@article{17869, author = {{Poniatowski, Martin and Lüttenberg, Hedda and Beverungen, Daniel and Kundisch, Dennis}}, journal = {{Information Systems and e-Business Management, Special Issue on Platform Business Models and Platform Strategies}}, pages = {{257 -- 283}}, title = {{{Three Layers of Abstraction—A Conceptual Framework for Theorizing digital Multi-Sided Platforms}}}, volume = {{2}}, year = {{2022}}, } @article{30735, abstract = {{While the Information Systems (IS) discipline has researched digital platforms extensively, the body of knowledge appertaining to platforms still appears fragmented and lacking conceptual consistency. Based on automated text mining and unsupervised machine learning, we collect, analyze, and interpret the IS discipline’s comprehensive research on platforms—comprising 11,049 papers spanning 44 years of research activity. From a cluster analysis concerning platform concepts’ semantically most similar words, we identify six research streams on platforms, each with their own platform terms. Based on interpreting the identified concepts vis-à-vis the extant research and considering a temporal perspective on the concepts’ application, we present a lexicon of platform concepts, to guide further research on platforms in the IS discipline. Researchers and managers can build on our results to position their work appropriately, applying a specific theoretical perspective on platforms in isolation or combining multiple perspectives to study platform phenomena at a more abstract level.}}, author = {{Bartelheimer, Christian and zur Heiden, Philipp and Lüttenberg, Hedda and Beverungen, Daniel}}, issn = {{1019-6781}}, journal = {{Electronic Markets}}, keywords = {{Management of Technology and Innovation, Marketing, Computer Science Applications, Economics and Econometrics, Business and International Management}}, publisher = {{Springer Science and Business Media LLC}}, title = {{{Systematizing the lexicon of platforms in information systems: a data-driven study}}}, doi = {{10.1007/s12525-022-00530-6}}, year = {{2022}}, } @article{21242, author = {{Lüttenberg, Hedda and Beverungen, Daniel and Poniatowski, Martin and Kundisch, Dennis and Wünderlich, Nancy}}, journal = {{Wirtschaftsinformatik & Management}}, number = {{2}}, pages = {{120--131}}, title = {{{Drei Strategien zur Etablierung digitaler Plattformen in der Industrie}}}, volume = {{13}}, year = {{2021}}, } @inproceedings{16837, author = {{Lüttenberg, Hedda}}, booktitle = {{Designing for Digital Transformation. Co-Creating Services with Citizens and Industry. DESRIST 2020}}, editor = {{Hofmann, Sara and Müller, Oliver and Rossi, Matti}}, issn = {{1611-3349}}, location = {{Kristiansand, Norway}}, publisher = {{Springer}}, title = {{{PS³—A Domain-specific Modeling Language for Platform-based Smart Service Systems}}}, doi = {{10.1007/978-3-030-64823-7_42}}, volume = {{12388}}, year = {{2020}}, } @inproceedings{15499, author = {{Wolf, Verena and Lüttenberg, Hedda}}, booktitle = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}}, title = {{{Capabilities for Ambidextrous Innovation of Digital Service}}}, year = {{2020}}, } @techreport{13181, author = {{Post, Till and Heuermann, Aaron and Wiesner, Stefan and Olschewski, Detlef and Maaß, Wolfgang and Klatt, Rüdiger and Jussen, Philipp and Ragab, Sherif and Senderek, Roman and Höckmayr, Benedikt and Schulz, Thomas and Meyer, Kyrill and Heinen, Ewald and Hocken, Christian and Fischer, Simon and Lattemann, Christoph and Redlich, Beke and Schlimm, Katrin and Ziegler, Christoph and Rechtien, Christopher and Schröder, Markus and Kube, Bernhard and Pöppelbuß, Jens and Wiesche, Manuel and Semmann, Martin and Bartelheimer, Christian and Beverungen, Daniel and Lüttenberg, Hedda and Wolf, Verena and Bongers, Franziska and Winkler, Corinna and Schumann, Jan Hendrik and Li, Mahei and Brinker, Jonas and Hagen, Simon and Kammler, Friedemann and Strina, Giuseppe and Ernst, Philipp and Falkus, Michael}}, title = {{{DIN SPEC 33453:2019-09, Entwicklung digitaler Dienstleistungssysteme}}}, doi = {{10.31030/3085072}}, year = {{2019}}, } @inproceedings{2861, abstract = {{The Digital Transformation alters business models in all fields of application, but not all industries transform at the same speed. While recent innovations in smart products, big data, and machine learn-ing have profoundly transformed business models in the high-tech sector, less digitalized industries—like agriculture—have only begun to capitalize on these technologies. Inspired by predictive mainte-nance strategies for industrial equipment, the purpose of this paper is to design, implement, and evaluate a predictive maintenance method for agricultural machines that predicts future defects of a machine’s components, based