Facial Recognition Retail Interactions and Green Purchase Intentions Through Privacy Calculus Awareness Mechanisms
Keywords:
Facial recognition, Green purchase intention, Retail technology, Consumer behaviorAbstract
The integration of biometric technologies in physical retail environments has fundamentally transformed consumer experiences, yet its psychological impact on sustainable consumption remains underexplored. This paper investigates the interaction effects of facial recognition technology on green purchase intention within retail settings. Drawing upon objective self-awareness theory and privacy calculus theory, this research proposes a comprehensive framework to understand how personalized interactions driven by facial recognition influence consumers' propensity to select environmentally friendly products. Through a controlled laboratory-in-the-field experiment, we manipulate the level of facial recognition interaction and measure its downstream effects on green purchase intention, with perceived social presence and privacy concerns serving as competing mediating mechanisms. The findings reveal a dual-pathway effect where facial recognition interaction significantly enhances green purchase intention by elevating perceived social presence, effectively simulating a digital watching eyes effect that promotes pro-social and pro-environmental behavior. Conversely, heightened privacy concerns act as a suppressive mediator, negatively impacting purchase intentions when the interaction is perceived as overly intrusive. These insights contribute to the growing discourse on human-computer interaction in retail by demonstrating that the architectural design of artificial intelligence interfaces can actively shape sustainable consumption patterns. The study offers practical recommendations for retailers seeking to balance personalized technological engagement with ethical considerations, ultimately fostering an environment conducive to green purchasing.
References
1. Yi, X. (2026). Trusted AI Commercialization Infrastructure for SMBs: A Unified Multi-Tenant Architecture Integrating Incentive Systems, Content Governance, and Standardized Recommendation APIs.
2. Liu, T. (2026). Interpretable Machine Learning for Volatility Forecasting Under Realistic Walk-Forward Constraints.
3. Li, Z., Dong, Y., Gao, C., Zhao, Y., Li, D., Hao, J., ... & Wang, Z. (2023, April). Breaking filter bubble: A reinforcement learning framework of controllable recommender system. In Proceedings of the ACM web conference 2023 (pp. 4041-4049).
4. Jia, Y., Liu, X., Huang, J., Fan, Z., & Wang, X. (2026). Identity awakening in digital marketing: how facial recognition interactions foster green consumption behavior. Journal of Research in Interactive Marketing, 1-18.
5. Hu, J., Hu, X., Yang, S. A., & Yang, Y. (2025). Tokenizing Loyalty Programs: The Role of Tradability. Available at SSRN 5183227.
6. Zeng, G., Leung, T. S., Maylott, S. E., Malik, A., Adornato, A. A., Lebowitz, M., ... & Simpson, E. A. (2024). Infants' salivary oxytocin and positive affective reactions to people. Hormones and behavior, 164, 105579.
7. Liu, T. (2026). Leakage-Safe Benchmark Design for Market-Stress Early Warning: An Economically Credible Evaluation.
8. Leung, T. S., Zeng, G., Maylott, S. E., Malik, A., Zhang, S., McNamara, E. C., ... & Simpson, E. A. (2024). Emerging adults mirror infants’ emotions and yawns. Developmental psychobiology, 66(6), e22539.
9. Fu, J., Zhang, H., Yu, X., Zhong, T., Tao, X., & Xiao, Y. (2025, November). A Review of Mechanisms Underlying Modulation of Cardiorespiratory Endurance and Psychological Stress in College Students by High-Intensity Interval Training (HIIT) Combined with B-Vitamin Supplementation. In Healthcare (Vol. 13, No. 22, p. 2873). MDPI.
10. Tao, X., Wu, X., Zhuo, S., Fu, J., Xiao, Y., Zhao, Y., ... & Zhong, T. (2025). Unveiling the sedentary epidemic through insights from college students in Guangdong. Scientific Reports, 15(1), 35197.
11. Li, S. (2025). Momentum, volume and investor sentiment study for us technology sector stocks—A hidden markov model based principal component analysis. PloS one, 20(9), e0331658.
12. Black, F., & Scholes, M. (1973). The pricing of options and corporate liabilities. Journal of Political Economy, 81(3), 637–654.
13. Zhao, J. Analysis of working women's perceptions of state-regulated family planning policy: China as a case study (Doctoral dissertation, Loughborough University).
14. Tao, Xiaoyu, et al. "A comparative study on knowledge towards COVID-19 prevention among undergraduate students in Macao and Zhuhai, China." PeerJ 9 (2021): e11833.
