@article{45112,
  author       = {{Beverungen, Daniel and Kundisch, Dennis and Mirbabaie, Milad and Müller, Oliver and Schryen, Guido and Trang, Simon Thanh-Nam and Trier, Matthias}},
  journal      = {{Business & Information Systems Engineering}},
  number       = {{4}},
  pages        = {{463 -- 474}},
  title        = {{{Digital Responsibility – a Multilevel Framework for Responsible Digitalization}}},
  doi          = {{10.1007/s12599-023-00822-x}},
  volume       = {{65}},
  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}},
}

@article{35740,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>While 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.</jats:p>}},
  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}},
}

@article{35741,
  abstract     = {{<jats:title>Abstract</jats:title><jats:p>Business process management (BPM) drives corporate success through effective and efficient processes. In recent decades, knowledge has been accumulated regarding the identification, discovery, analysis, design, implementation, and monitoring of business processes. This includes methods and tools for tackling various kinds of process change such as continuous process improvement, process reengineering, process innovation, and process drift. However, exogenous shocks, which lead to unintentional and radical process change, have been neglected in BPM research although they severely affect an organization’s context, strategy, and business processes. This research note conceptualizes the interplay of exogenous shocks and BPM in terms of the effects that such shocks can have on organizations’ overall process performance over time. On this foundation, related challenges and opportunities for BPM via several rounds of idea generation and consolidation within a diverse team of BPM scholars are identified. The paper discusses findings in light of extant literature from BPM and related disciplines, as well as present avenues for future (BPM) research to invigorate the academic discourse on the topic.</jats:p>}},
  author       = {{Röglinger, Maximilian and Plattfaut, Ralf and Borghoff, Vincent and Kerpedzhiev, Georgi and Becker, Jörg and Beverungen, Daniel and vom Brocke, Jan and Van Looy, Amy and del-Río-Ortega, Adela and Rinderle-Ma, Stefanie and Rosemann, Michael and Santoro, Flavia Maria and Trkman, Peter}},
  issn         = {{2363-7005}},
  journal      = {{Business & Information Systems Engineering}},
  keywords     = {{Information Systems, Business process management, Exogenous shocks, Challenges, Opportunities}},
  number       = {{5}},
  pages        = {{669--687}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{Exogenous Shocks and Business Process Management}}},
  doi          = {{10.1007/s12599-021-00740-w}},
  volume       = {{64}},
  year         = {{2022}},
}

@article{35728,
  abstract     = {{Technological developments such as Cloud Computing, the Internet of Things, Big Data and Artificial Intelligence continue to drive the digital transformation of business and society. With the advent of platform-based ecosystems and their potential to address complex challenges, there is a trend towards greater interconnectedness between different stakeholders to co-create services based on the provision and use of data. While previous research on digital transformation mainly focused on digital transformation within organizations, it is of growing importance to understand the implications for digital transformation on different layers (e.g., interorganizational cooperation and platform ecosystems). In particular, the conceptualization and implications of public data spaces and related ecosystems provide promising research opportunities. This special issue contains five papers on the topic of digital transformation and, with the editorial, further contributes by providing an initial conceptualization of public data spaces' potential to foster innovative progress and digital transformation from a management perspective.}},
  author       = {{Beverungen, Daniel and Hess, Thomas and Köster, Antonia and Lehrer, Christiane}},
  issn         = {{1019-6781}},
  journal      = {{Electronic Markets}},
  keywords     = {{Digital transformation, Public data spaces, Digital platforms, GAIA-X}},
  pages        = {{493--501}},
  publisher    = {{Springer Science and Business Media LLC}},
  title        = {{{From private digital platforms to public data spaces: implications for the digital transformation}}},
  doi          = {{10.1007/s12525-022-00553-z}},
  volume       = {{32}},
  year         = {{2022}},
}

@article{35732,
  abstract     = {{While 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     = {{Platform, Text mining, Machine learning, Data communications, Interpretive research, Systems design and implementation}},
  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{22514,
  author       = {{Kucklick, Jan-Peter and Müller, Jennifer and Beverungen, Daniel and Müller, Oliver}},
  booktitle    = {{European Conference on Information Systems}},
  location     = {{Virtual}},
  title        = {{{Quantifying the Impact of Location Data for Real Estate Appraisal – A GIS-based Deep Learning Approach}}},
  year         = {{2021}},
}

@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     = {{<jats:p>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.</jats:p>}},
  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}},
}

@article{17156,
  abstract     = {{Business Process Management is a boundary-spanning discipline that aligns operational capabilities and technology to design and manage business processes. The Digital Transformation has enabled human actors, information systems, and smart products to interact with each other via multiple digital channels. The emergence of this hyper-connected world greatly leverages the prospects of business processes – but also boosts their complexity to a new level. We need to discuss how the BPM discipline can find new ways for identifying, analyzing, designing, implementing, executing, and monitoring business processes. In this research note, selected transformative trends are explored and their impact on current theories and IT artifacts in the BPM discipline is discussed to stimulate transformative thinking and prospective research in this field.}},
  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}},
  keywords     = {{Business process management (BPM), Social computing, Smart devices, Big data analytics, Real-time computing, BPM life-cycle}},
  pages        = {{145--156}},
  publisher    = {{SpringerNature}},
  title        = {{{Seven Paradoxes of Business Process Management in a Hyper-Connected World}}},
  doi          = {{10.1007/s12599-020-00646-z}},
  volume       = {{63}},
  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}},
}