This study is an examination of the essential sizing and reference information required by women aged in their 20s to 50s when shopping for athleisure wear online. It is focused on the sizing information that is deemed important by women in this age group, taking into account their age and consumer needs related to size. As our bodies change over time, it becomes increasingly important to have accurate age-specific sizing information when shopping online, especially in the athleisure market, where fit is crucial. In this analysis, it was found that while all age groups prioritize detailed sizing and reference size information, there are differences in their preferences based on age. Younger consumers, particularly those in their 20s and 30s, are most concerned with hip circumference, while women in their 40s and 50s prioritize abdomen measurements, owing to changes in body composition. Additionally, middle-aged groups are more interested in sizing information to reduce the likelihood of returns. These findings highlight the importance of providing accurate age-specific sizing information to build consumer trust, increase brand satisfaction, and reduce return rates. Overall, this study highlights the importance of a personalized approach in online athleisure retail, where accurate sizing information can meet the evolving needs of varying age groups and result in a more satisfying shopping experience.
RohEK.A study on the purchase status of athleisure wear and consumers’ dissatisfaction with online shopping post-COVID-19. Korean Fashion Text Res J2023;
25(2): 165–174.
2.
LeeJKLimHS.A study on purchasing and wearing status of Korean women’s athleisure wear products—Focusing on women in their 20s to 50s. Korean Fashion Text Res J2021;
23(3): 370–379.
3.
AnEJ.A study on athleisure fashion tendency and consumer behavior according to COVID-19 pandemic. Korean Soc Des Cult2022;
28(1): 239–249.
KimGAKimCK, andKimMJ.An analysis of the problem for providing product information in internet shopping mall. Korean Fashion Text Res J2013;
38: 387–397.
6.
LazimNAMSulaimanZZakuanN, et al. Measuring post-purchase regret and impulse buying in online shopping experience from cognitive dissonance theory perspective. Proceedings of the 6th international conference on information management, London, UK, 27–29 March 2020, pp. 7–13. Piscataway, NJ: IEEE.
7.
JeonEJLeeAL.Consumer awareness and preferences regarding apparel sizing in online shopping. Korean Fashion Text Res J2024;
26(1): 25–34.
8.
LeeMYHwangSJ.A study on the size information presentation method of women's upper garments in internet shopping malls for the improvement of consumer satisfaction. J Korean Soc Costume2013;
63(3): 95–109.
9.
ParkJHLeeAL.The sizing communications of menswear on retail websites. J Korean Soc Clothing Text2023;
47(1): 73–84.
10.
LeeALKimHE.Sizing communications on online apparel retail websites—Focusing on ready-to-wear women’s pants. Korean Fashion Text Res J2022;
24(1): 117–126.
11.
JeongHY.Analysis of the current state of clothing size systems in children’s clothing online shopping malls. J Korea Fashion Costume Des Assoc2022;
24(3): 145–158.
12.
NestlerAKaressliNHajjarK, et al. Sizeflags: Reducing size and fit-related returns in fashion e-commerce. KDD ’21: Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data mining, Singapore, 14–18 August 2021, pp. 3432–3440. New York, NY: Association for Computing Machinery.
13.
Mohammed AbdullaGSinghS, andBorarS. Shop your right size: A system for recommending sizes for fashion products. Companion proceedings of the 2019 world wide web conference, San Francisco, CA, USA, 13 May 2019, pp. 327–334. New York, NY: Association for Computing Machinery.
14.
SheikhASGuigourèsRKoriaginE, et al. A deep learning system for predicting size and fit in fashion e-commerce. RecSys '19: Proceedings of the 13th ACM conference on recommender systems, Copenhagen, Denmark, 16–20 September 2019, pp. 110–118. New York, NY: Association for Computing Machinery.
15.
LipsonSMStewartS, andGriffithsS.Athleisure: A qualitative investigation of a multi-billion-dollar clothing trend. Body Image2020;
32: 5–13.
16.
Grand View Research. Athleisure market size, share & trend analysis report by product (yoga apparel, leggings), by category, by end-user (men, women, children), by distribution channel, by region, and segment forecasts, 2024–2030. https://www.grandviewresearch.com/industry-analysis/athleisure-market (2024, accessed 13 January 2025).
17.
OlshavskyRWMillerJA.Consumer expectations, product performance, and perceived product quality. J Mark Res1972;
9(1): 19–21.
18.
