The effect of dynamic information cues on sales performance in live streaming e-commerce: an IFT and ELM perspective

Publication Name

Electronic Commerce Research


Compared with traditional e-commerce, the advanced technology of live streaming e-commerce provides more dynamic information cues to enable viewers to make better decisions. Drawing on the information foraging theory (IFT) and elaboration likelihood model (ELM), we construct a synthetic model by considering how live streaming information cues influence viewers’ decision making via two distinct routes (central and peripheral). Using the technology of web crawling and text mining, Douyin’s live streaming data were collected, transformed, and then analyzed by fixed-effect regression. The results indicated that product interpretation duration, popularity cue, and herding information are significantly associated with sales performance in live streaming e-commerce. This study enriches our knowledge about live streaming e-commerce, extends the application of IFT and ELM in the individuals’ information foraging and processing by using objective data in the live streaming e-commerce context, and offers practical suggestions to live streaming e-commerce practitioners.

Open Access Status

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