Factors influencing the technology upgrading and catch-up of Chinese wind turbine manufacturers: Technology acquisition mechanisms and government policies

Energy Policy 55 (2013) 305–316

Contents lists available at SciVerse ScienceDirect

Energy Policy journal homepage: www.elsevier.com/locate/enpol

Factors influencing the technology upgrading and catch-up of Chinese wind turbine manufacturers: Technology acquisition mechanisms and government policies Yueming Qiu a,n, Leonard Ortolano b, Yi David Wang c a

Arizona State University, Morrison School of Agribusiness and Resource Management, 7231 E Sonoran Arroyo Mall, Mesa, AZ 85212, USA Stanford University, Department of Civil and Environmental Engineering, 473 Via Ortega, Stanford, CA 94305, USA c University of International Business and Economics, School of Banking and Finance, no. 10 Huixin Dongjie, Chaoyang District, Beijing, China b

H I G H L I G H T S c c c c c

Technology acquired through joint design has the highest level. Technology acquired through purchasing production license has the lowest level. Technology acquired through domestic R&D has the level in between. A firm with related other businesses tends to have a higher level of technology. The influence of policies is significant for technology upgrade but not catch-up.

a r t i c l e i n f o

abstract

Article history: Received 27 April 2012 Accepted 3 December 2012 Available online 3 January 2013

This paper uses firm level data for the Chinese wind turbine manufacturing industry from 1998 to 2009 to quantify the effects of technology acquisition mechanisms – purchasing production licenses from foreign manufacturers, joint design with foreign design firms, joint-ventures and domestic R&D – on wind turbine manufacturers’ technology levels (as measured by turbine size, in megawatts). It also examines the impacts of government policies on manufacturer technology levels. Technology upgrading (measured by increase of turbine size) and catch-up (measured by decrease in the distance to the world technology frontier in terms of turbine size) are used to measure advances in technology level. Results from econometric modeling studies indicate that firms’ technology acquisition mechanisms and degree of business diversification are statistically significant factors in influencing technology upgrading. Similar results were found for the catch-up variable (i.e., distance to the world technology frontier). The influence of government policies is significant for technology upgrading but not catch-up. These and other modeling results are shown to have implications for both policymakers and wind turbine manufacturers. & 2012 Elsevier Ltd. All rights reserved.

Keywords: Chinese wind turbine manufacturer Technology acquisition mechanisms Government policies

1. Introduction During the past few years, China has made a significant effort to enhance and deploy its wind energy technology. This is reflected in China’s increase in rank based on annual installed wind power capacity from fifth in 2005 to first in 2009. In terms of share of cumulative global installed capacity, Chinese firms (in 2010) still trailed perennial front runner Vestas (Denmark),

n

Corresponding author. Tel.:þ 1 623 209 4725. E-mail addresses: [email protected], [email protected] (Y. Qiu), [email protected] (L. Ortolano), [email protected] (Y. David Wang). 0301-4215/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.enpol.2012.12.012

but China’s Sinovel occupied the second position and Goldwind and Dongfang were not far behind (see Table 1). Chinese wind turbine manufacturers have also improved rapidly in terms of wind turbine technology level. In the wind turbine domain, turbine size (the rated capacity of a single turbine) is a widely used index of technology level. The larger the turbine size, the more complicated and efficient the turbine technology. Notwithstanding its steady improvements, China still lags in the average turbine size of countries on the world technology frontier (Fig. 1). We determine the average turbine size of world technology frontier countries by averaging the countrywide average turbine sizes of Germany, Spain, UK, Sweden, and the United States; wind turbine technologies in these five countries are widely known to be more advanced than

306

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

Table 1 Rank of worldwide wind turbine manufacturers in terms of share of cumulative global installed capacity (2008–2010). Sources: MWPS (2011), ES (2008), and BTM (2010). 2008

2009

2010

Rank

Company

Country

Share (%)

Company

Country

Share (%)

Company

Country

Share (%)

1 2 3 4 5 6 7 8 9 10

Vestas GE Energy Gamesa Enercon Suzlon Siemens Acciona Goldwind Sinovel Nordex

Denmark United States Spain Germany India Denmark/Germany Spain China China Germany

19 18 11 9 7 7 4 4 4 4

Vestas GE Energy Sinovel Enercon Goldwind Gamesa Dongfang Suzlon Siemens Repower

Denmark United States China Germany China Spain China India Denmark/Germany Germany

12.50 12.40 9.20 8.50 7.20 6.70 6.50 6.40 5.90 3.40

Vestas Sinovel GE Energy Goldwind Enercon Suzlon Dongfang Gamesa Siemens United Power

Denmark China United States China Germany India China Spain Denmark/Germany China

14.30 10.70 9.30 9.20 7.00 6.70 6.50 6.40 5.70 4.10

Average turbine size (MW)

2.1 1.9

China World frontier countries

1.7 1.5 1.3 1.1 0.9 0.7 0.5 2000

2002

2004

2006

2008

2010

Year Fig. 1. Comparison of the average turbine size installed in China and world frontier countries. Sources: Hansen and Hansen (2007), BTM (2009), and Xia and Song (2009).

countries (Li et al., 2008) in the rest of the world1 . Ideally, Denmark would also have been included, but the relevant data could not be obtained. This paper demonstrates that technology acquisition mechanisms and government policies are significant factors influencing the technology level adopted by Chinese wind turbine manufacturers; it also determines the magnitude of each factor’s influence. The results have implications for governments in China and other developing countries in terms of policies and resource allocation decisions that can help their wind turbine manufacturers improve their technology levels and, eventually, produce turbines that are closer to those at the world technology frontier. Abundant literature exists on technology development and the innovation performance of companies, with many notable examples for the semiconductor industry (Mody, 1990; Almeida and Grant, 1998; Mathews and Cho, 2000; Henisz and Macher, 2004; Mu and Lee, 2005). While there have been many studies analyzing Chinese wind turbine manufacturing at the industry level, only a few studies have analyzed the wind turbine manufacturing industry at the firm level. Lewis (2006) identified technology acquisition mechanisms, including creation of joint ventures and purchase of production licenses, taken by several Chinese domestic wind turbine manufacturers. She used case studies to compare qualitatively the associated ownership of intellectual property rights, as well as the extent to which these strategies involved domestic manufacturing compared with the import of components. In a subsequent study, Lewis (2007)

compared the technology acquisition strategies of one Chinese and one Indian wind turbine manufacturer, and discussed how the strategies they employed influenced the companies’ innovation performance. Ru et al. (2012) used 10 Chinese wind turbine manufacturers to qualitatively analyze interactions among technology capability, innovation modes, market formation, and wind energy policy. Ru and his colleagues concluded that public policy serves as a key driving force for the evolution of innovation modes, as well as market development. Zhou et al. (2012) assessed the performance of joint R&D activities using the structure-conductperformance paradigm. Zhao et al. (2012) evaluated six Chinese wind turbine manufacturers using the enterprise niche theory. Notwithstanding these efforts, the following gaps remain in literature concerning technology development strategies of Chinese wind turbine manufacturers:

 Number of firms studied—Previous studies involved case





 1 We do not compare the turbine size of Chinese wind turbine manufacturers with the size of the most advanced wind turbine technologies in existence. The technology adoption issues we examine concern technologies that are commercialized and ready to be manufactured, so it is also reasonable to compare Chinese technologies with the commercialized technologies in the world frontier countries.

studies of at most 10 Chinese companies; no studies have yet looked at the most up-to-date and comprehensive sample of Chinese wind turbine manufacturers, which increased in number from 6 at the end of 2003 (Wang et al., 2005) to 60 at the end of 2007 (Li et al., 2008). Number and categorization of technology acquisition mechanisms considered—Zhou et al. (2012) focused only on joint R&D. Lewis (2006, 2007) analyzed joint ventures, mergers and acquisitions (M&A) and production licensing as technology acquisition mechanisms of Chinese wind turbine manufacturers, but she did not consider joint design, in-house R&D and technology transfer from domestic research institutes. Ru et al. (2012) grouped M&A, building international centers and cooperation with domestic research institutes as the same category, which does not account for the fact that the technology and know-how from M&A and building international centers originate from foreign sources while cooperation with domestic research institutes relies purely on domestic sources. Consideration of business diversification, experience and technology gap—In assessing the wind turbine technology level associated with different technology strategies, most studies did not control for key factors identified in the technology and innovation literature, including the firm’s business diversification, previous technology gap and cumulative wind turbine manufacturing and technology acquisition experience. Use of quantitative modeling—Previous research has not used econometric modeling to quantify factors affecting the technology level of Chinese wind turbine firms.