on a data-driven analysis of service records. An evaluation with 3,407 real-world service records proves that the method predicts damaged parts with a mean accuracy of 86.34%. The artifact is an exaptation of previous design knowledge from high-tech industries to agriculture—a sector in which machines move through rough territory and adverse weather conditions, are utilized exten-sively for short periods, and do not provide sensor data to service providers. Deployed on a platform, the prediction method enables co-creating a predictive maintenance service that helps farmers to avoid resources shortages during harvest seasons, while service providers can plan and conduct maintenance service preemptively and with increased efficiency. }}, author = {{Lüttenberg, Hedda and Bartelheimer, Christian and Beverungen, Daniel}}, location = {{Portsmouth, UK}}, title = {{{Designing Predictive Maintenance for Agricultural Machines}}}, year = {{2018}}, } @inbook{4519, author = {{Lüttenberg, Hedda and Wolf, Verena and Beverungen, Daniel}}, booktitle = {{Service Engineering}}, isbn = {{9783658209049}}, pages = {{31--49}}, publisher = {{Springer Fachmedien Wiesbaden}}, title = {{{Service (Systems) Engineering für die Produktion}}}, doi = {{10.1007/978-3-658-20905-6_3}}, year = {{2018}}, } @article{4516, abstract = {{Although many methods have been proposed for engineering service systems and customer solutions, most of these approaches give little consideration to recombinant service innovation. Recombinant innovation refers to reusing and integrating resources that were previously unconnected. In an age of networked products and data, we can expect that many service innovations will be based on adding, dissociating, and associating existing value propositions by accessing internal and external resources instead of designing them from scratch. The purpose of this paper is to identify if current service engineering approaches account for the mechanisms of recombinant innovation and to design a method for recombinant service systems engineering. In a conceptual analysis of 24 service engineering methods, the study identified that most methods (1) focus on designing value propositions instead of service systems, (2) view service independent of physical goods, (3) are either linear or iterative instead of agile, and (4) do not sufficiently address the mechanisms of recombinant innovation. The paper discusses how these deficiencies can be remedied and designs a revised service systems engineering approach that reorganizes service engineering processes according to four design principles. The method is demonstrated with the recombinant design of a service system for predictive maintenance of agricultural machines.}}, author = {{Beverungen, Daniel and Lüttenberg, Hedda and Wolf, Verena}}, issn = {{2363-7005}}, journal = {{Business & Information Systems Engineering}}, keywords = {{Service engineering, Recombinant innovation, (Product-)service system, Design science research, New service development}}, number = {{5}}, pages = {{377--391}}, publisher = {{SpringerNature}}, title = {{{Recombinant Service Systems Engineering}}}, doi = {{10.1007/s12599-018-0526-4}}, volume = {{60}}, year = {{2018}}, } @inproceedings{2860, abstract = {{Although many methods have been proposed for engineering services and customer solutions, most of these approaches give little consideration to recombinant service innovation. In an age of smart products and smart data, we can, however, expect that many of future service innovations need to be based on adding, transferring, dissociating, and associating existing value propositions. The purpose of this paper is to outline what properties constitute recombinant service innovation and to identify if current service engineering approaches fulfill these properties. Based on a conceptual in-depth analysis of 24 service engineering methods, we identify that most methods focus on designing value propositions instead of service systems, view service independent of physical goods, are linear or iterative, and incompletely address the mechanisms of recombinant innovation. We discuss how these deficiencies can be remedied and propose a first conceptual model of a revised se rvice system engineering approach.}}, author = {{Beverungen, Daniel and Lüttenberg, Hedda and Wolf, Verena}}, booktitle = {{Proceedings der 13. Internationalen Tagung Wirtschaftsinformatik (WI 2017)}}, editor = {{Leimeister, Jan Marco and Brenner, Walter}}, keywords = {{Service engineering, recombinant innovation, (product - )service system, literature analysis, new service development}}, location = {{St. Gallen, Switzerland}}, pages = {{136--150}}, title = {{{Recombinant Service System Engineering}}}, year = {{2017}}, }