15. Wang, Z., Dessouky, M., & Ioannou, P. (2026). Incentivized personalized coordinated freight routing considering system optimization with driver-in-loop utility learning. IEEE Transactions on Intelligent Transportation Systems.
16. Wang, Z., Dessouky, M., Van Woensel, T., & Ioannou, P. (2023). Pickup and delivery problem with hard time windows considering stochastic and time-dependent travel times. EURO Journal on Transportation and Logistics, 12, 100099.
17. Jia, Y., Wang, T., Xiao, K., & Guo, C. (2020). How to reduce opportunism through contractual governance in the cross-cultural supply chain context: evidence from Chinese exporters. Industrial Marketing Management, 91, 323-337.
18. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
19. Dang, Y., Chen, W., Pan, Z., Zhang, X., Duan, Y., Cai, F., & Chen, H. (2026). Dual-space feature representation learning network for multimodal recommender systems. Advanced Engineering Informatics, 72, 104462. Elsevier.
20. Li, S. (2024). Machine Learning in Credit Risk Forecasting — — A Survey on Credit Risk Exposure. Accounting and Finance Research, 13(2), 107-107.
21. Liu, T., Jia, Y., Zeng, S., & Yan, J. (2026). Social media use and attitudes toward premarital sex in China: a chain-mediating analysis. Sexuality Research and Social Policy, 1-17.
22. Yi, X. (2026). A Theoretically‐Grounded Federated Attribution Framework with Adaptive Differential Privacy Budgets for Cross‐Device Social Commerce Advertising Systems.
23. Nonaka, I. (1991). The knowledge-creating company. Harvard Business Review, 69(6), 96–104.
24. Han, Z., Meng, L., & Zhang, J. (2025). A Distributed Hierarchical Spatio-Temporal Edge-Enhanced Graph Neural Network for City-Scale Dynamic Logistics Routing. arXiv preprint arXiv:2512.18441.
25. Chen, L. (2026). Beyond external constraints: The missing dimension of ai governance. Available at SSRN 6449738.
26. Yi, X. (2025, December). A Federated and Differentially Private Incentive–Marketing Framework for Privacy-Preserving Cross-Channel Measurement in AI-Powered Digital Commerce. In Proceedings of the 2025 6th International Conference on Big Data Economy and Information Management (pp. 881-888).
27. Lu, Yao, Kaiyi Hu, and Luyan Zhang. "S 3 G: Stock State Space Graph for Enhanced Stock Trend Prediction." ICASSP 2026-2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2026.
28. Liu, T. (2022, December). Financial Constraint’Impact on Firms’ ESG Rating Based on Chinese Stock Market. In 2022 4th International Conference on Economic Management and Cultural Industry (ICEMCI 2022) (pp. 1085-1095). Atlantis Press.
29. Fu, J., Wu, X., Yu, X., Zhong, T., Xiao, Y., & Tao, X. (2026). Associations between diet, exercise, and mental health among college students in Guangdong, China: A cross-sectional and interventional study. Medicine, 105(5), e47375.
30. Tang, M., Liu, M., Li, H., Yang, J., Wei, C., Li, B., ... & Reddy, S. (2024). Async learned user embeddings for ads delivery optimization. arXiv preprint arXiv:2406.05898.
31. Hu, X., Wan, Z., & Yin, Q. (2025). Token Design for Favor Trading with Dynamic Membership. Available at SSRN 6175079.
32. Xu, S., Jiang, L., & Gu, B. (2025, September). Design and Validation of a Smart Neuromorphic System Architecture for Algorithmic Trading. In Proceedings of the 2nd International Symposium on Integrated Circuit Design and Integrated Systems (pp. 127-136).
33. Zhao, J. Multi-level influences on women’s careers under China’s family planning policy: A literature review.
34. Dong, J., Shen, Z., Luo, H., Lyu, T., & Gao, W. (2026). Graph attention and text semantics improve personalized recommendation. Scientific Reports.
35. Zeng, G., Ahn, Y. A., Leung, T. S., Maylott, S. E., Malik, A., Messinger, D. S., & Simpson, E. A. (2025). Automated detection of mouth opening in newborn infants. Behavior research methods, 57(12), 1-17.
36. Yao, H., Ding, J., & Wang, Z. (2026). CloudPayGuard: Hardware-Aware Real-Time Fraud Detection for Cloud-Native Credit Systems with OoO CPU Microarchitecture Optimization. Journal of Computer Science and Frontier Technologies, 3(2), 154-166.
37. Liu, Y. (2026). The effect of contradictory thinking on psychosocial adaptation: the mediating role of social distance. Current Psychology, 45(3), 221.
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