The Role of Digital Platforms in Data Markets: How Platform-Shared Market Data Through Advanced Analytics Empower Firm Innovation

Despite the growing value of data in digital markets, data sharing across firms is constrained by increasingly stringent privacy regulations. Digital platforms with their extensive data and analytical capabilities can help overcome these constraints by sharing market information through advanced analytics rather than raw data. In collaboration with Alibaba’s Taobao Marketplace, we utilize a natural experiment and examine how platform-shared data affect retailers’ performance. We find that advanced data analytics increase retailer sales by 31.8% beyond the effects of descriptive analytics. Analytics leveraging platform-level market data generate larger and more persistent performance gains than those relying solely on firm-level data, with small retailers benefiting disproportionately as market data help bridge their information gaps. Mechanism analyses reveal no effect on price and advertising expenditures; instead, platform-shared data enable retailers to innovate their product assortments, expanding category scope by 6.8% and increasing new stock-keeping unit introductions by 10.5%. This study contributes to the data economy literature by demonstrating that platform-shared market data can serve as a critical input to firm innovation, fostering more effective product assortment innovation and sustained performance improvements. Our findings also inform ongoing debates on data and platforms regulation by offering managerial and policy insights into how nonrival market data can be shared by platforms through data analytics to empower traditional businesses.

This paper was accepted by Duncan Simester, marketing.

Funding: Y. Chen and L. Yang acknowledge the financial support from the National Natural Science Foundation of China [Grant 71991461] and Tsinghua University School of Economics and Management Research Grant. X. Cui acknowledges the financial support from the National Natural Science Foundation of China [Grant 72002096]. B. Wu acknowledges the financial support from the National Natural Science Foundation of China [Grants 72372109 and 71902148] and Guanghua Talent Project of Southwestern University of Finance and Economics.

Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06633 .