# Research on the Efficiency Evaluation of Cross-Organizational Knowledge Synergy in Industry University Cooperation Based on BP Neural Network Algorithm

Authors: Li Jing
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

The difference of decision-making knowledge among members is conducive to the successful realization of group cooperative production. In the actual production, if the different knowledge environments between organizations can cooperate and penetrate each other, the common knowledge of groups can be formed, which is a key step to successfully solve the social and economic problems of public resources. The final efficiency of cross-organizational knowledge collaboration is the key to measure the success or failure of collaboration. Because the cross-organizational knowledge synergy efficiency of industry university cooperation is the result of the cross-influence of many factors, the general linear regression model is difficult to describe the relationship between these influencing factors and knowledge synergy efficiency. Based on the analysis of the importance of cross-organizational knowledge sharing efficiency evaluation of industry university cooperation, this study constructs the efficiency evaluation index system from different angles. At the same time, based on the field investigation of the index system, BP network model is established to effectively evaluate the collaborative efficiency.


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## Body

## 1. Introduction

For a single member, how to make a decision or what kind of decision to make mainly depends on the decision-making knowledge of a single member, and even the decision-making environment will affect the result of the decision. In real life, it is not difficult to find that some people are good at calculating and free riding. Events like this can be seen everywhere, but more often, some people or organizations cannot calculate clearly, so some people will introduce to others the benefits of new collective action and how to take collective action. The main reason is that some people do not really understand the interests, so there must be “understanding people” to tell the interests. In fact, as far as public resources are concerned, the decision-making state of individual members can be summarized as whether there are new collective action reserves and whether there are payment expectations of prisoners’ dilemma, which are the decision-making knowledge state of individual members [1]. Obviously, there must be knowledge differences among members, which is mainly reflected in the distribution of new knowledge and collective action cooperation strategy, because this is a necessary condition for realizing knowledge cooperation, which is embodied in the following two aspects: first, if there is no such new knowledge, it means that there is no knowledge gap between members, so it is difficult for a single member to spontaneously invest. The noncooperative equilibrium of individual decision-making has nothing to do with the degree of knowledge. Second, if there is this new knowledge gap and this new knowledge is widely distributed, it will be conducive to the development of individual spontaneous investment, so as to realize cooperative production and supply [2].It can be seen from the above that before the formation of new common knowledge, some “ignorant” are not free riders in the real sense [3]. If they are punished too early, they will bring more serious consequences, which cannot be ignored. Therefore, in the process of transforming the obtained information into new common knowledge, some members must determine the accuracy and timeliness of the information, because it will directly affect the formation of new common knowledge and is also an important link that cannot be ignored. In the next process of the formation of new common knowledge, the heterogeneity of other dimensions will play a leading role, which cannot be replaced in the formation of collective cooperation strategies and benefited new knowledge. Taking the preference difference between members as an example, for members, the greater the difference, the smaller the difference between the output levels of public resources cooperated by members, and the supply of public resources will be borne by the members with larger preference [4]. If the output level is larger, the members providing supply will tend to be consistent. Although there is a monotonous relationship between one-dimensional differences and cooperative production, it is also possible to play the same role under the joint action of multi-dimensional differences [5].With the advent of the era of knowledge economy, a single enterprise is also unable to learn and create knowledge. The specialized division of labor of knowledge learning and innovation based on the enterprise is becoming more and more obvious. Only through specific business experience and coordination of low-cost industry university cooperation can enterprises continuously acquire and accumulate proprietary knowledge. Therefore, as mentioned above, how to choose partners, efficient knowledge collaboration in the alliance, and the ability to continuously accumulate and create new knowledge are of great concern to many enterprises in the process of participating in the inter-organizational knowledge collaboration of the alliance, and it is also the core of collaboration efficiency [6].


## 2. Influencing Factors of Efficiency

### 2.1. Organizational Difference Elements

In general, the realization of cross-organizational knowledge collaboration of industry university cooperation often occurs between organizations with equal knowledge stock and knowledge collaboration ability. However, due to the problems of information asymmetry and entry barriers of industry university cooperation itself, there will be obvious deficiencies in distinguishing the knowledge synergy ability of its member organizations. For example, a series of problems such as organizational knowledge management system, knowledge stock, knowledge coding degree, knowledge staff quality, and corporate culture are difficult to make accurate judgments in a reasonable time [7]. If the knowledge collaboration capabilities of member organizations differ greatly, it will increase the transaction cost, lead to disharmony in the collaboration process, reduce the value of synergy, and then reduce the efficiency of knowledge collaboration. On the other hand, due to the different survival and development environment of different member organizations, their knowledge stock is different, and the paths of knowledge learning and knowledge accumulation are also different. Therefore, there are differences in the knowledge required by different projects in industry university cooperation [8]. This gap often leads to the inconsistency and knowledge conflict of partners, improves the transaction cost, and affects the synergy efficiency. For example, in the collaborative innovation process of the atmospheric pollution control alliance initiated and established by environmental protection, there are relatively complete agreed terms before technology research and development to avoid subsequent income disputes [9].In the initial stage of industry university cooperation, member organizations are often unfamiliar with each other, and there are differences in the overall cognition of knowledge synergy, especially in the expectation of synergy benefits. This is because each partner will recognize, assume, design, and specify the key issues of the whole knowledge sharing according to their past experience, which may eventually lead to cognitive differences among partners on many issues. It is manifested in the differences in the expectation of cooperation objectives, the expectation of benefit acquisition, the confidence of cooperation, and the understanding of knowledge itself. Therefore, in order to improve the efficiency of collaboration, the selection of partners in cross-organizational knowledge collaboration of industry university cooperation is more critical, and the matching and collaboration among member organizations are the main factors to be considered [10].Due to the implicit characteristics of knowledge, the private knowledge owned by knowledge employees participating in cross-organizational knowledge collaboration is often difficult to measure, which will bring unpredictable results to the efficiency of knowledge collaboration. On the one hand, employees with richer knowledge have better overall knowledge structure and stronger ability to modulate and absorb knowledge. In the process of participating in knowledge collaboration, they have stronger learning ability and faster speed of acquiring knowledge, and are in an advantageous position and higher benefit in collaboration, which is the expected goal of all alliance organizations [11]. However, due to the complex environment of knowledge collaboration, some knowledge workers are prone to leakage of private knowledge, resulting in collaboration failure or infringement of organizational intellectual property rights. Therefore, the cognitive structure and psychological structure of employees will be analyzed to make a reasonable impact on their cognitive and collaborative response to knowledge structure.


