Introduction

A network is a set of central and peripheral nodes around which symmetric or asymmetric interaction relationships are established. In the first case, the central nodes are distanced from the peripheral nodes. The informational gap between the nodes is explained by the discontinuous transfer of knowledge. In the second case, the differences between the central and peripheral nodes are reduced to their minimum expression, facilitating the exchange of information.

In the educational organizational field, professional training is the process around which it is expected to develop the competencies that will allow the student to enter the labor market. In this sense, the collaboration agreements between universities and companies are aimed at adjusting the skills and knowledge of students to the requirements of the local and global market. This supposes symmetrical relationships between the participants since trust, cooperation, commitment, satisfaction and ease are indicators of an entrepreneurial training.

In contrast, when asymmetric relationships prevail over the members of a network, distrust, selfishness, dissatisfaction and stress emerge as a limiting paradigm of task and collaborative relationships.

In the present work, both relationships are analyzed from the speeches of professors inserted in a collaboration agreement between a public university and a for-profit organization. The analysis of the meanings around the knowledge network by teachers shows a work environment of asymmetric relationships. Around which the absence of professional entrepreneurship is a factor to consider when evaluating the effectiveness of the professional internship program.

Knowledge Network Theory

The theoretical frameworks that explain the behavior of knowledge networks through information and communication technologies have established as determining factors the evaluative principles, the beliefs about information and the normative principles of the socialization of the Internet and electronic devices. The relationship between these variables with respect to technological behavior has been established from the assumption according to which attitudes, perceptions and intentions are mediators of the impact of values, beliefs and norms on the use of a technological device.

The Knowledge Networks Theory (NRT) proposes that universities and companies are nodes of information exchange that become productive relationships through their knowledge exchanges, development of interdisciplinary projects and training flows ( Adenike, 2011).

Innovation, from the NRT, is an effect of the exchange of information between research and technology projects and the strategic planning of knowledge. In this sense, a knowledge network implies the collaborative participation of specialists and technologists around a productive-technological activity. Therefore, the configuration of a network is carried out from the organizational-collaborative structure between universities and industrial sectors (Borjas, 2010).

In terms of organizational networks, two types of knowledge converge: codified and tacit.

The first refers to productive relationships in which the communication of procedures, recruitment and training are responsible for implementing the mission and vision of the organization among human resources (Cerrón, 2010).

The second type of knowledge is articulated from the exchange of procedures not written in a manual, but transferred by more experienced personnel to new personnel. These are beliefs and values ​​around the execution of tasks, the use of technical equipment and production-distribution procedures (Coronel, 2010).

Both types of knowledge symbolize the construction of an organizational-labor-technical culture around which trust is essential. The NRT considers that in the absence of the trust factor, the configuration of a network could not be carried out since collaborative learning requires a distribution of responsibilities where those who do not follow the work dynamics or organizational climate are excluded (Cuesta, 2012) .

In this sense, knowledge networks require three conditions to survive: horizontal power, redistributed among the members of the network, and the burden of responsibility, aimed at each and every one of the members of the network. The solution to problems after configuring the network is in the network itself. For this reason, decisions are established through an induction mechanism rather than a selection mechanism (Díaz, 2013).

An essential factor of the network are the translators who have skills and knowledge about the needs of the operational staff and the requirements of the administrative staff regarding the strategic planning of goals (Gargallo, 2010).

If different languages ​​are considered between the growth needs of a company and basic research, translators are essential since their transdisciplinary training and their theoretical-applied experience are a link between entrepreneurs, administrators and staff (Gil, 2010).

Self-efficacy is a perception and / or a belief motivated by trials of personal or impersonal successes and errors carried out deliberately or discursively. Given that self-efficacy refers to failure, but mainly to success, even despite those failed trials that encourage achievement, the perception and belief of self-efficacy is based on the achievement of expected objectives rather than on competitiveness, recognition or learning vicar. If self-efficacy is a system of perceptions and beliefs focused on success, then the group to which the self-efficacy agent belongs or wants to belong is related to success. Because groups are diverse, self-efficacy varies based on this diversity. A competitive group attributes success to one of its members when he has exceeded previous achievements,which by the way were set by the group. In this sense, the concept of self-efficacy seems reliably adjusted to the influence of a group on the objectives, the system and achievements of an individual (Anwar and Norulkamar, 2012).

If self-efficacy is a system of perceptions that encourage achievement by delimiting effective capacities, self-efficacy would also be a system of perceptions and beliefs, but unlike self-efficacy, these would be oriented to the execution of a procedure or technology. The factors driving self-efficacy would be identical in the case of self-efficacy. If competitiveness, recognition, and vicarious learning drive self-efficacy, then self-efficacy would also have that drive (Arnau and Montané, 2010). 