This study attempts to fill the above-noted gaps. It also makes a contribution to the literature by demonstrating the significance of technology acquisition mechanisms – including purchasing

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

production license from foreign manufacturers, joint design with foreign design firms, joint-venture and domestic R&D – as factors affecting firms’ technology levels. Using firm-level data for 68 Chinese wind turbine manufacturers2 from 1998 to 2009, we employ econometric models to identify factors influencing Chinese wind turbine manufacturers’ choice of the level of technology to adopt; in addition, we also quantify the impact of each factor.

2. Theoretical foundation The literature review in Section 2.1 and direct observation based on field research provide the underlying foundation for hypotheses introduced in Section 2.2. Based on conclusions from literature review and field research, a conceptual framework that links the key factors and the outcome variable – technology level – is presented in Section 2.3

307

Some studies have been done at the sectoral level. For example, Li (2011) analyzed how in-house R&D investment, foreign technology import expenditures, and domestic technology purchases influence sectoral patent counts. The results show that importing foreign technology alone does not facilitate innovation in Chinese state-owned high-tech enterprises, unless in-house R&D is also conducted. However, domestic technology purchases were found to have a favorable direct impact on innovation. A common theme in these studies is that foreign technology transfer and in-house R&D both significantly impact technology performance. However, when analyzing the impact of foreign technology transfer, the majority of existing studies do not distinguish the impacts from different foreign technology transfer channels, such as joint R&D, purchase of production licenses, and joint ventures. Our study contributes to literature by quantifying the impacts of different foreign technology transfer mechanisms as well as domestic mechanisms. 2.2. Field research and generation of hypotheses

2.1. Studies on technology acquisition mechanisms and technology performance Due to increasing globalization and international business cooperation, more diversified technology acquisition channels and mechanisms, including both domestic and international acquisitions, have been seen in recent years. In the past decade, there has emerged a body of literature evaluating the contribution of various technology acquisition mechanisms to firm technology performance. Some studies have been conducted at the firm level. Belderbos et al. (in press) described how technology transfer may occur through R&D contracting, purchase of licenses and know how, purchase of specialized machinery, hiring of specialized personnel, and various informal channels. Using a sample of 440 firms, Belderbos et al. (in press) found that firms engaging in international knowledge sourcing record substantially and significantly higher productivity growth than firms relying on domestic sourcing. Hu et al. (2005) used firm-level data to investigate the impact of in-house R&D, domestic and foreign technology transfer, and foreign direct investment on productivity within the Chinese manufacturing industry. They found that in-house R&D and foreign technology transfer have strong impact on productivity, and the impact of foreign technology transfer is largely conditional on its interaction with in-house R&D. Using electronics manufacturing firms, Tsai and Wang (2008) found that the positive impact of external technology acquisition on firm performance increases with the level of internal R&D efforts. Other relevant studies have been conducted at the industry level. Liu and White (1997) concluded that in developing countries, innovation is driven by the synergy between investment in absorptive capacity embodied in R&D personnel and investment in sources of new knowledge embedded in foreign technologies. Through industry-level analysis, Bin (2008) investigated the impact of four technology acquisition channels on industry innovation performance and productivity, including in-house R&D, foreign technology transfer, domestic technology transfer and inter-industry R&D spillover. Bin (2008) found that foreign technology transfer and inter-industry R&D spillover make significant contributions to both labor productivity and the level of total factor productivity in Chinese manufacturing industries. 2 Our focus is on utility scale wind turbine technologies; commercial and residential scale wind turbine technologies are not considered. Moreover, we focus on the technology of wind turbine manufacturers who produce or assemble entire wind turbines; this study does not examine manufacturers of individual turbine components.

The first author interviewed industry experts from several major Chinese wind turbine manufacturers and wind farm developers. In addition, interviews were also conducted with scholars from the Chinese Wind Energy Association and the Energy Research Institute of the National Development and Reform Commission (NDRC). This field research indicates that technology acquisition mechanisms and government policies are important in shaping the technology level adopted by Chinese wind turbine manufacturers. 2.2.1. Technology acquisition mechanisms 2.2.1.1. Production licenses from foreign wind turbine companies. Some of China’s manufacturing firms purchase production licenses from foreign companies as a way to acquire new technologies. In the context of wind turbines, the foreign firm is normally a wind turbine manufacturer. A production license gives a Chinese company the right to produce products according to instructions within the license, and the right to sell products to a market specified in the licensing contract. The licensee typically pays an up-front licensing fee to the licensor; then, at a later time after sales begin, the licensee also pays the licensor royalties as a fraction of the revenues from sales. Another common license provision is a restriction on the regions or markets in which Chinese companies can sell their products. Exporting is usually prohibited. These restrictions prevent Chinese wind turbine manufactures from becoming competitors of the foreign manufacturer granting the license. Licensing contracts differ from one case to another. For example, some contracts only require an upfront fee without royalties, and some contracts do not contain stringent restrictions on markets. 2.2.1.2. Domestic R&D: Production license from domestic institutes and in-house R&D by firms. Some Chinese wind turbine manufacturers acquire their technology via transfer from domestic public research institutes. The majority of Chinese wind turbine manufacturers who used this approach obtained their technology from Shenyang University of Technology. Two other public research institutes have been engaged in this way: Zhejiang University and Hadian Power Equipment National Engineering Research Center. Each has transferred one technology to a Chinese manufacturer. Licensing from domestic research institutes and from foreign turbine manufacturers differ in two important ways. First, the transaction costs for Chinese wind turbine manufacturers are typically lower when dealing with a domestic institute because it is easier to obtain and discuss relevant information. Second,

308

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

technology from these domestic research institutes sometimes differs from those of foreign wind turbine companies’ frontier technologies by being at lower levels of both quality and technology level. A number of Chinese wind turbine manufacturers reported that their technologies were acquired through their own in-house R&D. However, because most companies whose technology stemmed from in-house R&D have cooperated with universities or domestic research institutes in developing their technologies, in our study we combined obtaining production licenses from domestic institutes together with firms’ in-house R&D into a single category called ‘‘domestic R&D’’. 2.2.1.3. Joint venture with a foreign manufacturer. A Chinese wind turbine manufacturer can acquire a technology by forming a joint venture with a foreign equity partner. Normally the foreign partner would provide manufacturing instructions and/or knowhow, as well as training for the Chinese partner to produce the foreign manufacturer’s wind turbines in China. 2.2.1.4. Joint design with a foreign design firm. Some foreign wind turbine design companies focus only on design and R&D and do not engage in manufacturing. Such companies regard Chinese wind turbine manufacturers as clients rather than competitors. Some Chinese wind turbine manufacturing companies have entered into joint design agreements with foreign design companies. In such instances, the Chinese companies become involved in the design process; the resulting intellectual property rights are owned either solely by the Chinese company or jointly with the foreign design company. The technology acquisition strategy based on joint design is different from the production license strategy in three ways. First, production licensing normally involves a foreign turbine manufacturer, but the joint design process usually is done together with a foreign R&D/design focused company. Because there is no concern about competition from a Chinese manufacturer, the strategy of joint design with a foreign design firm provides a greater opportunity to acquire a more advanced technology. Second, the cost structure is different because joint design normally does not involve royalty payments. Third, the restrictions on markets are different. In the case of joint design, a Chinese company owns (solely or jointly) the intellectual property (IP) associated with a technology and therefore, in principle at least, it can sell its products in any market and it can license its technology to other companies. If the IP is jointly owned, the foreign partner needs to agree. 2.2.1.5. Influence of technology acquisition strategy on adopted technology level. We employ a technology acquisition mechanism variable with four categories: joint design, production license, domestic R&D and joint venture. The influence of Chinese wind turbine manufacturer technology acquisition strategy on technology level (i.e., turbine size) needs to be accounted for because: (i) the mechanism can influence available technologies to be acquired by a manufacturer and (ii) technology acquisition methods differ in terms of the magnitude of needed R&D investments, including upfront fees of technology acquisition agreement, human capital investment, etc. For example, the up-front funding required using a production license is typically lower than for joint design. Also the degree of personnel training and the extent of information and know-how transfer in using a production license are lower than with joint design. In brief, the technology acquisition mechanism variable measures two important factors: the available technologies to be acquired, and (indirectly) the manufacturer’s investment in R& D for technology development. This indirect measure of a firm’s R&D

