An empirical study on the influencing factors of the stability of the coupling symbiosis network of industry-university-research

Abstract

This paper theoretically analyzed the influence of symbiosis intimacy, cultural coupling, betrayal cost, degree of lock-in, geographic distance, and economic development on the stability of the coupling symbiosis network of industry-university-research (IUR), and conducted empirical analysis. The study found that symbiosis intimacy, cultural coupling, betrayal cost, degree of lock-in, and economic development all play a role in promoting the stability of the coupling symbiosis network of IUR, while geographical location is related to the stability of the coupling symbiosis network of IUR, but does not have a direct impact. Based on the empirical analysis results, the countermeasures and suggestions to improve the stability of coupling symbiosis network of the IUR were proposed.

Keywords

Industry-university-research (IUR)coupled symbiosis network stability influencing factors

1. Introduction

In the 21st century with the rapid development of scientific and technological revolution, IUR collaborative innovation and cooperation is a new driving force to promote scientific and technological development and a key factor to promote the improvement of China’s comprehensive national strength [1]. The concept of IUR coupling symbiosis network provides a new perspective for collaborative innovation research. Many scholars have explored the production-university-research coupling symbiosis network and its stability. Mindruta [2] believed that the factors affecting the stability of IUR cooperation not only come from the technical level, but also from the soft power such as culture or communication level, as well as some factors of supervision and governance level. Zhu and Peng [3] integrated the meaning of IUR cooperation, innovation and network organization, put forward the definition of IUR cooperative innovation network organization, and introduced its characteristics and advantages. Feng and Wang [4] used the small-world network model to analyze the network structure characteristics of the IUR institute and put forward the methods and strategies to promote its cooperation and communication, in order to maximize the IUR cooperative innovation performance. Zhang et al. [5] integrated the symbiosis theory into the theoretical study of the IUR cooperation network, proposed the concept of the symbiosis network, and showed how to use the concept to guide the IUR cooperation activities. According to the existing studies, the following characteristics can be found in the current studies on the IUR cooperation:

The purpose of IUR cooperation is to meet the needs of coupling symbiosis of all parties. However, the existing studies lack of tracking the influencing factors of IUR stability from the perspective of coupling symbiosis.

Due to differences in research perspectives and regions, some existing research conclusions are controversial. For example, Lawson and Lorenz [6] proposed that geographical proximity can stimulate the generation of similar languages, technical attitudes and problem-solving solutions, which plays a promoting role in maintaining a stable IUR coupling symbiosis network. However, Cao and Yu [7] proved that geographical distance did not significantly promote the stability of the IUR coupling symbiosis network by using the survival analysis method.

In this paper, the IUR partnership is regarded as a special coupling symbiotic network relationship, and correlation analysis and regression analysis are used to explore the relevant factors that affect the stability of IUR institute. And relevant suggestions are put forward for these influencing factors. Symbiosis network undoubtedly provides a new perspective for the study of IUR cooperation and has unique theoretical significance. At the same time, it is of great practical value to study how to make the network organization more stable from this perspective.

2. Research hypothesis

IUR cooperation refers to a cooperative relationship in which industry, university and research share benefits and risks in order to survive and develop [8]. Coupling in IUR cooperation emphasizes the “fit” of cooperation, that is, the interdependence and mutual penetration of all parties [9]. The concept of symbiosis first existed in biology, and later studies showed that there was symbiosis among the subjects of IUR. For example, Liu and Ding [10] showed in their research that it is difficult for any one of the industry, university and research to complete the whole process of technological innovation by their own strength, so a symbiotic relationship of synergistic progress must be formed. The network formed by the relationship chain is the symbiotic network in the process of symbiotic activities and symbiotic relations among the subjects in IUR cooperation. Therefore, this paper defines the IUR coupling symbiotic network as a benefit sharing system without unplanned changes formed by symbiotic units such as industry, university and research through symbiotic activities and symbiotic relationships [5, 11, 12]. The stability of the IUR coupling symbiotic network refers to an interdependent symbiotic force formed by all parties through long-term cooperation and communication, which can promote the cooperation parties to maintain a high degree of “combination” [13]. Even when the symbiotic network is disturbed by the influencing factors of the external symbiotic environment, it can still rely on the internal adjustment mechanism between symbiotic units to make the symbiotic network run stably [14]. Based on literature review, the stability of IUR coupling symbiotic network is influenced by symbiosis intimacy, cultural coupling, betrayal cost, degree of lock-in, geographic distance and economic development.

