IMPACT OF ONLINE RECOMMENDATION ON PURCHASE BEHAVIOUR OF GREEN APPAREL ON GEN Z IN AHMEDABAD
DOI:
https://doi.org/10.62737/nqzdxj32Keywords:
Green Apparels, Ecological concerns, Online Recommendations, Gen Z, Purchase behaviorAbstract
The quick growth of e-commerce and the rising awareness of environmental sustainability in the current digital era have changed how consumers shop. Generation Z is one of the most digitally active and ecologically sensitive consumer groups on the market. Examining how internet recommendations for eco-friendly clothing affect Gen Z customers' purchasing decisions is the goal of this planned study. Green gear, which stands for clothing made ethically and sustainably, is being marketed more and more through influencer marketing, online reviews, and digital platforms. The study will look into how things like ecological concerns and trust in online recommendations affect Gen Z's propensity to buy eco-friendly clothing. Online surveys that are structured will be used in a quantitative research strategy. It was found that there were many factors but engagement in sustainable fashion issues having the most impact, credibility was the best predictor, whereas information novelty had no discernible impact on Gen Z's purchasing of green apparels. This study will give marketers important information for creating digital communication plans that will encourage Gen Z consumers to buy eco-friendly clothing.
References
Linh Hoang Nguyen , Mai Thi Tuyet Nguyen, & Hung V. (2019). Materialistic values and green apparel purchase intention among young Vietnamese consumers. Young consumers. DOI: https://doi.org/10.1108/YC-10-2018-0859
[2] Amir Hossein Nabizadeh, J. P., Hamed N. Rafsanjani, & Rajiv Ratn Shah. (2020). Learning path personalization and recommendation methods:A survey of the state-of-the-art. Elesvier. DOI: https://doi.org/10.1016/j.eswa.2020.113596
[3] Danafa, M., Felix Becker, Xiang Song, Bilge Atasoy, & Moshe Ben-Akiva. (2019). Online discrete choice models: Applications in personalized reccomendation. Elsevier . DOI: https://doi.org/10.1016/j.dss.2019.02.003
[4] Iftikhar Alam, Shah Khusro , & Mumtaz Khan. (2021). Personalized content recommendations on smart TV: Challenges,opportunities, and future research directions. Elesvier. DOI: https://doi.org/10.1016/j.entcom.2021.100418
[5] Jain, S., & Jacob Joseph Kalapurackal. (2023). A Systematic Review of green apparel manufacturing. Environmental Research, Engineering and Management . DOI: https://doi.org/10.5755/j01.erem.79.4.34368
[6] Juthamon Sithipolvanichgul, Fahad Asmi, Anushree Tandon, Muhammad Azfar Anwar, & Amandeep Dhir. (2022). Drivers of green apparel consumption: Digging a little deeperinto green apparel buying intentions. Wiley .
[7] Khan, S. J., Badghish, S., Kaur, P., Sharma, R., & Dhir, A. (2022). What motivates the purchasing of green apparel products? Asystematic review and future research. Wiley . DOI: https://doi.org/10.1002/bse.3360
[8] Khare, A., & Amrut Sadachar. (2016). Green apparel buying behaviour: A study on Indian youth. Wiley .
[9] Kim, M. S., & Seongcheol Kim. (2018). Factors influencing willingness to provide personal information for personalized recommendations. Elsevier . DOI: https://doi.org/10.1016/j.chb.2018.06.031
[10] Leea, D. H., & Peter Brusilovsky. (2017). Improving personalized recommendations using community membership information. Elsevier . DOI: https://doi.org/10.1016/j.ipm.2017.05.005
[11] Li Zhao, Bing Fu , & Sha Bai. (2025). Understanding the Influence of Personalized Recommendation on Purchase Intentions from a Self-Determination Perspective: Contingent upon Product Categories. Theoritical and applied electronic commerce research . DOI: https://doi.org/10.3390/jtaer20010032
[12] Pandey, M., & Pinnika Syam Yadav. (2023). Understanding the role of individual concerns, attitude, and perceived value in green apparel purchase intention; the mediating effect of consumer involvement and moderating role of generation Z&Y. Elsevier. DOI: https://doi.org/10.1016/j.clrc.2023.100120
[13] Shang, Q., Jailiang chen, Huijain fu, Cuicui wang, Guanxiang Pei , & Jai jin. (2023). “Guess You Like It” – How personalized recommendation timing and product type influence consumers’ acceptance: An ERP study. Elesvier. DOI: https://doi.org/10.1016/j.neulet.2023.137261
[14] Shen, A. (2013 ). Recommendations as personalized marketing:insights from customer experiences. Emeralds, Journal of Services Marketing. DOI: https://doi.org/10.1108/JSM-04-2013-0083
[15] Shrestha, d. S. (2023). Exploring the impacts of technology and emotion on compulsive . Juni khyat .
[16] Sushant Kumar a, & Rambalak Yadav. (2021 ). The study aims to investigate the impact of shopping motivation on consumers’ intention to buy green apparel. Elsevier .
[17] Ting-Peng Liang, Y.-F. Y., , Deng-Neng Chen , & Yi-Cheng Ku. (2007). A semantic-expansion approach to personalized knowledge recommendation. Elesvier.
[18] Wang, K., Tiantian Zhang , Tianqiao Xue, Yu Lu, & Sang-Gyun Na. (2019). E-commerce personalized recommendation analysis by deeply-learned clustering. Elesvier. DOI: https://doi.org/10.1016/j.jvcir.2019.102735
[19] Zhenga, Y., & Ting Ch. (2014). Factors influencing purchase intention towards environmentally friendly apparel: an empirical study of US consumers. Nternational Journal of Fashion Design, Technology and Education. DOI: https://doi.org/10.1080/17543266.2014.990059
