In this article, the methodology of curves in S is applied in series of data on articles in Biotechnology and Nanotechnology since 1956 obtained from the ISI Web of Science and of patents since 1962 (year of priority) and 1970 (year of publication). Belonging to controlled release, of the medical context, the data was obtained from a Tech Mining approach using the Vantage Point software tool. With the accumulated data, in time, nonlinear regression was achieved and the inflection point in the two series was calculated, taking into account the statistical parameters like Fitted R2, Value T, Value P, and Durbin Watson. The data of the articles and patents were analyzed under the following models: Weibull, Gompertz, Logistic and Sigmodial, among others, for a total of 13 models analyzed. The models with the best fit in the inflection point were selected. In the series of data from the articles, one of the models that had the best fit was the Sigmoidal model. The Sigmoidal model contained three parameters which generated a value of 33.4 for the inflection point for the year of the studied series. With the obtained values for the inflection points in the series of articles and patents, the uncertainty can be reduced in the making of decisions about the Technology Life Cycle (TLC), especially in the following aspects: the identification of the kind of technology (before and after of the inflection point), the determination of the suitable moment to apply technological rights and intellectual property, and the establishment of strategies for monitoring (when the technology is emerging) and investment.
Full-text available at http://www.revistaespacios.com/a16v37n07/16370719.html
Author(s): Jhon Wilder ZARTHA Sossa; Fernando PALOP Marro; Bibiana ARANGO Alzate; Fabián Mauricio VELEZ Salazar; and Andres Felipe AVALOS Patiño
Organization(s): Universidad Pontificia Bolivariana, Universidad Politécnica de Valencia
Source: Espacios
Year: 2015