Attitudinal psychological studies have focused on its conceptualization, formation, activation, accessibility, structure, function, prediction, change, inoculation, identity, and ambivalence. Attitudes have been defined from emotional and rational dimensions. Both dimensions are the result of experiences and expectations. This implies its structure: unidimensional or multidimensional that is configured in exogenous and endogenous factors. That is, when attitudes activate decisions and behaviors they cause a peripheral, emotional, spontaneous, heuristic and ambivalent process. In contrast, when attitudes transmit the effects of values ​​and beliefs on intentions and actions, they are endogenous mediators of a central, rational, deliberate, planned and systematic process (Berdecia, González & Carrasquillo, 2012). 

Psychological studies have shown significant differences between attitudes towards people and attitudes towards objects. The former refer to stereotypes or attributes and the latter refer to evaluations or dispositions. In both, ambivalence is an indicator of change when beliefs and evaluations interact, forming negative and positive dispositions towards the object. Conflicts are formed within the components formed by beliefs towards the object. Resistance to persuasion is a consequence of attitudinal ambivalence. If the environment threatens the formation and function of attitudes,These will adapt the individual to contingencies. Thus, attitudes have two essential functions: selfish and utilitarian (Cardon, Gregoire, Stevens & Patel, 2013).

There are three theories that use attitudes as a predictor variable of intentions and behaviors: Theory of Reasoned Action, Theory of Planned Behavior and Theory of Spontaneous Processing.

The Theory of Reasoned Action holds that attitudes mediate the effect of beliefs on intentions and behaviors. An increase in beliefs increases dispositions towards specific and deliberate decisions and actions. It is a process that goes from the general, in terms of beliefs, to the particular in terms of intentions and actions. However, the predictive power of general beliefs is limited by the specificity and one-dimensionality of attitudes. Since attitudes transmit the effect of beliefs, they delimit their indicators in dispositions likely to be carried out (Castel and Freundlich, 2010).

The Theory of Planned Behavior warns that the effect of beliefs on behavior is mediated by attitudes and perceptions of control. Faced with a contingent situation or event, the perception of control increases its predictive power of intentions and behaviors if and only if it interacts with specific dispositions. As the perception of control decreases, its relationship with attitudes makes a minimal effect on decisions predictable. Necessarily, the deliberate and planned process of decision-making and implementation of strategies requires a perception of control consisting of the dispositions towards the object (Castro and Martins, 2010).

The Spontaneous Processing Theory raises attitudes as a consequence of the activation of experiences with the attitudinal object. Attitudes are associations between evaluations of objects. A negative evaluation increases the disposition and with it the spontaneity of the behavior (Caykoylu, Egri, Havlovic and Bradley, 2011).

Attitudinal change refers to emotions and affects that are consequential to individual acts and for which people feel responsible. It is also about the social influence that teaching groups have on students. Or, the reception of persuasive messages aimed at central reasoning, or persuasive messages aimed at peripheral emotionality. In general, the attitudinal system is sensitive to the instability of the object and the cognitive variations that affect the consistency, stability, prediction, competence or morality of the individual (Celik, Turunc & Begenirbas, 2011).

The consistent change in attitudes is related to its multidimensional structure resulting from majority pressure. The diversity of dimensions implies a consistent construction of attitudinal change. That is, attitudes assume a function of internalized responses to constant situations framed by the mass media (Chiang, Méndez & Sánchez, 2010).

The attitudinal change is related to the deterrent principle of inoculation. Before the attack of persuasive messages, the perception of threats, risk and uncertainty is induced. In general, overexposure to persuasive messages induces high elaboration and thus persuasion. Massive delivery of persuasive messages, motivation, and consistent driving skills can lead to helplessness. That is, before the wave of information, people reduce their perception of control and tend to believe that events are immeasurable, unpredictable and uncontrollable. Or, individuals form an identity that consists of identifying with an administrative group in reference to a teaching group. In the process of helplessness, the individual builds the change of attitude and its reinforcement of hopelessness. In the identity process, it is the group that influences the person's attitudinal change. Helplessness is a process of self-validation or self-fulfilled prophecy. In contrast, identity is a convergent validation of group norms (Chinchilla and Cruz, 2010).

The social influence of the teaching group or administrative group refers to the majority norms and minority principles oriented to attitudinal change. The influence of the majorities fosters individual conformity and minority principles, conflict, and attitudinal change. Recently, the minority style has turned out to be the most permanent factor of social influence and attitudinal change. In other words, the construction of majority consensus seems to have an ephemeral effect and the construction of dissent seems to offer constant change (Díaz, Hernández and Roldán, 2012).

