2017 International Conference on Education Innovation and Economic Management (EIEM 2017) ISBN: 978-1-60595-495-0

Research on the Relationship Between Organizational Inertia and Ambidextrous Technological Innovation:

The Influence of Network Position

Ping ZHANG, He-ming FENG and Shu-yin LIANG

School of Business Management, South China University of Technology, P.R. China

Keywords: Ambidexterity Technological Innovation, Organizational Inertia, Network position.

Abstract. Facing the fierce market competition, enterprises need to handle the relationship between the existing technologies and technological innovation well. This study takes the Pearl River Delta manufacturing enterprises as the research object. From the perspective of combining internal and external factors, we explored how enterprises weigh exploitative technological innovation and exploratory technological innovation. Results of this study show that resource rigidity has positive relationship with exploitative technological innovation and negative relationship with exploratory technological innovation; routine rigidity is positively related to exploitative technological innovation and negatively related to exploratory technological innovation. The network position plays a negative moderating role on the relationship between resource rigidity and exploitative technological innovation, resource rigidity and exploratory technological innovation, routine rigidity and exploratory technological innovation.

Introduction

After China's economy entered a new normal, the uncertainty and complexity of competitive market have increased a lot. In order for the efficient and sustainable development, companies are faced with the choice between consolidating the existing technologies, retaining the current market field and developing new technologies. It has become a research focus on how to weigh the exploitative technological innovation and exploratory technological innovation, and carrying out ambidexterity technological innovation. Existing researches on ambidexterity technological innovation mainly came from the organizational view to achieve mechanism antecedent variables, discussing the effects of organizational structure, leadership behavior, organizational resources, capabilities and other factors on the ambidexterity technological innovation. Technological innovation activities cannot be completely divorced from the company's existing resources, which may be affected by organizational inertia. From another aspect, technological innovation enterprises with limited resources depend on the heterogeneous resources and capabilities gaining from partners outside the network. Therefore, scholars concerned about the inter-enterprise network ambidexterity’s impact on technological innovation across the organizational boundary. In an open network environment, network location determines the quality and access to resources from the network relationships. This study will combine internal and external level of analysis to study the inherent ambidexterity mechanism’s effect on technological innovation. We will study how does organizational inertia affect ambidexterity technological innovation? And how the network position plays the moderating role.

Theory and Hypotheses

Resource-based theory regards the enterprise as a resource assembly (Wernerfelt, 1984), and thus resource acquired within or without the enterprise is the basis of technological innovation. The resources that can be deployed by innovative companies have a crucial impact on the exploitative technological innovation and exploratory technological innovation. Innovative enterprise resources can be obtained from within or without the enterprise. Resources are limited and scarce inside the

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organization. Because of the resource constraints, companies should allocate internal resources for the exploitative technological innovation and exploratory technological innovation (Feng Zhong Lei et al., 2014). In terms of the outside, companies are in an open external environment. Working together with other companies helps build an enterprise network. In the network, the organization will gain more access to new knowledge and resources. Different network locations determine the quality and difficulty of getting resources (Juan Zangjin et al., 2012). Only integrating internal and external factors affecting by the ambidexterity technological innovation, organizations are able to fully understand the impact of microscopic mechanism of ambidexterity technological innovation.

Enterprises in the role of organizational inertia will carry out technological innovation along the path of existing resources and organizational processes. In the development of ambidexterity technological innovation activities, the intensity of organizational inertia will affect the allocation of resources for the enterprise to exploitative technological innovation and exploratory technological innovation. In terms of the network, enterprises in different network positions, in an open network environment (Allee, 2006), determines how many resources that they can obtain innovation from the network, which have an impact on the development of the internal allocation of resources in the innovation activities. Therefore, this study chooses the organization inertia as the independent variable, and the network position as the moderating variable, to further discuss the micro mechanism of the ambidexterity technological innovation.

