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

TitleLet Artificial Intelligence Be Your Shelf Watchdog: The Impact of Intelligent Image Processing-Powered Shelf Monitoring on Product Sales
Authors
KeywordsEconomic value of artificial intelligence
field experiment
monitoring
quasi-experiment
shelf management
Issue Date22-Aug-2023
PublisherManagement Information Systems Research Center
Citation
MIS Quarterly, 2023, v. 47, n. 3, p. 1045-1072 How to Cite?
Abstract

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.


Persistent Identifierhttp://hdl.handle.net/10722/340358
ISSN
2023 Impact Factor: 7.0
2023 SCImago Journal Rankings: 4.105
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDeng, Yipu-
dc.contributor.authorZheng, Jinyang-
dc.contributor.authorHuang, Liqiang-
dc.contributor.authorKannan, Karthik -
dc.date.accessioned2024-03-11T10:43:34Z-
dc.date.available2024-03-11T10:43:34Z-
dc.date.issued2023-08-22-
dc.identifier.citationMIS Quarterly, 2023, v. 47, n. 3, p. 1045-1072-
dc.identifier.issn0276-7783-
dc.identifier.urihttp://hdl.handle.net/10722/340358-
dc.description.abstract<p>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.</p>-
dc.languageeng-
dc.publisherManagement Information Systems Research Center-
dc.relation.ispartofMIS Quarterly-
dc.subjectEconomic value of artificial intelligence-
dc.subjectfield experiment-
dc.subjectmonitoring-
dc.subjectquasi-experiment-
dc.subjectshelf management-
dc.titleLet Artificial Intelligence Be Your Shelf Watchdog: The Impact of Intelligent Image Processing-Powered Shelf Monitoring on Product Sales-
dc.typeArticle-
dc.identifier.doi10.25300/MISQ/2022/16813-
dc.identifier.scopuseid_2-s2.0-85180134044-
dc.identifier.volume47-
dc.identifier.issue3-
dc.identifier.spage1045-
dc.identifier.epage1072-
dc.identifier.isiWOS:001110245400012-
dc.identifier.issnl0276-7783-

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