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The Changing Models of International Technology Transfer in China

ABSTRACT

In recent years, there have been some changes in technology transfer and cooperation

activities that are different from traditional unidirectional technology transfer paradigm. This

paper aims to explore the changing models of international technology transfer in China. This

research examines the transfer of technology in three aspects: scientific knowledge, explicit

technology, and tacit technology. Based on the network methods, we adopt a framework that

integrates quantitative bibliometrics and patent analysis methods, complemented by qualitative

enquiries with domain experts. Specifically, the research selects two emerging industries as

representative cases: wind turbine and dye-sensitized solar cell. We find that the technology

transfer models have experienced significant changes when considering scientific knowledge

flows and industrial technology cooperation – the technology transfer models are different

between these two emerging industries. The newer technology transfer models of dye-sensitized

solar cell signify the rising innovation capacity of Chinese institutions which allows them to play

more central roles in global innovation network.

Keywords:

international technology transfer; patent; bibliometrics; China

Zhou, Yuan (1); Xu, Guannan (2)

1: Tsinghua University, China, People's Republic of; 2: Beijing University of Posts and Telecommunications, People's Republic ofChina

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The Changing Models of International Technology Transfer in China

INTRODUCTION

Many scholars within innovation literature have looked at international technology

transfer for innovation diffusion from a nation state perspective (Freeman, 1986; Nelson, 1993).

In this context, China has been a recipient of transferred technology from developed economies

such as the US and the European Union (EU) countries (Lema et al., 2015) for at least three

decades. This followed the classical North-South technology transfer model involving Foreign

Direct Investment (FDI), Overseas Development Aid (ODA), or a variety of measures for

domestic absorption of foreign technologies. Many argue that the traditional technology transfer

model has successfully helped China to build competitive manufacturing capacity as well as to

catch up in many conventional industries (Urban et al., 2015).

In many emerging industries the technologies are newly developed or even in its nascent

stage, and still have uncertainties that need to be researched. In these cases, emerging countries

may participate in early-stage research and contribute to global innovation communities with

scientific inventions or industrial technologies – very different from cases in traditional industries

where technologies are already well-established, and developing countries just adopt the mature

technologies in a routine way. This is particularly true in emerging industries in China, where

local players may no longer be passive recipients of well-developed technologies form developed

countries. Rather, they engage in more knowledge-oriented cooperation in scientific research as

well as industrial innovation with their partners in developed countries (Urban et al., 2015).

These phenomena may bring new insights to the theory of international technology transfer and

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cooperation, which has been intensively discussed since the early 1980s but with few

fundamental changes (Ockwell and Mallett, 2012). In addition, there is even fewer literature that

use multi-dimensional quantitative data such as integrated patent/bibliometrics to examine the

technology transfer and cooperation for various industries, partially due to the scarce of suitable

data and methodologies.

This paper, therefore, attempts to fill these gaps by addressing the following questions:

what are the new models of international technology transfer and cooperation for emerging

industries in China? And how do the transfer patterns evolve? We will also explore what these

differences in technology transfer and cooperation activities may tell us about the China’s

changing institutional settings and rising capacity in emerging industries. Policy implications for

technology transfer for developing countries will be discussed.

The remainder of this paper is organized as follows. Section 2 provides a review of

existing literature. Section 3 discusses our methodology. Section 4 conducts the case studies and

cross-case analysis. Section 5 discusses the findings and draws conclusions.

LITERATURE REVIEW: INTERNATIONAL TECHNOLOGY TRANSFER FOR

EMERGING TECHNOLOGIES IN CHINA

The term “technology transfer” encompasses the diffusion of technologies and

technology cooperation across and within countries (Urban et al., 2015). 1 It considers “the

process of learning to understand, utilise and replicate the technology, including the capacity to 1 Usually, the term technology diffusion describes a wider effect, which is not strictly related to the productive sector, whereas the

term transfer and cooperation may suggest a more intentional approach (Costantini and Liberati, 2014). In this paper, however, we

view both as synonymous. In addition, we follow Kogut’s argument that simple replication or reverse-engineering is NOT

recognized as a measure of technology transfer/cooperation (Kogut and Zander, 1992) – it may indicate the unidirectional flow of

technology, but in many cases it conveys incomplete knowledge with the loss of technical details and in an and inappropriate way.

