Satellite imagery and machine learning for channel member selection

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Brei, Vinicius Andrade and Rech, Nicole and Bozkaya, Burçin and Balcısoy, Selim and Pentland, Alex Paul and Silveira Netto, Carla Freitas (2023) Satellite imagery and machine learning for channel member selection. International Journal of Retail and Distribution Management, 51 (11). pp. 1552-1568. ISSN 0959-0552 (Print) 1758-6690 (Online)

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Abstract

Purpose: This study aims to propose a new method to predict retail store performance using publicly available satellite imagery data and machine learning (ML) algorithms. The goal is to provide manufacturers and other practitioners with a more accurate and objective way to assess potential channel members and mitigate information asymmetry in channel selection and negotiation. Design/methodology/approach: The authors developed an open-source approach using publicly available Google satellite imagery and ML algorithms. A computer vision algorithm was used to count cars in store parking lots, and the data were processed with a CNN. Linear regression and various ML algorithms were used to estimate the relationship between parked cars and sales. Findings: The relationship between parked cars and sales was nonlinear and dependent on the type of channel member. The best model, a Stacked Ensemble, showed that parking lot occupancy could accurately predict channel member performance. Research limitations/implications: The proposed approach offers manufacturers a low-cost and scalable solution to improve their channel member selection and performance assessment process. Using satellite imagery data can help balance the marketing channel planning process by reducing information asymmetry and providing a more objective way to assess potential partners. Originality/value: This research is unique in proposing a method based on publicly available satellite imagery data to assess and predict channel member performance instead of forward-looking sales at the firm and industry levels like previous studies.
Item Type: Article
Uncontrolled Keywords: Channel member selection; Channel performance; Machine learning; Retail; Sales assessment; Satellite imagery
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Sabancı Business School
Depositing User: Burçin Bozkaya
Date Deposited: 24 Sep 2024 22:57
Last Modified: 24 Sep 2024 22:57
URI: https://research.sabanciuniv.edu/id/eprint/50124

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