The influence of Organizational Inertia on Ambidexterity Technological Innovation

Technological innovation activities have a high degree of situational dependence (Li Jianli, 2010). Innovation activities cannot be completely divorced from the existing resources and organizational processes, and will be constrained by the inertia of the organization (ET al. Chandy, 1998). In the dynamic environment, enterprises want to guarantee the long-term competitive advantage. On the one hand, enterprise need to make full use of existing knowledge and the technology to ensure profitability. On the other hand, enterprises need to continue to explore new knowledge and technology to meet the needs of future competition. However, there is a certain internal conflict between the technological innovation and the exploratory technology (Li Jianli, 2009), which requires for enterprise resource investment, capacity support, organization modes, management modes, etc. Therefore, in the process of carrying out technological innovation activities, enterprises face the problem of balancing between the exploitative technological innovation and exploratory technological innovation activities.

This study will adopt Gilbert (2005) division method of organization inertia, to explore two dimensions of organizational inertia: resource rigidity and old-fashioned program of ambidexterity technological innovation effect. When the resource rigidity performance is under the impact of external environment, the enterprise has failed to change the investment model of its resources (Gilbert, 2005). From the perspective of resource dependence, stakeholders like suppliers, customers and investors constitute the value network, in which customers and investors have the key resources of enterprises. Only if the enterprise produces the products or services that meet the requirements of the functions from customers and those of profit from investors, can we use and control the resources that we need. Under the conditions of resource constraints, with the enhancement of enterprise resources conservative, the company's existing network will subsequently be strengthened. The resources of the enterprise investment will focus on exploitative technological innovation tracking along the product performance improvement that the existing customer value, rather than the exploratory innovation that deviates from the main stream of customer requirements and does not conform to the existing investors value, which leads to the exploitative technological innovation activities always precede exploratory technological innovation activities to obtain resources (Chen Lixin, 2008). Therefore, the resources of enterprises will have a positive impact on exploitative technological innovation activities, and have a negative impact on exploratory technological innovation activities.

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Therefore, this study proposes the following hypotheses: Hypothesis 1A: Resource rigidity will be positively related to exploitative technological innovation; Hypothesis 1B: Resource rigidity will be negatively related to exploratory technological innovation.

The old-fashioned program failed to change the procedure of using these resources, in the face of the dynamic environment (Gilbert, 2005). Due to the stereotypical programs, enterprises’ innovative activities will be based on inherent organizational processes and innovative activities. In a certain extent, it ensures that the organization's stability can effectively support the operation of the existing business. It is conducive to the use of technological innovation in an orderly manner (Nelson et al., 1982). Old-fashioned program mainly comes from the dominant logic of management, which makes managers look at new things by fixed thinking patterns. As a result, they are not sensitive to external changes, which cannot be timely and correctly identify technological changes in the generating of new opportunities. And exploratory technological innovation, as the development of new technology and new capacity, requires for a timely new practice and behavior patterns. With the strengthening process of the enterprise old patterns, more enterprises will be limited by the original mode of thinking. Path dependence degree will deepen (Jansen et al., 2006)and inhibit the exploration of new model of intention and behavior, which leads to the defects of abilities of enterprises to explore the technology innovation (Chen Lixin, 2008). From another point of view, enterprise in search for a new convention will tend to search in the existing practice rather than encourage a fundamental change in the original convention, which may depress the effective absorption the speed of external resources and knowledge. It is not conducive to explore the effective development of technological innovation. Therefore, this study proposes the following hypotheses: Hypothesis 2A: Old-fashioned program will be positively related to exploitative technological

innovation; Hypothesis 2B: Old-fashioned program will be negatively related to exploratory technological

innovation.

