Research institutes and R&D subsidies

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Int. J. Technoentrepreneurship, Vol. 2, Nos. 3/4, 2011

Research institutes and R&D subsidies: Taiwan’s national innovation system and policy experiences Meng-chun Liu* and Fang-I. Wen Chung-Hua Institution for Economic Research, 75, Chang-Hsing Street, Taipei, Taiwan Fax: +886-2-27390610 E-mail: [email protected] E-mail: [email protected] *Corresponding author Abstract: In Taiwan’s national innovation system, the Government-Sponsored Research Institutes (GSRIs) facilitate technology assimilation and/or transfer and cooperative R&D promotion in support of firms, and also act as a policy assistant. Drawing on the dataset of the “Local Industry Innovation Engine Program”, the study quantitatively compares various types of the R&D alliances initiated by GSRIs and the types of R&D grants they received. Based on the empirical evidence, the study argues that there are significantly matching effect between types of GSRIs and the size of firms in organising R&D alliances. Some of GSRIs have their advantage in relieving the distribution inequality problem of innovation resources across sectors and regions. Keywords: R&D; innovation; subsidies; SMEs; R&D alliances. Reference to this paper should be made as follows: Liu, M-C. and Wen, F-I. (2011) ‘Research institutes and R&D subsidies: Taiwan’s national innovation system and policy experiences’, Int. J. Technoentrepreneurship, Vol. 2, Nos. 3/4, pp.240–260. Biographical notes: Meng-chun Liu has been a Research Fellow and Deputy Director of Mainland China Division at Chung-Hua Institution for Economic Research (CIER), Taipei since 2002. He received his PhD in Economics from Monash University, Australia. He is also teaching at Universities with subjects surrounding mainland China’s economy, foreign direct investment, and technology policies. Based on his previous researches on R&D internationalisation, part of his current areas of research is Regional Innovation System in China and R&D Investments by FDI Firms, which empirically looks at the influences of regional attributions on R&D networking and investment by Taiwanese firms in China. In addition, he is looking at the interaction between institution and technologies as part of his research interests. He has many academic publications including: “Offshore R&D Networks of Taiwanese Firms in China” in the book Competing Chinese and Foreign Firms in Swelling Chinese Economy: Competition Strategies for Japanese, Western and Asian Firms, and international refereed journals such as Scientometrics, Government Information Quarterly, International Journal of Technology Management, World Development, Economic Record, Food Policy, Agricultural Economics, and Pacific Economic Review among other economics and technology policy journals.

Copyright © 2011 Inderscience Enterprises Ltd.

Research institutes and R&D subsidies

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Fang-I. Wen is the Assistant Research fellow in Chung-Hua Institution for Economic Research (CIER). She received her PhD Degree from the Department of Agricultural, Environmental and Regional Economics, Pennsylvania State University. Her research interests focus on production theory, applied econometrics, knowledge management, and agricultural economics. In CIER, she has participated in projects involving agricultural development and food safety issues in China, the international marketing and branding strategies of Taiwan’s phalaenopsis orchid, the science and technology cooperation between the developed countries and China, the survey and analysis of Taiwan’s outward and inward foreign direct investment, industry clustering and R&D strategies of Taiwan’s manufacturing sector, and the policies for innovation financing in Taiwan. She has also published in journals such as Education, Knowledge, and Economy, The Journal of Developing Areas, and Agricultural Economics.

1

Introduction

The financial crisis has triggered an intensive debate on industrial and technology policies in most countries. Policies have been redefined within the context of the Triple Helix. The Triple-Helix innovation is considered as a process by which academia, government, and industry collaborate to create or discover new knowledge, technology, or products and services that are transmitted to intended final users in fulfilment of a social need (The Institute for Triple Helix Innovation, 2011). The effective uses of new knowledge in all sectors target boosting new products, processes, and services eventually leading to the creation of jobs and businesses. While R&D grants as a policy tool are popularly adopted by many countries in their pursuit of technological progress and economic development, they are employed to foster the cooperation within the Triple-Helix innovation framework. In order to effectively achieve the objectives of industrial innovation, the R&D-grant schemes tend to subsidise firms with high innovation capacity usually towards leading-edge and emerging technologies. Because R&D policies are mainly based on pure excellence and efficiency criteria, the mechanisms of R&D allocation have caused the R&D resources to be seriously biased against the regions and industrial sectors with lower competitiveness. Such policy should be counterbalanced by public policies for transferring funds to the least developed regions in the pursuit of economic cohesion (Martin et al., 2004). In the event of financial crises, the problems associated with the unequal distribution of innovation resources across industrial sectors and regions stand out more significantly. Especially during the financial crisis, to relieve the traditional sectors of the difficulties that they face from import competition and further reinforce local industrial clusters, the Taiwan government has launched since 2008 a new policy program, entitled the “Local Industry Innovation Engine Plan” (LIIEP). In this program, research institutes are assigned with the tasks of organising R&D alliances with local firms, especially in the regions with less cutting-edge technologies, in order to support them in accessing the government R&D subsidies embedded in various R&D grant programs. Such R&D programs are in line with Taiwan’s national innovation system, which can be described as an SME-public research institute innovation network model (Wong, 1995, 1999).