Studies of attitudes toward behavior have focused on their ambivalence. People try to balance the favorable and unfavorable information towards that dispositional object by maintaining ambivalent attitudes. That is, attitudinal objects are part of the environment in which people find themselves and their need to order, predict and control it. Therefore, although the attitudinal object is consistent with their perceptions, values ​​and beliefs, people must contrast these objects with the behaviors associated with them (Figeiredo, Grau, Gil and García, 2012). 

Education is a system of knowledge networks that make up a teaching-learning cycle. At the beginning of the educational cycle, knowledge networks are just a blueprint. Production strategies are guided by an emerging rather than dominant paradigm. It is about the plausibility of theories because knowledge is hardly supported by ideologies. The second stage of the educational cycle is peer evaluation, which consists of adjusting the projects to the policy of the administrative group. Later, in the third stage, the diffusion of knowledge is observed in institutional academic spaces (Fuentes, Herrero and Gracia, 2010).

Studies on knowledge networks warn that group formation and project planning are as important as trust and identity around an organization, institution or university (Fuentes and Sánchez, 2010).

The formation of groups has its origin in the social psychological processes of categorization, comparison, representation and social identity around which conflict and change are the foundations of knowledge networks (Galindo and Echavarría, 2011).

Conflict precedes change. These are asymmetric relationships between the members of a group in reference to members of another group considered as alien to the common interests of a group. The conflict emerges when the differences between the groups are evident (González, Sánchez and López, 2011).

In the case of UAEM students and Nissan employees, there is no underlying conflict since the transit from UAEM students to Nissan employees is perceived as normal and there is no disagreement in this regard (Guillén, Lleó and Perles , 2011).

However, the conflict emerges at the moment in which some of the students violate the internship regulations affecting knowledge transfers. Since the teacher-researchers are responsible for managing and training students in their insertion into the mission and vision of the organizations, they have to ensure compliance with the regulations and sanction those who violate the collaboration rules (Holden and Karsh , 2010).

In this space we can use a mathematical model called Predator-Prey, with this model we can measure the interactions between two species (seen from biology), we can apply them to encounters as follows:

No species lives in isolation and interactions between people provide some of the most interesting models. We present below a simple predator-prey system of differential equations where one species "eats" the other. In this model we have two quantities that depend on the weather. Our model then has two dependent variables that are both functions of time. In this case we will call the prey "students" and the predators "Nissan", and we will denote the prey S and the predators by Z.

The Lotka-Volterra growth model, also known as the predator-prey equation, is a pair of non-linear first-order differential equations used for modeling two interacting populations, a prey and a predator. The equations were proposed independently by Alfred J. Lotka in 1925 and Vito Volterra in 1926. Such equations are defined as:

Where:

 Z is the number of UAEM students;

 S is the number of contacts in the Nissan;

 dZ / dt and dS / dt represent the growth of the two populations over time;

 t represents time.

To formulate this model in mathematical terms, we need four additional parameters to our independent variable t and to our two dependent variables S and Z. The parameters are:

 α, β, γ and δ are parameters that represent the interactions of the two groups of people.

 α: Coefficient of the acceptance ratio of UAEM students

 β: Proportionality constant that measures the number of Nissan Student- Worker interactions in which the policies are applied to students.  

 ϓ: Coefficient of the rate of decrease of NIssan Policies

 δ: Constant of proportionality that measures the benefit of the population growth of the Nissan group with respect to the accepted students (Blanchard 1998: 11-12).

Another type of conflict, the one related to innovation defined as the influence of a persevering minority in their actions with the intention of persuading or dissuading an administrative group. It underlies the interior of the organization or the university, it is the conflict in which the students involved perceive a greater use of their capacities and resources. Consequently, they demand greater management and training to achieve objectives focused on administrative-technological innovation (López and López, 2011).

On the other hand, change is a consequence of conflict. It is a process in which conversion precedes persuasion that activated a conflict and a central or peripheral attitude of need for cognition (Molero, Recio & Cuadrado, 2010).

The attitudinal change around the questioning of convictions, alludes to a dissuasive process in which the information can be rationalized or emotional. In the first case, the need for cognition can lead to a dissonance in which the information does not match expectations. In the second case, the information fosters emotions that increase expectations towards the informational-attitudinal object (Morales, Ariza, & Muñiz, 2012).

In this sense, change is also synonymous with conversion in which attitudes towards an object lead to a modification of the individual's behavior towards the group (Ríos, Téllez & Ferrer, 2010).

