The effect of R&D internationalization on the innovation performance in Chinese high-tech firms

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Master’s Degree

in International Management

Final Thesis

The effect of R&D internationalization

on the innovation performance in

Chinese high-tech firms

Supervisor

Ch. Prof. Chiara Saccon

Graduand Xinger Tan

Matricolation number

871090

Academic Year

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Abstract

Using the samples of listed high-technology companies with oversea subsidiaries recorded in the China Stock Market and Accounting Research (CSMAR) Database, this paper discusses the effect of R&D internationalization on innovation performance in terms of intensity and di-versity. Additionally, this paper also tests the impacts of international experience, R&D input degree, firm’s age, firm’s size and firm’s financial situation on the relationship between R&D internationalization and innovation performance. The result is for Chinese high-tech firms, the degree of R&D internationalization intensity has an inverted U-shape effect on the innovation performance. Whereas the degree of R&D internationalization diversity has a U-shape effect on the innovation performance. Additionally, international experience slightly negatively mod-erating the relationship between R&D internationalization intensity and firm’s innovation per-formance, but it is not a significant moderator in the relationship between R&D internationali-zation diversity and firm’s innovation performance.

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List of Figures

Figure 1: FDI flows outward of China and the world ... 2 Figure 2: The inverted U-shape relationship between R&D internationalization intensity and innovation

performance ... 2 Figure 3: The U-shape relationship between R&D internationalization diversity and innovation performance.... 3

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Figure 1: FDI flows outward of China and the world

FDI flows outward of China and the world, Million US dollars, 2007-2017

Figure 2: The inverted U-shape relationship between R&D internationalization intensity and innovation performance

0 500,000 1,000,000 1,500,000 2,000,000 2,500,000 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 China (People's Republic of) World

Million US dollars

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Figure 3: The U-shape relationship between R&D internationalization diversity and in-novation performance.

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List of Tables

Table 1: Industry distribution of listed firms on the SSE and SZSE ... 5

Table 2: Variables and Definitions ... 6

Table 3: Variance inflation factor ... 7

Table 4: Descriptive statistics and correlation matrix ... 8

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Table 1: Industry distribution of listed firms on the SSE and SZSE

Industry distribution of listed firms on the SSE and SZSE

Industry Number of

firms

Agriculture, forestry, animal husbandry and fishing (A01-A05) 11

Mining and quarrying (B06–B12) 13

Manufacturing (C13–C43) 783

Manufacture of computer, communication equipment, electronic and

optical products (C3900) 146

Electricity, gas, steam and air conditioning supply & Water supply (D44-D46) 9

Construction (E47-E50) 22

Wholesale and retail trade (F51-F52) 23

Transportation, storage, Postal (G53-G60) 19

Accommodation and food service activities (H61-H62) 2

Information communication, software and information technology services

(I63-I65) 106

Financial and insurance activities (J66-J69) 22

Real estate activities (K70) 7

Leasing and business services (L71-L72) 22

Professional, scientific and technical activities (M73-M75) 20

Water, environmental and public facilities management (N76-N79) 13

Resident services, repairs and other services & Education (O80-P83) 2

Human health and social work activities & Arts, entertainment and

recreation (Q84–Q85, R86–R90) 24

Public administration, defense and social organization (S91-S96) 0

International organizations (T97) 0

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Table 2: Variables and Definitions

Variables and Definitions.

Variables Definitions

Dependent Variable

Innovation performance The number of patents a firm granted in a certain

year

Independent Variables

R&D int. intensity R&D internationalization intensity, ratio of R&D

sub-sidiaries

R&D int. diversity R&D internationalization diversity, Blau index of the

location of R&D subsidiaries

Moderator Variable

International experience Year of firm first involved into foreign business

Control Variables

Firm size Natural logarithm of the total employees' number

Firm age The age of a firm since it founded

R&D Intensity Ratio of R&D expenditures to the firm's sales

reve-nue

Financial leverage Ratio of total debt to the total assets in a given year

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Table 3: Variance inflation factor

Variance inflation factor

Variable VIF 1/VIF

R&D internationalization intensity X international experience 5.84 0.171378

R&D internationalization diversity X international experience 5.8 0.172311

R&D internationalization diversity 5.28 0.189503

R&D internationalization intensity 4.24 0.235821

International experience 2.35 0.425058 Firm size 1.44 0.693122 Financial leverage 1.36 0.737659 Firm age 1.23 0.814395 R&D intensity 1.17 0.852922 Mean VIF 3.19

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Table 4: Descriptive statistics and correlation matrix D escrip ti ve s tatis ti cs an d cor rel atio n m at ri x a . 8 1.000 * p < 0 .1, ** p < 0.05 , *** p < 0 .01 a N =819 b Lo ga ri th m 7 1.000 _0.212 *** 6 1.000 _0.333 *** 0.227 *** 5 1.000 _0.206 *** 0.048 _0.166 *** 4 1.000 -0.335 ** * -0.036 0.020 0.022 3 1.000 _-0.043 0.056 _0.385 *** -0.009 _0.116 *** 2 1.000 _0.176 ** -0.263 ** 0.428 *** 0.274 *** 0.193 *** 0.311 *** 1 1.000 _0.505 *** 0.07 ** 0.031 _0.283 *** 0.315 *** 0.196 *** 0.264 *** SD 62 .52 5 1.087 5.472 5.726 0.167 3.923 0.417 0.198 M ea n 43 .45 5 7.460 ₁₂.72 8 7.283 0.300 5.499 0.388 0.115 V aria bl es Inn ova ti on p er for m an ce Fi rm si ze b Fi rm ag e R & D i ntensi ty Fi na nci al l eve rag e Inte rna ti on al exp e ri en ce R & D i nter na ti on al izatio n intensi ty R&D inter na ti on al izatio n di versity 1 2 3 4 5 6 7 8