2.1 Symbiosis intimacy ( ${\bm{X}}_{1}$ )

Symbiosis intimacy refers to the degree of dependence that can be achieved by all parties of industry, university and research after mutual contribution and cooperation [15]. Scholars have long studied the mechanism of symbiosis intimacy affecting the stability of IUR coupling symbiotic network. First of all, high symbiosis intimacy can increase the direct contact between symbiotic units and enhance the information fluidity, thus improving the mutual trust. Due to the formation of a symbiotic mode with high intimacy and strong connection, symbiotic units are more likely to produce symbiotic rules that are adhered to and understood by each other. Whether a symbiotic unit enters or exits, it will pay a high cost, which is shown as a stable symbiotic network structure [16]. Secondly, the higher the symbiosis intimacy, the more familiar the symbiotic units are with each other, and the more conducive to the formation of consistent strategic goals, which can play a certain positive role in promoting the stability of the IUR coupling symbiosis network [17]. On the contrary, in the network relationship with weak symbiosis intimacy, there is almost no in-depth resource communication between symbiotic units, and the trust degree is low. Moreover, the establishment and maintenance costs of weak intimacy are relatively low, so the cost of entering or exiting is low, which leads to the poor stability of the IUR institute coupled symbiosis network [18]. To sum up, this paper proposes the following hypotheses:

Hypothesis 1: Symbiosis intimacy has a significant positive influence on the stability of the IUR coupling symbiosis network.

2.2 Cultural coupling ( ${\bm{X}}_{2}$ )

Culture is one of the indispensable elements to promote knowledge connection. All parties involved in the production, learning and research need to go through a period of exploration to finally form innovative achievements, but this process is tortuous and complex, and needs the spiritual support of coordinated thoughts and cultural values [19]. Therefore, cultural coupling is very important to maintain the stable state of the IUR coupling symbiosis network. However, existing studies show that, as different organizational structures, the cultural values of the university-research side and the enterprise side have different characteristics: the academic university-research side focuses on the infinite exploration of academic research, and their market awareness is relatively weak [20]; On the other hand, enterprise side pay more attention to the pursuit of commercial profits, and they are more concerned about the commerciality and practicality of innovation outputs [21]. Therefore, if the degree of cultural coupling between the two parties is not high, knowledge distortion is likely to occur during knowledge docking or vagueness will be caused to some extent in the process of knowledge transmission. For IUR organizations with a high degree of cultural coupling, knowledge transmission will become relatively efficient and knowledge flow will be more smooth, so as to ensure the stability of the IUR coupling symbiosis network [22]. To sum up, this paper proposes the following hypothesis:

Hypothesis 2: Cultural coupling has a significant positive influence on the stability of the IUR coupling symbiosis network.

2.3 Betrayal cost ( ${\bm{X}}_{3}$ )

If the cooperative subjects betray the IUR coupling symbiosis network, they will pay the corresponding price. Some of this manifests itself as a loss of credibility, some as a loss of interest, or both [23]. This paper argues that the higher the betrayal cost, the stronger the stability of the IUR coupling symbiosis network. First of all, when the price of betrayal is manifested as the loss of credibility, the defector will not choose to betray, considering that it will be difficult for him to participate in other networks with higher requirement of credibility in the future, that is, the IUR coupling symbiosis network is stable [24]. Secondly, when the cost of betrayal is represented by the loss of interests, the defector will not choose to betray because he considers that the cost of damage to the symbiosis network of betrayal is higher than the gain of maintaining the network, that is, the symbiosis network of IUR coupling is stable [25]. Finally, when the price of betrayal is sometimes both, the defector usually chooses to maintain the symbiosis network. At this point, the symbiosis network of IUR coupling presents a stable state. To sum up, this paper proposes the following hypothesis:

Hypothesis 3: Betrayal cost has a significant positive influence on the stability of the IUR coupling symbiosis network.

