4. Results and Main Findings
4.3. Networks
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4.3. Networks
With regard to the networks; the Production network is the most important linkage for Peruvian companies with 59.89% of firms that have a relationship with a supplier, competitor or firms of the same group. Also, the customer network is another important linkage with 49.45%. The less important in term of linkages is the Knowledge network with 27.81% of the firms that have a relationship with universities, research institutes or laboratories.
4.4. Analyzing the regressions
Using the basic model described in the research method. The research finds that the presence of a production network and knowledge network are highly significant in the probability to innovate (in all its four dimensions). In the case of the customer network, it seems not to be important for innovation (at least using this measure). Analysing the results, it is possible to observe that the odds of innovation in product (the probability to innovate over the probability to not innovate) of the firms that have relationships with other firms (production network) is 2.02 bigger than the odds of the innovation in product of the firms that do not possess any kind of relationship with other firms. In a similar way, the research finds that the odds of innovation in process, innovation in the organization, and innovation in commerce tend to be bigger (19.6, 1.83 and 1.52 respectively) for the firms that possess a relationship than firms that do not have any
Table N° 15
Type of Networks Percentage Knowledge Network 27.81 Production Network 59.85
Customer Network 49.45
Networks
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higher probability to innovate in the four types of innovation. For the case of the knowledge network, the analysis of the odd ratios reveals that the odds to innovate (in the four types of innovations) for the firms that own a relationship with knowledge components are bigger (1.61, 1.70, 1.85 and 1.78 respectively) than the firms that are not connected with knowledge components.
Using the improved measure of innovation, it is interesting to see a stronger degree of innovative relationships with the production networks and knowledge networks can be significant in the probability to innovate compared with the weaker relationships.
For instance, analysing the degree of relations with production components (competitors, suppliers, and firms of the same economic group), it is possible to observe that the odds of innovation in product for the firms that have relationship more related with Joint studies, Engineering and designs and Investigation, and development is 2.28 bigger than the odds of innovation in product for the firms that do not have relationships or only have commercial relationship with other production components. Also, observing the second strong type of innovative relationship; Training, Testing of
Table N° 16
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products/processes, and Technical assistance; it is possible to observe that the odds of innovation in product for the firms that have an educational relationship with other firms is 1.95% bigger than the firms that only have a commercial relationship or do not have any relationship.
Despite having a result with less significance, the relationship related to the information required has a probability in product innovation that is 1.58 times larger than companies
Table N° 17
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that do not have contact with other companies or are limited to only a commercial relationship.
In the case of process innovation, it is also observed that those companies that have a relationship with other companies focused on joint work, process engineering, research, and development present a probability to innovate in the process that is2.5 higher with regard to companies that do not have any kind of relationship with other companies or the relationship is purely commercial. Also, an important and unexpected result is the fact that the firms that have relationships with other firms focused on finances present a probability to innovate in process of 2.4 times larger than those companies that do not have a relationship or only have a commercial relationship. Similar results are found for the innovation in organizations and the innovation in commercialization where the relationship related to financial requests and joint studies with other firms present the largest odds in the logistic regression.
Analysing the degree of relationships of the companies that have links with the knowledge infrastructure (universities, public institutes, private institutes and non-university laboratories), the research finds that the relationship focused on joint studies, research and development and engineering is the most important for the four types of innovation according to significance and value of the odds ratio (2.07 for innovation in product, 2.133 for innovation in process, 2.099 for innovation in organization and 2.279 for innovation in marketing). The second most important relationship with knowledge components that foster the innovation (except innovation in the product) is the training, testing of products/processes, and technical assistance where the variable is significant for all the types of innovation except the innovation in product.
Adding the other important explanatory variables considered in the research and using
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production remains important in the propensity to innovate however the network knowledge variable lose importance in the innovation in the product after the incorporation of the research and development activities. This last fact has to be interpreted with caution, and it is possible that the role of the knowledge network of innovation in the products of Peruvian companies is the linkage with the purpose of doing research and development activities, so the knowledge network and R&D activities are overlapping variables.
The last factor becomes highly important for the four types of innovation. Thus, for instance, the odds of innovation in products for firms that carry out activities in research and development is 10.94 times higher than the odds of innovation in product for firms that do not carry out those activities. In the same way, the odds of innovation in the process, organization, and commercialization for the companies that carry out research and development activities are more than three times the odds of companies that do not carry out such activities. Also, the measure of absorptive capacity shows that a basic infrastructure that is destined to manage and create knowledge increases the probability to innovate in all aspects.
Table N° 18
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Analysing the second model with the improved measure of the network, R&D activities and absorptive capacity remain important in the propensity to innovate. It is also possible to see that the most obvious change is the decreasing in significance and in the value of the odds ratio of the degree of the knowledge network.