### 2.2. Risk Elements

At present, under the condition of market economy, the possibility of opportunistic behavior increases in order to maximize interests and minimize costs. This opportunistic behavior is embodied in the following aspects: first, in terms of technology and intellectual property rights, there is a potential competition between members in the same alliance. Sometimes, some members will steal the core technology of other members, thus weakening the competitive advantage of competitors; in terms of cooperation, some members of the alliance hold a negative attitude toward the operation of the enterprise, which cannot guarantee the quality of the project, so it brings irreparable losses to the alliance; in terms of credit, due to the imperfection of the overall law of the alliance, the members unilaterally broke the contract, falsely reported information, leaked secrets, and other acts, resulting in the leakage and misappropriation of knowledge, leading to the disintegration of the alliance; in terms of incentive, when the benefits obtained by alliance members are not commensurate with the risks they bear, they will take measures to damage other members of the alliance, so as to maximize their own interests. The existence of the above behavior directly affects the interests and ultimate goal of the alliance, and even poses a threat to the cooperation among the members of the alliance, thus affecting the stability of the alliance and causing the risk of disintegration of the alliance.As shown in Figure1, the cause of alliance opportunistic behavior and alliance relationship risk is the specificity of enterprise technology assets. For the development of the enterprise alliance, a special investment must be set up for the technology research and development of the alliance. For example, in order to ensure the smooth progress of the project, the alliance must provide some professional technical talents and management personnel. If the human resources of the enterprise cannot meet the demand, it will directly affect the progress of the project. Therefore, the human resources department should strengthen the training of talents in this field; therefore, funds must be injected into the decision. In practice, the technology alliance does not agree that enterprises have business exchanges with enterprises different from itself, because the enterprise technical standards, enterprise culture, internal information exchange mode, and R&D operation form must be suitable for the corresponding adjustment of partners. At the same time, in order to meet the R&D requirements of enterprise projects, enterprises must provide professional equipment. All these require investment. These investments only have high value within the alliance and small value to the outside world, which is the so-called specific transaction investment [12].Figure 1
Conflict risk of knowledge collaboration.Therefore, enterprises’ choice of alliance operation mode mainly takes into account the stability of the alliance, which is the choice that alliance member enterprises have to face. The utilization and protection of resources by enterprises can reflect that enterprises have to face the integration and protection of resources in the alliance, which is the trade-off made by enterprises in a dilemma, and the existence of opportunistic behavior is a major obstacle to this. Therefore, the choice of alliance operation mode is the response of alliance enterprises to opportunism and alliance risk relationship [13].


### 2.3. Environmental Elements

Environment is the element of any activity. Obviously, the efficiency of inter-organizational knowledge synergy of industry university cooperation is also affected by the environment, that is, the interactive environment among alliance members. In essence, industry university cooperation is an economic community, which is composed of multiple enterprises or institutions within a certain space. Industry university cooperation contains rich knowledge, which includes various types of knowledge activities. These activities mainly include knowledge acquisition, learning, and creation. This is a complex activity, in which knowledge innovation is the foundation, knowledge transfer is the key, and the application of knowledge is the key. Such a structural form determines the enrichment of the content of knowledge activities, and knowledge innovation is the core of knowledge activities. From the perspective of system engineering, the knowledge, knowledge activities, and its management process contained in industry university cooperation are a complex system, but it is a knowledge collaboration system [14].Industry university cooperation is an organizational form with “local embeddedness,” “spatial agglomeration,” and “industrial relevance.” It is not only a social system, but also an economic system. From the perspective of social technology system, industry university cooperation is also a technical system, so it is a technical, economic, and social system. The technical activities and economic activities of industry university cooperation are affected by various factors, which makes the relationship between them more complex. The reason is that they are affected by cultural and social factors. Therefore, to a more accurate extent, industry university cooperation is not only a technical system, but also a social and cultural system. These two systems have their corresponding networks in technology alliance, namely, value network and social network [15].With the continuous development of economy, no knowledge system of industry university cooperation can maintain its own operation, which means that the technology alliance itself cannot carry out knowledge activities in a “closed door” way. It must widely absorb foreign knowledge and supplement its own shortcomings, so as to form an inseparable and close relationship with foreign knowledge. In this way, industry university cooperation can timely absorb the latest scientific and technological knowledge and production and management information, so as to overcome the problems faced by industry university cooperation in operation and promote itself to take the road of sustainable development. To sum up, a complete knowledge collaboration system of industry university cooperation must be open.


