TY - CONF AU - Berendes, Carsten Ingo AU - zur Heiden, Philipp AU - Niemann, Marco AU - Hoffmeister, Benedikt AU - Becker, Jörg ID - 17087 T2 - Proceedings of the Twenty-Eighth European Conference on Information Systems (ECIS2020) TI - Usage of Local Online Platforms in Retail: Insights from retailers' expectations expectations ER - TY - JOUR AU - Beverungen, Daniel AU - Buijs, Joos C. A. M. AU - Becker, Jörg AU - Di Ciccio, Claudio AU - van der Aalst, Wil M. P. AU - Bartelheimer, Christian AU - vom Brocke, Jan AU - Comuzzi, Marco AU - Kraume, Karsten AU - Leopold, Henrik AU - Matzner, Martin AU - Mendling, Jan AU - Ogonek, Nadine AU - Post, Till AU - Resinas, Manuel AU - Revoredo, Kate AU - del-Río-Ortega, Adela AU - La Rosa, Marcello AU - Santoro, Flávia Maria AU - Solti, Andreas AU - Song, Minseok AU - Stein, Armin AU - Stierle, Matthias AU - Wolf, Verena ID - 17156 JF - Business & Information Systems Engineering SN - 2363-7005 TI - Seven Paradoxes of Business Process Management in a Hyper-Connected World ER - TY - CONF AB - 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. AU - zur Heiden, Philipp AU - Berendes, Carsten Ingo AU - Beverungen, Daniel ID - 16285 KW - Town Center Management KW - High Street Retail KW - Recommender Systems KW - Geospatial Recommendations KW - Design Science Research T2 - Proceedings of the 15th International Conference on Wirtschaftsinformatik TI - Designing City Center Area Recommendation Systems ER - TY - JOUR AB - 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. AU - Hoffmann, Martin W. AU - Wildermuth, Stephan AU - Gitzel, Ralf AU - Boyaci, Aydin AU - Gebhardt, Jörg AU - Kaul, Holger AU - Amihai, Ido AU - Forg, Bodo AU - Suriyah, Michael AU - Leibfried, Thomas AU - Stich, Volker AU - Hicking, Jan AU - Bremer, Martin AU - Kaminski, Lars AU - Beverungen, Daniel AU - zur Heiden, Philipp AU - Tornede, Tanja ID - 35723 IS - 7 JF - Sensors KW - Electrical and Electronic Engineering KW - Biochemistry KW - Instrumentation KW - Atomic and Molecular Physics KW - and Optics KW - Analytical Chemistry SN - 1424-8220 TI - Integration of Novel Sensors and Machine Learning for Predictive Maintenance in Medium Voltage Switchgear to Enable the Energy and Mobility Revolutions VL - 20 ER - TY - CONF AU - Wolf, Verena AU - Bartelheimer, Christian AU - Beverungen, Daniel ID - 4517 T2 - Proceedings of the 52nd Hawaii International Conference on System Sciences (HICSS-52) TI - Digitalization of Work Systems—An Organizational Routines’ Perspective ER - TY - CONF AU - Betzing, Jan H. AU - Bartelheimer, Christian AU - Niemann, Marco AU - Berendes, Carsten Ingo AU - Beverungen, Daniel ID - 9617 T2 - Proceedings of the 27th European Conference on Information Systems (ECIS) TI - Quantifying the Impact of Geospatial Recommendations: A Field Experiment in High Street Retail ER - TY - CONF AB - 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. AU - Wolf, Verena ID - 9708 KW - Exploration KW - Exploitation KW - Service Innovation KW - Organizational Routines KW - Ambidexterity T2 - Proceedings of the 14th International Conference on Wirtschaftsinformatik TI - Ambidexterity in Service Innovation Research: A Systematic Literature Review ER - TY - JOUR AU - Bräuer, Sebastian AU - Plenter, Florian AU - Klör, Benjamin AU - Monhof, Markus AU - Beverungen, Daniel AU - Becker, Jörg ID - 12929 JF - Business Research SN - 2198-3402 TI - Transactions for trading used electric vehicle batteries: theoretical underpinning and information systems design principles ER - TY - JOUR AU - Beverungen, Daniel AU - Breidbach, Christoph F. AU - Poeppelbuss, Jens AU - Tuunainen, Virpi Kristiina ID - 14023 JF - Information Systems Journal SN - 1350-1917 TI - Smart service systems: An interdisciplinary perspective ER - TY - CONF AB - 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. AU - Lüttenberg, Hedda AU - Bartelheimer, Christian AU - Beverungen, Daniel ID - 2861 TI - Designing Predictive Maintenance for Agricultural Machines ER -