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Authors: Christian Daase ; Christian Haertel and Klaus Turowski

Affiliation: Institute of Technical and Business Information Systems, Otto-von-Guericke University, Magdeburg, Germany

Keyword(s): Artificial Intelligence, Business Intelligence, Video Analytics, Society 5.0, Data Science.

Abstract: This paper explores research questions and perspectives for the next stage of societal development, often referred to as Society 5.0, and the field of modern retail. Artificial intelligence (AI) is seen as a key component that provides retailers with the means to optimize their store layouts, advertising campaigns, and overall business strategy. The need to make AI-based decisions comprehensible and tangible to ensure acceptance by the respective target groups has been emphasized with the concept of explainable AI in various research works. Based on observations from the AI domain and the business world, the need to integrate explainability into commercial AI-driven operations is addressed and the concept of explainable business intelligence (XBI) is proposed. A set of potential research questions for video analytics in retail in the age of Society 5.0, as one of the most promising use cases in this regard, is derived from the literature and the proposal of XBI in terms of the outlin ed opportunities and challenges is explained, critically discussed, and visualized. (More)

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Paper citation in several formats:
Daase, C.; Haertel, C. and Turowski, K. (2024). Explainable Business Intelligence for Video Analytics in Retail. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-692-7; ISSN 2184-4992, SciTePress, pages 784-791. DOI: 10.5220/0012694600003690

@conference{iceis24,
author={Christian Daase. and Christian Haertel. and Klaus Turowski.},
title={Explainable Business Intelligence for Video Analytics in Retail},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2024},
pages={784-791},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012694600003690},
isbn={978-989-758-692-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Explainable Business Intelligence for Video Analytics in Retail
SN - 978-989-758-692-7
IS - 2184-4992
AU - Daase, C.
AU - Haertel, C.
AU - Turowski, K.
PY - 2024
SP - 784
EP - 791
DO - 10.5220/0012694600003690
PB - SciTePress