In the case of knowledge networks, conflict and change are essential processes to understand the barriers and the facilities of knowledge transfer between symmetric and asymmetric groups around the information of an object, process, institution or organization (Rodríguez, Retamal, Lizana and Cornejo, 2011).

Individuals establish categories, comparisons, identities and representations around themselves in relation to members of a group and in reference to other individuals belonging to other groups (Rojas, García and García, 2011).

By establishing benchmarks, conflicts within an academic group can be transferred to conflicts between organizational groups. This is the first step for the delimitation of identity or belonging to a group (Shrrof, Denenn and Ng, 2011).

The intra- and inter-group categorization consists of a set of perceptions around the resources, abilities and capacities within a group in reference to another group. If perception is the biased ordering of objects, groups and their individuals, they skew their appraisals when evaluating their actions and those of others. This is the case of the attribution bias around which individual perceptions attribute achievements to their abilities and attribute their failures to the abilities of others (Sobrados and Fernández, 2010).

In both cases, UAEM and Nissan construct attributive biases in which knowledge is compared in relation to its application to categories of specialization or strategic planning of knowledge. This process is also inherent in the teaching and administrative groups around the knowledge transfer system (Tayo and Adeyemi, 2012).

After categorization and comparison, identity underlies. These are membership decisions based on biased attributive judgments. If a student perceives greater possibilities for personal growth in a group to which he does not belong, he will decide to change or convert his ideas to those of the favored group. In this sense, the knowledge network would be the one most favored by individual judgments and attributions. At this point in the group formation process, two types of reference are built: teaching group and administrative group (Teh, Chong, Yong, and Yew, 2010).

The administrative group builds its identity underlying the capacities of the teaching group. In other words, the constitution of a knowledge network is not only carried out from the perceptions of capacity of the members of a group, but also from the perceptions of disability of the teaching group (Vargas and Arenas, 2012).

To the extent that an administrative group skews its evaluative judgments, it transfers its conflicts to the teaching group. Perceptual bias turns into attributive bias and ends up as selective bias. By focusing the bias on the teaching group, the individual from the administrative group builds a network of representations around which the capacities, resources and limits of the administrative group are interpreted in reference to the teaching group (Yáñez, Arenas & Ripoll, 2010) .

The representation of the teaching group competences supposes an evaluation of their behaviors by the individual and their teaching group. It is a set of emotions and cognitions around the causes of the teaching group's actions compared to the actions of the administrative group. That is, individuals only want to observe the acts that contradict the administrative group and try to minimize their effects on people's decisions (Zampetakis and Moustakis, 2013).

To the extent that the individual has contact with the teaching group, he increases his emotions and cognitions around the actions of the teaching group. Precisely, from these experiences, it is possible to infer attitudinal processes that explain the exclusion of the teaching group because they are attributed different resources and capacities compared to the administrative group (Yuangion, 2011).

In this exclusion process, the emotional-cognitive-behavioral consistency that explains the differences between the groups underlies. If the administrative group excludes the members of the teaching group, then it will have shown a high consistency that threatens the consistency of the administrative group. Therefore, individuals who belong to an administrative group tend to see significant differences with respect to the teaching group and its members (Vargas, 2011).

However, the consistency of the administrative group is biased when compared to the teaching group since a biased idea can only be a prejudice rather than an argument (Prada, 2013).

In the field of knowledge networks, the consistency of the administrative group and the teaching group is incompatible. For a knowledge network to work, an administrative group is required that can link their knowledge with a teaching group inconsistent in their emotions, cognitions and actions, reasons for which, the transfer of knowledge from the administrative group would justify the synergy of groups because it remedies the inconsistency of the teaching group. This process can also be observed if the administrative group is inconsistent and the teaching group is consistent (Orantes, 2011). 

However, individuals who perceive emotional-cognitive-behavioral inconsistency around the production of knowledge in their administrative group end up migrating to the teaching group since it will allow them greater personal growth. This migration process is of an emotional-cognitive nature since the emotions around the teaching group produce aversion to the administrative group, affinity and adherence to the teaching group (Omar, 2010).

Translators, those who have the knowledge, capacities and abilities to manage synergies between the administrative group and the teaching group, tend to look for data that corroborates their knowledge management. However, inaccessibility to the teaching group prevents knowledge management, the formation of synergies and the transfer of knowledge. If individuals have restricted access to a teaching group, they can mimic it with the administrative group and fall into the assumption of natural compatibility of the knowledge of both the teaching group and the administrative group. The consequence of this compatibility will be the inhibition of the knowledge network and its turning into corruption, simulation or nepotism around the production and transfer of knowledge. That is, an increase in inaccessibility to the teaching group increases the probability of failure of organizational, scientific and technological programs between the administrative group and the teaching group (Medina, 2010).

