ARTÍCULO ORIGINAL
DOI: 10.17533/udea.redin.n77a02
Barriers for innovation detected in 400 colombian businesses, based on the innovation ''U'' coefficient methodology
Barreras para la innovación detectadas en 400 empresas colombianas, a partir de la metodología coeficiente ''U'' de innovación
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Bibiana Arango-Alzate*, Jhon Wilder Zartha-Sossa, José Gamaliel Medina-Henao, Andrés Felipe Avalos-Patiño, Fabian Mauricio Velez-Salazar
Escuela de Ingenierías, Universidad Pontificia Bolivariana. Circular 1 # 70-01. A. A. 56006. Medellín, Colombia.
* Corresponding author: Bibiana Arango Alzate, e-mail: bibiana.arango@upb.edu.co
(Received May 4, 2014; accepted April 28, 2015)
ABSTRACT
]]> The barriers for innovation have been studied for the past 40 years. However, in most of these studies, the subject has been examined in a qualitative way. Consequently, certain tools are required to measure the barriers of innovation inside the organizations. This time, the results of the barriers of an innovation tool is presented; this tool has been developed by researchers from Universidad Pontificia Bolivariana, which was applied to 400 businesses from different areas. The tool is composed by a total of 18 internal and external barriers, and allows the controllable barriers to be determined by identifying the sector and region. Furthermore, there is a coefficient that classifies the businesses in ranges from high, medium and low in terms of innovation´s facilities. The methodology for the calculation of the barriers for innovation in business can be the base to measure innovation obstacles in regions, clusters and sectors, because it provides an indicator of the most representative barriers in each of them. This can be useful to generate some strategies to close or eliminate those barriers through public policies and summons with specific projects.Keywords: Barriers for innovation, innovation projects, U coefficient
RESUMEN
Las barreras para la innovación han sido estudiadas desde hace más de 40 años, sin embargo, en la mayoría de estos estudios el tema ha sido abordado de una forma cualitativa, lo que indica que se requieren herramientas que permitan cuantificar el efecto de las barreras para la innovación dentro de las organizaciones. En esta ocasión, se presentan los resultados de la herramienta, coeficiente ''U'' de innovación, desarrollada por investigadores de la Universidad Pontificia Bolivariana, la cual fue aplicada a 400 empresas de diversos sectores. La herramienta está conformada por un total de 18 barreras internas y externas, y permite detectar las barreras controlantes (o más importantes) por sector y región; así como un coeficiente que clasifica las empresas en rangos de alto, medio y bajo en cuanto a facilidades para innovar. Sin embargo, ha surgido la necesidad de aumentar el número de barreras y de generar otros indicadores por empresa. La metodología para el cálculo de barreras para la innovación en empresas puede ser la base para la medición de los obstáculos de innovación en regiones, cluster y sectores, ya que reflejaría un indicador de las barreras más representativas en cada uno de ellos y sería útil para generar estrategias eliminar esas barreras a través de políticas públicas y convocatorias con proyectos específicos que permitan la eliminación de las barreras para la innovación.
Palabras clave: Barreras para la innovación, proyectos de innovación, coeficiente U de innovación
1. Introduction
In recent years, several investigations have been conducted in order to analyze the barriers for innovation inside different businesses or industrial sectors, where the lack of comprehension between the academy and the industry to the joint implementation of innovative projects emerges [1, 2]. The barriers for innovation are presented inside the companies or sectors, but there are also some exogenous barriers that hinder the innovation process [3] . Regarding the exogenous barriers, which the company may face, researchers have followed the effect of government support in biotechnological research in Germany, determining the effect of public research on private companies making it a possible barrier [4] .
Although intensive knowledge companies are very dynamic in terms of innovation, they tend to be incremental and focused, and present barriers to improve their innovation level [5] . However, they may find companies which stand out thanks to their innovation achievements. These companies must overcome the cultural barriers regarding the innovation that they may find in all the organizational levels [6] . In general, barriers for innovation have been researched in different sectors such as construction and education, amongst others [7, 8]. In the education sector, the barriers for innovation regarding online education have been studied, and they found that the teachers just adapt these tools when it is mandatory [8] .
