@article{WolteringSardouxKlasenFeldmann2020,
  author    = {Woltering, Tim and Sardoux Klasen, Andr{\´e} and Feldmann, Carsten},
  title     = {The Economic Value Added of Augmented Reality in the Packing Process},
  series = {Journal of Applied Business and Economics},
  volume    = {22},
  journal   = {Journal of Applied Business and Economics},
  number    = {5},
  doi       = {10.33423/jabe.v22i5.3051},
  pages     = {88 -- 96},
  year      = {2020},
  language  = {en}
}
@inproceedings{WolteringSardouxKlasenFeldmann2020,
  author    = {Woltering, Tim and Sardoux Klasen, Andre and Feldmann, Carsten},
  title     = {Augmented Reality in the Packing Process A Model for Analyzing Economic Efficiency},
  series = {Dynamics in Logistics. LDIC 2020. Lecture Notes in Logistics.},
  booktitle = {Dynamics in Logistics. LDIC 2020. Lecture Notes in Logistics.},
  editor    = {Freitag, Michael and Haasis, Hans-Dietrich and Kotzab, Herbert and Pannek, J{\"u}rgen},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-030-44783-0},
  doi       = {https://doi.org/10.1007/978-3-030-44783-0_46},
  pages     = {493 -- 503},
  year      = {2020},
  abstract  = {The use of augmented reality (AR) in outbound logistics is associated with potentially strong stimuli for cost savings and throughput time. Nevertheless, the benefits of AR compared to conventional methods require a holistic analysis for investment decision making. Until now, research has only assessed case-study-related potentials and selected aspects of the technology. This paper answers the following research questions: How can the economic efficiency of AR in the packing process be quantified by utilizing a holistic model of value drivers? How can AR be technically implemented for packing processes in outbound logistics? What economic profit results from the use of AR technology in a case company's packing process? The presented model enables the investment decision to be supported based on economic value added (EVA), thereby providing an assessment of value drivers in packing systems. Cost drivers are identified on the basis of the Supply Chain Operations Reference (SCOR) process model. The technical and economic validation of the model was carried out by means of an empirical study: Expert interviews were conducted for validating the model elements. Data collection by a prototype at a mechanical-engineering company was used to calculate the value contribution. The mapping of cause-effect relationships within the framework of EVA driver trees has proven itself in both the expert interviews and the prototype validation. The field experiment at the case company demonstrated a positive value contribution of AR, in particular regarding employee productivity, length and variance of throughput time, quality aspects, volume utilization, and quantity of packing material used.},
  language  = {de}
}
@inproceedings{WiethoelterSalingreFeldmannetal.2023,
  author    = {Wieth{\"o}lter, Jost and Salingr{\´e}, Jan and Feldmann, Carsten and Schwanitz, Johannes and Niessing, J{\"o}rg},
  title     = {Exploring Customer Journey Mining and RPA: Prediction of Customers' Next Touchpoint},
  series = {Business Process Management: Blockchain, Robotic Process Automation and Educators Forum},
  booktitle = {Business Process Management: Blockchain, Robotic Process Automation and Educators Forum},
  editor    = {K{\"o}pke, Julius and Plattfaut, Ralf and Gdowska, Katarzyna and Munoz-Gama, Jorge and van der Werf, Jan Martijn and L{\´o}pez-Pintado, Orlenys and Rehse, Jana-Rebecca and Gonzalez-Lopez, Fernanda and Smit, Koen},
  publisher = {Springer},
  isbn      = {978-3-031-43432-7},
  issn      = {1865-1348},
  doi       = {https://doi.org/10.1007/978-3-031-43433-4},
  pages     = {181 -- 196},
  year      = {2023},
  abstract  = {In-depth analysis of customer journeys to broaden the understanding of customer behaviors and expectations in order to improve the customer experience is considered highly relevant in modern business practices. Recent studies predominantly focus on retrospective analysis of customer data, whereas more forward-directed concepts, namely predictions, are rarely addressed. Additionally, the integration of robotic process automation (RPA) to potentially increase the efficiency of customer journey analysis is not discussed in the current field of research. To fill this research gap, this paper introduces "customer journey mining". Process mining techniques are applied to leverage digital customer data for accurate prediction of customer movements through individual journeys, creating valuable insights for improving the customer experience. Striving for improved efficiency, the