Study on the impact of big data sharing on individuals’ welfare—from the perspective of consumption and privacy

This paper constructs a macro-level theoretical framework, grounded in the theory of creative destruction, to explain how big data sharing affects individuals’ welfare from the perspectives of consumption and privacy. First, we treat data as a new type of production factor and endogenize it within the production function. We then propose an innovative view: individuals’ welfare is influenced by both the privacy cost of big data sharing and their consumption levels. Consumption, in turn, is affected by the multiplier effect and the transformation patterns of R&D. Finally, we provide a theoretical analysis of the optimal level of big data sharing and its impact on the growth of individuals’ welfare. Our results indicate that the optimal level of data sharing achieves the best balance between economic development and privacy, thereby maximizing individuals’ welfare. In the short term, big data may inhibit welfare growth; however, in the long term, it promotes sustained improvements in individuals’ welfare. Based on these findings, we propose new mechanisms through which big data affects individual welfare.