signal quality, the power spectral densities have also been evaluated. Figures 10, 11 and Figure 12 show that the density in the important frequency domain (<5 Hz) has not been strongly degraded [14]4-ethylenedioxythiophene. Moreover, after 50 cycles of washing, the power spectral density decreased from unwashed bands except band made by Madeira conductive yarn protected by nonconductive yarn (Figure 12b) when there is not obviously difference between the signal from unwashed and from 50 washing cycle bands. The significant decrease in signal quality after repetitive washing can be explained by mechanical stresses exerted in the laundry machine. Moreover water temperature and detergent lead to damages of fibers and small fractures which affect negatively the adhesion between silver coating and polyamide yarn and therefore electrical conductivity of embroidered electrodes. The TPU film used here is not a good solution to protect lines and the best choice is to use Madeira yarn protected by nonconductive yarn.

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Zaman et al [15] explained the change in resistance after repetitive washing cycles and concluded that electrical resistance increased gradually as a function of washing cycles because of mechanical damages.

Tao et al [12] used two techniques to protect the e-textile systems including TPU or latex protection. They concluded that TPU protection was not up to the mark when investigated after certain number of washing cycles and several connection points were damaged.

Figure 10. Power spectral densities of ECG signal measured from brands without protection (a) Shieldex; (b) Madeira

Figure 11. Power spectral densities of ECG signal measured from brands with TPU (a) Shieldex; (b) Madeira

Figure 12. Power spectral densities of ECG signal measured from brands with simple yarn (a) Shieldex; (b) Madeira

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CONCLUSION This study was developed to assess the performance of embroidered bands for ECG long term monitoring.

Two different types of yarns with two different protection types were used in this experiments and effect of washing on ECG signal quality was examined. For all ECG signals recorded by the two types of conductive yarns (Shieldex and Madeira), cardiac waves were clearly identified. In comparison of both yarns, shieldex yarn seemed to be more sensitive to damage by washing forces than Madeira yarn. This is because each ply in Madeira yarn is separately silver coated while in case of Shieldex, only the outer side of yarn is silver coated. Results revealed that non-conductive yarn embroidered on the top of conductive thread layer has clear advantage on TPU protection. TPU protection was applied at high temperature (140°C) which affects the quality of adhesion between silver layer and polyamide surface in conductive yarn after washing. Moreover water temperature and detergent lead to damages of fibers and small fractures which affect negatively the adhesion between silver coating and polyamide yarn and therefore electrical conductivity of embroidered electrodes. The TPU film used here is not a good solution to protect lines. Nonconductive yarn protected the inner conductive yarn from surface damage during washing and also from the effect of detergent. Consequently, according to our results, the best choice is to use Madeira yarn protected by nonconductive yarn to make bands.

Acknowledgements Partial funding of this work was obtained from ANRT and @HEALTH Company.

REFERENCES [1] Pani D, Achilli A, Bonfiglio A. Survey on Textile Electrode Technologies for Electrocardiographic (ECG) Monitoring, from Metal Wires to Polymers. Advanced Materials Technologies. 2018;1800008.

[2] Castano LM, Flatau AB. Smart fabric sensors and e-textile technologies: a review. Smart Materials Structures. 2014;23:053001.

[3] Grancaric AM, Jerkovic I, Koncar V, Cochrane C, Kelly FM, Soulat D, Legrand X. Conductive polymers for smart textile applications. Journal of Industrial Textiles. 2018;48(3):612–642.

[4] Tao X, Huang TH, Shen CL, Ko YC, Jou GT, Koncar V. Bluetooth Low Energy-Based Washable Wearable Activity Motion and Electrocardiogram Textronic Monitoring and Communicating System. Advanced Materials Technologies. 2018;1700309.

[5] Ankhili A, Tao X, Cochrane C, Coulon D, Koncar V. Washable and Reliable Textile Electrodes Embedded into Underwear Fabric for Electrocardiography (ECG) Monitoring. Materials. 2018;11(2):256.

[6] Global Smart Wearable Fitness and Sports Devices and Services Market 2016-2020 Available online: https://www.technavio.com/report/global-machine-machine-m2m-and-connected-devices-smartwearable-fitness-and-sports-devices (accessed on Dec 9, 2018).

[7] Wearable Medical Devices Market Size, Analysis, Industry Trends (2018-23) [cited on Dec 9, 2018] Available online: https://www.mordorintelligence.com/industry-reports/global-wearable-medicaldevice-market-industry.

[8] Yapici MK, Alkhidir T, Samad YA, Liao K. Graphene-clad textile electrodes for electrocardiogram monitoring. Sensors and Actuators B: Chemical. 2015;221(31):1469–1474.

[9] Ankhili A, Tao X, Cochrane C, Koncar V, Coulon D, Tarlet JM. Comparative Study on Conductive Knitted Fabric Electrodes for Long-Term Electrocardiography Monitoring: Silver-Plated and PEDOT:PSS Coated Fabrics. Sensors. 2018;18(11):3890.

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[10] Ramasamy S, Balan A. Wearable sensors for ECG measurement: a review. Sensor Review. 2018;38(4):412â&#x20AC;&#x201C; 419.

[11] Weder M, Hegemann D, Amberg M, Hess M, Boesel L, Abacherli R, Meyer V, Rossi R. Embroidered Electrode with Silver/Titanium Coating for Long-Term ECG Monitoring. Sensors. 2015;15(1):1750â&#x20AC;&#x201C;1759.

[12] Tao X, Koncar V, Huang TH, Shen CL, Ko YC, Jou GT. How to Make Reliable, Washable, and Wearable Textronic Devices. Sensors. 2017;17(4):673.

[13] Clifford GD, Azuaje F, McSharry P. Advanced methods and tools for ECG data analysis. Boston: Artech House; 2006.

[14] Ankhili A, Tao X, Cochrane C, Koncar V, Coulon D, Tarlet JM. Ambulatory Evaluation of ECG Signals Obtained Using Washable Textile-Based Electrodes Made with Chemically Modified PEDOT:PSS. Sensors.

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[15] Zaman SU, Tao X, Cochrane C, Koncar V. Market readiness of smart textile structures - reliability and washability. IOP Conference Series: Materials Science and Engineering. 2018;459:012071.

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SHABANI A, et al. The anisotropic structure of electro conductive leather â&#x20AC;Ś TEXT LEATH REV 2 (3) 2019 136-144.

The anisotropic structure of electro conductive leather studied by Van der Pauw method Aulon SHABANI1, Majlinda HYLLI2, Ilda KAZANI2, PĂŤllumb BERBERI3, Orion ZAVALANI1, Genti GUXHO2 Department of Electrotechnics, Polytechnic University of Tirana, Tirana, Albania Department of Textile and Fashion, Polytechnic University of Tirana, Tirana, Albania 3 Department of Engineering Physics, Faculty of Engineering Mathematics and Engineering Physics, Polytechnic University of Tirana, Tirana, Albania * aulonshabani@yahoo.com 1 2

Original scientific article UDC 675.017.57 DOI: 10.31881/TLR.2019.16 Received 29 December 2018; Accepted 25 March 2019; Published Online 10 May 2019

ABSTRACT Determining the surface resistance of electro conductive refined natural leather materials is in the focus of this paper. Natural leather samples are initially transformed to conductive by applying chemical treatment process known as polymerization. Due to the existence of various techniques for measuring electrical resistance of conductive materials, we are focused on measuring surface resistance by arranging four electrodes in the edges of square leather samples, also known as Van der Pauw method. Improving the results accuracy, we use a multi-variant electrode placement over the sample edges. The result is the average of all results gained for different placements. Moreover, we use this electrode placement technique to analyse the anisotropy of conductive samples. The results of this research provide important knowledge about leather chemical treatment and its electrical proprieties.

KEYWORDS Leather, conductivity, anisotropy, Van der Pauw method

INTRODUCTION Textiles have a variety of uses, most commonly in the clothing industry. In recent years, smart textiles are used as they are able to respond to changes in the environment. These kinds of textiles are a mix of textile materials with electric, magnetic, chemical and thermal systems.

Smart textiles are used in different areas, for example, sportswear, where they monitor physical parameters, in clothing for elderly people where they monitor life signs, or in living spaces to help improve human thermal comfort and energy efficiency. Smart textiles are seen as the new trend in the last decades.

In this paper, we focus on electrical properties of conductive sheep leather obtained through polymerization. It is important to investigate electrical properties of leather materials in order to predict their possible applications in the future. Leather is used for clothes, accessories, on furniture, and car interiors.

