@article{30735,
  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     = {{Management of Technology and Innovation, Marketing, Computer Science Applications, Economics and Econometrics, Business and International Management}},
  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}},
  year         = {{2022}},
}

@article{21242,
  author       = {{Lüttenberg, Hedda and Beverungen, Daniel and Poniatowski, Martin and Kundisch, Dennis and Wünderlich, Nancy}},
  journal      = {{Wirtschaftsinformatik & Management}},
  number       = {{2}},
  pages        = {{120--131}},
  title        = {{{Drei Strategien zur Etablierung digitaler Plattformen in der Industrie}}},
  volume       = {{13}},
  year         = {{2021}},
}

@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}},
}

@article{17860,
  abstract     = {{Purpose
The purpose of this paper is to identify strategic options and challenges that arise when an industrial firm moves from providing smart service toward providing a platform.

Design/methodology/approach
This conceptual study takes on a multidisciplinary research perspective that integrates concepts, theories and insights from service management and marketing, information systems and platform economics.

Findings
The paper outlines three platform types – smart data platform, smart product platform and matching platform – as strategic options for firms that wish to evolve from smart service providers to platform providers.

Research limitations/implications
Investigating smart service platforms calls for launching interdisciplinary research initiatives. Promising research avenues are outlined to span boundaries that separate different research disciplines today.

Practical implications
Managing a successful transition from providing smart service toward providing a platform requires making significant investments in IT, platform-related capabilities and skills, as well as implement new approaches toward relationship management and brand-building.

Originality/value
The findings described in this paper are valuable to researchers in multiple disciplines seeking to develop and to justify theory related to platforms in industrial scenarios.}},
  author       = {{Beverungen, Daniel and Kundisch, Dennis and Wünderlich, Nancy}},
  issn         = {{507-532}},
  journal      = {{Journal of Service Management}},
  keywords     = {{Smart service, Platform, Interdisciplinary research, Manufacturing company, Smart service provider, Platform economics, Information systems, Multi-sided markets, Business-to-business (B2B) markets}},
  number       = {{4}},
  pages        = {{507--532}},
  publisher    = {{Emerald Insight}},
  title        = {{{Transforming into a Platform Provider: Strategic Options for Industrial Smart Service Providers}}},
  doi          = {{10.1108/JOSM-03-2020-0066}},
  volume       = {{32}},
  year         = {{2021}},
}

@techreport{20131,
  author       = {{Kundisch, Dennis and Beverungen, Daniel}},
  pages        = {{22--26}},
  title        = {{{Als Wirtschaftsinformatiker die digitale Transformation in Organisationen gestalten}}},
  year         = {{2020}},
}

@article{17426,
  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}},
  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}},
  year         = {{2020}},
}

@inproceedings{16947,
  author       = {{Weinzierl, Sven and Wolf, Verena and Pauli, Tobias and Beverungen, Daniel and Matzner, Martin}},
  booktitle    = {{Proceedings of the 28th European Conference on Information Systems}},
  location     = {{Marrakech, Morroco}},
  title        = {{{Detecting Workarounds in Business Processes — A Deep Learning Method for Analyzing Event Logs}}},
  year         = {{2020}},
}

@inproceedings{15501,
  author       = {{Wolf, Verena and Franke, Alena and Bartelheimer, Christian and Beverungen, Daniel}},
  booktitle    = {{Proceedings of the 15th International Conference on Wirtschaftsinformatik}},
  title        = {{{Establishing Smart Service Systems is a Challenge: A Case Study on Pitfalls and Implications}}},
  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}},
}