2.4 Degree of lock-in ( ${\bm{X}}_{4}$ )

In the IUR coupling symbiosis network, if each symbiotic unit can choose partners in multiple paths, it indicates that the locking degree of this coupling symbiosis network is not high; otherwise, it is high [26]. Current studies mainly focus on the view that the degree of lock-in is usually related to the investment of highly specialized assets by enterprise side or university-research side [27]. The higher the investment in highly specialized assets, the higher the sunk cost of pre-investment. From the psychological point of view, the more the investment cost, the more reluctant people will be to quit, in order to obtain the due benefits. When the coupled symbiotic units are unwilling to quit the symbiosis network, the coupled symbiosis network is stable [28]. In addition, empirical studies have shown that the selection of appropriate partners is the basis for the combination of IUR, which is conducive to locking each other between coupling symbiotic units and avoiding the emergence of alternative partners at any time, so as to enable long-term cooperation of the IUR coupling symbiosis network and promote the stability of the network [29]. Thus it can be seen that the degree of lock-in is reflected in the relationship between the investment of special assets and the selection of appropriate partners, and then affects the stability of the IUR coupling symbiosis network. To sum up, this paper proposes the following hypothesis:

Hypothesis 4: Degree of lock-in has a significant positive influence on the stability of the IUR coupling symbiosis network.

2.5 Geographic distance ( ${\bm{X}}_{5}$ )

The influence of the geographical distance of partners on the stability of the production-university-research coupling symbiosis network has always been one of the research hotspots in the academic circle. Hu and Li [30] believed that the close geographical location was conducive to the formation of close interaction between symbiotic units, which could facilitate the mutual transmission of tacit knowledge more smoothly. Cao and Yu [7] learned in the field interview that although the communication technology is increasingly developed, the interviewees still believe that the geographical distance will affect their communication. Based on the analysis of relevant literatures, Chen et al. [31] found that, as the geographical distance gradually gets longer, the tacit degree of knowledge will continue to increase and information asymmetry and other phenomena will be amplified, which will affect the stability of the IUR coupling symbiosis network. Therefore, it can be seen that, even though communication, network and other technologies are developed, more people believe that face-to-face communication is more conducive to the transfer of knowledge and the development of cooperation. This is because partners should not only exchange explicit knowledge, but also communicate tacit knowledge. To sum up, this paper proposes the following hypothesis:

Hypothesis 5: Geographic distance has a significant positive influence on the stability of the IUR coupling symbiosis network.

2.6 Economic development ( ${\bm{X}}_{6}$ )

Good economic development is the basis for the stable performance of the coupling symbiosis network of IUR. First of all, regions with faster economic development have stronger financial strength, which can seek more financial support for the IUR coupling symbiosis network, which is conducive to the smooth development of a series of collaborative innovation activities of the IUR coupling symbiosis network [32]. Secondly, the improvement of the level of economic development will drive the improvement of the level of scientific and technological development, and people will pay more attention to the cultivation of scientific and technological innovative talents, so as to inject better human resources and cooperation teams into the IUR coupling symbiosis network [33]. Finally, the regions with excellent IUR collaborative innovation will in turn drive the local economic development, thus forming a virtuous cycle. The continuous expansion of the national economic level will provide a strong power to all aspects of the IUR coulping symbosis network, while the regions with underdeveloped economic level will be restricted by tangible or intangible aspects, which makes the IUR symbosis netwok show an unstable trend. Moreover, the collaborative innovation level of the IUR coupling symbiosis network in the eastern region of China is higher than that in the central and western regions, and this difference is consistent with the regional difference in China’s economic development. To sum up, this paper proposes the following hypothesis:

Hypothesis 6: Economic development has a significant positive influence on the stability of the IUR coupling symbiosis network.

