AI-Enabled Social Commerce and Strategic Resilience: Dynamic Capabilities in TikTok Shop by Tokopedia and Shopee Live
DOI:
https://doi.org/10.61978/novatio.v4i3.1554Keywords:
AI-enabled social commerce, digital marketing resilience, dynamic capabilities, Indonesia’s platform ecosystemAbstract
AI-enabled social commerce has become a strategic form of platform-based digital marketing in Indonesia, where content discovery, live interaction, creators, seller tools, and regulation reshape how digital commerce is organized. This study examines how publicly observable AI-enabled social commerce capabilities support digital marketing strategic resilience in Indonesia’s platform ecosystem. It addresses a platform-level gap by shifting attention from consumer outcomes to the ways platforms translate social commerce features into adaptive capabilities. Using a descriptive qualitative comparative case study, the research analyzes TikTok Shop by Tokopedia and Shopee Live through publicly available secondary data, including regulations, corporate announcements, official platform pages, industry reports, academic literature, credible business news, and public market data. The data were examined through document analysis, qualitative content analysis, event chronology, platform comparison, and capability mapping based on the dynamic capabilities framework. The findings indicate that TikTok Shop by Tokopedia illustrates structural resilience through social content and marketplace integration, whereas Shopee Live illustrates functional resilience through livestream commerce, seller support, and in-app interactive shopping. Conceptually, the study shows that personalization, recommendation, content discovery, live shopping, creator mechanisms, advertising, and seller support become strategically relevant when they support sensing, seizing, and reconfiguring. The study contributes a conceptual model linking AI-enabled social commerce capabilities, dynamic capabilities, and digital marketing strategic resilience, while acknowledging that secondary data do not allow examination of internal algorithms, proprietary performance data, or causal effects.
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