### 2.4. Behavioral Elements

There are both interdependence and competition among members of cross-organizational knowledge collaboration. The reason why industry university cooperation can exist is that in order to maximize the interests, members can reach a collaborative relationship in the form of collaboration, so as to better seek interests. Therefore, members of technology alliance need to apply this way of collaborative cooperation to complete difficult tasks in this complex environment. This mutually beneficial relationship between members has formed a trend. This relationship is mainly maintained by the equal coordination relationship between organizations, not based on the price mechanism, which has laid a solid foundation for the stability of industry university cooperation.Behavior mechanism is the mechanism to deal with the relationship between organizations. Because many knowledge resources in the organization are often secret, if you want to obtain the secret knowledge resources of other organizations, you must consult with them to reach an agreement, and the behavior mechanism plays a vital role in this process. The behavior mechanism can not only make the members of industry university cooperation better use of their own learning resources, but also promote the harmonious relationship with other organizations. Especially in this social network, the exchange and flow of knowledge resources must rely on a certain mechanism for protection, so as to efficiently transfer knowledge resources and form a good speed of cooperation.The transfer of knowledge resources cannot be directly applied to the recipient, it needs to be sorted and reconstructed, so the coordination and cooperation between the two sides can promote the improvement of knowledge synergy efficiency. At the same time, it can also improve the speed of knowledge collaboration, so as to promote the establishment of knowledge resource sharing among industry university cooperation members and make the collaboration of knowledge resources more convenient. Through the corresponding cooperation adjustment, it can promote the cooperation and exchange between the members of the technology alliance and increase their understanding of each other. At the same time, it can also promote the members to be familiar with the industry terminology, professional vocabulary, communication language, and common transaction rules, so as to ensure the smooth cooperation between the members of the industry university cooperation. The adjustment of industry university cooperation norms and systems can promote the ability, knowledge, and preference of industry university cooperation members to lock in a certain range, so as to ensure the consistency of rules and regulations, beliefs, and language symbols in the process of cooperation, because language and symbols are the main tools of social group communication. Only by determining the language and symbols between industry university cooperation members can we ensure the realization of knowledge synergy. Under the common language and symbol, the members of industry university cooperation can promote the knowledge collaboration of technology alliance to achieve the expected results, ensure the smooth operation of industry university cooperation, and promote the sustainable development of industry university cooperation.


## 2.1. Organizational Difference Elements

In general, the realization of cross-organizational knowledge collaboration of industry university cooperation often occurs between organizations with equal knowledge stock and knowledge collaboration ability. However, due to the problems of information asymmetry and entry barriers of industry university cooperation itself, there will be obvious deficiencies in distinguishing the knowledge synergy ability of its member organizations. For example, a series of problems such as organizational knowledge management system, knowledge stock, knowledge coding degree, knowledge staff quality, and corporate culture are difficult to make accurate judgments in a reasonable time [7]. If the knowledge collaboration capabilities of member organizations differ greatly, it will increase the transaction cost, lead to disharmony in the collaboration process, reduce the value of synergy, and then reduce the efficiency of knowledge collaboration. On the other hand, due to the different survival and development environment of different member organizations, their knowledge stock is different, and the paths of knowledge learning and knowledge accumulation are also different. Therefore, there are differences in the knowledge required by different projects in industry university cooperation [8]. This gap often leads to the inconsistency and knowledge conflict of partners, improves the transaction cost, and affects the synergy efficiency. For example, in the collaborative innovation process of the atmospheric pollution control alliance initiated and established by environmental protection, there are relatively complete agreed terms before technology research and development to avoid subsequent income disputes [9].In the initial stage of industry university cooperation, member organizations are often unfamiliar with each other, and there are differences in the overall cognition of knowledge synergy, especially in the expectation of synergy benefits. This is because each partner will recognize, assume, design, and specify the key issues of the whole knowledge sharing according to their past experience, which may eventually lead to cognitive differences among partners on many issues. It is manifested in the differences in the expectation of cooperation objectives, the expectation of benefit acquisition, the confidence of cooperation, and the understanding of knowledge itself. Therefore, in order to improve the efficiency of collaboration, the selection of partners in cross-organizational knowledge collaboration of industry university cooperation is more critical, and the matching and collaboration among member organizations are the main factors to be considered [10].Due to the implicit characteristics of knowledge, the private knowledge owned by knowledge employees participating in cross-organizational knowledge collaboration is often difficult to measure, which will bring unpredictable results to the efficiency of knowledge collaboration. On the one hand, employees with richer knowledge have better overall knowledge structure and stronger ability to modulate and absorb knowledge. In the process of participating in knowledge collaboration, they have stronger learning ability and faster speed of acquiring knowledge, and are in an advantageous position and higher benefit in collaboration, which is the expected goal of all alliance organizations [11]. However, due to the complex environment of knowledge collaboration, some knowledge workers are prone to leakage of private knowledge, resulting in collaboration failure or infringement of organizational intellectual property rights. Therefore, the cognitive structure and psychological structure of employees will be analyzed to make a reasonable impact on their cognitive and collaborative response to knowledge structure.


