Authors:
C. Timurhan Sungur
;
Uwe Breitenbücher
;
Oliver Kopp
;
Frank Leymann
and
Andreas Weiß
Affiliation:
University of Stuttgart, Germany
Keyword(s):
Informal Processes, Unstructured Processes, Resource Discovery, Capability Discovery, Relevant Resources, Relevant Capabilities.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Operational Research
;
Organisational Learning
;
Project Management
;
Society, e-Business and e-Government
;
Tools, Techniques and Methodologies for System Development
;
Web Information Systems and Technologies
Abstract:
Achieving goals of organizations requires executing certain business processes. Moreover, the effectiveness
and the efficiency of organizations are affected by how their business processes are enacted. Thus, increasing
the performance of business processes is in the interest of every organization. Interestingly, resources and
their capabilities impacting past enactments of business processes positively or negatively can similarly have
a positive or a negative impact in their future executions. Therefore, in our former work, we demonstrated
a systematic method for identifying such resources and capabilities of business processes using interactions
between resources of business processes without detailing the concepts required for this identification. In
this work, we fill this gap by presenting a conceptual framework including concepts required for identifying
resources possibly impacting business processes and capabilities of these resources based on their interactions.
Furt
hermore, we present means of quantifying the significance of resources and their capabilities for business
processes. To evaluate the identified resources and capabilities with their significance, we compare the results of
the case study on the Apache jclouds project from our former work with the data collected through a survey. The
results show that our system can estimate the actual values with 18% of a mean absolute percentage error. Last
but not least, we describe how the presented conceptual framework is implemented and used in organizations.
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