Workflow management versus case handling

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Workflow management versus case handling: results from a controlled software experiment

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Symposium on Applied Computing archive
Proceedings of the 2008 ACM symposium on Applied computing table of contents

Fortaleza, Ceara, Brazil

SESSION: Coordination models, languages and applications table of contents

Pages 82-89

Year of Publication: 2008

ISBN:978-1-59593-753-7

Authors

Bela Mutschler	Daimler AG Group Research, Ulm, Germany
Barbara Weber	University of Innsbruck, Austria
Manfred Reichert	University of Twente, The Netherlands

Sponsor

SIGAPP: ACM Special Interest Group on Applied Computing

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 18, Downloads (12 Months): 148, Citation Count: 1

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ABSTRACT

Business Process Management (BPM) technology has become an important instrument for improving process performance. When considering its use, however, enterprises typically have to rely on vendor promises or qualitative reports. What is still missing and what is also demanded by IT decision makers are quantitative evaluations based on empirical and experimental research. This paper picks up this demand and illustrates how experimental research can be applied in the BPM field. The conducted experiment compares efforts for implementing a sample business process either based on standard workflow technology or on a case handling system. We motivate and describe the experiment design, discuss threats for the validity of experiment results (as well as risk mitigations), and present experiment results. In general, more experimental research is needed in order to obtain more valid data on the various aspects and effects of BPM technology and tools.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Y. L. Antonucci. Using Workflow Technologies to improve Organizational Competitiveness. Int'l. J. of Management, 14(1), pp.117--126, 1997.
	2	P. Athena. Case Handling with FLOWer: Beyond Workflow. 2002.
	3	V R Basili , R W Selby , D H Hutchens, Experimentation in software engineering, IEEE Transactions on Software Engineering, v.12 n.7, p.733-743, July 1986
	4	M. Dumas, W. M. P. van der Aalst, and A. ter Hofstede. Process-aware IS. Wiley, 2005.
	5	N. Juristo and A. M. Moreno. Basics of Software Engineering Experimentation. 2001.
	6	N. Kleiner. Can Business Process Changes Be Cheaper Implemented with Workflow-Management-Systems? IRMA 2004, pp.529--532.
	7	C. M. Lott and H. D. Rombach. Repeatable Software Engineering Experiments for Comparing Defect-Detection Techniques. Empirical Software Engineering, 1(3), pp. 241--277, 1996.
	8	B. Mutschler, M. Reichert, and J. Bumiller. Unleashing the Effectiveness of Process-oriented Information Systems: Problem Analysis, Critical Success Factors, Implications. IEEE Transactions on Systems, Man, and Cybernetics - Part C: Application and Reviews, 2008 (accepted for publication).
	9	B. Mutschler, M. Reichert, and S. Rinderle. Analyzing the Dynamic Cost Factors of Process-aware IS: A Model-based Approach. CAiSE 2007.
	10	Glenford J. Myers, A controlled experiment in program testing and code walkthroughs/inspections, Communications of the ACM, v.21 n.9, p.760-768, Sept. 1978 [doi>10.1145/359588.359602]
	11	Michiko Oba , Sen'ichi Onoda , Norihisa Komoda, Evaluating the Quantitative Effects of Workflow Systems Based on Real Cases, Proceedings of the 33rd Hawaii International Conference on System Sciences-Volume 6, p.6031, January 04-07, 2000
	12	L. Prechelt. Controlled Experiments in Software Engineering (in German). Springer, 2001.
	13	P. Reason and H. Bradbury. Handbook of Action Research. 2001.
	14	H. A. Reijers and W. M. P. van der Aalst. The Effectiveness of Workflow Management Systems - Predictions and Lessons Learned. Int'l. J. of Inf. Manag., 25(5), pp.457--471, 2005.
	15	P. Runeson. Using Students as Experiment Subjects. EASE 2003.
	16	D. J. Sheskin. Handbook of Parametric and Nonparametric Statistical Procedures. 2000.
	17	Dag I. K. Sjoberg , Jo E. Hannay , Ove Hansen , Vigdis By Kampenes , Amela Karahasanovic , Nils-Kristian Liborg , Anette C. Rekdal, A Survey of Controlled Experiments in Software Engineering, IEEE Transactions on Software Engineering, v.31 n.9, p.733-753, September 2005 [doi>10.1109/TSE.2005.97]
	18	Tibco. Staffware Process Suite. User Manual, 2005.
	19	W. M. P. Van Der Aalst , A. H. M. Ter Hofstede , B. Kiepuszewski , A. P. Barros, Workflow Patterns, Distributed and Parallel Databases, v.14 n.1, p.5-51, July 2003 [doi>10.1023/A:1022883727209]
	20	W. M. P. van der Aalst and K. van Hee. Workflow Management. MIT Press, 2004.
	21	Wil M. P. van der Aalst , Mathias Weske, Case handling: a new paradigm for business process support, Data & Knowledge Engineering, v.53 n.2, p.129-162, May 2005 [doi>10.1016/j.datak.2004.07.003]
	22	B. Weber, S. Rinderle, and M. Reichert. Change patterns and change support features in process-aware is. CAiSE 2007.
	23	Marvin V. Zelkowitz , Dolores R. Wallace, Experimental Models for Validating Technology, Computer, v.31 n.5, p.23-31, May 1998 [doi>10.1109/2.675630]