## 2.2. Risk Elements

At present, under the condition of market economy, the possibility of opportunistic behavior increases in order to maximize interests and minimize costs. This opportunistic behavior is embodied in the following aspects: first, in terms of technology and intellectual property rights, there is a potential competition between members in the same alliance. Sometimes, some members will steal the core technology of other members, thus weakening the competitive advantage of competitors; in terms of cooperation, some members of the alliance hold a negative attitude toward the operation of the enterprise, which cannot guarantee the quality of the project, so it brings irreparable losses to the alliance; in terms of credit, due to the imperfection of the overall law of the alliance, the members unilaterally broke the contract, falsely reported information, leaked secrets, and other acts, resulting in the leakage and misappropriation of knowledge, leading to the disintegration of the alliance; in terms of incentive, when the benefits obtained by alliance members are not commensurate with the risks they bear, they will take measures to damage other members of the alliance, so as to maximize their own interests. The existence of the above behavior directly affects the interests and ultimate goal of the alliance, and even poses a threat to the cooperation among the members of the alliance, thus affecting the stability of the alliance and causing the risk of disintegration of the alliance.As shown in Figure1, the cause of alliance opportunistic behavior and alliance relationship risk is the specificity of enterprise technology assets. For the development of the enterprise alliance, a special investment must be set up for the technology research and development of the alliance. For example, in order to ensure the smooth progress of the project, the alliance must provide some professional technical talents and management personnel. If the human resources of the enterprise cannot meet the demand, it will directly affect the progress of the project. Therefore, the human resources department should strengthen the training of talents in this field; therefore, funds must be injected into the decision. In practice, the technology alliance does not agree that enterprises have business exchanges with enterprises different from itself, because the enterprise technical standards, enterprise culture, internal information exchange mode, and R&D operation form must be suitable for the corresponding adjustment of partners. At the same time, in order to meet the R&D requirements of enterprise projects, enterprises must provide professional equipment. All these require investment. These investments only have high value within the alliance and small value to the outside world, which is the so-called specific transaction investment [12].Figure 1
Conflict risk of knowledge collaboration.Therefore, enterprises’ choice of alliance operation mode mainly takes into account the stability of the alliance, which is the choice that alliance member enterprises have to face. The utilization and protection of resources by enterprises can reflect that enterprises have to face the integration and protection of resources in the alliance, which is the trade-off made by enterprises in a dilemma, and the existence of opportunistic behavior is a major obstacle to this. Therefore, the choice of alliance operation mode is the response of alliance enterprises to opportunism and alliance risk relationship [13].


## 2.3. Environmental Elements

Environment is the element of any activity. Obviously, the efficiency of inter-organizational knowledge synergy of industry university cooperation is also affected by the environment, that is, the interactive environment among alliance members. In essence, industry university cooperation is an economic community, which is composed of multiple enterprises or institutions within a certain space. Industry university cooperation contains rich knowledge, which includes various types of knowledge activities. These activities mainly include knowledge acquisition, learning, and creation. This is a complex activity, in which knowledge innovation is the foundation, knowledge transfer is the key, and the application of knowledge is the key. Such a structural form determines the enrichment of the content of knowledge activities, and knowledge innovation is the core of knowledge activities. From the perspective of system engineering, the knowledge, knowledge activities, and its management process contained in industry university cooperation are a complex system, but it is a knowledge collaboration system [14].Industry university cooperation is an organizational form with “local embeddedness,” “spatial agglomeration,” and “industrial relevance.” It is not only a social system, but also an economic system. From the perspective of social technology system, industry university cooperation is also a technical system, so it is a technical, economic, and social system. The technical activities and economic activities of industry university cooperation are affected by various factors, which makes the relationship between them more complex. The reason is that they are affected by cultural and social factors. Therefore, to a more accurate extent, industry university cooperation is not only a technical system, but also a social and cultural system. These two systems have their corresponding networks in technology alliance, namely, value network and social network [15].With the continuous development of economy, no knowledge system of industry university cooperation can maintain its own operation, which means that the technology alliance itself cannot carry out knowledge activities in a “closed door” way. It must widely absorb foreign knowledge and supplement its own shortcomings, so as to form an inseparable and close relationship with foreign knowledge. In this way, industry university cooperation can timely absorb the latest scientific and technological knowledge and production and management information, so as to overcome the problems faced by industry university cooperation in operation and promote itself to take the road of sustainable development. To sum up, a complete knowledge collaboration system of industry university cooperation must be open.


## 2.4. Behavioral Elements

There are both interdependence and competition among members of cross-organizational knowledge collaboration. The reason why industry university cooperation can exist is that in order to maximize the interests, members can reach a collaborative relationship in the form of collaboration, so as to better seek interests. Therefore, members of technology alliance need to apply this way of collaborative cooperation to complete difficult tasks in this complex environment. This mutually beneficial relationship between members has formed a trend. This relationship is mainly maintained by the equal coordination relationship between organizations, not based on the price mechanism, which has laid a solid foundation for the stability of industry university cooperation.Behavior mechanism is the mechanism to deal with the relationship between organizations. Because many knowledge resources in the organization are often secret, if you want to obtain the secret knowledge resources of other organizations, you must consult with them to reach an agreement, and the behavior mechanism plays a vital role in this process. The behavior mechanism can not only make the members of industry university cooperation better use of their own learning resources, but also promote the harmonious relationship with other organizations. Especially in this social network, the exchange and flow of knowledge resources must rely on a certain mechanism for protection, so as to efficiently transfer knowledge resources and form a good speed of cooperation.The transfer of knowledge resources cannot be directly applied to the recipient, it needs to be sorted and reconstructed, so the coordination and cooperation between the two sides can promote the improvement of knowledge synergy efficiency. At the same time, it can also improve the speed of knowledge collaboration, so as to promote the establishment of knowledge resource sharing among industry university cooperation members and make the collaboration of knowledge resources more convenient. Through the corresponding cooperation adjustment, it can promote the cooperation and exchange between the members of the technology alliance and increase their understanding of each other. At the same time, it can also promote the members to be familiar with the industry terminology, professional vocabulary, communication language, and common transaction rules, so as to ensure the smooth cooperation between the members of the industry university cooperation. The adjustment of industry university cooperation norms and systems can promote the ability, knowledge, and preference of industry university cooperation members to lock in a certain range, so as to ensure the consistency of rules and regulations, beliefs, and language symbols in the process of cooperation, because language and symbols are the main tools of social group communication. Only by determining the language and symbols between industry university cooperation members can we ensure the realization of knowledge synergy. Under the common language and symbol, the members of industry university cooperation can promote the knowledge collaboration of technology alliance to achieve the expected results, ensure the smooth operation of industry university cooperation, and promote the sustainable development of industry university cooperation.


