@inproceedings{DinghoferHartung2020,
  author    = {Dinghofer, Kai and Hartung, Frank},
  title     = {Analysis of Criteria for the Selection of Machine Learning Frameworks},
  series = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  booktitle = {2020 International Conference on Computing, Networking and Communications (ICNC)},
  publisher = {IEEE},
  address   = {New York, NY},
  doi       = {10.1109/ICNC47757.2020.9049650},
  pages     = {373 -- 377},
  year      = {2020},
  abstract  = {With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.},
  language  = {en}
}
@article{BensbergAuthCzarnecki2020,
  author    = {Bensberg, Frank and Auth, Gunnar and Czarnecki, Christian},
  title     = {Literaturanalyse mit Text Mining},
  series = {E-Learning and Education (eleed)},
  journal   = {E-Learning and Education (eleed)},
  number    = {13},
  editor    = {Haake, J{\"o}rg M.},
  publisher = {FernUniversit{\"a}t in Hagen},
  address   = {Hagen},
  issn      = {1860-7470},
  pages     = {1 -- 13},
  year      = {2020},
  abstract  = {Die Durchf{\"u}hrung einer systematischen Literaturrecherche ist eine zentrale Kompetenz wissenschaftlichen Arbeitens und bildet daher einen festen Ausbildungsbestandteil von Bachelor- und Masterstudieng{\"a}ngen. In entsprechenden Lehrveranstaltungen werden Studierende zwar mit den grundlegenden Hilfsmitteln zur Suche und Verwaltung von Literatur vertraut gemacht, allerdings werden die Potenziale textanalytischer Methoden und Anwendungssysteme (Text Mining, Text Analytics) dabei zumeist nicht abgedeckt. Folglich werden Datenkompetenzen, die zur systemgest{\"u}tzten Analyse und Erschließung von Literaturdaten erforderlich sind, nicht hinreichend ausgepr{\"a}gt. Um diese Kompetenzl{\"u}cke zu adressieren, ist an der Hochschule Osnabr{\"u}ck eine Lehrveranstaltung konzipiert und projektorientiert umgesetzt worden, die sich insbesondere an Studierende wirtschaftswissenschaftlicher Studieng{\"a}nge richtet. Dieser Beitrag dokumentiert die fachliche sowie technische Ausgestaltung dieser Veranstaltung und zeigt Potenziale f{\"u}r die k{\"u}nftige Weiterentwicklung auf.},
  language  = {de}
}
@incollection{SchneiderWisselinkNoelleetal.2020,
  author    = {Schneider, Dominik and Wisselink, Frank and N{\"o}lle, Nikolai and Czarnecki, Christian},
  title     = {Influence of artificial intelligence on commercial interactions in the consumer market},
  series = {Automatisierung und Personalisierung von Dienstleistungen : Methoden - Potenziale - Einsatzfelder},
  booktitle = {Automatisierung und Personalisierung von Dienstleistungen : Methoden - Potenziale - Einsatzfelder},
  editor    = {Bruhn, Manfred and Hadwich, Karsten},
  publisher = {Springer Gabler},
  address   = {Wiesbaden},
  isbn      = {978-3-658-30167-5 (Print)},
  doi       = {10.1007/978-3-658-30168-2_7},
  pages     = {183 -- 205},
  year      = {2020},
  abstract  = {Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.},
  language  = {en}
}
@incollection{BensbergAuthCzarnecki2021,
  author    = {Bensberg, Frank and Auth, Gunnar and Czarnecki, Christian},
  title     = {Finding the perfect RPA match : a criteria-based selection method for RPA solutions},
  series = {Robotic process automation : Management, technology, applications},
  booktitle = {Robotic process automation : Management, technology, applications},
  editor    = {Czarnecki, Christian and Fettke, Peter},
  publisher = {De Gruyter},
  address   = {Oldenbourg},
  isbn      = {978-3-11-067677-8},
  doi       = {10.1515/9783110676693-201},
  pages     = {47 -- 75},
  year      = {2021},
  abstract  = {The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.},
  language  = {en}
}
@incollection{SchneiderWisselinkNoelleetal.2021,
  author    = {Schneider, Dominik and Wisselink, Frank and N{\"o}lle, Nikolai and Czarnecki, Christian},
  title     = {Einfluss von K{\"u}nstlicher Intelligenz auf Customer Journeys am Beispiel von intelligentem Parken},
  series = {K{\"u}nstliche Intelligenz in der Anwendung : Rechtliche Aspekte, Anwendungspotenziale und Einsatzszenarien},
  booktitle = {K{\"u}nstliche Intelligenz in der Anwendung : Rechtliche Aspekte, Anwendungspotenziale und Einsatzszenarien},
  editor    = {Barton, Thomas and M{\"u}ller, Christian},
  publisher = {Springer Vieweg},
  address   = {Wiesbaden},
  isbn      = {978-3-658-30935-0 (Print)},
  doi       = {10.1007/978-3-658-30936-7_7},
  pages     = {99 -- 122},
  year      = {2021},
