Espacios. Vol. 36 (Nº 09) Año 2015. Pág. 18

Application of Technological Intelligence Tools and S-Curves in a Foresigth Evaluation Regarding Biodegradables Packaging and Environmentally Friendly Up to 2032

Aplicação de Ferramentas de Inteligência Tecnológica e S-Curves em uma Avaliação Foresigth Quanto Biodegradáveis Embalagem e Ambiente Amigável para 2032

Jhon Wilder ZARTHA Sossa 1; Hector Samuel VILLADA Castillo 2; Andres Felipe AVALOS Patiño 3; Bibiana ARANGO Alzate 4; Luciano Amanda Lucía FERNANDEZ Pérez 5; Gina Lía OROZCO Mendoza 6; Rafael BERMUDEZ Ortega 7; Raúl HERNANDEZ Zarta 8; Diego Fabián JOAQUI Daza 9; Alcy René CERÓN Mosquera 10; John Fredy MORENO Sarta 11

Recibido: 29/01/2015 • Aprobado: 14/02/2015


1. Introduction

2. Technology intelligence

3. S-curves

4. Metodology

5. Technological intelligence Results

6. S-curves results

7. Conclusions


This paper is an input of "foresigth evaluation regarding biodegradable packaging and environmentally friendly, up to 2032". The intention is to show the results obtained through the use of tools such as intelligence technology and S-curves as supports for decision making. In the process, two databases were used: Scopus and Freepatentsonline. Based in the results by patents and articles, collected data was used in function and were applied non linear regression techniques to calculate the inflection point. Statistical parameters such as adjuste d R2, value T, Value P, and Durbin Watson, Zartha et al. (2014); Cortés et al (2013); Ávalos et al. (2011) were calculated to validate the results obtained. The articles and patents data were analyzed through the Weibull, Gompertz, Logistic, Sigmoidal, Hill models and others, 13 models were applied in total. The chosen models had the better statistics fit and inflection point were calculated, for the appears case, the sigmoidal model had the better statistic fit with 4 parameters, showing what inflection point will by 2019. In patents, the better model statistic fit was sigmoidal model with 4 parameter, showing what the inflection point was in the year 2004.
Keyword: Technological Intelligence Tools, S-Curves, Environmentally Friendly.

Este paper es un insumo del estudio de prospectiva relacionada con empaques biodegradables y amigables con el medio ambiente al 2032. La intención es mostrar los resultados obtenidos a través del uso de herramientas tales como vigilancia tecnológica y curvas en S como soporte a la toma de decisiones. En el proceso dos bases de datos fueron usadas: Scopus y Freepatentesonline. Basado en los resultados de patentes y artículos, a los datos obtenidos se le aplicaron técnicas de regresión no lineal para calcular el punto de inflexión. Parámetros estadísticos tales como R2, valor T, valor P y Durbin Watson Zartha et al. (2014); Cortés et al (2013); Ávalos et al. (2011) fueron calculados para validar los resultados obtenidos. Los datos de artículos y patentes fueron analizados a través de los modelos de Weibull, Gompertz, Logistico, Sigmoidal y Hill entre otros, en total fueron aplicados 13 modelos. Los modelos con el mejor ajuste estadístico fueron elegidos y se calcularon los puntos de inflexión, para este caso el modelo sigmoidal con cuatro parámetros tuvo el mejor ajuste estadístico mostrando que el punto de inflexión será en el 2019, en patentes el mejor ajuste estadístico fue igualmente el modelo sigmoidal de cuatro parámetros mostrando que el punto de inflexión se presentó en el 2004.
Palabra clave: Herramientas de Inteligencia Tecnológica, S-curvas, respetuosos del medio ambiente.

1. Introduction

Biodegradable packaging is in increasing demand, the market is raising awareness about the importance of this kind of materials and the impact they can have on  the environment. The demand has accelerated the scientific interest in the subject, generating a wide range of technologies and materials suitable for its development, such dynamic can be seen in the number of papers and patents related to the topic. The main objective of this work was to contribute through tools such as the Technology intelligence and S-curves in building the technology tree which was the first input for the foresight study through Delphi, new commodities / technologies / innovations biodegradable packaging technology up to 2032.

