ABSTRACT This study investigates how environmental concern translates into green banking behavior by distinguishing three behavioral mechanisms: cost‐sensitive (instrumental—via perceived benefits and adoption intention), loyalty‐based, and sacrifice‐based (affective—via trust). Grounded in the theory of planned behavior (TPB) and self‐determination theory (SDT), we employ structural equation modelling (SEM) and a conditional moderated mediation model (PROCESS Model 11), with perceived benefits, adoption intention, and trust serving as mediators, and personal responsibility and social norms acting as moderators. Findings indicated that different psychological paths trigger different outcomes of pro‐environmental financial behavior. Artificial neural networks (ANN) complement the analysis by detecting nonlinear patterns, supporting the multidimensional nature of environmental behavior. The study challenges one‐dimensional measurement of green behavior and underscores the need for tailored policy approaches in sustainable finance. By aligning motivation types with targeted behavioral outcomes, this work advances applications of behavioral economics in green banking.
Kaçani et al. (2025) studied this question.
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