Methodological analysis of the composition of innovation management: competences and the impact of its elements on innovation performance

INTRODUCTION

The main research purpose of this paper is to clarify the constituent factors of innovation management competence and the influence of different factors on innovation performance.

Through the questionnaire survey of high-tech enterprises, 206 valid data were collected, and factor analysis was carried out through SPSS25 to verify the factor composition of different variables and their contribution to the innovation performance of high-tech enterprises, and to clarify the composition system of innovation management competences.

Most of previous researches are still in the theoretical stage, and the main research content focuses on the importance of innovation management and the impact of innovation management on innovation performance. Few studies have analyzed the specific components of innovation management competence, and the specific content of different factors. Almost no studies have empirically analyzed the contribution of different innovation management competence factors to innovation performance through actual data.

For companies that want to truly improve their innovation management competences, needs to clarify the specific composition of innovation management competences and the contribution of different elements to the improvement of innovation management competences, to realize the optimal allocation of invested innovation resources.

In the first part of this paper, on the basis of previous research the author puts forward five hypotheses, namely, innovative strategic management competences, innovative organizational culture, innovative organizational structure, innovative knowledge management competences, innovative project management ability have a significant positive impact on innovation performance

The second part mainly focuses on the design of the questionnaire, including how to develop the scale, and clarifies the variable composition and measurement of innovation management ability, and conducts a descriptive statistical analysis of the collected questionnaires.

In the third and fourth part of this paper, by using SPSS 25.0 to carry out the data analysis of the relationship between innovation management ability and innovation performance, firstly, the author analyzes the reliability and validity of the questionnaire, then performs factor analysis on the variables to find out the key factors. Then, the author carries out multiple regression analysis to verify the research hypothesis, clarifies the relationship between variables and innovation performance, and the contribution of different variables to innovation performance.

The research results of this paper have an important reference for high-tech enterprises to improve their innovation management competences and improve their innovation performance. The five components of innovation management competences have specific corresponding indicators and contents. Enterprises can compare their own development to identify the cause of low innovation performance or long-term lack of breakthrough growth in innovation performance. Find the shortcomings of innovation management competences and effectively improve innovation performance.

1. Methodological analysis of the composition of innovation management competences and the impact of its elements on innovation performance

Regarding the composition of innovation management competence, Mao (2006) believes that innovation management competences are composed of strategic management competences, technological innovation management competences, market demand management competences, and basic management competences [3] (Mao Wuxing, 2006). Per Sundstrom (2009) believes that except innovation strategy perspective, projects management also important. He proposed that innovation management ability consists of the ability to construct innovative organizational culture, project management ability and innovative team building ability [19] (Per Sundstrom, Annika Zika-Viktorsson, 2009). Tidd (2006) believes that innovation management competence includes a whole process of innovation strategy formation and innovation project implementation.

On the basis of previous research, this paper proposes the five key components of innovation management competence: innovation strategic management competence, innovation organizational structure, innovation organizational culture, innovation knowledge management competence, and innovation project management competence.

The primary purpose of improving innovation management competences of enterprises is to better improve innovation performance. Therefore, this paper establishes the hypothesis that each factor has a significant positive impact on innovation performance.

Innovative strategic management competences

Innovation strategic management means that the enterprise determines its mission; the leadership attaches great importance to and supports innovation, and sets the enterprise's strategic goals according to the internal and external environment and internal conditions of the organization.

Richaed Adams [1] (Adams, Bessant, Phelps, 2006) and Benn Lawson [2] (Benn Lawson, Danny Samson, 2001) put forward the variables of innovation strategic management competence when analyzing the composition of innovation management competence. The results of Mao Wuxing's empirical analysis show that there is a positive correlation between innovation strategic management competence and enterprise innovation performance [3] (Mao Wuxing, 2006).

Therefore, this study establishes the following assumptions:

Hypothesis 1: Innovation strategic management competence has a significant positive impact on innovation performance.