Translators, as knowledge managers, are mediators of relationships between teachers and students. When the organizational climate between the administrative group and the teaching group turns into ambiguity and adversity rather than transparency and loyalty, those involved in knowledge networks manipulate the information to pursue their interests, translators must persuade both groups of the unsustainability of their relationship. It is not enough to diagnose group differences, it is also essential to reduce risks and uncertainty by enhancing the benefits of each link and node of the knowledge network (Manning, 2010).

Now, the affective-behavioral consistency between both groups implies creativity which introduces an innovative dynamic to both groups. It is a flexible organizational climate in which ideas around the production and transfer of knowledge are potentiated. Given that knowledge networks are diverse, in each link or node it is necessary to heterogenize the production and transfer of knowledge. To the extent that the organizational climate is soft, it increases trust and identity within both groups (Long, 2013).

Trust and identity are the result of a type of persuasive information known as beliefs and the organizational environment in which beliefs are disseminated is known as attitude towards the knowledge network, its members and processes. An increase in information related to the network increases the certainty, production and transfer of knowledge. In contrast, the decrease in information inhibits the group relationship. Consequently, collaborative and innovative relationships have an impact on productivity, however, stress such as exhaustion, depersonalization or frustration can emerge as a result of the increase in productive demands (Gil, 2010). 

State of Knowledge

However, more recent research has shown that the socialization of information in knowledge networks spreads its effect on perceptions of utility and risk, as well as on attitudes related to anxiety and addiction to networks, the main determinants of behavior.

In this way, technological behavior is determined by the processing of information around a knowledge network. This effect, being mediated by collaborative decisions, increases the predictive power of beliefs about task and interpersonal relationships in an organization (Adenike, 2011).

On the other hand, collaborative intentions suppose attitudes of trust, perceived capacities and informative beliefs that, when interrelated, determine the decision-making favorable or unfavorable to a group of knowledge (Borjas, 2010).

However, the knowledge construction process would not be feasible without the formation of trust attitudes in which collaborative groups disseminate information that will be categorized into learning or motivation tools aimed at achieving objectives and goals (Cerrón, 2010).

In parallel, the perceived capacities complement the formation of categories of information since it is about skill and knowledge around the construction of a professional training network (Coronel, 2010).

However, some studies suggest that professional training and the construction of a network are different processes since they assume selfish values ​​that contradict altruistic values ​​(Díaz, 2013). It is a series of group norms around which individuals are professionally trained, or are emotionally oriented when forging an identity (Cuesta, 2012). However, it is the socialization of the information that will determine the behavior of an individual in a collaborative group (Gargallo, 2010).  

Relationship Specification

However, the model used by the state of knowledge by assuming that the socialization of knowledge consists of general information beliefs, supposes general effects on each of the mediating factors of its relationship with behavior. Therefore, the specification of the behavioral dimensions could indicate that there are other intermediate factors with respect to socialization.

These are eight indicators of technological behavior which explain the formation of a collaborative group based on information processing.

In the case of trust, technological behavior is indicated by collaborative relationships in which the benefits would not be based on costs, but rather derived from interdependence when carrying out a specific task (Gil, 2010). In other words, professional training that involves the intensive use of technologies comes from symmetrical relationships that a group establishes to distribute skills and disseminate knowledge. These are committed relationships since if a member does not develop work skills, then they will be excluded from a group that has established a culture of high productive quality (Long, 2010). In this sense, collaboration is the result of shared objectives, while individualism would be an effect of the goal system that rewards personal effort (Manning, 2010).

In the case of cooperation, unlike simple normative collaboration, technological behavior implies specialized skills and knowledge for the fulfillment of purposes. That is why groups are forced to establish cooperative relationships since the group itself must exchange information, process strategies or implement techniques that involve continuous support among its members (Medina, 2010). 

However, another indicator of technological behavior is the empathy between its members since intensive work and the achievement of objectives or the fulfillment of goals implies affective and emotional relationships to reduce personal conflicts to the absence of communication (Omar, 2010).

Regarding solidarity, unlike collaboration or cooperation, it involves professional training based on the dynamics of collaborative teams within the knowledge network. While collaboration and cooperation are determined by social values, solidarity goes beyond the normative or evaluative principles that unite groups, it is an awareness of scarcity and uncertainty that allows anticipating situations of shortage by sharing resources (Orantes , 2011).

Consequently, propensity for the future is the result of supportive behaviors that anticipate risk scenarios. Indeed, collaborative groups are motivated by prevention and coping strategies in the face of unfavorable situations for groups with whom they share objectives and goals (Prada, 2013).

