Abstract: From the perspective of the non-rivalrous nature of data, and based on the theoretical models of data’s ability to promote horizontal technological innovation in endogenous industrial structural transformation, this paper conducts a study. The findings demonstrate that data factors will influence sectoral technological innovation through direct data innovation effects and data cost effects, as well as indirect market size effects. The data innovation effect strengthens innovation incentives in sectors with higher data innovation elasticity, while the data cost effect weakens these incentives. These two mechanisms jointly determine the contribution rate of data to technological innovation. Departments with higher data innovation contribution rates experience faster technological progress than those with lower rates. Since the products of the two departments are not substitutes, the relative price effect drives factors toward departments with lower data innovation contribution rates. When data ownership is held by consumers, data privacy costs will restrict data transactions, thereby limiting data’s contribution to technological innovation and economic growth. The above conclusion implies that the government should strengthen data privacy management, improve the design of data ownership structures, and enhance the level of public data sharing to facilitate in-depth development and utilization of the existing data.

Key words: data element, technological innovation, industrial structural transformation, economic growth