Metodología para la selección de sistemas enterprise resource planning desplegados en la nube para pequeñas y medianas empresas: Aproximación alineada con la realidad ecuatoriana

Authors

Keywords:

cloud computing, Enterprise Resource Planning, software as a service

Abstract

Currently Enterprise Resource Planning (ERP) is an essential tool for companies looking for the automation of their processes, which is why several companies spend a lot of time and effort in selecting the ERP that fits the best to their needs. Despite the effort, it is often the case that this selection is made in an empirical way or through informal recommendations, which means that the best option is not always chosen. This paper presents a methodology for ERP selection using cloud computing technology, a technology that offers new services for the provision of software under the Software as a Service (SaaS) model. Several software options exist, specifically ERP systems, that exploit the advantages of the cloud such as availability, payment for use, service on demand among others. Additionally, the ERP system selected should be in harmony with the Ecuadorian legislation and day-to-day reality. The aim of the study is to expose and match the requirements of ERP systems, the requirements for a deployment of a software as a service (SaaS) model and the requirements to comply with Ecuadorian legislation, as to choose the deployed ERP in the cloud that best fits the needs of the Ecuadorian company. A proof of concepts is presented, which exemplifies the application of the methodology and to demonstrate the feasibility of our proposal.

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References

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Published

2017-12-30

How to Cite

Carrión, F., & Cedillo, P. (2017). Metodología para la selección de sistemas enterprise resource planning desplegados en la nube para pequeñas y medianas empresas: Aproximación alineada con la realidad ecuatoriana. Maskana, 8(1), 35–49. Retrieved from https://publicaciones.ucuenca.edu.ec/ojs/index.php/maskana/article/view/1964

Issue

Vol. 8 (2017): PROCEEDINGS: R+D+Engineering

Section

First Congress of Computer Science

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