Finally, the quintessential indicator of technological behavior is entrepreneurship or dissident spirit. In effect, the use of a technology and even more so the formation of collaborative networks would not make sense if profits were only pursued in the short or medium term. Vocational training consists of anticipating scenarios of scarcity, risk and uncertainty for which knowledge groups form networks that are essentially entrepreneurs, dissenters from the situations that are coming or the catastrophes that are expected (Vargas, 2011).    

What symbols, meanings and meanings are developed in a knowledge network established by a public university, a set of organizations oriented by values, norms, beliefs, attitudes, perceptions, skills, knowledge, intentions and behaviors closely linked to information and communication technologies What do specific task organizational styles entail?

Discussion

The public university, from its foundation, assumed a critical identity towards the productive-lucrative organizations, companies and industries were perceived as spaces of labor exploitation and ideological alienation. For the most part, the organizations had a perceptual bias that identified them as scenarios of production of surplus value that would come to implement automated processes replacing operational personnel and leading to massive unemployment.

However, the benefits granted by the State and the organizations, the unions reflected as inalienable achievements; 8-hour working hours, medical coverage, pension security, profit sharing and training to improve wages.

Between social benefits and union conquests, a collaborative climate emerged in transnational companies and a conflictive climate in local companies. In the case of automotive companies, each and every one of them activated by foreign capital with a minimal participation of national capital, adapted organizational models from their parent companies in their countries of origin. This was the case of Nissan, which was located in Mexico at the end of the 1950s and whose influence in the maquiladora and sales sectors has been decisive in the growth of the country's productive and service economy, mainly in the city of Cuernavaca, Morelos, the automotive company has its main outlets.

The relationship between university and business has a long tradition since universities and human resources departments have implemented training programs, training and exchange of scientific and technological information with their university counterparts.

In the case of Nissan, updating production processes offers opportunities for collaboration with institutes and universities. Specifically, the areas of automotive engineering and human resources have built collaboration synergies to update knowledge and even innovate technology transfer processes as well as organizational development.

In this sense, Nissan and both public and private universities have developed strategic scientific-technological training programs through scholarships or financing contests that have resulted in internship programs for students and, at the end of these, a contract.

In the city of Cuernavaca, the UAEM has managed to strengthen collaborative ties between the institution and the franchises that distribute semi-new cars and maintenance of auto parts. Being a city in which the service sector predominates more than the maquiladora sector, the direct sales branches to the client have asked the UAEM the possibility of training students in their areas of human resources and sales to form collaborative teams of workforce. sales in each branch that is projected to expand in an increasingly competitive market.

This is how the relationship between UAEM and Nissan has proliferated since 2005, the year in which the curricula of the faculties were modified to strengthen collaboration with automotive and service franchises in general.

The current study plan includes comprehensive training for the student. Carry out your professional practices and theoretical training at the university. These are two phases in which the student can carry out basic research on the organizational climate and its intervention for organizational change.

This study aims to explore the knowledge transfer process without considering its internal organizational aspects, but rather, those in relation to the collaborative processes between UAEM and Nissan.

Regarding professional practices and social service, the professors in charge of coordinating the scientific-organizational collaboration, manage the schedules and spaces for training and knowledge transfer. Once the link is established through the exchange of information regarding the number of vacancies and the demand for internships. The teacher draws up a list of priorities and proposes courses that encourage areas of opportunity.

For their part, the student makes a field diary where he highlights the characteristics of the vacancy and asks the teacher for training in the skills that, in his opinion, would allow him to perform better.

However, the student also covers four hours of training practice in which he helps the tutors of areas in administrative tasks; motivation, training and education. The university recognizes organizations, administrative staff, research professors, and practitioners for their participation in extracurricular activities. 

Finally, within the inductive process, companies offer temporary contracts to interns. This process has allowed the increase of graduates who entered the labor market before graduating.

The knowledge transfer process would have its main limitation in the update and evolution of the transfer or professional practice system since the permanent update will allow to correct the decrease in sales and the increase by hours / sales.

It is also important to consider that the system depends on the degree of teacher specialization who assumes a fundamental role in the construction of explicit and implicit knowledge to face the challenges of the knowledge transfer system.

The sponsorship of the system is the responsibility of the UAEM. The payroll of teachers and scholarships to students are absorbed by its budget.

The technology transfer process would have its greatest success in the UAEM-Nissan synergy since the key administrative staff are graduates of the university and each year interns are incorporated.

However, the analysis of knowledge networks can not only be located in institutions or organizations, it can also be considered training sessions and training that teachers give to practitioners.

