Intelligent simulation of enterprise re-innovation support system based on system dynamics

Abstract

Technology innovation failure exists objectively. How to provide support for failed enterprises and improve their willingness to re-innovate has become a hot issue in the field of innovation management. To build a re-innovation support system for enterprises with failed innovation from the perspective of institutional environment, the system model of the re-innovation support system of the enterprises with failed innovation was established through the system dynamics method, the system boundary was defined, the causal relationship and the system flow graph of the model were analyzed, and the operation effect of the support system model was intelligent simulated by using Vensim software. The results show that institutional support can effectively reduce the number of enterprises with failed innovation, increase the number of re-innovation enterprises, and further improve the enterprise income and government revenue, thus verifying the effectiveness of the re-innovation support system of enterprises with failed innovation.

Keywords

Re-innovation support system system dynamics intelligent simulation

1 Introduction

Theoretical and practical exploration shows that the institutional environment is an important factor affecting the technological innovation activities of enterprises. A good institutional environment can effectively match the technological innovation behavior of enterprises and bring huge innovation benefits to enterprises. The advantages and disadvantages of institutional environment will also affect the success or failure of technological innovation of enterprises, and affect the re-innovation behavior of enterprises. Therefore, in view of the phenomenon of technological innovation failure, it is necessary to build the corresponding re-innovation support system to encourage the enterprises with failed innovation.

Technological innovation is a process in which knowledge, economy and society interact. In this complex system, only in a certain environment, conditions and elements of innovation support, the innovation subject and innovation elements can effectively develop and show their innovation vitality. In the process of technological innovation of enterprises, necessary resource elements such as enterprise management system, innovation resources, knowledge stock are needed to ensure the smooth operation of technological innovation of enterprises. However, due to the deficiency of the enterprise’s own resource endowment, the enterprise’s technological innovation activities cannot be separated from the support of the external environment, and the institutional environment is just an important part of the external environment of technological innovation. On the one hand, the institutional environment can provide the necessary innovation resources for the technological innovation activities of enterprises, and sufficient resources guarantee can continuously promote the development of innovation activities, reduce the failure probability of technological innovation of enterprises, and avoid the decline of the technological innovation system of enterprises to a certain extent. On the other hand, the support of institutional environment can also bring the internal power of re innovation to the enterprises with failed innovation, and the institutional environment is closely related to the re-innovation performance of enterprises. The further improvement of the re-innovation behavior and innovation ability of the enterprises with failed innovation needs the external support of institutional environment.

From the above analysis, it can be seen that the institutional support of enterprises with failed innovation is a complex dynamic process. According to the viewpoint of system theory, the analysis of this complex problem needs to be carried out in-depth analysis and discussion with the help of system method theory, so as to grasp the law of its change and development. Therefore, based on the core idea of system theory, from the perspective of the coupling of system elements, the supporting process of institutional environment to the enterprises with failed innovation is regarded as a complex system, that is, the re-innovation supporting system of enterprises with failed innovation.

2 Literature review

According to the failure theory, theory and practice realize the value of innovation failure. Since McGrath’s research, the recognition of the value of innovation failure has been paid more and more attention, that is, what can be obtained from innovation failure. Stokes et al. [1] believed that enterprises that have experienced innovation failure often perform better than the first innovation in the ability of opportunity identification and utilization, which helps to reduce the uncertainty of innovation activities to a certain extent, so as to improve the subsequent innovation willingness of enterprises with failed innovation [2]. From the perspective of resource management, failure experience can promote the improvement of failed innovation enterprises’ ability in resource management [3, 4]. From the perspective of the self-value of managers and R&D personnel, some scholars believed that innovation failure can stimulate self-learning [5], improve the subjective initiative of their own ability, make their decision-making more mature and rational in the process of innovation, and significantly improve their ability to be frustrated and their attitude of tolerating failure. However, some scholars put forward the opposite view; the innovation failure seriously hit the confidence of innovative enterprises and has a negative impact on the subsequent innovation intention [6, 7].

