@inproceedings{44855, abstract = {{Market transactions are subject to information asymmetry about the delivered value proposition, causing transaction costs and adverse market effects among buyers and sellers. Information systems research has investigated how review systems can reduce information asymmetry in business-to-consumer markets. However, these systems cannot be readily applied to business-to-business markets, are vulnerable to manipulation, and suffer from conceptual weak spots since they use textual data or star ratings. Building on design science research, we conceptualize a new class of reputation systems based on monetary-based payments as quantitative ratings for each transaction stored on a blockchain. Using cryptography, we show that our system assures content confidentiality so that buyers can share and sell their ratings selectively, establishing a reputation ecosystem. Our prescriptive insights advance the design of reputation systems and offer new paths to understanding the antecedents, dynamics, and consequences to reduce information asymmetry in B2B transactions.}}, author = {{Hemmrich, Simon and Bobolz, Jan and Beverungen, Daniel and Blömer, Johannes}}, booktitle = {{ECIS 2023 Research Papers}}, title = {{{Designing Business Reputation Ecosystems — A Method for Issuing and Trading Monetary Ratings on a Blockchain}}}, year = {{2023}}, } @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 = {{https://doi.org/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{35728, abstract = {{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 = {{Management of Technology and Innovation, Marketing, Computer Science Applications, Economics and Econometrics, Business and International Management}}, number = {{2}}, 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 = {{AbstractWhile 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}}, 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 = {{AbstractBusiness 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.}}, 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}}, 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{35740, abstract = {{AbstractWhile 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}}, 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}}, } @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}}, }