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choose it and adapt it to local conditions and integrate it with indigenous technologies” (Hedger

et al., 2000:1.4), and particularly refers to the movement of knowledge among firms or sectors

located in different countries.

As aforementioned, developing countries requires additional conditions that transform

the technology stock into development achievements. These may comprise absorptive capacity,

institutional quality, as well as the sector-specific technological contents. Institutional setting may

involve many aspects, such as the quality of governance, the degree of control of property rights,

the degree of corruption, the height of transaction costs, the rules of law, and the political

instability. In addition, there are also informal factors, such as caste, ethnicity and trust, and

reputation. On the other hand, disparate sector-based technological contents may produce

different effects in different context, so technology transfer patterns may vary across different

sectors (Boschma and Iammarino, 2009) – this will be specifically explored in this study.

Specifically, for emerging technologies in developing countries, there is a strand of

literature highlights the global implications of a rising China (Kaplinsky and Messner, 2008) and

discusses how innovation capabilities have been rapidly growing in developing countries. Awate

et al. (2014) discuss about the catch-up strategies of emerging-technology firms in developing

economies and conclude that this is fundamentally different to the firm strategies of developed

countries. This has also influenced the thinking on technology transfer and cooperation in

developing economies. Current literature highlights how historically Asian and European firms

were engaged in different forms of technology transfer and technology cooperation and how

Asian firms are increasingly catching up (e.g. Gosens and Lu, 2013; Zhou et al., 2015a; Lema et

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al., 2015). Some literature also mentions how recently Chinese and European firms are engaged

in new models of technology cooperation (e.g. Lewis, 2013).

Though limited, some research tentatively explores most recent phenomenon of

“Reverse” South-North technology cooperation, which can be defined as technology cooperation

that is driven by emerging economies in the Global South that were formerly technology

importers in an unidirectional way. According to Urban et al. (2015), there are four models: 1. the

capital for the technology cooperation comes from emerging economies; 2. overseas market

access is driven by firms from emerging economies, potentially opening up access to new

markets; 3. Technologies are jointly developed by firms from emerging and developed economies;

4. The origins of innovation (such as patents and other IPRs) come from emerging economies.

This paper, therefore, focuses on the latter two that concern about technological innovation, and

explore whether these models do exist.

METHODOLOGY

As aforementioned, bibliometrics and patent analysis has been proved effective to

examine the explicit knowledge flows across borders, while tacit knowledge flows may be

detected by using qualitative enquires. In order to address our research questions (see Section 1),

this paper develops a framework that integrates bibliometrics, patent analysis and qualitative

interviews to analyze the new patterns of international technology transfer and cooperation for

emerging industries in China. This framework focuses on three dimensions related to examining

the technology transfer and cooperation of emerging-industry in China: (i) the scientific

knowledge transfer/cooperation (indicated by bibliometrics co-authorship network); (ii) the

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explicit technology transfer/cooperation (indicated by worldwide patent citation network); (iii)

the tacit technology transfer/cooperation (studied by interviews and desktop research).

In this study, two emerging industries have been selected as representative cases in

China: Wind turbine industry, and Dye-sensitized Photovoltaic industry. The case selection was

purposive rather than random. A theoretical sampling procedure applied three case selection

criteria: first, these cases are highly-received and promising emerging industries in China with a

global reach; and second, they are knowledge-intensive so that can be analyzed by patents and

bibliometrics; third, these two technology-based sectors may demonstrate the differences in

technology transfer and cooperation in terms of paper-indicated scientific knowledge,

patent-indicated technology, and tacit technology through joint research or people flows –

specifically, wind is older emerging industries when China has inferior innovation settings; and

Dye-sensitized photovoltaic is more nascent when China has its innovation system much

improved. The framework for analyzing the changing patterns of international technology

transfer in China is depicted as follows (Table 1).

Insert Table 1 about here

In response to the three research questions raised in this paper, we design a 3-step

process in the framework that integrates bibliometrics, patent analysis and qualitative interviews.

