This book examines the impact of Computer Vision Systems (CVS) on business value creation. Recent advances in hardware, network architectures, and analytical methods have made it possible to automate the processes of visual perception, object recognition, and decision-making. As a result, organizations have unprecedented opportunities to enhance existing value creation processes and develop entirely new business models through the targeted application of CVS.
Using a mixed-methods research approach, this study identifies the key factors influencing the successful implementation of CVS and analyzes their interrelationships. Particular attention is given to business value creation and the underlying business models. The findings from both qualitative and quantitative analyses are integrated into a comprehensive theoretical model that explains the relationships among the identified factors. Building on these findings, the book develops practical design recommendations for the successful implementation of CVS. It therefore contributes both to academic research and to the practical, sustainable, and value-creating adoption of Computer Vision Systems in organizations.

Sebastian Trinks was a research associate at the Institute of Information Systems at Technische Universität Bergakademie Freiberg for six years. His research focused on real-time analytics, edge computing, image mining, and computer vision. Since 2023, he has been working as a Project Manager specializing in Data Science and Business Intelligence.