Journals / 21. Yüzyılda Fen ve Teknik / 2026 / Cilt: 13

The Textile Industry in the Era of Global Competition: A Strategic Analysis of Sustainable Competitive Advantage

Küresel Rekabet Çağında Tekstil Endüstrisi: Sürdürülebilir Rekabet Avantajının Stratejik Analizi

Murat Kodaloğlu(ISPARTA UYGULAMALI BİLİMLER ÜNİVERSİTESİ)0000-0001-6644-8068
Feyza Akarslan Kodaloğlu(SÜLEYMAN DEMİREL ÜNİVERSİTESİ)0000-0002-7855-8616
Pages
11–24
Publication Date
2026-09-21
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With demand=70, innovation=60, machinery=80, workforce=65, sustainability=75, and supply chain=55, the competitive advantage was calculated to be approximately 0.78.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:With the acceleration of globalization, textile businesses operate under intense competitive pressure.
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Key Findings & Data:In the model, six key criteria—demand level, machine status, labor productivity, innovation level, sustainability pressure, and supply chain performance—are evaluated using a fuzzy logic approach, and a competitive advantage output is obtained.
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Conclusion & Impact:With demand=70, innovation=60, machinery=80, workforce=65, sustainability=75, and supply chain=55, the competitive advantage was calculated to be approximately 0.78.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Tekstil işletmeciliği · Küresel rekabet · İnovasyon

Abstract

With the acceleration of globalization, textile businesses operate under intense competitive pressure. To gain a competitive advantage, developing innovative products, systematically conducting innovation activities, optimizing production processes, and increasing efficiency are critically important. Furthermore, strengthening supply chain management, effectively utilizing new technologies, and integrating into global markets through global collaborations stand out as fundamental elements for sustainable success. This study examines the evaluation of competitive advantage in textile businesses from a multi-criteria decision-making (MCDM) perspective and proposes an innovative fuzzy logic-based decision support model to overcome the limitations of classical deterministic methods. In the model, six key criteria—demand level, machine status, labor productivity, innovation level, sustainability pressure, and supply chain performance—are evaluated using a fuzzy logic approach, and a competitive advantage output is obtained. The findings demonstrate that the fuzzy logic-based approach produces more realistic and flexible results in uncertain competitive conditions and offers a strong alternative to classical MCDM methods. As demand and machine status increase, competitive advantage is observed to systematically rise. This confirms the internal consistency of the fuzzy rule base and demonstrates that the model exhibits the expected behavior. With demand=70, innovation=60, machinery=80, workforce=65, sustainability=75, and supply chain=55, the competitive advantage was calculated to be approximately 0.78.

Özet

Küreselleşmenin hızlanmasıyla birlikte, tekstil işletmeleri yoğun rekabet baskısı altında faaliyet göstermektedir. Rekabet avantajı elde etmek için, yenilikçi ürünler geliştirmek, sistematik olarak inovasyon faaliyetleri yürütmek, üretim süreçlerini optimize etmek ve verimliliği artırmak son derece önemlidir. Ayrıca, tedarik zinciri yönetimini güçlendirmek, yeni teknolojileri etkin bir şekilde kullanmak ve küresel iş birlikleri yoluyla küresel pazarlara entegre olmak, sürdürülebilir başarı için temel unsurlar olarak öne çıkmaktadır. Bu çalışma, tekstil işletmelerinde rekabet avantajının değerlendirilmesini çok kriterli karar verme (MCDM) perspektifinden incelemekte ve klasik deterministik yöntemlerin sınırlamalarının üstesinden gelmek için yenilikçi bir bulanık mantık tabanlı karar destek modeli önermektedir. Modelde, altı temel kriter—talep düzeyi, makine durumu, işgücü verimliliği, inovasyon düzeyi, sürdürülebilirlik baskısı ve tedarik zinciri performansı—bulanık mantık yaklaşımı kullanılarak değerlendirilmekte ve rekabet avantajı çıktısı elde edilmektedir. Bulgular, bulanık mantık tabanlı yaklaşımın belirsiz rekabet koşullarında daha gerçekçi ve esnek sonuçlar ürettiğini ve klasik MCDM yöntemlerine güçlü bir alternatif sunduğunu göstermektedir. Talep ve makine durumu arttıkça, rekabet avantajının sistematik olarak arttığı gözlemlenmektedir. Bu, bulanık kural tabanının iç tutarlılığını doğrular ve modelin beklenen davranışı sergilediğini gösterir. Talep=70, yenilik=60, makine=80, iş gücü=65, sürdürülebilirlik=75 ve tedarik zinciri=55 değerleriyle rekabet avantajı yaklaşık 0,78 olarak hesaplanmıştır.

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Cite This Article

Kodaloğlu, M., Kodaloğlu, F. A. (2026). The Textile Industry in the Era of Global Competition: A Strategic Analysis of Sustainable Competitive Advantage. 21. Yüzyılda Fen ve Teknik, Cilt: 13, 11–24. https://ajindex.com/articles/1628553

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References (24)

