zur Heiden, Philipp, et al. “Predictive Maintenance on the Energy Distribution Grid—Design and Evaluation of a Digital Industrial Platform in the Context of a Smart Service System.”10.1109/tem.2024.3352819__IEEE Transactions on Engineering Management, vol. 71, Institute of Electrical and Electronics Engineers (IEEE), 2024, pp. 3641–55, doi:10.1109/tem.2024.3352819.

zur Heiden, Philipp, et al. “Location-Based Service and Location-Contextualizing Service: Conceptualizing the Co-Creation of Value with Location Information.” Proceedings of the 56th Conference on System Sciences, 2023.

Priefer, Jennifer. “Geographic Information Systems in Information Systems Research - Review and Research Prospects.” Proceedings of the 56th Hawaii International Conference on System Sciences, edited by T.X. Bui and R.H. Sprague, 2023.

zur Heiden, Philipp, et al. “Utilizing Geographic Information Systems for Condition-Based Maintenance on the Energy Distribution Grid.” Proceedings of the 55th Hawaii International Conference on System Sciences, edited by Tung X. Bui, 2022.

Priefer, Jennifer, and Lennart Steiger. “Designing a GIS-AHP-Based Spatial Decision Support System for Discovering and Visualizing Suitable Locations for Electric Vehicle Charging Stations.” Wirtschaftsinformatik 2022 Proceedings, vol. 31, 2022.

zur Heiden, Philipp, et al. “Smart Service für die prädiktive Instandhaltung zentraler Komponenten des Mittelspannungs-Netzes.”10.1007/978-3-658-37344-3_14__Forum Dienstleistungsmanagement, edited by Manfred Bruhn and Karsten Hadwich, Springer Fachmedien Wiesbaden, 2022, pp. 435–57, doi:10.1007/978-3-658-37344-3_14.

zur Heiden, Philipp, and Jennifer Priefer. “Transitioning to Condition-Based Maintenance on the Distribution Grid: Deriving Design Principles from a Qualitative Study.” Pre-Conference 16th International Congress on Wirtschaftsinformatik at Universität Duisburg-Essen, edited by Michael H. Breitner et al., BIS-Verlag der Carl von Ossietzky Universität Oldenburg, 2021.

Kucklick, Jan-Peter, et al. “Quantifying the Impact of Location Data for Real Estate Appraisal – A GIS-Based Deep Learning Approach.” European Conference on Information Systems, 2021.