From contexts to constructs: the use of grounded theory in operationalising contingent process models

G H Galal

European Journal of Information Systems, 2001, vol. 10, issue 1, 2-14

Abstract: In software and systems engineering, process models have been suggested that partly develop artifacts and then deploy them to evaluate the degree of their success in satisfying requirements, using the results of the evaluation to inform further engineering efforts. This paper discusses the important role of evaluation in non-sequential process models, and suggests an interpretive framework for effecting such evaluation, as well as the determination of risks and constraints to operationalise such models. We outline a particular mode of the Grounded Systems Engineering Methodology (GSEM) which aims at supporting the application of non-sequential process models, thus enabling them to be more responsive to the development context. GSEM utilises the philosophy and procedures of the Grounded Theory method, an interpretive research strategy which is being widely used for the inductive analysis of qualitative data in theory building. An illustrative case study is used to show how the framework can be applied in practice.

Date: 2001
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1057/palgrave.ejis.3000381 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tjisxx:v:10:y:2001:i:1:p:2-14

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/tjis20

DOI: 10.1057/palgrave.ejis.3000381

Access Statistics for this article

European Journal of Information Systems is currently edited by Par Agerfalk

More articles in European Journal of Information Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().