3. The empirical analysis

3.1 Variable setting and data collection

The data collected in this study mainly comes from questionnaire survey. According to the definition of the IUR coupling symbiosis network, all the research institutions, enterprises and universities that have participated in the IUR cooperation activities can be taken as the objects of investigation. In order to design a reasonable questionnaire, the author referred to the existing mature questions at home and abroad, and actively communicated with the organizations that are cooperating with the industry, university and research to obtain their understanding of the relevant issues. The questions of the questionnaire were modified according to their suggestions and discussed with experts. Finally, the revised questionnaire was fed back to the organizations that were cooperating with the industry, university and research, and the questionnaire was basically approved, and the formal version was finally formed. In this paper, the questionnaire is in the form of Likert five-level scale. Numbers 1–5 in the evaluation scale respectively represent the judgments on the facts stated in the questionnaire: “Completely inconsistent”, “Relatively inconsistent”, “Generally”, “Relatively consistent” and “Completely consistent”.

Questionnaire survey was carried out in two ways: field filling and online filling. A total of 270 questionnaires were sent out by the two ways, and 234 were recovered with a recovery rate of 86.7%. After excluding the questionnaires with obvious information errors, incomplete answers to questions and other invalid questionnaires, the number of valid questionnaires was 158, accounting for 67.5% of the collected questionnaires. The personnel surveyed in this paper are R&D personnel and middle and senior managers in universities and research institutes. They are the core forces in the innovation activities of IUR, and have a relatively better understanding of the basic process and situation in the cooperative innovation process. Among them, R&D personnel accounted for 58%, middle and senior management personnel accounted for 42%.

3.2 Reliability and validity tests

The test of reliability and validity is an indispensable part of the questionnaire survey. The purpose of the test is to ensure the validity of the hypothesis verification conclusion. Among them, reliability reflects the consistency and stability of measurement results; validity can indicate whether the measurement results are valid or not. In this paper, Cronbach’s $\alpha$ coefficient is used to test the reliability and confirmatory factor analysis is used to test the validity. The reliability and validity analysis results of the scale are shown in Table 1. It can be seen that the $\alpha$ value of each variable is greater than 0.7, which indicates that each variable has good reliability. KMO values of all variables were greater than 0.8 and Sig. $<$ 0.001, which was suitable for factor analysis. In conclusion, the reliability and validity indexes of the measurement scales for each variable meet the requirements.

Table 1
Reliability and validity tests of variables

Variable	Item number	$\alpha$ value	Comprehensive $\alpha$	KMO	Sig.
$X_{1}$	Symbiotic Mode Fit ( $X_{1a}$ )	0.832	0.831	0.835	0.000
	Symbiotic relationship satisfaction ( $X_{1b}$ )	0.713
	Degree of Trust ( $X_{1c}$ )	0.863
	Frequency of Communication ( $X_{1d}$ )	0.956
$X_{2}$	Target Culture ( $X_{2a}$ )	0.937	0.845	0.819	0.000
	Vision culture ( $X_{2b}$ )	0.798
	Values culture ( $X_{2c}$ )	0.712
	Management culture ( $X_{2d}$ )	0.862
$X_{3}$	Cost of reputation ( $X_{3a}$ )	0.913	0.898	0.884	0.000
	Cost of profit ( $X_{3b}$ )	0.906
$X_{4}$	Dedicated asset investment ( $X_{4a}$ )	0.732	0.791	0.865	0.000
	Partner complementarity ( $X_{4b}$ )	0.851
$X_{5}$	Geographic distance ( $X_{5a}$ )	0.916	0.916	0.842	0.000
$X_{6}$	GDP ( $X_{6a}$ )	0.901	0.901	0.839	0.000

