Abstract
This study empirically analyses the impact of Digital transformation (DT) in the manufacturing industry as a major activity aimed at improving productivity and strengthening competitiveness in the digital era. It uses the nationally approved statistical database of Statistics Korea and seeks to explain how innovation capabilities and firm characteristics, particularly industry characteristics, affect the technological innovation of SMEs in the manufacturing sector.
The theoretical contribution of this empirical study lies in its focus on the hierarchical linear relationship between individual firm characteristics affecting technological innovation and the endogenous innovativeness of the industry to which the firm belongs. The study applies the Hierarchical Linear Model (HLM, also known as the multilevel model, MLM) to account for multilayered effects. This contrasts with empirical models such as multiple regression or logit regression, which often ignore industry characteristics or treat them simply as dummy variables, thus potentially overestimating the relationship between DT and technological innovation performance. By understanding the impact of industry characteristics on manufacturing technology innovation, the HLM empirical analysis model presented in this study is expected to serve as foundational research for establishing differentiated and customised policy support based on both industry characteristics and individual firm characteristics in future government support systems.