## 3. Efficiency Evaluation Index System

### 3.1. Importance of Efficiency Evaluation

The maximum expected goal of industry university cooperation members refers to the best result obtained in a relatively ideal state of knowledge collaboration, in which there are no negative influence and interference factors and knowledge collaboration obstacles. However, in practice, there will be various interfering factors in the process of knowledge collaboration, resulting in the reduction of its knowledge collaboration efficiency. There are relative difference and distance between the actual knowledge collaboration effect and the maximum expected target effect. Knowledge collaboration efficiency is difficult to achieve in practical operation. The maximum expected goal set belongs to the ultimate goal pursued by cross-organizational knowledge collaboration of industry university cooperation. It is unscientific to directly measure the efficiency of cross-organizational knowledge collaboration from the theoretical concept, because the maximum expected goal of knowledge collaboration under the theoretical condition cannot be possessed or nonexistent under the realistic condition. However, taking the maximum expected goal as an important standard to measure efficiency, if the actual result of knowledge collaboration is close to the maximum expected goal, it can indicate that the actual efficiency of knowledge collaboration is high; otherwise, it indicates that the efficiency of knowledge collaboration is low. In order to achieve the purpose of fair evaluation, a large number of experts must participate in the evaluation process. The evaluation subject is required to be an expert or scholar who is proficient in the law and evaluation law of cross-organizational knowledge synergy efficiency of industry university cooperation, defines and understands the goal of knowledge synergy efficiency in industry university cooperation and innovation, and forms an evaluation team. The group members shall include industry scholars, entrepreneurs, alliance managers, government departments, middle-level cadres of enterprises, core knowledge workers, skilled workers, etc. Only in this way can the evaluation activities of cross-organizational knowledge synergy efficiency of industry university cooperation make appropriate evaluation according to the law and goal of knowledge synergy development.In inter-organizational knowledge management mechanism of industry university cooperation, the evaluation of knowledge synergy efficiency is an important content of management. The goal of cross-organizational knowledge management behavior of industry university cooperation is to improve the innovation ability and adaptability of a single member organization by using the collective knowledge of members based on the external sharing way of tacit knowledge or explicit knowledge. Building an effective cross-organizational knowledge coordination mechanism can realize the repeated investment of a single organization in knowledge innovation, avoid problems, save certain knowledge resources, and carry out knowledge innovation from a relatively high starting point, so as to improve the practical efficiency of knowledge innovation, and then enhance the knowledge competitiveness of member organizations. However, in the process of the operation of the knowledge collaboration mechanism of industry university cooperation, how to judge and measure the operation effect of the mechanism has become an important problem in the application of the mechanism. If there are problems in the operation mechanism itself, it is necessary to consider whether an effective feedback monitoring mechanism can be set, and the mechanism can be corrected through the capture and feedback of existing problems. In order to ensure the operation quality of the knowledge collaboration mechanism, the knowledge sharing evaluation mechanism is introduced, and the evaluation mechanism is used as a feedback mechanism to reflect whether there is coordination and consistency in the strategies, objectives, and changes in the cross-organizational operation of the industry university cooperation. The member behavior coordination is carried out through the feedback mechanism to ensure the smooth realization of the organizational knowledge management objectives.The practical functions of the evaluation mechanism of knowledge synergy efficiency are as follows: first, through the evaluation mechanism, it can promote all organization members to recognize the differences between cooperation goals, behaviors, confidence, and various expected results, and promote members to more rationally recognize and evaluate the cognitive gap existing in knowledge synergy; second, the evaluation mechanism urges the organization members to think about the degree of trust, fairness of benefit distribution, and cultural compatibility, so as to provide support for creating a better knowledge coordination atmosphere and environment; third, give play to the incentive role of the evaluation mechanism, coordinate and optimize the behavior of managers and organization members under the feedback results of the evaluation mechanism, encourage them to carry out knowledge collaboration in a better state, and effectively improve the efficiency of knowledge collaboration. It can be seen that the evaluation mechanism plays an important role in the cross-organizational knowledge management of industry university cooperation.Based on certain standards and purposes, the evaluation mechanism of knowledge collaboration efficiency adopts scientific and reasonable methods to evaluate and judge the value of the evaluation object. The operation goal of the mechanism is to optimize and improve the cross-organizational knowledge collaboration activities of industry university cooperation, so as to improve the efficiency of knowledge collaboration to the greatest extent and ensure the smooth completion of the goal of knowledge sharing.


### 3.2. Basic Idea of Efficiency Evaluation

In the cooperative innovation of industry university cooperation, the process of knowledge collaboration is very obvious, and it itself is a complex process. Therefore, the purpose of paying attention to the evaluation of knowledge collaboration process is mainly to analyze and adjust the process in time, so we can achieve the goal of improving the efficiency of knowledge collaboration. In the cooperative innovation of industry university cooperation, the evaluation subject of knowledge collaboration efficiency must clarify the main objective system of the whole process of knowledge collaboration, evaluate the situation or behavior of each stage of knowledge collaboration on this basis, and revise the objectives and guidance plans of each stage according to the evaluation results.Because the process of inter-organizational knowledge collaboration of industry university cooperation is cyclic, this study can divide the knowledge collaboration process in industry university cooperation innovation into four stages according to time: preparation period, behavior start period, operation integration period, and coordination application period. Firstly, in the preparation period, the potential difference between alliance organizations must have a far-reaching impact on the process and efficiency of knowledge collaboration. Therefore, the evaluation in this period should reflect the compatibility of knowledge collaboration strategy matching between organizations, that is, the driving problem, find out the key indicators that affect the understanding difference of knowledge collaboration itself, and achieve the goal of driving organizations to carry out knowledge collaboration behavior. Through evaluation, we can find out the differences and differences between organizations in the value chain of knowledge collaboration, and find out the root causes affecting the efficiency of knowledge collaboration. Secondly, at the beginning of behavior, different organizations in the alliance form knowledge collaboration teams. These organizations must face the complex environment and the basis of knowledge collaboration efficiency, such as partner selection and income distribution. Through the evaluation of the corresponding indicators, we can find the existing problems. Third is the operation integration period. Through the understanding of the above evaluation process, knowledge collaboration does not necessarily produce high efficiency in the innovation of industry university cooperation and needs to be adjusted and integrated in the process of knowledge collaboration. Therefore, the key to improve the efficiency of knowledge collaboration lies in the adjustment of the operation process, mainly including the construction of organizational model, organizational stability, and ability training. These are the efficiency evaluation of integration for the problems in operation, which is in the core position in the efficiency evaluation of knowledge collaboration. Fourth is collaborative application period. During this period, knowledge collaboration has been more mature, which directly shows the efficiency of knowledge collaboration. Due to the lag of collaborative efficiency, it is necessary to evaluate the indicators in the coordination application stage. These indicators reflect the continuity and sustainable development of the later knowledge collaboration process. Although knowledge synergy efficiency is directly related to the contribution of member organizations, the cross-organizational knowledge synergy efficiency of industry university cooperation is more affected by the factors that are difficult to quantify, and its knowledge synergy effect cannot be expressed immediately. Its efficiency performance has the characteristics of lag and delay. When evaluating the efficiency of knowledge collaboration, we need to comprehensively consider the impact of the interaction and relationship between member organizations, which are difficult to quantify.


