Related Research Using Embeddings

Below, we list some (marketing) papers that use product embeddings. Product embeddings can be derived with Product2Vec or other methods.

• Scalable bundling via dense product embeddings (Kumar, Eckles, and Aral 2020)
• Studying Product Competition Using Representation Learning (Chen et al 2020)
• Overcoming the Cold Start Problem of Customer Relationship Management Using a Probabilistic Machine Learning Approach (Padilla and Ascarza 2021)
• Identifying Market Structure: A Deep Network Representation Learning of Social Engagement (Yang, Zhang, and Kannan 2021)
• Product Choice with Large Assortments: A Scalable Deep-Learning Model (Gabel and Timshenko 2022)
• Mapping Market Structure Evolution (Matthe, Ringel, and Skiera 2022)
• Multimarket Membership Mapping (Ringel 2022)
• Distilling Brand Alliance Opportunities from Information Networks (Malhotra et al. 2024)
• Browsing the Aisles or Browsing the App? How Online Grocery Shopping is Changing What We Buy (Chintala, Liaukonytė, and Yang (2024)
• …