Table N° 19
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However, it is possible to observe that knowledge network is still important in innovation performance, especially the relationships related with joint studies, research and development and engineering. This fact shows the limitation of the first measure of network, and it give us a better perspective about the role of networks in the decision to innovate within the firm.
Advancing in this analysis, the research adds the control variables that were discussed and defined in the previous chapters: year, technology intensity and size of the firm.
The model reveals that the variable year is significance on the innovation in the organization and it also has an odd ratio minor to 1. Then it is necessary to use the
Table N° 20
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inverse of the coefficient to be able to give a correct interpretation. Thus, if the age is decreased by one unit and all the values of the other variables of the model remain constant, the odds of the firms to innovate increase by 1.01 times more than the odds if they did not decrease that year. That means that there is a negative relationship between year and innovation in the organization. This is aligned with other empirical papers.
The explanation of this fact is that young companies tend to innovate more due to the more flexible rules and costs they have to face. In term of size, it is interesting that the odds of innovation for mediums firms are 2.56 times larger than the odds of innovation for microenterprise. Another interesting finding is that the odds of innovation for mediums firms is1.94 times larger than the odds of innovation for microenterprise. This result is aligned with a wide range of empirical evidence. The explanation is that medium and big companies are more willing to reorganize their areas to find a more optimal labor division.
Also, the model reveals that technology intensity (measured by industry) is not a significant variable in our model of innovation. Although the empirical evidence in other countries indicates that companies from highly technology-intensive sectors innovate more than companies from sectors of low technological intensity, Peruvian companies innovate equally regardless of sector.
Adjusting the previous model with the improved measure of the network, the research establishes a more complete version of the model proposed to study the impact of networks along the different dimensions of innovation. The model includes the other important explanatory variables and the more acceptable control variables in the empirical evidence. In general, the model shows that networks play an important role in the propensity to innovate. The production network seems to be the more important network for innovation because after examining the significance of the different degree
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of relations for this variable in the model, it is possible to see that the interaction between a firm and another firm is significant from the most basic interaction such as asking information until the most complex interaction such as making joint studies or making together research and development activities (except the impact of training in the innovation in process).
Table N° 21
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In the case of knowledge, the network is interesting that relationships with a high degree of interaction and related with knowledge creation are positive and retain high significance with the different types of innovations (production, process, organizational and commercial). It is also interesting that educational relationships (such as training and technical assistance) with knowledge organization have a positive and significant effect on innovation in process and organization.
And, although the network with customers seems to be a weaker variable, it can be important for the innovation in commercialization where the Research and Development collaboration has a high significance with this innovation. It might be understandable due to the fact that this collaboration would tend to focus on the customization of the appearance more than the customization in the function of the product itself. Confirming the theory, the decision to perform a Research and Development activity and the presence of a good absorptive capacity has a high significance for the four dimensions of innovation. Also, there is a negative relationship between the innovation in organization and the years of operation, so younger firms have a greater possibility to change their form of operation. And medium and big firms tend to innovate in organization more than microenterprises.
Finally, in order to answer the second research question, the study makes a model that reformulates the variable networks in the variable origin. As it was mentioned in the previous chapter, the variable origin has five categories: non-relationship (0), only relationship with National Organization (1), only relationship with Asia Pacific Organization (2), only relationship with Non-Asia Pacific Organization (3), and relationship with more than one source.
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In the model, the relationship and importance of the rest of the independent variable and control variable are still the same. The importance of each origin is contrasted with the lack of relationship and it is possible to see that the relationship with Asia Pacific organizations is highly significant and positive. However, this is also true to the relation
Table N° 22
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with national organizations and Non-Asia Pacific organizations. To compare if there is a significant difference between Asia Pacific Organization and the other two sources, the study will test the coefficients of each origin between them.
Although the coefficients of Asia Pacific Relation has a greater impact than the coefficients of Non-Asia Pacific Regions in the innovation in process and innovation in the organization, the test shows that the coefficient is not statistically significantly different. The same is possible to observe if we compare the relationship with Asia Pacific Organizations and national organizations. In this sense, all the origins of relations have importance in innovation but none of them is dominant over the others.
This fact is already significant because the positive impact of Asia Pacific linkages exists and it accomplishes an important role in innovation. Due to this, comparing with the impact of other networks could undermine the understanding of the current work of relations with this region and may not be the best way to understand its importance.
Therefore, the present research sees the need to include two case studies that allow us to visualize the importance of relationships with organisms in the Asia-Pacific region.
Table N° 23
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In this way, the first case to study is the successful case of the collaboration between the Intercorp and IDEO group. The Intercorp group is one of the most successful economic groups in Peru led by businessman Carlos Rodríguez Pastor and it has its most important companies in the financial, retail, education and entertainment sectors (Rosado, 2016). Meanwhile, IDEO is a company recognized worldwide for its innovation consultancies and the use of "design thinking" methodology to find solutions, and it is located in many cities of related to the Asia Pacific, such as Cambridge (Massachusetts), Chicago, New York, Palo Alto, San Francisco, Shanghai and Tokyo5.