investment was used because we were unable to obtain data to measure it directly. Based on our reading of literature and conversations with wind turbine technology experts, we anticipate that the highest level of technology available (in terms of turbine size) is likely to be associated with joint design, and the lowest level will be for production licenses. No defensible basis exists for distinguishing between the technology acquisition via domestic R&D vs. joint venture, and we group them in the same category. We postulate that either would be in a middle position in terms of available technologies. We formalize this position with the following hypothesis. Hypothesis 1. Joint design is associated with the highest technology level adopted by Chinese wind turbine manufacturers and production license is associated with the lowest. The technology levels associated with domestic R&D and joint ventures are between these two. 2.2.2. Supply chain and localization policy As elaborated by He and Chen (2009), supply chains for wind turbine generator systems are not well established within China. Many key components still need to be imported, such as the principal axis bearings and electrical control systems, especially for large turbine sizes. The level of maturity and completeness of the domestic supply chain influences the technology levels adopted by domestic Chinese wind turbine manufacturers in the following way. A relatively advanced wind turbine technology has much higher requirements in terms of components, and many sophisticated components can be produced only by foreign suppliers. Moreover such components are often relatively costly. Hence domestic Chinese wind turbine manufacturers might be less likely to manufacture a more advanced wind turbine technology because of the need to import expensive components. In contrast, a Chinese subsidiary of a foreign wind turbine manufacturer could manufacture a more advanced technology in China because either its foreign parent manufacturer is a component supplier or the foreign parent is familiar with the supply chain outside of China and can assist in linking the Chinese subsidiary with foreign component suppliers. In July of 2005, the Chinese government issued a policy, Notice Concerning Wind Farm Construction and Management Requirements (hereinafter called the 2005 Localization Policy). The policy requires all wind turbines installed in China to have a ‘‘component localization rate’’ – the percentage of components manufactured inside China – of at least 70% (NDRC, 2005). Consequently, foreign wind turbine manufacturers selling in China were required to transfer certain know-how to Chinese suppliers in order to comply with the 70% component localization rate requirement. The expected impact of the localization policy is that all Chinese manufacturers can purchase more advanced components at relatively low cost and thus they would be more capable of manufacturing advanced turbines. Thus we propose: Hypothesis 2. China’s 2005 Localization Policy had a positive impact on the technology level adopted by Chinese wind turbine manufacturers and this is demonstrated by the adoption of higher levels of wind turbine technologies after 2005. 2.2.3. Policies concerning technology level In January 2008, the Chinese Ministry of Finance issued the Notice Regarding the Adjustment of Importing Tariff of Wind Turbines, Relevant Key Components and Raw Materials. This policy was the basis for a tariff and VAT rebate program for import of parts and raw materials used in the manufacture of wind turbines of large turbine sizes (2.5 MW and above). The policy is linked to supply chain constraints: large size wind turbines were

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

309

Localization policy 3

Supply Chain Technology acquisition mechanisms

2

1

Technology level

Firm capacity and motivation

5

4 MW policies

Fig. 2. Conceptual framework notes: Arrow 1: technology acquisition mechanisms directly impact the level of technology acquired through: (1) different investments in R&D, know-how and related personnel and (2) different technologies available through each mechanism. Arrow 2: supply chain directly impacts technology level through: (1) availability of certain components and (2) cost of components. Arrow 3: localization policy directly impacts the supply chain through the introduction of local and cheaper component suppliers. Arrow 4: 2008 MW policies directly impact firm capacity and motivation through the provision of: (1) direct subsidies and thus more funding available for technology development and (2) financial incentives to develop higher levels of technology Arrow 5: firm capacity and motivation directly impacts technology level through: (1) manufacturing and know-how capacity and (2) improved information about market demand and market trends.

considered advanced in China in 2008, and key components for these turbines had to be imported at a high cost. The government provided this tariff and VAT rebate program to make it possible for Chinese manufacturers to afford importing the high-cost components needed to produce turbines of larger turbine size (2.5 MW and above). The Notice also eliminated, as of May 2008, the tariff-free importation of wind turbines of size less than 2.5 MW. Consequently, starting in May 2008, Chinese wind turbine manufacturers had fewer incentives to import components for turbines less than 2.5 MW. Collectively, the aforementioned policies increased incentives to import parts and materials for turbines larger than 2.5 MW, which would further enhance the technology levels used by turbine manufacturers. In August 2008, the Chinese Ministry of Finance issued the Trial Method to Manage the Specific Fund for Wind Turbine Manufacturing Scale-up, which provided incentives for wind turbine manufacturers to produce wind turbines larger than 1 MW: the first 50 wind turbines over 1 MW would receive a subsidy of RMB 600 per kilowatt from the government. To be eligible for the subsidy, the wind turbines had to be tested and certified via the China General Certification (CGC) process.3 In addition, the turbines had to have entered the market, been put into operation and be connected to a grid. In addition, the turbines receiving subsidies had to use domestically manufactured components and subsidies had to be shared with component manufacturers. Based on the previous discussion, the 2008 MW policies provided incentives for firms to produce more advanced turbines. The policies also helped enhance firm capacity by providing direct subsidies for technology development. With enhanced firm capacity, manufacturers will be able to obtain better manufacturing and know-how capacity as well as knowledge of market demand and market trends, and thus be able to produce more advanced turbines. We propose: Hypothesis 3. The two 2008 policies related to technology levels (hereinafter called the 2008 MW Policies) caused Chinese wind manufacturers to adopt higher levels of technology after 2008. 3 CGC is backed by the National Institute of Metrology, which is subordinate to the State General Administration of Quality Supervision and Inspection and Quarantine of the People’s Republic of China.

2.3. Conceptual framework Based on existing literature and field research, we have formed a conceptual framework, as illustrated in Fig. 2, that links technology acquisition mechanisms and government policies to the outcome variable—the technology level. The arrows in the conceptual framework also illustrate underlying interactions among the different factors and the outcome variable. The notes in Fig. 2 provide explanations for each arrow.

3. Hypotheses testing and construction of econometric models 3.1. Dependent variable: Level of technology adoption As mentioned, we employed turbine size as the measure of technology level adopted. There are several reasons for this. Larger turbines produce at lower cost per kilowatt-hour of electricity; this represents the levelized cost of electricity (LCOE), an important characteristic for utility scale operations (EWEA, 2009; Bolinger and Wiser, 2011). Larger turbines also make it possible to utilize land more effectively and they are more easily maintained (EWEA, 2009). Based on He (2009) and our interviews with technical experts, the larger the turbine size, the more complicated and sophisticated the technology because increased levels of complex aerodynamic computer modeling and higher levels of accuracy in the manufacturing process are needed. Given that turbine size is an important measure of the efficiency, complexity and sophistication of wind turbine technology, it serves well as an indicator of the level of a firm’s technology. Control system characteristics (e.g., fixed speed vs. variable speed control) provide an alternative measure of the complexity and sophistication of wind turbines. However, for technologies transferred by Chinese companies in our study, larger turbines tend to have more advanced control systems (CAMIA, 2009). Because control system characteristics and turbine size are correlated in our study, it is sufficient to use turbine size as a measure of technology level.

