Process modelling success factors and measures
Bandara, Wasana (2007) Process modelling success factors and measures. .
Business process modelling has gained widespread acceptance, particularly in
large IT-enabled business projects. It is applied as a process design and
management technique across all project lifecycle phases. While there has been
much research on process modelling, there has been little attention on 'how to'
conduct process modelling effectively, or on the evaluation of process modelling
initiatives and outcomes. This study addresses this gap by deriving a process
modelling success model that contains both the success factors (independent
variables) and success dimensions (dependent variables) of process modelling.
The study employs a multi-method approach, blending both qualitative and
quantitative research methods. The research design commenced with a
comprehensive literature review, which includes the first annotated bibliography
in process modelling research. A multiple case study approach was used to build
the conceptual process modelling success model which resulted in a model with
eleven (11) success factors (namely Modeller Expertise, Team Structure, Project
Management, User Competence, User Participation, Management Support,
Leadership, Communication, Modelling Tool, Modelling Language and Modelling
Methodology), two (2) moderating variables (namely Process Complexity and
Project Importance) and five (5) process modelling success dimensions (namely
Modeller Satisfaction, Model Quality, User Satisfaction, Model Use and Modelling
Impact). This conceptual model was then operationalised and tested across a
global sample, with an online survey instrument.
290 valid responses were received. The constructs were analysed seeking a
parsimonious, valid and reliable model. The statistical analysis of this phase
assisted in deriving the final process modelling success model. The dependent
variables of this model consisted of three (3) contextual success factors (namely
Top Management Support, Project Management and Resource Availability), two
(2) Modelling specific success factors (namely Modelling Aids and Modeller
Expertise), and two (2) moderating variables (namely Importance and Process
Complexity). The dependent variable; Process Modelling Success (PMS) was
derived with three (3) success measurement dimensions (namely Model Quality,
Process Impacts and Process Efficiency). All resulting success factors proved to
have a significant role in predicting process modelling success. Interaction
effects with the moderating variables (Importance and Process Complexity)
proved to exist with Top Management Support (TMS) and Resource Availability
(RA). A close analysis to their interaction relationship illustrated that Importance
(IMP) moderated the relationship between Top Management Support (TMS) and
Process Modelling Success (PMS) in a linear manner and that Process Complexity
(PC) moderated the relationship between Resource Availability (RA) and Process
Modelling Success (PMS), also in a linear manner.
This is the first reported study with empirical evidence on process modelling
success. The progressive outcomes of this study have been readily accepted by
the practitioner and academic community, with 16 published internationalrefereed-
conference papers [including best paper award at the Pacific Asian
Conference on Information Systems (PACIS 2004)], 2 journal publications, and
over 5 major industry presentations made upon invitation.
Impact and interest:
Citation countsare sourced monthly fromand 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 downloadsdisplays 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:||QUT Thesis (PhD)|
|Supervisor:||Rosemann, Michael, Gable, Guy, & Middleton, Michael|
|Keywords:||process modelling, success factors, success measures, moderating variables, case study method, survey method, multi-method approach|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Past > Schools > Information Systems
|Department:||Faculty of Information Technology|
|Institution:||Queensland University of Technology|
|Copyright Owner:||Copyright Wasana Bandara|
|Deposited On:||03 Dec 2008 14:02|
|Last Modified:||29 Oct 2011 05:47|
Repository Staff Only: item control page