The value of innovation failure is mainly reflected in the reallocation of innovation failure resources. Innovation failure resource reengineering emphasizes how to learn from innovation failure and reuse failure resources. Relevant scholars believed that innovation failure is an important resource to improve the innovation ability of enterprises [8]. Zhang [9] believed that innovation failure learning is the realization of maximizing the value of innovation failure. By acquiring useful innovation knowledge from failure experience, it can improve innovation ability and reduce the uncertainty of subsequent innovation. In the research of innovation failure learning, it mainly includes three aspects: failure learning process, learning content and learning mode. In the process of innovation failure learning, the failure sources should be identified first, and then the failure experience can be transformed into innovation knowledge through the analysis of failure events [10]. In terms of learning content, it includes the identification and evaluation of opportunities [11, 12], management skills of innovative resources, access to resources [13]. Learning mode is a way of learning from innovation failure. There is a choice of exploratory and utilization learning mode [14], which will be affected by failure experience and learning content. According to the findings of Politics [15] and Ni [16], innovation failure makes failed enterprises more inclined to exploratory learning mode.

The output of innovation failure learning and resource reengineering has an impact on the re-innovation behavior [17]. For the enterprises with failed innovation, their follow-up behavior includes two kinds, namely, continuous innovation or innovation termination [18]. Therefore, in terms of the relationship between innovation failure and subsequent innovation, the existing study presents two views: one is the positive relationship [19], that is, after experiencing innovation failure, enterprises can more objectively examine the difficulties of innovation, reasonably evaluate the problems encountered, enhance their confidence, and improve their innovation skills and knowledge resources through innovation failure learning, and then stimulate the degree of effort to develop their follow-up innovation. The other reflects the negative relationship, emphasizing the pain relief of innovation failure to enterprises. The negative emotions brought by this hinder the positive attitude of enterprises with failed innovation to learn from the failure to a certain extent, and lose the confidence in the subsequent innovation success, so that it has a negative impact on the subsequent innovation behavior. However, whether the effect is positive or not is often controlled by external factors [20]. However, the impact between the reuse of failed resources and innovation performance is not directly related [21].

From the perspective of institutional environment, the elements of the re-innovation support system of enterprises with failed innovation mainly include the following parts: the government departments that provide policy support for the re-innovation activities of enterprises with failed innovation, the intermediary agencies that provide services for the re-innovation activities of enterprises with failed innovation, and the universities and research institutes that provide innovative talents support for the re-innovation activities of enterprises with failed innovation. The system structure of the re-innovation support system for enterprises with failed innovation is shown in Fig. 1.

Fig. 1

The system structure of the re-innovation support system for enterprises with failed innovation.

Enterprises with failed innovation. It is the core content of the re-innovation support system to promote the re-innovation behavior of the enterprises with failed innovation. First, the enterprises are the main body of technological innovation activities. Although the previous failure experience affects the enterprises’ willingness to re-innovation, in order to obtain market competitive advantage through new products and services, the enterprises with failed innovation also combines their own resource reserves to invest in R&D as much as possible and carry out independent innovation activities. Second, enterprises are also the main body of technological innovation investment, and insufficient support of technological resources is also the main reason for the technological innovation failure. Therefore, the key to the support of institutional environment is to promote the innovation investment of enterprises with failed innovation. The government departments use policy guidance to coordinate the activities of universities, scientific research institutions, and intermediary service agencies, and provide resource support for enterprises with failed innovation from the external environment. Third, the enterprises with failed innovation are to receive high-level talents from universities, research institutes and foreign ports. Due to the previous failure experience, on the one hand, it may affect the stability of the existing technology innovation team, resulting in turnover and other phenomena. On the other hand, the failure experience also affects the external reputation of enterprises and weakens the attraction of external talents. The intellectual advantages of universities and research institutes can effectively make up for the lack of human resource capacity of enterprises with failed innovation.

Government departments. According to North’s institutional theory, government is the main body of institutional environment optimization. Therefore, from the perspective of institutional environment, government departments play an important role in the re-innovation support system of enterprises with failed innovation. Specifically, the government departments refer to the central or provincial administrative departments that provide policy support for the enterprises with failed innovation and directly engage in technological innovation activities, and promote the re-innovation behavior of the enterprises with failed innovation through policy guidance, administrative intervention. The role of government is mainly reflected in the following aspects: first, to provide support for the re-innovation activities of enterprises with failed innovation. Second, Government departments protect the re-innovation behavior of enterprises with failed innovation. Third, Government departments encourage the willingness and enthusiasm of enterprises with failed innovation. The result of innovation failure will not only bring huge failure cost to enterprises, but also lead to negative emotions and inhibit the willingness of enterprises to innovate again.