310

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

There is literature that supports our use of a technology attribute – in our case, turbine size – as a measure of a firm’s technology level. For example, Dodson (1985) used delivered impulse, thrust and motor weight to measure advances in the technology for rocket motors. And Katila and Chen (2008) used repeatability, speed, load capacity and degree of freedom to measure the technology level of robots. We constructed two forms of dependent variable: upgrading in technology level and catch-up in technology level. The variable based on upgrading considers how a firm’s technology level improves compared with its existing technology. The variable based on technology catch-up reflects how a firm’s technology level improves from one technology acquisition period to the next in comparison with the technology level of the world frontier countries. 3.1.1. Upgrading in technology level We use the logarithmic form of turbine size adopted by a firm as the form of the dependent variable based on technology upgrading. In doing so, we are measuring the percentage change of the technology level adopted by a firm. The models based on this variable are used to analyze how various factors influence the change in a firm’s technology level. We use TS as short for turbine size and ln TS as the associated dependent variable. 3.1.2. Catch-up in technology level The second form of the dependent variable concerns how Chinese firms’ technology levels compare to the average technology level used in the world technology frontier countries. The value of this variable for a particular year, referred to herein as ‘‘distance,’’ represents the difference between a firm’s technology level in a particular year and the average turbine size of world technology frontier countries in that year. Because the distance is negative for some firms in some years, the logarithmic form of distance cannot be used. The change in value of this variable measures the change in the aforementioned distance (not the percentage change), and this change in distance is a measure of technology catch-up. The models using this variable analyze how various factors influence a firm’s technology catch-up. In this set of models, DISTANCE is the name of the dependent variable, TSit is the largest turbine size that firm i has in year t, and ASFRt is the average single turbine size of the world technology frontier countries in year t. (TSit is also equal to the size of the last technology adopted by the firm.)

only one mechanism was used to obtain that particular technology. We use JD as the base case, and therefore only LI, JV and DOM appear in the models. The coefficients for these technology acquisition mechanism dummy variables are used to test Hypothesis 1. 3.2.2. Policy The 2005 Localization Policy was intended to develop a local supply chain and thus provide a basis for Chinese wind turbine manufacturers to improve the levels of their technologies. In the model, LOCAL is the relevant dummy variable and it is defined in relation to whether a technology is acquired before or after 2005. The coefficient of LOCAL is used to test Hypothesis 2. The 2008 MW Policies was designed to encourage wind turbine manufacturers to produce larger turbines starting in 2008. In the model, MW is the dummy variable to test the hypothesis related to the 2008 MW Policies, and its definition is similar to that of LOCAL. The coefficient of MW is used to test Hypothesis 3. 3.3. Control variables In addition to the above explanatory variables for testing hypotheses, we also employed the control variables introduced below. 3.3.1. Firm’s technology gap ‘‘Technology gap’’ – used here to mean the distance between the technology level of a firm and the level of technology used by firms on the world technology frontier – is often discussed as a factor influencing innovation (Kokko et al., 1996; Girma et al., 2001; Griffith et al., 2002, 2004; Benhabib and Spiegel 2005; ¨ Girma, 2005; Girma and GAorg, 2007). We employed a modification of the approach followed by Katila and Chen (2008) to measure the technology gap. In considering a technology acquisition in year t, we measured the technology gap that existed in the previous year (i.e., year t  1) by comparing the turbine size of the technology employed by a firm in year t  1 with the average turbine size in the world technology frontier countries in that year. That is, TGit1 ¼ ASFRt1 TSit1 where:

DISTANCEit ¼ ASFRt TSit In considering the distance variable, note that turbine sizes have increased substantially since the 1980s (Red, 2008; EWEA, 2009). Indeed, this is among the more significant trends in the wind turbine marketplace (Hansen and Hansen, 2007). As late as the end of 2007, China lacked the core R&D capacity associated with wind turbine technology, particularly for turbines larger than 1 MW in capacity (Li et al., 2008). 3.2. Explanatory variables and hypotheses testing 3.2.1. Technology acquisition mechanism We define variables representing different technology acquisition mechanisms as follows: LI¼ production license from a foreign company JV¼formation of a joint venture with a foreign company JD¼ joint design with a foreign design/R&D company DOM¼a Chinese firm’s in-house R&D or technology transfer from a domestic research institute. Every firm used at least one of the above four technology acquisition methods. But for each technology a firm acquired,

TGit-1 ¼technology gap for firm i in year t  1. TSit  1 ¼ turbine size in year t  1of the most recently adopted technology by firm i. ASFRt  1 ¼average turbine size of the world frontier countries in year t 1. In our dataset, year t was the year in which the technology acquisition process began, not the year in which the technology was put into production. For firms represented in our dataset, mass production begins one or two years after the start of the technology acquisition process. Also, we use the technology gap of the previous year (t  1) to analyze the technology acquisition in the current year (t). No endogeneity problems exist with the technology gap measure because the technology level adopted in year t does not an influence the technology gap in earlier years. 3.3.2. Firm’s technology acquisition experience A firm’s previous experience could have effects on adopting new technology (Louis et al., 1991; Violante, 2002; Weinberg, 2004). We measure technology adoption experience using the cumulative number of adoptions by the time a firm adopts a new

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

Background of parent company’s other business areas

RELATOTHER

Aerospace Wind turbine component supplier Electrical Heavy equipment Non-heavy equipment Wind turbine manufacturing only Unrelated business areas (e.g., cement production and real estate development)

1 1 1 1 1 0 0

technology. Adoption of a new technology in this context involves a firm adopting a wind turbine technology with higher megawatt capacity. In the model, Nt  1 represents the total number of technology adoptions a firm has made as of year t  1. 3.3.3. Firm’s business diversification Several researchers have identified a firm’s business diversification (i.e., the variety of a firm’s business areas) as a factor influencing a firm’s innovation performance (Kamien and Schwartz, 1982; Hoskisson and Hitt, 1988; Katila and Chen, 2008). We use the following procedure to measure a firm’s business diversification. We divide the manufacturers in our study into seven categories based on the business area of each firm’s parent company (Table 2). In China, a small fraction of the wind turbine manufacturers focus only on wind turbines. A typical Chinese manufacturer is a recently opened subsidiary of a large corporation with a number of other businesses. Wind turbine manufacturers’ parent companies often have other businesses linked to products such as aerospace equipment, electrical equipment, heavy mechanical equipment and oil drilling equipment. Some manufacturers started out as wind turbine component suppliers and then expanded their businesses by becoming wind turbine manufacturers. We employ a dummy variable that measures a firm’s business diversification. The dummy variable is RELATOTHER and its values are given in Table 2. A value of 1 has the following meaning: a wind turbine manufacturer’s parent company has other business areas related to wind turbine manufacturing. A value of 0 means that either a wind turbine manufacturer’s parent company has other business areas that are not related to wind turbine manufacturing or a wind turbine manufacturer does not work in other business areas. 3.3.4. Firm size Literature contains many studies that use firm size to help explain performance in terms of technology innovation (Feder and Slade, 1984; Katila and Chen, 2008). We accounted for firm size by applying a method similar to that of Montalvo and Yafeh (2002). We used data for the cumulative installed capacity of each manufacturer’s wind turbines over time as a measure of a manufacturers’ sales volume. We assumed that all turbines sold would be installed by wind farms. In the model, FIRMSIZEt  1 is the name for the size of a manufacturer as of year t  1. 3.3.5. Ownership type The majority of wind farm developers in China are stateowned enterprises (SOEs). A state-owned wind turbine manufacturer might be able to secure government R&D funds through programs such as State High-Tech Development Plan and the National Basic Research Program. Moreover, a manufacturer that is an SOE might have special connections to government agencies and might use those relationships to increase turbine sales. This linkage can have positive effects on technological improvements.

