Macroscopic properties of buyer-seller networks in online marketplaces

2021-11-18 17:52 - 18:52

Abstract:  Online marketplaces are the main engines of legal and illegal e-commerce, yet the aggregate properties of buyer-seller networks behind them are poorly understood. We analyse two datasets containing 245M transactions (16B USD)  between 2010 and 2021 involving online marketplaces: 28 dark web marketplaces (DWM), unregulated markets whose main currency is Bitcoin, and 144 product markets of one regulated e-commerce platform. We show how transactions in online marketplaces exhibit strikingly similar patterns of aggregate behavior despite significant differences in language, products, time, regulation, oversight, and technology. We find remarkable regularities in the distributions of (i) transaction amounts, (ii) number of transactions, (iii) inter-event times, (iv) time between first and last transactions. We then show how buyer behavior is affected by the memory of past interactions, and draw on these observations to propose a model of network formation able to reproduce the main stylised facts of the data. Our findings have important implications for understanding market power on online marketplaces as well as inter-marketplace competition.