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@PHDTHESIS{Keler:979943,
      author       = {Keßler, Melanie},
      othercontributors = {Arlinghaus, Julia and Letmathe, Peter},
      title        = {{T}he human factor in operations management - understanding
                      the influence of cognitive biases in production and risk
                      management},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2024-01971},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2023},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2024; Dissertation, Rheinisch-Westfälische
                      Technische Hochschule Aachen, 2023},
      abstract     = {10 years after the introduction of the term Industry 4.0,
                      it is becoming apparent in practice that many potentials
                      remain unharnessed. Many companies still associate the
                      concept of the autonomous, self-controlling factory with the
                      hope of productivity increases and efficiency gains.
                      Particularly in the area of production planning and control
                      (PPC) – one of the main areas in operations management –
                      industrial practice is hoping for increased transparency and
                      reductions in complexity and costs through the use of
                      digital technologies. However, these new digital
                      technologies lead to new risks, for instance in the area of
                      cyber security, and also change existing risk profiles. This
                      situation requires an appropriate risk management which
                      addresses these new risks. Despite this increasing
                      automation, the human factor remains a key resource in the
                      smart factory and represents as a central decision maker a
                      crucial role in the success of digital transformation
                      projects and risk management. Although research in
                      behavioural economics has increased significantly in recent
                      years, the majority of decision-making models in PPC and
                      risk management are based on the assumption of rationally
                      human behaviour. However, the application of these models in
                      industrial practice shows that this often leads to problems
                      due to the fact that people do not decide rationally and
                      tend to be influenced in their decision-making by so called
                      “cognitive biases”. In risk management, risks are
                      therefore often assessed incorrectly or even ignored. In the
                      area of PPC, process deviations frequently occur with the
                      consequence of a deterioration in logistical performance.
                      The aim of this dissertation is therefore to analyse how
                      human behaviour influences decisions in operations
                      management and subsequently the logistic performance.
                      Furthermore, recommendations will be developed for how to
                      consider the influencing factors in human decision making in
                      order to improve results. Based on a structured literature
                      review, the findings from the research fields of psychology
                      and operations management were combined. Using a broad
                      database of Industry 4.0 implementation projects, it was
                      possible to observe the influence of cognitive biases in the
                      area of human decision-making. Initial hypotheses were
                      developed and the influence of cognitive distortions on
                      decisions in the risk management and PPC environment was
                      demonstrated with the help of behavioural experiments.},
      cin          = {812110},
      ddc          = {330},
      cid          = {$I:(DE-82)812110_20140620$},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2024-01971},
      url          = {https://publications.rwth-aachen.de/record/979943},
}