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M-C. Liu and F-I. Wen

In Taiwan’s NIS, the Government-Sponsored Research Institutes (GSRIs) facilitate technology assimilation and/or transfer and cooperative R&D promotion in support of firms. Taiwan is famous for successfully using GSRIs to promote the diffusion of industrially-relevant technologies. At least, there are two rationales for the LIIEP. First of all, there has been a considerable trend whereby innovation policy has shifted toward R&D alliances and the efforts to advance indigenous firms’ technologies and competences. Direct policies for R&D alliances have become a favoured incentive scheme in some countries (Czarnitzki et al., 2007). R&D alliances not only internalise the positive external effects for knowledge-creation, but also result in cost/risk sharing on the part of both the government and the firms. LIIEP can be regarded as a policy used to improve the research infrastructure (Knoll, 2003). The GSRIs complement the internal efforts of firms by providing access to specialised knowledge and to additional governmental R&D resources. Second, LIIEP is implemented in order to resolve the problem of information asymmetries. Information asymmetries may exclude local firms in the lower-edge regions from private investment. As a signal, the government R&D subsidies help to address the gap (Kleer, 2008). In taking market failure into consideration, various mixes of innovation policy instruments are implemented to foster public R&D and to leverage private business R&D investments. Under the LIIEP, the GSRIs are leveraged to share their innovation resources with the local firms, and to further create investment opportunities in the regions with low levels of technology. R&D cooperation among firms, universities and research institutes is central to the activities of the national innovation system in Taiwan. SMEs account for a significant portion of the industry in Taiwan. Most of them, especially in the traditional sectors, usually engage in innovation only weakly. By using a dataset of a community innovation survey in Taiwan for 2004–2006, Hsu et al. (2009) intended to explore the determinants for innovative firms to engage in R&D cooperation with five types of partners: suppliers, customers, competitors, universities, and research institutes. They indicate that the Taiwan’s NIS consists of two cores with weak connections: R&D cooperation with universities and institutes, and also that within industry itself (among competitors, suppliers, customers). The R&D cooperation within industry is closely related, but weakly related to universities and research institutes. There are many R&D subsidies programs of Taiwan’s government intend to increase firms’ cooperation. Under the LIIEP, the GSRIs are used to promote cooperation within an industry as well as outside. However, in this study, we do not review the performance of the LIIEP, but examines the patterns of various R&D alliances organised by different types of GSRIs as well as the types of R&D grants that they secure under such a program. From the perspective of the concept of the Triple Helix of a NIS, the study intends to point out that the roles played by the GSRIs with their specific capacities may be heterogeneous in fostering R&D cooperation especially between firms and various GSRIs, and in upgrading the innovation of SMEs in low-income regions. By considering Taiwan’s experience, this study further argues that to some extent these research institutes usually organise local R&D alliances by mainly relying on their own technology fields and pursuing their own research interests, but not necessarily meeting the local technological demands of industrial clusters. This may reflect a typical agency problem between the government and its sponsored research institutes.


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The remainder of this paper is arranged as follows. A brief introduction regarding the LIIEP and R&D alliance is presented in Section 2. In Sections 3 and 4, we employ a quantitative approach to compare the patterns of R&D alliances organised by different types of research institutes in different locations. That is, we quantitatively draw on a unique dataset made by the project office, “Traditional Industry Technology Integration Program Office”, to explore the roles played by two types of GSRIs and to review the performance of the program based on the contents of these secured R&D grants. As the concluding section, Section 5 summarises the findings of this study and provides policy implications.

2

R&D alliances and the local industry innovation engine program

Okada et al. (2006) summarised three noteworthy characteristics of public R&D grant systems as follows: •

Research grants generally consist of just a small portion of the total budget, but account for a significant share of the total S&T budget.