Studies on electrical measurement of textile materials have been carried out since Hersh and Montgomery [1] used a novel apparatus to study the electrical resistance of textile fibres and fibre assemblies. They inves-

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tigated electrostatic properties of natural fibres on different ambient conditions. They found that electrical properties of those fibres are highly dependent on material moisture. Another novel approach for evaluating electrical properties of textile assemblies was proposed by Berberi [2]. The author proposed a new multi-step method for evaluating electrical resistance. Furthermore, he developed a novel probe for resistance measurement using volume fraction properties of the material. Kacprzyk [3] described measurement of volume and surface resistance of textile materials as well. They compared different electrode systems for resistance measurement. Yang and Wang [4] provided an approach for measuring resistivity of thin film insulating material by developing a new circular probe.

The above mentioned methods focused on electrical properties of textile fibres, but a variety of methods can be found in literature that focus on measurement of textile’s surface resistance by placing different number of electrodes over thin film surface material. The most commonly used measurement methods are the two- and the four-probe measurement methods. The two-probe methods evaluate electrical resistance of the material by using Ohm’s law, but the accuracy is volatile in case of thin films. It is for this reason that four-probe methods are most commonly used. These methods are classified into two main groups: linear placement and peripheral placement. Wenner [5] proposed a surface resistance measurement by placing four equidistant electrodes in a line where two of them measure voltage drop and the remaining two measure the current flow. On the other hand, Van der Pauw [6] proposed a different four-probe system for measuring surface electrical resistance for any arbitrarily shaped thin material. In our work, we focus on Van der Pauw’s technique for resistance measurement.

Many authors used this method for measuring electrical resistance. Authors [7] applied Van der Pauw’s method for measuring electrical resistance on thin film materials; they also took into account the correction factor. The application of the method in textile material resistance measurement is published in a paper

by Tokarska [8], where she investigated the contact diameter of electrodes and their arrangement. Kazani et. al [9] used van der Pauw’s method to measure electrical resistance of anisotropic thin layers screenprinted on textile.

Furthermore, the four-probe method is used by Schnabel [10] for evaluating anisotropy on parallel-plane crystals. Investigation of anisotropy of electrical properties of textile fabrics was the focus in Azoulay [11].

The author analysed the electrical properties in different weaving directions of the textile material. Tokarska, Frydrysiak, and Zięba [12] analysed the electrical properties of textile materials by exposing its anisotropy and homogeneity properties.

Other electrical properties are investigated by different authors as well. Asanovic et al. [13] analysed resistance and dielectric properties of different textile materials as function of air humidity. Banaszczyk et al. [14] modelled current distribution of electro-conductive fabrics. They modelled textile fabrics by using electrical circuit model and then mapping current distribution generated by the simulated circuit model.

The characteristics of textile materials are investigated after chemical treatment have been applied as well.

For example, Yoon and Lee [15] assessed performance characteristics of developed breathable waterproof materials. The investigation of chemical treatments of textile fabrics is also reported in [16]. The authors focused on developing an electronic textile resistor by treating less conductive fabric with polypyrrole in order to increase conductivity. They developed a prototype for measuring electrical resistance on conductive fabric. Improving textile materials’ conductivity using polypyrrole treatment is investigated by Kaynak and Beltran as well [17]. They analysed the relationship between surface resistivity and concentration of conductive elements used. Electrical conductivity of polypyrrole coated textiles was investigated by Varesano et al. [18]. Electrical surface resistivity of conductive polymers using statistical approach was investigated in [19]. www.textile-leather.com 137

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Conductive transformation of textile materials is the focus of many authors. In recent publications, the investigation of leather conductivity and it possible applications to smart textiles has an important place.

Conductive leather analysis for smart textile applications is the focus of Wegene and Thanikaivelan [20].

After using single in situ polymerization of pyrrole to produce conductive leather, they analysed polypyrrole coating by using Fourier transform infrared spectroscopy and electron microscopic analysis. In addition, the leather colour was investigated using reflectance measurements. Likewise, Yang et al. [21] produced artificial leather with high thermal conductivity by adding aluminium oxide (Al2 O3). Furthermore, they [22] developed high thermal conductive leather for smart electronic materials. Hong [23] processed leather in a conductive chemical treatment in order to develop conductive leather gloves.

Our study focuses on determining surface resistance of natural leather processed for conductivity by the four probe method known as the Van der Pauw method. Our previous works [24, 25] were focused on transforming nonconductive leather using chemical treatments. Attention was given not only to surface resistance, but to analysing anisotropy of conductive material after chemical processing as well.

VAN DER PAUW RESISTIVITY MEASUREMENT METHOD This method, introduced by Van der Pauw, is intended for resistance measurement of any arbitrarily shaped flat sample of homogeneous thickness [6]. The method evaluates two-dimensional surface resistivity using a minimum of four measurements by placing four electrodes in different positions around the periphery of the sample as shown in Figure 1(a-h).

More specifically, according to the Van der Pauw’s theory, surface resistance is calculated using the following equation:

e -πRvertical/Rs + e -πRhorizontal/Rs = 1

(1)

where Rvertical is the mean sample resistance of four configurations (Figure 1, b-d-f-h) defined by Ohm’s law as the ratio between potential difference in two points with current flowing in the two other, opposite points. is calculated in a similar manner. Surface resistance is obtained by solving equation 1.

Figure 1. Electrode configurations for Van der Pauw’s resistance measurement taking polarity into consideration

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LEATHER CONDUCTIVE TRANSFORMATION Leather is a natural material created by tanning raw hides to make it durable, resistant, flexible, etc. White sheep crust leather is treated chemically in order to make it conductive. Different methods can be used to prepare conductive leather. We decided to use the single in-situ polymerization of pyrrole method which produces conductive and coloured leather samples in one chemical treatment and is environmentally friendly. The leather samples are taken in accordance with ISO 2418 : 2017 (Leather – Chemical, physical and mechanical and fastness tests. – Sampling location). The samples (8 x 8 cm) were first treated with a pyrrole/AQSA mixed solution for 1 hour at room temperature rotating manually at 10 rpm in order for the solution to penetrate in a homogenous way. Next, ferric chloride solution, which plays the role of an oxidant, was added to initiate the polymerization. The concentrations of monomer (pyrrole), AQSA as a dopant, and FeCl3 as oxidant, were varied and optimized in order to provide the maximum conductivity of leather. Polymerization was carried out for 2 h at 5°C rotating manually at 10 rpm. Finally, the polypyrrole coated leather samples were washed with distilled water and dried at 35 °C. The treated leather samples were conditioned according to ISO 2419:2012 method (Leather – Physical and mechanical tests – Sample preparation and conditioning) before the electrical measurements.

MEASUREMENTS OF SURFACE RESISTANCE OF LEATHER SAMPLE The purpose of this study was to determine surface resistance of conductive leather samples and compare how chemical substrate was distributed during the process. Surface resistance was determined using fourprobe method which indicates the ratio of voltage drop between one pair of electrodes with current flow between the other pair of electrodes placed opposite each other in case of square shaped samples. The anisotropy of leather samples was observed using four-electrode technique, by adding different probe placement scenarios. Each of the results is the observation of five repetitions and the error of measurement is estimated using the standard deviation formula.

I. Surface resistance measurements Leather samples resistances were calculated based on electrode placement as shown in Figure 1(a-h). First, the ratio between voltage drop and current flow was calculated and then a script file was used to solve Van der Pauw’s equation for determining square-shaped surface resistance. In order to conduct this experiment, a Tektronix DMM4050 Multimeter, a DC Power supply PS23023 and four measurement probes were used as shown in Figure 2. The surface resistances obtained for four different leather samples are shown in Table 1 and Table 2.