However, a contrary effect may occur: if a state-owned wind turbine manufacturer enjoys high sales already, it might lack the incentive to improve its technological competence in order to gain additional market share. In the model, SOE is the dummy variable that controls for form of ownership. 3.4. Potential problems and major assumptions 3.4.1. Using turbine size as a proxy for technology level Turbine sizes in our data include each of the following (in units of megawatts): 0.6, 0.75, 0.81, 0.85, 0.9, 1, 1.2, 1.25, 1.3, 1.5, 1.65, 2, 2.5, and 3. Turbine sizes are not completely continuous, but in our model we treat turbine sizes as continuous; this is a noteworthy assumption. However, while we use turbine size as a proxy for technology level, our dependent variable is the logarithmic form of turbine size, which measures the percentage change of technology level; the latter is continuous. For the model of using distance to the world frontier as the dependent variable, there are no problems concerning whether the variable is continuous. We use a weighted-average method to calculate the average turbine sizes using countries representing the world technology frontier and that variable is continuous. 3.4.2. Endogeneity and selection bias issues The econometric model might possibly be subject to endogeneity and sample selection bias. If firms that select certain technology acquisition mechanisms have certain characteristics (e.g., if more capable firms tend to select more complicated mechanisms such as joint design), then the model would have endogeneity and selection bias because those firms are also more likely to be able to produce higher level technologies. If, however, firms select technology acquisition mechanisms at random, then the model would not be biased. Thus it is important to look at the distribution pattern of technology acquisition mechanisms among firms with different capacities. We used initial registered capital as a proxy for a firm’s capacity when the firm was first established. Data was limited and we were only able to find relevant information for 60 of the 68 firms in the analysis. Fig. 3 and Table 3 show results of analyzing whether a correlation exists between initial registered capital and the first technology acquisition mechanisms used by firms. The figure and the table, which show the distribution of firms’ registered capital by choice of initial technology acquisition mechanism, do not reveal any patterns (e.g., firms with larger capital do not tend to choose joint design and smaller firms do not tend to choose production licenses). Given these results, our models are not likely subject to endogeneity or sample selection bias. 16000 11000 6000 Million RMB

Table 2 Assigned Values of RELATOTHER.

311

1000 800 600 400 200 0 Production license

Domestic R&D

Joint venture

Joint design

Fig. 3. Distribution of firm initial registered capital by choice of first technology acquisition mechanism.

312

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

Table 3 Percentage by registered capital size of firms that chose a particular technology acquisition mechanism (60 firms). Firms’ first acquisition mechanism

Production license Self R&D Joint venture Joint design

Firms’ registered capital (million RMB) 0–50

50–100

100–300

4300

23 33 33 11

23 23 44 22

8 30 11 33

46 13 11 33

Note: Percentages for each mechanism sum to 100%.

3.4.3. Robustness check To provide a robustness check, we also ran models which include year as a control variable. Time can serve as a control factor because it can capture the change of the average turbine size in China and the global market. Time can also capture the change of market structure within the wind turbine manufacturing industry. There is colinearity between the year and policy dummy variables; i.e., the year can partly capture the effect of a dummy variable used to control for policy changes. Therefore, for models in which we use year as a variable to control for annual trends we exclude the dummy variables for policies. As shown in Table 6, estimation results do not show significant differences when using these different model specifications; this is an indication of the robustness of our models. 3.5. Model specifications Due to data size limitations (discussed in Section 4), we treated the unbalanced panel dataset as cross sectional data and applied ordinary least squares (OLS) models.4 Table 4 summarizes the model specifications. The models in Table 4(a) use the log of turbine size as the dependent variable and those in Table 4(b) use distance to the world technology frontier. Models 1 and 3 are the models without the variable for year and Models 2 and 4 include year to provide a robustness check.

4. Data Descriptive statistics for key variables are summarized in Table 5. Each technology adoption represents a single observation, and there are 95 observations in total. There are 68 manufacturers, and each of them adopted 1–5 technologies through 1998–2009, with an average of 1.4. We treated our data as cross sectional data instead of unbalanced panel data. Our data come from multiple sources. Data concerning technology adoption – including turbine size, technology acquisition mechanism and ownership type – is from the wind energy equipment unit within the Chinese Agricultural Machinery Industry Association (CAMIA, 2010). Information concerning the background of each wind turbine manufacturer comes from the websites and documents of each of the companies. Statistics on cumulative installed capacity were obtained from Shi (2008) and the Chinese Wind Energy Association (CAMIA, 2009).5 4 Ordinary least squares (OLS) is a method to estimate the parameters of a linear regression equation. This method minimizes the sums of squares of deviations between observed and expected values (Amemiya,1985). 5 CAMIA does not provide the year in which each technology adoption was announced by the company. We found this information on the Internet by searching based on each wind turbine manufacturer’s name and corresponding turbine size and by looking at the companies’ own websites. CAMIA (2010) has records on 100 technology adoptions by Chinese wind turbine manufacturers. For the 5 cases of technology adoptions by manufacturers, we were unable to

We identified six countries as the world technology frontier countries – Denmark, Germany, Spain, Sweden, UK, and the United States—because their wind turbine technologies are widely considered to be among the most advanced in the world (Li et al., 2008). However, because we were unable to obtain the needed information for Denmark, we could not include it in calculations concerning the world technology frontier. Data on average turbine size of the five selected world technology frontier countries was obtained from three sources. BTM (2010) was used to obtain the average turbine size installed by the five countries for the period 2004–2009. Due to the absence of complete data, the world frontier average turbine size for 2003 was calculated using turbine sizes from only four of the five countries—Germany, Spain, UK, and the United States; the source Efiong and Cirspin (2007), a report from Merrill Lynch. Turbine size information for the five world technology frontier countries for 1997–2002 was obtained from Hansen and Hansen (2007).

5. Model and hypotheses testing results For each of the two dependent variables, model results are robust for different model specifications. In general, the modeling results indicate that factors that have statistically significant associations (at p¼ 0.1) with a firm’s upgrading in technology level (as measured by increase in turbine size, in megawatts) include technology acquisition mechanisms, firm business diversification and government policies. Technology acquisition mechanisms and business diversification have statistically significant associations with a firm’s catch-up in technology level, where catch-up is characterized by decreasing distance to the world technology frontier. Policy variables do not have significant associations with catch-up. Table 6 summarizes model results. The t-test results of the individual parameters in the OLS models support the statistical significance of a number of the models’ parameters. 5.1. Technology acquisition mechanisms and Hypothesis 1 Empirical results are consistent with Hypothesis 1; i.e., joint design is associated with the highest technology level adopted, and production license is associated with the lowest. For upgrading in technology level (Models 1 and 2), the coefficients of variables representing production license and domestic R&D are negative and statistically significant. The coefficient for joint venture is also negative but not significant. Results indicate that the turbine size adopted using the base case mechanism, joint design, is the largest among all mechanisms, and production license is associated with the smallest turbine size adoption. Turbines adopted using domestic R&D have a size between those from joint design and production license. Although it is not statistically significant, the turbine size adopted through joint venture is below joint design. Based on Models 1 and 2, a technology acquired using a production license has a technology level that is 22.3–27.8% less advanced than one acquired via joint design; a technology acquired based on domestic R&D has a technology level that is 15.2–16.4% less advanced than one acquired by joint design. For catch-up in technology level (Models 3 and 4), joint design leads to the smallest values of DISTANCE (i.e., closeness to the (footnote continued) determine the year of adoption, and thus those were discarded from our dataset. In the end, we had complete information on 95 instances of technology adoptions and we used those to construct our models. Two of the 95 adoptions were announced in 1998, and the others were announced between 2001 and 2009.

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

313

Table 4 a Models using the logarithm of turbine size (ln TS) as the dependent variable. Model number

Model specification

Notes

1

lnTSit ¼ b0 þ b1 LIit þ b2 JVit þ b3 DOMit þ b4 lnTGit1 þ b5 lnN it1 þ b6 RELATOTHERi 1 1 1 1 þ b7 lnFIRMSIZEit þ b8 SOEi þ l1 LOCALt þ l2 MWt þ n1 it

2

lnTSit ¼ b0 þ b1 LIit þ b2 JVit þ b3 DOMit þ b4 lnTGit1 þ b5 lnN it1 þ b6 RELATOTHERi 2 2 2 þ b7 lnFIRMSIZEit þ b8 SOEi þ l3 YEARt þ n2 it

1

1

1

1

1

1

1

Policy dummies included; year excluded.

