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Feuerriegel, Stefan; Dolata, Mateusz; Schwabe, Gerhard - In: Business & information systems engineering 62 (2020) 4, pp. 379-384

Persistent link: https://www.econbiz.de/10012271843

Using explainable artificial intelligence to improve process quality : evidence from semiconductor manufacturing

Senoner, Julian; Netland, Torbjørn H.; Feuerriegel, Stefan - In: Management science : journal of the Institute for … 68 (2022) 8, pp. 5704-5723

Persistent link: https://www.econbiz.de/10013371026

The cost of fairness in AI : evidence from e-commerce

Zahn, Moritz von; Feuerriegel, Stefan; Kuehl, Niklas - In: Business & information systems engineering 64 (2022) 3, pp. 335-348

Persistent link: https://www.econbiz.de/10013350728

Data-driven dynamic treatment planning for chronic diseases

Naumzik, Christof; Feuerriegel, Stefan; Nielsen, Anne … - In: European journal of operational research : EJOR 305 (2023) 2, pp. 853-867

Persistent link: https://www.econbiz.de/10013479335

Data-driven allocation of preventive care with application to diabetes mellitus type II

Kraus, Mathias; Feuerriegel, Stefan; Saar-Tsechansky, Maytal - In: Manufacturing & service operations management : M & SOM 26 (2024) 1, pp. 137-153

Persistent link: https://www.econbiz.de/10014471307

Algorithmic fairness in business analytics : directions for research and practice

De-Arteaga, Maria; Feuerriegel, Stefan; … - In: Production and operations management : the flagship … 31 (2022) 10, pp. 3749-3770

Persistent link: https://www.econbiz.de/10013419394

From scarcity to abundance : scholars and scholarship in an age of generative artificial intelligence : from the editors

Grimes, Matthew; Krogh, Georg von; Feuerriegel, Stefan; … - In: Academy of Management journal : AMJ 66 (2023) 6, pp. 1617-1624

Persistent link: https://www.econbiz.de/10014448683

Forecasting Electricity Prices With Machine Learning : Predictor Sensitivity

Naumzik, Christof - 2020

Purpose: Trading on electricity markets occurs such that the price settlement takes place before delivery, often day-ahead. In practice, these prices are highly volatile as they largely depend upon a range of variables such as electricity demand and the feed-in from renewable energy sources....

Persistent link: https://www.econbiz.de/10012834232