Figure 2. Leather sample measurement schematics for multi-scenario electrode placement

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Table 1. Electrical properties of leather samples 1-2

Sample 1 Variant

Sample 2

Fig.2.a

Fig.2.b

Fig.2.c

Fig.2.d

Fig.2.a

Fig.2.b

Fig.2.c

Fig.2.d

Voltage (V)

1.74

2.09

0.76

0.84

0.8

0.98

2.6

2.2

Current (A)

0.08

0.1

0.1

0.11

0.09

0.09

0.09

0.07

Resistance (Ω)± estimated stda

21.75 ±1.41

20.9 ±1.128

7.6 ±0.53

7.63 ±0.61

8.889 ±0.578

10.889 ±0.59

28.88 ±2.02

31.42 ±1.89

Attribute

Surface resistance (Ω/m2)) ± estimated std

60.15 ± 4.04

78.53 ± 4.89

Table 2: Electrical properties of leather samples 3-4

Sample 3 Variant

Sample 4

Fig.2.a

Fig.2.b

Fig.2.c

Fig.2.d

Fig.2.a

Fig.2.b

Fig.2.c

Fig.2.d

Voltage (V)

1.14

1.35

1.8

1.67

1.22

1.52

1

1.25

Current (A)

0.08

0.09

0.09

0.08

0.05

0.06

0.05

0.07

Resistance (Ω) ± estimated std

14.25 ±0.92

15 ±1.2

20 ±1.24

20.87 ±1.48

24.4 ±1.78

25.33 ±1.65

20 ±1.139

17.85 ±1.17

Attribute

Surface resistance (Ω/m2)) ± estimated std

78.69 ± 4.81

98.61 ± 6.14

II. Anisotropy observation In our study, anisotropy indicates how the chemical treatment of leather samples was applied from the electrical point of view. We observed it using different electrode placements as shown in Figure 3. 12 different variants were used in order to observe electrical properties each of them based on the opposites principle.

In the first variant, AB points were used as voltage measurements and the two remaining points were used as the path for current flow. In the second variant, AB points were used as current flow and the voltage drop was measured on the CD points.

Electrical properties for both chemical treatment samples were measured under ambient conditions (19 ⁰C and 47 %). The values of the measurements were taken 60 seconds after the current started flowing through the leather sample. Five measurements were done for each sample and the mean value was calculated.

As can be seen in Table 3, the resistance values obtained using two variants of swapping electrode placement were Ra=21.75 Ω and Rb=20.9 Ω, meaning that anisotropy of conductive material distribution occurred.

For the results in Table 3, there was an obvious conclusion that the conductive substrate was not spread homogeneously leading to anisotropy in electrical properties of the leather.

a

Estimated standard deviation measures the dispersion of five different measurements

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Figure 3. Electrode placement for anisotropy identification

Table 3. Electrical characteristics of four samples using different electrode placement Sample 1 Variant

Fig.4.a

Fig.4.b

Fig.4.c

Fig.4.d

Fig.4.e

Fig.4.f

Fig.4.g

Fig.4.h

Fig.4.i

Fig.4.j

Fig.4.k

Fig.4.l

Voltage (V)

1.74

2.09

0.76

0.84

0.7

0.54

3.6

3.85

1.12

1.27

1.99

2.01

Current (A)

0.08

0.1

0.1

0.11

0.11

0.1

0.16

0.16

0.1

0.12

0.12

0.11

Resistance (Ω) ± estimated std

21.75 ±1.41

20.9 ±1.12

7.6 ±0.53

7.63 ±0.61

6.36 ±0.41

5.4 ±0.38

22.5 ±1.68

24.06 ±1.32

11.2 ±0.89

10.58 ±0.74

16.58 ±1.12

18.27 ±0.92

Attribute

Sample 2 Variant

Fig.4.a

Fig.4.b

Fig.4.c

Fig.4.d

Fig.4.e

Fig.4.f

Fig.4.g

Fig.4.h

Fig.4.i

Fig.4.j

Fig.4.k

Fig.4.l

Voltage (V)

0.80

0.98

2.6

2.2

0.74

0.69

1.09

3.37

3.14

1.82

1.4

1.79

Current (A)

0.09

0.09

0.09

0.07

0.09

0.09

0.09

0.16

0.15

0.09

0.11

0.09

Resistance (Ω) ± estimated std

8.889 ±0.58

10.89 ±0.59

28.88 ±2.02

31.42 ±1.89

8.22 ±0.51

7.67 ±0.53

12.11 ±0.78

21.06 ±1.19

20.93 ±1.46

20.22 ±1.62

12.73 ±0.83

19.89 ±1.57

Attribute

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Sample 3 Variant

Fig.4.a

Fig.4.b

Fig.4.c

Fig.4.d

Fig.4.e

Fig.4.f

Fig.4.g

Fig.4.h

Fig.4.i

Fig.4.j

Fig.4.k

Fig.4.l

Voltage (V)

1.14

1.35

1.8

1.67

0.47

0.26

3.23

3.15

0.55

0.62

2.24

2.04

Current (A)

0.08

0.09

0.09

0.08

0.09

0.08

0.14

0.13

0.09

0.08

0.09

0.09

Resistance (Ω) ± estimated std

14.25 ±0.92

15 ±1.2

20 ±1.24

20.87 ±1.48

5.22 ±0.33

3.25 ±0.23

23.07 ±1.49

24.23 ±1.35

6.11 ±0.42

7.7 ±0.61

24.9 ±1.61

22.67 ±1.78

Attribute

Sample 4 Variant

Fig.4.a

Fig.4.b

Fig.4.c

Fig.4.d

Fig.4.e

Fig.4.f

Fig.4.g

Fig.4.h

Fig.4.i

Fig.4.j

Fig.4.k

Fig.4.l

Voltage (V)

1.22

1.52

1

1.25

0.39

0.38

3.16

3.03

0.78

0.67

1.55

1.93

Current (A)

0.05

0.06

0.05

0.07

0.09

0.08

0.12

0.12

0.09

0.08

0.07

0.08

Resistance (Ω) ± estimated std

24.4 ±1.78

25.33 ±1.65

20 ±1.14

17.85 ±1.17

4.33 ±0.31

4.75 ±0.41

26.33 ±1.71

25.25 ±2.16

9.75 ±0.68

8.37 ±0.66

22.14 ±1.43

24.13 ±1.90

Attribute

CONCLUSION Conclusion results from the conducted analysis on conductive transformed leather resistance measurements.

The results of this research can provide important knowledge about electrical proprieties of conductive leather.

The following conclusions result from analysis of transformed nonconductive to conductive by applying chemical treatment. Understanding the transformed samples, electrical proprieties are surveyed, taking into consideration surface resistance for conductivity analysation and linear resistances in case of anisotropy. Both of these methods rely on four probe measurement techniques.

Obtained surface resistance values indicate significant outcomes, where we have samples with high conductivity values. Analysing leather conductivity values will be subject to upcoming research, since the research interests are in the application of them in the real life scenarios.

The other measurement technique also applies different electrode placement, where linear resistance values indicate anisotropic characteristics of leather samples. These results show that chemical treatment of conductive leather is not uniformly distributed.

We aimed to provide important knowledge about the electrical properties of conductive leather materials, a problem not so treated in literature.

As a future improvement of this research, we aim to try the effectiveness of conductivity transformation on real applications.

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JOKIC D, Field classification in Dimensions: a case study of textile... TEXT LEATH REV 2 (3) 2019 145-153.

Field classification in Dimensions: A case study of textile technology Davor JOKIÄ&#x2020;

Faculty of Textile Technology, Library, University of Zagreb, Zagreb, Croatia davor.jokic@ttf.hr Original scientific article UDC 001:677 DOI: 10.31881/TLR.2019.31 Received 20 May 2019; Accepted 8 July 2019; Published Online 10 July 2019

ABSTRACT Given the latest research on Dimensions classification, this article discusses the novelty of such classification in the field of textile technology from the standpoint of Croatian scientific career advancement system. New machine learning article based classification system is compared to a traditional journal based classification system brought by the Web of Science and Scopus in terms of evaluation significance. The starting point of assigned category comparison were 13 journals indexed in the Web of Science in just one common category - Materials science, Textiles. Since Scopus does not have a unique category for the textile technology a list of 11 assigned categories was put in the comparison. Lastly, 58 research fields assigned to the articles published in mentioned journals indexed in Dimensions were analyzed for validity. Results show that the unique category of Textiles in Web of Science fully fits the field of textile technology from Croatian point of view. Scopus model with multi category assignment is not so reliable and useful in field evaluation. Lastly, Dimensions with its novel approach failed to validly classify indexed publications.

KEYWORDS Dimensions, bibliometrics, field classification, textile technology, research evaluation

INTRODUCTION The recent studies on relatively new research data platform Dimensions produced sufficient amount of information about its origin and features [1,2,3]. The main characteristics can be pointed out for the first time users. In 2018 a technology company Digital Science launched their product named Dimensions1 offering scientific and research communities a research data infrastructure and tool without charge. The purpose was to introduce a new way the research is discovered, accessed and analyzed.

