Business process modeling success: An empirically tested measurement model
Bandara, Wasana, Gable, Guy G., & Rosemann, Michael (2006) Business process modeling success: An empirically tested measurement model. In Straub, D. & Klein, S. (Eds.) Proceedings of International Conference on Information Systems, University of Wisconsin, Milwaukee, Wisconsin, pp. 1-20.
The visualization of business processes in the form of process models has increased in popularity and importance. The resultant prevalence and magnitude of process modeling projects demand appropriate means of evaluating such initiatives. This paper presents a validated measurement model and instrument for assessing process modeling success. The final validated model employs 15 measures within the 3 dimensions - Model Quality, Process Impacts and Project Efficiency. The model was empirically tested with 290 responses to a global survey of process modelers. The overall study design consists of an exploratory model building phase (extensive literature review and multiple case studies) to identify salient success dimensions and measures, which was followed by an exploratory model testing phase. Test results evidence the discriminant validity of the model dimensions as well as their convergence on the single higher-order concept - Process modeling success (PM-Success). Criterion validity testing further evidences the additivity of the 3 dimensions of success, and the completeness of the resultant overarching second-order measure of PM-Success.
The contributions from this work are twofold. From the perspective of practice, it offers a validated success model and measurement instrument that can be employed by organizations to measure the degree of success of completed process modeling projects. From an academic perspective: it presents a validated success measure, which can be used as the dependent variable in further research aimed at a better understanding of the important antecedents of process modeling success. Process modeling success can also be an important independent variable in research that aims to explore causal relations further along the Information Systems Development (ISD) cycle. In both research and practice, process modeling success benchmark scores can be valuable in comparative analyses across project types and project contexts, for highlighting process modeling related problems and issues deserving of attention, or best practices worthy of replication.
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|Item Type:||Conference Paper|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2006 (please consult authors)|
|Deposited On:||06 Dec 2007 00:00|
|Last Modified:||25 Apr 2015 02:26|
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