Criteria for ERP selection using an AHP approach

Information systems are a foundation key element of modern organizations. Quite often, chief executive officers and managers have to decide about the acquisition of new software solution based in an appropriated set of criteria. Analytic Hierarchy Process (AHP) is one technique used to support that kind of decisions. This paper proposes the application of AHP method to the selection of ERP (Enterprise Resource Planning) systems, identifying the set of criteria to be used. A set of criteria was retrieved from the scientific literature and validated through a survey-based approach.

Utilização do método Multicritério AHP, na aquisição de um sistema ERP

The selection of an Enterprise Resource Planning (ERP) system is one of the most sensitive and highest impact processes in the area of information systems and technologies, because it supports and integrates the whole business of an organization. Hence the importance of deciding the best solution in order to contribute to the organization's competitiveness in a global and increasingly demanding market. Therefore, it is essential to provide tools to support decision making, turning complex and often intangible decisions into simple and quantifiable scenarios. This study addressed the adoption of the Analytical Hierarchy Process (AHP) multicriteria decision method to support the selection of an ERP system. The literature review was the source used to obtain the set of the most relevant criteria to be considered in this decision, which were subsequently validated through systematic application of various surveys of experts and people related to the field of ERP systems. To support the application of AHP, according to the model obtained in the study, it was developed a web application that will be available to the general public. The responsible for the acquisition of ERP systems can use it to easily apply the AHP method based on validated decision model. On the other hand, the web application can be used as a validation tool, allowing collecting data for future developments of the decision model.

PROPOSAL OF AN EMPIRICAL MODEL FOR SUPPLIERS SELECTION

The problem of selecting suppliers/partners is a crucial and important part in the process of decision making for companies that intend to perform competitively in their area of activity. The selection of supplier/partner is a time and resource-consuming task that involves data collection and a careful analysis of the factors that can positively or negatively influence the choice. Nevertheless it is a critical process that affects significantly the operational performance of each company. In this work, trough the literature review, there were identified five broad suppliers selection criteria: Quality, Financial, Synergies, Cost, and Production System. Within these criteria, it was also included five sub-criteria. Thereafter, a survey was elaborated and companies were contacted in order to answer which factors have more relevance in their decisions to choose the suppliers. Interpreted the results and processed the data, it was adopted a model of linear weighting to reflect the importance of each factor. The model has a hierarchical structure and can be applied with the Analytic Hierarchy Process (AHP) method or Simple Multi-Attribute Rating Technique (SMART). The result of the research undertaken by the authors is a reference model that represents a decision making support for the suppliers/partners selection process.

The influence of the dispersion method on the electrical properties of vapor-grown carbon nanofiber/epoxy composites

The influence of the dispersion of vapor-grown carbon nanofibers (VGCNF) on the electrical properties of VGCNF/ Epoxy composites has been studied. A homogenous dispersion of the VGCNF does not imply better electrical properties. In fact, it is demonstrated that the most simple of the tested dispersion methods results in higher conductivity, since the presence of well-distributed nanofiber clusters appears to be a key factor for increasing composite conductivity.