Table 2

Correlation analysis results among variables

Variable	$X_{1}$	$X_{2}$	$X_{3}$	$X_{4}$	$X_{5}$	$X_{6}$	$X_{7}$
$X_{1}$	1
$X_{2}$	0.831 ${}^{**}$	1
$X_{3}$	0.526 ${}^{*}$	0.547 ${}^{*}$	1
$X_{4}$	0.723 ${}^{**}$	0.719 ${}^{**}$	0.529 ${}^{*}$	1
$X_{5}$	0.439 ${}^{*}$	0.762 ${}^{**}$	0.516 ${}^{*}$	0.546 ${}^{*}$	1
$X_{6}$	0.518 ${}^{*}$	0.689 ${}^{**}$	0.638 ${}^{**}$	0.649 ${}^{**}$	0.462 ${}^{*}$	1
$X_{7}$	0.534 ${}^{*}$	0.593 ${}^{*}$	0.597 ${}^{*}$	0.781 ${}^{**}$	0.698 ${}^{**}$	0.764 ${}^{**}$	1

Note: 1) ${}^{*}$ means significant at the level of 0.05 (bilateral); 2) ${}^{**}$ means significant at 0.01 level (bilateral).

3.3 Correlation analysis

Correlation analysis is used to study the relationship between variables, including whether there is a relationship and how close the relationship is. This analysis method is usually used before regression analysis. In order to understand the correlation between symbiosis intimacy, cultural coupling, betrayal cost, degree of lock-in, geographical distance, economic development and the stability of the IUR coupling symbiosis network, this paper conducted correlation analysis, and the analysis results are shown in Table 2.

Table 3
Regression coefficient table of variables to the stability of the IUR coupling symbiosis network

	Nonstandardized coefficient		Normalized coefficient	T	Sig	Collinearity statistics		R ${}^{2}$
	B	Standard error	Beta			The tolerance	VIF
Constant ( $M_{1}$ )	2.036	0.157		8.195	0.000			0.509
$X_{1a}$	0.019	0.048	0.026	1.162	0.000	0.412	2.765
$X_{1b}$	0.168	0.056	0.194	5.264	0.000	0.487	2.468
$X_{1c}$	0.157	0.034	0.178	0.649	0.000	0.435	2.561
$X_{1d}$	0.243	0.041	0.346	0.843	0.000	0.438	2.168
Constant ( $M_{2}$ )	1.883	0.29		6.319	0.000			0.416
$X_{2a}$	0.256	0.054	0.294	3.192	0.000	0.516	1.468
$X_{2b}$	0.315	0.091	0.314	3.016	0.000	0.412	1.598
$X_{2c}$	0.325	0.018	0.267	3.194	0.000	0.598	2.498
$X_{2d}$	0.137	0.128	0.194	3.894	0.000	0.597	1.168
Constant ( $M_{3}$ )	1.732	0.32		6.198	0.000			0.508
$X_{3a}$	0.269	0.069	0.294	4.168	0.000	0.543	4.136
$X_{3b}$	0.324	0.068	0.319	3.164	0.000	0.498	2.164
Constant ( $M_{4}$ )	1.568	0.286		7.226	0.000			0.492
$X_{4a}$	0.364	0.169	0.319	4.689	0.000	0.492	2.661
$X_{4b}$	0.459	0.064	0.542	2.691	0.000	0.451	2.139
Constant ( $M_{5}$ )	1.236	0.561		0.941	0.000			0.512
$X_{5a}$	0.062	0.066	0.059	0.968	0.346	0.264	3.152
Constant ( $M_{6}$ )	2.168	0.419		6.146	0.000			0.436
$X_{6a}$	0.621	0.419	0.592	6.146	0.000	0.359	2.721

As can be seen from Table 2, all variables are significant ( $P<$ 0.05), and the correlation values are all higher than 0.4, indicating a close positive correlation among all variables.However, correlation analysis only tells whether there is a relationship between variables and how strong the relationship is, but it cannot tell whether there is an influence relationship or what the influence relationship is. Therefore, this paper adopts regression analysis to conduct further research.