Innovative knowledge management competences

Stevenson proposed that the essence of knowledge management is the means and tools used to control enterprise knowledge [4] (Stevenson, Gumpert, 1985). Liu proposed that The knowledge management process includes knowledge generation, acquisition, transfer, sharing, storage, reconstruction, utilization and protection [5] (Liu Lei, Qiao Zhong, Liu Chang, 2012). Tanigawa’s research shows the specific process mainly includes knowledge collection, organization, storage, learning, assimilation and application [6] (Tanigawa, An Yufa, Liu Chang, 2011).

Gold, et al. (2001) proposed that knowledge management competence have an important influence in the technological innovation performance of enterprises [7] (Gold, Malhotra, Segars, 2001). The influence of knowledge management ability on the performance of technological innovation of enterprises presents structural changes [8] (Xie Hefeng, 2012).

Therefore, this study establishes the following assumptions:

Hypothesis 2: Innovation knowledge management ability has a significant positive impact on innovation performance.

Innovative organizational structure

The organizational structure that supports innovation and the related organizational characteristics plays an important role in the implementation of innovation strategies and the development of innovation projects.

Zhao proposed that the formalization and specialization of organizational structures can effectively improve employee's working efficiency and has a positive impact on the performance output [9] (Zhao Xiaolu, 2008).

Wang found that the higher the degree of formalization of the organizational structure, the less resistance it is to coordinate with customers and departments of the enterprise [10] (Wang Hui, Chen Jianbin, Li Yuxia, 2011). Nahm’s study shows that the formalized organizational structure, the level of horizontal integration and the efficiency of internal communication have a positive impact on enterprise performance [11] (Nahm, Vonderembse, Koufteros, 2003).

Therefore, the study established the following hypotheses:

Hypothesis 3: The organizational structure that supports innovation has a significant positive impact on innovation performance.

Innovative organizational culture

Organizational culture is the spiritual connotation of an organization's values, concepts, beliefs, and habits. Culture that supports innovation can motivate employees to innovate, and encourage employees to continuously pursue culture with an innovative spirit and a spirit of cooperation.

Feng pointed out that organizational culture has a significant positive predictive effect on innovation competence and organizational performance, and innovation competence plays a certain mediating role in the relationship between organizational culture and organizational performance [12] (Feng Cailing, 2019).

Yin’s practical study pointed out that corporate culture has a significant impact on innovation cognition, decision-making and performance. The stability of corporate culture is also crucial, and a certain intensity of organizational value orientation are conducive to the acceptance and implementation of innovation decisions [13] (Yin Chong, 2009).

Therefore, this study establishes the following assumptions.

Hypothesis 4: An organizational culture that supports innovation has a significant positive impact on innovation performance.

Innovative project management competences

Elena Huergo illustrates the impact of technology management on innovation. Technology management variables including cooperation, technical specialization level, and market demand, innovation planning, innovation monitoring, special technical personnel and so on [14] (Elena Huergo, 2006). Thamhain's study emphasizes effective communication, effective project planning and support systems, stable long-term organizational goals and priorities that influence innovation performance and innovation outcomes, and illustrates the control of design innovation processes. Mechanisms are very important [15] (Thamhain, 1990). Therefore, this study established the following hypotheses:

Hypothesis 5: Innovation project management ability has a significant positive impact on innovation performance.

Innovation management competence is a comprehensive competence, different variable of innovation management competence together promote innovation performance. Therefore, this study establishes hypotheses to prove the relationship between the main constituent variables of innovation management competence and innovation performance, analyzes the impact of variables on innovation performance.

2. Research design on the relationship between innovation management competence and innovation performance

In this study, research on the relationship between innovation management ability and innovation performance is mainly conduct through questionnaires to collected date and make analyses.

The survey process mainly adopts the methods of Email, telephone survey and direct interview. A total of 360 questionnaires were distributed in the research on high-tech enterprises, and 206 valid samples were finally obtained, with an effective rate of 57.2%.

After analyzing the composition of innovation management variables, this study developed the scale. The development of the scale was mainly based on the research literature, and the scale with high reliability and validity was selected.

