Ensuring fair platform practices has become a critical challenge in Operations Management. Increasing anecdotal evidence suggests that digital platforms may leverage consumer data to engage in data-driven price discrimination (DDPD)—charging discriminatory prices to customers based on inferred willingness to pay. Yet, despite widespread concern, no platform has publicly acknowledged the operation of DDPD, and academic research has thus far lacked the means and empirical evidence to quantify its magnitude in practice. Against this backdrop, the first objective of this study therefore is to provide direct evidence on the presence of DDPD. To this end, we conducted a field experiment with a leading e-retailing platform in China. The results reveal that customers for whom the platform possesses more data are subject to a higher level of price discrimination. Recently, various regulations have been introduced to protect consumers from unfair use of their data, but there is a lack of evidence on platform compliance to these regulations. The second research objective is then to investigate whether and to what degree platforms complied with these regulations. We leverage a unique natural experiment in which the Chinese government implemented a new regulation banning DDPD in 2020. The findings reveal that while DDPD practice did not disappear entirely, the level decreased significantly post-regulation. As the first empirical study to present direct evidence of DDPD presence and platform compliance, the findings have significant implications for policymakers, platforms, and customers.

Data sharing between upstream and downstream entities is vital for the success of a supply chain. However, distrust, privacy concerns, data misuse, and the asymmetric valuation of shared data between entities often hinder data sharing. This problem calls for a secure, efficient, fair, and trustworthy data‐sharing mechanism. The key to such a successful system hinges on how to trace the data usage, determine the value of the seller’s data to the buyer and then compensate the seller accordingly. To this end, we design and implement a blockchain‐enabled data‐sharing marketplace for a stylized supply chain. We demonstrate how a blockchain can be used to overcome these impediments in supply‐chain data sharing and provide a detailed tutorial with a step‐by‐step implementation for how to set up such a data exchange prototype using Hashgraph.