In a technologically changing consumer behavior, it has never been more important to learn how artificial intelligence (AI) affects the purchase of green products triggered by emotions and nostalgic stimuli. This paper focuses on how nostalgia proneness and cues, artificial intelligence‐based individualized experience, brand attachment, and consumer affective reaction influence the development of purchase intentions for green products, thus applying attachment theory and emotional marketing framework to the sustainable consumption setting. The analysis of the data was conducted with the help of the SmartPLS 4.0 software with a sample of 397 environmentally conscious consumers. The findings reveal that nostalgia proneness and nostalgic cues positively influence emotional responses, which subsequently strengthen brand connection and purchase intention toward eco‐friendly products. Furthermore, emotional response and brand connection serve as significant sequential mediators in explaining consumers' sustainable purchase behavior. The moderation analysis demonstrates that AI‐driven personalized experiences significantly strengthen the relationship between nostalgic cues and emotional response, whereas their moderating effect on the relationship between nostalgia proneness and emotional response is not significant. These findings indicate that AI‐driven personalization is more effective in enhancing the emotional impact of externally embedded nostalgic stimuli than consumers' inherent nostalgic tendencies. By integrating nostalgia, emotional response, brand connection, and AI‐driven personalization within the context of sustainable consumption, this study provides important theoretical and practical insights for marketers seeking to promote eco‐friendly products in both emerging and developed markets.
Nabeel Rehman, Asad Abbas Jaffari, Maria Palazzo· Corporate Social Responsibil...· 0 citations
This study examines the role of strategic flexibility (SF) in supporting sustainable growth among small and medium-sized enterprises (SMEs) operating in an emerging economy context. Specifically, it investigates the relationships between SF, business model innovation (BMI), competitive advantage (CA), and firm performance (FP) in Iranian SMEs. Drawing on the Resource-Based View (RBV) and Dynamic Capabilities Theory (DCT), the study empirically examines a capability–innovation–performance model and contributes by extending existing theoretical relationships to the context of SMEs in an emerging economy. Using structural equation modeling (SEM), data were collected through 391 validated questionnaires from SMEs across different sectors in Iran. The findings reveal that SF has a direct and significant effect on both BMI and CA, while BMI positively influences CA and FP. However, CA does not show a significant direct effect on FP, suggesting that competitive positioning alone may be insufficient to generate performance outcomes in uncertain and resource-constrained environments. The results indicate that adaptive and innovation-oriented capabilities play a central role in enhancing long-term organizational resilience and sustainable performance among SMEs operating under institutional and market volatility.
Mohammadsadegh Omidvar, Giovanna Lusini, Maria Palazzo· Sustainability· 0 citations