Network Position

Network theory believes that the enterprise is in an open network environment (Allee, 2006). Each enterprise’s position in the network is different, meaning that each enterprise can benefit different abilities from the network. Enterprises occupying the position of dominant network have many advantages in innovative activities (Powell & Owen-Smith, 2004; & Nobeoka Dyer, 2000). Network position represents status, power and relative stable relationship between the enterprises in the network (White, 1992). Different network position means that enterprises can obtain different resources and opportunities in the network (Chen, 2006). The access to resources and knowledge is the key to innovation activities. Therefore, the network position has important influence on technological innovation (Tsai, 2001). The enterprise in the center position of the network is more easy to obtain and control more types of innovation resources (Hossain, 2009). They could take advantage of the information (Powell et al., 1996), have diversified and unimpeded channels of the knowledge and information, as well as reduce the costs and risks of innovation and improve the efficiency of innovation (Huang, 2004).

The companies, in the center position of the network, have more strong connection. Companies gain access to more information and resources in the companies as well as industry. It is conducive to the improvement of existing knowledge and technology. Companies can better coordinate and grasp the network resources’ allocation situation, because of allocation ability of the network information and resources (Zeng Deming, 2012; Chen Xiaolin, 2012). To a certain extent, companies have broken the inherent mode of resource input, weakening the impact of resource conservation on the use of technological innovation. And for the exploratory technological innovation, the companies located in the center of the network have the advantage to occupy the knowledge, resources, information control, and able to obtain diversified resources and information. In the center of the network, the companies can easier integrate complementary resources, get more chances to cooperate with the best companies, gathering different companies complementary skills (Qian Xihong, 2010), in favor of disengagement or exceed the original knowledge, innovation and technology to carry out exploratory

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technique, which can weaken the negative effect of conservative resources of exploratory technological innovation.

Enterprises in the control center position of network can attract more excellent cooperation partners and form a high degree of cooperation, friendship and trust with other enterprises, promoting the transfer of implicit knowledge in the network. But interacting frequently with other companies makes the central enterprises perceive the external environment threats quickly, and this will intensify the old-fashioned procedures (Gilbert, 2005), making enterprises think and act rigidly. It is not conducive for the companies to learn external knowledge and deepen the existing knowledge system, to weaken the positive impact of the exploitative technological innovation. For exploratory technological innovation, program old-fashioned will make the enterprise reduce the dynamics of exceeding the existing knowledge stock. But the enterprise located in the center of the network through contacting diversified knowledge, enhancing their learning ability to learn, and promoting the enterprise to integrate internal and external information and developing new knowledge (Brown, 1991). And the advantage position can reduce the search cost and uncertainty of new opportunities, weakening the negative impact of old-fashioned program on the exploratory technological innovation.

Therefore, this study proposes the following hypotheses: Hypothesis 3A: Network position negatively moderates the relationship between the resource

rigidity and exploitative technological innovation. It is the network location that will weaken the impact of resource rigidity on technological innovation.

Hypothesis 3B: Network position negatively moderates the relationship between the resource rigidity and exploratory technological innovation. It is the network location that will weaken the impact of resource rigidity on the exploratory technological innovation.

Hypothesis 3C: Network position negatively moderates the relationship between the old-fashioned program and exploitative technological innovation. It is network position that will weaken old-fashioned program’s effect on exploitative technological innovation.

Hypothesis 3D: Network position negatively moderates the relationship in the old-fashioned program and exploratory technological innovation. It is network position that will weaken old-fashioned program’s effect on exploratory technological innovation.

The Questionnaire Design

Definitions and Measurement Variables

Ambidexterity technological innovation. Use Atuahene-Gima (2005), Wu Yong’s (2013) scale, 10 questions, to measure exploitative technological innovation and exploratory technological innovation.

Organizational inertia. Use Gilbert (2005), Chen Lixin (2008), Zhao Yap (2012)’s organizational inertia scale. The scale has nine questions.

Network position. Referring to existing research and combining with the purpose of this study, this article will use the index to describe the central network position. Use Batjargal (2001), Tsai (2001) Dou Hongbin (2012) scale with four questions of metrics to measure the center of a network position.

