Proceedings of the 12th European Conference on Knowledge ...

Choon-Bae Yoo, Igor Hawryszkiewycz and Kyeong-Soon Kang
6.1 Deriving <strong>the</strong> measurement model
In terms <strong>of</strong> selecting criteria, literature review was carried out and feedback from informal practitioners
interview that enabled to identify <strong>the</strong> important factors which are relevant to measure success model.
These relate to user satisfaction, model quality, model use and model content.
To devise a multi-dimensional concept <strong>of</strong> a multi perspective model success, a complete set <strong>of</strong>
measurement dimension is important (Kanellis et al. 1998). Bandara et al. (2006) describe success is
complex and due to <strong>the</strong> lack <strong>of</strong> IS success frameworks studies, adaptation <strong>of</strong> modeling success
dimensions deriving from <strong>the</strong> literature by conceptualizing <strong>the</strong> model success to measure four
dimensions as identified below Table 1. These extracted dimensions will correlate to <strong>the</strong> multiple
perspective contexts.
Table 1: Modeling success dimensions
User Satisfaction The extent to which <strong>the</strong> users believe multi
perspective modeling achieves <strong>the</strong> objectives
in unforeseen circumstances
Multi Perspective Model
Quality
Multi Perspective Model
Use
Multi Perspective Model
Content
*Adapted from Bandara et al. (2006)
6.2 Case study design
The extent to which <strong>the</strong> users believe multi
perspective modeling affects <strong>the</strong>
responsiveness in unforeseen circumstances
The extent to which <strong>the</strong> users believe multi
perspective modeling controls <strong>the</strong> adaptability
in unforeseen circumstances
The extent to which <strong>the</strong> users believe multi
perspective modeling delivers <strong>the</strong> reliability in
unforeseen circumstances
A pilot case study was performed and four subsequent multiple case studies are being carried out
with <strong>the</strong> modeling success dimensions which described in Table 1. Qualitative method is being
employed to examine <strong>the</strong> organizations to understand <strong>the</strong> complex processes and collaboration
issues facing participating organizations. Moreover, case study to evaluate <strong>the</strong> effectiveness <strong>of</strong> <strong>the</strong>
proposed framework allows an easier management <strong>of</strong> system evolution and in supporting multiple
stakeholders with coordination <strong>of</strong> complex projects.
6.3 Data collection
In recognition <strong>of</strong> various known case study method, participants are being asked questions about
complex project coordination across organizations. The focus <strong>of</strong> this research is semi-structured
interviews as a method <strong>of</strong> obtaining primary data on <strong>the</strong> working practice in dynamic organizations. In
particular, documenting all procedures relates to <strong>the</strong> interview findings and <strong>the</strong> analysis <strong>of</strong> data for
validation phases <strong>of</strong> <strong>the</strong> research project. All <strong>the</strong> interviews will instigate with two phases which are a
comparison <strong>of</strong> pre and post experimental questionnaires that will be used to collect information
regarding case study. Fur<strong>the</strong>rmore, research will be employing content analysis to review literature
and evaluation <strong>of</strong> multi perspective approaches is critically conducted.
6.4 Data analysis
The purpose <strong>of</strong> analysis is to understand <strong>the</strong> structure <strong>of</strong> what already exist, and to identify <strong>the</strong>
causes <strong>of</strong> any problems or restrictions. The data collected have subject to both analysis and syn<strong>the</strong>sis
in addressing research questions. Each case follows a standard format, reflecting <strong>the</strong> <strong>the</strong>oretical
motivation for <strong>the</strong> research, and includes as much <strong>of</strong> <strong>the</strong> common data as possible to facilitate
comparative analysis, such as constant comparison (Strauss 1987) and case study method (Yin
2002).
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