Abstract
Numerous use cases exist in industrial practice in which data availability, up-to-dateness, accessibility and volume are insufficient to solve time-critical problems optimally. One example is bottleneck management (BM) in the automotive industry, where information is often time-delayed and incomplete. Time-critical volume coverage for supply risks leads to the question of how and where to obtain the information. Improved data accuracy therefore enables faster and more precise decisions. The literature offers approaches for the use of social media (SM) for risk assessment, which are reviewed regarding their suitability for transfer to BM in the automotive industry. Adapted from a multiple-cases study, this paper presents the first application of using external data generated by SM formats and develops a new, obstacle mitigated method of SM-knowledge-based BM. The goal of this study is to apply SM in the BM of the automotive industry and, hence, to enhance the typical current BM process.