Regarding extracurricular training, the UAEM organizes events to update and discuss knowledge around the training of competencies, self-efficacy among them.  

The UAEM-Nissan knowledge network includes three actors: administrators, teachers and students. Strategic planning, alliance management and professional practice correspond to each group in the network.

Such a network organization system is for teachers a simulation of knowledge when mistrust and uprooting appear within the administrative group. However, when trust and identity around the administrative group emerge, the production and transfer of knowledge cannot be certified by teachers outside the network, skewing scientific-technological quality.

The knowledge network between UAEM and Nissan includes hierarchies circumscribed to teachers such as translators, researchers, managers, advisers and evaluators of the UAEM-Nissan knowledge network

Teachers ensure that strategic planning inhibits conflict and organizational change since it facilitates the simulation of management, production and transfer of knowledge by not establishing development parameters for organizational culture, knowledge management, cognitive processes and complexity of the network. This results in a supply and demand determined at the discretion of Nissan rather than the UAEM translators. 

The management, production and transfer of knowledge is based on organizational theoretical bases avoiding complex processes of conflict and organizational change with a view to the innovation of knowledge rather than its simulation and reproduction.

The translators point out the need to reduce the uncertainty of the UAEM-Nissan alliance from its collaborative regulation. For this purpose, they emphasize the preparation of reports for the administrative area to make decisions aimed at strategic planning around alliances with organizations that meet the minimum requirements for professional practice.

However, the translators are self-critical when pointing out that they do not have sufficient management skills to identify those organizations with whom the production and transfer of knowledge would be managed.

Trust and identity would be the main barriers of the knowledge network since translators, when managing knowledge, do not establish the criteria for the production and transfer of knowledge necessary to encourage a climate of relationships and tasks.

Regarding the transfer of knowledge, the UAEM-Nissan relationship seems to be based on an academic pragmatism: the simulation of knowledge. In other words, the transfer of knowledge is weighted by indicators of efficiency, efficacy and effectiveness that are not always sufficient to demonstrate the evolution of a system of scientific-technological thought or innovation.

Efficiency is considered as the achievement of objectives and goals established by administrative group in comparison to the participation of the teaching group in a knowledge network. Upon initiating the transfer system, graduates or interns move from social service to professional practice until they are hired. This process is considered as an indicator of terminal efficiency. However, the Knowledge Network Theory explains that since a hiring is determined by the formation of administrative impressions and opinions, there is an underlying bias of the administrative group that would consist of hiring the social service provider for the simple fact of having demonstrated their capabilities , skills and knowledge in a group or work area without having weighed their productivity and its impact on the growth of the organization.

This is the preamble to a monopoly knowledge simulation system since conflict is reduced by being replaced by a collaborative environment of perceptual rather than conceptual or technological exchange.

In this sense, the evaluation of the knowledge network should not only be limited to self-report, but also to the achievement of objectives and their economic, political, social, institutional and organizational impact. That is, the evaluation of the network corresponds to its most basic and specific aspects around those factors that influence the network.

Efficacy is considered as obtaining the objectives without taking into account the procedures that imply the means to achieve such ends. These are indicators of attendance, punctuality, performance, and extracurricular activities.

The UAEM-Nissan network establishes its effectiveness based on the number of interns and interns who manage to graduate, elaborating the diagnosis of the professional practice area or social service. Said report is permanently evaluated by the professors-researchers and knowledge managers through seminars and consultancies. Precisely, it is at this point in the transfer of knowledge when the teacher discretionally defines the qualification of continuous use and with it, the evaluation of the effectiveness of a process inherent to the knowledge network. As there is no external opinion to the network, the teacher's weighting loses relevance.

It should be noted that the UAEM only has the certifications of its faculties through its study plans who are under permanent scrutiny of disciplinary associations. However, the academic associations do not evaluate, much less determine, the agreements and alliances between the UAEM and the organizations around which the students aspire to carry out their professional practices and social service.

From the Theory of Knowledge Networks it is possible to explain the discretion wielded by teachers on terminal effectiveness. Being a characteristic attributed to the administrative group in comparison to a teaching group, individuals skew their perceptions about a high efficiency of the administrative group with respect to a low efficiency of the teaching group. Teachers bias their evaluation of the thesis or terminal report of the intern or intern. Such bias is determined by the teaching group rather than the administrative group. If the teaching group is highly competitive, the teachers will establish a series of beliefs within the administrative group about their ability to command. Such capacity consists of an image of authority in front of the administrative group compared to the leader of the teaching group. The image of the teacher in front of the administrative group is more important than their knowledge and skills. The attribution that the teacher makes by his students defines the teacher's evaluation always in comparison to the leader of the teaching group. If the teacher has a consistent image between his actions and speeches, he will generate an influence on the administrative group who expect a level of transfer and demand for knowledge. 

