AI‐Driven Sentiment Analysis for Retail Management: A Graph‐Based DSS Comparing Franchise and Company‐Owned Stores
ABSTRACT This paper introduces an AI‐driven Decision Support System (DSS) for sentiment analysis of customer reviews in Starbucks UK. The methodology involves three main steps: collecting customer reviews from trusted sources, applying AI‐driven preprocessing techniques to extract key attributes, and using Graph Machine Learning techniques to unveil customer satisfaction. A new Graph‐Based Sentiment Analysis Algorithm is proposed to extract object–sentiment pairs from each comment and model relationships through a graph‐based approach. Results indicate a superior performance in terms of accuracy and efficiency compared to cell‐based methods. The analysis identifies drivers of customer satisfaction, including value for money, quality experience, and ambiance.
Authors
- Jérôme Baray (ORCID: https://orcid.org/0000-0002-1720-7185)
- Gérard Cliquet
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Nantes Angers Le Mans (FR)
- Le Mans Université (FR)
- Université de Rennes (FR)
Publication Details
- Journal
- Managerial and Decision Economics
- Published
- 2024-12-16
- DOI
- https://doi.org/10.1002/mde.4462
- Citations
- 2
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.69