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Curated Memories: The Role of Algorithms and Cultural Memory in Shaping Gen Z’s Fashion Nostalgia
Jönköping University, Jönköping International Business School.
Jönköping University, Jönköping International Business School.
Jönköping University, Jönköping International Business School.
2025 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

Background: Fashion styles from the 1990s and 2000s have made a strong return among Generation Z, especially on social media platforms (e.g., Instagram, TikTok and Pinterest) These platforms not only spread nostalgic trends but also shape how young people relate to the past.

Purpose: This study explores how cultural memory and algorithm-driven content influence Gen Z’s interest in nostalgic fashion. It looks at how personal experiences and repeated exposure online affect how these trends are understood and used as part of identity.

Method: The study used a qualitative approach based on Consumer Culture Theory (CCT). Two online focus groups were held with Gen Z participants who actively follow fashion on social media. A thematic analysis was conducted using an abductive process: starting with codes drawn directly from the participants’ words and then refining them using ideas from theory. Coding was done in Microsoft Word by highlighting and grouping the data into themes

Conclusion: The findings show that Gen Z’s interest in nostalgic fashion is shaped by both personal memories and the constant repetition of certain styles through social media algorithms. Nostalgia becomes a way to express identity, influenced by both emotional connections to the past and the trends made visible online. These insights can help marketers better understand how to connect with Gen Z using messages that feel culturally relevant and digitally aware.

Place, publisher, year, edition, pages
2025. , p. 77
Keywords [en]
Gen Z, Nostalgic Fashion, Cultural Memory, Algorithmic Exposure, Consumer Culture Theory (CCT), Digital Identity Construction
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-68254OAI: oai:DiVA.org:hj-68254DiVA, id: diva2:1965916
Subject / course
JIBS, Business Administration
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Available from: 2025-06-25 Created: 2025-06-09 Last updated: 2025-10-13Bibliographically approved

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CiteExportLink to record
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