Control variables. Studies have shown that technological innovation will be affected by firm age, size, social capital and other factors (Takara seek et al., 2009; Zhang Jianyu, 2014; Zhang Yu et al., 2013). Enterprise establishment time is beneficial to the accumulation of innovative experience (Sorensen and Stuart, 2000). The scale of the enterprise also affects its innovation ability. According to industry attributes, manufacturing enterprises can be divided into high technology industry and general manufacturing industry. Due to the different technological content, the two industries have some differences in the technological change and innovation ability. Therefore, this article selects age, scale, capital, industry and so on, as control variable.

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Questionnaire Pre-Testing and Determination

The questionnaire used Likert five-point scale, from "very much in line" to "totally inconsistent" scores given 5-1 points. Prior to this study, the initial design of the questionnaire conducted a pre-test. The initial aim of the preliminary scale is to do reliability and validity analysis, detecting whether there is a questionnaire design unreasonable and improve the questionnaire. To do pre-test, we distributed 150 questionnaires to South China University of Technology’s MBA students working in manufacturing companies. We called back of 64 copies, which had 60 valid questionnaires.

Validity Analysis. Validity is the extent to which the scale can accurately measure the content of the content that you want to measure. The scale of technological innovation, network position and technological innovation performance has been proved by a large number of studies in the domestic and international research, which ensures the validity of the scale. As for the weight table of organizational inertia this research developed, under the theoretical framework of Gilbert (2005), organizational inertia is divided into resource rigidity and procedural old-fashioned. This paper induced and refined 10 measurement problems from related literature, and refer to the translation of the American Academy of Management Journal of best paper by Pei Xuecheng (2012), in order to ensure the content validity of the scale. This paper also uses the factor analysis method to examine the discriminant validity of the questionnaire. Generally speaking, the problem of factor load is more than 0.50 can be retained. Each item is more than 0.5. That is each scale has good validity.

Reliability Analysis. Reliability is the reliability or stability of the scale. Internal reliability can measure the same concept. That is whether the inherent consistency of these issues can be measured in a stable manner. Testing reliability commonly uses internal consistency coefficient Cronbach α. A better reliability of the scale Cronbach α is 0.70 or more, indicating the scale has a higher reliability (Wu Minglong, 2000), there are some scholars believe that 0.50 is the lowest acceptable value (Bryman & Cramer, 1997). The Cronbach α of each scale were more than 0.60, so it had good reliability.

Reliability analysis and validity analysis of the initial questionnaire were carried out by pre-test. And then the questionnaire was modified and the formal questionnaire finally came out. (If you need, you can ask for it from the author).

Results

Questionnaire

This study used a questionnaire survey method to obtain the required data, with a professional survey of consulting companies. Random sampling method was used to select the object of investigation, and the samples were randomly selected from the list of manufacturing enterprises of Guangdong trade and Industry Bureau. Invited sample enterprises participated in the questionnaire survey by telephone interview and mail return visit. The questionnaire survey was conducted from February 2016 to November 2015. In the investigation, we issued 600 questionnaires, 185 questionnaires were recovered. The recovery rate was 30.83%. After removing 39 invalid questionnaires, we had the 146 valid questionnaires ultimately. The effective recovery rate was 24.33%.

Validity Analysis

In this paper, the AMOS software was used to verify the validity of the scale. Examinations were mainly through the calculation of 2/df, GFI, NFI x, CFI, RMR, RMSEA index. Refer to the relevant literature, χ2/df less than3, GFI, NFI, CFI greater than 0.9, RMR less than 0.05 and RMSEA less than 0.08 is appropriate. From table 1, validity analysis results can be seen, the index of the variables are basically consistent with the criteria. Individual variables of RMSEA index did not reach the best standards, but are in acceptable range. And the factor loadings are greater than 0.7. The results show that all the variables have good validity.

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Reliability Analysis

In this study, the Cronbach α coefficient was used to test the reliability of the scale. The greater the Cronbach α is, the better the internal consistency of the scale is used. From the results of the reliability analysis of Table 2, we can see that the Cronbach α of each variable is greater than 0.7, and the correction of the total correlation is greater than 0.4. The results show that all the variables have good reliability.

