Forecasting the Profitability of the Textile Sector in Emerging European Countries Using Artificial Neural Networks

1. Akhtar, W.H., Watanabe, C., Tou, Y, & Neittaanmäki, P. (2022). A new perspective on the textile and apparel industry in the digital transformation era. Textiles, 2 (4), 633–656. Available from: https://doi.org/10.3390/textiles2040037 AkhtarW.H. WatanabeC. TouY NeittaanmäkiP. 2022 A new perspective on the textile and apparel industry in the digital transformation era Textiles 2 4 633 656 Available from: https://doi.org/10.3390/textiles2040037 Search in Google Scholar

2. Ikram, M. (2022). Transition toward green economy: Technologi)cal Innovation's role in the fashion industry. Current Opinion in Green and Sustainable Chemistry, 37. Available from: https://doi.org/10.1016/j.cogsc.2022.100657 IkramM. 2022 Transition toward green economy: Technologi)cal Innovation's role in the fashion industry Current Opinion in Green and Sustainable Chemistry 37 Available from: https://doi.org/10.1016/j.cogsc.2022.100657 Search in Google Scholar

3. Anis, M, Chawky, S, & Abdel Halim, A. (2023). Mapping innovation. The discipline of building opportunity across value chains. Springer Cham. AnisM ChawkyS Abdel HalimA. 2023 Mapping innovation The discipline of building opportunity across value chains Springer Cham Search in Google Scholar

4. The Business Research Company Textile Global Market Report, 2023. Available from: https://www.thebusinessresearchcompany.com/report/textile-global-market-report The Business Research Company Textile Global Market Report 2023 Available from: https://www.thebusinessresearchcompany.com/report/textile-global-market-report Search in Google Scholar

5. World Trade Organization. World Trade Statistical Review, 2023. https://www.wto.org/english/res_e/booksp_e/wtsr_2023_e.pdf World Trade Organization World Trade Statistical Review 2023 https://www.wto.org/english/res_e/booksp_e/wtsr_2023_e.pdf Search in Google Scholar

6. GMDH Inc. GMDH Sheel Forecasting Software 3.5.8 https://gmdhsoftware.com/docs/demand_forecasting GMDH Inc GMDH Sheel Forecasting Software 3.5.8 https://gmdhsoftware.com/docs/demand_forecasting Search in Google Scholar

7. GMDH, INC. GMDH Sheel Forecasting Software 3.5.8 https://gmdhsoftware.com/docs/learning_algorithms GMDH, INC GMDH Sheel Forecasting Software 3.5.8 https://gmdhsoftware.com/docs/learning_algorithms Search in Google Scholar

8. Refinitiv. Eikon. https://eikon.refinitiv.com/ Refinitiv. Eikon. https://eikon.refinitiv.com/ Search in Google Scholar

9. Peterson Drake, P., & Fabozzi, J.F. (2012). Analysis of financial statements, (3rd ed.), Wiley, 101. Peterson DrakeP. FabozziJ.F. 2012 Analysis of financial statements 3rd ed. Wiley 101 Search in Google Scholar

10. Berk, J., & DeMarzo, P. (2020). Corporate Finance (5th ed.). Pearson. BerkJ. DeMarzoP. 2020 Corporate Finance 5th ed. Pearson Search in Google Scholar

11. Kristóf, T., & Virág, M. (2022). What drives financial competitiveness of industrial sectors in Visegrad Four countries? Evidence by use of machine learning techniques. Journal of Competitiveness, 14(4), 117–136. Available from: https://doi.org/10.7441/joc.2022.04.07 KristófT. VirágM. 2022 What drives financial competitiveness of industrial sectors in Visegrad Four countries? Evidence by use of machine learning techniques Journal of Competitiveness 14 4 117 136 Available from: https://doi.org/10.7441/joc.2022.04.07 Search in Google Scholar

12. Lyroudi, K. (2019). Examination of the liquidity, profitability and indebtness relations for Polish companies with neural networks. In: Horobet, A., Belascu, L., Polychronidou, P. and Karasavvoglou, A. (eds) Global, regional and local perspectives on the economies of Southeastern Europe. Proceedings of the 11th International Conference on the Economies of the Balkan and Eastern European Countries (EBEEC) in Bucharest, Romania, 135–151. LyroudiK. 2019 Examination of the liquidity, profitability and indebtness relations for Polish companies with neural networks In: HorobetA. BelascuL. PolychronidouP. KarasavvoglouA. (eds) Global, regional and local perspectives on the economies of Southeastern Europe Proceedings of the 11th International Conference on the Economies of the Balkan and Eastern European Countries (EBEEC) in Bucharest Romania 135 151 Search in Google Scholar

