Managing next generation BP-x initiatives

Myriam Schaschek (), Fabian Gwinner, Nicolas Neis, Christoph Tomitza, Christian Zeiß and Axel Winkelmann
Additional contact information
Myriam Schaschek: Julius-Maximilians-Universität Würzburg (JMU)
Fabian Gwinner: Julius-Maximilians-Universität Würzburg (JMU)
Nicolas Neis: Julius-Maximilians-Universität Würzburg (JMU)
Christoph Tomitza: Julius-Maximilians-Universität Würzburg (JMU)
Christian Zeiß: Julius-Maximilians-Universität Würzburg (JMU)
Axel Winkelmann: Julius-Maximilians-Universität Würzburg (JMU)

Information Systems and e-Business Management, 2024, vol. 22, issue 3, No 3, 457-500

Abstract: Abstract Past generations of BPM involved the efficient and effective management of business processes. Yet, we currently face a turning point. The technological facets of data-driven BPM add complexity to traditional BPM applications. As a result, organizations face intended and unintended technology-related changes across all business process initiatives. Using the term BP-x, we summarize the recent changes in BPM knowledge that has hitherto been fragmented across academic literature. To address the challenges of BP-x initiatives, we envision a holistic model that focuses on managing related cutting-edge technologies and BPM. Thus, we propose the operationalized BP-x management model as a valuable IT meta-artifact. We develop the model using a two-cycled Design Science Research methodology and conduct a threefold summative evaluation. The results of our study indicate that creating awareness of potentials and opportunities accelerates the process toward action and fosters new business outcomes in terms of performance and innovation. By strategically aligning BP-x endeavors, organizations promote visibility, shared understanding, and culture among stakeholders. Our model guides managers throughout the BP-x adoption journey in conjunction with organizational, managerial, and technological prerequisites.

Keywords: BPM; Process analytics; Predictive analytics; Prescriptive analytics; Process automation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10257-024-00681-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:infsem:v:22:y:2024:i:3:d:10.1007_s10257-024-00681-3

Ordering information: This journal article can be ordered from
http://www.springer. ... ystems/journal/10257

DOI: 10.1007/s10257-024-00681-3

Access Statistics for this article

Information Systems and e-Business Management is currently edited by Jörg Becker and Michael J. Shaw

More articles in Information Systems and e-Business Management from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().