Thesis or dissertation
Date of this Version
In eCommerce, information asymmetry between sellers and buyers has greatly increased compared to traditional offline retail due to increased temporal and physical distance. Signal theory suggests that signals play a key role in closing this information gap, building consumer trust, and increasing purchasing intent. This paper analyzes how different signals on Amazon.com, the largest eCommerce platform in the United States, impact sales rank through a panel regression analysis of 30 days of data in the Lip Scrub category. This study finds that Amazon.com-generated signals are more impactful than user-generated or sponsored signals and that sponsored product recommendations are not as effective as other studied signals, even though sellers pay to be sponsored. Future research can dive deeper into these signals and better understand their relationship with sales volume, growing the understanding of how consumers are influenced by information signals.
Amazon, signal, sales, eCommerce, signal theory, sales rank, sponsored, listings, tags, lip scrub
Date Posted: 15 October 2019