Background

Becker and Schütte's Handelsinformationssysteme and the associated "Handels-H" reference model provide a domain-specific business process framework (Ordnungsrahmen) that structures the core processes of a retail enterprise: the procurement side (purchasing, disposition, goods receipt, invoice auditing, accounts payable), the distribution side (marketing, selling, goods issue, billing, accounts receivable), the connecting warehousing, and further controlling and supporting functions. This reference framework brings together the typical processes of retail companies with an integrated data view to conceptualize the foundation for retail information systems.

Modern AI and machine learning systems (e.g., for demand forecasting, replenishment processes, pricing optimization) impose data requirements for organizations that are not necessarily captured by the originally developed reference model.

Object of investigation

This thesis systematically revisits the data view of the Handels-H reference model and compares it with the data requirements of current retail AI use cases. The goal is a structured mapping showing which reference-model entities feed which AI application areas, and where gaps exist that the original model does not cover.

Possible research questions

• Which data objects of the Handels-H reference model correspond to the input requirements of the recent retail AI application areas?
• Where does the data view of the original model fall short of the requirements?
• How can the reference model be annotated so that AI-relevant data flows become explicit?

Possible results

• A concept-level mapping table (reference-model entity → AI application area → data-quality requirement).
• A gap analysis and a set of extension recommendations for the data view of the reference model.

Starting literature

• Becker, J. & Schütte, R. (2004). Handelsinformationssysteme: Domänenorientierte Einführung in die Wirtschaftsinformatik, 2nd ed. Frankfurt a. M.: Redline Wirtschaft.
• Becker, J. & Schütte, R. (2007). A Reference Model for Retail Enterprise. In P. Fettke & P. Loos (eds.), Reference Modeling for Business Systems Analysis, pp. 182–205. Hershey, PA: IGI Global. DOI 10.4018/978-1-59904-054-7.ch009.
• Brackmann, C., Hütsch, M. & Wulfert, T. (2023). Identifying Application Areas for Machine Learning in the Retail Sector: A Literature Review and Interview Study. SN Computer Science, 4(5), Art. 426. DOI 10.1007/s42979-023-01888-w.

Recommended prior knowledge

Data Warehousing / Business Intelligence; conceptual and reference modeling (information modeling); foundations of retail management