The main novelty is a classification system based on machine learning automatic category assignment on the level of single publication. Such classification is completely different from traditional journal based classification brought by relevant scientific databases, especially the Web of Science and Scopus. The reason for employment of such model was an effort to solve a problem of consistent categorization of grants, patents and clinical trials, indexed by Dimensions, which could not be identified within journal-based category system [4]. www.dimensions.ai

1

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In addition, Bornmann implies an advantage of recognition of multidisciplinary journals, which are not classified in corresponding fields in the context of standard journal-based scheme [3]. It is supposed that single paper classification should give a more precise picture of multidisciplinary journals. Instead of one to few categories assigned to a journal, Dimensions offers a large amount of categories, of which few, assigned to single paper. In that way the categories with the biggest share in total number of categories assigned to the papers published in the indexed journal should point out the journal scope.

In that regard, this paper brings further research on the novelty of Dimensions classification system in terms of applicability in evaluation of the field of textile technology from the standpoint of Croatian scientific career advancement system. The textile technology was used as a case study because it is the author’s field of interest and professional activity.

The Croatian scientific career advancement system and overall evaluation of science is oriented on journalbased classification system. Science is classified in to the fields and subfields according to the Fields of Science and Technology (FOS) published by Organization for Economic Co-operation and Development (OECD). In order to advance in higher title, a researcher or academic must meet a number of criteria among which are papers published in a journal within the same field of science as his or hers vocation. The same is with evaluation and accreditation of academic or scientific institutions. Members of such institutions are supposed to publish papers in the journals with the aim and scope of the same scientific field as its institution’s registered activity.

Given that, the usefulness of the introduced novelties of Dimensions classification will depend on accuracy of machine learning category assignment opposed to the traditional journal based classification system used by the Web of Science and Scopus.

Assuming that the Croatian model is not the only one and that there are some similar models in other countries an analysis of possible benefits of Dimensions classification in such a context is conducted in order to get a bigger picture.

Initial studies already put in question the reliability and general validity of results of machine learning classification at the article level. Although, it is likely to be questionable in the field of Textile technology as well, this research will demonstrate empirically the accuracy of this classification. Since Dimensions aims to offer the alternative to traditional classification, it is important to conduct such a research. Users from textile research community that are not familiar with the new Dimensions platform should have an insight of its value. In addition, previous articles on this matter stated that more empirical studies are needed [1,2,3].

Within the novelty of Dimensions platform, another question arises. In the paper bibliographic records one key element is missing – the keywords. Could it be assumed that the assigned categories took over the role of the keywords in some way? If a comparison is made, the purpose of the keywords is virtually the same as the assigned research categories. The point is to describe the specific paper with the standardized words enabling the interconnection in terms of discovering related papers or determination of specific field of science. The absence of the keywords in the Dimensions paper bibliographic records, while both Web of Science and Scopus employ them, goes in favor of the assumed. Besides the author keywords, stated in the papers themselves, Web of Science and Scopus offer service like KeyWords Plus and Indexed keywords bringing the additional relevant keywords that were not listed by the author or publisher. These services offer the greater possibility of uncovering more papers that may not have been listed in the results of one’s search [5].

The real reason behind the absence of the keywords is unknown. Additionally surprising is the fact that the keywords are stated in the papers anyhow so it would be easy to index them and present in the paper record.

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The reasons for the lack of the keywords should be investigated further or should be explained by Dimensions. If the argument of relationship between the field categories and keywords is valid, the importance of introduced novelties is reduced.

METHOD The aim of this research is to see whether the novelty of Dimensions classification has some usability value in comparison to standard journal based classification systems brought by relevant scientific databases in terms of journals and papers they index within the field of textile technology. If so, assigned categories should match with those assigned by Web of Science and Scopus. Additionally, in what proportion categories assigned by Dimensions relate to the journals identified to pertain to the field of textile technology.

Methodological approach time span of the research was 2017 since it is the last year with available data in the InCites Journal Citation Reports (JCR) and Scimago Journal & Country Rank (SJR). There was no need to use a wider time span than a year, because it gave representative number of papers (N=1163) and if there were some errors or misclassifications in the data they would appear most likely. Comparison of the results in the Web of Science, Scopus and Dimensions is made, analyzing the results for any correlation.

The starting point of the research was the Web of Science category Materials Science, Textiles in the JCR. This category was chosen since it gathers all indexed journals focused on the manufacture of clothing and furniture from materials made of natural fibers (e.g., leather, cotton, wool, wood) and/or synthetic fibers (e.g., polyester, vinyl, nylon), covering dyes and colors and fiber chemistry [6]. There are 24 indexed journals in this category in 2017. The 13 of them have the Materials Science, Textiles as only assigned category. For the reason of strict determination of textile technology, these 13 journals will be analyzed and compared in Scopus and Dimensions classification. Other 11 journals have few categories assigned one of which is Materials Science, Textiles. They are excluded for the possibility of misleading in direction of other assigned categories. Shown in the Table 1.

Table 1. Journals indexed in Web of Science category Materials Science, Textiles in InCites Journal Citation Reports in 2017

Journal Data Filtered By: Selected JCR Year: 2017 Selected Editions: SCIE Selected Categories: â&#x20AC;&#x2DC;MATERIALS SCIENCE, TEXTILESâ&#x20AC;&#x2122; Selected Category Scheme: WoS Rank

Full Journal Title

1

CELLULOSE

2

DYES AND PIGMENTS

3

TEXTILE RESEARCH JOURNAL (Only - Materials Science, Textiles)

4

FIBERS AND POLYMERS

5

Journal of Industrial Textiles (Only - Materials Science, Textiles)

6

JOURNAL OF THE TEXTILE INSTITUTE (Only - Materials Science, Textiles)

7

COLORATION TECHNOLOGY

8

JOURNAL OF VINYL & ADDITIVE TECHNOLOGY

9

Journal of Natural Fibers (Only - Materials Science, Textiles)

10

Autex Research Journal (Only - Materials Science, Textiles)

11

WOOD AND FIBER SCIENCE

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12

JOURNAL OF THE AMERICAN LEATHER CHEMISTS ASSOCIATION

13

Journal of Engineered Fibers and Fabrics (Only - Materials Science, Textiles)

14

Journal of Fiber Science and Technology

15

FIBRES & TEXTILES IN EASTERN EUROPE (Only - Materials Science, Textiles)

16

International Journal of Clothing Science and Technology (Only - Materials Science, Textiles)

17

JOURNAL OF THE SOCIETY OF LEATHER TECHNOLOGISTS AND CHEMISTS (Only - Materials Science, Textiles)

18

Industria Textila (Only - Materials Science, Textiles)

19

INDIAN JOURNAL OF FIBRE & TEXTILE RESEARCH (Only - Materials Science, Textiles)

20

AATCC Journal of Research (Only - Materials Science, Textiles)

21

AATCC REVIEW

22

FIBRE CHEMISTRY

23

Tekstil ve Konfeksiyon Only - Materials Science, Textiles)

24

SEN-I GAKKAISHI

*Web of Science InCites Journal Citation Reports, institutional access by AAI@EduHr â&#x20AC;&#x201C; Croatian Research and Education Federation

The second stage of the research was to analyze Scopus based SJR categories assigned to those 13 journals for any correlation. Data for Journal of Engineered Fibers and Fabrics are not available so 12 journal will be compared for relations in assigned categories.

Unfortunately, SJR classification does not have a specific category related to the textile technology, so the results show 11 categories assigned to the journals. Shown in Chart 1.

Chart 1. Representation of SJR subject areas and categories per number of journals in research

Besides the lack of textile technology category, it can be seen, from the Chart 1., that there is not one unique category that is assigned to all 13 journals. It can also be seen that there are some overlapping categories. If related categories are put together, we get that every journal is assigned with category of Materials Sciences. This subject area is too broad to define anything specific. Also, it is the only connection between 148 www.textile-leather.com

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these journals, besides possible citation relations whose analysis is not conducted in this research, showing the limited possibilities of field research in Scopus.

RESULTS It can be said that small group of journals (N=13) indexed in Scopus with scope of textile technology has an unnecessary dispersion in 7 subject areas or 11 subject categories making it impossible to compare them on category level. In addition, there is one deviation. The subject area of Agricultural and Biological Sciences is assigned to The Journal of The Textile Institute. Stated in the journalâ&#x20AC;&#x2122;s scope it welcomes papers concerning research and innovation, reflecting the professional interests of the Textile Institute in science, engineering, economics, management and design related to the textile industry and the use of fibers in consumer and engineering applications [7]. The reason for misclassification is probably, as Wang & Waltman state, in Scopus inaccurate classification [8].

