Capturing Cannibalization and Complementarity Effects in Retail. A Multimodal Deep Learning Approach

Posted: 6 Feb 2024

See all articles by Tamar Cohen-Hillel

Tamar Cohen-Hillel

UBC Sauder; Massachusetts Institute of Technology (MIT) - Operations Research Center

Manuel Moran-Pelaez

Massachusetts Institute of Technology (MIT), Operations Research Center, Students

Georgia Perakis

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Daniel Schoess

ETH Zürich - Department of Management, Technology, and Economics (D-MTEC)

Date Written: February 2, 2024

Abstract

This paper presents a novel two-stage multimodal approach for capturing cannibalization and complementarity effects within the retail sector. Traditional demand methods often assume independence between items and hence struggle to capture the intricate interplay between products. In response, we propose a framework that combines product information (textual, visual, and numerical features), and ticket data to provide a holistic understanding of product relationships. The model is validated using real-world retail data, demonstrating its ability to predict and quantify the impact of cross-item effects accurately. The findings derived from this approach enhance our understanding of cannibalization and complementarity dynamics and offer valuable insights into retail operations, such as assortment optimization, pricing, and inventory management.

Keywords: cross-item effects, multimodal deep learning

Suggested Citation

Cohen-Hillel, Tamar and Moran-Pelaez, Manuel and Perakis, Georgia and Schoess, Daniel, Capturing Cannibalization and Complementarity Effects in Retail. A Multimodal Deep Learning Approach (February 2, 2024). Available at SSRN: https://ssrn.com/abstract=4714230

Tamar Cohen-Hillel

UBC Sauder ( email )

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada

Massachusetts Institute of Technology (MIT) - Operations Research Center ( email )

77 Massachusetts Avenue
Bldg. E 40-149
Cambridge, MA 02139
United States

Manuel Moran-Pelaez (Contact Author)

Massachusetts Institute of Technology (MIT), Operations Research Center, Students ( email )

77 Massachusetts Avenue
Bldg. E 40-149
Cambridge, MA 02139
United States

Georgia Perakis

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-565
Cambridge, MA 02142
United States

Daniel Schoess

ETH Zürich - Department of Management, Technology, and Economics (D-MTEC) ( email )

ETH-Zentrum
Zurich, CH-8092
Switzerland

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