A Multi‐Level Analysis of Psychological, Cultural, and Strategic Drivers of Corporate Environmental Responsibility

ABSTRACT This research aims to unravel the complex psychological, organizational, and environmental factors that underpin employee environmentally friendly behavior and sustainable marketing performance in the U.S. fertilizer sector. It examines a fully moderated serial mediation model in which employee environmental consciousness and organizational green culture serve as primary antecedents, with employee green commitment and green innovation as mediators. Through various relational pathways, the model also incorporates three moderators: leadership support for sustainability, psychological green climate, and customer environmental demand. A sample of 1108 U.S. fertilizer workers was surveyed with validated measurement instruments. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS‐SEM) to evaluate causal paths, and supervised machine learning in JASP was used to assess predictive accuracy and robustness. All the relationships proposed were confirmed. SEM demonstrated strong explanatory power, whereas machine learning showed predictive accuracy, especially with neural networks and KNN. Outcomes emphasize the interaction of employee awareness, organizational culture, and external pressures in influencing green commitment, innovation, and sustainable marketing performance. This research makes an original contribution by combining SEM and machine learning to test the causal and predictive validity of a multilevel sustainability model in the less‐researched U.S. fertilizer sector. It develops a theory by illustrating how organizational enablers and employee‐level psychological mechanisms dynamically interact, providing new insights into how green behaviors are translated into sustainable marketing performance.