Artificial intelligence and machine learning for maturity evaluation and model validation
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Publication date
2022
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04B - Conference paper
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ICEME 2022. The 2022 13th International Conference on E-business, Management and Economics (ICEME 2022). Beijing, China (vurtual conference), July 16-18, 2022
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Pages / Duration
256-260
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Beijing
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Abstract
In this paper, we discuss the possibility of using machine learning (ML) to specify and validate maturity models, in particular maturity models related to the assessment of digital capabilities of an organization. Over the last decade, a rather large number of maturity models have been suggested for different aspects (such as type of technology or considered processes) and in relation to different industries. Usually, these models are based on a number of assumptions such as the data used for the assessment, the mathematical formulation of the model and various parameters such as weights or importance indicators. Empirical evidence for such assumptions is usually lacking. We investigate the potential of using data from assessments over time and for similar institutions for the ML of respective models. Related concepts are worked out in some details and for some types of maturity assessment models, a possible application of the concept is discussed.
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Subject (DDC)
330 - Wirtschaft
Event
2022 13th International Conference on E-business, Management and Economics (ICEME 2022)
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16.07.2022
Conference end date
18.07.2022
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978-1-4503-9639-4
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Language
English
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Yes
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Published
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Closed
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Citation
HANNE, Thomas, Phillip GACHNANG, Stella GATZIU GRIVAS, Ilyas KIRECCI und Paul SCHMITTER, 2022. Artificial intelligence and machine learning for maturity evaluation and model validation. In: ICEME 2022. The 2022 13th International Conference on E-business, Management and Economics (ICEME 2022). Beijing, China (vurtual conference), July 16-18, 2022. Beijing. 2022. S. 256–260. ISBN 978-1-4503-9639-4. Verfügbar unter: https://irf.fhnw.ch/handle/11654/43411