Table 1

Variable composition and measurement of innovation management competence

Innovation performance and its measurement

The measurement of innovation performance can measure the patents applied for and authorized by the company, the formulation of industry standards, and the market share of new products. Some studies suggest that innovation output can be measured by patents, including the number of patents, and the successful application of patents in a given period. Scherer’s research shows that patents are also related to the economy can measure the economic effects of patents by the profit of new products [21] (Scherer, 1988). Based on previous research on the measurement indicators of innovation performance, this study selected four indicators: the company has a satisfactory new product profit margin in the past three years, the market share of the company's new products, the company's patent applications in the past three years and in terms of the number of authorizations, the company plays a major role in the formulation of industry standards.

Descriptive statistical analysis was carried out on the obtained 206 valid sample data, and the samples of the questionnaires involved enterprises of different natures and industries, which were representative to a certain extent.

Table 2

Descriptive analysis of questionnaires

3. Empirical analysis and research conclusions of the impact of innovation management competence on innovation performance

By using SPSS 25.0 to carry out the data analysis of the relationship between innovation management ability and innovation performance, firstly, the factor analysis is carried out on the variables, and the reliability and validity of the questionnaire is analyzed to find out the key factors;

The reliability and validity of the questionnaire and the results of factor analysis

Before the factor analysis, the Bartlett test and KMO value test used in this study to determine whether the factor analysis is suitable. After factor analysis, reliability was tested using Cronbach's Alpha.

Table 3

KMO values of each measured variable and Bartlett's intensite test

Both the KMO value and Bartlett's test passed the test, indicating that the factor analysis is suitable as it shown in table 3.

Factors analysis of the variable innovation strategic management competence

In the process of factor analysis in this paper, the factor load of the variable is greater than 0.5 as the standard, and the items that do not meet the above requirements are eliminated.

Table 4

Factor composition of innovation strategy management competence variables

The lowest factor loading is 0.892. The explained variance of the factor is 0.90364>0.5. The Cronbach's Alpha value of the generated factor is 0.946>0.7, which indicates that the factor scale is reliable, has passed the consistency test, and has good reliability.

Table 5

Factor composition of the variables of innovative knowledge management competence

It can be seen from the analysis results that the lowest factor loading is 0.863, therefore all the items can be retained. The explained variance of the generation factor is 0.87299>0.5. The Cronbach's Alpha value is 0.925, which indicates that the factor table is reliable, has passed the consistency test, and has good reliability.

Table 6

Factor composition of innovative organizational structure

The lowest factor loading of the question term is 0.723; therefore all the question terms can be retained. The explained variance of the generation factor was 0.81136>0.5. The Cronbach's Alpha value is 0.961, which indicates that the factor table is reliable, and it has passed the consistency test, and has good reliability.

Table 7

Factor composition of innovative organizational culture

The lowest factor loading is 0.880. The explained variance of the factor is 0.87100>0.5. The Cronbach's Alpha value of the generated factor is 0.923>0.7, which indicates that the factor scale is reliable, has passed the consistency test, and has good reliability.

Table 8

Factor composition of innovation project management competence variables

The lowest factor loading of this item is 0.710; therefore all the terms can be retained. The explained variance of the generation factor is 0.71437>0.5. The Cronbach's Alpha value is 0.918, which indicates that the factor table is reliable, and it has passed the consistency test and has good reliability.

Table 9

Summary of Cronbach’s Alpha values for each measurement variable

Through factor analysis, the Cronbach's Alpha values of the five variables are all >0.7 and the overall reliability meets the requirements. Through the reliability test, the scale used in this study has a high level of reliability.

At the same time, the explained variances of each variable are all greater than 0.5, indicating that the scale has a good level of validity.

4. Innovation management and innovation performance regression analysis results

Before carrying out regression analysis, test for multicollinearity and normal distribution among variables. After passing the above test, carry out regression analysis on the variables to test the relationship between each variable and innovation performance.

Multicollinearity test

Table 10

Results of multicollinearity analysis

When 0<VIF<10, there is no multicollinearity; when 10<VIF<100, there is strong multicollinearity; when VIF>100, there is severe multicollinearity. If the tolerance of an independent variable is less than 0.1, the collinearity problem may be serious.

It can be seen from the above table that the VIF in all models is less than 10, so there is no close linear relationship between the assumed variables. It can be seen that there is no obvious multicollinearity in this study, and regression analysis can be carried out.

