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Online Fashion Gen-Z Consumers’ Reviews: A Text Mining Approach

Author

Listed:
  • Sudaryanto Sudaryanto

    (Associate Professor, Faculty of Economics and Business, University of Jember, Jl. Kalimantan 37, Jember, East Java, Indonesia 68121)

  • Ivana Rosediana Dewi

    (Faculty of Economics, Universitas Tidar, Magelang, Central Java, Indonesia)

  • Intan Larasati Anisa Rahma

    (Master Student, Faculty of Computer Science, University of Brawijaya, Malang, East Java, Indonesia)

  • Anifatul Hanim

    (Associate Professor, Economics Development, Faculty of Economics and Business, University of Jember, Jl. Kalimantan 37, Jember, East Java, Indonesia 681213)

Abstract

The study aims to evaluate electronic service quality (e-SERVQUAL) and insert the Freudian theory to reformulate the model. The research employs text mining and psychoanalytic models, a unique methodology, to investigate the dominant factors in application services based on customer reviews. Ten thousand reviews were collected online through e-Matahari, Zalora, and Pomelo between 2020 and mid-2023. The re-modelling of the cross theory of electronic service quality and the psychoanalytic model theory from Sigmund Freud reveals that consumers have structured mind (Id, ego, and superego) motives that encourage them to purchase. The electronic service quality theory suggests that a positive image of the service quality would influence the intention to repurchase. The text mining analysis using the Orange application produces ten topic keywords and a sentiment analysis. Using Social Semiotics Analysis (SSA), customer review items are tabulated in a cross-item table and some comments as Id are more ego and superego. This means that Gen-Z consumers prefer to buy fashion products as a result of stimuli, immediate gratification, and instincts. Factors influencing reusing such e-commerce could contribute to quantitative research insights.

Suggested Citation

  • Sudaryanto Sudaryanto & Ivana Rosediana Dewi & Intan Larasati Anisa Rahma & Anifatul Hanim, 2026. "Online Fashion Gen-Z Consumers’ Reviews: A Text Mining Approach," International Journal of Latest Technology in Engineering, Management & Applied Science, RSIS International, vol. 15(9), pages 430-440, September.
  • Handle: RePEc:bjf:ijltem:v:15:y:2026:i:9:a:385
    DOI: 10.51583/IJLTEMAS.2026.150900034
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