RintamäkiTSpenceMTSaarijärviH, et al.
Customers’ perceptions of returning items purchased online: Planned versus unplanned product returners. Int J Phys Distrib Logist Manage2021;
51(4): 403–422.
19.
KimYE.Influence of attitudes toward online fashion shopping mall models on shopping emotion and advertising effects. Master’s Thesis, Hanyang University, South Korea, 2013.
20.
RosaJAGarbarinoEC, andMalterAJ.Keeping the body in mind: The influence of body esteem and body boundary aberration on consumer beliefs and purchase intentions. J Consum Psychol2006;
16(1): 79–91.
21.
LeeALKimHE.The sizing communications in online apparel retail websites—Focusing on ready-to-wear women’s tailored jacket. Korean Fashion Text Res J2020;
22(5): 617–627.
KimJHLennonSJ.Information available on a web site: Effects on consumers’ shopping outcomes. J Fashion Mark Manage2010;
14(2): 247–262.
29.
Size Korea–Korean Agency for Technology and Standards. 7th human body size data. https://sizekorea.kr/support/pds (accessed 21 March 2021).
30.
KSK0051:2019. Sizing systems for female adult’s garments.
31.
LouCTseCH.Which model looks most like me? Explicating the impact of body image advertisements on female consumer well-being and consumption behaviour across brand categories. Int J Advert2021;
40(4): 602–628.
32.
ZhangYIkonenIEelenJ, et al.
One size does not fit all: Optimizing size-inclusive model photography mitigates fit risk in online fashion retailing. J Acad Mark Sci. Epub ahead of print 22 July 2024. DOI: 10.1007/s11747-024-01034-9.
33.
MiellSGillS, andVazquezD.Enabling the digital fashion consumer through fit and sizing technology. J Glob Fashion Mark2018;
9(1): 9–23.
34.
SongHKAshdownSP.Female apparel consumers’ understanding of body size and shape: Relationship among body measurements, fit satisfaction, and body cathexis. Cloth Text Res J2013;
31(3): 143–156.
35.
RiekeSEFowlerDCChangHJ, et al.
Exploration of factors influencing body image satisfaction and purchase intent: Millennial females. J Fash Mark Manag2016;
20(2): 208–229
36.
HuangLZhouJLinJ, et al.
View analysis of personal information leakage and privacy protection in big data era—based on Q method. Aslib J Inf Manag2022;
74(5): 901–927.
37.
ZhangJZhengW, andWangS.The study of the effect of online review on purchase behavior: Comparing the two research methods. Int J Crowd Sci2020;
4(1): 73–86.
38.
AnDJLeeJY.Survey on the brand of online custom dress shirts and analysis of the sizing system. Korean Fashion Text Res J2018;
20(5): 556–568.
39.
LeeJEChoiSL, andDoWH.A study on the wearing condition of athleisure wear of Korean women in their 20’s. Korean Fashion Text Res J2017;
19(5): 579–588.
40.
SoloveDJ.Understanding privacy.
Cambridge, MA:
Harvard University Press; 2010.
41.
HyunEKKangMH, andNamYJ.A study on middle and high school boys’ and girls’ uniform wearing conditions. J Korean Soc Clothing Text2008;
32(8): 1190–1201.
42.
KooHK.Analysis of preferences based on purchasing frequencies and recognitions of sizing systems for female garments. J Korea Fashion Costume Des Assoc2011;
13(1): 125–134.
43.
KimKSHanH, andNamYJ.The change pattern of body shape on chronological age in Korea adult women. Korean Fashion Text Res J2017;
19(1): 49–60.
44.
RahmanOYuH.Key antecedents to the shopping behaviors and preferences of aging consumers: A qualitative study. J Fashion Mark Manage2019;
23(2): 193–208.
45.
ChoiYK.Shape classification of body type on adult females and its variation of size and shape according to their age. PhD Thesis, Seoul National University, South Korea, 1997.
46.
KwonSH.A study on somatotypes of 18–54-year-old females. Hum Ecol Res1998;
36(5): 17–27.
47.
SzulcRMusielakK.Product photography in product attractiveness perception and e-commerce customer purchase decisions. Sci Pap Sil Univ Technol Series Organ Manag2022;
166: 783–796.
48.
YangTLouC, andTandocECJr.Realistic skin vs. flawless skin: Explicating the appeal of retouch-free advertising among Chinese women. Int J Advert2023;
42(8): 1315–1351.