The story begins with a call from Carlos Rodríguez Pastor to IDEO, in which he comments on his desire to transform Peru through the design of a new educational system. Within the three initial requirements, the implementation of schools with international quality was sought, which is within the budget of an emerging middle class and which can be rescaled throughout the national territory (Innova School, 2018).
Therefore, IDEO and the "Innova" team (the name of the project) worked together on the challenge of creating a chain of schools with international quality for middle class families. The process had a field work with the purpose of knowing the needs and expectations of Peruvian families; the revision of educational models that have been able to scale and that meet the aspirations and educational quality that the families revealed in the fieldwork (especially the "blending learning school" model); the design phase and the testing of the "blending learning school" model designed (Quattrocchi, 2014).
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The results of this collaboration as a whole was the creation of the "Innova" school chain. These schools have an educational model that mixes the direction of teachers and technology, and encourages the student to be the protagonist of their own learning after the resolution of challenges proposed by the teacher, the development of their own abilities, and the resolution of social problems within a team. Initially the parents had doubts about this new educational model; “students at Innova schools have already surpassed the achievement of their peers in both government and private schools in Peru (61% achieved proficiency in math, 86% in literacy). But tripling the scores of the government schools and doubling those of other private schools is not enough. School leaders have pledged to go from 61% proficiency in math (compared with the country's 17%), to 75% in the next five years” (Quattrocchi, 2014).
Another important collaboration of Intergroup and IDEO is reflected in the commercial innovation implemented by Interbank (a company of the Intergroup group) through which a new model of customer service is implemented (Ideo, 2013). After identifying that the attention received, the time in the queue and the environment are key factors in the experience that the consumer; Interbank and IDEO revolutionized Peruvian banking through the creation of “Interbank Explora” (Interbank, 2017). This innovative format presents some disruptive aspects with respect to the usual Peruvian banking:
- In Interbank Explora, the user registers with his / her card, his / her ID card or foreign identity card and will be called by his / her name just before being attended. In this way, the attention becomes much more personalized.
- Eliminate the queue by implementing screens that show the name of the person to be served. In addition, the client has reminders by SMS indicating that he is about to be served. With this last aspect, the user does not necessarily have to
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- They actively promote the use of electronic and digital banking, so that the client can do their banking operations wherever they are. Using the Internet Banking or Interbank App, the client can save more time in operations.
- They break physical barriers with open counters to facilitate interaction with the client.
- They create learning spaces to share with clients how to obtain the maximum benefit from the bank's products. Also, they create social spaces to make the visit of the client more pleasant.
The second case to study is the successful case of the collaboration between the Ajinomoto Co., Inc. and Ajinomoto Peru. Ajinomoto Co., Inc. is a Japanese company that produces condiments for food, cooking oil and medicines; and it is the parent company of the Ajinomoto group that has subsidiaries in 35 countries (Ajinomoto, 2018).As a world leader in research and technological innovation, the Ajinomoto group has an R&D network that links together with the R&D centers of Ajinomoto Co., Inc., and the other group companies of the Ajinomoto Group (Ajinomoto, 2018).Thus, due to the intensive investigation of the umami component by the Ajinomoto Group companies, Ajinomoto Peru launched an instant noodle line called Aji-no-men that represented a whole product innovation for the Peruvian market (Cueva, 2017). Despite the fact that the instant ramen soup is not a novelty worldwide, the presence of instant soup in Peru before Ajinomen was almost nil. Currently, this product is the leader of the country category (concentrating 90% of sales). Its success is being replicated in other markets such as Chile, Colombia, Bolivia and Panama. In addition, it recently made its entry to Suriname and Costa Rica. Many of these destinations have special varieties according to the tastes of consumers (Paan, 2014).
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4.5. Diagnostic of the model
Chen, Ender, Mitchell, and Wells (2013)explain: It is necessary to verify whether our model satisfies the assumptions of logistic regression because the results can be biased if the basic assumptions are not met.
First of all, it is necessary to specify what assumptions are needed to take into account.
Chen, Ender, Mitchell, and Wells (2013) made the next list of assumptions that our model needs to meet:
- The true conditional probabilities are a logistic function of the independent variables.
- No important variables are omitted.
- No extraneous variables are included.
- The independent variables are measured without error.
- The observations are independent.
- The independent variables are not linear combinations of each other.
4.5.1. Specification Error
According to Chen, Ender, Mitchell, and Wells (2013), building a logit or logistic model can be subject to two types of specification errors: First, the logit is not the correct function to use. Second, the model does not include relevant variables, the model includes variables that are not relevant and the combination of the predictors is not linear. However, the second specification error is the most important to solve, because the inclusion or exclusion of the correct variables become important in practice.
In order to do this, the research uses the test given by the software STATA on our third
In order to do this, the research uses the test given by the software STATA on our third