3.4 Regression analysis

The empirical research model of this paper is designed as follows:

$\displaystyle y=\beta_{1}\ast X_{1a}+\beta_{2}\ast X_{1b}+\beta_{3}\ast X_{1c}% +\beta_{4}\ast X_{1d}+\varepsilon_{1}$ (1) $\displaystyle y=\beta_{1}\ast X_{2a}+\beta_{2}\ast X_{2b}+\beta_{3}\ast X_{2c}% +\beta_{4}\ast X_{2d}+\varepsilon_{2}$ (2) $\displaystyle y=\beta_{1}\ast X_{3a}+\beta_{2}\ast X_{3b}+\varepsilon_{3}$ (3) $\displaystyle y=\beta_{1}\ast X_{4a}+\beta_{2}\ast X_{4b}+\varepsilon_{4}$ (4) $\displaystyle y=\beta_{1}\ast X_{5a}+\varepsilon_{5}$ (5) $\displaystyle y=\beta_{1}\ast X_{6a}+\varepsilon_{6}$ (6)

Where, $y$ represents the stability of the IUR coupling symbiosis network; $\beta$ represents the regression coefficient corresponding to the model; $\varepsilon$ represents the random error of each model.

Model (1) is a regression equation to verify the relationship between the symbiosis intimacy and the stability of the IUR coupling symbiosis network. Model (2) is a regression equation to verify the relationship between cultural coupling and the stability of the IUR coupling symbiosis network. Model (3) is a regression equation to verify the relationship between the betrayal cost and the stability of the IUR coupling symbiosis network. Model (4) is a regression equation to verify the relationship between the degree of lock-in and the stability of the IUR coupling symbiosis network. Model (5) is a regression equation to verify the relationship between the geographic distance and the stability of the IUR coupling symbiosis network. Model (6) is a regression equation to verify the relationship between economic development and the stability of the IUR coupling symbiosis network. The specific regression coefficients are shown in Table 3.

As it can be seen from Table 3, firstly, the tolerance of multicollinearity test is all greater than 0.1, and the VIF value is all less than 5, so there is no multicollinearity and the model is good. Secondly, the sig. value of Model 5 is 0.346, greater than 0.05, which is not statistically significant. Sig. values of other models are all $<$ 0.01, which means that in addition to the “geographical distance”, the other five factors have a positive effect on the stability of the IUR coupling symbiosis network. Finally, among all the influencing factors, the higher the standardized coefficient value, the greater the influence degree.

4. Conclusions and suggestions

4.1 Conclusions

With the increasing demand of science and technology innovation in today’s society, the innovation of science and technology and the cultivation of science and technology innovative talents have become one of the problems that people pay close attention to. The emergence of the IUR coupling symbiosis network speeds up the utilization efficiency of scientific and technological resources to some extent and solves the problems such as the imbalance of information resources. Theoretically speaking, the cooperative activities among IUR coupling symbiotic units can help each coupling symbiotic unit make full use of its own advantages and obtain benefits that cannot be obtained independently. However, in fact, the coupling symbiosis network is not necessarily very stable due to the problems of communication, cooperation, target and benefit distribution among the coupling symbiotic units. Therefore, in order to make full use of the innovative power of the IUR coupling symbiosis network to accelerate the progress of science and technology in today’s society, it is necessary to explore the factors that affect the stability of the IUR coupling symbiosis network. Through correlation analysis and regression analysis, this paper explores the correlation and influence of symbiosis intimacy, cultural coupling, betrayal cost, lock-in degree, geographical distance and economic development on the stability of the symbiosis network of IUR coupling. The findings are as follows:

Symbiotic closeness promotes the stability of the IUR coupling symbiosis network. Generally speaking, the higher the degree of symbiosis intimacy, the more familiar the symbiotic units are with each other, so the better the degree of tacit understanding, the fit of the symbiotic mode, the degree of trust, the degree of communication, etc., and thus the symbiosis network presents a stable trend.

Cultural coupling promotes the stability of the IUR coupling symbiosis network. In any production, IUR coupling symbiosis network, cultural coupling is equivalent to setting up a defense system inside the network. When the external environment change, the defense system can react quickly and adjust the strategy and the challenge, maintain the stability of the IUR coupling symbiosis network state.

The betrayal cost promotes the stability of the IUR coupling symbiosis network. From the angle of the symbiotic unit usually seek to maximize its own interests consideration, one of the principles of choosing whether to betray a symbiotic network is whether the price of betrayal is too high. If the price is symbiotic unit cannot bear betrayal, it will not choose betrayal symbiosis network, then the IUR coupling symbiosis network tends to be stable.