On the other hand, the barriers for innovation that are presented when using R&D teams on separate or integrated environments have found that, in the first case, the teams show a lack of motivation when it comes to exploring new options; meanwhile the groups in a separate environment show interdepartmental collaboration problems [9].
An analysis of the case of Siemens (Australia), highlighting the innovation achievements that were accomplished by the company, concludes that the key to staying is to overcome the cultural barriers regarding the innovation that they may find in all organizational levels [6] . In a study of some companies in a market with mature characteristics, the necessity to change certain general paradigms to overcome and implement a real innovation strategy has been found [10] .
]]> Recently, some approaches have described the barriers for innovation that companies have when activities are aimed towards innovation, such as: costs, knowledge, market and regulation factors [11] . On the other hand, the relationship between product, process, and innovation management has been examined, finding that barriers have a different impact on the types of innovation and innovation management [12] .In the last years, researchers such as [13-15] have analyzed the barriers for innovation in Portugal, Brazil and Morocco, respectively.
The barriers for innovation quantitative analysis related to this paper is based on innovation ''U'' coefficient methodology, and seeks to analyze how susceptible organizations are to the adoption, promotion, leverage, and support of new ideas, projects or activities in the R&D process. The tool was developed within the framework of several research projects and a specialization thesis at the in Universidad Pontificia Bolivariana, Medellin – Colombia and is available in the following webpage: http://barrerasparalainnovacion.com/.
2. Methodology
The ''U'' innovation coefficient is a methodology based on physical models of heat transfer by conduction and convection. The tool includes a total of 18 barriers, which at first instance are the result of the barriers raised in an evaluation type workshop, or resemble the ones posted in Management Innovation Lab [16] . This raises a similar exercise to the proposed activity regarding this work. These barriers are classified as conduction barriers (tangible barriers) and convective barriers (intangible barriers, money and information). The developed tool allows a quick ''U'' innovation coefficient inside companies to be determined, based on physical models of heat transfer by conduction and convection [17] .
A random sample was extracted from the web application of 400 companies that evaluate ideas or projects through the tool. Then, the information was debugged, detecting outliers. Figure 1 presents the region and sector's participation percentage.
2.1. Information analysis and comparative methods
The comparison between the regions is presented firstly, through a distribution data analysis, using the box and whisker plot, which allows an estimate of the range where more than 75% of the data is concentrated. Then, the mean analysis allows meaningful statistical difference to be established between the mean values of the ''U'' innovation coefficient. This is done through a test factorial ANOVA, which shows the ratings of the barriers of regions with the highest average ''U'' innovation coefficient; which generates a confidence level of 95%. An ANOVA test was performed to identify the barriers that have significant statistical difference at a confidence level of 95%. Table 1 shows the ranges and categories with which companies are classified in terms of the coefficient of innovation.
]]> Finally, the three most representative sectors were selected, in which the barriers' weights were analyzed, with the purpose of establishing higher barriers in the projects or evaluated ideas. Table 2 shows the relative sum and the rating of the barriers. The qualifications with a rating of 5, indicate than the barrier is in a medium, medium-high or high state.To evaluate the ideas, projects or activities inside the process of R+D+i, the tool considers a total of 18 barriers, which are classified as: physical, monetary, informational; and time. Table 3 shows the barriers and their qualification.
3. Results and discussion
3.1. Innovation coefficient distribution in different regions
Figure 2 shows ''U'' innovation coefficient distribution in the referred regions. The figure shows that 75% of data in Antioquia is in the range (40,751; 74,432), in other regions (40,048; 81,307), Quindío (37,497; 69,599), Risaralda (34,087; 67,558) and Santander (37,216; 60,463). That means that in terms of ''U'' innovation coefficient, Antioquia and the rest of the regions are in the low-medium category; while Quindío, Risaralda and Santander are in the low category. In these regions, the upper ''U'' coefficients are values outside the data distribution that show that they are not common cases in all regions.
In terms of the ''U'' innovation coefficient, Table 4 shows that there is no significant difference between the mean values of the coefficient of innovation in each of the regions, at confidence level of 95%. However, Figure 3 shows that Antioquia, Risaralda and Quindío are in a medium-low, although Risaralda leans toward lower values. Meanwhile Santander is in a category of a low innovation coefficient.