•

Many of the government research institutes and independent administrative agencies are generally well-funded.

•

Government research funds are spread through many vertically-divided funding agencies. This is possibly due to a lack of common guiding principles for peer reviews across agencies and to the small number of star or key scientists allocating a much larger volume of research funds from multiple funding agencies. The three characteristics are likely to reinforce the tendency of the Matthew effect (Merton, 1968) in resources of science and technology across sectors. In other words, a small number of eminent firms generate the lion’s share of major innovations and important start-up companies in what appears to be a self-sustaining Matthew effect.

Research institutes, in particular, are seen as crucial for assisting local firms in their innovation activities. From the perspective of regional innovation system theories, the research institutes may function as both local ‘buzz’ and global ‘pipelines’. A high degree of innovative buzz should increase the region-specific knowledge-stock and lead to a comparative advantage with respect to other localities (Graf and Krüger, 2009). That is, the research institutes are assigned to increase the internal density of a local network for the specific knowledge-stocks and also to promote successful clusters by combining local and external knowledge in order to generate novelty. Graf (2011) refers to the ‘gatekeepers’ as actors that serve two functions in the regional innovation system: external knowledge sourcing and diffusion within the local system. Drawing on the patent data from four East Germany regions and applying social network analysis, Graf (2011) argue that the sizes of gatekeepers play minor roles but their absorptive capabilities matter, and the actual significance of public research institutes serve the function of a gatekeeper to a higher degree than private actors.

2.1 NIS and roles of government-sponsored research institutes in Taiwan A proper course of development in Taiwan’s science and technology depends on the government’s policies and effective use of resources. Taiwan employs a highly supportive

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system of comprehensive and active GSRIs as well as various kinds of preferential financing to help indigenous firms overcome various barriers to innovation commercialisation, R&D internationalisation, and advanced S&T development. The government leverages these GSRIs’ capabilities to act as a policy implementation body in organising industrial R&D alliances and transferring innovative products and technologies to local industries. These institutes provide a platform for the interchange of ideas and for setting standards, as well as other dimensions. That is, to meet the policy objectives, these GSRIs serve as the coordinating nodes to promote indigenous technology creation via innovation networks and strategic R&D programs. As expected, these GSRIs in Taiwan have been adapting their strategic roles to a new model of encouragement of, and engagement with, local scientific research (Dodgson, 2009). Furthermore, Taiwan’s GSRIs serve as innovation intermediaries across the business base, and the research base serves to strengthen the technological competitiveness of industry. The research results of academia, mainly universities, are often too primitive to be commercialised. As one of its feasible policy strategies, the government mobilises these GSRIs to develop industrial technologies and to transfer the results to local industries. As a typical case dating back to 1990, ITRI provided its own sub-micron technology to participating firms that were required to share in the R&D expenses. Such an approach is a practical mechanism for firms with common interests to exchange ideas and form standards. These government-sponsored research institutes are intended to accelerate the advance of new industrial technologies, to upgrade industrial technology techniques, and to establish future industrial technologies. That is to say, these research institutes do not target pure science, but rather industrial technologies as they pursue business potential. The Basic Law of Science and Technology was approved in January 1999 in order to lay a sound legal foundation to develop national science and technology. In doing so, the MOEA has been required to provide annual funding for “Technology Research and Development Programs (TDPs)” since 1979. Specifically, the “Organisation TDPs”, the most important type of TDPs, can be regarded as one of the policy tools used by the MOEA to support various research institutes in the implementation of pioneering, key and potential technological research and development. The technological R&D achievements of the Organisation TDPs have been distributed to the industries and eventually transferred to the private sector to promote Taiwan’s economic growth (White Paper on Taiwan’s Industrial Technology: 2009). As argued in Wong (1995), these GSRIs have initially played a role of assimilating advanced technologies from overseas, which they have rapidly diffused to local firms. They also increasingly serve as coordinating nodes in the promotion of indigenous technology creation via innovation networks and strategic R&D programs as well. In Taiwan, the upstream research consists primarily of basic research engaged in mainly by Academia Sinica,1 as well as colleges and universities under the Ministry of Education. In comparison with the other government-sponsored research institutes, Academia Sinica has the mission of pursuing academic excellence rather than of achieving the goals of industrial and technology development. The mid-stream research in Taiwan consists primarily of applied research and technological development conducted by research units of the various agencies of the Executive Yuan (the Cabinet)


