An Analysis of the Pathways for Enhancing Green Total Factor Productivity in Livestock Industry Listed Companies: A Study Based on Dynamic QCA

Improving the green total factor productivity (GTFP) of publicly listed companies in the livestock sector is essential for achieving sustainable and high-quality development in China’s agricultural industry. This study proposes an integrated analysis framework for the advancement of GTFP, focusing on internal resource allocation and external business environment configurations. Using panel data from 32 publicly listed companies in China’s livestock sector covering the period 2016 to 2021, we apply the dynamic qualitative comparative analysis (QCA) and necessary condition analysis (NCA) methodologies to explore the configuration pathways for multiple factors that influence GTFP, aiming to identify the mechanisms that drive these pathways in publicly listed livestock companies. The findings reveal that individual antecedent conditions are not essential for achieving high green total factor productivity (GTFP) in firms. Rather, internal and external factors jointly facilitate GTFP enhancement, resulting in three distinct configurational pathways that share the equivalence of “diverse configuration pathways leading to the same objective”. Over time, the consistency level of each configuration pathway fluctuates above 0.94, demonstrating their stability over the study period. In terms of individual companies, the explanatory power of each configuration remains uniform across enterprises, exhibiting no significant differences. This study expands the scope of GTFP-related research and advances the application of the dynamic QCA method. It also provides enlightenment for policymakers to refine sectoral regulations and for companies seeking strategies to improve GTFP.