@article{50649, author = {{zur Heiden, Philipp and Priefer, Jennifer and Beverungen, Daniel}}, issn = {{0018-9391}}, journal = {{IEEE Transactions on Engineering Management}}, keywords = {{Electrical and Electronic Engineering, Strategy and Management}}, pages = {{1--16}}, publisher = {{Institute of Electrical and Electronics Engineers (IEEE)}}, title = {{{Predictive Maintenance on the Energy Distribution Grid—Design and Evaluation of a Digital Industrial Platform in the Context of a Smart Service System}}}, doi = {{10.1109/tem.2024.3352819}}, year = {{2024}}, } @inproceedings{35893, author = {{zur Heiden, Philipp and Priefer, Jennifer and Beverungen, Daniel}}, booktitle = {{Proceedings of the 56th Conference on System Sciences}}, title = {{{Location-Based Service and Location-Contextualizing Service: Conceptualizing the Co-creation of Value with Location Information}}}, year = {{2023}}, } @inbook{42681, author = {{zur Heiden, Philipp}}, booktitle = {{DASC-PM v1.1 Fallstudien}}, editor = {{Schulz, Michael and Neuhaus, Uwe and Kühnel, Stephan and Rohde, Heiko and Hoseini, Sayed and Theuerkauf, René}}, pages = {{29--38}}, publisher = {{NORDAKADEMIE gAG Hochschule der Wirtschaft}}, title = {{{Projekt FLEMING – Predictive Maintenance von zentralen Komponenten des Mittelspannungsnetzes}}}, year = {{2023}}, } @article{46478, author = {{Bartelheimer, Christian and zur Heiden, Philipp and Berendes, Carsten Ingo and Beverungen, Daniel}}, issn = {{0960-085X}}, journal = {{European Journal of Information Systems}}, keywords = {{Library and Information Sciences, Information Systems}}, pages = {{1--34}}, publisher = {{Informa UK Limited}}, title = {{{Designing digital actor engagement platforms for local high streets: an action design research study}}}, doi = {{10.1080/0960085x.2023.2242847}}, year = {{2023}}, } @techreport{47107, author = {{Beverungen, Daniel and zur Heiden, Philipp and Lehrer, Christiane and Trier, Matthias and Bartelheimer, Christian and Bradt, Tobias and Distel, Bettina and Drews, Paul and Ehmke, Jan Fabian and Fill, Hans-Georg and Flath, Christoph M. and Fridgen, Gilbert and Grisold, Thomas and Janiesch, Christian and Janson, Andreas and Krancher, Oliver and Krönung, Julia and Kundisch, Dennis and Márton, Attila and Mirbabaie, Milad and Morana, Stefan and Mueller, Benjamin and Müller, Oliver and Oberländer, Anna Maria and Peters, Christoph and Peukert, Christoph and Reuter-Oppermann, Melanie and Riehle, Dennis M. and Robra-Bissantz, Susanne and Röglinger, Maximilian and Rosenthal, Kristina and Schryen, Guido and Schütte, Reinhard and Strahringer, Susanne and Urbach, Nils and Wessel, Lauri and Zavolokina, Liudmila and Zschech, Patrick}}, pages = {{16}}, publisher = {{Department of Information Systems, Paderborn University}}, title = {{{Implementing Digital Responsibility through Information Systems Research: A Delphi Study of Objectives, Activities, and Challenges in IS Research}}}, year = {{2023}}, } @inproceedings{29146, author = {{zur Heiden, Philipp and Priefer, Jennifer and Beverungen, Daniel}}, booktitle = {{Proceedings of the 55th Hawaii International Conference on System Sciences}}, editor = {{Bui, Tung X.}}, isbn = {{978-0-9981331-5-7}}, location = {{Honolulu, HI}}, title = {{{Utilizing Geographic Information Systems for Condition-Based Maintenance on the Energy Distribution Grid}}}, year = {{2022}}, } @inproceedings{29147, author = {{Herwix, Alexander and zur Heiden, Philipp}}, booktitle = {{Proceedings of the 55th Hawaii International Conference on System Sciences}}, editor = {{Bui, Tung X.}}, isbn = {{978-0-9981331-5-7}}, location = {{Honolulu, HI}}, title = {{{Context in Design Science Research: Taxonomy and Framework}}}, year = {{2022}}, } @inproceedings{29148, author = {{zur Heiden, Philipp and Beverungen, Daniel}}, booktitle = {{Proceedings of the 55th Hawaii International Conference on System Sciences}}, editor = {{Bui, Tung X.}}, isbn = {{978-0-9981331-5-7}}, location = {{Honolulu, HI}}, title = {{{A Renaissance of Context in Design Science Research}}}, year = {{2022}}, } @misc{30737, author = {{Schulz, Michael and Neuhaus, Uwe and Kaufmann, Jens and Kühnel, Stephan and Alekozai, Emal M. and Rohde, Heiko and Hoseini, Sayed and Theuerkauf, René and Badura, Daniel and Kerzel, Ulrich and Lanquillon, Carsten and Daurer, Stephan and Günther, Maik and Huber, Lukas and Thiée, Lukas-Walter and zur Heiden, Philipp and Passlick, Jens and Dieckmann, Jonas and Schwade, Florian and Seyffarth, Tobias and Badewitz, Wolfgang and Rissler, Raphael and Sackmann, Stefan and Gölzer, Philipp and Welter, Felix and Röth, Jochen and Seidelmann, Julian and Haneke, Uwe}}, publisher = {{NORDAKADEMIE gAG Hochschule der Wirtschaft}}, title = {{{DASC-PM v1.1 - Ein Vorgehensmodell für Data-Science-Projekte}}}, year = {{2022}}, } @inbook{32363, author = {{zur Heiden, Philipp and Priefer, Jennifer and Beverungen, Daniel}}, booktitle = {{Forum Dienstleistungsmanagement}}, editor = {{Bruhn, Manfred and Hadwich, Karsten}}, isbn = {{9783658373436}}, issn = {{2662-3382}}, pages = {{435--457}}, publisher = {{Springer Fachmedien Wiesbaden}}, title = {{{Smart Service für die prädiktive Instandhaltung zentraler Komponenten des Mittelspannungs-Netzes}}}, doi = {{10.1007/978-3-658-37344-3_14}}, year = {{2022}}, } @article{35732, abstract = {{AbstractWhile 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}}, number = {{1}}, pages = {{375--396}}, 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}}, volume = {{32}}, year = {{2022}}, } @inproceedings{24534, author = {{zur Heiden, Philipp and Priefer, Jennifer}}, booktitle = {{Pre-Conference 16th International Congress on Wirtschaftsinformatik at Universität Duisburg-Essen}}, editor = {{Breitner, Michael H. and Lehnhoff, Sebastian and Nieße, Astrid and Staudt, Philipp and Weinhardt, Christof and Werth, Oliver}}, location = {{Universität Duisburg-Essen}}, publisher = {{BIS-Verlag der Carl von Ossietzky Universität Oldenburg}}, title = {{{Transitioning to Condition-Based Maintenance on the Distribution Grid: Deriving Design Principles from a Qualitative Study}}}, year = {{2021}}, } @inproceedings{21263, author = {{zur Heiden, Philipp and Winter, Daniel}}, booktitle = {{Proceedings of the 16th International Conference on Wirtschaftsinformatik}}, title = {{{Discovering Geographical Patterns of Retailers' Locations for Successful Retail in City Centers}}}, year = {{2021}}, } @article{17426, abstract = {{The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.}}, author = {{Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and Stich, Volker and Hicking, Jan and Bremer, Martin and Kaminski, Lars and Beverungen, Daniel and zur Heiden, Philipp and Tornede, Tanja}}, issn = {{1424-8220}}, journal = {{Sensors}}, title = {{{Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions}}}, doi = {{10.3390/s20072099}}, year = {{2020}}, } @inproceedings{17087, author = {{Berendes, Carsten Ingo and zur Heiden, Philipp and Niemann, Marco and Hoffmeister, Benedikt and Becker, Jörg}}, booktitle = {{Proceedings of the Twenty-Eighth European Conference on Information Systems (ECIS2020)}}, location = {{Virtual Conference}}, title = {{{Usage of Local Online Platforms in Retail: Insights from retailers' expectations expectations}}}, year = {{2020}}, } @inproceedings{16285, abstract = {{To decide in which part of town to open stores, high street retailers consult statistical data on customers and cities, but they cannot analyze their customers’ shopping behavior and geospatial features of a city due to missing data. While previous research has proposed recommendation systems and decision aids that address this type of decision problem – including factory location and assortment planning – there currently is no design knowledge available to prescribe the design of city center area recommendation systems (CCARS). We set out to design a software prototype considering local customers’ shopping interests and geospatial data on their shopping trips for retail site selection. With real data on 500 customers and 1,100 shopping trips, we demonstrate and evaluate our IT artifact. Our results illustrate how retailers and public town center managers can use CCARS for spatial location selection, growing retailers’ profits and a city center’s attractiveness for its citizens.}}, author = {{zur Heiden, Philipp and Berendes, Carsten Ingo and Beverungen, Daniel}}, booktitle = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}}, keywords = {{Town Center Management, High Street Retail, Recommender Systems, Geospatial Recommendations, Design Science Research}}, location = {{Potsdam}}, title = {{{Designing City Center Area Recommendation Systems }}}, doi = {{doi.org/10.30844/wi_2020_e1-heiden}}, year = {{2020}}, } @article{35723, abstract = {{The development of renewable energies and smart mobility has profoundly impacted the future of the distribution grid. An increasing bidirectional energy flow stresses the assets of the distribution grid, especially medium voltage switchgear. This calls for improved maintenance strategies to prevent critical failures. Predictive maintenance, a maintenance strategy relying on current condition data of assets, serves as a guideline. Novel sensors covering thermal, mechanical, and partial discharge aspects of switchgear, enable continuous condition monitoring of some of the most critical assets of the distribution grid. Combined with machine learning algorithms, the demands put on the distribution grid by the energy and mobility revolutions can be handled. In this paper, we review the current state-of-the-art of all aspects of condition monitoring for medium voltage switchgear. Furthermore, we present an approach to develop a predictive maintenance system based on novel sensors and machine learning. We show how the existing medium voltage grid infrastructure can adapt these new needs on an economic scale.}}, author = {{Hoffmann, Martin W. and Wildermuth, Stephan and Gitzel, Ralf and Boyaci, Aydin and Gebhardt, Jörg and Kaul, Holger and Amihai, Ido and Forg, Bodo and Suriyah, Michael and Leibfried, Thomas and Stich, Volker and Hicking, Jan and Bremer, Martin and Kaminski, Lars and Beverungen, Daniel and zur Heiden, Philipp and Tornede, Tanja}}, issn = {{1424-8220}}, journal = {{Sensors}}, keywords = {{Electrical and Electronic Engineering, Biochemistry, Instrumentation, Atomic and Molecular Physics, and Optics, Analytical Chemistry}}, number = {{7}}, publisher = {{MDPI AG}}, title = {{{Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions}}}, doi = {{10.3390/s20072099}}, volume = {{20}}, year = {{2020}}, }