RT Journal Article
T1 Pricing powered by artificial intelligence: an assessment model for the sustainable implementation of AI supported price functions
A1 Erdmann, Anett
A1 Yazdani, Morteza
A1 Mas, José Manuel
A1 Marín, Cristina
AB Artificial Intelligence (AI) in the price management process is being applied in business practice and research to a variety of pricing use cases that can be augmented or automated, providing opportunities as a forecasting tool or for price optimization. However, the complexity of evaluating the technology to prioritize implementation is challenging, especially for small and medium enterprises (SMEs), and guidance is sparse. Which are the relevant stakeholder criteria for a sustainable implementation of AI for pricing purpose? Which type of AI supported price functions meet these criteria best? Theoretically motivated by the hedonic price theory and advances in AI research, we identify nine criteria and eight AI supported price functions (AISPF). A multiple attribute decision model (MADM) using the fuzzy Best Worst Method (BWM) and fuzzy combined compromise solution (CoCoSo) is set up and evaluated by pricing experts from Germany and Spain. To validate our results and model stability, we carried out several random sensitivity analyses based on the weight of criteria exchange. The results suggest accuracy and reliability as the most prominent attribute to evaluate AISPF, while ethical and sustainable criteria are sorted as least important. The AISPF which best meet the criteria are financial prices followed by procurement prices.
PB Vilnius University Institute of Data Science and Digital Technologies, Lithuanian Academy of Sciences, Lithuania
SN 0868-4952
YR 2024
FD 2024-05-22
LK https://hdl.handle.net/20.500.14352/120752
UL https://hdl.handle.net/20.500.14352/120752
LA eng
NO Erdmann, A., Yazdani, M., Mas Iglesias, J. M., & Marin Palacios, C. (2024). Pricing powered by artificial intelligence: An assessment model for the sustainable implementation of AI supported price functions. Informatica, 35(3), 529-556.
DS Docta Complutense
RD 16 jun 2025