An extensible framework for analysing resource behaviour using event logs
Pika, Anastasiia, Wynn, Moe T., Fidge, Colin J., ter Hofstede, Arthur H.M., Leyer, Michael, & van der Aalst, Wil M.P. (2014) An extensible framework for analysing resource behaviour using event logs. In Jarke, Matthias, Mylopoulos, John, & Quix, Christoph (Eds.) Lecture Notes in Computer Science [Proceedings of the 26th International Conference on Advanced Information Systems Engineering, CAiSE 2014], Springer Verlag, Thessaloniki, Greece, pp. 564-579.
Business processes depend on human resources and managers must regularly evaluate the performance of their employees based on a number of measures, some of which are subjective in nature. As modern organisations use information systems to automate their business processes and record information about processes’ executions in event logs, it now becomes possible to get objective information about resource behaviours by analysing data recorded in event logs. We present an extensible framework for extracting knowledge from event logs about the behaviour of a human resource and for analysing the dynamics of this behaviour over time. The framework is fully automated and implements a predefined set of behavioural indicators for human resources. It also provides a means for organisations to define their own behavioural indicators, using the conventional Structured Query Language, and a means to analyse the dynamics of these indicators. The framework's applicability is demonstrated using an event log from a German bank.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||Process mining, Resource behaviour indicators, Employee performance measurements|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)|
|Divisions:||Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2014 Please consult the authors|
|Deposited On:||10 Mar 2014 00:00|
|Last Modified:||26 Jul 2014 04:47|
Repository Staff Only: item control page