For emerging industry that is in the embryonic and nurturing stage, the first question lays greater

emphasis on the science and technology basics of the industry aspects, so we can use the

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bibliometric method and patent analysis to analyze the scientific knowledge transfer and the

explicit technology transfer of the emerging industries. In addition, the tacit knowledge

(information on production processes, product design, managerial methods and contract design)

transfer for emerging industry relies on our understanding of complex market and industrial

settings, as well as the dynamics development of the emerging industry, which call for the

interviews and consensus of industrial experts, policy makers and academics.

CASE STUDY

An Analysis of the Scientific Knowledge Transfer/Cooperation for Emerging Industries in

China

An Analysis of the Scientific Knowledge Transfer for Wind Turbine Industry Based on

Bibliometric Co-authorship Network

(1) Bibliometric data collection

As for the scientific knowledge transfer/cooperation, this paper applies the bibliometric

method to analyze global and China’s industrial knowledge transfer in the wind turbine

technology domain. This paper uses the terms “(wind turbine* generator*) OR (wind turbine

generator*) OR (wind turbine*)” as the query to search published papers on the Web of Science

(SCI-EXPANDED) database. We choose the document types as articles and the retrieval time

range is from 1931 to 2010, and the search was done on November 9th, 2015. Altogether 3,425

published SCI papers were retrieved from the database.

(2) Co-authorship network analysis

Based on the total 3,425 SCI published papers from 1931 to 2010, we try to make an

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analysis of co-authorship cooperation network among the top 70 organizations (leading firms,

universities and institutes). To achieve this, Ucinet software was also used in this section. The

steps are as follows. Firstly, the 3,425 published papers were saved as a txt file. The author’s

organization and the organization cooperation matrix of each paper were extracted using

Thomson Data Analyzer (TDA). Then, the data about the organization cooperation matrix were

imported into Ucinet software. Finally, the co-authorship cooperation network of wind turbine

technology was drawn using Ucinet software. The result is shown in Figure 1.

Insert Figure 1 about here

In Figure 1, the nodes represent organizations. The name of the organization is displayed

to the right of each node. The size of an organization’s node represents the total SCI publications

number of the organization. The link between the different nodes indicates the cooperation

relations between the organizations, and the thickness of the link represents the frequency of the

cooperation. In addition, the red color node is used to illustrate China’s organization, while the

blue color node represents the other countries’ organization.

From Figure 1, we can see that China has a weak scientific knowledge transfer in the

field of wind turbine technology: (i) from the nodes of the cooperation network perspective, only

9 Chinese organizations are ranked in the top 70, accounting for 12.8%, with 6 Chinese

organizations are embedded in the network, which are still in the peripheral positions, and 3

organizations are isolated from the bibliometrics cooperation network. (ii) From the cooperation

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degree of the network perspective, Chinese organizations have not ranked into the top 10 among

the whole 70 organizations. The Chinese organization that ranks highest is Chongqing University,

which is ranked 15 in the whole 70 organizations (see the appendix II). On the other hand, the

collaboration between Chinese organizations and other foreign universities or institutes is very

few, which can be seen from whether there are the connective lines or the thickness of lines

between them. (iii) By doing the core-periphery model used by Ucinet software in the network,

we find only Chongqing University appears in the core class, while the other 8 Chinese

organizations are in the periphery class. In terms of the time to research and develop on wind

turbine technology, the starting time to research and develop this technology in China is far

behind of other foreign countries. In the mid 1950s, Denmark built the first modern wind turbine.

After the first oil shock in 1973, wind power entered a new stage of development. Denmark,

Germany, Sweden, the United Kingdom, the United States and other countries were scrambling

to design more wind turbines. However, China began its early demonstration stage in 1986, while

the exploration of industrialization stage was in 1994. So China is apparently following western

countries in the emergence of wind turbine industry.

An analysis of the scientific knowledge transfer for dye-sensitized PV industry based on

Bibliometric co-authorship network

(1) Bibliometric data collection

We use the same bibliometric method as wind turbine technology to analyze the

scientific knowledge transfer/cooperation in the Dye-sensitized solar cell technology domain. To

obtain the published SCI papers of Dye-sensitized solar cell technology, this paper firstly uses

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“solar cell” as the theme query to search published papers on the Web of Science

(SCI-EXPANDED) database. We choose the document types as articles and the time range of

retrieval is from 1975 to 2014, and the search was done on November 14th, 2015. Then we use

the term “Dye-sensitized solar cell”as the query for a second retrieval. Finally, we obtain 10,338

published SCI papers related to Dye-sensitized solar cell technology.

