The Impact of New Quality Productivity Forces on ESG Performance in Chinese Listed Tourism Companies: The Mediating Role of Artificial Intelligence and the Moderating Effects of Governance, Profitability, and Policy

Abstract

New Quality Productive Forces (NQPF), characterized by breakthroughs in digital transformation, intelligent systems, and eco-friendly development models, are instrumental in driving high-quality economic progress in China. In the context of the tourism sector, achieving robust Environmental, Social, and Governance (ESG) performance is critical for sustained growth; yet, the mechanisms and drivers shaping ESG outcomes remain underexplored. Utilizing panel data from A-share listed tourism enterprises in Shanghai and Shenzhen spanning 2000 to 2024, this study employs a two-way fixed effects model to examine the influence of NQPF on ESG performance. The empirical results confirm a significant positive association between NQPF and corporate ESG performance. Notably, artificial intelligence (AI) exhibits a statistically significant negative mediating effect, indicating a suppressive rather than enhancing role in this relationship. Moderation analysis reveals that firm profitability strengthens the positive impact of NQPF on ESG outcomes, whereas corporate governance quality and policy enforcement intensity, measured through R&D investment, attenuate it. Heterogeneity analyses show that the positive effects of NQPF are more pronounced in state-owned enterprises, labor-intensive firms, and companies located in eastern regions of China. This research highlights NQPF as a crucial driver for improving ESG standards in China’s tourism industry. However, the counterproductive mediation of AI reflects its dual-edged nature, raising concerns about ethical implications and suboptimal resource utilization in current AI integration strategies. The divergent moderating roles of internal organizational capacities and external institutional environments yield important insights for corporate decision-makers and regulatory agencies. These findings offer empirical grounding for tourism firms to enhance governance over AI applications and for policymakers to design precise interventions that support sustainable industrial upgrading.