Universities, research institutes and intermediary services are important components of the re-innovation support system of enterprises with failed innovation, and play a bridge role between the relationship between enterprises with failed innovation and government departments. It is mainly reflected in the following aspects: first, through the implementation of education and talent policy, the government departments promote the quality of innovative talents training in universities, research institutes, and then provide sufficient intellectual support for enterprises with failed innovation. Second, government departments optimize the intermediary service system of technological innovation. By increasing the number of technological intermediaries and improving the quality of technological services, they can further reduce the information asymmetry in the process of technological research and development and commercialization of scientific and technological achievements, and reduce the failure probability of technological innovation caused by the failure of commercial transformation. Third, through the design and implementation of financial policies, the government departments optimize the financial industry system in the innovation environment, improve the degree of marketization of the financial industry, and provide external financing support for the re-innovation activities of enterprises with failed innovation. Four, through the construction of the legal environment, the government departments further optimize the protection level of intellectual property rights in the innovation environment, effectively curb the infringement of the property rights of scientific and technological achievements in the process of technological innovation, and regulate technological innovation activities, so as to create a fair and just innovation environment for the enterprises with failed innovation.

3 Methodology

3.1 Causal model

According to the analysis of the overall structure of the re-innovation support system of enterprises with failed innovation, this study establishes a causal relationship model of the re-innovation support system of enterprises with failed innovation, as shown in Fig. 2. In addition, the construction of the system model follows the following hypotheses:

Fig. 2

Causal relationship model of the re-innovation support system of enterprises with failed innovation.

H1: The operation of re-innovation support system is a continuous and progressive dynamic process.

H2: In the process of establishing the model system, this study do not consider major policy changes, social changes, and other abnormal situations that lead to the overall system collapse.

As the main body of institutional environment construction, the government mainly optimizes the institutional environment by means of financial investment. Firstly, in terms of talent training and education investment, the large amount of local education funds and the implementation of talent introduction policies not only provide financial guarantee for regional talent training and ensure high-quality talent output, but also preferential talent introduction policies can attract high-level talents from other ports to work locally, so as to provide sufficient and high-quality technology innovation enterprises R&D personnel guarantee. Secondly, in the current development process of China’s economic restructuring, the role of the government in guiding the financial industry cannot be ignored. Through the introduction and implementation of relevant financial policies, the market-oriented development of the financial industry will provide greater space, and then bring more ways and means for the external financing of technological innovation enterprises. Thirdly, in terms of the intervention of enterprises’ technological innovation behavior, due to the innovation “market failure” caused by the external characteristics of technological innovation itself, the government can solve the constraints of the lack of innovation motivation and innovation resources to a certain extent through innovation incentives such as R&D subsidies. Finally, the construction of the legal environment is inseparable from the strong support of the government departments. Through the continuous improvement of relevant laws and regulations, as well as the further legal interpretation of new problems and contradictions in the process of economic development in the new era, a more legal and more effective intellectual property protection system is provided for technological innovation enterprises, thus forming a fairer and just market competition environment.

The technological resources and level of an enterprise are the core elements that determine the success or failure of technological innovation, while the technological resources and level are closely related to the investment in technological innovation and the number of R&D personnel. The lack of R&D investment and R&D personnel increase the possibility of technological innovation failure and increase the number of enterprises with failed innovation. Through the external impact of the institutional environment, improving the willingness of enterprises with failed innovation, driving more enterprises with failed innovation to choose re-innovation activities, and then increase the number of patents. Through the provision of new products and services, enterprises will increase the number of enterprises with failed innovation and bring more market benefits to itself.

3.2 System flow graph

According to the causality of the re-innovation support system of the enterprises with failed innovation in Fig. 2, the system flow graph of the re-innovation support system of the enterprises with failed innovation is established, as shown in Fig. 3.

Fig. 3

System flow graph of re-innovation support system for enterprises with failed innovation.