Table 1. Validity analysis.

Variables Items Factor loading Confirmatory factor analysis

Technological innovation

Utilizable technological innovation

B1 0.925

χ2/df=2.496 GFI=0.911 NFI=0.944 CFI=0.965

RMR=0.029 RMSEA=0.100

B2 0.938

B3 0.918

B4 0.850

B5 0.848

Exploratory technological innovation

B6 0.807

B7 0.850

B8 0.868

B9 0.875

B10 0.863

Organization inertia

Resource rigidly

C1 0.734

χ2/df=2.125 GFI=0.924 NFI=0.893 CFI=0.939

RMR=0.031 RMSEA=0.087

C2 0.776

C3 0.803

C4 0.783

C5 0.743

Old-fashioned program

C6 0.756

C7 0.699

C8 0.740

C9 0.755

Network position （central）

D1 0.872 χ2/df=2.330 GFI=0.960 NFI=0.946 CFI=0.967

RMR=0.017 RMSEA=0.094

D2 0.841

D3 0.865

D4 0.713

Correlation Analysis of Statistical Variables

In this study, we use SPSS 19.0 software to analyze the correlation of organizational inertia, network location, technology innovation, technology innovation performance and other variables, to understand the status of organizational inertia, network position, technological innovation, technological innovation performance, and to explore the statistical results. The statistical analysis of the correlation of each variable is shown in table 3.

Regression Analysis

Regression Analysis of Organizational Inertia on Ambidexterity Technological Innovation. The two dimensions of organizational inertia, resource rigidity and old-fashioned program are independent variables. We did the regression analysis of the two dimensions of the ambidexterity technology innovation of the dependent variable: the exploitative technological innovation and exploratory technological innovation. Model1 and model4 are control variables. The regression results are shown in table 5.

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The influence of resource rigidity on ambidexterity technological innovation It is known from the results of table 5 that the influence of resource conservation on technological

innovation is significant, and the regression coefficient is 0.173. This indicates that the resource rigidity and exploitative technological innovation is positively related, assuming that H1A was supported; Resource conservation has a significant impact on the exploratory technological innovation, and the regression coefficient is -0.195. This explains the negative correlation between resource rigidity and exploratory technological innovation, assuming that H1B was supported.

Table 2. Reliability analysis.

Variables Items Coefficient of α Total correlation of corrected item The value of α deleted items

Exploitative technological

innovation

B1

0.936

0.871 0.914 B2 0.890 0.911 B3 0.860 0.917 B4 0.774 0.932 B5 0.772 0.934

Exploratory technological

innovation

B6

0.906

0.702 0.898 B7 0.761 0.886 B8 0.782 0.880 B9 0.795 0.878

B10 0.778 0.881

Resource rigidly

C1

0.825

0.576 0.803 C2 0.633 0.787 C3 0.666 0.777 C4 0.641 0.786 C5 0.588 0.800

Old-fashioned program

C6

0.718

0.533 0.644 C7 0.463 0.684 C8 0.511 0.654 C9 0.525 0.645

Network position （central）

D1

0.839

0.742 0.765 D2 0.685 0.790 D3 0.735 0.768 D4 0.539 0.856

Technological innovation performance

E1

0.892

0.747 0.865 E2 0.741 0.867 E3 0.754 0.864 E4 0.706 0.875 E5 0.728 0.870

Table 3. Correlation analysis of variables.