2

2

2

2

2

2

2

Year included; no policy dummies

Table 4b. Models using distance to the world technology frontier (DISTANCE) as the dependent variable. Model number

Model specification

Notes

3

lnTSit ¼ b0 þ b1 LIit þ b2 JVit þ b3 DOMit þ b4 lnTGit1 þ b5 lnN it1 þ b6 RELATOTHERi 1 1 1 1 þ b7 lnFIRMSIZEit þ b8 SOEi þ l1 LOCALt þ l2 MWt þ n1 it

4

lnTSit ¼ b0 þ b1 LIit þ b2 JVit þ b3 DOMit þ b4 lnTGit1 þ b5 lnN it1 þ b6 RELATOTHERi 2 2 2 þ b7 lnFIRMSIZEit þ b8 SOEi þ l3 YEARt þ n2 it

1

1

1

1

1

1

1

2

2

2

2

2

2

2

Policy dummies included; year excluded

Names of variables: TS ¼ turbine size, LI ¼production license, JV¼ joint venture, DOM ¼ domestic R&D, TG ¼technology gap, N ¼ number of prior technology acquisitions, RELATOTHER ¼other business related to wind turbine manufacturing, FIRMSIZE ¼ firm size, SOE ¼state owned enterprise, LOCAL ¼the localization policy, MW¼ the MWrelated policies, YEAR¼ linear year trend, and DISTANCE ¼ distance to the world technology frontier.

Table 5 Descriptive statistics for key variables. Variable

Number of obs.

Average

Min

Max

Standard deviation

Turbine size Distance to world technology frontier average Technology gap in previous year Cumulative installed capacity of a firm by previous year (t  1) Number of technology adoptions by a firm as of year (t  1)

95 95 95 95 95

1.531 0.171 1.339 4.755 0.284

0.600  1.217 0.000 0.000 0.000

3.000 1.125 1.885 214.950 4.000

0.500 0.460 0.533 24.853 0.679

Variable

Number of obs.

Production license Domestic R&D Joint venture Joint design

95 95 95 95

Number of adoptions via stated mechanism 27 44 9 15

Unrelated previous business Related previous business but not restricted to wind SOE

68 68 68

Number of firms with stated characteristic 15 39 44

world frontier), followed by joint venture and domestic R&D. The values of DISTANCE are largest for production license. Coefficients for all technology acquisition mechanisms except joint venture are significant. Models 3 and 4 indicate that technology transferred via production licenses tend to have a distance to the world frontier that is about 0.299–0.304 MW larger than joint design and domestic R&D has a distance to the world frontier average about 0.226–0.227 MW larger than joint design. Possible explanations for the above differences among different technology acquisition mechanisms are as follows:

 Joint design. As Chinese wind manufacturers became increasingly familiar with their supply chains and as local component suppliers became more mature, it became productive to conduct joint designs with foreign wind turbine design companies capable of designing advanced technologies. These foreign companies viewed the Chinese turbine manufacturers as their clients and were willing to cooperate with them because they were not concerned about possibilities that their Chinese joint design partners would become competitors. That



explains why joint design has the potential to yield a more advanced technology than is possible via a production license. And joint design may yield more advanced technologies than joint ventures because of fears that Chinese partners might eventually be in direct competition with their foreign partners. Domestic R&D. Designs resulting from Chinese domestic R&D are currently not at the same level as those produced by leading foreign design companies, and this is consistent with the finding that the technology acquired in this way is not as advanced as with joint design. However, since there is no competition between Chinese domestic R&D (public research institutes or firm in-house R&D) and Chinese wind turbine manufacturers, the technology level of the turbines adopted through domestic R&D is higher than through production licenses. In addition, a growing pool of well-trained engineers, and relatively cheap labor cost help explain why Chinese turbine manufacturers might be eager to engage with domestic R&D units or conduct in-house R&D (Von Zedtwitz et al., 2007).

314

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

Table 6 Summary of model results. Name of independent variable

ln TS

Distance

Model number

1

2

3

4

Production license

LI

Domestic R&D

DOM

Joint venture

JV

Log (technology gap)

ln TG

Log (number of prior technology acquisitions)

ln N

Other business related to wind turbine manufacturing

RELATOTHER

Log (firm size)

ln FIRMSIZE

State owned enterprise

SOE

 0.2227 (0.033)nn  0.1520 (0.079)n  0.1119 (0.351) 0.0018 (0.180) 0.0016 (0.156) 0.1451 (0.047)nn 0.0010 (0.475) 0.0589 (0.445)

MW

Localization policy

LOCAL

0.3043 (0.052)n 0.2271 (0.077)n 0.1076 (0.548)  0.0031 (0.122)  0.0018 (0.275)  0.2381 (0.030)nn  0.0039 (0.071)n  0.0383 (0.738)  0.0775 (0.504) 0.1152 (0.426) No 0.1698

0.2988 (0.053 )n 0.2264 (0.077)n 0.1444 (0.416)  0.0030 (0.135)  0.0021 (0.220)  0.2230 (0.039)nn  0.0033 0.1200  0.0453 (0.691)

MW-related policies

 0.2780 (0.012) nn  0.1639 (0.072) n  0.1565 (0.217) 0.0014 (0.327) 0.0017 (0.159) 0.1550 (0.046)nn 0.0006 (0.715) 0.0535 (0.509) 0.1767 (0.031)nn 0.2979 (0.004)nnn No 0.2887

Year included Adjusted R-square

Yes 0.3561

Yes 0.1706

A p-value smaller than 0.1 means that the coefficient is statistically significant. Adjusted R-square is a measure of goodness-of-fit of the models. Note: p-values in parentheses: nnn

po 0.01. p o0.05. p o 0.1.

nn n

 Production license. Some Chinese wind turbine manufacturers began their operations by purchasing production licenses from foreign wind turbine manufacturers. Because foreign manufacturers interested in selling in China generally regard Chinese manufacturers as competitors, they have been reluctant to transfer their most advanced technologies to China. This is consistent with the observation that foreign manufacturers selling production licenses to Chinese companies were often second-tier manufacturers that used less advanced technologies and were not ready to enter the Chinese market; they could profit from selling production licenses without fear of enabling competitors. For example, the foreign wind turbine manufacturers that sold production licenses to Chinese wind turbine manufactures include Dewind, Frisia, Delta and Jacbos, all of which were second tier and had little market share in China’s wind turbine manufacturing industry (Li et al., 2008). Top-tier manufacturers saw few advantages in selling production license to Chinese firms because they could sell turbines to wind farms in China on their own.

5.2. Policies and Hypotheses 2 and 3 For upgrading in technology level (Model 1), coefficients for policy dummies were statistically significant: the 2005 Localization Policy raised the technology level by about 30%; and the 2008 MW Policies raised the technology level by about 17.6%. The results are consistent with our Hypotheses 2 and 3: China’s 2005 Localization Policy had a positive impact on the technology level adopted by Chinese wind turbine manufacturers, as did the 2008 MW Policies. For catch-up in technology level (Model 3), the policy dummies are not statistically significant. Thus, although local and MW policies appear to have been effective in improving the domestic technology level, they have not been effective in helping China catch-up with the world technology frontier.