As can be seen from Fig. 3, the system involves six level variables, namely: enterprise income (EI), government revenue (GR), number of enterprises with failed innovation (NEFI), number of re-innovation enterprises (NRE) and number of enterprise patents (NEP). The rate variables mainly include six variables: the increase of enterprise income (IEI), the increase of government revenue (IGR), the increase of enterprises with failed innovation (IEFI), the increase of re-innovation enterprises (IRE) and the increase of patents (IP). System constants include R&D investment proportion (RDIP), talent policy (TP), talent training and education investment intensity (TTEII), financial policy (FP), R&D subsidy intensity (RDSI), legal environment construction intensity (LECI) and tax rate (TR). The other variables are auxiliary variables. It should be pointed out that the innovation environment index (IEI) is a new auxiliary variable introduced on the basis of the system causality graph. Its purpose is to test the improvement effect of the re-innovation support system on the innovation environment by the change of the innovation environment index.

3.3 Main structural equation

Due to the principle of model construction of system dynamics, the main structural equations of the model are established. Since the initial values of level variables and constants need to be set during the establishment of structural equations. In this study, the statistical data of economic and social development of Hubei, China in 2016 are used as the basis for setting and calculating relevant variables. The structural equation is optimized according to the need of the conversion of variables. Relevant statistical data are obtained through the query of CEInet statistics database. The level variable equation, rate variable equation, auxiliary variable equation and constant initial value are set as follows:

(1) Level variable equation $EI = INTEG (IEI, 4585.6)$ (1) $GR = INTEG (IGR, 3102.06)$ (2) $NRE = INTEG (IRE, 2933)$ (3) $NEFI = INTEG (IEFI, 9778)$ (4) $NEP = INTEG (IP, 4000)$ (5)

In the above equations, the variables EI, GR, NEFI, NRE, NEP will accumulate with the influence of rate variable, and their initial values are the level variable values of the 0th period. According to the data of economic development of Hubei, China in 2016, the local fiscal revenue of Hubei Province was 310.206 billion RMB, the tax revenue was 21.2293 billion RMB, the main business income of Industrial Enterprises above designated size was 4585.06 billion RMB, and the total profit reached 271.346 billion RMB, of which R&D expenditure was 4459.6 million RMB, and the number of industrial enterprises above designated size was 16296. Because it is difficult to obtain the data of the number of enterprises with failed innovation and the number of re-innovation enterprises, the initial values of these two level variables are estimated. It is assumed that according to 60% of the failure rate of enterprise innovation, the level variable NEFI is selected. In addition, due to the relatively small number of re-innovation enterprises in the initial stage of the support system, it is assumed that 30% of the number of enterprises with failed innovation will make re-innovation decisions. Initial value setting of level variables is shown in Table 1.

Table 1

Initial value setting of level variables

EI	GR	NRE	NEFI	NEP
45850.6	3102.06	2933	9778	4000

(2) Rate variable equation $IEI = NEP \times 0.1$ (6) $\begin{matrix} IP = NRE \times ((RDI \times 0.0008 / 10 + \\ \begin{matrix} & \end{matrix} NRDP \times 0.0012 / 1000) + 0.755 \end{matrix}$ (7) $\begin{matrix} IRE = (LEC - DELAY 1 (LEC, 1)) / \\ \begin{matrix} & \end{matrix} DELAY 1 (LEC, 1) \times NRE / 10 \end{matrix}$ (8) $\begin{matrix} IEFI = - (LEC \times 0.0119 + NRDP \times 0.005 + \\ \begin{matrix} \end{matrix} RDSI \times 0.0379 + RDI \times 0.05 + FDL \times 0.0302 \end{matrix}$ (9) $IGR = ET$ (10) (3) Auxiliary variable equation $TTEI = GR \times TTEII$ (11) $ET = EI \times TR$ (12) $IEI = (NRE - NEFI) / 10000$ (13) $LEC = LECI \times GR$ (14) $RDP = TTEI \times TP + EP \times 0.03$ (15) $RDI = EP \times RDIP$ (16) $RDS = GR \times RDSI$ (17) $FDL = GR \times FP$ (18) $EP = EI \times 0.05$ (19)

(4) Constant

The initial value settings for constants are shown in Table 2.

