@inproceedings{3279, author = {{Bartelheimer, Christian and Hendrik Betzing, Jan and Berendes, Ingo and Beverungen, Daniel}}, booktitle = {{Proceedings of the 26th European Conference on Information Systems}}, location = {{Portsmouth, UK}}, title = {{{Designing Multi-sided Community Platforms for Local High Street Retail}}}, year = {{2018}}, } @inproceedings{3280, author = {{Hendrik Betzing, Jan and Beverungen, Daniel and Becker, Jörg}}, booktitle = {{Tagungsband Data driven X --- Turning Data into Value --- Band V}}, editor = {{Drews, Paul and Funk, Burkhardt and Niemeyer, Peter and Xie, Lin}}, pages = {{2083----2094}}, title = {{{Design Principles for Co-Creating Digital Customer Experience in High Street Retail}}}, year = {{2018}}, } @article{4516, author = {{Beverungen, Daniel and Lüttenberg, Hedda and Wolf, Verena}}, issn = {{2363-7005}}, journal = {{Business & Information Systems Engineering}}, number = {{5}}, pages = {{377--391}}, publisher = {{Springer Nature America, Inc}}, title = {{{Recombinant Service Systems Engineering}}}, doi = {{10.1007/s12599-018-0526-4}}, volume = {{60}}, 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}}, } @inproceedings{4766, author = {{Ingo Berendes, C. and Bartelheimer, Christian and Hendrik Betzing, Jan and Beverungen, Daniel}}, booktitle = {{Proceedings of the 39th International Conference on Information Systems}}, location = {{San Francisco USA}}, title = {{{Data-driven Customer Journey Mapping in Local High Streets: A Domain-specific Modeling Language}}}, year = {{2018}}, } @misc{9687, author = {{Beverungen, Daniel and Wolf, Verena and Bartelheimer, Christian}}, booktitle = {{Service Business Development. spot.on marketing - Der Newsletter für Marketing und Business Development}}, title = {{{Dienstleistungssysteme erfolgreich digital transformieren}}}, year = {{2018}}, } @inproceedings{9709, author = {{Gernreich, Chris and Wolf, Verena and Bartelheimer, Christian and Prinz, Christopher}}, booktitle = {{Proceedings of the 39th International Conference on Information Systems}}, location = {{San Francisco, USA}}, title = {{{The Impact of Process Automation on Manufacturers’ Long-Term Knowledge}}}, year = {{2018}}, } @inbook{5073, author = {{Beverungen, Daniel and Wolf, Verena and Bartelheimer, Christian}}, booktitle = {{Service Business Development}}, isbn = {{9783658224233}}, pages = {{395--422}}, publisher = {{Springer Fachmedien Wiesbaden}}, title = {{{Digitale Transformation von Dienstleistungssystemen}}}, doi = {{10.1007/978-3-658-22424-0_17}}, year = {{2018}}, } @article{2856, abstract = {{Taxi ridesharing1 (TRS) is an advanced form of urban transportation that matches separate ride requests with similar spatio-temporal characteristics to a jointly used taxi. As collaborative consumption, TRS saves customers money, enables taxi companies to economize use of their resources, and lowers greenhouse gas emissions. We develop a one-to-one TRS approach that matches rides with similar start and end points. We evaluate our approach by analyzing an open dataset of > 5 million taxi trajectories in New York City. Our empirical analysis reveals that the proposed approach matches up to 48.34% of all taxi rides, saving 2,892,036 km of travel distance, 231,362.89 l of gas, and 532,134.64 kg of CO2 emissions per week. Compared to many-to-many TRS approaches, our approach is competitive, simpler to implement and operate, and poses less rigid assumptions on data availability and customer acceptance.}}, author = {{Barann, Benjamin and Beverungen, Daniel and Müller, Oliver}}, journal = {{Decision Support Systems}}, keywords = {{Taxi ridesharing Collaborative consumption Transportation Open data Sustainability Shared mobility}}, pages = {{86----95}}, title = {{{An open-data approach for quantifying the potential of taxi ridesharing}}}, doi = {{10.1016/j.dss.2017.05.008}}, year = {{2017}}, } @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}}, }