Impact of artificial intelligence technology application on digital recombinant innovation in manufacturing enterprises: an exaptation theory perspective

Purpose Geopolitical factors coupled with a global economic downturn impose dual constraints on manufacturing enterprises by weakening demand and rising costs. Traditional adaptive innovation appears insufficient to address this issue. Digital recombinant innovation, which involves the functional migration of digital technologies to develop low-cost technology trajectories, offers a key solution. The mechanism underlying this “answers-precede-questions” innovation paradigm lacks theoretical explanation and empirical support. Therefore, exaptation theory is introduced to analyse how artificial intelligence (AI) technology applications shape digital recombinant innovation (reuse/creation). Design/methodology/approach Multiple linear regression and structural equation modelling were used to analyse data from 525 Chinese manufacturing enterprises concerning the relationships between variables and the importance of paths, respectively. This study aimed to examine the mediating roles of cooperative network bricolage and competitive network bricolage, as well as their complementary and substitutive relationships with digital recombinant innovation. Findings AI technology application significantly promoted both dimensions, with a stronger effect on digital recombinant creation. This relationship was mediated by two types of network bricolages, with mediating proportions varying by recombination type. A substitution effect was significant only for digital recombinant reuse. A complementary effect existed only for digital recombinant creation but was not statistically significant. Originality/value By applying and verifying the concept of digital recombinant innovation, this study provides enterprises in developing countries with a theoretical foundation and practical pathways to overcome technological blockades and achieve sustainable development under dual pressures.