Sustainable development with Artificial Intelligence: Examining the absorptive capacity pathways to green innovation

Abstract

Artificial intelligence holds a lot of promise in tackling global societal challenges. However, there is still no consensus on how companies can effectively harness AI to promote green innovation (GI). We develop a moderated mediation model grounded in absorptive capacity theory to fill this research gap. In this paper, our empirical study based on data drawn from 361 Chinese firms reveals the significant roles of two critical capacities, potential absorptive capacity (PAC) and realized absorptive capacity (RAC), in fostering a positive relationship between AI capabilities and GI. Notably, this study's results show that environmental heterogeneity (EH) amplifies the mediating effects of PAC and RAC. This implies that companies with access to Artificial intelligence (AI) capabilities will likely learn and absorb available information and knowledge outside the organizations better. This improves GI, mainly when EH levels are high. The present work advances the research by addressing how AI impacts GI through different mediating and moderating factors. It can help inform companies wanting to achieve GI amid sustainability imperatives.