Research on the impact of data elements utilization on new quality productive forces under the background of digital economy

Leveraging data elements to enhance the formation of new quality productive forces (NQPF) is crucial for achieving a competitive edge in development. This study examines data from China’s A-share listed companies spanning the years 2011 to 2022, grounded in the established theory of data elements driving NQPF. Utilizing panel regression alongside dynamic QCA, this research empirically assesses the impact and configuration effects of enterprises’ utilization of data elements on the advancement of NQPF. The findings reveal that (1) the extent to which enterprises utilize data elements significantly affects the enhancement of NQPF. This conclusion persists robustly after undergoing rigorous tests for robustness and endogeneity. (2) Although the utilization level of data elements by enterprises is not a prerequisite for the progression of NQPF, the need to foster such forces through reduced data element utilization declines over time. (3) Three configurations and two model types have been identified as influencing the advancement of high-quality NQPF. Within the data elements model, the interaction between data elements and traditional enterprise development factors produces a configuration effect that collectively influences the progression of NQPF. The extent of enterprises’ data element utilization acts as a sufficient condition for this progression. (4) The within-group results demonstrate that the primary case areas are largely first-tier cities, with the main industries centered in the secondary sector. The between-group results disclose a growing sufficiency of data elements in nurturing NQPF.