2. Technology intelligence

"Technology intelligence is an organized, selective and permanent process of capturing information from abroad and within the own organization about science and technology,  in order to select, analyze, disseminate and communicate it to turn it into knowledge to make  less risky decisions and to anticipate changes "AENOR (2006)

Palop and Martinez (2012), say in their methodological Practice Guide of Technology intelligence and Competitive Intelligence: Having clarity of the organizational environment facilitates the implementation of activities to achieve the strategic objectives and achieving goals in certain periods (short, medium and / or long term). Indeed, this is the effective contribution of (VI / CI), then this process is important because:

1. It helps the process of making decision strategically expanding the perspective of the organization, to detect events that may affect the organization.

2. Organizations can beneficially anticipate changes proactively avoiding  reactionary  decisions tendency affecting the sustainability of the organization.

3. It reduces the risks and uncertainties that may occur in the process of making.decision

In Figure 1, some of the benefits about the implementation in the making decision process are illustrated.

Figure 1: Adapated  from Palop y Martinez (2012)


3. S-curves

Since years ago, academics, researchers and entrepreneurs have tried to understand the behavior of the technology over time as well as strategies that can be implemented according to each specific phase of its career, some alternatives to analyze technology over time are models of S-curves. (Kucharavy & De Guio, 2007), (Zartha, et al. 2009), (Pérez, 2001), (Ortiz and Pedroza, 2006), thus is possible to identify whether a technology is emerging, starting, central (key), mature or declining (figure 2) and whether is necessary to establish a monitoring strategy, selective investment or non over-investment in certain technology and establish its phased behavior: Initial Dissemination, early groh, slow groh and technology maturity  (Figure 3).

In studies related to the usage of S curves, different stages or phases are identified, bounded by specific points in their groh. This evolution has been studied by authors like Nelson and Winter (1977), Dosi (1982), Pérez (2001), amongst others. Ortiz and Pedroza, (2006) describe the evolution of a technology and its trajectory by means of the S curves. (Figure 2).

Figure 2: Technology state

Source:  Evolution of a technology. Adapted from (Ortiz y Pedroza, 2006)

The curves obtained can be correlated with the existent information about the type of technology (emerging technology, edge technology, key technology and base technology) and the decisions that can be made based on the different types (figure 3).

Figure 3: S-curves stage. Maturity level

Source: Adapted from Pérez (1992)

The S curves method, given its easy practice, has become a widely used tool in a broad range of applications, now that using it shows appropriate forecast results in a wide spectrum of systems (Ávalos, Bermúdez, Zartha, & Ávalos, 2012).

Different authors have estudied the S- curves applied in the analisys of the disseminate technological Innovations, they divided it in four stages and suggested the  estrategies to be implementted in each stage. Pérez (1992); Fernández (2005); White and Bruton (2007).

On the other hand, it is known that the technological diffusion to describe an S graphic way and its compound by different stages that belong to many innovation strategies that should be applied with the pourpose  of improving the efficiency and  application on innovation.  Different mathematical models can be adjusted in the curve and the  statistical variables obtained  are used for making conclusions on the topic. Zartha et al. (2014); Cortés et al. (2013); Ávalos et al. (2011).

4. Metodology

The SCOPUS database was used to search  for biodegradable packaging scientific papers and

Freepatentesonline was used for patent searching, which includes patent databases of  United States, Japan, Germany and WIPO - World Organization of the intellectual property.

Subsequently, the data found were accumulated and processed in the SIGMAPLOT software trough nonlinear regression, a total of 13 models contained in the software were applied, among which: Sigmoidal 3 parameters, sigmoidal 4 Gompertz 3 parameters, Chapman and Hill were applied.

With the results of nonlinear regression,  R2 parameter,  value t, p value, Durbin Watson (DW) were obtained. Then, based on the values of these parameters, the best adjusted models were chosen and inflection points of the series of papers and patents on biodegradable packaging were calculated, the latest were found by calculating the second derivate.

Figure 4 shows a summary of the methodology

Figure 4: Methodology by technology analisys througth S-Curves.

Source: Modified from Zartha S, Palop F, Arango. B., Avalos A, Velez F (2013) S-ANALYSIS AND TECHNOLOGY LIFE CYCLE.
Application in series of data of articles and patents. PICMET 2013.

5. Technological intelligence Results

For information search, two databases were used: Scopus and Freepatentsonline; with the first tool, scientific papers were obtained from the search equation: TITLE("bio packaging" OR biopackaging OR (packaging W/3("bio degradable" OR biodegrada* OR "bio polymer" OR biopolymer))) the results were 119 in total.  Graphic 1 shows the dinamyc publications in the topic time.

