INTEGRATING ADVANCED TECHNOLOGIES IN RETAIL: A CONCEPTUAL FRAMEWORK FOR ENHANCING CONSUMER EXPERIENCE AND TRUST

Authors

  • Dr. Raghavendra Lecturer, University Evening College, Mangaluru, Karnataka, India
  • Dr. Eswara MG Associate Professor and HOD, Department of Economics, Alvas's College Moodabidre, Karnataka, India

DOI:

https://doi.org/10.29121/ijetmr.v11.i10.2024.1506

Keywords:

Retail Technologies, AI Personalization, AR Engagement, Big Data, Personalization-Privacy Paradox, Consumer Trust

Abstract

This study explores the integration of advanced technologies, such as Artificial Intelligence (AI), Augmented Reality (AR), and Big Data Analytics, in retail to enhance personalized consumer experiences while addressing privacy concerns. This research investigates the personalization-privacy paradox, where consumers value tailored recommendations but remain wary of data collection practices. Through a comprehensive literature review, this study developed a conceptual framework for responsibly integrating these technologies in retail. The framework illustrates how AI personalizes shopping experiences, AR enhances consumer engagement, and Big Data improves operational efficiency while also considering privacy issues. The key findings reveal that balancing personalized services with transparent data practices is essential for building consumer trust. This study emphasizes the importance of transparency and ethical data handling in mitigating privacy concerns and fostering a more consumer-centric retail environment. These insights contribute to retail strategies and provide practical guidance for leveraging cutting-edge technologies without compromising privacy, thereby highlighting the need for a balanced approach that maximizes the benefits of innovation while safeguarding consumer trust.

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Published

2024-10-29

How to Cite

Raghavendra, & MG, E. (2024). INTEGRATING ADVANCED TECHNOLOGIES IN RETAIL: A CONCEPTUAL FRAMEWORK FOR ENHANCING CONSUMER EXPERIENCE AND TRUST. International Journal of Engineering Technologies and Management Research, 11(10), 26–36. https://doi.org/10.29121/ijetmr.v11.i10.2024.1506