Table 2

Initial value of constants

TTEII	TP	LECI	RDIP	RDSI	TR	FP
0.1475	1	0.5	0.05	0.003	0.06	0.005

4 Simulation and result analysis

Because of the re-innovation support system of enterprises with failed innovation is to test the impact of institutional environment on the technological innovation failure and the re-innovation from failure, as well as the test and intelligent prediction of the operation effect of the system. Therefore, the results of intelligent simulation focus on the innovation failure and re-innovation of enterprises, the technological output and income of enterprise, and the change of government finance with the evolution of the system. In the simulation process of the system, the simulation time length is set to 15 years, and the time step is 0.01. The purpose is to obtain as many simulation data as possible to fit a smoother variable change curve.

4.1 The evolution of the number of enterprises with failed innovation and re-innovation enterprises

Figures 4 and 5 show the evolution of the number of enterprises with failed innovation and re-innovation enterprises under the initial state of the system. In the aspect of technological innovation failure, the number of enterprises with failed innovation shows a declining trend with time evolution. In the early stage of evolution, the number of enterprises with failed innovation decreased relatively slowly, but in the middle and late stage of evolution, the scope of this decline trend is increasing. The results show that under the influence of government R&D subsidy, educational personnel training investment, financial support, and legal environmental protection, the possibility of technological innovation failure is decreasing, thus promoting the decline of the number of enterprises with failed innovation, which is consistent with the conclusion of Xiong et al. [22]. From the perspective of this declining trend, it also reflects the cumulative effect of institutional environment on the effect of technological innovation failure. Because the effect of institutional environment often needs a certain period to be manifested, the effect of institutional environment on the enterprises with failed innovation may not be obvious in the early evolution process, which results in a small decline in the number of enterprises with failed innovation in the early stage. However, with the accumulation of institutional environmental effects, the number of enterprises with failed innovation shows a relatively rapid downward trend in the middle and late stage.

Fig. 4

Change in the number of enterprises with failed innovation.

Fig. 5

Changes in the number of re-innovation enterprises.

In the aspect of re-innovation from innovation failure, the system evolution results show that the number of re-innovation enterprises shows a rising trend, and the rising trend of the curve is relatively stable. Furthermore, affected by the institutional environmental factors, the willingness of enterprises with failed innovation will be significantly enhanced, especially under the protection of the intellectual property protection system, more and more enterprises with failed innovation will make re-innovation decisions, thus forming a re-innovation atmosphere of “more and more courage and enthusiasm for innovation” in the case of previous innovation failure.

4.2 Evolution of technological innovation achievements and benefits of enterprises

Figures 6 and 7 show the change trend of enterprise income and the number of enterprise patents under the influence of the re-innovation support system of enterprises with failed innovation. In terms of the change of enterprise income, under the double influence of the decrease in the number of enterprises with failed innovation and the increase in the number of re-innovation enterprises, the innovation output of enterprise group has increased greatly, thus forming more new products and services. In addition, the impact of institutional environment on the innovation behavior of enterprises is not only reflected in the relatively lower failure rate of technological innovation, but also in the promotion of enterprises’ willingness to re-innovate from failure, which can also bring good innovation performance and benefits to enterprises. According to Huang’s findings [23], a fair and market-oriented competition environment has been formed with good institutional guarantee, thus enhancing the innovation income of enterprises.

Fig. 6

Change in enterprise income.

Fig. 7

Changes in the number of enterprise patents.

In terms of the change of innovation output, the number of enterprise patents also shows a growing trend, and the number of growth is more, and different from the trend of enterprise income growth, the change curve of the number of patents shows a linear relationship. The possible reasons are as follows: on the one hand, the decrease of the number of enterprises with failed innovation and the increase of the number of re-innovation enterprises make the base of innovation subject of the whole society expand continuously, And under the guidance of the current national innovation driven development strategy, the optimization of the institutional environment has led to the further improvement of the innovation environment and atmosphere, the stronger willingness of technological innovation of enterprises, and the higher innovation efficiency, so as to promote the increasing number of patents. On the other hand, patents are only the phased achievement form of technological innovation. The increase of the number of patents drives the increase of innovation income. In addition, enterprises need to form new products and services through the commercial transformation of patent achievements. The lack of efficiency in the transformation of scientific and technological achievements is also an important problem to be solved in the development process of technological innovation in China, although the optimization of institutional environment can effectively improve the efficiency of technological achievements transformation [24]. However, from the development experience of developed economies, the huge gap between the number of patents and innovative products and services is often difficult to be effectively alleviated, which can further explain the huge difference in the growth trend and magnitude of enterprise income and the number of enterprise patents under the influence of the re-innovation support system of enterprises with failed innovation.

