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|a 9783658110840
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|a 10.1007/978-3-658-11084-0
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|a G. Schuetz, Christoph.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Multilevel Business Processes
|h [electronic resource] :
|b Modeling and Data Analysis /
|c by Christoph G. Schuetz.
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|a 1st ed. 2015.
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|a Wiesbaden :
|b Springer Fachmedien Wiesbaden :
|b Imprint: Springer Vieweg,
|c 2015.
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|a XXIV, 232 p. 42 illus.
|b online resource.
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|a text
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|a computer
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|a text file
|b PDF
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|a Core Metamodel for Multilevel Objects -- Multilevel Business Artifacts -- Hetero-Homogeneous Business Process Models -- Multilevel Business Process Automation -- Multilevel Business Process Intelligence.
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|a Christoph G. Schuetz examines the conceptual modeling aspects of multilevel business processes without neglecting the implementation aspects. Furthermore, he investigates the advantages of hetero-homogeneous models for quantitative business process analysis. Multilevel models reflect the reality of many information systems. In this respect process-aware information systems are no exception. Multilevel models capture interdependencies between business processes at different organizational levels and allow for a convenient representation of business process variability which, in turn, facilitates the analysis of business processes across different organizational units. Contents Core Metamodel for Multilevel Objects Multilevel Business Artifacts Hetero-Homogeneous Business Process Models Multilevel Business Process Automation Multilevel Business Process Intelligence Target Groups Researchers and students in business informatics, computer science, and business administration. Business process management professionals The Author Christoph G. Schuetz is a postdoctoral researcher at the Department of Business Informatics - Data & Knowledge Engineering of the Johannes Kepler University Linz, Austria. His research interests include data warehousing, semantic web, business process management, and data privacy.
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|a Computer Communication Networks.
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|a Software Engineering.
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|a Artificial Intelligence.
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783658110833
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|i Printed edition:
|z 9783658110857
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|u https://doi.uam.elogim.com/10.1007/978-3-658-11084-0
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|a Computer Science (SpringerNature-11645)
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|a Computer Science (R0) (SpringerNature-43710)
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