Human Computer Interaction, Artificial Intelligence and Intelligent Augmentation
Loading...
Paper Type
Complete
Paper Number
2324
Description
We collaborate with Danone to study how AI-based shelf monitoring helps with manufacturers' shelf management efforts by using data from a field experiment. We find that AI-powered shelf monitoring significantly improves product sales. This effect is only partially persistent in that it diminishes after monitoring is terminated. We further reveal that the positive effect is attributed to independent retailers rather than chained retailers. Since the major difference in shelf monitoring between these two types of retailers is the degree of heterogeneity in shelf space rental contracts, this finding indicates that AI-powered monitoring is better than human monitoring when facing more heterogeneous shelf displays. The finding further suggests the better scalability of AI in coping with more heterogeneous objects. We also interview with the delegates and find a low marginal cost of adopting, which suggests a long-term applicability of AI-powered shelf monitoring to generate value for the manufacturer.
Recommended Citation
Deng, Yipu; Zheng, Jinyang; Huang, Liqiang; and Kannan, Karthik, "The Impact of AI-powered Shelf Monitoring on Product Sales" (2020). ICIS 2020 Proceedings. 16.
https://aisel.aisnet.org/icis2020/hci_artintel/hci_artintel/16
The Impact of AI-powered Shelf Monitoring on Product Sales
We collaborate with Danone to study how AI-based shelf monitoring helps with manufacturers' shelf management efforts by using data from a field experiment. We find that AI-powered shelf monitoring significantly improves product sales. This effect is only partially persistent in that it diminishes after monitoring is terminated. We further reveal that the positive effect is attributed to independent retailers rather than chained retailers. Since the major difference in shelf monitoring between these two types of retailers is the degree of heterogeneity in shelf space rental contracts, this finding indicates that AI-powered monitoring is better than human monitoring when facing more heterogeneous shelf displays. The finding further suggests the better scalability of AI in coping with more heterogeneous objects. We also interview with the delegates and find a low marginal cost of adopting, which suggests a long-term applicability of AI-powered shelf monitoring to generate value for the manufacturer.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.