@incollection{BraunerVervierBrillowskietal.2022,
  author    = {Brauner, Philipp and Vervier, Luisa and Brillowski, Florian and Dammers, Hannah and Steuer-Dankert, Linda and Schneider, Sebastian and Baier, Ralph and Ziefle, Martina and Gries, Thomas and Leicht-Scholten, Carmen and Mertens, Alexander and Nagel, Saskia K.},
  title     = {Organization Routines in Next Generation Manufacturing},
  series = {Forecasting Next Generation Manufacturing},
  booktitle = {Forecasting Next Generation Manufacturing},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-07734-0},
  doi       = {10.1007/978-3-031-07734-0_5},
  pages     = {75 -- 94},
  year      = {2022},
  abstract  = {Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.},
  language  = {en}
}
@inproceedings{PuetzBaierBrauneretal.2022,
  author    = {P{\"u}tz, Sebastian and Baier, Ralph and Brauner, Philipp and Brillowski, Florian and Dammers, Hannah and Liehner, Luca and Mertens, Alexander and Rodemann, Niklas and Schneider, Sebastian and Schollemann, Alexander and Steuer-Dankert, Linda and Vervier, Luisa and Gries, Thomas and Leicht-Scholten, Carmen and Nagel, Saskia K. and Piller, Frank T. and Schuh, G{\"u}nther and Ziefle, Martina and Nitsch, Verena},
  title     = {An interdisciplinary view on humane interfaces for digital shadows in the internet of production},
  series = {2022 15th International Conference on Human System Interaction (HSI)},
  booktitle = {2022 15th International Conference on Human System Interaction (HSI)},
  publisher = {IEEE},
  isbn      = {978-1-6654-6823-7 (Print)},
  issn      = {2158-2246 (Print)},
  doi       = {10.1109/HSI55341.2022.9869467},
  pages     = {8 Seiten},
  year      = {2022},
  abstract  = {Digital shadows play a central role for the next generation industrial internet, also known as Internet of Production (IoP). However, prior research has not considered systematically how human actors interact with digital shadows, shaping their potential for success. To address this research gap, we assembled an interdisciplinary team of authors from diverse areas of human-centered research to propose and discuss design and research recommendations for the implementation of industrial user interfaces for digital shadows, as they are currently conceptualized for the IoP. Based on the four use cases of decision support systems, knowledge sharing in global production networks, human-robot collaboration, and monitoring employee workload, we derive recommendations for interface design and enhancing workers' capabilities. This analysis is extended by introducing requirements from the higher-level perspectives of governance and organization.},
  language  = {en}
}