(2) Co-authorship network analysis

Based on the total 10,338 published SCI papers from 1975 to 2014, we try to make an

analysis of co-authorship cooperation network among the top 70 organizations (leading firms,

universities and institutes). The process is same with the wind turbine technology, and the

Dye-sensitized solar cell co-authorship cooperation network is shown in figure 2.

Insert Figure 2 about here

From figure 2, we can see that China has a better-performed scientific knowledge

transfer in the field of Dye-sensitized solar cell technology: (i) from the nodes and cooperation

degree of the cooperation network perspective, 18 Chinese organizations are ranked in the top 70,

accounting for 25.71%, and the 18 Chinese organizations are embedded in the cooperation

network. In addition, among the top 10 organizations, there are 2 China institutes or universities,

Chinese Academy of Science ranked 2, Dalian University of Technology ranked 3 (see the

appendix II). On the other hand, the collaboration between Chinese organizations and other

foreign organizations is much more active, which can be seen from whether there are the

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connective lines or the thickness of lines between them, and these mean that they are have better

scientific knowledge transfer with each other. (ii)By doing the core-periphery model used by

Ucinet software in the network, we find Chinese Academy of Science, Dalian University of

Technology and Peking University appears in the core class, which means that they are leading

research organizations in the basic research field of Dye-sensitized solar cell technology.

An Analysis of the Explicit Technology Transfer/Cooperation for Emerging Industries in

China

An Analysis of the Explicit Technology Transfer for Wind Turbine Industries Based on Patent

Citation Network

(1) Patent data collection

As for the explicit technology transfer, this paper applies the patent citation analysis

method to analyze the technology transfer for wind turbine industry in China. In this paper, the

patent data are retrieved from the Derwent Innovation Index (DII) patent database in the

Thomson Innovation (TI) search engine. The TI databases involve patents from most countries of

the world, which have been rewritten by experts at Derwent to reduce the number of errors and

lead to better interpretation. Moreover, patents in TI have applied the Derwent Classification with

Manual Code (DCMC). This DCMC classification system will be used in this paper to search the

worldwide patent data from the DWPI and DPCI databases. With the DCMC term “X11-U01E

OR X13-G02T5 OR X13-H02T5 OR X21-B04A” as the query, and the priority year 1931-2010

as the retrieval time range, we finally obtained 5,075 records related to wind turbine technologies.

The search was done on December 9th, 2015.

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(2) Patent citation network analysis

Based on the total 5,075 patents, we try to make an analysis of patent citation network

between the worldwide patent assignees (leading firms, universities and institutes). The operation

process can be viewed as three steps. Firstly, we import the patent data that we get from the TI

search engine into the TDA software. Then, we pick out the top 50 patent assignees in the “citing

patent assignees” and then clean up those both in the “cited patent assignees” and “citing patent

assignees” terms. Next, we choose a few number of representative Chinese wind turbine firms

which are not included in the top 50. Here, in the top 50 patent assignees, 8 Chinese

organizations (2 firms and 6 universities) are evolved in the network. Then we select another 7

representative Chinese wind turbine firms based on the Internet research, and add them into the

network. Using the TDA software, we create the citation matrix between the 57 patent assignees

as “cited” vs. “citing”. The matrix is then imported into the Ucinet software, based on which the

patent citation networks have been generated. The citation network of the 57 patent assignees

during 1931-2010 is shown in Figure 3.

Insert Figure 3 about here

In figure 3, the nodes represent organizations. The name of the organization is displayed

to the right of each node. The size of nodes is determined by the number of self-citations. The

nodes of Chinese organizations are made in red, while others are in blue. The lines represent the

cumulative citations in both directions; the thicker the line, the more citations between the two

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organizations. The core/periphery structure of the citation network visualizes the organization’s

position in the network. Through the algorithms in the Ucinet software, the core/peripheral

positions are determined by the thickness of the links (citation) and their distance from the other

nodes (paths). Organizations with higher citations and shorter paths are positioned at the center in

the network, which are defined as the core positions.

