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AUT Research Repository advisor Kapitan, Sommer advisor Phillips, Megan author Xu, Yujun 2025-09-03T23:22:51Z 2025-09-03T23:22:51Z 2025 http://hdl.handle.net/10292/19752 Live streaming commerce has emerged as a transformative force in online retail, combing real‑time interaction with traditional e‑commerce to create immersive shopping experiences. This thesis investigates how streamer types, characteristics, community interaction, and information dynamics shape consumer responses in live streaming context. My PhD research makes several key contributions. First, it combines Theory–Context–Characteristics–Methodology (TCCM) framework and Stimulus–Organism–Response (SOR) model to generate the first dual-SOR model between streamers and viewers for live streaming commerce, offering a unified structure that captures both platform and individual factors. Second, it advances empirical understanding by clarifying how streamer type, perceived authenticity, and danmaku volume interact to influence trust, endorsement acceptance, continuance and purchase intention. Third, it extends theory on community interaction by uncovering its dual effects and identifies actionable strategies to balance engagement with information overload and sensitivity. In general, these contributions enrich marketing scholarship on online influencers, social interaction and information management, and provide practical guidelines for brands, platforms, retailers, and streamers to optimise live streaming strategies. Chapter 2 presents a framework‑based systematic literature review of 89 peer‑reviewed articles, synthesising theories, contexts, characteristics, and methodologies (TCCM) of live streaming and live streaming commerce research. Using the Theory‑ Context‑ Characteristics‑ Methodology (TCCM) and dual Stimulus‑ Organism‑ Response (SOR) models, it maps key drivers of streamers and viewers on triggering the commercial impacts of live streaming and proposes a comprehensive future research agenda that spans commercial and social dimensions. Chapter 3 empirically examines the roles of streamer type (macro versus micro), authenticity, and community interaction (danmaku) on consumer responses through four online experiments (N = 900). Study 1 demonstrates that macro‑streamers lead stronger consumer responses by enhancing trust. Study 2 finds that micro‑streamers with low to moderate authenticity can also boost trust and drive engagement. Study 3 shows that while macro‑streamers suffer from overloaded community interaction, micro‑streamers build trust regardless of interaction level. Study 4 reveals that excessive danmaku overloads viewers, reducing trust, endorsement acceptance and purchase intention. Together, these studies illuminate two pathways to effective live commerce strategy: authoritative endorsement by macro‑streamers with moderated interaction and relatable authenticity by micro‑streamers. Chapter 4 integrates these findings to demonstrate the theoretical and practical contributions, and Chapter 5 outlines emerging future research on value co‑creation and co-destruction, social impact, and brand activism in the live streaming era. The thesis offers both theoretical advancements in understanding live streaming strategy and practical guidelines for brands and platforms to optimise this strategy. en Examining the Dynamics of Streamer-Viewer and Community Interactions in Live Streaming Thesis 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 URL https://openrepository.aut.ac.nz/bitstreams/bada859d-b1fb-4e33-9405-851a286549dd/download File MD5 9bae82e8876c302364ca3cb076dd3d53 6949421 application/pdf XuY.pdf URL https://openrepository.aut.ac.nz/bitstreams/bd8bc801-29f2-4f80-84ad-c8e238e44972/download File MD5 2d41016e542884fdb79b1e891fffd269 482616 text/plain XuY.pdf.txt