13. Green, J, & Zhao, W. (2022). Forecasting earnings and returns: A review of recent advancements. The Journal of Finance and Data Science, 8, 120–137. Available from: https://doi.org/10.1016/j.jfds.2022.04.004 GreenJ ZhaoW. 2022 Forecasting earnings and returns: A review of recent advancements The Journal of Finance and Data Science 8 120 137 Available from: https://doi.org/10.1016/j.jfds.2022.04.004 Search in Google Scholar

14. Das, D. (2022). Assessing financial distress and its association with leverage, liquidity and profitability: Evidence from textile industry of Bangladesh. International Journal of Research and Review. 9 (11), 451–462. Available from: http://dx.doi.org/10.52403/ijrr.20221161 DasD. 2022 Assessing financial distress and its association with leverage, liquidity and profitability: Evidence from textile industry of Bangladesh International Journal of Research and Review 9 11 451 462 Available from: http://dx.doi.org/10.52403/ijrr.20221161 Search in Google Scholar

15. Narwal, K.P., & Jindal, S. (2015). The impact of corporate governance on the profitability: An empirical study of Indian textile industry. International Journal of Research in Management, Science & Technology, 3(2), 81–85. https://www.researchgate.net/publication/361924226_The_Impact_of_Corporate_Governance_on_the_Profitability_An_Empirical_Study_of_Indian_Textile_Industry NarwalK.P. JindalS. 2015 The impact of corporate governance on the profitability: An empirical study of Indian textile industry International Journal of Research in Management, Science & Technology 3 2 81 85 https://www.researchgate.net/publication/361924226_The_Impact_of_Corporate_Governance_on_the_Profitability_An_Empirical_Study_of_Indian_Textile_Industry Search in Google Scholar

16. Pham, M., Nguyen, H., & Hoang. Q. (2021). Role of research and development on profitability: An empirical research on textile listed firms in Vietnam. Economic Insights – Trends and Challenges, 4, 1–9. Available from: http://dx.doi.org/10.51865/EITC.2021.04.01 PhamM. NguyenH. HoangQ. 2021 Role of research and development on profitability: An empirical research on textile listed firms in Vietnam Economic Insights – Trends and Challenges 4 1 9 Available from: http://dx.doi.org/10.51865/EITC.2021.04.01 Search in Google Scholar

17. Rahaman, M., & Sur, D. (2014). Profitability trends in selected textile companies in India: A cross-sectional analysis. IUP Journal of Business Strategy, 11(4), 60–81. Available from: https://ssrn.com/abstract=2639035 RahamanM. SurD. 2014 Profitability trends in selected textile companies in India: A cross-sectional analysis IUP Journal of Business Strategy 11 4 60 81 Available from: https://ssrn.com/abstract=2639035 Search in Google Scholar

18. Ullah, A., Pinglu, C., Ullah, S., Zaman, M., & Hashmi, S.H. (2020). The nexus between capital structure, firm-specific factors, macroeconomic factors and financial performance in the textile sector of Pakistan. Heliyon, 6 (8), e04741, 2–10. Available from: https://doi.org/10.1016/j.heliyon.2020.e04741 UllahA. PingluC. UllahS. ZamanM. HashmiS.H. 2020 The nexus between capital structure, firm-specific factors, macroeconomic factors and financial performance in the textile sector of Pakistan Heliyon 6 8 e04741 2 10 Available from: https://doi.org/10.1016/j.heliyon.2020.e04741 Search in Google Scholar

19. Wadho, W., & Chaudhry, A. (2018). Innovation and firm performance in developing countries: The case of Pakistani textile and apparel manufacturers. Research Policy, 47(7). 1283–1294. Available from: https://doi.org/10.1016/j.respol.2018.04.007 WadhoW. ChaudhryA. 2018 Innovation and firm performance in developing countries: The case of Pakistani textile and apparel manufacturers Research Policy 47 7 1283 1294 Available from: https://doi.org/10.1016/j.respol.2018.04.007 Search in Google Scholar

