This study investigates the critical roles of green innovation adoption (GIA) and green technology adoption (GTA) in advancing the digital economy (DE). It explores how creative enterprises (CE) and financial capability (FC) mediate and moderate the relationships between green innovation, technology adoption, and the digital economy. Data were collected from 400 respondents in the automotive industry in China through a structured survey questionnaire. Structural Equation Modeling (SEM) was conducted using Smart PLS 4.0 to analyze the data and test the proposed hypotheses. The findings indicate that green innovation and technology adoption significantly and positively impact the digital economy. Moreover, these factors positively influence creative enterprises, enhancing the digital economy. Creative enterprises were also found to mediate the relationship between green innovation/technology adoption and the digital economy. In addition, financial capability significantly moderated the link between creative enterprises and the digital economy. This research contributes to the literature by examining the synergistic effects of environmental sustainability, innovation adoption, and technological integration within the digital economy. It provides actionable insights into embedding sustainable practices in the evolving digital landscape while highlighting the intricate dynamics among innovation, technology adoption, and financial resources in driving economic transformation. This study contributes to the literature by exploring the synergistic effects of green innovation, technology adoption, and financial capability in driving the digital economy, focusing on creative enterprises as a mediating factor. It provides actionable insights for integrating sustainability into the digital landscape, offering a novel framework for economic transformation in the automotive industry.

Adopting innovative, systematically structured, and sustainable human resource management (SHRM) practices is essential for enhancing logistics agility and deriving sustainable development in logistics operations. This study examines the influence of sustainable human resources management practices on logistics agility with a mediating role of artificial intelligence (AI) in China’s logistics industry. Given the rapid growth and technological advancements in China’s logistics sector, this study employed quantitative research and convenience sampling techniques to collect data from 341 employees working in the industry. Smart PLS was used to test the proposed hypotheses through structural equation modeling (SEM). The study’s findings reveal that reward management, training and development, job appraisal, and teamwork significantly enhance logistics agility, while recruitment and selection show an insignificant impact. Similarly, the results reveal that sustainable HRM practices and artificial intelligence positively and significantly influence logistics agility. In addition, artificial intelligence substantially mediates the relationship between sustainable HRM practices and logistics agility. These findings offer valuable insights for HRM and logistics management, highlighting how AI can strengthen sustainable HRM practices to foster agility and improve logistics performance. The findings are particularly relevant for practitioners and policymakers aiming to enhance sustainability and efficiency in the logistics sector.