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Table 5: Results of regression analysis on innovation performance In n o v a tion p e rf o rman c e S ta n d a rd e rr o rs in b ra c k e ts ; * p < 0 .1 , ** p < 0 .0 5 , *** p < 0 .0 1 MOD E L 5 0 .4 4 0 4 *** [0 .0 1 6 6 ] -0 .0 0 6 5 [0 .0 1 1 9 ] 0 .0 2 6 7 *** [0 .0 0 2 7 ] 0 .0 4 9 5 [0 .0 6 8 7 ] 0 .1 4 6 4 *** [0 .0 1 2 7 ] -0 .8 3 7 8 *** [0 .3 0 7 6 ] 2 .8 4 9 2 *** [0 .6 0 9 4 ] -0 .0 0 0 7 [0 .0 1 0 2 ] 788 83 4 1 .6 7 *** MOD E L 4 0 .4 2 5 1 *** [0 .0 1 6 5 ] -0 .0 0 0 4 [0 .0 1 2 0 ] 0 .0 2 6 1 *** [0 .0 0 2 7 ] 0 .1 1 0 3 [0 .0 6 7 7 ] 0 .1 4 1 5 *** [0 .0 1 3 3 ] 1 .8 4 1 4 *** [0 .1 1 1 0 ] -1 .7 1 9 1 *** [0 .1 0 0 4 ] -0 .0 2 7 7 *** [0 .0 0 6 0 ] 788 85 1 5 .4 2 *** MOD E L 3 0 .4 4 0 3 *** [0 .0 1 6 4 ] -0 .0 0 6 4 [0 .0 1 1 9 ] 0 .0 2 6 7 *** [0 .0 0 2 7 ] 0 .0 4 9 5 [0 .0 6 8 7 ] 0 .1 4 6 3 *** [0 .0 1 2 6 ] -0 .8 4 5 3 *** [0 .2 8 9 5 ] 2 .8 5 4 2 *** [0 .6 0 5 5 ] 788 83 4 2 .2 7 *** MOD E L 2 0 .4 2 3 9 *** [0 .0 1 6 5 ] 0 .0 0 5 6 [0 .0 1 1 9 ] 0 .0 2 7 3 *** [0 .0 0 2 7 ] 0 .1 0 7 7 [0 .0 6 7 7 ] 0 .1 2 3 0 *** [0 .0 1 2 7 ] 1 .7 1 6 2 *** [0 .1 0 7 5 ] -1 .7 3 4 0 *** [0 .1 0 0 4 ] 788 85 2 0 .4 4 *** MOD E L 1 0 .4 6 0 5 *** [0 .0 1 6 2 ] 0 .0 0 5 2 [0 .0 1 1 8 ] 0 .0 2 7 8 *** [0 .0 0 2 7 ] 0 .1 5 8 2 ** [0 .0 6 7 3 ] 0 .1 3 9 4 *** [0 .0 1 2 5 ] 788 82 7 5 .0 7 *** V a riab les In te rc e p t Firm s iz e Firm a g e R & D int e n s it y Fina n c ial lev e ra g e In te rn a tion a l e x p e rien c e R & D int e rn a tion a liz a tion in te n s it y R & D int e rn a tion a liz a tion in te n s it y 2 R & D int e rn a tion a liz a tion d iv e rs it y R & D int e rn a tion a liz a tion d iv e rs it y 2 R & D int e rn a tion a liz a tion in te n s it y X int e rn a tion a l e x p e rien c e R & D int e rn a tion a liz a tion d iv e rs it y X int e rn a tion a l e x p e rien c e N _chi2

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List of Abbreviations

R&D Research and development

EMNE Emerging multinational enterprise

MNE Multinational enterprise

FDI Foreign direct investment

CSMAR China Stock Market and Accounting Research SSE Shanghai Stock Exchange

SZSE Shenzhen Stock Exchange

ISIC International Standard Industrial Classification NBSC National Bureau of Statistics of China

CNIPA China National Intellectual Property Administration

OLS

Ordinary least square

GLS Generalized least square GLM Generalized least model FEM Fixed-effect model REM Random-effect model VIF Variance inflation factors

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1 Introduction

With the deepening of economic globalization and firm internationalization, innovation has be-come an important source for companies to create and maintain competitive advantage in the global market. In order to take a place in the fierce competition, multinational corporations in developed countries are no longer satisfied to transfer only the processes of production, man-ufacturing and sales to aboard. Instead, they are eager to transfer their R&D activities in the upstream of the enterprise value chain to overseas, in order to maximize the use of the

com-pany it self’s technological advantages and the advanced scientific and technological

re-sources from host country (Nieto & Rodríguez, 2011), thus the firm is able to develop interna-tionalization through the most effective allocation and searching for R&D resources on a global scale. Multinational enterprises originating from emerging economies (EMNEs) has become important players in foreign direct investment (FDI) since decades ago. At present, the R&D internationalized ratio of global top 500 companies is close to 40%. Big multinational enter-prises such as Microsoft, Siemens and Samsung have established a large international R&D network, which has become a solid foundation for their independent innovation strategy. It is a key strategic choice for maintaining technological leadership and adapting to global market competition (Filatotchev & Piesse, 2009). Due to the increasing technical complexity of the product market, multinational companies have stronger incentives to achieve the goal of knowledge acquisition through global technology R&D cooperation, thus enhance the diversity and complementarity of their technologies. Additionally, in order to decrease the technological gap with developed countries and catch up with developed countries’ innovation capability, multinational enterprises from emerging economies carry out plenty of research and develop-ment activities abroad, which allows them to explore opportunities and acquire advanced for-eign technology and resources, and finally speed up in the process of transferring innovative resources to their home companies. Meanwhile, multinational enterprises originating from emerging economies increasingly create and collect knowledge outside their home countries by locating R&D centers and doing innovation activities in various host countries – most nota-bly from China (OECD 2018, Figure 1), a strong indicator for the build-up of knowledge and superior assets, and the expenditures for R&D have increased considerably. For example, in communication industry, one of the greatest Chinese companies Huawei has founded many of oversea R&D centers in the United States, India, Sweden and other countries all over the world (Huawei Investment Holdings Co., Ltd. 2018 Annual Report, 2018); in home appliance industry, Hisense has seven R&D centers in Germany, United States and Canada (Hisense Home Appliances Group Co., Ltd. 2018 Annual Report, 2018) .

As one of important member of ‘BRICS’, China has become the second largest economy in

the world and is regarded as the leader in the development of emerging economies (Tang, Tang, & Su, 2019). Chinese government has set “Build an innovative country” as a major stra-tegic goal for China's development. In 2013, President of the People’s Republic of China Xi Jinping proposed “One Belt and Road Initiative”, which aimed at actively developing economic partnerships with other countries and jointly creating a community of interests and political mutual trust. According to the data published by Ministry of commerce of the People’s republic of China, department of outward investment and economic cooperation, after the opening of the “Belt and Road” economic zone, Chinese enterprises made foreign direct investments in 49 countries related to the “Belt and Road” in 2015, and the investment amount increased by 18.2% year-on-year. How can Chinese firms obtain advanced technology, branding and

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man-agement capabilities, and develop from late-stage enterprises to global leaders? It is an im-portant theoretical proposition that whether "Made in China" trend toward "Create in China" can be achieved. The purpose of this paper is to study the pattern of China's R&D internation-alization, and analysis the effect of R&D internationalization on the Chinese firms’ innovation performance. I would be very appreciated if any of my research could contribute to the exist studies on Chinese firms’ internationalization.

The extant literature on R&D internationalization focus on many different emphases including the motivations of R&D internationalization included expand international markets (Tang, Tang, & Su, 2019), the processes and strategies of R&D internationalization (Elosge, Oesterle, Stein, & Hattula, 2018), the geopolitical influence (Moghaddam, Sethi, Weber, & Wu, 2014), and the performance outcomes of R&D internationalization (Hsu, Lien, & Chen, 2015; Vithessonthi & Racela, 2016). But the previous study results about the outcome of R&D inter-nationalization are various.