20. Burkhanov, A., & Bakhodirovna, B.D. (2021). Evaluation of economic potential of textile industry enterprises. Fibres and Textiles, 28(2), 9–21. Available from: http://vat.ft.tul.cz/2021/2/VaT_2021_2_2.pdf BurkhanovA. BakhodirovnaB.D. 2021 Evaluation of economic potential of textile industry enterprises Fibres and Textiles 28 2 9 21 Available from: http://vat.ft.tul.cz/2021/2/VaT_2021_2_2.pdf Search in Google Scholar

21. Arslan, Ö., Polatgil, M., & Arslan, E. (2022). Examining the financial ratios and profitability of companies by using ANFIS: A study on leather and clothing industries traided in BIST. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 61, 369–384. Available from: https://doi.org/10.18070/erciyesiibd.1013035 ArslanÖ. PolatgilM. ArslanE. 2022 Examining the financial ratios and profitability of companies by using ANFIS: A study on leather and clothing industries traided in BIST Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 61 369 384 Available from: https://doi.org/10.18070/erciyesiibd.1013035 Search in Google Scholar

22. Suh, WM. (1992). Quality, process, and cost controls—a ‘Random Walk’ in textile profitability. The Journal of The Textile Institute, 83(3), 348–360. Available from: https://doi.org/10.1080/00405009208631208 SuhWM. 1992 Quality, process, and cost controls—a ‘Random Walk’ in textile profitability The Journal of The Textile Institute 83 3 348 360 Available from: https://doi.org/10.1080/00405009208631208 Search in Google Scholar

23. Hawley, D.D., Johnson, D.J., & Raina, D. (1990). Artificial neural systems: A new tool for financial decision-making. Financial Analysts Journal, 46(6), 63–72. Available from: https://doi.org/10.2469/faj.v46.n6.63 HawleyD.D. JohnsonD.J. RainaD. 1990 Artificial neural systems: A new tool for financial decision-making Financial Analysts Journal 46 6 63 72 Available from: https://doi.org/10.2469/faj.v46.n6.63 Search in Google Scholar

24. Hoptroff, R.G. (1993). The principles and practice of time series forecasting and business modelling using neural nets. Neural Computing and Applications, 1, 59–66. Available from: https://doi.org/10.1007/BF01411375 HoptroffR.G. 1993 The principles and practice of time series forecasting and business modelling using neural nets Neural Computing and Applications 1 59 66 Available from: https://doi.org/10.1007/BF01411375 Search in Google Scholar

25. Martín-del-Brío, B., & Serrano-Cinca, C. (1993). Self-organizing neural networks for the analysis and representation of data: Some financial cases. Neural Computing and Applications, 1, 193–206. Available from: https://doi.org/10.1007/BF01414948 Martín-del-BríoB. Serrano-CincaC. 1993 Self-organizing neural networks for the analysis and representation of data: Some financial cases Neural Computing and Applications 1 193 206 Available from: https://doi.org/10.1007/BF01414948 Search in Google Scholar

26. Maciel, L.S, & Ballini, R. (2010). Neural networks applied to stock market forecasting: An empirical analysis. Journal of the Brazilian Neural Network Society, 8(1), 3–22. 10.21528/lmln-vol8-no1-art1 MacielL.S BalliniR. 2010 Neural networks applied to stock market forecasting: An empirical analysis Journal of the Brazilian Neural Network Society 8 1 3 22 10.21528/lmln-vol8-no1-art1 Search in Google Scholar

27. Adhikari, R., & Agrawal, R. K. (2011). A homogeneous ensemble of artificial neural networks for time series forecasting. International Journal of Computer Applications, 32 (7), 1–8. Available from: https://doi.org/10.48550/arXiv.1302.6210 AdhikariR. AgrawalR. K. 2011 A homogeneous ensemble of artificial neural networks for time series forecasting International Journal of Computer Applications 32 7 1 8 Available from: https://doi.org/10.48550/arXiv.1302.6210 Search in Google Scholar

28. Mihai, D.A., & Pica, A.Ş. (2023). The role of artificial intelligence in business sustainability. FAIMA Business & Management Journal, 11(3), 56–67. Available from: https://www.proquest.com/scholarly-journals/role-artificial-intelligence-business/docview/2868337278/se-2 MihaiD.A. PicaA.Ş. 2023 The role of artificial intelligence in business sustainability FAIMA Business & Management Journal 11 3 56 67 Available from: https://www.proquest.com/scholarly-journals/role-artificial-intelligence-business/docview/2868337278/se-2 Search in Google Scholar

