A framework for the analysis and evaluation of enterprise models

Doctoral Thesis


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University of Cape Town

The purpose of this study is the development and validation of a comprehensive framework for the analysis and evaluation of enterprise models. The study starts with an extensive literature review of modelling concepts and an overview of the various reference disciplines concerned with enterprise modelling. This overview is more extensive than usual in order to accommodate readers from different backgrounds. The proposed framework is based on the distinction between the syntactic, semantic and pragmatic model aspects and populated with evaluation criteria drawn from an extensive literature survey. In order to operationalize and empirically validate the framework, an exhaustive survey of enterprise models was conducted. From this survey, an XML database of more than twenty relatively large, publicly available enterprise models was constructed. A strong emphasis was placed on the interdisciplinary nature of this database and models were drawn from ontology research, linguistics, analysis patterns as well as the traditional fields of data modelling, data warehousing and enterprise systems. The resultant database forms the test bed for the detailed framework-based analysis and its public availability should constitute a useful contribution to the modelling research community. The bulk of the research is dedicated to implementing and validating specific analysis techniques to quantify the various model evaluation criteria of the framework. The aim for each of the analysis techniques is that it can, where possible, be automated and generalised to other modelling domains. The syntactic measures and analysis techniques originate largely from the disciplines of systems engineering, graph theory and computer science. Various metrics to measure model hierarchy, architecture and complexity are tested and discussed. It is found that many are not particularly useful or valid for enterprise models. Hence some new measures are proposed to assist with model visualization and an original "model signature" consisting of three key metrics is proposed.Perhaps the most significant contribution ofthe research lies in the development and validation of a significant number of semantic analysis techniques, drawing heavily on current developments in lexicography, linguistics and ontology research. Some novel and interesting techniques are proposed to measure, inter alia, domain coverage, model genericity, quality of documentation, perspicuity and model similarity. Especially model similarity is explored in depth by means of various similarity and clustering algorithms as well as ways to visualize the similarity between models. Finally, a number of pragmatic analyses techniques are applied to the models. These include face validity, degree of use, authority of model author, availability, cost, flexibility, adaptability, model currency, maturity and degree of support. This analysis relies mostly on the searching for and ranking of certain specific information details, often involving a degree of subjective interpretation, although more specific quantitative procedures are suggested for some of the criteria. To aid future researchers, a separate chapter lists some promising analysis techniques that were investigated but found to be problematic from methodological perspective. More interestingly, this chapter also presents a very strong conceptual case on how the proposed framework and the analysis techniques associated vrith its various criteria can be applied to many other information systems research areas. The case is presented on the grounds of the underlying isomorphism between the various research areas and illustrated by suggesting the application of the framework to evaluate web sites, algorithms, software applications, programming languages, system development methodologies and user interfaces.

Bibliography: leaves 264-288.