Big Data "Price Discrimination": Characteristics·Detriments· Governance
Yun Deng, Man Xu · Theory and Practice of Science and Technology · 2024
In the data-driven market landscape, various online service platforms employ sophisticated and intelligent algorithmic tools to assess and predict consumers' willingness to pay and purchasing power. While these tools contribute positively to orderly competition and rational production, they also facilitate the emergence of new forms of detrimental marketing practices, such as big data "price discrimination." Unlike traditional price discrimination, big data "price discrimination" is underpinned by robust technical support and exhibits characteristics including extensive reach, significant destructiveness, and pronounced concealment. The rise of this adverse marketing behavior not only infringes upon consumers' legitimate rights but also impacts the structuring and advancement of emerging industries while disrupting fair market order. To effectively mitigate the negative repercussions of big data "price discrimination" on both economic stability and societal welfare, governance has made strides toward legal regulation; however, challenges persist in terms of inadequate institutional frameworks, ineffective administrative oversight, and a lack of awareness regarding rights protection. Addressing these governance challenges, this paper proposes targeted solutions aimed at alleviating the potential crises posed by algorithmic misuse on consumer market vitality and the competitive dynamics within the digital economy.