On the one hand, some studies have found that entrepreneurial companies with higher de-grees of R&D internationalization have better independent innovation performance (Xu, Xia, & Li, 2017), company with higher degrees of R&D internationalization deploy their intangible as-sets to explore market imperfections in foreign countries (Loncan & Nique, 2010), some other studies suggested that to geographically increase R&D internationalization means better ex-ploring and exploiting knowledge and resource from all over the world (Schulz, 2001). On the contrary, some other studies suggested that high degree of internationalization may lead a higher knowledge and technology leaking risk, which has a negative impact on firm’s innova-tion performance (Randaccio & Veugelers, 2007), whereas some other study proved that firm’s high degree of in internationalization in Greenfield project turned out negative effects due to Agency Theory, which suggested that managers may invest in international projects that de-stroy value, to be able to capture cash flows from owners (Loncan & Nique, 2010). Additionally, some studies found that higher level of R&D internationalization may result to lower economies of scale for R&D sites (Kafouros, Buckley, Sharp, & Wang, 2008), which results to lower inno-vation performance. Although previous studies have used empirical data and found different results about the relationship between R&D internationalization and firms’ innovation perfor-mance, the strength in various contingencies remain ambiguous (Lahiri, 2010). Some re-searchers suggested that the reason why previous studies generated various results may be the different definitions and measuring characters of R&D internationalization (Hsu, Lien, & Chen, 2015). With all the concerns, I have two questions. Firstly, will R&D internationalization improve the firm’s innovation performance as expected? Secondly, under the constraint of technology gap and knowledge flow, can firms orienting from emerging countries obtain the technology spillover through R&D internationalization ideally?

On the other hand, the motive of R&D internationalization of multinational corporations orient-ing from emergorient-ing economies is to make full use of advanced foreign knowledge to enhance their innovation capabilities. Whereas the motive of R&D internationalization of multinational corporations from developed countries is mainly to take their own technological advantages to open up markets (He & Zhong, 2019). Additionally, many internal and external factors may have a substantial impact on the firm’s innovation performance, e.g. overseas R&D subsidi-ary’s type (Chen, Li, Wang, & Wu, 2016), the character of multinational R&D network (Achcaoucaou, Miravitlles, & León-Darder, 2014), organizational redundancy (Chen, Huang, & Lin, 2012), institution environment of host countries (Sanna-Randaccio & Veugelers, 2007). Therefore, it is still unclear that whether the existed research results based on the experience of R&D internationalization of firms from developed economies are also suitable for those ori-enting from emerging economies such as China. Additionally, it deserves further exploration

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that what is the specific process of Chinese firms’ R&D internationalization affecting on their innovation performance and how do the disturbances encounter in this process.

In order to solve the ambiguous problem, I adopt researchers Chia-Wen Hsu, Yung-Chih Lien and Homin Chen’s method (2015) to explain R&D internationalization in term of intensity and diversity. Thus, my experimental approach uses 2 main factors: the intensity of R&D interna-tionalization (a firm’s R&D expansion related to its foreign expansion) and the diversity of R&D internationalization (the firm’s geographic distribution of R&D activities) (Hsu, Lien, & Chen, 2015). After that, I attempt to focus on the following two questions: Firstly, do the two factors of R&D internationalization (R&D internationalization intensity and R&D international diversity) have a significant impact on the innovation performance of the researched firm itself? Sec-ondly, do the endogenous absorptive capacity factors of the firms, such as international expe-rience, have any influence on the relationship between R&D internationalization and innovation performance as a moderator?

This paper aims to provide some reference and inspiration for the formulation and implemen-tation of Chinese high-tech firms’ R&D internationalization strategy, thus contribute to promot-ing the strategic transformation and realizpromot-ing innovation capability catch-up in Chinese high-tech firms. With this original intention, I use a panel dataset on R&D internationalization for the listed Chinese firms in manufacture of computer, communication equipment, electronic and optical products industry spanning 11 years from 2007 to 2017 to test the framework.

2 Theoretical background and hypotheses

2.1 R&D internationalization literature

Internationalization can be broadly defined as ‘expanding across country borders into

geo-graphic locations that are new to the firm’ (Hitt, Hoskisson, & Ireland, 1994), also describes a firm’s level of involvement in international market. Firms may internationalize in the face of domestic constrains and/or to exploit foreign market opportunities and country-specific endow-ments (Vithessonthi & Racela, 2016). Internationalization, as the process of studying and knowledge accumulation, can help companies obtain more resources, information, ideas, tech-nologies and opportunities (Kotabe, 1990; Kobrin, 1991); use the international market to dilute and reduce R&D costs (Cheng & Bolon, 1993) and form innovative strategic alliances (Santos, Doz, & Williamson, 2004). The learning effect (Grossman & Helpman, 1991; Bratti & Felice, 2012; Love & Ganotakis, 2013) and the competitive incentive effect (Hitt, Hoskisson, & Ireland, 1994; Bratti & Felice, 2012) of internationalization can increase companies’ attention to inno-vation, improve their capacity for innovation and earn more exclusive income of innovation (Teece, 1986; Kafouros, Buckley, Sharp, & Wang, 2008).

Internationalization is an important innovation strategy for emerging market multinational cor-porations to catch up with MNEs in developed countries in rapidly changing environments; (Luo & Tung, 2007), creating opportunities for firms to transform from followers into leaders as emerging market multinationals (Tang, Tang, & Su, 2019). Existing studies on R&D interna-tionalization focused on the issues such as the motivations (Child & Rodrigues, 2005; Luo & Tung, 2007), processes, strategies, and the performance outcomes.

Studies investigated the motivations of R&D internationalization included expand international markets, helped enterprises to organize and obtain technical resources from around the world (Tang, Tang, & Su, 2019), natural resource seeking, downstream and upstream knowledge

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seeking, efficiency seeking, global value consolidation seeking, geopolitical influence seeking (Moghaddam, Sethi, Weber, & Wu, 2014).

Research on the processes and strategies of R&D internationalization discussed about two

types of learning activities – exploration and exploitation (March, 1994; He & Wong, 2004) ,.

Firms can aim at transferring and leveraging R&D capabilities developed in their global learn-ing network (i.e., they exploit existlearn-ing knowledge), and they can utilize the foreign R&D capac-ity to augment their knowledge base by tapping into foreign R&D knowledge (i.e., they explore new knowledge) (Chen, Huang, & Lin, 2012; He & Wong, 2004). Exploration is characterized by ‘experimentation with new alternatives’ (March, 1994), which means exploring new possi-bility and knowledge during the process of R&D internationalization. Whereas exploitation is

characterized by ‘the refinement and extension of existing competencies, technologies and

paradigms’ (March, 1994), which means exploiting existing knowledge to take known opportu-nities.

The literatures on the performance outcomes of R&D internationalization mainly discussed about the innovation performance of a firm. That is also what I will research on later in detail. In order to examine the issue in a more comprehensive way, the previous researches intro-duced scientific and normative indicators for measuring R&D internationalization in term of geographic distribution (the width of R&D internationalization, also defined as the diversity of R&D internationalization) and intensity of relative activities (the depth of R&D internationaliza-tion, also defined as the intensity of R&D internationalization) (Hsu, Lien, & Chen, 2015; Tang, Tang, & Su, 2019; He & Zhong, 2019). Additionally, I also study on the moderating effect (the international experience) to research on the impact of a Chinese firm’s R&D internationaliza-tion on the innovainternationaliza-tion performance.

