Digital intelligence transformation, green knowledge recombination capability and directed technical change in firms

Purpose Standard models of directed technical change treat relative prices and regulation as the main forces steering innovation toward cleaner technologies. From a knowledge management perspective, this paper aims to examine whether digital-intelligence transformation can tilt innovation by reshaping knowledge system inside the firm. Design/methodology/approach This paper tests these predictions in a panel of Chinese listed firms, proxying innovation direction with the green patent share and its year-to-year adjustment. Findings A one−standard deviation increase in digital-intelligence transformation the green patent share by about 7.4% of its sample mean. Decomposing the mechanism, this paper finds that digital intelligence strengthens both exploratory and exploitative recombination, but only exploration translates into a greener direction, whereas exploitation reinforces lock-in, leaving a positive net effect. The shift is most pronounced where environmental regulation is more stringent. It is also concentrated among firms that lack alternative offline search networks, and it is strongest at intermediate levels of knowledge breadth, with excessive breadth diluting depth and attenuating the marginal gain. Originality/value This paper argues that digital-intelligence transformation can lower the perceived cost of sourcing codifiable external knowledge while making system integration and tacit coordination more salient constraints, so the direction of innovation reflects a tug-of-war between exploratory recombination and exploitative lock-in. These results suggest a knowledge-management-based non-price micro-channel through which digital-intelligence transformation shapes directed technical change.