The 10 SJR categories are valid in describing major aspects of textile technology but only when reached through targeted journals, which requires advanced knowledge. In fact, these general categories are useless for not being able to present the group of journals that are related to each other. In this sense, the absence of the specific category of the textile technology is obvious fault.

Lastly, the analysis of categories assigned to the single papers of all 13 journals in Dimensions is not possible because four journals do not have their papers classified. The reason is unknown, but it can be assumed that it is the consequence of Dimensions product development and that those papers will be classified eventually. The nine journals with categories assigned to the single papers show the total of 58 different research fields (Table 2. and Table 3.).

Table 2. Journals with single paper assigned categories indexed in Dimensions out of 13 journals in the comparison No.

Journal title

1

AATCC JOURNAL OF RESEARCH

2

AUTEX RESEARCH JOURNAL

3

FIBRES & TEXTILES IN EASTERN EUROPE

4

INTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY

5

JOURNAL OF ENGINEERED FIBERS AND FABRICS

6

JOURNAL OF INDUSTRIAL TEXTILES

7

JOURNAL OF NATURAL FIBERS

8

JOURNAL OF THE TEXTILE INSTITUTE

9

TEXTILE RESEARCH JOURNAL

Dimensions implements the Field of Research (FOR) system covering all areas of research from the Australian and New Zealand Standard Research Classification (ANZSRC) using automated allocation of FOR codes to indexed documents based on category definitions defined by machine learning [9]. The ANZSRC has a field of textile technology in its classification. It is under division 09 Engineering; group 0910 Manufacturing Engineering as 091012 Textile Technology. Along that, there is a textile engineering under the 0912 Materials Engineering within the same division 09 Engineering. However, analysis of categories assigned to the nine journals shows that there is not a single paper with Textile Technology assigned. The reason for that lies in the Dimensions categorization that is on level 2 with 4 digit codes unlike the original Field of Research

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system, which has three levels with 2, 4 and 6 digit codes. The field 091012 Textile Technology is on the third level with six-digit code.

As such, the complete three level Australian and New Zealand Standard Research Classification (ANZSRC) has 22 divisions, 157 groups and 1238 fields. For comparison, the Web of Science has 235 categories and Scopus uses 27 subject areas with 287 categories. Given that, it can be assumed that Dimensions nonuse of the third level of FOR classification has something to do with the large number of fields. The real reason is unknown.

Table 3. Dimensions categories in relation to number of journals to which papers they are assigned to Category

Number of journals

Manufacturing Engineering 0910

9

Materials Engineering 0912

9

Physical Chemistry (incl. Structural) 0306

9

Artificial Intelligence and Image Processing 0801

7

Civil Engineering 0905

7

Statistics 0104

7

Clinical Sciences 1103

6

Environmental Engineering 0907

6

Interdisciplinary Engineering 0915

6

Applied Mathematics 0102

5

Biochemistry and Cell Biology 0601

5

Macromolecular and Materials Chemistry 0303

5

Other Physical Sciences 0299

5

Psychology 1701

5

Applied Economics 1402

4

Biomedical Engineering 0903

4

Business and Management 1503

4

Chemical Engineering 0904

4

Information Systems 0806

4

Microbiology 0605

4

Analytical Chemistry 0301

3

Cardiorespiratory Medicine and Haematology 1102

3

Communications Technologies 1005

3

Electrical and Electronic Engineering 0906

3

Inorganic Chemistry 0302

3

Medical Physiology 1116

3

Numerical and Computational Mathematics 0103

3

Plant Biology 0607

3

Atomic, Molecular, Nuclear, Particle and Plasma Physics 0202

2

Genetics 0604

2

Nanotechnology 1007

2

Public Health and Health Services 1117

2

Pure Mathematics 0101

2

Soil Sciences 0503

2

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Archaeology 2101

1

Cognitive Sciences 1702

1

Computer Software 0803

1

Crop and Pasture Production 0703

1

Demography 1603

1

Design Practice and Management 1203

1

Econometrics 1403

1

Geophysics 0404

1

Historical Studies 2103

1

Human Movement and Sports Science 1106

1

Language Studies 2003

1

Law 1801

1

Linguistics 2004

1

Marketing 1505

1

Optical Physics 0205

1

Organic Chemistry 0305

1

Other Chemical Sciences 0399

1

Other Medical and Health Sciences 1199

1

Performing Arts and Creative Writing 1904

1

Physiology 0606

1

Resources Engineering and Extractive Metallurgy 0914

1

Sociology 1608

1

Specialist Studies In Education 1303

1

Veterinary Sciences 0707

1

At first glance, the distribution of the valid categories on journal level is 100%. All 10 journals have Manufacturing Engineering and Materials Engineering assigned to at least one paper. Both group categories include textile technology and textile engineering outlining the field of investigation. Third and last category that is assigned to at least one paper published in every journal is Physical Chemistry, which also have meaningful relation.

Nevertheless, the results on the single paper level are not so favorable. In total number of papers (N=918) published in nine journals in 2017, categories Manufacturing Engineering and Materials Engineering are underrepresented with 143 (15.6%) and 298 (32.4%) papers. Such a small share of valid categories is completely unexpected. It is not even possible to define the related field of science to the journals. With such high dispersion of categories and obvious incorrectly assigned categories whole classification model comes in question.

The worst thing is that group 0910 Manufacturing Engineering, to which 091012 Textile Technology strictly belongs in FOR system, has second smallest share of three most represented categories. The share of 15.6% is significantly smaller than Materials Engineering (32.5%), which does not even have field related to the textile technology in its classification. Textile engineering is only mentioned in the context of 091209 Polymers and Plastics. Representations are shown in Table 4.

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Table 4. Representation of relevant categories per indexed papers Category

Number of papers*

Share

Materials Engineering 0912

298

32.5%

Manufacturing Engineering 0910

143

15.6%

Physical Chemistry (incl. Structural) 0306

137

14.9%

*Total number of papers - 918

In addition to that, in total relations of all indexed papers, regardless of years published, in nine journals the picture is even worse. Manufacturing Engineering has a share of 12.5%, Materials Engineering has 17.2% and Physical Chemistry has 11.6%.

The most of the other categories point out various aspects of textile technology but only under the condition that those categories are not the assigned primary. They can be assigned as a complementation to the field of Manufacturing Engineering.

Further analysis of currently assigned categories shows obvious mistakes. For example, article entitled Characterization of Thermal Properties of Pig Hair Fiber published in Journal of Natural Fibers (2017, Vol. 14, Iss. 2) is classified as 0707 Veterinary Sciences. The field of research is incorrectly assigned because article investigates the thermal properties of pig hair fiber in order to provide insights for application in places where natural fibers are utilized for insulation. Another article entitled Using a 3D Body Scanner in Designing Compression Products Supporting External Treatment published in Fibres and Textiles in Eastern Europe (2017, Vol. 25, Iss. 5) shows the same inaccuracy. The article comprises a statistical tolerance analysis of human body dimensions using a 3D body scanner and its impact on the value of unit pressure exerted by a compression product on the subjectâ&#x20AC;&#x2122;s body. Instead of clothing technology or its related category the assigned field of research is 1801 Law. The reason for that is the Laplace law used in model calculations of changes in unit pressure. The machine picked the term law and automatically assigned it to the category of 1801 Law. The same principle repeats throughout the majority of indexed papers. The list of articles with incorrectly assigned categories is too long to present them all. These two examples are quite enough to get the insight. It is impossible to conduct deeper analysis because there are no valid grounds. Application of advanced bibliometric methods would be pointless.

The FOR system has classified Textile Technology as a field of research so a suggestion goes to the Dimensions to employ it. If the inherent lack of the FORâ&#x20AC;&#x2122;s third level of classification in Dimensions is put aside, still the under-representation of Manufacturing Engineering indicates inaccuracy of classification model.

Thereby, the Dimensions cannot be recommended for valid analysis, interpretations or result based decision making in terms of field of textile technology. In that regard the possibility of free use, compared to Web of Science and Scopus subscription, is insignificant.

CONCLUSION Comparison of traditional journal based classification, brought by relevant scientific databases, and classification system based on machine learning automatic category assignment on the level of single publication showed some significant differences.