From Figure 3, we can see that firms from Europe and Japan are still playing a leading

role in the network, while all of Chinese organizations, including firms and universities are

mainly distributed at the periphery of the network. By looking at the citing (Indegree) and cited

(Outdegree) rankings (see the appendix III) we can see that China do not have a better explicit

technology transfer in the field of wind turbine technology: (i) From the view of the ranking of

the patent citing numbers (not including self-citation), STATE GRID CORP CHINA and

SINOVEL is ranked 41 and 43 respectively (see the appendix III), while others organizations in

China are all ranked behind compared with the foreign firms; from the view of the ranking of the

number of cited patents (not including self-citation), Zhejiang University, Southeast University,

Tsinghua University, and Chongqing University are ranked at 36, 41, 45 and 46 respectively (see

the appendix III). On the other hand, the citation between Chinese organizations and other

foreign organizations is very few, which can be seen from whether there are the connective lines

or the thickness of lines between them. (ii)By doing the core-periphery model used by Ucinet

software in the network, we can also find all of Chinese organizations are listed in the periphery

class.

Based on the above analysis results, organizations in developed countries are leading in

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the creation of wind turbine industrial knowledge, whereas Chinese organizations are apparently

the follow-up learners and are mainly absorbing the knowledge in the network, and its position in

global industrial knowledge network is still marginalized. Furthermore, in the top 50

organizations, firms from developed countries play leading roles in patent generation, while most

of the organizations from China shown in the network are universities or research institutes; firms

as the mainly technological innovation body in China are insufficient lifting force to promote the

wind turbine industry.

An Analysis of the Explicit Technology Transfer for Dye-sensitized PV Industry Based on

Patent Citation Network

(1) Patent data collection

As for the explicit technology transfer, this paper also applies the patent citation analysis

method to analyze the explicit technology transfer for Dye-sensitized PV industry in China. In

this paper, the patent data are also retrieved from the DII patent database in the TI search engine.

With the Derwent manual code “X15-A02D1” OR “U12-A02A8” OR “L03-E05B1” as the query,

and the priority year from1975 to 2014 as the retrieval time range, we finally obtained 5,829

records. The search was done on December 14th, 2015.

(2) Patent citation network analysis

Based on the total 5,289 records, we try to make an analysis of patent citation network

between the worldwide patent assignees (leading firms, universities and institutes). The operation

process is the same as wind turbine technology. The citation network of the patent assignees

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during 1975-2014 is shown in Figure 42.

Insert Figure 4 about here

From Figure 4, we can see that China does NOT have well-performed explicit

technology transfer in the field of Dye-sensitized solar cells technology: (i) from the nodes of the

citation network perspective, there is only one Chinese firm (IRICO) included in the top 50

patent citation organizations. Other Chinese organizations are all institutes or universities (see the

appendix III). (ii) From the view of the ranking of the numbers of patents cited (not including

self-citation), Chinese Academy of Science, IRICO and Tsinghua University are ranked at 21, 24

and 25 respectively; from the view of the ranking of the patent cited numbers (not including

self-citation), Chinese Academy of Science, IRICO and Tsinghua University are ranked at 25, 33

and 34 respectively (see the appendix III). On the other hand, the citation between Chinese

organizations and other foreign organizations is very few, which can be seen from whether there

are the connective lines or the thickness of lines between them. (iii) By doing the core-periphery

model used by Ucinet software in the network, we can find all of Chinese organizations are listed

in the periphery class.

DISCUSSION AND CONCLUSIONS

Discussion

2 There involves 4 Chinese organizations (IRICO , CHINESE ACADEMY OF SCIENCE, UNIV TSINGHUA, UNIV BEIJING)

in the top 50 organizations, and then we select another 6 representative Chinese Dye-sensitized PV firms based on the Internet

research to add them into the network. The citation network of the 56 patent assignees during 1975-2014 is shown in Figure 4.

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Based on the literature-based analysis, we can understand the transfer activities of

explicit technologies (indicated by scientific publications and patents) for the two emerging

industries. Complements to this, the authors also conduct interviews and desktop research to

understand the existence of tacit knowledge flows in these two emerging industries, which may

involve the transfer of know-how via the exchange of people or joint-initiatives like teamwork.

Through these two case studies above, this paper reveals that these two emerging industries in

China demonstrate new patterns in international technology transfer when involving both

intensive knowledge flow with developed economies in science knowledge and industrial

technologies, which challenges the traditional North-South transfer model as Chinese firms of

being followers to absorb embodied technologies or know-how in a unidirectional way.

