2026-10-14T16:48:03Z https://www.scidb.cn/oai

10.57760/sciencedb.30828 2026-03-20T11:11:23Z

2026-03-20 Configurational Analysis of carbon footprint management strategy and green innovation quality of SRDI Enterprises doi:10.57760/sciencedb.30828 en Specialized, refined, and innovative enterprises are the backbone of promoting high-quality economic development. How to effectively improve the quality of green innovation in enterprises through carbon footprint management has become a new research focus. Based on the "Miles Snow" analysis framework, this article proposes seven antecedent conditions that affect the improvement of green innovation quality in specialized and innovative enterprises from three dimensions: carbon footprint management strategy, technological endowment, and environmental regulation. Through a configurational study of data from 160 manufacturing specialized and innovative "little giant" listed companies in China, it was found that: (1) "tracking carbon tracing", "certification carbon tracing", and "dual effect carbon tracing" are the main paths for improving the quality of green innovation in specialized and innovative enterprises. (2) Specialized and innovative enterprises respond to external environmental regulatory pressures from the market, the public, and the government through the above three paths, and promote the improvement of green innovation quality through the combination of internal strategies and resources; (3) Based on the AMC theoretical model, the internal process mechanism of specialized and innovative enterprises improving the quality of green innovation through "cognitive activation motivation generation capability enhancement" has been further revealed. The conclusion of this study provides useful management and policy insights for China's specialized, refined, and innovative enterprises to implement carbon footprint strategies and improve the quality of their green innovation.  SRDI enterprise; Carbon footprint management strategy; Green innovation quality; Environmental regulation; AMC model Tang Linjia Yu Lingli Wu Aiqi Cao Dongxin RESTRICTED dataset Science Data Bank