Software to improve the implementation of quantitative techniques in prospective studies

Abstract

Over the last two decades, organizations have expressed concern on achieving competitiveness and obtaining market stability, which has driven them to analyzing the advantages of going to the desired future by using tools like prospective studies. In order to optimize the use of prospective studies support tools were developed that still do not cover certain interests of stakeholders, including: use of economic, environmental, technological, and human resources. To supply the need identified, software was proposed to contribute to supporting prospective studies based on web 2.0 technologies, independent from techniques employed to optimize resources exploiting advantages offered by the Internet. This research concluded that prospective studies are a viable alternative for organizations seeking to achieve their business goals; however, the attempt to accomplish the desirable future will bring a range of costs, which are increased when the implementation of these studies conducted apart from tools, software, and models. For this reason, we must employ methods that combine technological tools, software, collaborative and integration capabilities as offered by Web 2.0 to optimize their processes and, thus, allow areas like prospective to achieve high levels of efficiency and overcrowding.

Authors

  • Amaury Cabarcas Alvarez
  • Raul Jose Martelo Gomez
  • Luis Carlos Tovar Garrido

Downloads

Download data is not yet available.

Keywords

Author Biography


Profesor Asistente de la Facultad de Ingeniería de la Universidad de Cartagena, en programas de pregrado y postgrado. Investigador del Grupo GIMATICA (Grupo de Investigación en Tecnologías de las Comunicaciones e Informática) Categorizado B Colciencias. Ingeniero de Sistemas y Magister en Ciencias Computacionales.
Published
2013-06-27
| 27 |
How to Cite
Cabarcas Alvarez, A., Martelo Gomez, R., & Tovar Garrido, L. (2013). Software to improve the implementation of quantitative techniques in prospective studies. Cuadernos De Administración, 29(49), 64-74. https://doi.org/10.25100/cdea.v29i49.65
Section
Research