Insert Table 2 about here

From the above analysis, the authors find that heterogeneities also exist between the two

emerging industries when represented by sectoral lead firms, considering the forms of technology

transfer and cooperation activities (Table 2). Specifically, China’s dye-sensitized PV sector has

strong transfer/cooperation in both scientific knowledge and industrial technology. Wind turbine

generator sector has strong tacit technology transfer, but is less embedded (playing marginal roles)

into the global scientific knowledge and industrial technology network. From these results, we

argue that the international transfer models for Chinese emerging industries are changing across

three major patterns that are different from traditional ones and are significant to build up

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innovation competences in a global reach: high tacit-technology transfer model (wind turbine)

high knowledge-technology transfer model (dye-sensitized PV). Based on this observation, we

argue that the technology transfer patterns for China’s emerging industries have evolved in recent

years.

Conclusions

In this study, we conduct an empirical examination on the international technology

transfer patterns for emerging industries in China, and successfully address the research questions.

We have used an integrated method that combines bibliometrics, patent analysis, and interviews

to analyze the specific two emerging industries: wind energy, and the dye-sensitized industry. We

find that the technology transfer models are different for emerging industries in China compared

to traditional ones; in addition, there are also differences between these emerging industries.

This paper makes important theoretical contributions in two-folds. Firstly, this study has

explored the heterogeneity of technology transfer and cooperation patterns of different emerging

industries in China. Specifically, the patterns seem to be different from one emerging industry to

another. For example, China is now the world’s largest wind energy market and has developed

lead firms (e.g. Goldwind, Mingyang, etc.) through intensive tacit technology transfer with

European firms; however, China’s wind firms play marginal roles in the global

patent/bibliomtrics network and have limited contribution as explicit knowledge producers.

Moreover, in the newer industries like dye-sensitized solar photovoltaic industry, China

demonstrates strong competitiveness not only in manufacturing but also in scientific knowledge

discoveries that are led by leading universities such as Tsinghua University. The new technology

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transfer patterns of dye-sensitized solar cell signify the rising of China’s innovation capacity,

which allows Chinese organizations to play more central roles in global innovation network;

while the wind and photovoltaic sectors that have less influences on global science but higher

impacts on technology may represent transitional phases when China strove to catch up in

innovation.

There are several policy implications that can be drawn from this research. First, China

should continue to invest in science and technology as well as the innovation system, because the

local absorptive capacity, institutional settings, and human resources can be finally contribute to

the technology transfer activities – this is particularly important for catch-up economies. On the

other hand, however, China and other developing economies should emphasize firms’ role in

technology transfer, as they are more significant in creating commercial values such as attracting

investment, in-scale production, cost reduction, linking the customers, etc.

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TABLE 1

The Framework for Analyzing the Changing Patterns of International Technology Transfer

in China

Research questions Dimension of

Analysis

Method Case study

(1) What are the new

patterns of

international

technology transfer

and cooperation for

emerging industries

in China?

(2) To what extent do

these technology

transfer and

cooperation patterns

differ from one

emerging industry to

another?

(3) How do the

transfer patterns

evolve from one to

another?

(i) The scientific

knowledge

transfer/cooperation

for emerging

industries in China

Bibliometric

co-authorship

network

analysis

Two emerging

industries as

representative

cases in China:

Wind turbine,

Dye-sensitized

Photovoltaic. (ii) The explicit

technology

transfer/cooperation

for emerging

industries in China

Patent citation

network

analysis

(iii) The tacit

technology

transfer/cooperation

for emerging

industries in China

Interviews and

desktop

research

TABLE 2

Mapping the Technology Transfer Patterns for Emerging Industries in China

Knowledge transfer high Knowledge transfer low

Industrial tech transfer

explicit & tacit high

Dye-sensitized solar cell

Industrial tech transfer

explicit low but tacit

high

Wind turbine

23

FIGURE 1

The Wind Turbine Bibliometrics Co-authorship Network

FIGURE 2

The Dye-sensitized PV Bibliometrics Cooperation Network

24

FIGURE 3

The Wind Turbine Patent Citation Network

FIGURE 4

The Dye-sensitized PV Patent Citation Network