The first level of marked differences is the single paper classification, which disables the journal search by scientific fields. This kind of search is typical for users who wish to explore their possibilities of publication in specific field of research. The comparison of journals, by quartiles according to metric indicators like

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impact factor or SJR, is also common. Due to the nonuse of the third level of FOR’s classification Dimensions provides too broad and general fields for any kind of specific research. Standard metric indicators are also unavailable, at least in the free version of Dimensions which was used in this research.

The second level of mentioned differences is related to the machine learning automatic category assignment. It just does not classify papers correctly. There are numerous misclassifications, which could lead to the wrong conclusions. All papers, which are not assigned with the Manufacturing Engineering, are in the context of this research incorrect. Currently assigned categories can only be complementary or additional in terms of outlining the aspect of research being conducted. The core remains in the field of textile technology.

Results show that the unique category of Textiles in Web of Science fully fits the field of textile technology from Croatian point of view. Dimensions machine learning automatic category assignment on the level of single publication has a potential for providing valuable information but in reality, it just does not work right.

Application of the third level of FOR’s classification and expert guided machine learning is suggested. That is the only way that Dimensions could offer the alternative and rival the Scopus and Web of Science in some way.

REFERENCES [1] Thelwall M. Dimensions: A competitor to Scopus and the Web of Science?. Journal of Informetrics [Internet]. 2018 Mar [cited 2019 Apr 25];12(2):430-435. Available from: https://www.sciencedirect. com/science/article/abs/pii/S175115771830066X doi: 10.1016/j.joi.2018.03.006 [2] Orduna-Malea E, Delgado Lopez-Cozar E. Dimensions: re-discovering the ecosystem of scientific information. El Profesional de la Informacion [Internet]. 2018 Apr [cited 2019 Apr 25];27(2):420-431.

Available from: https://arxiv.org/abs/1804.05365 doi: 10.3145/epi.2018.mar.21 [3] Bornmann L. Field classification of publications in Dimensions: a first case study testing its reliability and validity. Scientometrics [Internet]. 2018 Jul [cited 2019 Apr 25];117(1):637-640. Available from: https://link.springer.com/article/10.1007/s11192-018-2855-y doi: 10.1007/s11192-018-2855-y [4] Bode C, Herzog C, Hook D, McGrath R. A Guide to the Dimensions Data Approach - A collaborative approach to creating a modern infrastructure for data describing research: where we are and where we want to take it [Internet]. Cambridge: Digital Science; 2018 [cited 2019 Apr 25]. 24 p. Available from: https://www.digital-science.com/resources/portfolio-reports/a-guide-to-the-dimensions-dataapproach/ [5] THOMSON REUTERS. Web of Knowledge: User tips – research made easy [Internet]. 2010 [Cited 2019 Apr 26]. Available from: http://interest.science.thomsonreuters.com/content/WOKUserTips-201010-IN [6] Clarivate Analytics. InCites Journal Citation Reports: Materials Science, Textiles – Category Profile [Internet]. 2019 [Cited 2019 May 8]. Available from: https://jcr.clarivate.com/JCRCategoryProfileAction. action?year=2017&categoryName=MATERIALS%20SCIENCE%2C%20TEXTILES&edition=SCIE&categor y=QJ [7] Taylor & Francis Online. The Journal of The Textile Institute: Aims and scope [Internet]. 2019 [Cited 2019 May 10]. Available from: https://www.tandfonline.com/action/journalInformation?show=aimsS cope&journalCode=tjti20 [8] Wang Q, Waltman L. Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus. Journal of Informetrics [Internet]. 2016 [Cited 2019 May 10]. Available from: https:// www.sciencedirect.com/science/article/abs/pii/S1751157715301930 doi: 10.1016/j.joi.2016.02.003 [9] Digital Science. Dimensions – Fields of Research [Internet]. 2019 [Cited 2019 May 13]. Available from: https://app.dimensions.ai/browse/publication/for?and_facet_year=2017&and_facet_source_ title=jour.1136310&redirect_path=/analytics/publication/for/aggregated www.textile-leather.com 153

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Knowledge, attitudes and behavior of consumers towards sustainability and ecological fashion Ă&#x2013;zgĂźr CEYLAN Eskisehir Technical University, Faculty of Architecture and Design, Department of Fashion and Textile Design, Yunusemre Campus, 26470, Eskisehir, Turkey ozgurceylan@eskisehir.edu.tr Original scientific article UDC 391:31:364.68 DOI: 10.31881/TLR.2019.14 Received 23 October 2018; Accepted 22 July 2019; Published Online 26 July 2019

ABSTRACT The knowledge, attitudes and behavior of consumers towards sustainability and ecological fashion were explored through a survey of 476 participants and data were analyzed using descriptive statistics and correlation analysis.

The attitude of participants towards sustainability was found to be positive. However, participants did not show positive behavior towards sustainability practices, meaning the positive attitude does not necessarily reflect on their behavior. Yet, participants who have positive attitudes towards environmental sustainability practices seem to reflect these attitudes relatively more toward their behavior. In addition, the knowledge level of participants was determined to be above the average in terms of ecological fashion. Their attitudes towards ecological fashion were also positive. Yet, this positive attitude, does not always reflect positively on behaviors. The results of this study provide a better understanding of the different factors that can influence consumer behavior towards sustainability, eco fashion and corresponding products, and thus will facilitate the implementation of relevant company strategies.

KEYWORDS Sustainability, ecological fashion, consumer attitude, consumer behavior

INTRODUCTION Economic, social and environmental concerns and threats can no longer be reduced to national boundaries due to the globalization phenomenon [1]. Globally emerged environmental issues in the last decades such as population increase, climate change, decrease of ground water level, destruction of agricultural areas, decrease of living species brought sustainability into the forefront of business practice and scholarly research [2].

Sustainability is defined as finding a balance between using and replacing resources while considering the environment, the economy, and social factors [3]. In contrast to sustainability and related principles, the fashion industry is known for its detrimental effects on the both human and natural resources. In addition to these detrimental effects, the low labor standards of the industry have led to a sweatshop problem [4].

Thus, for many of the fashion companies, sustainability programs addressing environmental and social problems, are implemented as a part of their managements operations and substantial budgets are allocated to

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them [5]. Underlying these sustainability programs is the assumption that consumers know and care about environmental as well as social issues and thus their purchase behavior would be influenced by them.

The variables which motivates individuals for environmental action were indeed found to be knowledge on issues and means of action, attitudes, verbal commitment and an individual’s sense of responsibility [6].

In addition to other factors influencing purchasing decisions, environmental consciousness and attitudes are known to be the most consistent predictor of environmental purchasing behavior [7]. Also for apparel consumption, knowledge and attitudes towards social and environmental issues are significant predictors of socially and environmentally responsible purchasing behavior [8]. The more knowledge and concern related to the issues in the apparel industry results in more support for socially responsible businesses [9].

However, further research is necessary to better understand these relationships.

In this context, the hierarchical relationship between knowledge, attitudes and behaviors serves as the underlying theoretical framework of this study. The main objective is to determine knowledge, attitudes and behavior of consumers towards sustainability as well as ecological fashion and further examine the relationships between them. Specifically, this study sought to explore how knowledge and attitude would influence the behavior towards sustainable and ecological fashion practices. For this purpose, a survey was administered to consumers and data were analyzed using descriptive statistics and correlation analysis. The intent of the research is to provide a better understanding on consumer behavior which might facilitate implementation of relevant marketing strategies.

EXPERIMENTAL Survey method was employed as data collection technique. The questionnaire used to determine the knowledge, attitudes and behaviors of the participants towards sustainability and ecological fashion was prepared based on studies of Hustvedt [10], Kim [11] and Bostic’s [12]. The questionnaire consists of five main sections. The first and second sections of the questionnaire surveyed respectively the participants’ attitude and behavior towards sustainability. The third part aims to determine the knowledge of consumers about ecological fashion. The statements in the fourth section concern participants’ attitudes towards the ecological fashion. In the last section participants’ ecological fashion behavior is determined. The statements in the questionnaire are rated on a five-point Likert scale by which participants indicate either their degree of agreement with the statement ranging from strongly agree (5) to strongly disagree (1), or indicate the frequency with which they carry out the activity mentioned in the statement ranging from always (5) to never (1). For data analysis and interpretation purposes, results generated for attitude and behavior were categorized using the following classifications: Strongly Disagree/Never = 1–1.79, Disagree/Rarely = 1.802.59, Undecided = 2.60-3.39, Agree/Often = 3.40-4.19, Strongly Agree/Always = 4.20-5.0. Also, Cronbach alpha coefficient was calculated to test the reliability of the questionnaire and found to be .77. Özdamar (2004) states if Cronbach’s alpha coefficient is between .60 and .80, then the measurements are “quite reliable” [13]. Additionally, the instrument included standard demographic measures such as gender, age and education level. All collected data were analyzed with SPSS 15 (SPSS Inc., Chicago, IL, USA) using descriptive statistics and correlation analysis. The analyses were conducted with a significance level (α) of ,05.