The degree of lock-in promotes the stability of the IUR coupling symbiosis network. On the one hand, the more highly specialized assets are invested, the higher the conversion cost of changing the original assets, so the higher the threshold to enter the IUR coupling symbiosis network, and the more difficult it is to exit. The symbiosis network has a higher degree of locking and higher stability of cooperation. On the other hand, the stronger the complementarity of partners, the lower the cost of communication between symbiotic units and the less extra time needed for running-in, which can make the symbiosis network generate tacit understanding and cooperation in knowledge cooperation activities, thus forming a locked state, and then make the IUR coupling symbiosis network tend to be stable.

Geographical distance is related to the stability of the IUR coupling symbiosis network but has no direct influence on it. Hypothesis 5 has not been verified. On the one hand, the enterprise side gives priority to the scientific research ability of the university-research side, and the university-research side gives priority to the market insight ability of the enterprise side. If it has to make a choice, the geographical location comes after the ability [34]. On the other hand, geographical proximity does not represent cognitive proximity and institutional proximity. The proximity of the above two non-spatial dimensions is usually increased by geographical proximity, but it does not mean that geographical proximity has a direct influence on the stability of the IUR coupling symbiosis network [30].

Economic development promotes the stability of the IUR coupling symbiosis network. The rapid development of economy is one of the external factors for the stabilization of the IUR coupling symbiosis network. Cities or regions with fast economic development can provide a relatively easy soil environment for the IUR coupling symbiosis network to survive, and even encourage enterprises of different natures to actively carry out IUR knowledge collaboration activities, so as to promote the sustained, stable and long-term development of the IUR coupling symbiosis network.

4.2 Suggestions

We should actively respond to cooperation projects and build symbiotic and intimate relationships. Enterprises, universities and scientific research institutions actively cooperate with each other to enhance their recognition and cooperation degree, and reduce the instability of symbiotic intimate relationship caused by unclear responsibilities and inactive attitudes. During the cooperation period, the university-research side shall continuously improve its own value, send more high-quality technologies and talents to the enterprise, and make continuous achievements in academic and scientific research. Enterprise side should make rational investment in universities and research institutes to help them solve the funding problems encountered in scientific research and increase the possibility of continuous innovation. At the same time, it is necessary to adapt to the changes of the times, make efforts to respond to the development of the times, and timely feedback the effective information of the market to the university-research side, so that the university-research side has a clearer direction. Therefore, the university-research side and the enterprise side must take a positive attitude towards the IUR cooperation activities, and establish close relationship, so as to make the IUR coupling symbiosis network develop stably.

Hold regular forums to promote cultural exchanges. In the IUR coupling symbiosis network, the coupling symbiotic units should not only pay attention to the explicit heterogenous cultural exchange, but also pay attention to the implicit heterogenous cultural integration [35]. Implicit heterogeneous culture includes material culture and institutional culture that can restrain people’s behavior without explicit regulations or obvious marks.If the IUR coupling symbiosis network wants to cultivate the implicit heterogenous culture of the symbiotic unit, it is necessary to cultivate the common behavior and thinking mode of all the coupling symbiotic units, so it is particularly important to hold the forum regularly. During the development of the forum, the coupling symbiotic unit can express its own views. On the one hand, it should let the university-research side understand the business cooperation models and market operation rules. On the other hand, enterprise side should understand the order of scientific research and technological innovation process.In this way, the coupling symbiotic unit can form a real cultural integration cooperative partner and promote the stable operation of the IUR coupling symbiosis network.

Reasonable distribution of interests, the introduction of intermediary agencies, increase the cost of betrayal. Because betray cost can divide into benefit cost and credit cost two kinds. In terms of benefits costs, a reasonable distribution of benefits should be adopted so that each symbiotic unit can get what it needs and obtain reasonable benefits in cooperation. At the same time, it is necessary to ensure the symmetry of the income of the university-research side and the enterprise side, so that all parties can achieve a “win-win situation”, and each coupling symbiotic unit can obtain the income that cannot be obtained in its own independent activities [36]. In terms of the credit cost, the introduction of intermediary agencies can be adopted. One of the functions of intermediaries is to provide the basic information of each coupling symbiotic unit on the basis of full investigation, which can make those who would like to betray the coupling symbiosis network choose to maintain the stability of the IUR coupling symbiosis network in order to avoid the punishment of trust-breaking.

