Research Grant
[Cite as https://purl.org/au-research/grants/arc/DP150103356]
Researchers:
Chun Ouyang
(Chief Investigator)
,
Dr Michael Adams
(Chief Investigator)
,
Marcello La Rosa
(Chief Investigator)
,
Moe Wynn
(Chief Investigator)
,
Prof Arthur ter Hofstede
(Chief Investigator)
View all 9 related researchers
Brief description Improved Businesss Decision-Making via Liquid Process Model Collections. This project aims to develop an innovative approach to create and update as necessary the large collection of business process models that represent a complex organisation, so that this collection captures the actual way in which the organisation performs its business processes. Deploying theoretical, conceptual and empirical research, this project aims to capitalise on the value hidden in large process data, as recorded in event logs. The approach is intended to be implemented in an open-source technology to facilitate advanced investigations and predictions that can ultimately lead to better strategic decision-making. This technology also has the potential to become a research-enabling tool for the large research community in business process management.
Funding Amount $847,700
Funding Scheme Discovery Projects
- ARC : DP150103356
- PURL : https://purl.org/au-research/grants/arc/DP150103356
