Digital transformation and new quality productivity: Empirical analysis of the moderating role of gai technology application - Cui, Jun; Wan, Qiang; Shin, Sangwoo (The Economics and Finance Letters, 2025)
This study explores the impact of Chinese firms’ digital transformation on the evolution of new quality productivity, with a focus on the catalytic role of Generative Artificial Intelligence (GAI) technology installation. To evaluate the hypothesized relationships, the study uses a strict econometric framework, drawing on a large panel dataset of 9,280 firm-year findings from authoritative Chinese repositories such as the CNRDS and CSMAR. The empirical findings reveal a statistically significant and positive association between organizational digitization efforts and improvements in quality-centric productivity indices. Notably, the use of GAI solutions enhances this link, serving as an important mediator in improving the efficacy of digital operations. Moreover, mechanistic analysis reveals that productivity gains are primarily mediated by enhanced innovation capacity and streamlined operations, reflected in patent activity, R&D efficiency, and improved workflow metrics. Additionally, this study employs a multifaceted validation strategy that includes propensity score matching (PSM) to reduce selection bias and heterogeneous effect tests across industry sectors and firm sizes. This study adds new theoretical and practical perspectives to the discussion of technology-driven competitive advantage by recognizing the dual mediating pathways through which digital transformation promotes productivity growth and measuring the conditional reinforcement provided by GAI.