Neuro-Fuzzy-ANP based decision model for ERP system selection

This PhD dissertation addressed an applied Information System research issue in the domain of ERP selection. ERP selection is one of ERP research issues, which is concerned on product selection, consultant selection, calculation of return on investment, and on the preparation of contractual agreement. Accordingly, this study addressed the development of a decision model to support users in the selection of ERP solutions. The proposed model is composed of framework, criteria, and a Neuro-Fuzzy- Analytical Network Process (NFANP) based decision support system. In discussing the proposed model, the first four chapters of the dissertation provides general overview and research methodology. The first component of the model, which is the framework, is discussed in chapter five. Seven procedures are identified as suitable steps in ERP selection process and they are organized in a structural representation formulating the new framework. The second components of the model, which are ERP selection criteria, are discussed in chapter six. The criteria are identified from literature and standardized based on the comparison made with ISO9126 software quality model. The study identified Neuro-Fuzzy ANP (NFANP) method, as a suitable method to facilitate ERP selection process and introduced it as the third component of the model. In this regard, chapter seven provides a depth discussion on existing ERP selection methods. The eighth chapter then discussed the integration of the FANP and ANN components of the proposed method in order to provide a seamless operating decision support system (DSS). Finally the dissertation presents the evaluation of the model and provides summary, conclusions and further research directions in the last two chapters.