## 3.1. Importance of Efficiency Evaluation

The maximum expected goal of industry university cooperation members refers to the best result obtained in a relatively ideal state of knowledge collaboration, in which there are no negative influence and interference factors and knowledge collaboration obstacles. However, in practice, there will be various interfering factors in the process of knowledge collaboration, resulting in the reduction of its knowledge collaboration efficiency. There are relative difference and distance between the actual knowledge collaboration effect and the maximum expected target effect. Knowledge collaboration efficiency is difficult to achieve in practical operation. The maximum expected goal set belongs to the ultimate goal pursued by cross-organizational knowledge collaboration of industry university cooperation. It is unscientific to directly measure the efficiency of cross-organizational knowledge collaboration from the theoretical concept, because the maximum expected goal of knowledge collaboration under the theoretical condition cannot be possessed or nonexistent under the realistic condition. However, taking the maximum expected goal as an important standard to measure efficiency, if the actual result of knowledge collaboration is close to the maximum expected goal, it can indicate that the actual efficiency of knowledge collaboration is high; otherwise, it indicates that the efficiency of knowledge collaboration is low. In order to achieve the purpose of fair evaluation, a large number of experts must participate in the evaluation process. The evaluation subject is required to be an expert or scholar who is proficient in the law and evaluation law of cross-organizational knowledge synergy efficiency of industry university cooperation, defines and understands the goal of knowledge synergy efficiency in industry university cooperation and innovation, and forms an evaluation team. The group members shall include industry scholars, entrepreneurs, alliance managers, government departments, middle-level cadres of enterprises, core knowledge workers, skilled workers, etc. Only in this way can the evaluation activities of cross-organizational knowledge synergy efficiency of industry university cooperation make appropriate evaluation according to the law and goal of knowledge synergy development.In inter-organizational knowledge management mechanism of industry university cooperation, the evaluation of knowledge synergy efficiency is an important content of management. The goal of cross-organizational knowledge management behavior of industry university cooperation is to improve the innovation ability and adaptability of a single member organization by using the collective knowledge of members based on the external sharing way of tacit knowledge or explicit knowledge. Building an effective cross-organizational knowledge coordination mechanism can realize the repeated investment of a single organization in knowledge innovation, avoid problems, save certain knowledge resources, and carry out knowledge innovation from a relatively high starting point, so as to improve the practical efficiency of knowledge innovation, and then enhance the knowledge competitiveness of member organizations. However, in the process of the operation of the knowledge collaboration mechanism of industry university cooperation, how to judge and measure the operation effect of the mechanism has become an important problem in the application of the mechanism. If there are problems in the operation mechanism itself, it is necessary to consider whether an effective feedback monitoring mechanism can be set, and the mechanism can be corrected through the capture and feedback of existing problems. In order to ensure the operation quality of the knowledge collaboration mechanism, the knowledge sharing evaluation mechanism is introduced, and the evaluation mechanism is used as a feedback mechanism to reflect whether there is coordination and consistency in the strategies, objectives, and changes in the cross-organizational operation of the industry university cooperation. The member behavior coordination is carried out through the feedback mechanism to ensure the smooth realization of the organizational knowledge management objectives.The practical functions of the evaluation mechanism of knowledge synergy efficiency are as follows: first, through the evaluation mechanism, it can promote all organization members to recognize the differences between cooperation goals, behaviors, confidence, and various expected results, and promote members to more rationally recognize and evaluate the cognitive gap existing in knowledge synergy; second, the evaluation mechanism urges the organization members to think about the degree of trust, fairness of benefit distribution, and cultural compatibility, so as to provide support for creating a better knowledge coordination atmosphere and environment; third, give play to the incentive role of the evaluation mechanism, coordinate and optimize the behavior of managers and organization members under the feedback results of the evaluation mechanism, encourage them to carry out knowledge collaboration in a better state, and effectively improve the efficiency of knowledge collaboration. It can be seen that the evaluation mechanism plays an important role in the cross-organizational knowledge management of industry university cooperation.Based on certain standards and purposes, the evaluation mechanism of knowledge collaboration efficiency adopts scientific and reasonable methods to evaluate and judge the value of the evaluation object. The operation goal of the mechanism is to optimize and improve the cross-organizational knowledge collaboration activities of industry university cooperation, so as to improve the efficiency of knowledge collaboration to the greatest extent and ensure the smooth completion of the goal of knowledge sharing.