Even though there’re many existed studies on R&D internationalization, the previous studies mainly focus on the R&D internationalization of developed countries. But the pattern and mo-tivation of R&D internationalization for emerging economies like China are different with devel-oped economies (Du & Zhou, 2018).

The companies in developed countries established overseas R&D centers date back to the Second World War. At that time, multinational companies such as Philips in the Netherlands and SKF in Sweden had established overseas R&D centers, which main function was to pro-vide technical support to local factories. After the 1970s, the overseas R&D centers of devel-oped countries have gradually develdevel-oped from the local technical support departments to an important part of the global R&D system. The purpose of these overseas R&D centers is to help companies promoting their advanced technologies which developed in their home coun-tries, thus making full use of those existed technologies (Hu, Tang, Wang, Sun, & Cao, 2018). In the market level, R&D system improves product for local consumers to realize product lo-calization, thus adapts to local consumers’ demand. In the technical level, R&D system ab-sorbing and utilizing local unique innovation resources to achieve optimal allocation of innova-tive resources on a global scale.

Along with their mounting economic might, emerging economies are becoming the object of ever closer analytical attention (Di Minin, Zhang, & Gammeltoftd, 2012). Innovation is important to creating and sustaining competitive advantage in global market (Filatotchev & Piesse, 2009). As I’ve mentioned above, the motivation for Chinese firms to build R&D internationali-zation is different from the firms from developed countries. From the perspective of the national innovation system, the innovation system of European and American enterprises is relatively mature, and the R&D centers of enterprises in those countries are often established in high knowledge-intensive areas of related industries. The purpose of R&D internationalization for European and American companies is complementary to the home country’s R&D center.

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Whereas in China, the innovation system of the home country is still under construction, lack-ing high technology and knowledge-intensive areas. The current studies analyze Chinese com-panies’ investment in R&D, focusing on three different aspects: technology exploration vs. technology exploitation as investment motive; local strategies for R&D investments; and the dynamics of motives of overseas R&D unites (Di Minin, Zhang, & Gammeltoftd, 2012). In this way, R&D internationalization is regarded as an efficient way for Chinese firms to develop and catch up with the first-class companies in the world. Due to most Chinese firms still have a large technological gap compared with European and American firms, this makes it more ur-gent for Chinese firms to acquire and utilize foreign innovative resources and improve their technological innovation capabilities through the establishment of oversea R&D centers.

2.2 Intensity of R&D internationalization

Although it has been suggested that greater intensity of R&D internationalization has signifi-cant impact on a firm’s innovation performance, the previous empirical findings are still mixed, not always confirming this proposition. For example, Xin Xu, Yun Xia and Chuntao Li found that entrepreneurial companies with higher degree of intensity of R&D internationalization have better independent innovation performance (Xu, Xia, & Li, 2017). Based on the samples and financial data from the China Stock Market and Accounting Research (CSMAR) Database, they examined the trihedral hypotheses to demonstrate the relationship between R&D interna-tionalization and innovation performance. Finally, they concluded that Chinese firms with higher degree of R&D internationalization have greater patent output. The reasons are: inter-nationalization as the process of studying and knowledge accumulation, can help firms to ob-tain more resources, information, ideas, technologies and opportunities (Kotabe, 1990; Kobrin, 1991) and increase companies’ attention to innovation (Teece, 1986). Moreover, firms with greater intensity of R&D internationalization are more likely to have greater innovative output (Penner-Hahn & Shaver, 2005). Greater intensity of R&D internationalization promotes firm adaptability through modifying knowledge in response to the demands of specific markets, which facilities the firm’s full exploitation of knowledge developed at home (Hsu, Lien, & Chen, 2015). With the continuous investment in R&D internationalization, Chinese enterprises may overcome the learning barriers in R&D internationalization, accumulate more experience in managing oversea R&D centers and subsidiaries, thus to acquire richer heterogeneous inno-vation resources (Kafouros, Buckley, Sharp, & Wang, 2008), and breakthrough from the origi-nal path (He & Wong, 2004).

On the other hand, higher degree of internationalization intensity may lead to a higher knowledge and technology leaking risk (Randaccio & Veugelers, 2007). Many studies also indicated that a firm’s internationalization activities made a limited or even negative contribu-tion to the innovacontribu-tion performance. One of the most popular argument is about the disad-vantages of decentralization is the unwitting dissemination of knowledge from poorly-controlled departments (Fisch, 2003). Moreover, Kafouros, Buckley, Sharp and Wang argued that not all firms can reap rewards from innovation (Kafouros, Buckley, Sharp, & Wang, 2008). They uti-lized firm-level data, suggested that firms are unable to benefit from innovation if their interna-tional activity is below a threshold level. Especially when the firm’s R&D activity is in an envi-ronment with full of many uncertain factors, the greater the intensity of the firm's overseas R&D investment, the greater the external disadvantage pressure the company may have (Vithessonthi & Racela, 2016).

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To implement R&D activities abroad for multinational firm is a gradual evolution process. Therefore, under the influence of innovative income and cost of overseas R&D investment, the relationship between R&D internationalization intensity and innovation performance may not be simplify linear. Based on the arguments in the previous literatures and considering that intensity of R&D internationalization, I suggest that for Chinese firms, there is a U-shape cur-vilinear relationship between the increasing intensity of R&D internationalization and innova-tion performance. At first, increasing intensity of internainnova-tionalizainnova-tion has a negative effect on innovation performance to a certain extent, mainly due to the consequent coordinating and managing cost. However, after the certain extent, firms’ reward from internationalization input begin to make the cost up. Hence, I form the first hypothesis:

Hypothesis 1. For Chinese firms, there is a U-shape relationship between intensity of R&D internationalization and innovation performance.

2.3 Diversity of R&D internationalization

A firm increases R&D internationalization diversity by extending the spread of its operations across different countries (Ghoshal & Bartlett, 1990). As a result, international diversity in-volves costs and benefits associated with the breadth of internationalization (Miller, Lavie, & Delios, 2016). A firm is likely to increase R&D internationalization diversity gradually as it es-tablishes subsidiaries in new host countries. As the firm begins to enter foreign countries, it incurs liabilities of foreignness (Zaheer, 1995). There were many prior empirical studies inves-tigated the impact of the diversity of R&D internationalization on innovation performance in developed countries, which have contributed to our better understanding of the relationship between diversity of R&D internationalization and innovation performance, but gap still remains (Wu, Chen, & Jiao, 2016).

Previous studies have showed that exploitation of knowledge and resource generally involves modifying existing knowledge that firm already have or importing knowledge from outside through the R&D subsidiaries to extent existing knowledge (Schulz, 2001). To geographically increase diversity of R&D internationalization means better exploring and exploiting knowledge and resource from all over the world.

Nevertheless, Kafouros, Buckley, Sharp and Wang (2008) found that higher level of diversity of R&D internationalization may result to lower economies of scale for R&D sites (Kafouros, Buckley, Sharp, & Wang, 2008). Another negative consequence of higher level of diversity of R&D internationalization is the substantial cost that the coordination and control of a global network requires (Granstrand, Håkanson, & Sjölander, 1993). For emerging economies, the negative impact of R&D internationalization diversification is more significant. In the early stage of R&D internationalization, it is often constrained by ‘Curse to The Late Comer’.