Graphic 1: Publication dinamyc about topic

With the freepatentsonline database, the patents were looked up throughout the next equation: ABST/("bio packaging" OR "biodegradable packaging" OR "biopolymer packaging") in this case 100 patents associated  with the topic were obtained. Graphic 2 shows the dinamyc about the topic.

Graphic 2: Patents dinamyc about the topic.

Graphic 3: shows the data series of papers and accumulated patents. The S-curves in the techonology  can be observated in the graphic.

Grapic 3: Data series of papers and patents accumulated



After using the search equation in the Scopus Database, keywords of papers found were obtained  according to project relevance, which are shown in the table 1 along with its repeability level:

Table 1: Keywords Scopus database

6. S-curves results

The S-curves technology were elaborated with the results of papers data series and the published patents to identify its inflection point.  The figure 5 shows the papers S-curve

Figure 5: Papers S-curves

Table 2 shows the results obtained with the 4-parameter sigmoidal model with its correspondent equation, among 13 models used through SIGMAPLOT software, this model had the best statistical adjust

Table 2: Sigmaplot software data obtained for papers



Error estándar

Standard error













X0: Punto de inflexión

Inflection point














R2 ajusted




Equation 1: 4-parameter sigmoidal

The scientist publications inflection point will be released in 2019

The S-curves technology were elaborated with the results of patents data series, figure 6 shows the inflection point in the curve

Figure 6: Patents S-curve


Table 3 shows the results obtained with 4 - sigmoidal parameters, this model had the best values of  R2, t value, P value and Durbin Watson.

Table 3: shows the patents results obtained with sigmoidal software



Standard error













X0: Inflection point














R2 ajusted




According to results of SIGMAPLOT software, the patents inflection point occurred in 2004

7. Conclusions

The results between technological intelligence procces: biodegradables packaging papers and patents, and the techonology inflection points estimations were lined up succesfully by giving supporting elements for decisión makers in this knowlegde area.

Two performance parameters were used in the same techonology or knowledge area and inflection points were obtained, this is important because  just one parameter; papers or patents had been used in previous studies about S-curves.

With the values obtained in the inflection points in the series of articles and patents, decision making can be made with relation to the type of technology identification before and after the inflection point. Before: emerging technology, edge technology and key technology. After: mature technology and base technology.

In the different stages of technology transfer, or in the operations that can be developed through it, such as: transmission, absorption, usage, learning, accumulation, generation and diffusion, among others. There is always an interest concern about knowing the stage of the analyzed technology, especially if the technology is actually emerging or incoming, or if it is mature or declining instead.

The point of inflection regarding patents occurred in 2004, and scientist publications inflection point will be released in 2019, in the analyzed series, the inflection points for the articles will occur years after the inflection points were obtained from the patents. This may be because, from the beginning of the article's dynamic publishing, the previous existence of information is required, so that it can only be obtained from the first patents, furthermore, it could be explained because of the early stages of the technology life cycle where the researchers found a "mine", or  high inventory of new knowledge, that is susceptible to being applied in some industrial sectors, and therefore generate a high dynamic scientific production  that can be observed in a high slope, with the curve in the growing stage.

An additional an analysis can be made from the inflection point for the determination of the adequate moment to apply technological right mechanisms and intellectual property. Before the inflection point: technological right mechanisms and intellectual properties are performed. After the inflection point: technical experience and knowledge are available and over costs should be considered to protect new dominant designs that could enter the market. 

At last, S curves and their inflection point can help reduce uncertainty in monitoring decisions, when technology is emerging before the inflection point, to not over-invest, and when a technology becomes base after the inflection point.


Working in a future project with three performance parameters: papers, patents and annual publication patent priority, the latest can help  to refin and contrast inflection points obtained.

It is fundamental to review alongside experts to be sure that working with patents and articles corresponds to the technology being studied.


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1.Escuela de Ingenierías – Facultad de Ingeniería Agroindustrial. Email:

2. Universidad del Cauca. Email:

3. Universidad Pontificia Bolivariana Email:

4. Universidad Pontificia Bolivariana. Email:

5. Universidad del Cauca. Email:

6. Universidad Pontificia Bolivariana.  Email:

7. Centro Regional de Productividad e Innovación del Cauca.  CREPIC Email:

8. Universidad Pontificia Bolivariana. Email:

9. Universidad del Cauca. Email:

10. Universidad del Cauca. Email:

11. Instituto Tecnológico Metropolitano:

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