How does Generative AI understand the phygital customer experience? A strategic retail decision-making approach using social listening methods
Year: 2025
Type: article
Abstract: The adoption of Generative Artificial Intelligence (GAI) for converting extensive textual data into strategic knowledge has emerged as a significant trend within business research. While prior studies acknowledge the operational applications of GenAI, its role in offering strategic decision-making support remains underexplored. This study presents a novel social listening framework powered by GenAI that combines advanced text analysis methods, specifically: (a) Long Short-Term Memory (LSTM), a variant of Recurrent Neural Networks (RNN) capable of identifying long-range dependencies through its memory mechanisms, and (b) Google’s Bidirectional Encoder Representations from Transformers (BERT). The proposed model leverages bi-directional contextual learning to extract deeper insights from large-scale textual datasets, enabling the transformation of user-generated content into actionable knowledge. These insights are intended to guide managers in enhancing customer experiences and supporting decision-making processes within phygital retail environments.
Source: Dangdai jingji kexue
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7127066816