Resource

conservation Old-fashioned

program Network position

Exploitative innovation

Exploratory innovation

Age Scale Capital Industry

Resource conservation

1 0.521** 0.079 0.176* -0.190* 0.125 0.183* 0.059 0.087

Old-fashioned program

1 0.092 0.189* -0.147 0.169* 0.211* 0.116 -0.017

Network position

1 0.230** 0.240** -0.132 -0.042 -0.060 0.138

Exploitative innovation

1 0.546** 0.002 0.271** 0.339** -0.057

Exploratory innovation

1 -0.074 0.091 0.160 0.019

Age 1 0.637** 0.608** -0.314**

Scale

1 0.607** -0.033

Capital 1 -0.284**

Industry

1

Old-fashioned Program Effects on Ambidexterity Technological Innovation

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According to the analysis results from the regression, old-fashioned program affecting the exploitative technological innovation significantly. The regression coefficient was 0.167. This shows that the positive correlation between old program and utilizable technological innovation. Hypothesis H2A was supported. The old-fashioned program significantly affect exploratory technological innovation. The regression coefficient is -0.155. The old-fashioned program and explorative innovation are negatively correlated, assuming that H2B was supported.

Analysis of Network Position. In this study, we select the network location to explore its moderating effect on organizational inertia and the two dimensions of ambidexterity technological innovation ambidexterity technological innovation: the exploitative technological innovation and the exploratory technological innovation. Table 6 is the result of the regression of the moderating variable network position.

The moderating effect of network position on the relationship between resource rigidity and ambidexterity technological innovation

The model 7 added the independent and dependent variables into the regression equation. The F value of the regression equation was 8.973, reaching a significant level of 0.001. The regression equation was significant. On the basis of that, we standardized resources rigidity and the network position, calculating the interaction terms between them. In model 8, the interaction term between the independent variable resource and the network position is added, and the regression analysis is carried out. The F was 8.650, which reached a significant level of 0.001, and the regression equation was significant. Resource rigidity and network position interaction coefficient is significant, adjusted R2 also rise from 0.248 to 0.270. The interaction coefficient of resource rigidity and network position was -0.174, indicating that the network position negatively influenced the relationship between resource rigidity and exploratory technological innovation. Hypothesis 3A was supported.

Similarly, model 11 added independent and dependent variables into the regression equation. The regression equation F is 4.626, which was significant, above 0.01. The regression equation was significant. Based on this, we standardized the resource rigidity and network position data, calculating the interaction term. In the model 12, we added interaction terms. The value of F was 4.381, which reached a significant level of 0.001, and the regression equation was significant. The coefficient of interaction of resource rigidity and the network position is significant. The adjusted R2 was also increased from 0.111 to 0.123, and the resource rigidity and network position of the interaction coefficient is -0.135. This indicates that the network position negatively moderated the influence of old-fashioned program on exploratory technological innovation. H3B was supported.

The moderating effect of network position on the relationship between old-fashioned program and ambidexterity technological innovation

The model 9 added the independent (old-fashioned program& network position) and dependent variables (exploratory technological innovation) into the regression equation. The value of F was 7.434, reaching a significant level of 0.001. The regression equation was significant. On the basis of that, we standardized old-fashioned program and the network position and calculating the interaction terms between them. In model 10, the interaction term between the independent variable resource and the network position was added, and the regression analysis is carried out. The value of F was 6.986, which reached a significant level of 0.001, and the regression equation was significant. Resource rigidity and network position interaction coefficient is significant, adjusted R2 also from 0.182 rise to 0.199. The coefficient of the interaction between old-fashioned program and network location was -0.174, indicating that network position negatively influenced the relationship between old-fashioned program and exploratory technological innovation. Therefore, this finding provides support for H3C.

Similarly, model 13 added independent (old-fashioned program& network location) and dependent variables (exploration technology innovation) into the regression equation. The value of F was 4.086, reaching a significant level of 0.001. The regression equation was significant. On the basis of that, we standardized old-fashioned program and the network position, calculating the interaction terms between them. In model 14, the interaction term between the independent variable old-fashioned program and the network position was added, and the regression analysis was carried out. The value of F was 3.418, which reached a significant level of 0.001, and the regression equation was

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significant. But the interaction coefficient of old-fashioned program and network position was insignificant, indicating that network position cannot adjust the relationship between old-fashioned program and exploratory technological innovation. This finding is opposite to the prediction of H3.