RESULTS AND DISCUSSION A total of 476 respondents from Eskisehir, Turkey participated in the study. Table 1 provides a full summary of the sample’s demographics.

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Table 1. Sample Demographics Demographics

Percentage

N (476)

Male

42

200

Female

58

276

Below 18

10

48

18-24

42

200

25-35

34

162

36-45

10

48

Above 45

4

18

Below High School

7

33

High School

57

271

Bachelor

24

114

Master

9

44

PhD

3

14

Gender

Age

Education Level

In the first section of the questionnaire the participants were asked to respond 12 different statements about sustainability using a five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree).

An attitude score between 3,40 and 4,19 for a given statement would indicate a positive attitude for the participant towards environmental sustainability practices. It would be possible to state that the participant who scores below 2,60 points has a negative attitude towards corresponding practices. The attitude scores of the participants were found to be above 3,40 for almost all statements. The only statement rated lower than 3,40 was: “Human beings are meant to rule the rest of nature” (Mean: 2,40). The strongest attitude statement in this section on which participants strongly agreed was: “People must be in harmony with nature to survive” (Mean: 4,26). Table 2 demonstrates the list of attitude statements. From these results, it can be stated that participants have a commitment to support the sustainability approach.

Table 2. Participant Attitudes Towards Sustainability Attitude Statement (*Reverse Coded Items)

Mean

Standard Deviation

People must be in harmony with nature to survive.

4,26

1,04

People are recklessly destroying the nature.

4,17

1,13

I care about the environment.

4,10

,96

The balance of nature is very sensitive and fragile.

4,02

1,05

People do not need to adapt to the natural environment, since they can change it according to their needs.*

3,96

1,01

People have the right to change the natural environment according to their needs.*

3,83

1,14

I am well aware of the environmental issues.

3,70

,92

Earth is like a spaceship with limited number of rooms and resources.

3,62

1,13

I see myself as an environmentalist.

3,58

,93

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The number of people on earth is approaching to the limit that earth can take can take.

3,47

1,21

Intervene of people with nature always result in disasters.

3,42

1,12

Human beings are meant to rule the rest of nature.*

2,40

1,12

The second part of the questionnaire measures sustainability behavior of participants. A 5-point Likert scale ranging from 1 (never) to 5 (always) was used to measure the frequency of 12 pre-defined sustainability behaviors. A difference value was calculated to assess participants’ behavior on sustainability. This value shows the distance from the participant’s response to the ideal one. Thus, when the difference value calculated for each question is 0, the participant exhibits ideal behavior, while the value of 4 means no positive behavior towards the sustainability practice. The average value between the two end points is 2. In the case of reaching small difference values than the mean value indicates positive behaviors related to sustainability. As can be seen from the Table 3, only half of the statements scored below the mean value. Thus, it is possible to conclude that participants did not show positive behavior towards sustainability practices. The statements that the participants scored closest to the ideal were: “I prefer to purchase more durable products” and “I reduce gas emission using public transport”. The least ideal statements that the participants scored were: “I write to a politician about environmental issues and topics” and “I donate to environmental groups and/or organizations”. See Table 3 for a complete list of the behavior statements.

Table 3. Participant Behavior Towards Sustainability Behavior Statement

Mean

Standard Deviation

I prefer to purchase more durable products.

1,10

,94

I reduce gas emission using public transport.

1,56

1,29

I buy reusable products instead of disposable products.

1,81

1,01

I return bottles, cans and/or glass to a recycling center.

1,82

1,13

I buy recycled products and/or packed products with recycled packing.

1,86

1,01

I used products with refilling option.

1,88

1,02

I purchase in gross and/or big amounts.

2,02

,99

I recycle newspapers.

2,04

1,31

I read the tags on the product to see if the content is environmentally friendly.

2,08

1,15

I avoid buying products of companies ignorant to environmental issues.

2,14

1,13

I donate to environmental groups and/or organizations.

2,93

,98

I write to a politician about environmental issues and topics.

3,42

,94

In the third section of the questionnaire participants’ level of knowledge about ecological fashion is measured using seven multiple choice questions. The mean knowledge score acquired by participants in this section was 65.97%. Participants scored the highest on the question “Eco Fashion is most closely associated with which concept?”. Nearly 80% of participants chose the correct answer. Only 35.7% of the respondents seems to know that fair trade is one of the characteristics of eco fashion. See all the items in Table 4.

According to the results obtained from this section, it is possible to state that the participants have a level of knowledge above the average in terms of ecological fashion.

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Table 4. Participant Knowledge on Ecological Fashion Knowledge Question

% of Participants Who Correctly Answered

Eco Fashion is most closely associated with which concept:

81,6

People who buy eco-friendly apparel are probably concerned with:

79,6

Green clothing refers to:

76,9

Eco Fashion focuses on clothing that:

69,2

Eco Fashion encompasses all of the concepts except:

68,7

Which of the following is not used in the construction of eco-friendly apparel?

50,1

One of the characteristics of Eco Fashion is fair trade. Fair trade is:

35,7

Mean Knowledge Score

65,97

The fourth part of the questionnaire was prepared to determine the attitudes of participants towards ecological fashion practices. The consumers were asked to respond 12 different statements about ecological fashion using a five-point Likert scale ranging from 1 (Strongly Disagree) to 5 (Strongly Agree). See Table 5 for a complete list of the attitude statements.

Table 5. Participant Attitudes Towards Ecological Fashion Attitude Statement (*Reverse Coded Items)

Mean

Standard Deviation

The dyes and chemicals used in apparel production can be harmful to the environment.

3,97

1,08

Major retailers should carry environmental friendly products.

3,94

1,04

Sustainable agriculture is important to me.

3,86

,96

I feel that I have an ethical obligation to purchase eco-friendly apparel.

3,42

1,00

Eco friendly clothing is too expensive.*

3,38

,95

Eco friendly apparel is a fad that will soon go away.*

3,36

1,08

I go out of my way to buy fairly traded clothing.

3,32

,93

I would not go out of my way to purchase a garment classified as Eco Fashion.*

3,27

,95

The clothing purchases I make as an individual have an impact on the environment.*

3,18

1,04

I would buy eco-friendly apparel to help support organic farming.

3,10

,98

Eco Fashions are primarily for tree huggers.*

3,07

1,12

It takes more energy to recycle clothing than it is worth.*

2,89

,94

An attitude score between 3,40 and 4,19 for a given statement would indicate a positive attitude for the participant towards environmental sustainability practices. It would be possible to state that the participant is undecided on the given statement when the score is between 2,60 and 3,39. The strongest attitude statements in this section was: “The dyes and chemicals used in apparel production can be harmful to the environment” (3,97), “Major retailers should carry environmental friendly products.” (3,94) and “Sustainable agriculture is important to me.” (3,86), respectively. Participants also agree on “I feel that I have an ethical obligation to purchase eco-friendly apparel.” (3,42) statement. Yet, participants were undecided on the rest of statements in this section. The lowest rated statement was: “It takes more energy to recycle clothing than it is worth.” From these results, it can be concluded that participants have a mediocre level commitment to support the ecological approach to fashion.

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The last section of the questionnaire identifies ecological fashion behavior of the participants. A 5-point Likert scale ranging from 1 (never) to 5 (always) was used to measure the frequency of 12 pre-defined ecological behaviors. A difference value was calculated with the same method as in the section two of the questionnaire. Smaller difference values than the mean value (2) indicates positive behaviors related to ecological fashion. As can be seen from the Table 3, only half of the statements scored below the mean value while the other behavior statements scored higher. Thus, it is possible to conclude that participants did not show positive behavior towards ecological fashion practices. The statement that the participants scored closest to the ideal is: “I prefer to wear clothes for a longer period of time instead of high fashion ones”. The least ideal statement that the participants scored was: “I purchase second hand clothing”. See Table 6 for a complete list of the behavior statements.

