@inproceedings{EigelshovenUllrichBender2020,
  author    = {Eigelshoven, Felix and Ullrich, Andr{\´e} and Bender, Benedict},
  title     = {Public blockchain},
  series = {Proceedings of the 28th European Conference on Information Systems (ECIS)- A Virtual AIS Conference},
  booktitle = {Proceedings of the 28th European Conference on Information Systems (ECIS)- A Virtual AIS Conference},
  pages     = {1 -- 19},
  year      = {2020},
  abstract  = {Blockchain has the potential to change business transactions to a major extent. Thereby, underlying consensus algorithms are the core mechanism to achieve consistency in distributed infrastructures. Their application aims for transparency and accountability in societal transactions. As a result of missing reviews holistically covering consensus algorithms, we aim to (1) identify prevalent consensus algorithms for public blockchains, and (2) address the resource perspective with a sustainability consideration (whereby we address the three spheres of sustainability). Our systematic literature review identified 33 different consensus algorithms for public blockchains. Our contribution is twofold: first, we provide a systematic summary of consensus algorithms for public blockchains derived from the scientific literature as well as real-world applications and systemize them according to their research focus; second, we assess the sustainability of consensus algorithms using a representative sample and thereby highlight the gaps in literature to address the holistic sustainability of consensus algorithms.},
  language  = {en}
}
@article{EigelshovenGronauUllrich2020,
  author    = {Eigelshoven, Felix and Gronau, Norbert and Ullrich, Andr{\´e}},
  title     = {Konsens-Algorithmen von Blockchain},
  series = {Industrie 4.0 Management : Gegenwart und Zukunft industrieller Gesch{\"a}ftsprozesse},
  volume    = {36},
  journal   = {Industrie 4.0 Management : Gegenwart und Zukunft industrieller Gesch{\"a}ftsprozesse},
  number    = {1},
  publisher = {Gito},
  address   = {Berlin},
  issn      = {2364-9208},
  doi       = {10.30844/I40M_20-1_S29-32},
  pages     = {29 -- 32},
  year      = {2020},
  abstract  = {Neben dem enormen Kursanstieg des Bitcoins in den Jahren 2017/2018, stieg im gleichen Maß auch die ben{\"o}tigte Rechenleistung und der damit verbundene Elektrizit{\"a}tsbedarf, um Bl{\"o}cke innerhalb der Bitcoin-Blockchain zu verifizieren. Aus diesem Problem ableitend besch{\"a}ftigt sich dieser Beitrag mit der Fragestellung, welchen Beitrag unterschiedliche Konsens-Algorithmen innerhalb einer Blockchain zur Nachhaltigkeit liefern. Im Ergebnis liegt ein {\"U}berblick {\"u}ber die meist genutzten Konsens-Algorithmen und deren Beitrag zur Nachhaltigkeit vor.},
  language  = {de}
}
@article{ThimUllrichEigelshovenetal.2020,
  author    = {Thim, Christof and Ullrich, Andr{\´e} and Eigelshoven, Felix and Gronau, Norbert and Ritter, Ann-Carolin},
  title     = {Crowdsourcing bei industriellen Innovationen},
  series = {Industrie 4.0 Management : Gegenwart und Zukunft industrieller Gesch{\"a}ftsprozesse},
  volume    = {36},
  journal   = {Industrie 4.0 Management : Gegenwart und Zukunft industrieller Gesch{\"a}ftsprozesse},
  number    = {6},
  publisher = {GITO mbH Verlag},
  address   = {Berlin},
  issn      = {2364-9208},
  doi       = {10.30844/I40M_20-6_S9-13},
  pages     = {9 -- 13},
  year      = {2020},
  abstract  = {Die Innovationst{\"a}tigkeit im industriellen Umfeld verlagert sich durch die Digitalisierung hin zu Produkt-Service-Systemen. Kleine und mittlere Unternehmen haben sich in ihrer Entwicklungst{\"a}tigkeit bisher stark auf die Produktentwicklung bezogen. Der Umstieg auf „smarte" Produkte und die Kopplung an Dienstleistungen erfordert h{\"a}ufig personelle und finanzielle Ressourcen, welche KMU nicht aufbringen k{\"o}nnen. Crowdsourcing stellt eine M{\"o}glichkeit dar, den Innovationsprozess f{\"u}r externe Akteure zu {\"o}ffnen und Kosten- sowie Geschwindigkeitsvorteile zu realisieren. Bei der Integration von Crowdsourcing-Elementen ist jedoch einigen Herausforderungen zu begegnen. Dieser Beitrag zeigt sowohl die Potenziale als auch die Barrieren einer Crowdsourcing-Nutzung im industriellen Umfeld auf.},
  language  = {de}
}
@misc{UllrichVladovaEigelshovenetal.2022,
  author    = {Ullrich, Andr{\´e} and Vladova, Gergana and Eigelshoven, Felix and Renz, Andr{\´e}},
  title     = {Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Wirtschafts- und Sozialwissenschaftliche Reihe},
  number    = {160},
  issn      = {1867-5808},
  doi       = {10.25932/publishup-58907},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-589077},
  pages     = {18},
  year      = {2022},
  abstract  = {Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.},
  language  = {en}
}
@article{UllrichVladovaEigelshovenetal.2022,
  author    = {Ullrich, Andr{\´e} and Vladova, Gergana and Eigelshoven, Felix and Renz, Andr{\´e}},
  title     = {Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions},
  series = {Discover artificial intelligence},
  volume    = {2},
  journal   = {Discover artificial intelligence},
  publisher = {Springer},
  address   = {Cham},
  issn      = {2731-0809},
  doi       = {10.1007/s44163-022-00031-7},
  pages     = {18},
  year      = {2022},
  abstract  = {Teaching and learning as well as administrative processes are still experiencing intensive changes with the rise of artificial intelligence (AI) technologies and its diverse application opportunities in the context of higher education. Therewith, the scientific interest in the topic in general, but also specific focal points rose as well. However, there is no structured overview on AI in teaching and administration processes in higher education institutions that allows to identify major research topics and trends, and concretizing peculiarities and develops recommendations for further action. To overcome this gap, this study seeks to systematize the current scientific discourse on AI in teaching and administration in higher education institutions. This study identified an (1) imbalance in research on AI in educational and administrative contexts, (2) an imbalance in disciplines and lack of interdisciplinary research, (3) inequalities in cross-national research activities, as well as (4) neglected research topics and paths. In this way, a comparative analysis between AI usage in administration and teaching and learning processes, a systematization of the state of research, an identification of research gaps as well as further research path on AI in higher education institutions are contributed to research.},
  language  = {en}
}