Discussion and Conclusions

The Effect of Organizational Inertia on Ambidexterity Technological Innovation

According to the resource dependence theory and organizational learning, this paper finds that the organizational inertia has both positive and negative impact on ambidexterity technological innovation. From the perspective of resource dependence, the ability of obtaining and maintaining resources is the key to the survival of enterprises (Pfeffer, 1978). It depends on the ability of the enterprise to match and coordinate with the external environment. The exploration and consolidation of this kind of ability is also the driving force in the enterprise to encourage innovation. Enterprises acquire and maintain resources from external environment and reduce the dependence on external resources in order to adapt to changes in the environment and keep the competitive advantage through control of organizational inertia, so as to ensure the stability and continuity of innovation resources, which shows that the organizational inertia has a positive effect on technological innovation. And from the perspective of organizational learning, rules of process that came from organizational inertia make the mode of thinking and action solidified, hindering the absorption of new knowledge and new things. Consequently, organizations miss the opportunity to learn new knowledge and to open up new areas, which could become the obstacles in the process of technological innovation. Therefore, the impact of organizational inertia on ambidexterity technological innovation will be complex. This is consistent with the finding of Liu Min (2011), who realized that organizational inertia is double-edged sword.

Table 4. Regression results of the influence of organizational inertia on ambidexterity technological innovation.

Model

Exploitative technological innovation Exploratory technological innovation Model 1 Model 2 Model 3 Model 4 Model 5 Model 6

Coefficient

Significance

Coefficient

Significance

Coefficient

Significance

Coefficient

Significance

Coefficient

Significance

Coefficient

Significance

Constants 3.659***

0.000 3.046*

** 0.000

3.064***

0.000 3.479*

** 0.000

4.168***

0.000 4.030*

** 0.000

Age -0.426***

0.000 -0.442***

0.000 -0.439***

0.000 -0.292

* 0.012

-0.275*

0.017 -0.280

* 0.016

Scale 0.263

* 0.032

0.226+

0.064 0.225

+ 0.065 0.072 0.582 0.115 0.381 0.108 0.414

Capital 0.392

** 0.001

0.413***

0.000 0.408***

0.000 0.290* 0.022 0.266* 0.033 0.275* 0.028

Industry -0.07

1 0.404 -0.086 0.307 -0.069 0.412 0.012 0.893 0.029 0.746 0.010 0.908

Resource rigidity

0.173* 0.024 -0.195

* 0.019

Old-fashioned

program

0.167*

0.030 -0.155

+ 0.063

R2 0.208 0.236 0.234 0.075 0.111 0.098 Adjusted

R2 0.185 0.209 0.207 0.049 0.079 0.065

F 9.234***

0.000 8.642*

** 0.000

8.551***

0.000 2.855* 0.026 3.492*

* 0.005

3.030**

0.002

Note：Sample N=146；*** P<0.001, ** p<0.01, * p<0.05, + p<0.10, two-tailed test

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Table 5. Regression results of network position regulation.