5.3. Other important factors In terms of upgrading technology level (Models 1 and 2), RELATOTHER (which reflects firm business diversification) is significant and has positive coefficients. A firm with related other business tends to have a 14.5–15.5% higher level of technology than a firm with wind turbine manufacturing as its only business or a firm that has other businesses unrelated to wind turbine manufacturing. For catch-up in technology level (Model 3 and 4), RELATOTHER is also significant and has a negative coefficient (i.e., the gaps to the world technology frontier are diminished). A firm with related other business has 0.223–0.238 MW smaller distance to the world frontier. Parent companies with related other business, such as aerospace equipment, heavy equipment manufacturing and electrical equipment manufacturing, have the ability to transfer their cumulative technical experience from their related businesses into wind turbine manufacturing. That explains why the technology levels of firms with related other business were higher than the levels of firms with unrelated businesses (e.g., real estate or paper production). For the comparison with a wind turbine manufacturer that is only focused on wind turbine manufacturing, a related explanation is based on an assessment by Montalvo and Yafeh (2002) of the role of corporate groups in Japan’s technological progress. They found that large corporation-affiliated firms acquired relatively more foreign technology than independent firms. There is an analogous argument in the case of Chinese wind turbine manufacturers. Following the reasoning used by Montalvo and Yafeh (2002), if a firm is only engaged in wind turbine manufacturing, it might be unable to benefit from the liquidity, economies of scale and related cumulative experience of its large parent corporation. For other variables, including ln TG, ln N, ln FIRMSIZE and SOE, most of the coefficients in Table 6 are not statistically significant. This means that technology gap, previous technology acquisition experience, firm size and whether a firm is an SOE are not

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

315

significant in influencing a wind turbine manufacturers’ technology level.

6. Policy implications 6.1. Encouraging international R&D collaboration Model results indicate that joint design leads to higher technology levels, which highlights the importance of international R&D collaboration under current global economic conditions in which value chains are often fragmented. One way that government can facilitate such collaboration involves the diffusion of information. The first author’s interview results indicate that access to information has a key influence on a firm’s technology acquisition mechanism choice. Chinese wind turbine manufacturers differed in terms of information available on where and how to acquire a technology and that clearly would affect their choice of technology acquisition strategy. The Chinese government could enhance the availability of information available to Chinese firms regarding international best practices in a number of ways, such as organizing international wind energy expositions and conferences. China recently made a start at this. In 2007, China began to hold an annual Wind Power China International Wind Energy Conference; and in 2008, it held its first annual China Wind Power meeting. A second way that the government can facilitate international R&D collaboration involves direct funding or other forms of subsidy that provide incentives and build capacity. Examples of this include the China Renewable Energy Scale-up Program (CRESP) developed in 2006 by the NDRC, together with the World Bank and the Global Environment Facility. CRESP provided awards of 700 million USD to Chinese wind turbine manufacturers that developed advanced technologies for which Chinese firms owned the IP. To win an award, the turbines had to be designed and manufactured in China. After two years of application and evaluation procedures, in 2008, CRESP made awards to five Chinese manufacturers: Goldwind (2.5 MW), Sinovel (3 MW), Dongfang (2.5 MW), Shanghai Electric (2 MW), and Yunda (1.5 MW). Each company received between 120 and 150 million USD to facilitate the acquisition of technology for large turbines through joint design or in-house R&D (CCCIN, 2009). Yunda used in-house R&D and the other firms relied on joint design. All five companies started adopting these technologies in 2006 or 2007. Since 2006, there has been a significant increase in the use of joint design (see Fig. 4). 6.2. Strengthening domestic R&D and capacity building According to the model results, domestic R&D leads to the second highest technology level. In addition, some existing literature suggests that in-house R&D is important in facilitating the positive impact of foreign technology transfer (Li, 2011; Hu et al., 2005; Liu and White, 1997). This suggests that higher wind turbine technology levels could be adopted if the government strengthened domestic R&D and facilitated capacity building for Chinese manufacturers. For example, the government could provide direct R&D funding to both wind turbine manufacturers and public research institutes. While data is limited, we obtained information on whether a firm had received government funding for in-house R&D. Based on the limited available data, we found that at least 4 companies that had created new technology through in-house R&D had obtained government funding to support R&D, either through the State High-Tech Development Plan or the ‘‘Key Project Program.’’ Also, there were 18 transfers from domestic research institutes in our dataset, and those institutes received government support. Thus, at least 22 out of 95 technology adoptions (i.e., 23.2%) in our analysis were supported by the

Fig. 4. Number of each technology acquisition mechanism.

government. Fig. 4 shows that the use of domestic R&D has been increasing over time; this could possibly be a result of the government support mentioned above (e.g., direct R&D funding to private companies, and support of domestic wind energy research institutes).

7. Conclusions Associations exist between technology acquisition mechanisms and levels of technology upgrading (measured by increased turbine size) and catch-up (measured by decreased distance to the world technology frontier based on turbine size). The following associations are statistically significant: a technology acquired by means of a production license has the lowest technology upgrading and catch-up level; a technology acquired via joint design has the highest; a technology developed from domestic R&D has a technology level in between production license and joint design. Such empirical results can assist both the business community and government in the following sense: when manufacturers decide to obtain an advanced wind turbine technology, they should consider the influence of technology acquisition strategy on the level of technology to be adopted. The results also imply the importance of technology R&D collaboration over own R&D and technology import via purchase production license under current global economic conditions. Our results suggest that government policies were effective in increasing the technology level of Chinese wind turbine manufacturers compared with their previous own technology level. But the policies did not contribute to reducing the technology gap to the world frontier technologies. Thus, further policy design efforts, including fostering information access, direct subsidies and capacity building for Chinese wind turbine manufacturers, are called for if the government is to be effective in helping Chinese wind turbine manufacturers catch up with world frontier technology levels.

Acknowledgments We would like to thank the following individuals for the helpful comments they offered during the preparation of the paper: James Sweeney, Matthew Harding, Kalina Manova, Jonathan Levin, Adam Millard-Ball and David Fedor. We are also grateful to the following individuals in China for their generous supply of valuable data and information: Director Wenke Han, Energy Research Institute of the National Development and Reform Commission of China; President Dexin He and Dr. Pengfei Shi of the Chinese Wind Energy Association; Dr. Siyong Wang of the China Huaneng Group; and Deputy Director Zhihong Luo of the China Renewable Energy Scale-up Program. Leonard Ortolano acknowledges, with gratitude, the support provided by the UPS Foundation.