Based on the arguments in the previous literatures and considering that diversity of R&D in-ternationalization, I suggest that for Chinese firms, there is an inverted U-shape relationship between the increasing diversity of R&D internationalization and innovation performance, that collaboration among R&D units located in different countries moderates the relationship by increasing the positive effect at the initial stage and challenges and influences of the collabo-ration among a firm’s R&D units located in different countries outweigh the benefits after a certain extent (e.g. cost related to transportation, communication over large distance).

Hypothesis 2. For Chinese firms, there is an inverted U-shape relationship between diversity of R&D internationalization and innovation performance.

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2.4 Moderating effect of international experience

Studies have demonstrated that firms took part in international business developed the capa-bilities to reduce the cost related to cross-border knowledge transfers (Pennings, Barkema, & Douma, 1994). Therefore, firms with more international experience should dealing better with great intensity or wide diversity R&D internationalization activities. Because a firm with more international experience means the firm is able to better analyze the situation and solve the problem that might occur in the international market, and abundant international experience helps the firm further carry out oversea activities and build international reputation around the international market at the same time.

The internationalization experience is not only the dynamic ability of the firm, but also the scarce resource, which playing an irreplaceable role in promoting the internationalization per-formance of the enterprise (He & Zhong, 2019). The firm with more International experience generate lower coordination costs in conducting overseas R&D activities, therefore it is more likely to adapt to new markets and benefit from new markets (Brouther & Hennart, 2007). As a result, I suggest the follow hypothesis:

Hypothesis 3. For Chinese firms, international experience positively moderating the effect of R&D internationalization on innovation performance.

3 Methodology

3.1 Date collection and sample

In order to test these hypotheses, I collected sample from companies listed on the Shanghai Stock Exchange (SSE) and Shenzhen Stock Exchange (SZSE). Listed companies on these exchanges are strictly monitored by the general public and investors, so we can have confi-dence in the information disclosed (Zhang, Yang, Qiu, Bao, & Li, 2018). After that, I filtered the list by excluding the companies which lacking complete data, in order to have a researching company list. According to the frame of International Standard Industrial Classification (ISIC), correlated with Industrial classification for national economic activities (GB/T 4754—2017) which was carried out by National Bureau of Statistics of China (NBSC)，the individual cate-gories of Industrial classification for national economic activities have been aggregated into the following 20 sections, 97 divisions.

After comparing the R&D expenditure of companies sorted by 97 different divisions of indus-tries between year 2007 to year 2017 in the industry list summation from the China Stock Market & Accounting Research (CSMAR) Database, C3900 as Manufacture of computer, com-munication equipment, electronic and optical products out of Section C Manufacturing (13-43) is selected due to ranking top 1 among all of the divisions of industries. Additionally, on the sub-industry list summation from the China Stock Market & Accounting Research (CSMAR) Database, Manufacture of computer, communication equipment, electronic and optical prod-ucts also ranked top 1 among the 97 sub-industries’ high-tech R&D expenditure during the same time period. China is a big developing country, which paid great effort in developing high-tech industry recent years. Chinese firms in Manufacture of computer, communication equip-ment, electronic and optical products industry show intense levels of willing to have better innovation performance, with many firms leading in global market, e.g. Huawei, Xiaomi, ZTE. Hence, Chinese firms which in Manufacture of computer, communication equipment, electronic

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and optical products industry are optimal samples to test my research hypothesis. Accordingly, I chose the listed firms in Manufacture of computer, communication equipment, electronic and optical products industry as my research samples, which are also regards as High-tech firms in China. Then I collected financial data of the sample companies from the China Stock Market and Accounting Research (CSMAR) Database, one of the most authoritative market and ac-counting databases in China. At first, I collected patent data (patent count information) from the China Patent Database published by National Intellectual Property Administration, PRC (CNIPA). But the firm granted patent records in the National Intellectual Property Administra-tion website only classified by the patent number, patent name and company name, and the firm’s stock code is not included. In this case, I could not corelate the patent data from National Intellectual Property Administration to the sample I got from the China Stock Market and Ac-counting Research (CSMAR) Database. After comparing and analyzing, I decided to collect the patent data from the China Stock Market and Accounting Research (CSMAR) Database, which is proved to provide the patent information orienting from National Intellectual Property Administration but also corelated with stock code, so that I could be able to use in my sample more convenient and convincible. After that, I collected the information of a firms’ foreign sub-sidiaries also from the China Stock Market and Accounting Research (CSMAR) Database. I also manually made double check for the information of a firm’s foreign subsidiaries in the

website of Ministry of commerce of the People’s republic of China, department of outward

investment and economic cooperation if there’s any missing data, aimed at getting overall

sample precise and complete. Since the data of the company's international experience is not provided in the website of Ministry of commerce of the People’s republic of China, department of outward investment and economic cooperation, nor the China Stock Market and Accounting Research (CSMAR) Database, I manually searched the international experience records of the above 146 high-tech companies through the annual reports of the companies.

I obtained the information of firms’ age, firms’ size, R&D Intensity (ratio of R&D expenditures to the firm’s total sales revenue) and financial leverage (ratio of a firm's debt to the total assets) through the CSMAR database, corporate official website and related news reports. In the end, I aggregated the data from these different sources into my sample all corelated by firms’ stock codes.

As each of the firm in my research has a unique stock code, and none of them has a listed subsidiary. The potential risk of overlapping patent data will not happen in my sample, such as counting total number of patents in parent firm and counting the number of patents in subsidi-ary again.

The time frame of the research covers 11 years from 2007 to 2017 (See Table 1). Thus, the sample size contained 819 observations, due to some firms are listed during the research time period, unbalanced panel data is employed in this study.

3.2 Variables and measurement

3.2.1 Dependent variable

Innovation performance. There are several ways to measure a firm’s innovation, such as

num-ber of new products launched in a certain amount of time; the actual vs. targeted breakeven time for new products; number of patents applied or granted; and the number of citations a firm got in a time period. Among them, number of patents granted is the optimal as a measure of innovation performance. Because it is easier to be observed and patents can be directly

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related to innovativeness. Many previous researches also suggested to measure innovation performance by patent count analysis (Hagedoorn & Cloodt, 2003; Penner-Hahn & Shaver, 2005). However, in the previous study carried out by Hsu, C., Lien, Y. and Chen, H. in 2015, they used the number of citations that a firm’s patents received divided by the number of pa-tents granted to a firm in a given year as computing a firm’s innovation performance. The reason was they suggested that a patent that receives a high citation rate should indicate the relative high-quality of a firm’s innovation output (Lahiri, 2010). But it is not a precise way to define so called ‘high-quality patent’ due to the risk of sample alienation (Zhang, Liu, Chen, & Jin, 2018). The interference caused by sample alienation on patent data refers to different technical fields, different industry categories, different organizational types, different organiza-tional scales, and different individual firms' different preferences on applying for or cite to pa-tents. Generally, the number of granted patents reflects the intensity of a firm’s engagement in innovation activities. Additionally, in the previous studies, many researchers have suggested that number of patents granted in a given year is a sophisticated and convenient measure of firm innovation performance (Zhang, Liu, Chen, & Jin, 2018). The source of R&D innovation information may be orient from domestic R&D centers or overseas subsidiaries. The reverse transfer of knowledge is neglected by some studies. This paper tries to also supplement this aspect in the relationship of R&D internationalization and enterprise innovation performance. As a result, I accordingly measure a firm’s innovation performance by the total number of pa-tents a firm granted in a certain year.