Model

Exploitative technological innovation Exploratory technological innovation

Model 7 Model 8 Model 9 Model 10 Model 11 Model 12 Model 13 Model 14

Coefficient

Significan

ce

Coefficient

Significan

ce

Coefficient

Significan

ce

Coefficie

nt

Significanc

e

Coefficie

nt

Significan

ce

Coefficie

nt

Significan

ce

Coefficient

Significan

ce

Coefficie

nt

Significanc

e

Constants

2.499**

* 0.000

2.462**

* 0.000

2.934**

* 0.000

2.864**

* 0.000

3.794**

* 0.000

3.701**

* 0.000

3.675**

* 0.000

3.658**

* 0.000

Age -0.412***

0.000 -0.374**

* 0.000

-0.344**

0.001 -0.361**

0.001 -0.19

8+ 0.075

-0.179

0.106 -0.20

2+ 0.072

-0.206+

0.069

Scale 0.225+

0.058 0.238*

0.043 0.467**

* 0.000

0.453**

* 0.000

0.268*

0.012 0.239*

0.025 0.269*

0.012 0.265*

0.014

Capital 0.403**

* 0.000

0.321**

0.006 0.398**

0.001 0.372**

0.001 0.254*

0.036 0.211+

0.096 0.263*

0.031 0.261*

0.035

Industry

-0.107

0.193 -0.11

7 0.151

-0.178*

0.031 -0.20

3* 0.014

-0.049

0.570 -0.04

3 0.615

-0.074

0.393 -0.07

9 0.363

Resource

Rigidity

0.155*

0.039 0.160*

0.031 -0.230**

0.005 -0.222**

0.006

Old-fashione

d progra

m

0.12

5 0.108

0.158*

0. 046

-0.19

4* 0.018

-0.187*

0.027

Network

Position

0.212**

0.004 0.242**

0.001 0.218**

0.005 0.238**

0.002 0.250**

0.002 0.272**

0.001 0.253**

0.002 0.258**

0.002

RR×NP

-0.174*

0.025 -0.13

5+ 0.094

OP×NP

-0.156*

0.049 -0.03

7 0.658

R2 0.279 0.305 0.210 0.232 0.142 0.159 0.127 0.129

Adjusted R2

0.248 0.270 0.182 0.199 0.111 0.123 0.096 0.091

F 8.973**

* 0.000

8.650**

* 0.000

7.434**

* 0.000

6.986**

* 0.000

4.626**

0.001 4.381**

* 0.000

4.086**

0.001 3.418**

0.004

Note：Sample N=146；*** P<0.001, ** p<0.01, * p<0.05, + p<0.10, two-tailed test

The Regulation Function of Network Position

As for the moderating effect of the relationship between the organization inertia and the ambidexterity technological innovation, from the perspective of organizational learning, the path dependence of organizational inertia will hinder enterprises to learn new knowledge from outside world. The enterprise network is to gain learning opportunities from other enterprises in the network (Ghosh, 2004) to absorb as much knowledge as possible. Network is more convenient for enterprises to communicate, while transferring and sharing the knowledge, skills, abilities, and other intangible resources, therefore weakening the negative effects of organizational inertia. From this point of view, the strategic partnership and interaction, based on the network, is beneficial to the acquisition of superior resources. Network provides a legal way for the enterprise to obtain valuable resources (Fan Zhigang, 2010). In the enterprise network, it will form a relationship between the relationship lock and the cognitive lock, which will hinder the ability of enterprises to adapt to the changing environment, so as to strengthening the negative impact of organizational inertia.

Future Prospects

This research breaks through the boundary of organization, combining the internal and external organizational perspectives of creatively. In this paper, we study the effect of inertia on ambidexterity technological innovation and the moderating effect of external network position on the relationship between the two groups. Avoiding problems caused by internal and external factors, results from this

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study are helpful for the understanding of the impact mechanism of ambidexterity technological innovation, and the broader context of ambidexterity technological innovation.

The limitations of this study, of course, constrain our interpretations of the findings. First, this study only examined the organizational inertia and external network position, and discussed the influencing factors of ambidexterity technological innovation, which have negative effect on the micro mechanism of the ambidexterity technological innovation. Second, the samples of this study are limited to the manufacturing enterprises in Guangdong, which has some typical characteristics. It is still needed to be further explored and tested that whether the research conclusions can be applied to manufacturing enterprises in other regions.

Future research can be carried out from the following aspects: Firstly, this paper studies the impact mechanism of ambidexterity technological innovation from the perspective of network theory, resource based view and organizational learning theory. It is needed to be studied that whether there are other theories from other perspectives that could explain the micro mechanism of ambidexterity technological innovation. Second, this study selects the organizational inertia and external network position as the focus to do an empirical study of the impact of ambidexterity technological innovation. However, future study might further examine the internal and external factors of organization involved in the mechanism of the ambidexterity technological innovation.

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