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Exploring E-Commerce Live-Streaming Strategy in China

Authors: Zilu Wang;

Exploring E-Commerce Live-Streaming Strategy in China

Abstract

This article conducts a comprehensive analysis of the most cutting-edge topics in live-streaming e-commerce by reviewing 15 studies published between 2019 and 2024. The research is organized around four core areas of inquiry: live-streaming e-commerce modes and strategies, user participation and behavior, brand marketing and platform strategy, and technology application and influence. The review demonstrates the influence of diverse sales modes, including self-operation and third-party live streaming, on market competition and consumer engagement. Furthermore, the analysis identifies the influence of several key factors on consumer purchasing behavior, the strategic approaches adopted by manufacturers in integrating live-streaming channels, and the implications of AI and blockchain technologies in live-streaming commerce. The findings emphasize the significance of context-specific strategies in optimizing live-streaming e-commerce. They suggest that the successful integration of these technologies and strategies can lead to enhanced consumer engagement, augmented brand visibility, and improved overall market performance. Nevertheless, the study also identifies potential challenges and limitations, including the unpredictability of real-world market dynamics and the risk of reduced innovation in algorithm-driven economies.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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