Survey design: Insights from a public sector ERP success story

Research on the impact of Information Systems (IS) reported in both academic literature and popular press has reported confounding results. Some studies have reported encouraging results of IS, while others have reported nil or detrimental results. The contradictory results of these research studies can be partially attributed to the weaknesses in survey instruments. In an attempt to increase the validity of conclusions of IS assessment studies, survey instrument design should follow a rigorous and scientific procedure. This paper illustrates key validity and reliability issues in measuring Information Systems performance, using examples from a study designed to assess Enterprise Resource Planning systems success. The article emphasizes on the importance of the survey method and the theoretical considerations of item derivation, scale development and item evaluation. Examples are provided from the ERP assessment study to supplement the readers understanding of the theoretical concepts of survey design.

Enhancing the Expressiveness of the Bunge-Wand-Weber Ontology

In practical terms, conceptual modeling is at the core of systems analysis and design. The plurality of modeling methods available has however been regarded as detrimental, and as a strong indication that a common view or theoretical grounding of modeling is wanting. This theoretical foundation must universally address all potential matters to be represented in a model, which consequently suggested ontology as the point of departure for theory development. The Bunge–Wand–Weber (BWW) ontology has become a widely accepted modeling theory. Its application has simultaneously led to the recognition that, although suitable as a meta-model, the BWW ontology needs to be enhanced regarding its expressiveness in empirical domains. In this paper, a first step in this direction has been made by revisiting BUNGE’s ontology, and by proposing the integration of a “hierarchy of systems” in the BWW ontology for accommodating domain specific conceptualizations.