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3.2. Barriers to innovation in Antioquia and Quindío
In terms of the mean value, Figure 4 shows that there are no differences between the barrier ratings in Antioquia and Quindío. According to Table 2, the mean value related to the barrier ratings falls between 3 and 5. While Antioquia tends to remain in the medium category with weights between 1318 and 2116, Quindío possesses weights that are between 927 and 1501; thus indicating that they are in the low-medium category. However, in terms of the mean and the mode, the barriers in Antioquia stay in a medium and low-medium category, meanwhile in Quindío, the barriers are in low, medium and high-medium categories.
Antioquia and Quindío present some common barriers such as having time to develop new ideas, keeping the project going despite the organization´s priority changes and the inability to carry the generated costs that come with removing a professional in order to dedicate full time to the development of the idea or project. However, the categorization of barriers and the U coefficient, indicates that Antioquia has a tendency towards medium score values (4 to 6), while Quindío has a tendency toward medium and medium-high values (between 3 and 10). In terms of the barriers, these two regions differ. In Table 4, the upper and middle barriers in each of these regions are shown, taking into account that the higher the barrier, the less prone the region is to innovation.
In terms of the barrier's weight, Table 5 shows that there is statistical significant difference at a confidence level of 95%, according to the P-value. In this regard, if the value of the barrier weight is low, the coefficient of innovation will be higher, which in comparative terms, gives an idea of how regions are more prone to innovation in respect to the others.
Figure 5 shows that Antioquia is noticeably different from other regions, with the lowest weight barrier, which equals to a higher coefficient of innovation; followed by the region of Quindío. Meanwhile Risaralda and Santander are the regions that have more difficulties to innovate because they have the highest weight barrier in respect to the others.
In general, the barriers in both Antioquia and Quindío have a central value that is between 3 and 5. However, Table 6 shows that there is a statistically significant difference between the two regions, amid all the barriers grouped together and between the scores of the barriers in both regions; with a confidence level of 95%.
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Meanwhile, Table 7 shows that there are similarities and differences between the barriers, finding differences in those related to information (B2, B9, B12) and money (B14, B15). It can be noted that the regions differ and that these regions are faced barriers.
Table 8 shows the main barriers founded in Antioquia, such as dealing with objections that reflect inflexible mental models inside the organization; getting financial support in early stages of the Project or the idea. This is what makes the project last despite the organization´s priorities changes, etc.
3.3. Barriers to innovation present in three economic sectors
Figure 6 shows the weighted sum associated to the rated values. Each barrier in different project or ideas explored by each company belongs to the three most representative sectors of the sample. In general terms, the figure gives an idea of the central values of each barrier and the distribution data of the ratings. In this logic, the TIC´s sector is in a range of (657; 1226), which means that the barriers are focused in values from 3 to 5. The Agro-industrial sector is in the range of (497; 720), which is equivalent to central values between 3 and 5; the education sector is in a range of (347; 685), between 3 and 6. It is obvious that the barriers in the three sectors are in a low-medium category, because the lowest weight prevails. However, in modal terms, it is possible to find barriers that can be in a high category. Under these circumstances, the figure shows that the barriers that may consider medium-high category are in black color.
Table 9 shows the barriers contemplated in Figure 6. It is regardless that the medium-high barriers in the educational sector and TICs correspond to related barriers with the monetary resource, meanwhile in the Agro-industrial sector, a physical barrier stands out, related to the human resource.
]]> 4. ConclusionsThe comparative analysis shows that Antioquia and the rest of the regions have a low-medium ''U'' innovation coefficient. Quindío, Risaralda, Santander are in a low category. Although it is unrelated, the central value in all regions is in a low category, which means that in statistical terms, the regions do not differ significantly. However, once the probability limits are established, Antioquia, Quindío and the rest of the regions have a certain similarity, but differ regarding the mode with Risaralda and Santander.
The three most representative sectors in the sample present a general distribution in the ratings, where the values between 3 and 6 stand out. In general, it means that the three sectors have a trend towards innovation. However, the higher barriers are economic type resources and staff availability.
A study of the barriers by region explains the value of the ''U'' innovation coefficient. Even though for this case, there are no significant differences between the core indicators of both regions, it is clear that the trend of the ratings in each of the barriers is presenting the differences or similarities that may occur, in this case, between Antioquia and Quindío.
5. References
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