## 3.2. Basic Idea of Efficiency Evaluation

In the cooperative innovation of industry university cooperation, the process of knowledge collaboration is very obvious, and it itself is a complex process. Therefore, the purpose of paying attention to the evaluation of knowledge collaboration process is mainly to analyze and adjust the process in time, so we can achieve the goal of improving the efficiency of knowledge collaboration. In the cooperative innovation of industry university cooperation, the evaluation subject of knowledge collaboration efficiency must clarify the main objective system of the whole process of knowledge collaboration, evaluate the situation or behavior of each stage of knowledge collaboration on this basis, and revise the objectives and guidance plans of each stage according to the evaluation results.Because the process of inter-organizational knowledge collaboration of industry university cooperation is cyclic, this study can divide the knowledge collaboration process in industry university cooperation innovation into four stages according to time: preparation period, behavior start period, operation integration period, and coordination application period. Firstly, in the preparation period, the potential difference between alliance organizations must have a far-reaching impact on the process and efficiency of knowledge collaboration. Therefore, the evaluation in this period should reflect the compatibility of knowledge collaboration strategy matching between organizations, that is, the driving problem, find out the key indicators that affect the understanding difference of knowledge collaboration itself, and achieve the goal of driving organizations to carry out knowledge collaboration behavior. Through evaluation, we can find out the differences and differences between organizations in the value chain of knowledge collaboration, and find out the root causes affecting the efficiency of knowledge collaboration. Secondly, at the beginning of behavior, different organizations in the alliance form knowledge collaboration teams. These organizations must face the complex environment and the basis of knowledge collaboration efficiency, such as partner selection and income distribution. Through the evaluation of the corresponding indicators, we can find the existing problems. Third is the operation integration period. Through the understanding of the above evaluation process, knowledge collaboration does not necessarily produce high efficiency in the innovation of industry university cooperation and needs to be adjusted and integrated in the process of knowledge collaboration. Therefore, the key to improve the efficiency of knowledge collaboration lies in the adjustment of the operation process, mainly including the construction of organizational model, organizational stability, and ability training. These are the efficiency evaluation of integration for the problems in operation, which is in the core position in the efficiency evaluation of knowledge collaboration. Fourth is collaborative application period. During this period, knowledge collaboration has been more mature, which directly shows the efficiency of knowledge collaboration. Due to the lag of collaborative efficiency, it is necessary to evaluate the indicators in the coordination application stage. These indicators reflect the continuity and sustainable development of the later knowledge collaboration process. Although knowledge synergy efficiency is directly related to the contribution of member organizations, the cross-organizational knowledge synergy efficiency of industry university cooperation is more affected by the factors that are difficult to quantify, and its knowledge synergy effect cannot be expressed immediately. Its efficiency performance has the characteristics of lag and delay. When evaluating the efficiency of knowledge collaboration, we need to comprehensively consider the impact of the interaction and relationship between member organizations, which are difficult to quantify.


## 4. Efficiency Evaluation Based on BP Neural Network

The basic BP algorithm formula mainly includes the forward propagation of signal and the back propagation of error.


### 4.1. Forward Propagation Process of Signal

Let the input mode of the network bex=x1,x2,…xnT, the hidden layer has h units, the output of the hidden layer is y=y1,y2,…yhT, the output layer has m units, and the target output is z=z1,z2,…zmT. Let the transfer function from the hidden layer to the output layer be f and the transfer function of the output layer be g.Thus,yj=f∑i=1nwijxi−θ=f∑i=0nwijxi.Among them,w0j=−θ,x0=1.zk=g∑j=0hwjkyj: output of the kth neuron in the output layer.At this time, the error between the network output and the target output isε=1/2∑k=1mtk−zk2. Obviously, it is a function of wij,wjk.The next step is to find a way to adjust the weight to reduce theε.From the knowledge of advanced mathematics, we know that the direction of negative gradient is the direction in which the value of function decreases fastest.Therefore, you can set a step size and adjust units along the negative gradient direction each time, that is,η, and the weight can be adjusted as follows:Δwpq=−η∂ε/∂wpq, η in neural networks, and it is called learning rate.It can be proved that the error will be gradually reduced by adjusting this method.The adjustment order of BP neural network (back propagation) isvk=∑j=0hwjkyj.Partial derivative formula of composite function is as follows.Ifgx=fx=1/1+e−x, then g′uk=e−vk/1+e−vk2=1/1+e−vk1−1/1+e−vk=zk1−zk.Therefore, the weight adjustment iterative formula from hidden layer to output layer is as follows.The iterative formula for weight adjustment from input layer to hidden layer is as follows.Note: thejth neuron in the hidden layer is connected with each neuron in the output layer; that is, it involves all weights, so(1)∂ε∂yj=∑k=0m∂tk−zk2∂zk∂zk∂uk∂uk∂yj=−∑k=0mtk−zkf′ukwjk.As shown in Figure2, first, set the number of layers of the network by adding neurons in the middle layer to reduce the error and improve the accuracy. Secondly, the number of neurons in the middle layer was calculated. You can determine the increased number by training and comparing different numbers of situations. In addition, the setting of initial weight is key, and its size has a great impact on learning efficiency.Figure 2
BP algorithm program flowchart.