Select complementary partners and lock symbiotic units. Before the formation of the IUR coupling symbiosis network, each coupling symbiotic unit should have a comprehensive understanding of the partners. When choosing a partner, ability is one thing, but more important is whether the partner can be used for oneself, and whether it can match one’s own scientific research level and technical ability [37]. Partners can only actively meet each other’s needs if they need each other. In addition, from the social level, the selection of complementary partners can also effectively avoid the emergence of resource waste, resource mismatch and other problems. Choosing complementary partners that match one’s own ability can reduce the communication cost, increase the stickiness of the coupling symbiosis network, thus lock the symbiotic unit, and realize the stability of the IUR coupling symbiosis network.

Focus on the adjacent construction of other non-spatial dimensions. The proximity of geographical location is conducive to promoting the validity of proximity of other non-spatial dimensions, while the proximity of geographical location alone cannot completely promote the validity of cooperation and communication between industry, university and research institute. Therefore, when the geographical location has not been determined, the coupling symbiotic unit should give priority to the complementarity of the capabilities and advantages of the partners, and then consider the proximity of the geographical location. When the geographical location has been determined, each symbiotic unit should be constructed and implemented according to the proximity of other non-spatial dimensions.

Interaction and economic win-win, forming a virtuous cycle. Economic environment is one of the external factors that should be considered in the IUR coupling symbiosis network. The change of the economic environment is both a challenge and an opportunity for the IUR coupling symbiosis network, which needs to timely adjust itself according to the change of the economic environment [17]. The IUR coupling symbiosis network needs to learn to take advantage of the power brought by economic development and cooperate with the economy to develop, or even form a virtuous cycle. Only in this way can it contribute to the stable development of the IUR coupling symbiosis network.

Through empirical analysis of the influencing factors of the stability of the IUR coupling symbiosis network, this paper provides some enlightenment for the stable cooperation activities between industry, university and research institute. However, there are still some shortcomings. For example, this paper only studies the influencing factors at the three main levels of industry, university and research institution, but the IUR cooperation will also be affected by the government and other levels. This is exactly the direction that the author will study deeply in the future.

Footnotes

Acknowledgments

We gratefully acknowledge the financial support from the National Social Science Fund Project of China (no. 19BJY068).

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An empirical study on the influencing factors of the stability of the coupling symbiosis network of industry-university-research

Abstract

Keywords

1. Introduction

2. Research hypothesis

2.1 Symbiosis intimacy ( 𝑿 1 )

2.2 Cultural coupling ( 𝑿 2 )

2.3 Betrayal cost ( 𝑿 3 )

2.4 Degree of lock-in ( 𝑿 4 )

2.5 Geographic distance ( 𝑿 5 )

2.6 Economic development ( 𝑿 6 )

3. The empirical analysis

3.1 Variable setting and data collection

3.2 Reliability and validity tests

Table 1 Reliability and validity tests of variables

Table 3 Regression coefficient table of variables to the stability of the IUR coupling symbiosis network

4.1 Conclusions

4.2 Suggestions

Footnotes

Acknowledgments

References

2.1 Symbiosis intimacy ( ${\bm{X}}_{1}$ )

2.2 Cultural coupling ( ${\bm{X}}_{2}$ )

2.3 Betrayal cost ( ${\bm{X}}_{3}$ )

2.4 Degree of lock-in ( ${\bm{X}}_{4}$ )

2.5 Geographic distance ( ${\bm{X}}_{5}$ )

2.6 Economic development ( ${\bm{X}}_{6}$ )

Table 1
Reliability and validity tests of variables

Table 3
Regression coefficient table of variables to the stability of the IUR coupling symbiosis network