S
Selim Erol
Researcher at Vienna University of Technology
Publications - 19
Citations - 1809
Selim Erol is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: Business process & Business process modeling. The author has an hindex of 8, co-authored 18 publications receiving 1311 citations. Previous affiliations of Selim Erol include Vienna University of Economics and Business & University of Applied Sciences Wiener Neustadt.
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Journal ArticleDOI
A Maturity Model for Assessing Industry 4.0 Readiness and Maturity of Manufacturing Enterprises
TL;DR: In this paper, the authors propose an empirically grounded model and its implementation to assess the Industry 4.0 maturity of industrial enterprises in the domain of discrete manufacturing by including organizational aspects.
Journal ArticleDOI
Tangible Industry 4.0: A Scenario-Based Approach to Learning for the Future of Production
TL;DR: A Scenario-based Industry 4.0 Learning Factory concept that is built upon a tentative competency model for Industry 5.0 and the use of scenarios for problem-oriented learning of future production engineering is suggested.
Journal IssueDOI
Combining BPM and social software: contradiction or chance?
Selim Erol,Michael Granitzer,Simone Happ,Sami Jantunen,Ben J. Jennings,Paul Johannesson,Agnes Koschmider,Selmin Nurcan,Davide Rossi,Rainer Schmidt +9 more
TL;DR: The results of the workshop on Business Process Management and Social Software (BPMS2'08), as part of the International Conference on Business process Management in Milano, show the manifold possibilities of combining concepts from Business Process management and social software.
Combining BPM and Social Software: Contradiction or chance?
Selim Erol,Michael Granitzer,Simone Happ,Sami Jantunen,Ben J. Jennings,Agnes Koschmieder,Selmin Nurcan,Davide Rossi,Rainer Schmidt,Paul Johannesson +9 more
TL;DR: The results of the workshop on Business Process Management and Social Software (BPMS2’08) show the manifold possibilities of joining concepts from Business Process management and social software and offers new possibilities for a more effective and flexible design of business processes.
Journal ArticleDOI
Rethinking Human-Machine Learning in Industry 4.0: How Does the Paradigm Shift Treat the Role of Human Learning?
TL;DR: This paper addresses the challenges of mutual human-machine learning in factories of the future with the ultimate goal to identify new learning patterns in highly digitalized industrial work scenarios.