Effects of Certain Factors on Individual Fashion Style
Main Article Content
Abstract
This study investigates the influence of various personal factors on individual fashion style. A quantitative research approach was employed using a questionnaire survey conducted with 813 participants aged 18 to 60 in Bac Giang province, Vietnam. The data were analyzed using descriptive statistics and exploratory data mining techniques with the Random Forest algorithm. The examined factors include gender, age, weight, height, skin tone, hair color, marital status, lifestyle preferences, occupation, income, among others. The results indicate that variables such as age, weight, height, income, and amount spent on fashion significantly influence personal fashion style. The study contributes to building a scientific foundation for the development of fashion product strategies that better meet the needs of Vietnamese consumers.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
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[5] N. T. Le and L. T. H. Thu, Research on the clustering of customers consuming domestic fashion products of company limited comtec, Journal of Science and Technology – Hanoi University of Industry, vol. 61, iss. 1, pp. 91–96, Jan. 2025. [In Vietnamese]: Nghiên cứu phân nhóm khách hàng tiêu dùng sản phẩm thời trang nội địa của công ty trách nhiệm hữu hạn Comtec, Khoa học Công nghệ trường Đại học Công nghiệp Hà Nội, 2025. https://doi.org/10.57001/huih5804.2025.020
[6] N. T. Le, L. T. Lanh, N. T. T. Linh, N. T. A. Ngoc, T. T. Anh, T. T. Q. Trang, and T. Q. Tri, Prediction of women’s fashion product expense in Hanoi City using artificial neural network, Journal of Science and Technology: Engineering and Technology for Sustainable Development, vol. 33, iss. 3, pp. 018–025, Jul. 2023. https://doi.org/10.51316/jst.167.etsd.2023.33.3.3
[7] Johnson, K. Lennon, S.J and Rudd, N. Dress, body and self: research in the social psychology of dress, Fashion and Textiles, vol. 1, Nov. 2014, Art. no. 20. https://doi.org/10.1186/s40691-014-0020-7
[8] Van Lieshout, K. Fashion, identity and the body 1. Culture of Fashion, 2011. [Online]. Available: https://www.academia.edu/37345999/Fashion_Identity_and_the_Body
[9] Rocha, M. A. V., Hammond, L., and Hawkins, D., Age, gender and national factors in fashion consumption, Journal of Fashion Marketing and Management, vol. 9, iss. 4, pp. 380–390, Dec. 2005. https://doi.org/10.1108/13612020510620768
[10] Kim, H., and Choo, H. J., How “K-Style” has influenced the younger generation through local Vietnamese influencers, Fashion and Textiles, vol. 10, iss. 1, Oct. 2023, Art. no. 40. https://doi.org/10.1186/s40691-023-00359-3
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[12] Harinaiha, A., Kansal, A., and Parekh, M., Effects of media representation on youth fashion and style preferences, Evolutionary Studies in Imaginative Culture, vol. 8, S2, 2024.
[13] L. Sztandera, C. Frank, and B. Vemulapali, Prediction of women’s apparel sales using soft computing methods, Knowledge-Based Intelligent Information and Engineering Systems, pp. 506–512, Oct. 2004. https://doi.org/10.1007/978-3-540-30134-9_68
[14] S. Thomassey, M. Happiette, and J. Castelain, A global forecasting support system adapted to textile distribution, International Journal of Production Economics, vol. 96, iss. 1, pp. 81–95, Apr. 2005. https://doi.org/10.1016/j.ijpe.2004.03.001
[15] S. Thomassey, and A. Fiordaliso, A hybrid sales forecasting system based on clustering and decision trees, Decision Support Systems, vol. 42, iss. 1, pp. 408–421, Oct. 2006. https://doi.org/10.1016/j.dss.2005.01.008
[16] Z. Sun, T. Choi, K. Au, and Y. Yu, Sales forecasting using extreme learning machine with applications in fashion retailing, Decision Support Systems, vol. 46, iss. 1, pp. 411–419, Dec. 2008.
https://doi.org/10.1016/j.dss.2008.07.009
[17] A. Aksoy, N. Öztürk, and E. Sucky, Demand forecasting for apparel manufacturers by using neuro-fuzzy techniques, Journal of Modelling in Management, vol. 9, iss. 1, pp. 18–35, Mar. 2014. https://doi.org/10.1108/JM2-10-2011-0045
[18] Tổng cục thống kê, [Online]. Avaiable: https://www.gso.gov.vn/so-lieu-thong-ke, Accessed on:
[19] N. T. Le, L. T. H. Nhung, and N. N. Trinh, Extraction of characteristic breast dimensions of north Vietnamese girl-students using random forests algorithm, Intelligent Systems and Networks, vol. 471, pp. 210–220, Jul. 2022. https://doi.org/10.1007/978-981-19-3394-3_25
[20] Nguyen, V. L., Statistical Processing of Experimental Data: Examples from the Textile and Garment Industry, Hanoi, Hanoi University of Science and Technology Publishing House, 2015.
[21] B. Lantz, Machine Learning with R, Birmingham UK, Packt Publishing, 2013.