@techreport{7622,
  author       = {{Kundisch, Dennis and Beverungen, Daniel}},
  pages        = {{22--26}},
  title        = {{{Als Wirtschaftsinformatiker die digitale Transformation in Organisationen gestalten}}},
  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{9676,
  abstract     = {{Employees’ acceptance and resistance of new technology and social structure are frequently examined in Information Systems research. Resistance is expressed in various forms, including a lack of cooperation, workarounds, and physical sabotage. Workarounds, in particular, have a dual nature and can refer to both, undesirable behavior that contradicts organizational struc-ture and to desired organizational innovation. While antecedents and different forms of worka-rounds have been explored, literature has remained silent on how and why workarounds of an individual employee can affect activities performed by other employees and thereby, change work routines on an organizational level. Since employees’ day-to-day performances constitute the ostensive patterns of a routine, we argue that workarounds will not only impact performanc-es of adjacent routines, but also transform the organization as a social structure. With a prelim-inary set of qualitative data from 24 interviews, we used a multiple case study design to concep-tualize six patterns that illustrate how and why workarounds can spread through an organiza-tion. The patterns are systematized by a framework that considers three types of collaboration and two types of handoffs across routines. This first evidence points at the nature of complex desired and undesired consequences that can emerge through workarounds performed in an organization.}},
  author       = {{Wolf, Verena and Beverungen, Daniel}},
  booktitle    = {{Proceedings of the 27th European Conference on Information Systems (ECIS)}},
  keywords     = {{Resistance, Workaround, Organizational Routines, Structuration Theory}},
  location     = {{Stockholm-Uppsala, Sweden}},
  title        = {{{Conceptualizing the Impact of Workarounds – An Organizational Routines’ Perspective}}},
  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}},
}

@inbook{13178,
  author       = {{Beverungen, Daniel and Bartelheimer, Christian and Wolf, Verena}},
  booktitle    = {{Digitale Dienstleistungsinnovationen – Smart Services agil und kundenorientiert entwickeln}},
  isbn         = {{978-3-662-59516-9}},
  publisher    = {{SpringerVieweg}},
  title        = {{{Smart Service Systems als Handlungsfeld einer konvergierenden Dienstleistungsforschung}}},
  year         = {{2019}},
}

@techreport{13181,
  author       = {{Post, Till and Heuermann, Aaron and Wiesner, Stefan and Olschewski, Detlef and Maaß, Wolfgang and Klatt, Rüdiger and Jussen, Philipp and Ragab, Sherif and Senderek, Roman and Höckmayr, Benedikt and Schulz, Thomas and Meyer, Kyrill and Heinen, Ewald and Hocken, Christian and Fischer, Simon and Lattemann, Christoph and Redlich, Beke and Schlimm, Katrin and Ziegler, Christoph and Rechtien, Christopher and Schröder, Markus and Kube, Bernhard and Pöppelbuß, Jens and Wiesche, Manuel and Semmann, Martin and Bartelheimer, Christian and Beverungen, Daniel and Lüttenberg, Hedda and Wolf, Verena and Bongers, Franziska and Winkler, Corinna and Schumann, Jan Hendrik and Li, Mahei and Brinker, Jonas and Hagen, Simon and Kammler, Friedemann and Strina, Giuseppe and Ernst, Philipp and Falkus, Michael}},
  title        = {{{DIN SPEC 33453:2019-09, Entwicklung digitaler Dienstleistungssysteme}}},
  doi          = {{10.31030/3085072}},
  year         = {{2019}},
}

@article{4684,
  abstract     = {{Recent years have seen the emergence of physical products that are digitally networked with other products and with information systems to enable complex business scenarios in manufacturing, mobility, or healthcare. These “smart products”, which enable the co-creation of “smart service” that is based on monitoring, optimization, remote control, and autonomous adaptation of products, profoundly transform service systems into what we call “smart service systems”. In a multi-method study that includes conceptual research and qualitative data from in-depth interviews, we conceptualize “smart service” and “smart service systems” based on using smart products as boundary objects that integrate service consumers’ and service providers’ resources and activities. Smart products allow both actors to retrieve and to analyze aggregated field evidence and to adapt service systems based on contextual data. We discuss the implications that the introduction of smart service systems have for foundational concepts of service science and conclude that smart service systems are characterized by technology-mediated, continuous, and routinized interactions.}},
  author       = {{Beverungen, Daniel and Müller, Oliver and Matzner, Martin and Mendling, Jan and vom Brocke, Jan}},
  issn         = {{14228890}},
  journal      = {{Electronic Markets}},
  keywords     = {{Boundary object, Internet of things, Service science, Smart products, Smart service}},
  pages        = {{7--18}},
  publisher    = {{SpringerNature}},
  title        = {{{Conceptualizing smart service systems}}},
  doi          = {{10.1007/s12525-017-0270-5}},
  volume       = {{29}},
  year         = {{2019}},
}