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Design of Data-Driven Decision Support Systems for Business Process Standardization

Fleig, Christian

Abstract (englisch):
Increasingly dynamic environments require organizations to engage in business process standardization (BPS) in response to environmental change. However, BPS depends on numerous contingency factors from different layers of the organization, such as strategy, business models (BMs), business processes (BPs) and application systems that need to be well-understood (“comprehended”) and taken into account by decision-makers for selecting appropriate standard BP designs that fit the organization. Besides, common approaches to BPS are non-data-driven and frequently do not exploit increasingly avail-able data in organizations. Therefore, this thesis addresses the following research ques-tion: “How to design data-driven decision support systems to increase the comprehen-sion of contingency factors on business process standardization?”.
Theoretically grounded in organizational contingency theory (OCT), this thesis address-es the research question by conducting three design science research (DSR) projects to design data-driven decision support systems (DSSs) for SAP R/3 and S/4 HANA ERP systems that increase comprehension of BPS contingency factors. ... mehr

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Volltext §
DOI: 10.5445/IR/1000117653
Veröffentlicht am 12.03.2020
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Hochschulschrift
Publikationsdatum 12.03.2020
Sprache Englisch
Identifikator KITopen-ID: 1000117653
Verlag Karlsruhe
Umfang 305 S.
Art der Arbeit Dissertation
Fakultät Fakultät für Wirtschaftswissenschaften (WIWI)
Institut Institut für Wirtschaftsinformatik und Marketing (IISM)
Prüfungsdatum 28.02.2020
Referent/Betreuer Prof. A. Maedche
Schlagwörter Business Process Management, Business Process Standardization, Decision Support Systems, Process Mining, Business Model Mining, Data-Driven
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