Deep learning in business analytics and operations research: Models, applications and managerial implications
By Mathias Kraus, Stefan Feuerriegel, Asil Oztekin. European Journal of Operational Research, 2018
329 citations recorded by the source corpus.
Business analytics refers to methods and practices that create value through data for individuals, firms, and organizations. This field is currently experiencing a radical shift due to the advent of deep learning: deep neural networks promise improvements in prediction performance as compared to models from traditional machine learning. However, our research into the existing body of literature reveals a scarcity of research works utilizing deep learning in our discipline. Accordingly, the objectives of this overview article are as follows: (1) we review research on deep learning for business analytics from an operational point of view. (2) We motivate why researchers and practitioners from business analytics should utilize deep neural networks and review potential use cases, necessary requirements, and benefits. (3) We investigate the added value to operations research in different case studies with real data from entrepreneurial undertakings. All such cases demonstrate improvements in operational performance over traditional machine learning and thus direct value gains. (4) We provide guidelines and implications for researchers, managers and practitioners in operations research who want to advance their capabilities for business analytics with regard to deep learning. (5) Our computational experiments find that default, out-of-the-box architectures are often suboptimal and thus highlight the value of customized architectures by proposing a novel deep-embedded network.
Subfields: Management Information Systems, Management Science and Operations Research
View Paper: https://www.semanticscholar.org/paper/d70ca622e4085c6643f07a3237fe54a52c173f8c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Management Information Systems
In Management Science and Operations Research
Citations in the corpus
- Generative AI (2023, unknown): “In addition, many unique use cases such as, for example, modeling functional properties of proteins (Unsal et al. 2022) (Janiesch et al. 2021; Kraus et al. 2020), for example, sequential data such as human language or spatial data such as images.”
- Understanding managers’ attitudes and behavioral intentions towards using artificial intelligence for organizational decision-making (2021, background): “The position has not changed much in the second era: for example, Kraus et al. (2020) considered the technical accuracy, potential value and data availability in respect of deep learning systems, but not managers ’ attitudes towards using them.”