Let Artificial Intelligence Be Your Shelf Watchdog: The Impact of Intelligent Image Processing-Powered Shelf Monitoring on Product Sales

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Publication History

Received: April 7, 2020
Revised: June 30, 2021; April 24, 2022; August 22, 2022
Accepted: October 16, 2022
Published Online as Articles in Advance: August 22, 2023
Published in Issue: September 1, 2023


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We collaborated with a leading fast-moving consumer goods (FMCG) manufacturer to investigate how intelligent image processing (IIP)-based shelf monitoring aids manufacturers’ shelf management by using data from a quasi-experiment and a field experiment. We discovered that such artificial intelligence (AI) assistance significantly and consistently improves product sales. Several underlying mechanisms were revealed by our quantitative and qualitative analysis. First, retailers are more likely to comply due to the greater monitoring effectiveness enabled by AI assistance. Second, the positive effect of IIP-based shelf monitoring partially persists after it is terminated, implying that human learning takes place. Third, the value of IIP-based shelf monitoring can be attributed to independent retailers rather than chain retailers. Since the degree of contract heterogeneity is the major difference between these retailers in terms of monitoring, this finding further suggests that AI is relatively more scalable when coping with more heterogeneous instances. Apart from these great benefits, we demonstrate the low marginal costs of implementing IIP-powered shelf monitoring, which indicates its long-term applicability and potential to generate incremental value. Our research contributes to several literature streams and provides managerial insights for practitioners who consider AI-assisted operational models.

Additional Details
Author Yipu Deng, Jinyang Zheng, Liqiang Huang, and Karthik Kannan
Year 2023
Volume 47
Issue 3
Keywords Economic value of artificial intelligence, quasi-experiment, field experiment, monitoring, shelf management
Page Numbers 1045-1072
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