Does AI catalyze novelty? Generative AI, resource allocation novelty, and innovation quality of high-performing manufacturing enterprises in emerging markets

High-performing firms play a pivotal role in driving technological breakthroughs and advancing industry progress in emerging markets. However, how such firms sustain and enhance innovation quality when their performance exceeds aspirational benchmarks—i.e., when they experience performance aspiration surplus—remains underexplored. Drawing on the behavioral theory of the firm and the digital affordance perspective, this study examines the mechanisms and conditions under which performance aspiration surplus influences innovation quality. Using a panel dataset of Chinese listed manufacturing firms from 2011 to 2022, we find that performance aspiration surplus positively affects innovation quality, with resource allocation novelty serving as a partial mediator in this relationship. Moreover, generative artificial intelligence (generative AI) adoption positively moderates the relationship between performance aspiration surplus and resource allocation novelty, amplifying its indirect effect on innovation quality. These findings contribute to literature on high-performing enterprises’ innovation strategies in emerging markets and provide insights into innovation practices in the AI era.