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Art der Publikation: Beitrag in Sammelwerk
A Structured Literature Review on the Application of Machine Learning in Retail
- Autor(en):
- Hütsch, Marek; Wulfert, Tobias
- Titel des Sammelbands:
- Proceedings of the 24th International Conference on Enterprise Information Systems (ICEIS)
- Ort(e):
- (Online Event)
- Veröffentlichung:
- 2022
- Digital Object Identifier (DOI):
- doi:10.5220/0011043200003179
- Zitation:
- Download BibTeX
Kurzfassung
Machine learning (ML) has the potential to take on a variety of routine and non-routine tasks in brick-andmortar and e-commerce. Many tasks previously executed manually are susceptible to computerization involving ML. Although procedure models for the introduction of ML across industries exist, it needs to be determined for which tasks in retail ML can be implemented. Hence, we conducted a structured literature review involving 225 research papers to derive possible ML application areas in retail along with the structure of a well-established information systems architecture. In total, we identified 20 application areas for ML in retail that mainly address decision-oriented and economic-operative tasks. We organized the application areas in a framework for practitioners and researchers to determine an appropriate ML usage in retail. Our analysis further revealed that while ML applications in offline retail focus on the article, in e-commerce the customer is pivotal for application areas of ML.