@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}}, } @article{17156, author = {{Beverungen, Daniel and Buijs, Joos C. A. M. and Becker, Jörg and Di Ciccio, Claudio and van der Aalst, Wil M. P. and Bartelheimer, Christian and vom Brocke, Jan and Comuzzi, Marco and Kraume, Karsten and Leopold, Henrik and Matzner, Martin and Mendling, Jan and Ogonek, Nadine and Post, Till and Resinas, Manuel and Revoredo, Kate and del-Río-Ortega, Adela and La Rosa, Marcello and Santoro, Flávia Maria and Solti, Andreas and Song, Minseok and Stein, Armin and Stierle, Matthias and Wolf, Verena}}, issn = {{2363-7005}}, journal = {{Business & Information Systems Engineering}}, title = {{{Seven Paradoxes of Business Process Management in a Hyper-Connected World}}}, doi = {{10.1007/s12599-020-00646-z}}, 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}}, } @inproceedings{4517, author = {{Wolf, Verena and Bartelheimer, Christian and Beverungen, Daniel}}, booktitle = {{Proceedings of the 52nd Hawaii International Conference on System Sciences (HICSS-52)}}, location = {{Maui, Hawaii}}, title = {{{Digitalization of Work Systems—An Organizational Routines’ Perspective}}}, year = {{2019}}, } @inproceedings{9617, author = {{Betzing, Jan H. and Bartelheimer, Christian and Niemann, Marco and Berendes, Carsten Ingo and Beverungen, Daniel}}, booktitle = {{Proceedings of the 27th European Conference on Information Systems (ECIS)}}, location = {{Stockholm}}, title = {{{Quantifying the Impact of Geospatial Recommendations: A Field Experiment in High Street Retail}}}, year = {{2019}}, } @inproceedings{9708, abstract = {{Increased interconnectedness of multiple actors and digital resources in service eco-systems offer new opportunities for service innovation. In digitally transforming eco-systems, organizations need to explore and exploit innovation simultaneously, which is defined as ambidexterity. However, research on ambidextrous service innovation is scarce. We provide a systematic literature review based on the concepts of ambidexterity, offering two contributions. First, research strands are disconnected, emphasizing either exploration or exploitation of service innovation, despite an organizations’ need to accelerate innovation cycles of exploring and exploiting services. Second, a new framework for ambidextrous service innovation is provided, inspired by the dynamism and generative mechanisms of the ontologically related concept of organizational routines. The framework adopts the perspective of a mutually constitutive relationship between exploring new and exploiting current resources, activities, and knowledge. The findings remedy the scattered literature through a coherent perspective on service innovation that responds to organizations’ needs and guides future research.}}, author = {{Wolf, Verena}}, booktitle = {{Proceedings of the 14th International Conference on Wirtschaftsinformatik}}, keywords = {{Exploration, Exploitation, Service Innovation, Organizational Routines, Ambidexterity}}, location = {{Siegen, Germany}}, title = {{{Ambidexterity in Service Innovation Research: A Systematic Literature Review}}}, year = {{2019}}, } @article{12929, author = {{Bräuer, Sebastian and Plenter, Florian and Klör, Benjamin and Monhof, Markus and Beverungen, Daniel and Becker, Jörg}}, issn = {{2198-3402}}, journal = {{Business Research}}, title = {{{Transactions for trading used electric vehicle batteries: theoretical underpinning and information systems design principles}}}, doi = {{10.1007/s40685-019-0091-9}}, year = {{2019}}, } @article{14023, author = {{Beverungen, Daniel and Breidbach, Christoph F. and Poeppelbuss, Jens and Tuunainen, Virpi Kristiina}}, issn = {{1350-1917}}, journal = {{Information Systems Journal}}, title = {{{Smart service systems: An interdisciplinary perspective}}}, doi = {{10.1111/isj.12275}}, 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}}, } @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}}, } @inproceedings{3282, author = {{Klör, Benjamin and Monhof, Markus and Bräuer, Sebastian and Beverungen, Daniel}}, booktitle = {{Proceedings of the 19th IEEE Conference on Business Informatics (CBI 2017)}}, location = {{Thessaloniki, Greece}}, title = {{{Recommendation and Configuration of Value-Added Services for Repurposing Electric Vehicle Batteries: A Vertical Software Prototype}}}, year = {{2017}}, } @article{3487, author = {{Hendrik Betzing, Jan and Beverungen, Daniel and Becker, Jörg and Matzner, Martin and Schmitz, Gertrud and Bartelheimer, Christian and Berendes, Carsten Ingo and Braun, Marina and Gadeib, Andera and Hoffen}, Moritz {von and Schallenberg, Christian}}, journal = {{HMD Praxis der Wirtschaftsinformatik}}, number = {{5}}, pages = {{659----671}}, title = {{{Interaktive, digitale Einkaufserlebnisse in Innenstädten}}}, doi = {{10.1365/s40702-017-0343-0}}, year = {{2017}}, } @article{3488, author = {{Beverungen, Daniel and Bräuer, Sebastian and Plenter, Florian and Klör, Benjamin and Monhof, Markus}}, journal = {{Computer Science --- Research and Development}}, number = {{1-2}}, pages = {{195----209}}, title = {{{Ensembles of Context and Form for Repurposing Electric Vehicle Batteries: An Exploratory Study}}}, doi = {{10.1007/s00450-016-0306-7}}, year = {{2017}}, } @article{3490, abstract = {{Digital interactions among businesses and consumers through powerful information systems and omnipresent connected devices establish today’s networked society. In this light, Service Science continues to take root as a research discipline that focuses on the integration of (digital) resources by service providers and service customers for value co-creation in service systems. Rapid advances in information technology allow for designing novel information systems that enable entirely new configurations of service systems. In turn, Service Science also leaves its mark on the design, adoption, and use of information systems and technology. With this special issue, we compile a set of timely papers that investigate selected facets of the complex interplay between information technology, information systems, and Service Science to design innovative IT artifacts for smart service. This editorial opens this special issue by elaborating on our understanding of smart service.