Bayesian nonparametric customer base analysis with model-based visualizations R Dew, A Ansari Marketing Science 37 (2), 216-235, 2018 | 60 | 2018 |
Letting logos speak: Leveraging multiview representation learning for data-driven branding and logo design R Dew, A Ansari, O Toubia Marketing Science 41 (2), 401-425, 2022 | 58 | 2022 |
Modeling dynamic heterogeneity using Gaussian processes R Dew, A Ansari, Y Li Journal of Marketing Research 57 (1), 55-77, 2020 | 35 | 2020 |
Mega or Micro? Influencer Selection Using Follower Elasticity Z Tian, R Dew, R Iyengar Journal of Marketing Research, 00222437231210267, 2023 | 8 | 2023 |
Adaptive preference measurement with unstructured data R Dew Available at SSRN 4641773, 2023 | 2 | 2023 |
Web Appendix Z Tian, R Dew, R Iyengar | | 2023 |
Detecting Routines: Applications to Ridesharing Customer Relationship Management R Dew, E Ascarza, O Netzer, N Sicherman Journal of Marketing Research, 00222437231189185, 2023 | | 2023 |
Web Appendix R Dew, E Ascarza, O Netzer, N Sicherman | | 2023 |
CRM R Dew, O Netzer | | 2023 |
Detecting Routines in Ride-sharing: Implications for Customer Management R Dew, E Ascarza, O Netzer, N Sicherman | | 2021 |
A Gaussian Process Model of Cross-Category Dynamics in Brand Choice R Dew, Y Fan arXiv preprint arXiv:2104.11702, 2021 | | 2021 |
Essays on Machine Learning Methods for Data-Driven Marketing Decisions RT Dew Columbia University, 2019 | | 2019 |