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Institute
We present an approach towards a data acquisition system for digital twins that uses a 5G net- work for data transmission and localization. The current hardware setup, which utilizes stereo vision and LiDAR for 3D mapping, is explained together with two recorded point cloud data sets. Furthermore, a resulting digital twin comprised of voxelized point cloud data is shown. Ideas for future applications and challenges regarding the system are discussed and an outlook on further development is given.
The advancing digitalization of daily life has led to an increasing number of choices in the digital sphere. User interfaces that require either a judgment or a decision, the so-called digital choice environments (DCEs), are essential focal points for interventions to alter behaviors towards individual or societal welfare. However, there is a lack of descriptive and prescriptive knowledge within the field of DCEs. In this research, we follow a multi-stage approach to classify the characteristics of DCEs from a choice-centric viewpoint and disclose configurational trade-offs. To achieve this, we first build a taxonomy of DCEs that we validate through expert interviews. Subsequently, we use cluster analysis to identify four configurations of DCEs, which serve as the basis for the development of a configurational model that outlines configuration-specific user outcomes. Our results contribute to the existing knowledge of digital value creation as well as the explanatory understanding of trade-offs among different DCEs.
