Abstract
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.
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Data availability
The datasets analysed during the current study are available from the corresponding author on reasonable request.
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Acknowledgements
The authors are grateful to the financial support provided by the Commission Humanities and Social Science Research Youth Program of 2024 Chongqing Municipal Education (24SKGH084), the National Natural Science Foundation of China(NO.72403148); the Project for Humanities and Social Sciences Project of the Ministry of Education (No. 23YJC790069); the Project for Shandong Provincial Natural Science Foundation (No. ZR2023QG053); the Project for Shandong Provincial Key Research and Development (Soft Science Projects) (NO. 2024RKY0101); the Project for Shandong Social Science Planning Fund Program (NO. 23DJJJ17); Project of the Research Center for Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era in Jiangsu Province(25ZXZB001) and Chongqing Normal University Foundation (24XWB008).
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HHD wrote manuscripts, and used software to do the scenario simulation and calibrate the paper. Both authors read and approved the final manuscript. XML proposed the idea, gave the method guidance for the paper, and wrote the research background. YDL refined the model and checked the revised manuscript. CW participated in revising the model optimization of revised manuscript, supplemented the content of the first draft, and checked the grammar. All authors contribute equally to this work.
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Dong, H., Li, X., Liu, Y. et al. Study on the impact of big data sharing on individuals’ welfare—from the perspective of consumption and privacy. Humanit Soc Sci Commun (2026). https://doi.org/10.1057/s41599-026-06747-6
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DOI: https://doi.org/10.1057/s41599-026-06747-6