Table 6. Participant Behavior Towards Ecological Fashion Behavior Statement (*Reverse Coded Items)

Mean

Standard Deviation

I prefer to wear clothes for a longer period of time instead of high fashion ones.

1,24

1,15

I place all unwanted clothing in a box, and store it away in my home.

1,40

1,27

When I purchase clothing I am more concerned about the look and feel of the garment versus if it‘s environmentally friendly.*

1,60

1,12

Purchasing environmentally friendly clothing, increases my peace of mind.

1,73

1,20

I donate my old clothing to charity.

1,82

1,18

I prefer clothes that require washing at low temperature, less ironing and dry quicker.

1,84

1,16

I use worn out garments for rags to do my part in decreasing environmental problems.

2,01

1,09

I am an organic consumer.

2,18

1,17

I purchase garments that are produced in an environmentally safe manner.

2,31

,90

I purchase garments labelled and packed with environmental friendly techniques.

2,33

,96

I purchase garments produced from recycled materials.

2,42

1,02

I purchase second hand clothing.

3,06

1,02

Correlation analysis was performed to determine the relationship between knowledge, attitude and behavior of consumers towards sustainability (Table 7) and ecological fashion (Table 8). Correlation analysis is one of the most commonly used methods to assess the direction and power of relationship between two variables [14].

Table 7. Pearson Correlation Coefficient Between Attitude and Behavior of Consumers Towards Sustainability Variables

Attitude

Behavior

Attitude

-

,215*

Behavior

-

*Correlation is significant at the ,05 level

There was a weak (r = ,215) yet statistically significant (p < ,000) positive correlation between participants’ positive attitudes on sustainability and the corresponding behavior. This finding is in line with previous literature in environmental and social marketing in which indeed weak linkages between attitudes and behavior have been noted [15]. Yet, participants who have positive attitudes towards environmental sustainability

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practices seem to reflect these attitudes relatively more toward their behavior. This finding is also in agreement with previous literature on green purchasing behavior where it was stated that attitudes are the most consistent predictor of pro‐environmental purchasing behavior [7].

Table 8. Pearson Correlation Coefficients Among Knowledge, Attitude and Behavior Towards Ecological Fashion Variables Knowledge

Knowledge

Attitude

Behavior

-

,334*

,221*

-

,350*

Attitude Behavior

-

*Correlation is significant at the ,05 level

A positive correlation was found between participants’ knowledge and their positive attitudes towards ecological fashion practices (r = ,335). Yet, there was a weak positive correlation (r = ,211) between participants’ knowledge on ecological fashion and the corresponding behavior. Also, a statistically significant, yet a weak relationship (r = ,350) was found between participants’ positive attitudes towards ecological fashion and their related behavior. All the correlations were statistically significant at the ,05 level (p < ,000). Although participants exhibited low scores for ecological fashion behavior, in line with previous research, knowledge and attitudes seem to be significant predictors for corresponding behavior [8-9].

CONCLUSION The knowledge, attitude and behavior of consumers towards sustainability and ecological fashion have been studied extensively. The results demonstrate that participants have a positive attitude towards sustainability approach. However, this positive attitude of participants does not necessarily reflect on their behavior towards sustainability practices. Yet, examining the relationship closely between attitudes and behaviors shows that participants who have positive attitudes towards environmental sustainability practices seem to reflect these attitudes relatively more toward their behavior. Also, participants have a level of knowledge above the average in terms of ecological fashion. Their attitudes towards ecological fashion were also found to be positive. Yet, this positive attitude, does not reflect positively on their behaviors. In sum, consumers are well aware and supporting ecological fashion approaches, yet they do not provide sufficient support in the implementation phase. Concerning the relationship between knowledge, attitudes and behaviors, it can be concluded that the increase in knowledge level has a slight positive effect on the attitudes and behaviors related to the ecological fashion practices, and a positive increase in the attitude has also a similar effect on behaviors. It is important to note that there are limitations to this study. Only tentative conclusions should be made from the present study due to the relatively small sample size in a restricted region. Yet, the study provides a better understanding of the different factors that can influence consumer behavior towards sustainability as well as ecological fashion and thus will facilitate implementation of relevant sustainability programs and marketing strategies.

Acknowledgements This work is part of a master thesis conducted in Graduate School of Social Sciences, in Anadolu University under supervision of Prof. Dr. Nuri Çalık.

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REFERENCES [1] Borghesi S, Vercelli A. Sustainable globalisation. Ecological Economics. 2003 44(1):77-89. doi: 10.1016/ S0921-8009(02)00222-7 [2] Ceylan Ö. A research to determine knowledge, attitudes and behaviors of consumer towards environmental sustainability and ecological fashion [Dissertation]. Eskisehir: Anadolu University; 2010.

45 p.

[3] Lorensen M. The balancing act of sustainability. Journal of Family and Consumer Sciences. 2003 Apr;95(2):74.

[4] Shen B, Zheng JH, Chow PS, Chow KY. Perception of fashion sustainability in online community. The Journal of The Textile Institute. 2014 105(9):971-979.

[5] Li WY, Choi TM, Chow PS. Risk and benefits brought by formal sustainability programs on fashion enterprises under market disruption. Resources, Conservation and Recycling. 2015 Nov;104(B):348-353.

[6] Hines JM, Hungerfold HR, Tomera AN. Analysis and Synthesis of Research on Responsible Environmental Behavior: A Meta-Analysis, The Journal of Environmental Education. 2010 18(2): 1-8.

[7] Schlegelmilch BB, Bohlen GM, Diamantopoulos A. The link between green purchasing decisions and measures of environmental consciousness, European Journal of Marketing. 1996 30(5):35-55.

[8] Kozar JM, Kim Y, Connell H. Socially and environmentally responsible apparel consumption: knowledge, attitudes, and behaviors, Social Responsibility Journal. 2013 9(2):315-324.

[9] Dickson MA. Personal values, beliefs, knowledge, and attitudes relating to intentions to purchase apparel from socially responsible businesses. Clothing and Textiles Research Journal. 2000 18(1):19-30.

[10] Hustvedt G. Consumer preferences for blended organic cotton apparel [Dissertation]. Kansas: Kansas State University; 2006. 222-231 p.

[11] Kim H, Damhourst L. Environmental Concern and Apparel Consumption. Clothing and Textiles Research Journal. 1998 Aug;16(3);126-133.

[12] Bostic NC. Knowledge, Attitudes, and Behaviors of College Students in Family and Consumer Sciences Towards Environmentally Friendly Apparel [Dissertation]: North Carolina: North Caroline State University; 2008. 28 p.

[13] Akbulut, Y. Sosyal Bilimlerde SPSS Uygulamaları (Sık Kullanılan İstatistiksel Analizler ve Açıklamalı SPSS Çözümleri). İstanbul: İdeal Kültür&Yayıncılık, 2010. 80 p.

[14] Bayram N. Sosyal Bilimlerde SPSS ile Veri Analizi. Bursa: Ezgi Kitabevi; 2004. 45 p.

[15] Gill JD, Crosby LA, Taylor JR. Ecological concern, attitudes, and social norms in voting behavior. Public Opinion Quarterly. 1986 50(4):537-554.

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Invitation Arranging the collection for spring and summer of

2020.

W

e invite all manufactures and wholesalers to arrange collection of footwear, accessories and related products for spring and summer 2020.

The arrangement will be held in Zagreb on 1st and 2nd of September (Sunday and Monday) 2019 at the Hotel Antunović in Zagreb, Zagrebačka avenija 100a, Croatia.

We also offer the possibility of presenting this year’s collection for autumn and winter if there is any interest. This collection must be clearly marked as this year’s.

Models are presented on the tables of approximate size of 1.00 m2 (+ 4 chairs).

Table price for domestic exhibitors is 400,00 HRK + VAT. Table price for foreign exhibitors is 80,00 €. License fee is 15,00 €.

on 1 and 2 of September 2019 st

nd

(Sunday and Monday)

at the Hotel Antunović Zagreb

The application must be submitted by 14th August 2018 to the email address: pihler@infonik.hr Payment of the total amount is to IBAN: HR7823600001101300785 no later than 17th August 2018 Contact person – Ivan Pihler, +385 98 219 641 Organizer Ivan Pihler

For Infonik Ltd. Vladimir Dubović

Instructions for Authors TEXT LEATH REV TEXT LEATH REV 2 (3) 2019 162-165.

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