3.2.2 Independent variables

R&D internationalization intensity. There are many different forms of R&D activities carried out abroad by Chinese firms, such as setting up R&D subsidiaries, conducting research and de-velopment cooperation with foreign multinational companies and cross-border mergers, etc. Many previous researchers suggested to set R&D internationalization as a dummy variable (Wang, Yu, & Zhong, 2017), which means the variable equal to 1 if the firm has R&D interna-tionalized, and the variable equal to 0 if the firm has not R&D internationalized. In order to examine the relationship between R&D internationalization intensity and firm’s innovation per-formance precisely, I adopt the method of dividing the number of a firm’s R&D subsidiaries by the total amount of its total foreign subsidiaries in a given year (Hsu, Lien, & Chen, 2015). As a result, the independent variable is related to the number of R&D subsidiaries out of all the oversea subsidiaries in a given year. This value indicated the intensity of a firm’s R&D activities in its foreign expansion. When the value equal to 1, indicating that all of the foreign subsidiaries of the firm are R&D type subsidiaries, accordingly, the intensity of the firm’s R&D internation-alization is very strong. On the contrary, if the value equal to 0, indicating that none the foreign subsidiaries of the firm is R&D subsidiary, or the firm do not have any foreign subsidiary, thus the intensity of the firm’s R&D internationalization is very weak. Generally, the value of R&D internationalization intensity ranges from 0 to 1. The large the value is, the more R&D interna-tionalization intensity the firm is. Several previous studies have used this concept to measure R&D internationalization intensity (Delios & Beamish, 1999; Lu & Beamish, 2004; Hsu, Lien, & Chen, 2015).

R&D internationalization diversity. The second independent variable represented the diversity of a firm’s R&D internationalization. There’re many diversity indexes that can use to measure the variable: e.g. Shannon index, Simpson index, Blau index. Whereas Shannon index is

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mainly used in measuring the entropy of ecological literature, here it is unsuitable for measur-ing the diversity of R&D internationalization (Tucker, et al., 2017), which mainly discussmeasur-ing about the locations that R&D subsidiaries distributed. After comparing, I used Blau index (Blau, 1977) of diversity to measure, in this way, the result is more direct and perceptually intuitive to represent the diversity of R&D internationalization.

𝐷 = 1 − ∑ 𝑝𝑖2

2

𝑖=1

Previous scholars have suggested that to measure the location of R&D subsidiary based on

level of economic development: 𝑝𝑖 = 1 is the proportion that R&D subsidiaries invested in

de-veloped countries, whereas 𝑝𝑖 = 2 is the proportion that R&D subsidiaries invested in

devel-oping countries (Hsu, Lien, & Chen, 2015). The country classification is based on the data published by United Nations - World Economic Situation and Prospects (2019). Following this concept, when a firm has very decentralized R&D subsidiaries which are located at same num-ber of developing country(s) and developed country(s), the Blau index for the firm is 0.5 which is also the largest value in this case. On the contrary, when a firm has very centralized R&D subsidiary(s) which is(are) only located at developing country(s) or developed country(s), the Blau index for the firm is 0, which is the smallest value in this case. Generally, the value of R&D internationalization diversity range between 0 to 0.5. The large the value is, the more R&D internationalization diversity the firm is.

3.2.3 Moderator

International experience. Several studies have proved that the longer time a firm has been carrying out international activities and cooperation, the more abundant international experi-ence the firm has. Internationalization experiexperi-ence such as export experiexperi-ence has a significant impact on the internationalization behavior of Chinese firms. However, the existing literature on the impact of international experience on innovation performance is not consistent, (Kafouros, Buckley, Sharp, & Wang, 2008)i found that international experience has a negative impact on innovation performance, while another study suggests that international experience has a positive impact on innovation performance (Samant, Hatfield, & Thakur Wernz, 2015), Referring to Johnson et al.’s empirical work, the moderating factor of international experience will be calculated by the year of a firm since it first involved in the foreign business or invested in the foreign market till the end of research time frame (Hsu, Lien, & Chen, 2015; Johnson, Tuggle, & Schnatterly, 2010). For instance, a firm carried out international activities since 2008, the international experience of the firm is 9 years till 2017. The information of international experience can be collected from the China Stock Market and Accounting Research (CSMAR) Database.

3.2.4 Control variables

Four control variables that may affect innovation performance are firm size, firm age, R&D intensity, financial leverage. The control variable firm size is employed according to previous studies investigating the factors of firm size that affecting firm’s financial performance (Lin, Cheah, Azali, Ho, & Yip, 2019; Yildiza, Bozkurt, Kalkan, & Ayci, 2013). Firms with large size may be more powerful in purchasing R&D equipment, hiring high-quality R&D human resource, attracting partners, and dealing with R&D risks. Thus, they are more willing to participate in

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R&D activities, thereby increasing their chances of improving innovation performance. Due to the number of employees of each company varies in a large extent, in order to control for size effects, I use the natural logarithm of the total employees’ number to calculate this proxy (Hsu, Lien, & Chen, 2015). Firm age is employed to control heteroscedasticity and measured as the number of firm age (Nam & An, 2017; Zhang, Yang, Qiu, Bao, & Li, 2018). Generally stated, the innovation and management experience accumulated by the firms with a long time’s oper-ating is advantage to smoothing the progress of firm’s R&D activities. However, the firms with relatively mature technology may weaken the enthusiasm for R&D, and they are relatively pre-ferring conservative innovation, which is not conducive to the innovation activities. I do not

choose to use the natural logarithm of the firm’s age because most firms in my sample are

founded within 20 years. That is, to measure the control variable of Firm age as the number of firm age is more proper. A firm’s age is calculated from the year of its parent’s establishment. I also use the variable R&D intensity to control for the effect that the intensity of R&D invest-ment may have on the firm’s innovational performance (Yildiza, Bozkurt, Kalkan, & Ayci, 2013). R&D intensity is measured by the ratio of R&D expenditures to the firm’s total sales revenue. A firm’s R&D intensity indicating its overall intensive of participating in R&D activities. Finally, I also employ financial leverage to control for the effect that the firm’s financial condition may have on the firm’s innovation performance (Hsu, Lien, & Chen, 2015; He & Zhong, 2019), which is measured by the firm’s total debt divided by total assets in the given year. A firm’s financial leverage reflecting the firm’s economic vitality, which means the firm is operating in a well financial situation if the financial leverage is at a certain level.

I employ those 4 control variables in my regression models to better test the effect of R&D internationalization (intensity and diversity) on firm’s innovation performance.

