@inproceedings{Grum2022,
  author    = {Grum, Marcus},
  title     = {Context-aware, intelligent musical instruments for improving knowledge-intensive business processes},
  series = {Business modeling and software design},
  volume    = {453},
  booktitle = {Business modeling and software design},
  editor    = {Shishkov, Boris},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-11509-7},
  doi       = {10.1007/978-3-031-11510-3_5},
  pages     = {69 -- 88},
  year      = {2022},
  abstract  = {With shorter song publication cycles in music industries and a reduced number of physical contact opportunities because of disruptions that may be an obstacle for musicians to cooperate, collaborative time consumption is a highly relevant target factor providing a chance for feedback in contemporary music production processes. This work aims to extend prior research on knowledge transfer velocity by augmenting traditional designs of musical instruments with (I) Digital Twins, (II) Internet of Things and (III) Cyber-Physical System capabilities and consider a new type of musical instrument as a tool to improve knowledge transfers at knowledge-intensive forms of business processes. In a design-science-oriented way, a prototype of a sensitive guitar is constructed as information and cyber-physical system. Findings show that this intelligent SensGuitar increases feedback opportunities. This study establishes the importance of conversion-specific music production processes and novel forms of interactions at guitar playing as drivers of high knowledge transfer velocities in teams and among individuals.},
  language  = {en}
}
@inproceedings{GrumBenderGronauetal.2020,
  author    = {Grum, Marcus and Bender, Benedict and Gronau, Norbert and Alfa, Attahiru S.},
  title     = {Efficient task realizations in networked production infrastructures},
  series = {Proceedings of the Conference on Production Systems and Logistics},
  booktitle = {Proceedings of the Conference on Production Systems and Logistics},
  publisher = {publish-Ing.},
  address   = {Hannover},
  doi       = {10.15488/9682},
  pages     = {397 -- 407},
  year      = {2020},
  abstract  = {As Industry 4.0 infrastructures are seen as highly evolutionary environment with volatile, and time-dependent workloads for analytical tasks, particularly the optimal dimensioning of IT hardware is a challenge for decision makers because the digital processing of these tasks can be decoupled from their physical place of origin. Flexible architecture models to allocate tasks efficiently with regard to multi-facet aspects and a predefined set of local systems and external cloud services have been proven in small example scenarios. This paper provides a benchmark of existing task realization strategies, composed of (1) task distribution and (2) task prioritization in a real-world scenario simulation. It identifies heuristics as superior strategies.},
  language  = {en}
}