  1. Abrar, M., Ali, S., Baig, S., Amjad, F., Rizwan, S., & Mohsin, B. (2019). Innovation is creating competitive advantage: A perspective to improve the organic textile products for business growth. Industria Textila, 70(2). https://doi.org/10.35530/it.070.02.1644
  2. Alam, M., Hosen, M., Mridha, J., Chowdhury, S., & Rahman, M. (2023). Assessing the barriers of integrating technological innovations in textiles sector: Implications towards sustainable production. Green Technologies and Sustainability. https://doi.org/10.1016/j.grets.2023.100039
  3. Arora, S., & Majumdar, A. (2022). Machine learning and soft computing applications in textile and clothing supply chain: Bibliometric and network analyses to delineate future research agenda. Expert Systems with Applications, 200, 117000. https://doi.org/10.1016/j.eswa.2022.117000
  4. Beltrán, L., Calderón, L., Guerra, V., Acosta, B., & Aguilar, J. (2025). Competitiveness analysis of the textile sector. Journal of Globalization, Competitiveness and Governability, 19(2). https://doi.org/10.58416/gcg.2025.v19.n2.01
  5. Chen, C. T., & Lee, H. T. (2010). Fuzzy decision making in manufacturing systems. International Journal of Production Economics, 125(2), 240–248.
  6. Dimitrijević, D. (2021). Theses for new strategies of work and development of textile and clothing industry, part 3. Tekstilna Industrija. https://doi.org/10.5937/tekstind2104004d
  7. Gu, B. (2025). Innovative model and international market exploitation of fabric export trade. Textile & Leather Review. https://doi.org/10.31881/tlr.2025.004
  8. Harsanto, B., Primiana, I., Sarasi, V., & Satyakti, Y. (2023). Sustainability innovation in the textile industry: A systematic review. Sustainability, 15(2), 1549. https://doi.org/10.3390/su15021549
  9. Hossain, M., Shahid, M., Limon, M., Hossain, I., & Mahmud, N. (2024). Techniques, applications, and challenges in textiles for sustainable future. Journal of Open Innovation: Technology, Market, and Complexity. https://doi.org/10.1016/j.joitmc.2024.100230
  10. Jariwala, G., Krishna, H., Biswas, D., & Bargavi, S. (2025). Transforming the textile industry: A study on sustainable manufacturing and innovation. International Journal on Science and Technology, 16(2). https://doi.org/10.71097/ijsat.v16.i2.4400
  11. Kodaloğlu, A. İ., & Yiğit, M. (2025). Isparta ilinde faaliyet gösteren firmaların ihracat sorunlarına ilişkin bir araştırma. Türkiye Mesleki ve Sosyal Bilimler Dergisi, 6(16), 1–24.
  12. Kodaloğlu, M., Akarslan, F., & Kodaloğlu, A. İ. (2021). Problems faced in export by the ginner role, cost analysis and assessments in terms of occupational safety. International Journal of Engineering and Innovative Research, 4(1), 23–32.
  13. Khan, M. J., Akram, M., Gurmani, S. H., Jiang, S., & Ding, W. (2026). Circular Intuitionistic Fuzzy Knowledge Modeling for Multi-Criteria Decision-Making in Supplier Selection. IEEE Transactions on Emerging Topics in Computational Intelligence. https://doi.org/10.1109/tetci.2026.3700942
  14. Marsono, M., Nasyuha, A. H., Widyayanti, E. R., & Chung, M.-Y. H. (2026). Evaluation of Green Marketing Strategy Using Fuzzy AHP-Based Decision Support System. Sinkron. https://doi.org/10.33395/sinkron.v10i3.16277
  15. Nguyen, X., Doan, T., & Hoang, V. (2020). The impact of global supply chain management on performance: Evidence from textile and garment industry. Uncertain Supply Chain Management, 8, 17–26. https://doi.org/10.5267/j.uscm.2019.9.003
  16. Purnomo, A., Syafrianita, S., Rahayu, M., Rohyana, C., Lestiani, M., Supardi, E., & Yant, R. (2024). Leveraging green innovation and green ambidexterity for green competitive advantage: The mediating role of green resilient supply chain. Uncertain Supply Chain Management. https://doi.org/10.5267/j.uscm.2024.5.003
  17. Radko, S., Prishlyak, E., & Nevmerzhitskaya, O. (2022). Innovative development of the textile industry in a competitive environment. International Conference on Textile and Apparel Innovation (ICTAI 2021). https://doi.org/10.1063/5.0076975
  18. Salehi, F., Gholamveisy, S., Rostamzadeh, R., Šaparauskas, J., & Turskis, Z. (2026). Hybrid Decision Making Model-Unitising for the Analysis of Competitive Intelligence, Green Marketing and Green Purchase Intention in the Pursuit of Sustainability. Transformations In Business & Economics. https://doi.org/10.15388/tibe.2026.25.1.5
  19. Tseng, M., Bui, T., Lim, M., Fujii, M., & Mishra, U. (2021). Assessing data-driven sustainable supply chain management indicators for the textile industry under industrial disruption and ambidexterity. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2021.108401
  20. Vela, J., Everling, M., Floriano, J., Stammerjohann, A., & De S. Cavalcanti, A. (2025). Sustainable innovation in products and services for the textile industry. ENSUS – Encontro de Sustentabilidade em Projeto. https://doi.org/10.29183/2596-237x.ensus2025.v13.n1.p1375-1385
  21. Wang, P., & Cheng, H. (2025). Research on the competitive situation and technical opportunities of global new textile materials technology R&D. PLOS One, 20. https://doi.org/10.1371/journal.pone.0321923
  22. Widodo, D., Primiana, I., Cahyandito, M., & Sutarman, S. (2024). Influence of technology and government regulations on the competitiveness of the textile industry: Case study of Indonesia. Uncertain Supply Chain Management. https://doi.org/10.5267/j.uscm.2024.1.010
  23. Yeganegi, K., & Najafi, A. (2022). The impact of innovation strategies on export performance: A case study of the textile industry. International Journal of Scientific Research and Management. https://doi.org/10.18535/ijsrm/v10i12.em05
  24. Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353.