Addressing big data discriminatory pricing facilitates healthy and sustainable market development. Photo: TUCHONG 

With the rapid development of digital technology and the platform economy, online consumption via internet platforms has become an essential part of modern life. Alongside this trend, the phenomenon of “big data discriminatory pricing” has emerged, where frequent customers are charged higher prices. Should “big data discriminatory pricing” be strictly prohibited, or does it have legitimate and reasonable grounds for existence? To answer this, three key aspects need to be clarified: the essence of “big data discriminatory pricing,” how big data enables it, and how it should be regulated.

Algorithmic pricing

From an economic perspective, the phenomenon of discriminatory pricing against regular customers refers to a differentiated pricing strategy employed by businesses, leveraging their market dominance, technological capabilities, and information ownership on internet platforms. It is fundamentally a form of price discrimination, which draws criticism for unfairly imposing higher prices on certain consumer groups.

However, not all differential pricing or price discrimination qualifies as “discriminatory pricing against regulars,” nor does this always have negative consequences. On one hand, differentiated and personalized pricing are resource allocation mechanisms of the market that do not inherently violate fairness and justice in market operations. On the other hand, regular customers may face higher prices, while new customers often benefit, with the interests of “regular customers” being damaged while those of “new customers” ensured. From the perspective of total social welfare, discriminatory pricing results in a complex welfare effect that is uncertain in the aggregate. In addition, price differentiation based on big data can intensify price competition across platforms and among businesses. A customer targeted for higher prices by one platform may become a target for discount offers from a competitor. In theory, as long as there is sufficient competition, whether between platforms or within the same platform among different vendors, businesses cannot indefinitely exploit consumer surplus.

Mechanisms 

The formation of big data discriminatory pricing requires at least three conditions, namely, the ability of merchants to implement differentiated pricing, the ability of merchants to identify target users for higher prices, and the acceptance of higher prices by users.

First, monopolistic power or market dominance is a fundamental prerequisite. Second, algorithmic pricing based on big data is a crucial tool. Essentially, discriminatory pricing against regulars is a strategic pricing behavior based on market segmentation. Traditionally, price discrimination was broadly applied by categorizing consumers into “new customers” and “regular customers” based on purchase volume. However, big data discriminatory pricing leverages big data and artificial intelligence to refine consumer segmentation more precisely. Finally, information asymmetry between platform buyers and sellers is a key driver. In the digital economy, data is a critical resource, and its ownership affects how benefits are distributed between buyers and sellers. In the platform economy, big data discriminatory pricing mainly arises from this information asymmetry.

Governance 

Regulating big data discriminatory pricing requires a comprehensive approach that integrates market governance, technological regulation, information management, and agile governance. The focus should be on both addressing root causes and managing symptoms through mechanism design and optimization. Market governance should take priority by improving competitive market mechanisms, while technological governance is essential for ensuring the soundness of algorithmic pricing systems. At the same time, information governance should be the focus, and it must emphasize the enhancement of transparency and the disclosure of information. Agile governance should be the aim and efforts should be guided to strengthen collaborative governance mechanisms.

In summary, as the process of building a high-standard socialist market economy accelerates, it is necessary to approach big data discriminatory pricing behavior dialectically and rationally. By designing fair rules and regulatory mechanisms, we can ensure that the market can play its decisive role in allocating resources and the government can better play its role.

Du Yuwei is an associate research fellow from the Institute of Regional Modernization at Jiangsu Academy of Social Sciences. Han Chao is a professor from the Center for Industrial and Business Organization at Dongbei University of Finance and Economics.

Edited by ZHAO YUAN