Affiliation:
1. School of Business Northwest University of Political Science and Law Xi'an China
2. Indiana University East Richmond Indiana USA
Abstract
AbstractThis study investigates the impact of intelligent manufacturing methods driven by artificial intelligence (AI) on cost stickiness in Chinese manufacturing enterprises. Leveraging the ABJ model， a regression analysis explores how different AI‐enabled intelligent manufacturing approaches influence cost stickiness through the lens of innovation equilibrium. The sample comprises manufacturing companies listed on China's A‐share market from 2013 to 2021. The findings reveal a negative correlation between intelligent manufacturing adoption and cost stickiness among these firms. Specifically, production‐based intelligent manufacturing exhibits a more significant effect on reducing cost stickiness compared with collaborative intelligent manufacturing methods. Moreover, intelligent manufacturing positively impacts both joint equilibrium innovation and matching equilibrium innovation. While joint equilibrium innovation is negatively associated with cost stickiness, matching equilibrium innovation shows no significant relationship with cost stickiness. The results indicate that innovation equilibrium plays a mediating role in the relationship between AI‐driven intelligent manufacturing and cost stickiness. Overall, this research sheds light on how AI capabilities enabling intelligent manufacturing processes and innovation equilibrium dynamics can help alleviate cost stickiness issues faced by manufacturing enterprises. It highlights the strategic value of adopting AI systems to enhance operational efficiency and cost management flexibility within manufacturing contexts.