Post on 10-Mar-2021
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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