Digital Transformation and Enterprise Innovation Performance: Organizational Agility as A Mediating Mechanism and Absorptive Capacity as A Boundary Condition

Abstract

Digital transformation is increasingly treated as a strategic route to enterprise innovation, yet digital investment does not automatically translate into superior innovation outcomes. This study develops a conditional process model explaining how digital transformation can improve enterprise innovation performance through organizational agility and when this mechanism is strengthened by absorptive capacity. Drawing on dynamic capability theory and the knowledge-based view, the model proposes that digital transformation expands firms' ability to sense market changes, coordinate resources, and reconfigure operating routines; organizational agility then converts these digital possibilities into faster and more effective innovation responses. Absorptive capacity is positioned as a first-stage moderator because firms differ in their ability to identify, assimilate, transform, and exploit new knowledge generated through digital systems. A two-wave questionnaire design targeting managers in Chinese manufacturing and technology-oriented enterprises is proposed. The empirical strategy uses IBM SPSS Statistics and Hayes' PROCESS Macro: reliability analysis and exploratory factor analysis are followed by hierarchical regression and PROCESS Model 7 with 5,000 bootstrap samples. The design provides a directly executable SPSS framework and a transparent results-reporting template without fabricating empirical findings. The study is intended to contribute to enterprise innovation research by clarifying a capability-based pathway through which digital transformation creates innovation value and by identifying absorptive capacity as an important organizational boundary condition.