316

Y. Qiu et al. / Energy Policy 55 (2013) 305–316

References Almeida, P., Grant, R.M., 1998. International corporations and cross-border knowledge transfer in the semiconductor industry. A Report to the Carnegie-Bosch Institute, Pittsburgh. Available from: /http://cosmic.rrz.uni-hamburg.de/web cat/hwwa/edok01/cbi/WP98-13.pdfS (accessed 25.06.11). Amemiya, T., 1985. Advanced Econometrics. Harvard University Press, Cambridge, MA., ISBN: 0-674-00560-0. Belderbos, R., Van Roy, V., Duvivier, F. International and domestic technology transfers and productivity growth: Firm level evidence. Industrial and Corporate Change. http://dx.doi.org/10.1093/icc/dts012, in press. Benhabib, J., Spiegel, M., 2005. Human capital and technology diffusion. In: Aghion, S., Durlauf, S. (Eds.), Handbook of Economic Growth. Elsevier, NorthHolland, pp. 935–966. Bin, G., 2008. Technology acquisition channels and industry performance: an industry-level analysisof Chinese large- and medium-size manufacturing enterprises. Research Policy 37 (2), 194–209. Bolinger, M., Wiser, R., 2011. Understanding trends in wind turbine prices over the past decade. Report, Lawrence Berkeley National Laboratory. LBNL-5119E. BTM, 2009. World wind energy outlook. Report, BTM Consult, Ringkøbing. BTM, 2010. World market update 2009. Report, BTM Consult, Ringkøbing. CAMIA, 2010. The 2009 statistics of wind turbine manufacturers in China. Wind energy equipment sub-association of Chinese Agricultural Machinery Industry Association, Beijing. CCCIN, 2009. Breakthrough of localization of the five big wind turbine manufacturers: the bottleneck of supply chain will disappear soon. News, China Climate Change info-Net. Available from: /http://www.ccchina.gov.cn/cn/ NewsInfo.asp?NewsId=16939S (accessed 30.06.11). CWEA, 2010. 2009 statistics of China wind energy installed capacity. Report, Chinese Wind Energy Association. Dodson, E., 1985. Measurement of state of the art and technological advance. Technological Forecasting and Social Change 27, 129–146. Efiong, A., Crispin,A.,2007. Wind turbine manufacturers; here comes pricing power. Industry Report, Merrill Lynch, August, UK. Available from: /http:// www.ml.com/media/81290.pdfS (accessed 30.06.11). ES, 2008. Global market share in wind turbine manufacturers unveiled. News, EcoSeed. Available from: /http://www.ecoseed.org/wind-energy/article/ 8-wind-energy/833-global-market-share-in-wind-turbine-manufacturersunveiledS (accessed 30.06.11). EWEA, 2009. Wind Energy-The Facts: Vol. 2, Costs & Prices, p.103. Report, European Wind Energy Association. Available from: /http://www.ewea.org/ fileadmin/ewea_documents/documents/publications/WETF/Facts_Volume_2. pdfS (accessed 30.06.11). Feder, G., Slade, R., 1984. The acquisition of information and the adoption of new technology. American Journal of Agricultural Economics 66 (3), 312–320. Girma, S., Greenaway, D., Wakelin, K., 2001. Who benefits from foreign direct investment in the UK? Scottish Journal of Political Economy 48, 119–133. Girma, S., 2005. Absorptive capacity and productivity spillovers From FDI: a threshold regression analysis. Oxford Bulletin of Economics and Statistics 67 (3), 281–306. Girma, S., Gorg, H., 2007. The role of the efficiency gap for spillovers from FDI: evidence from quantile regressions. Open Economies Review 18 (2), 215–232. Griffith, R., Redding, S., Simpson, H., 2002. Productivity convergence and foreign ownership at the establishment level. IFS Working Paper WP02/22, London School of Economics and Political Science, London. Available from: http:// eprints.lse.ac.uk/3666/1/Productivity_Convergence_and_Foreign_Ownership_ at_the_Establishment_Level.pdf (accessed 22.06.11). Griffith, R., Redding, S., van Reenen, J., 2004. Mapping the two faces of R&D: productivity growth in a panel of OECD industries. Review of Economics and Statistics 86 (4), 883–895. Hansen, A.D.H, Hansen, L.H., 2007. Wind turbine concept market penetration over 10 years (1995–2004). Wind Energy 10 (1), 81–97. He, D.X., 2009. Personal communication. Director of Chinese Wind Energy Association. He, Y.L., Chen, X.P., 2009. Wind turbine generator systems, the supply chain in China: status and problems. Renewable Energy, 1–6. Henisz, W.J., Macher, J.T., 2004. Firm-and country-level trade-offs and contingencies in the evaluation of foreign investment: the semiconductor industry, 1994–2002. Organization Science 15 (5), 537–554. Hoskisson, R., Hitt, M., 1988. Strategic control systems and relative R&D investment in large multiproduct firms. Strategic Management Journal 9 (6), 605–621. Hu, A.G.Z., Jefferson, G.H., Qian, J.C., 2005. R&D and technology transfer: firm-level evidence from Chinese industry. Review of Economics and Statistics 87 (4), 780–786.

Kamien, M., Schwartz, N., 1982. Market Structure and Innovation. Cambridge University Press, Cambridge. Katila, R., Chen, E.L., 2008. Effects of search timing on innovation: the value of not being in sync with rivals. Administrative Science Quarterly 53, 593–625. Kokko, A., Tansini, R., Zejan, M.C., 1996. Local technological capability and productivity spillovers from FDI in the Uruguayan manufacturing sector. Journal of Development Studies 32 (4), 602–611. Lewis, J.I., 2006. From Technology Transfer to Local Manufacturing: China’s Emergence in the Global Wind Power Industry. Presented at the Woodrow Wilson Center’s China Environment Forum, October 2, 2006. Available from: /http://www.google.com/url?sa=t&source=web&cd=5&ved=0CDoQFjAE&url= http%3A%2F%2Fwww.wilsoncenter.org%2Fevents%2Fdocs%2FCEF.Talk.Lewis. 10.06.ppt&rct=j&q=joanna%20lewis%20pew%20center%20China%20wind% 20turbine&ei=-aUBTrCZB4eiuQOxju3tDQ&usg=AFQjCNEyC2DxLKQV8rDRQ71I -3LQxR_saA&sig2=DmlmOGxWfEPpMiUfNJ6QPw&cad=rjaS (accessed 22.06.11). Lewis, J.I., 2007. Technology acquisition and innovation in the developing world: wind turbine development in China and India. Studies in Comparative International Development 42 (3-4), 208–232. Li, J.F., Gao, H., Ma, L.J., Wang, Z.Y., Dong, L.Y., 2008. China Wind Power Report 2008. China Environmental Science Press, Beijing. Li, X.B., 2011. Sources of external technology, absorptive capacity, and innovation capability in Chinese state-owned high-tech enterprises. World Development 39 (7), 1240–1248. Liu, X., White, R.S., 1997. The relative contributions of foreign technology and domestic inputs to innovation in Chinese manufacturing industries. Technovation 17 (3), 119–125. Lousi, A.L., Harvey, J., Lefebvre, E., 1991. Technological experience and the technology adoption decisions in small manufacturing firms. R&D Management 21 (3), 241–249. Mathews, J.A., Cho, T.S., 2000. Tiger Technology: The Creation of a Semiconductor Industry in East Asia. Cambridge University Press, Cambridge. Mody, A., 1990. Institutions and dynamic comparative advantage: the electronics industry in South Korea and Taiwan. Cambridge Journal of Economics 14 (3), 291–314. Montalvo., J.G., Yafeh, Y., 2002. A microeconometric analysis of technology transfer: the case of licensing agreements of Japanese firms. International Journal of Industrial Organization 12 (2), 227–244. Mu, Q., Lee, K., 2005. Knowledge diffusion, market segmentation and technological catch-up: the case of the telecommunication industry in China. Research Policy 34 (6), 759–783. MWPS, 2011. The top 10 major wind power companies in the world. News, My Wind Power System. Available from: http://www.mywindpowersystem.com/2011/10/ 28/the-10-major-wind-power-companies-in-the-world/. NDRC, 2005. Notice about Wind Farm Construction and Management Requirement. NDRC Energy [2005] no. 1204. National Development and Reform Commission, Beijing. Red, C., 2008. Wind turbine blades: big and getting bigger. Composites Technology. Available from: /http://www.compositesworld.com/articles/wind-tur bineblades-big-and-getting-biggerS (accessed 22.06.11). Ru, P., Zhi, Q., Zhang, F., Zhong, X., Li, J., Su, J., 2012. Behind the development of technology: the transition of innovation modes in China’s wind turbine manufacturing industry. Energy Policy 43, 58–69. Shi, P.F., 2008. 2007 wind power installation in China. China Wind Energy 1, 13. Tsai, K.H., Wang, J.C., 2008. External technology acquisition and firm performance: a longitudinal study. Journal of Business Venturing 23, 91–112. von Zedtwitz, M., Tadashi, I., Li, G., Richard, C., Seppo, H., 2007. Managing foreign R&D in China. Research Technology Management 50 (3), 19–27. Violante, G.L., 2002. Technological acceleration, skill transferability and the rise in residual inequality. Quarterly Journal of Economics 117 (1), 297–338. Wang, Z.Y., Hu, R.Q., Qin, H.Y., Yang, X.S., Shi, P.F., Li, J.F., Qi, H.S., 2005. National action plan on China wind energy industry development. Report, China Renewable Energy Scale-up Program, Beijing. Weinberg, B.A., 2004. Experience and technology adoption. Ohio State University and IZA Bonn Discussion Paper no. 1051, Ohio State University, Columbus. Available from: /http://www.econ.ohio-state.edu/weinberg/comadop.pdfS (accessed 22.06.11). Xia, C.L., Song, Z.F, 2009. Wind energy in China: current scenario and future perspectives. Renewable and Sustainable Energy Reviews 13, 1966–1974. Zhao, Z., Ling, W., Zillante, G., 2012. An evaluation of Chinese wind turbine manufacturers using enterprise niche theory. Renewable and Sustainable Energy Reviews 16 (1), 725–773. Zhou, Y., Zhang, B., Zou, J., Bi, J., Wang, K., 2012. Joint R&D in low-carbon technology development in China. a case study of the wind-turbine manufacturing industry Energy Policy 46, 100–108.