4.3 Sensitivity analysis

Sensitivity analysis is based on the adjustment of the variable value in the re-innovation support system of enterprises with failed innovation, and analyzes its impact on the overall system operation effect. It mainly tests the impact of constant variable changes such as talent policy, financial policy, R&D subsidy intensity and legal environment construction intensity on the operation effect of the re-innovation support system of enterprises with failed innovation.

The initial value of talent policy variable is 1, and then it is transferred up and down twice of the initial value respectively, it is assigned to 0.5 and 2 respectively, and the differences between the system operation and the initial state are compared and analyzed. Figure 8 reports the impact of increasing and decreasing talent policies on the number of enterprises with failed innovation. It can be seen that when the talent policy is reduced, the fitting curve of the number of enterprises with failed innovation will move to the top of the initial state. It shows that when the talent policy incentive is insufficient, it will lead to the lack of R&D personnel in the process of technological innovation, and it is more likely to greatly affect the technical level of R&D personnel. This leads to the defect of technological innovation ability, increases the probability of innovation failure, and increases the number of enterprises with failed innovation.

Fig. 8

The impact of talent policy changes on the number of enterprises with failed innovation.

In the initial state, the value of financial policy variable is 0.005, while in the case of other variables with the same initial value; the value of financial policy variable is changed to 0.1 and 0.001 respectively. Figure 9 shows the changes in the impact of financial policy on the number of enterprises with failed innovation. It can be seen that with the increase of financial policy, the decreasing trend of the number of enterprises with failed innovation will be further increased, which shows that financial policy strength can further activate the marketization of the financial industry, and provide a richer way for enterprises to obtain external financing for technological innovation.

Fig. 9

Impact of financial policy changes on the number of enterprises with failed innovation.

The R&D subsidy intensity variable is set to 0.003 in the initial state of the system, and the mobilization values are changed to 0.1 and 0.0001. Figure 10 reports the impact of R&D subsidy intensity change on the number of enterprises with failed innovation. The results show that, with the increase of government subsidy intensity, the decline range of the fitting curve of the number of technological innovation failure enterprises will further expand, which shows that the increasing intensity of government R&D subsidy can significantly reduce the probability of technological innovation failure, thus reducing the number of enterprises with failed innovation. However, it should be noted that theoretical and practical exploration show that the government’s R&D subsidy incentive means often have two-way effects, namely, the crowding out effect and crowding in effect on the innovation investment of enterprises. Therefore, the use of R&D subsidy incentive methods should be more cautious.

Fig. 10

The influence of R&D subsidy intensity on the number of enterprises with failed innovation.

Figure 11 reports the impact of changes in the intensity of legal environment construction on the number of enterprises with failed innovation. In the initial state of the system, the initial value of the legal environment construction intensity variable is set to 0.5, and the mobilization values are 1 and 0.01 respectively. It can be seen that when the construction intensity of the government to the legal environment is increasing, the number of enterprises that fail in technological innovation is also decreasing accordingly, which further shows that the continuous optimization of the legal environment and the continuous improvement of the intellectual property system can not only provide protection for the intellectual property achievements of enterprises, but also effectively regulate the negative acts of intellectual property infringement in the process of technological innovation, thus reducing the possibility of technological innovation failure.

Fig. 11

The impact of the intensity of legal environment construction on the number of enterprises with failed innovation.

5 Conclusions

From the perspective of institutional environment, this study constructs a re-innovation support system for enterprises with failed innovation, and defines the system boundary, including the constituent elements of enterprises with failed innovation, government departments, research institutes and intermediary service institutions, as well as the relationship between them. On this basis, the system flow graph and the main structural equations of the re-innovation support system of enterprises with failed innovation are established by using the system dynamics method, and the intelligent simulation of the system operation effect is carried out. The following conclusions are drawn: institutional support can effectively reduce the number of enterprises with failed innovation, increase the number of re-innovation enterprises, and further improve the enterprises income and government revenue, and verify the effectiveness of the re-innovation support system of enterprises with failed innovation.

Footnotes

Acknowledgments

This study was supported by the National Social Science Fund of China (Grant No. 18CJL006).

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