Algorithm supported induction for building theory : how can we use prediction models to theorize?
Year of publication: |
2021
|
---|---|
Authors: | Shrestha, Yash R. ; He, Fang ; Puranam, Phanish ; Krogh, Georg von |
Published in: |
Organization science : a journal of the Institute for Operations Research and the Management Sciences ; bridging disciplines to advance knowledge of organizations. - Catonsville, MD : Institute for Operations Research and the Management Sciences, ISSN 1047-7039, ZDB-ID 1022236-4. - Vol. 32.2021, 3, p. 856-880
|
Subject: | machine learning | algorithmic induction | theory building | Algorithmus | Algorithm | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Theorie | Theory |
-
Forecasting with Artificial Intelligence : Theory and Applications
Hamoudia, Mohsen, (2023)
-
Tuning parameters of deep neural network training algorithms pays off : a computational study
Coppola, Corrado, (2024)
-
A note on the interpretability of machine learning algorithms
Guégan, Dominique, (2020)
- More ...
-
Puranam, Phanish, (2018)
-
Searching together : a theory of human-AI co-creativity
He, Fang, (2023)
-
Organizational decision-making structures in the age of artificial intelligence
Shrestha, Yash R., (2019)
- More ...