BIG DATA-DRIVEN CONSUMER BEHAVIOR PREDICTION AS A BASIS FOR SUSTAINABLE DECISION-MAKING: A STUDY OF GENERATION Z IN EAST KALIMANTAN - Nurrohman, Rosyid; Hakim, Ahmad Firman; Hikmah, Mukhibatul; Nadroh, Ummi; Ibrizah, Ziya (GEMAH RIPAH: Jurnal Bisnis, 2025)
This study explores the optimization of big data analytics (BDA) to predict the consumer behavior of Generation Z (1997–2012) in East Kalimantan, Indonesia, within the context of digital transformation. The research aims to identify how localized digital consumption patterns intersect with cultural and infrastructural constraints. Employing a qualitative exploratory design through multiple case studies, data were gathered from 25–30 semi-structured interviews, four focus group discussions, and digital ethnography on platforms such as TikTok and Instagram. Thematic analysis uncovered five major findings: intensive use of TikTok for local product reviews significantly shaped purchase decisions; mixed attitudes toward personalization features; collectivist cultural norms driving peer-influenced behavior; limited awareness of data privacy mechanisms; and the emergence of a predictive model rooted in geo-cultural context. The study concludes that while BDA holds predictive potential, its efficacy is constrained by digital infrastructure and cultural values. A proposed cultural algorithm framework suggests integrating environmental variables and leveraging micro-influencer engagement to enhance sustainable digital decision-making. This research contributes to the development of culturally adaptive big data applications and advances the discourse in technology acceptance and ethical analytics.