Once an image and its corresponding attribution have been constituted, the teacher assumes the role of researcher, manager, trainer and evaluator. When evaluating the thesis, the final product of the knowledge network, the teacher establishes his criteria based on his self-concept. If the teacher supposes having a strict image in his administrative group, then he will seek to weigh the method and results of the thesis with a higher percentage than its epistemological-theoretical aspects. 

In short, attribution and self-concept inhibit conflict for nonconformity, creativity and innovation around the production and transfer of knowledge.

Finally, regarding the effectiveness defined as the impact of cost reduction and profit maximization on the production and transfer of knowledge between the administrative group and the teaching group. The UAEM-Nissan network, supported by the discretionary decisions of teachers, introduces a mechanism for the production and transfer of extracurricular knowledge that mainly benefits practitioners and social servants.

It should be noted that teachers and students have had the opportunity to share knowledge in regular courses of the curriculum of each discipline. However, because the priority of curricular courses is to reproduce knowledge on a theoretical level, the opportunity to investigate and intervene in a real setting is limited. For this reason, professional practices and social service are an opportunity to encourage future research and intervention cadres with an emphasis on profit-making organizations. Research in these areas is limited and the UAEM-Nissan network comes to fill the gaps in terms of data and training planning for future employees of a sales branch. In terms of teaching-learning, students seem to value extracurricular activities since teachers are constantly monitoring and evaluating their performance, which cannot be done in curricular sessions.

This study has analyzed the UAEM-Nissan knowledge network based on its management, production and transfer. Efficiency, efficacy and effectiveness are indicators that reveal the importance of teachers as translators of scientific-technological and tacit knowledge.

However, it is the teachers who in their speeches notice a simulation of knowledge when mistrust and uprooting underlie their functions as researchers, translators, managers, advisers and evaluators.

The processes of the UAEM-Nissan alliance, production, management, transfer, evaluation or simulation of knowledge, are explained by the TRC as they are considered as results of the asymmetric relationships between the administrative group made up of teachers and the teaching group made up of administrators and students. If the administrative group is compared with the teaching group, it constructs an attributive bias of higher capacities and resources in the administrative group and lower ones in the teaching group.

Within the administrative group, this research has revealed the teacher's self-concept as the symbol that provides evaluation criteria for strategic planning, knowledge management, job training and professional practice.

However, the speeches of administrators and students must corroborate, adjust or contradict the statements of teachers. In this sense, the CRT would explain psychosocial processes; categorization, comparison, identity, representation and attitude inherent to group dynamics. Since the teachers discretionally evaluate the UAEM-Nissan network and even deliver reports and research reports, the management, production and transfer of knowledge is biased despite the academic level of the teachers and the certification of the UAEM curricular system as well. such as Nissan's organizational growth rates.

According to teachers, an evaluation system is required in which training and professional practice are weighed based on trust and identity.

In this sense, the management, production and transfer of knowledge would not depend only on the discretion of teachers, but also on the weighting of the system based on its efficiency, effectiveness and above all: effectiveness.

Precisely, trust, identity, conflict, creativity, innovation and effectiveness seem to be substantial elements of a positive psychosocial process of specialization for the management, production and transfer of knowledge. Since a network is made up of administrative groups and teaching groups, it requires climates of relationships and tasks in which the conflict encourages creativity and innovation.

On the contrary, if mistrust and uprooting are underlying, the simulation is based on the conformity and complicity between administrative groups and teaching groups when producing and transferring knowledge to future generations.

Conclusion

Professional training in a knowledge network supposes the construction of an identity focused on the intensive and specialized use of information technologies based on an organizational culture of entrepreneurship. This explains the meanings that the agreements between the university and the organizations imply for teachers and administrators, but it opens the discussion around the discretion of these agreements since they seem to be focused on obtaining short-term goals. In this sense, the implemented social and professional service program has been effective since it inserts the student into the organization, adjusts their skills and knowledge to the labor policy and directs their values ​​to the requirements of the position.

However, administrators and teachers seem to disagree regarding the training of students since the former anticipate an entrepreneurial profile while the latter hope that the practitioner or social servant will win a position and open the possibility of directing another student by displacing the academic training short term. 

It is necessary to delve into the meanings that both groups in conflict have regarding professional training, entrepreneurship, quality of life and social responsibility inherent in local business organizations. This will allow anticipating contingency scenarios in which the university could establish strategic alliances to remedy the shortage of training and job opportunities that lies ahead.