Optimization of a massive data upload model using search engines for websites oriented to e-commerce

Autor: Hernan Aules, Freddy Tapia, Graciela Guerrero, Lenin Barrionuevo
Rok vydání: 2017
Předmět:
Zdroj: 2017 6th International Conference on Software Process Improvement (CIMPS).
DOI: 10.1109/cimps.2017.8169945
Popis: The development of Information and Communication Technologies (ICT) and the widespread growth of Internet has revolutionized the way of performing commercial operations. Due to this the organizations must reconsider the use of systemic thinking and aim their business models towards more globalized tendencies. All this has helped many companies to see the electronic commerce as a new way of on-line commercialization; this tendency is not strange to the Ecuadorian market. An example of this are virtual stores which offer a variety of products through digital information brochures. The present research work focuses on the design and optimization of a massive data upload model representing a reduction of costs and time optimization. In order to run tests of efficiency and veracity this investigation was centered on a virtual store (YaEsta.com) which for its size and characteristics (technological infrastructure and managed data), facilitate the delimitation and execution of agreed targets. All this consolidated on mathematical models that validated the results obtained by the proposed model concluding that there was an optimization of 60% against traditional processes (manual data upload).
Databáze: OpenAIRE