Identifying Dynamic Competition in Online Marketplaces Through Consumers’ Clickstream Data
Meihua Zuo, Spyros Angelopoulos, Carol Xiaojuan Ou, Hongwei Liu, Zhouyang Liang
Brands in online marketplaces are constantly faced with the challenge of identifying market structure and analyzing competitiveness. To address that lacuna, we model brands’ competition through consumers’ consideration sets. We draw on a dataset of 6,549,484 records over a period of 10 weeks from one of the biggest online marketplaces in China and employ network analysis to predict sales. We explore the relationship between products’ network position and brands’ sales volume through the local and global centrality and closure, and we depict the redistribution of market-share of related products after brands adjust production line length. Our analysis suggest that the span of structural holes of a brand negatively influences sales volume, while betweenness and degree centrality have a positive impact. Our findings show that the relationship among products of a brand has a significantly greater impact on sales volume compared to the relationships among brands, and the intra-brand product relationship is the main reason for sales volume fluctuations. We contribute to understandings of brand dynamic competition in online marketplaces and discuss the significance of our findings for brand competition in online marketplaces, while we draw an agenda for future research on the topic.
Suggested Citation: Zuo, M., Angelopoulos, S., Ou, C.X., Liu, H., and Liang, Z, Identifying Dynamic Competition in Online Marketplaces Through Consumers’ Clickstream Data (April 22, 2020). Available at SSRN: https://ssrn.com/abstract=3598889