29. Serrano-Cinca, C. (1997). Feedforward neural networks in the classification of financial information. The European Journal of Finance, 3(3), 183–202. Available from: https://doi.org/10.1080/135184797337426 Serrano-CincaC. 1997 Feedforward neural networks in the classification of financial information The European Journal of Finance 3 3 183 202 Available from: https://doi.org/10.1080/135184797337426 Search in Google Scholar

30. Aliahmadi, A., Jafari-Eskandari, M., Mozafari, A, & Nozari, H. (2016). Comparing linear regression and artificial neural networks to forecast total productivity growth in Iran. International Journal of Information, Business and Management, 8(1), 93–113. Available from: https://ijibm.elitehall.com/IJIBM_Vol8No1_Feb2016.pdf AliahmadiA. Jafari-EskandariM. MozafariA NozariH. 2016 Comparing linear regression and artificial neural networks to forecast total productivity growth in Iran International Journal of Information, Business and Management 8 1 93 113 Available from: https://ijibm.elitehall.com/IJIBM_Vol8No1_Feb2016.pdf Search in Google Scholar

31. Alexandropoulos, S.A.N., Aridas, C.K, Kotsiantis, S.B., & Vrahatis, M.N. (2019). A Deep Dense Neural Network for Bankruptcy Prediction. In: Macintyre J, Iliadis L, Maglogiannis I, Jayne C. (eds) Engineering Applications of Neural Networks. Proceedings of the 20th International Conference, EANN 2019, Xersonisos, Crete, Greece, 435–444. AlexandropoulosS.A.N. AridasC.K KotsiantisS.B. VrahatisM.N. 2019 A Deep Dense Neural Network for Bankruptcy Prediction In: MacintyreJ IliadisL MaglogiannisI JayneC (eds) Engineering Applications of Neural Networks Proceedings of the 20th International Conference, EANN 2019 Xersonisos, Crete, Greece 435 444 Search in Google Scholar

32. Anandarajan, M., Lee, P., & Anandarajan, A. (2004). Bankruptcy prediction using neural networks. In: Anandarajan M, Anandarajan A, Srinivasan CA. (eds) Business Intelligence Techniques, 117–132. Springer, Berlin, Heidelberg, Available from: https://link.springer.com/chapter/10.1007/978-3-540-24700-5_7 AnandarajanM. LeeP. AnandarajanA. 2004 Bankruptcy prediction using neural networks In: AnandarajanM AnandarajanA SrinivasanCA (eds) Business Intelligence Techniques 117 132 Springer Berlin, Heidelberg Available from: https://link.springer.com/chapter/10.1007/978-3-540-24700-5_7 Search in Google Scholar

33. Mostafa, F., Dillon, T., & Chang, E. (2017). Neural Networks and Financial Forecasting. In: Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk. Studies in Computational Intelligence, 697, 51–80. Springer, Cham. Available from: https://doi.org/10.1007/978-3-319-51668-4_4 MostafaF. DillonT. ChangE. 2017 Neural Networks and Financial Forecasting. In: Computational Intelligence Applications to Option Pricing, Volatility Forecasting and Value at Risk Studies in Computational Intelligence 697 51 80 Springer Cham Available from: https://doi.org/10.1007/978-3-319-51668-4_4 Search in Google Scholar

34. Marak, Z.R., Ambarkhane, D., & Kulkarni, A.J. (2022). Application of artificial neural network model in predicting profitability of indian banks. International Journal of Knowledge-based and Intelligent Engineering Systems, 26(3), 159–173. Available from: https://doi.org/10.3233/kes-220020 MarakZ.R. AmbarkhaneD. KulkarniA.J. 2022 Application of artificial neural network model in predicting profitability of indian banks International Journal of Knowledge-based and Intelligent Engineering Systems 26 3 159 173 Available from: https://doi.org/10.3233/kes-220020 Search in Google Scholar

35. McKinsey and Company. The state of fashion 2024: finding pockets of growth as uncertainty reigns. Report, 29 November 2023. Available from: https://www.mckinsey.com/industries/retail/our-insights/state-of-fashion# McKinsey and Company The state of fashion 2024: finding pockets of growth as uncertainty reigns Report, 29 November 2023. Available from: https://www.mckinsey.com/industries/retail/our-insights/state-of-fashion# Search in Google Scholar

36. World Bank. World development indicators. https://datatopics.worldbank.org/world-development-indicators/ World Bank World development indicators https://datatopics.worldbank.org/world-development-indicators/ Search in Google Scholar