### 4.2. The Learning Process and Steps of BP Network

Weight each connectionwij, vjt, θj, γt endowing interval (−1, 1).Select a set of input and target samples at random:Pk=a1k,a2k,…,ank, Tk=y1k,y2k,…,yqk.Set input samples:(2)sj=∑i=1nwijaik−θj,j=1,2,…p,bj=fsj,j=1,2,…p.Output of middle layerLt=∑j=1pvjtbj−γt, t=1,2,…,q, Ct=fLt, t=1,2,…,q.Using network target vector:Tk=y1k,y2k,…,yqk, calculate the generalization error of each element in the output layer: dtk.(3)dtk=ytk−Ct⋅Ct⋅1−Ct,t=1,2,…,q.Calculate the generalization error of each element in the middle layer:ejk。.(4)ejk=∑t=1qdtk⋅vjtbj1−bj.Modified connection right:vjt, γt.(5)vjtN+1=vjtN+α⋅dtk⋅bjγtN+1=γtN+α⋅dtkt=1,2,…,q,j=1,2,…p,0<α<1.Using the generalization error of each unit in the middle layer:ejk, modified connection right: wij, θj。.(6)wijN+1=wijN+β⋅ejk⋅aikθjN+1=θjN+β⋅ejki=1,2,…n,j=1,2,…p,0<β<1.Finally, the next learning sample vector is randomly selected and provided to the network until the training sample is trained.


## 4.1. Forward Propagation Process of Signal

Let the input mode of the network bex=x1,x2,…xnT, the hidden layer has h units, the output of the hidden layer is y=y1,y2,…yhT, the output layer has m units, and the target output is z=z1,z2,…zmT. Let the transfer function from the hidden layer to the output layer be f and the transfer function of the output layer be g.Thus,yj=f∑i=1nwijxi−θ=f∑i=0nwijxi.Among them,w0j=−θ,x0=1.zk=g∑j=0hwjkyj: output of the kth neuron in the output layer.At this time, the error between the network output and the target output isε=1/2∑k=1mtk−zk2. Obviously, it is a function of wij,wjk.The next step is to find a way to adjust the weight to reduce theε.From the knowledge of advanced mathematics, we know that the direction of negative gradient is the direction in which the value of function decreases fastest.Therefore, you can set a step size and adjust units along the negative gradient direction each time, that is,η, and the weight can be adjusted as follows:Δwpq=−η∂ε/∂wpq, η in neural networks, and it is called learning rate.It can be proved that the error will be gradually reduced by adjusting this method.The adjustment order of BP neural network (back propagation) isvk=∑j=0hwjkyj.Partial derivative formula of composite function is as follows.Ifgx=fx=1/1+e−x, then g′uk=e−vk/1+e−vk2=1/1+e−vk1−1/1+e−vk=zk1−zk.Therefore, the weight adjustment iterative formula from hidden layer to output layer is as follows.The iterative formula for weight adjustment from input layer to hidden layer is as follows.Note: thejth neuron in the hidden layer is connected with each neuron in the output layer; that is, it involves all weights, so(1)∂ε∂yj=∑k=0m∂tk−zk2∂zk∂zk∂uk∂uk∂yj=−∑k=0mtk−zkf′ukwjk.As shown in Figure2, first, set the number of layers of the network by adding neurons in the middle layer to reduce the error and improve the accuracy. Secondly, the number of neurons in the middle layer was calculated. You can determine the increased number by training and comparing different numbers of situations. In addition, the setting of initial weight is key, and its size has a great impact on learning efficiency.Figure 2
BP algorithm program flowchart.


## 4.2. The Learning Process and Steps of BP Network

Weight each connectionwij, vjt, θj, γt endowing interval (−1, 1).Select a set of input and target samples at random:Pk=a1k,a2k,…,ank, Tk=y1k,y2k,…,yqk.Set input samples:(2)sj=∑i=1nwijaik−θj,j=1,2,…p,bj=fsj,j=1,2,…p.Output of middle layerLt=∑j=1pvjtbj−γt, t=1,2,…,q, Ct=fLt, t=1,2,…,q.Using network target vector:Tk=y1k,y2k,…,yqk, calculate the generalization error of each element in the output layer: dtk.(3)dtk=ytk−Ct⋅Ct⋅1−Ct,t=1,2,…,q.Calculate the generalization error of each element in the middle layer:ejk。.(4)ejk=∑t=1qdtk⋅vjtbj1−bj.Modified connection right:vjt, γt.(5)vjtN+1=vjtN+α⋅dtk⋅bjγtN+1=γtN+α⋅dtkt=1,2,…,q,j=1,2,…p,0<α<1.Using the generalization error of each unit in the middle layer:ejk, modified connection right: wij, θj。.(6)wijN+1=wijN+β⋅ejk⋅aikθjN+1=θjN+β⋅ejki=1,2,…n,j=1,2,…p,0<β<1.Finally, the next learning sample vector is randomly selected and provided to the network until the training sample is trained.


## 5. Conclusion

The research shows that the efficiency evaluation of cross-organizational knowledge collaboration of industry university cooperation, as a complete system, is complex. In the industry university cooperation, multi-selection neural network model is used as the basic model for the evaluation of knowledge collaboration efficiency. Neural network model can also be applied to management practice, economy, and other fields. It has the advantages of fast and reliable calculation. Through this model, the relationship between knowledge collaboration efficiency index and knowledge collaboration efficiency can be described relatively objectively. In order to realize the objective description of the essence and law of knowledge collaboration, it is necessary to build a perfect index system. However, the operation of the index system composed of many indicators is difficult to achieve. A single index can describe one or more attribute characteristics of the knowledge synergy efficiency evaluation system. Therefore, in the process of constructing the index system, select more representative main indexes for analysis and processing to ensure the rationality and scientificity of the construction of the evaluation index system, which is the basis of scientific evaluation and judgment of the actual efficiency of knowledge synergy. At the same time, based on the evaluation of knowledge collaboration efficiency and related factors, this study selects three main elements in the analysis of knowledge collaboration efficiency, namely, organizational differences, knowledge collaboration real environment, and behavior elements, and realizes knowledge collaboration efficiency through the integration and operation of the three elements. The result of knowledge collaboration efficiency is the result of its comprehensive effect. According to the final evaluation results, this study can calculate the cross-organizational knowledge synergy efficiency of production learning cooperation within a certain confidence interval.



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*Source: 1873862-2022-06-08.xml*