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110 Publications


2020 | Journal Article | LibreCat-ID: 15414
G. Schryen, “Integrating Management Science into the HPC Research Ecosystem,” {Communications of the ACM}, vol. forthcoming, 2020.
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2020 | Journal Article | LibreCat-ID: 14985
G. Schryen, N. Kliewer, and A. Fink, “High Performance Business Computing,” Business & Information Systems Engineering, 2020.
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2020 | Journal Article | LibreCat-ID: 15022
G. Schryen, “Parallel computational optimization in operations research: A new integrative framework, literature review and research directions,” European Journal of Operational Research, vol. forthcoming, 2020.
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2020 | Journal Article | LibreCat-ID: 17934
G. Wagner, J. Prester, and G. Schryen, “Exploring the Scientific Impact of Information Systems Design Science Research,” Communications of the Association for Information Systems, 2020.
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2020 | Conference Paper | LibreCat-ID: 17055
G. Wagner, P. Empl, and G. Schryen, “Designing a Novel Strategy for Exploring Literature Corpora,” in 28th European Conference on Information Systems (ECIS 2020), 2020.
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2020 | Journal Article | LibreCat-ID: 11946
G. Schryen, G. Wagner, A. Benlian, and G. Paré, “A Knowledge Development Perspective on Literature Reviews: Validation of a New Typology in the IS Field,” Communications of the AIS, vol. 46, pp. 134–186, 2020.
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2020 | Journal Article | LibreCat-ID: 15513
G. Schryen, N. Kliewer, and A. Fink, “Interview with Utz-Uwe Haus on ‘High Performance Computing in Economic Environments,’” Business & Information Systems Engineering, no. 01/2020, 2020.
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2020 | Journal Article | LibreCat-ID: 16249
E. Szubartowicz and G. Schryen, “Timing in Information Security: An Event Study on the Impact of Information Security Investment Announcements,” Journal of Information System Security, 2020.
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2020 | Working Paper | LibreCat-ID: 17019
G. Schryen, G. Wagner, and A. Benlian, Distinguishing Knowledge Impact from Citation Impact: A Methodology for Analysing Knowledge Impact for the Literature Review Genre. 2020.
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2019 | Book Chapter | LibreCat-ID: 14890
S. Kuhlemann, M. Sellmann, and K. Tierney, “Exploiting Counterfactuals for Scalable Stochastic Optimization,” in Lecture Notes in Computer Science, Cham, 2019.
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