potential interplay of RPA and customer journey mining is examined accordingly. The research methodology followed is based on a design science research process. An initially defined customer journey mining artifact is operationalized through an illustrative case study. This operationalization is achieved by analyzing a log file of an online travel agency functioning as an orientation for researchers and practitioners while also evaluating the initially defined framework. The data is used to train seven distinct prediction models to forecast the touchpoint a customer is most likely to visit next. Gradient-boosted trees yield the highest prediction accuracy with 43.1\%. The findings further indicate technical suitability for RPA implementation, while financial viability is unlikely.},
  language  = {en}
}
@incollection{WiethoelterSalingreFeldmannetal.2023,
  author    = {Wieth{\"o}lter, Jost and Salingr{\´e}, Jan and Feldmann, Carsten and Schwanitz, Johannes and Niessing, Joerg},
  title     = {Exploring Customer Journey Mining and RPA: Prediction of Customers' Next Touchpoint},
  series = {Business Process Management: Blockchain, Robotic Process Automation and Educators Forum. BPM 2023. Lecture Notes in Business Information Processing, vol 491. J. K{\"o}pke (ed.)},
  booktitle = {Business Process Management: Blockchain, Robotic Process Automation and Educators Forum. BPM 2023. Lecture Notes in Business Information Processing, vol 491. J. K{\"o}pke (ed.)},
  publisher = {Springer},
  address   = {Cham},
  isbn      = {978-3-031-43432-7},
  doi       = {10.1007/978-3-031-43433-4_12},
  publisher      = {FH M{\"u}nster - University of Applied Sciences},
  pages     = {181 -- 196},
  year      = {2023},
  language  = {en}
}
@article{WertherFeldmann2020,
  author    = {Werther, Eike and Feldmann, Carsten},
  title     = {Auf der {\"U}berholspur: Digitale Speditionen},
  series = {Logistik Heute},
  volume    = {42},
  journal   = {Logistik Heute},
  number    = {7-8},
  editor    = {Huss, Wolfgang and Seebauer, Petra},
  issn      = {0173-6213},
  pages     = {58 -- 59},
  year      = {2020},
  language  = {de}
}
@inproceedings{ThesingFeldmannBurchardt2021,
  author    = {Thesing, Theo and Feldmann, Carsten and Burchardt, Martin},
  title     = {Agile versus Waterfall Project Management: Decision Model for Selecting the Appropriate Approach to a Project},
  series = {ProjMAN - International Conference on Project Management 2020, Procedia Computer Science 181 (2021)},
  booktitle = {ProjMAN - International Conference on Project Management 2020, Procedia Computer Science 181 (2021)},
  doi       = {10.1016/j.procs.2021.01.227},
  pages     = {746 -- 756},
  year      = {2021},
  language  = {en}
}
@inproceedings{TackenbergJungkindFeldmannetal.2019,
  author    = {Tackenberg, Sven and Jungkind, Wilfried and Feldmann, Carsten and Appelfeller, Wieland},
  title     = {Digital Transformation of Companies: Experience Gained in the Implementation of an IoT Check},
  series = {9th International Conference on Production Engineering and Management (PEM) 2019, Proceedings},
  booktitle = {9th International Conference on Production Engineering and Management (PEM) 2019, Proceedings},
  editor    = {Padoano, Elio and Villmer, Franz-Josef},
  address   = {Triest, Lemgo},
  isbn      = {978-3-946856-04-7},
  pages     = {281 -- 290},
  year      = {2019},
  language  = {en}
}
@article{TackenbergJungkindFeldmannetal.2019,
  author    = {Tackenberg, Sven and Jungkind, Wilfried and Feldmann, Carsten and Appelfeller, Wieland},
  title     = {Digitale Transformation von Unternehmen: Erfahrungen aus der Durchf{\"u}hrung eines Digitalisierungs-Checks},
  series = {ZWF Zeitschrift f{\"u}r wirtschaftlichen Fabrikbetrieb},
  volume    = {114},
  journal   = {ZWF Zeitschrift f{\"u}r wirtschaftlichen Fabrikbetrieb},
  number    = {11},
  issn      = {0032-678X},
  doi       = {10.3139/104.112190},
  pages     = {771 -- 775},
  year      = {2019},
  language  = {de}
}
@incollection{StahlFeldmannDircksen2022,
  author    = {Stahl, Maximilian and Feldmann, Carsten and Dircksen, Michael},
  title     = {Straßeng{\"u}terverkehr der Zukunft},
  series = {Jahrbuch Logistik},
  booktitle = {Jahrbuch Logistik},
  isbn      = {978-3-947135-09-7},
  publisher      = {FH M{\"u}nster - University of Applied Sciences},
  pages     = {14 -- 18},
  year      = {2022},
  language  = {de}
}
@techreport{SossnaSardouxKlasenFeldmann2020,
  author    = {Sossna, David and Sardoux Klasen, Andr{\´e} and Feldmann, Carsten},
  title     = {Antworten made in m{\"u}nsterLAND: Ergebnisbericht der DigiTrans@KMU Online-Umfrage},
  pages     = {18},
  year      = {2020},
  language  = {de}
}