Asil Oztekin

Deep learning in business analytics and operations research: Models, applications and managerial implications

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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 work are as follows: (1) we motivate why researchers and practitioners from business analytics should utilize deep neural networks and review potential use cases, necessary requirements, and benefits. (2) We investigate the added value to operations research in different case studies with real data from entrepreneurial undertakings. All such cases demonstrate a higher prediction performance in comparison to traditional machine learning and thus direct value gains. (3) 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. (4) We finally discuss directions for future research in the field of business analytics.

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