  abstract  = {Im Konsumentenmarkt entstehen vermehrt neue Anwendungen von K{\"u}nstlicher Intelligenz (KI). Zunehmend dr{\"a}ngen auch Ger{\"a}te und Dienste in den Markt, die eigenst{\"a}ndig {\"u}ber das Internet kommunizieren. Dadurch k{\"o}nnen diese Ger{\"a}te und Dienste mit neuartigen KI-basierten Diensten verbessert werden. Solche Dienste k{\"o}nnen die Art und Weise beeinflussen, wie Kunden kommerzielle Entscheidungen treffen und somit das Kundenerlebnis maßgeblich ver{\"a}ndern. Der Einfluss von KI auf kommerzielle Interaktionen wurde bisher noch nicht umfassend untersucht. Basierend auf einem Framework, welches einen ersten {\"U}berblick {\"u}ber die Effekte von KI auf kommerzielle Interaktionen gibt, wird in diesem Kapitel der Einfluss von KI auf Customer Journeys am konkreten Anwendungsfall des intelligenten Parkens analysiert. Die daraus gewonnenen Erkenntnisse k{\"o}nnen in der Praxis als Grundlage genutzt werden, um das Potenzial von KI zu verstehen und bei der Gestaltung eigener Customer Journeys umzusetzen.},
  language  = {de}
}
@incollection{BensbergCzarneckiGrob2022,
  author    = {Bensberg, Frank and Czarnecki, Christian and Grob, Heinz Lothar},
  title     = {Wirtschaftlichkeitsbewertung von Smart Services mit vollst{\"a}ndigen Finanzpl{\"a}nen},
  series = {Smart Services: Band 1: Konzepte - Methoden - Prozesse},
  booktitle = {Smart Services: Band 1: Konzepte - Methoden - Prozesse},
  editor    = {Bruhn, Manfred and Hadwich, Karsten},
  publisher = {Springer Gabler},
  address   = {Wiesbaden},
  isbn      = {978-3-658-37344-3 (Online)},
  doi       = {10.1007/978-3-658-37344-3_6},
  pages     = {225 -- 251},
  year      = {2022},
  abstract  = {Dieser Beitrag stellt einen Bewertungsrahmen f{\"u}r Smart Services vor, der auf dem Konzept vollst{\"a}ndiger Finanzpl{\"a}ne (VOFI) basiert. Zun{\"a}chst wird eine IoT-Architektur f{\"u}r Smart Services eingef{\"u}hrt, die die Grundlage f{\"u}r deren Betrachtung aus Sicht der Unternehmensplanung liefert. Hierauf aufbauend wird ein Bewertungsrahmen f{\"u}r die finanzplanorientierte Wirtschaftlichkeitsbewertung von Smart Services geschaffen, mit dem die relevanten Zahlungsfolgen differenziert erfasst werden. Mithilfe des entwickelten VOFI-Systems wird anschließend aufgezeigt, wie mithilfe einer Risikoanalyse die Unsicherheit von Modellparametern ber{\"u}cksichtigt werden kann.},
  language  = {de}
}
@incollection{SchneiderWisselinkCzarneckietal.2024,
  author    = {Schneider, Dominik and Wisselink, Frank and Czarnecki, Christian and N{\"o}lle, Nikolai},
  title     = {Benefits and framework conditions for information-driven business models concerning the Internet of Things},
  series = {Digitalization in companies},
  booktitle = {Digitalization in companies},
  publisher = {Springer},
  address   = {Wiesbaden},
  isbn      = {978-3-658-39093-8 (Print)},
  doi       = {10.1007/978-3-658-39094-5_5},
  pages     = {59 -- 75},
  year      = {2024},
  abstract  = {In the context of the increasing digitalization, the Internet of Things (IoT) is seen as a technological driver through which completely new business models can emerge in the interaction of different players. Identified key players include traditional industrial companies, municipalities and telecommunications companies. The latter, by providing connectivity, ensure that small devices with tiny batteries can be connected almost anywhere and directly to the Internet. There are already many IoT use cases on the market that provide simplification for end users, such as Philips Hue Tap. In addition to business models based on connectivity, there is great potential for information-driven business models that can support or enhance existing business models. One example is the IoT use case Park and Joy, which uses sensors to connect parking spaces and inform drivers about available parking spaces in real time. Information-driven business models can be based on data generated in IoT use cases. For example, a telecommunications company can add value by deriving more decision-relevant information - called insights - from data that is used to increase decision agility. In addition, insights can be monetized. The monetization of insights can only be sustainable, if careful attention is taken and frameworks are considered. In this chapter, the concept of information-driven business models is explained and illustrated with the concrete use case Park and Joy. In addition, the benefits, risks and framework conditions are discussed.},
  language  = {en}
}