Normal distribution detection

Whether the data is normally distributed can be observed by using the Q–Q chart, which compares the degree of agreement between the theoretical quantile and the actual quantile. If it obeys a normal distribution, the data points basically coincide with the theoretical straight line.

From the above normal distribution graph, we can know that the points in the graph are roughly on a straight line, so the data satisfies the normal distribution.

Variable composition of innovation management competence and innovation performance

A regression analysis was carried out on the variables of independent innovation management competence and innovation performance. The fit of the model is shown in the following table with good goodness of fit, and the results are shown in table 11. It shows that the regression relationship can explain more than 95% of the variance of the dependent variable.

Table 11

Goodness of fit of the model

Regression analysis was carried out on innovation performance, and T-test was used for the results, sig < 0.05, the test results were significant, and the original hypothesis was accepted. The regression results are shown in table 12.

Table 12

Results of regression analysis

The standardized partial regression coefficient is to compare the degree of influence of each variable through standard normal transformation. It can be used to directly compare the influence degree of the corresponding variable of each variable, so the coefficient of the regression equation here can be used to determine the importance and weight of the variable.

According to the results of empirical analysis, innovation strategic management competence, innovation organizational structure, innovation organizational culture, innovation knowledge management competence, and innovation project management competence all have a significant positive impact on innovation performance. The correlation coefficients between the five variables and innovation performance are shown in table 13.

Table 13

Research model of the relationship between innovation management competence and innovation performance

Through regression analysis, it can be seen that the influence of each component variable on innovation performance is different, and the relative importance of each component variable can be judged by the correlation coefficient.

The innovation strategy management variables show the most significant relationship with innovation performance. Therefore, organizations need to attach importance to the accumulation of knowledge, establish a knowledge transformation and learning mechanism, and at the same time carry out organizational innovation strategy management, promote the participation of project-level personnel in the formulation of organizational strategies, and ensure the sharing of innovation strategies in the organization.

The innovation organization culture has the second influence on innovation performance. A corporate culture that supports innovation can motivate employees to innovate, and encourage employees to continuously pursue excellence.

The innovation organization structure has the third influence on innovation performance. It is necessary to build a flexible and diversified organization that can promote employee participation in decision-making, empower employees to have autonomy in the organization.

Innovation knowledge management ability also has a significant impact on innovation performance. The ability to generate high-quality innovative ideas in an organization and to ensure that innovative ideas can be selected and evaluated and implemented in the organization is a major factor affecting organizational innovation performance.

Innovation project management competences also have an important impact on innovation performance. Establish flexible plans in the organization, establish milestones, and coordinate through plan implementation and meetings. At the same time, ensure that team members have a sense of responsibility for innovation, find problems, collect data, and make team members responsible for innovation through task decomposition and responsibility decomposition.

CONCLUSION

On the basis of previous research, this paper combines the theoretical analysis of innovation management competence, as well as the analysis of the connotation and status quo of innovation management competence of high-tech enterprises, puts forward five hypotheses that is five variables, namely innovation strategic management competence, innovation knowledge management competence, innovation organizational structure, innovative organizational culture and innovative project management ability, all have significant positive effects on innovation performance.

The data collection method of this study was mainly through questionnaires. The survey objects are mainly high-tech enterprises that carry out innovation activities. 206 valid data were collected through questionnaire survey.

After collecting the data, factor analysis is carried out on the variables firstly, the reliability and validity of the questionnaire are analyzed, and the key factors of each variable are found out. Secondly, use SPSS25 to carry out multiple linear regression analysis to verify the research hypothesis and clarify the contribution of different variables to innovation performance.

According to the results of empirical analysis, all five variables have a significant positive impact on innovation performance, in descending order of influence, innovation strategy management competence, innovation organizational culture, innovation organizational structure, innovation knowledge management competence, and innovation project management competence.

The research results of this paper have an important reference value for high-tech enterprises to improve their innovation management competences and improve innovation performance. The five components of innovation management competences have specific corresponding indicators and contents.

Enterprises can identify the reasons for low innovation performance or the long-term lack of breakthrough growth in innovation performance, find the shortcomings of innovation management competences, and effectively improve innovation performance.