A variable list with definitions is presented in Table 2. Detailed analysis for all the variables will be shown in the next part.

3.3 Regression model specification

I employ the number of the patents as independent variable Innovation performance, and the number of patents is a non-negative integer, which is typical count data. In the case of using logarithm of patent number as dependent variable, the result of OLS estimates may also be biased (He & Zhong, 2019). To better analyze the unbalanced panel data, I employ general linear square (GLS). The reason why I choose GLS model is because it addresses the prob-lems of autocorrelation and heteroscedasticity (Kmenta, 1986). Autocorrelation includes time autocorrelation (a variable is correlated to the year), spatial autocorrelation (near variable cor-relation) and disturbance term autocorrelation (missing an autocorrelation variable). And in this way, to ensure a quality analysis (Hsu, Lien, & Chen, 2015). Cameron and Trivedi suggested that when the dependent variable is the number of company’s granted patent, it is better to use Poisson distribution (Cameron & Trivedi, 2005). Poisson regression is a generalized linear model (GLM) form of regression analysis used to model count data and contingency tables. A Poisson random variable is a count of the number of occurrences of an event in a given unit of time, distance, area or volume. Also, there are also conditions of the observations that sat-isfied Poisson model: Events are occurring independently, the probability that an event occurs in a given length of time does not change through time. In a word, the events are occurring randomly and independently. The event of firms obtaining granted patents follow the rule of Poisson model. Therefore, in order to examine the relationship between R&D internationaliza-tion and firm’s innovainternationaliza-tion performance, I use the following equainternationaliza-tion: Poisson model to test my

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proposed hypotheses. Firstly, I regress the firm’s innovation performance on the intensity and the diversity of the R&D internationalization, it’s international experience, along with the four firm-level control variables.

𝐼𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑜𝑛 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒𝑖,𝑡 = 𝛼 + Χ𝑖,𝑡𝛽 + 𝜀𝑖,𝑡

Here 𝑖 represents the number of the firms in the sample and 𝑡 represents the year investigated.

Following this rule, 𝐼𝑛𝑛𝑜𝑣𝑎𝑡𝑖𝑜𝑛 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒𝑖,𝑡 represents the innovation performance of firm

𝑖 in the given year 𝑡. Similarly, Χ𝑖,𝑡 is a vector of both independent variables, moderating

vari-able and control varivari-ables relate to the company 𝑖 in the given year 𝑡. 𝜀𝑖,𝑡 represents the error

term of the regression model, is also taken to be an uncorrelated White-noise item, i.e. Ε[𝜀𝑖,𝑡] =

0.

Due to the data contains 146 companies over 11 years, it includes both time-series observa-tions and cross-sectional observaobserva-tions. The sample firms are listed during 2007 to 2017, the overall data I employed is unbalanced panel data. In order to test whether a random-effect or a fixed-effect is more precise to the GLS model, I run a Hausman test. Hausman test examines whether there is a significant difference between the fixed and random effect estimators. If the Hausman test is insignificant, I should use the random effects (re), and if the Hausman test is significant, I should use the fixed effects (fe). Generally, the random effects estimator is more efficient, can estimate coefficients of time invariant variables; and the fixed effects allow corre-lations between the effects and explanatory variables. The results of Hausman test show that the fixed-effects GLS model is more appropriate, so it is accordingly adopted. As the previous study methodology suggested (Hsu, Lien, & Chen, 2015), a pooled estimation of the empirical model was necessary in order to calculate the variance inflation factors (VIFs). And I can ac-cordingly further test if the model is appropriate. The pooled estimation provides an upper limit that help to identify the variance-induced bias. As shown in Table 3, the results I got shows that the variance inflation factor values ranged from 1.17 to 5.84. Overall, the correlation coef-ficient between variables is very low, the variance inflation factor values are far below the cutoff value of 10, and thus did not indicate any problem of multicollinearity (Hair, Anderson, Tatham, & Black, 1998)

4 Empirical analysis and results

First of all, this paper analyzes the descriptive statistics and correlation between variables. The results are shown in Table 4. Note that those statistic are based on the annual data of 146 firms for 11 years (2007-2017), making a total of 819 observations because of unbalanced panel data in my examination.

As can be seen from Table 4, the average number of granted patent for sample companies is 43, which is at a medium level, indicating that the firms’ innovation performances are still in the growing phase; the standard deviation is 63, indicating that there is a certain level of difference in innovation performance in those firms. The average value of intensity of R&D international-ization is 0.388. It shows that the intensity of setting up R&D subsidiaries overseas is relatively weak. The average value of diversity of R&D internationalization is 0.115, which has a maxi-mum value of 0.5, indicating that the diversity of international R&D is also relatively low, and the overseas R&D subsidiaries are set up relatively centralized. The average value of interna-tional experience is not big which is only 5.5 years, indicating that most firms are in the early

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phase of R&D internationalization and do not have much experience on international cooper-ation and activity. Furthermore, the average value of firm age is only 13 years, with the stand-ard deviation of 5, indicating that most firms are still very young and most of them are found in the same decades. The average value of R&D intensity is 7.283, means firms spend around 7.3% of their total sales revenue on R&D input, which is relatively strong; the standard devia-tion is 5.7, indicating that there’s a certain level of difference of the input of R&D activities between those firms from the same industry. The average value of financial leverage is 0.3, indicating that the amount of firms’ debt to the total amount of assets is around 30%, which is relatively small according to the average debt-to-value ratio for the firms from developed coun-tries. This indicator reflects the firms’ ability of managing debts while operating business.

4.1 Regression results

Table 5 provides the panel-data analysis results of the regression model. All the equations are

specified with significant Wald chi-squares (all at p < 0.01). This study uses Poisson regres-sion to analyze the impact of R&D internationalization on firms’ innovation performance by using the total number of granted patents as the dependent variable. 31 Observations dropped because only one observation per group. Thus, 788 observations out of 819 observations are run in the regression.

In the regression model 1, I add only all the control variables and moderating variable as a reference value to the other models.

In order to verify the Hypothesis 1: For Chinese firms, there is a U-shape relationship between intensity of R&D internationalization and innovation performance, I put the independent varia-ble of intensity of R&D internationalization and its square term in the regression model to test the relationship with the innovation performance. As shown in Model 2, both variables of the intensity of R&D internationalization and its square term are significant at the 1% level. The Chi-square of the Model 2 is slightly bigger than Model 1 (8520.44>8275.07), indicating that the model is more precise after adding the square term of intensity of R&D internationalization into it. The coefficient of the intensity of R&D internationalization’s square term is -1.73, which is negative; and the coefficient of the intensity of R&D internationalization is 1.71, which is positive. From the regression result, there is an inverted U-shape relationship between inten-sity of R&D internationalization and innovation performance, which does not support Hypoth-esis 1. The regression of Model 2 shows, at first increasing intensity of internationalization has a positive effect on innovation performance to a certain extent. However, after the certain ex-tent, with the continuing increase of R&D internationalization intensity, it no longer benefiting innovation performance. On the contrary, it has a negative effect on the firms’ innovation per-formance.

