Do Big Data Analytics and Artificial Intelligence Enhance Corporate Sustainability? The Moderating Roles of Regulation and Management Support

ABSTRACT

We examine the effects of big data analytics (BDA) and artificial intelligence (AI) on corporate sustainability performance, specifically investigating the influence of regulatory pressure and top management support. Utilizing hierarchical regression analysis on questionnaire data from 220 Chinese manufacturing firms, we find that both BDA and AI positively and significantly impact the corporate sustainability of manufacturing firms. Furthermore, regulatory pressure and top management support (TMS) significantly moderate the relationship between AI and BDA and firms' corporate sustainability performance. Our results also highlight heterogeneity and sector differences: the electronics, chemical, and automotive sectors exhibited significant positive effects of BDA and AI on sustainability performance dimensions, with the electronics sector demonstrating the strongest and most consistent results. Interestingly, the moderation analyses show that the interaction of BDA and regulatory pressure improved environmental performance; AI combined with regulatory pressure enhanced economic outcomes. Additionally, when supported by top management, BDA boosted social performance; AI strongly influenced economic performance. Importantly, the study also identifies potential risks: BDA implementation without adequate contextual support can negatively affect social and economic performance. While TMS is a significant moderator, its effectiveness is contingent on alignment with clear technological strategies. Without this alignment, TMS may lead to overconfidence, strategic misdirection, or resource misallocation. Our study emphasize that BDA and AI can improve sustainability in manufacturing, with effects varying by size, industry, and region, and reliant on supportive internal and external conditions.