Evolution Patterns, Structural Characteristics, and Convergence Types of Digital Economy Industry Convergence

The convergence of digital and traditional industries is a critical pathway for advancing modern industrial systems in digital economy era. This study employs input-output data from China to measure the degree of industry convergence from both the supply and demand sides. Through clustering analysis and network modeling, the research reveals heterogeneous convergence patterns, primarily characterized by growth and stability, and a trend toward concentration in core clusters dominated by digital and service industries, especially on the demand side. Among digital sub-industries, Digital factor-driven industry demonstrates the most substantial influence, contributing significantly to bidirectional convergence. Digital product service and Digital product manufacturing play key roles on the demand side, while Digital technology application industry shows relatively limited impact. Furthermore, this study identifies varying convergence types across industries, underscoring the need for differentiated, industry-specific policy approaches. These findings provide empirical insights into the structure and dynamics of industry convergence and offer strategic guidance for promoting the deep convergence of digital and traditional economies.