Similarly, in order to verify the Hypothesis 2: For Chinese firms, there is an inverted U-shape relationship between diversity of R&D internationalization and innovation performance, I add the independent variable of diversity of R&D internationalization and its square term in the regression model to test the relationship with the innovation performance. As shown in Model 3, both variables of the diversity of R&D internationalization and its square term are significant at the 1% level. The Chi-square of the Model 3 is slightly bigger than Model 1 (8342.27>8275.07), indicating that the model is more precise after adding the square term of diversity of R&D internationalization into it. The coefficient of the diversity of R&D internation-alization’s square term is 2.8542, which is positive; and the coefficient of the intensity of R&D internationalization is -0.8453, which is negative. From the regression result, there is a

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U-shape relationship between diversity of R&D internationalization and innovation performance, which also does not support Hypothesis 2. The regression of Model 3 shows, at first increasing diversity of internationalization has a negative effect on innovation performance to a certain extent. However, after the certain extent, with the continuing increase of R&D internationaliza-tion diversity, on the contrary, it has a positive effect on the firms’ innovainternationaliza-tion performance. To analysis the effect of moderating variable international experience on the relationship be-tween the intensity of R&D internationalization and innovation performance and the relation-ship between the diversity of R&D internationalization and innovation performance, I accord-ingly add two interaction terms: R&D internationalization intensity × international experience ,and R&D internationalization diversity × international experience in the next models. Model 4 is with the base of Model 2, add the interaction variable of R&D internationalization intensity × international experience. As shown in Model 4, variables of the intensity of R&D international-ization, its square term and interaction of R&D internationalization intensity and international experience are all significant at the 1% level. The Chi-square of the Model 4 is slightly smaller than Model 2 (8515.42>8520.44), indicating that the model is a little bit less precise after add-ing the interaction term of R&D internationalization intensity × international experience into it. Additionally, as shown in Model 4, the coefficient of the interaction term of R&D internationali-zation intensity × international experience is -0.0277, which is negative. It does not support Hypothesis 3.

Model 5 is with the base of Model 3, add the interaction variable of R&D internationalization diversity × international experience. As shown in Model 5, variables of the diversity of R&D internationalization and its square term are significant at 1% level, however, the interaction term of R&D internationalization diversity × international experience is not significant. It cannot support Hypothesis 3 neither.

5 Discussion

Internationalization is a complex phenomenon, yet prior research has studied its performance implications using alternative disciplinary perspective without systematically examining the mechanism underlying its various facets (Miller, Lavie, & Delios, 2016). My research is one of the first attempts to study on the effect of R&D internationalization on the innovation perfor-mance in Chinese high-tech firms. I run regressions to test how the intensity of R&D interna-tionalization and diversity of R&D internainterna-tionalization affecting on Chinese high-tech firms’ in-novation performance. As previous prediction, the regression results don’t show a linear rela-tionship. On the contrary, it shows a curvilinear inverted U-shape relationship between the intensity of R&D internationalization and Chinese high-tech firms’ innovation performance, and a U-shape relationship between the diversity of R&D internationalization and Chinese high-tech firms’ innovation performance, which are absolutely opposite with the previous hypothe-ses. The reason might be at first, firms can take advantage of spillover knowledge (Escribano, Fosfuri, & Tribo, 2006) and exploit existed international knowledge, technology and resources (He & Wong, 2004), positively influence innovation performance as levels of R&D internation-alization intensity. However, at a certain level of R&D internationinternation-alization intensity, the disad-vantages of increasing R&D internationalization intensity rise. Such as inefficient communica-tion between R&D subsidiaries located in different countries, which may affect the decision making and open innovation process (Rangus & Slavec, 2017). Gradually it leaded to an over-all decline of the firm’s innovation performance. Whereas in the effect that R&D internationali-zation diversity has on firm’s innovation performance, at first, the firms orienting from emerging

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economies usually encounter latecomer disadvantages in their initial international expansion (Luo & Tung, 2007). During the increasing of R&D internationalization diversity at the beginning phase, the firms also suffer from liabilities of foreignness and transaction cost due to their lack of experience in dealing with the complexities of international competition (Hoskisson, Eden, Lau, & Wright, 2000; Thomas, 2006). However, after a certain level of R&D internationalization diversity, the benefits of cumulative knowledge creation and externally knowledge sourcing from the geographically distributed R&D subsidiaries outweighs the previous cost. With the continuing increasing of R&D internationalization diversity, the firm’s innovation performance improves. Thus, 2 curvilinear effects of R&D internationalization on innovation performance are found in my research. Even though my findings respond the previous suggestion of R&D internationalization creates both advantage and cost, which have a joint influence on the firm’s innovation performance. The regressions are totally opposite of the hypotheses I proposed. Also, the joint influence of R&D internationalization intensity and R&D internationalization di-versity have on the firm’s innovation performance is still unknown.

Additionally, the regression results of the models with interaction terms of R&D internationali-zation intensity × international experience and R&D internationaliinternationali-zation diversity × interna-tional experience do not support the previous hypotheses that the internainterna-tional experience positively moderating the effect between R&D internationalization and innovation performance. In the model 4, regression result shows that the interaction terms of R&D internationalization intensity × international experience is significant. However, the firm’s international experience is slightly negatively moderating the intensity of R&D internationalization’s influence on inno-vation performance. In the model 5, the firm’s international experience is positively moderating the diversity of R&D internationalization’s influence on innovation performance, but regression result shows that the effect is not significant. For firms especially from emerging economies like China, to take advantage of international experience is regarded as a capability of learning and absorbing. Whereas in my finding of Chinese high-tech firms, the international experience is not positively moderating the relationship between R&D internationalization and innovation performance. The reason might be the Chinese high-tech firms did not fully absorb and inte-grate the advanced technological knowledge gained from R&D internationalization. And they did not pay attention to improve their absorptive capacity, thus gain benefit from continuously accumulate international experience.

Additionally, another factor that may also be relevant to the innovation performance is the firm’s ownership. Given the fact that China is a socialistic country, many previous studies have con-sidered ownership as an important factor. Institutions can determine firm behavior through formal (laws, legislations, and regulations) or informal (cultural, ethic, and morality) pressures (DiMaggio & Powell, 1983). Among them, the government's main formal institutional pressure, through the formulation of laws, implementation and the publication of rules and regulations, will not only affect the market at macro level, but also influence firms’ R&D behavior at micro level through several aspects such as taxation, supervision, research and development subsi-dies and loans, and national R&D system (Napshin & Azadegan, 2012). Especially in emerging economies characterized by a strong policy system such as China, firms rely on the privileges granted by the government to monopolize key scarce resources through non-market channels (Wang, Yu, & Zhong, 2017). A prominent issue closely related to the internationalization of Chinese firms is that many of these firms are state-owned enterprise (SOEs) (Kling & Weitzel, 2011). There’re lots of researchers studying on the effect of state-ownership on Chinese firm’s internationalization activities and behaviors (Cui & Jiang, 2012; Du & Boateng, 2015). Obvi-ously, the role of political connections in the process of R&D internationalization affecting en-terprise innovation cannot be underestimated on a certain extent.