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and state-owned enterprises, as well as special projects commissioned to research institutes. The largest research unit by far is ITRI. So far, Taiwan’s MOEA has established 16 government-supported research institutes that cover most fields of industrial technology. Some of these institutes have more than one thousand employees, such as ITRI (the Industrial Technology Research Institute) and III (the Institute for Information Industry). Table 1 lists the government-sponsored research institutes under MOEA. ITRI and III, as we can see, are the top two institutes in terms of their employee sizes. However, some newly-established institutes are small in size, with less than 100 employees. These smaller institutes include SRDC (the Stone and Resource Industry R&D Centre) and PTRI (the Printing Technology Research Institute). Of these 16 institutes, three were set up in the 1950–1960s, five were established in the 1970–1980s, and the others were built in the 1990s. Table 1

Government-sponsored research institutes under MOEA (2009)

Research institutes

Main technology fields

ITRI (Industrial Technology Research Institute)

•

Electronics and optoelectronics

•

Information and communications

•

Mechanical and systems

•

Materials and chemicals

•

Green energy and environment

•

Biomedical technology and devices

•

Networks and multimedia

•

Innovative digi-tech-enabled applications and services

•

Emerging smart technology

•

Digital education

•

Market intelligence and consulting

•

Casting technology

•

Metal forming technology

•

Welding technology

•

Molding and precision machining

•

Fluid control technology

•

Industrial automation

•

Biologics

•

Small molecule drugs

•

Botanical drugs

III (Institute for Information Industry)

MIRDC (Metal Industries Research and Development Centre)

DCB (Development Centre for Biotechnology)

FIRDI (Food Industry Research • Food processing technology and Development Institute) • Bio-resource collection and research

Size Year established (employees) 1973

6000

1979

1500

1963

591

1984

450

1965

360

246 Table 1

M-C. Liu and F-I. Wen Government-sponsored research institutes under MOEA (2009) (continued)

Research institutes ARTC (Automotive Research and Testing Centre)

Main technology fields •

Vehicle performance testing

•

Emission and fuel economy testing

•

Automotive light testing

• TTRI (Taiwan Textile Research • Institute) • PMC (Precision Machinery • Research & Development Centre) • ATIT (Animal Technology Institute Taiwan)

Size Year established (employees) 1990 350

Electromagnetic compatibility Textile industry-related technology

1959

350

1993

250

1970

192

1992

170

1991

150

1976

128

Fibres and related products Machine tool inspection, testing technology Safety of machinery and environmental protection

• Applied biology • Animal medicine • Biotechnology

PIDC (Plastics Industry Development Centre)

• Injection molding technology • Multifunctional materials technology • Green materials technology • Smart material technology • Medical device products

FRT (Footwear and Recreation Technology research institute)

• Footwear and recreation • Assistive devices • High performance elastomers, nanoelastomers, environmentally friendly materials

USDDC (United Ship Design and Development Centre)

• Marine industry research

PITDC (Medical and pharmaceutical industry technology and development centre) CHC (Cycling and health Technology industry R&D centre)

• Medical and pharmaceutical technology

1993

110

• Bicycle creative design and interaction interface technology

1992

110

1992

80

1993

30

•

Shipping, naval, yacht building and fishing

• Sports/medical devices

SRDC (Stone and Resource Industry R&D centre)

• Stone-related technology

PTRI (Printing Technology Research Institute)

• Printing exports, manufacturing and quality control management

• Inorganic waste treatment technology

Source: Combined from the websites of government-sponsored R&D institutes under Taiwan’s MOEA


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The government-sponsored research institutes with their comprehensive technologies (hereafter the RICT) are characterised by their multi-technology fields, and larger-sized capacities in terms of the numbers of researchers and technicians employed and financial resources. As a typical case, ITRI focuses on six technology fields, including Information and Communications, Electronics and Optoelectronics, Chemicals and Nanotechnology, Biomedical Technology, Advanced Manufacturing and Systems, and Green Energy and Environment. In this paper, we classify ITRI, III, and CSIST as the RICT. We further regard 14 other government-sponsored research institutes as RISTs, including MIRDC (Metal Industries Research and Development Centre), DCB (Development Center for Biotechnology), FIRDI (Food Industry Research and Development Institute), ARTC (Automotive Research and Testing Centre), TTRI (Taiwan Textile Research Institute), PMC (Precision Machinery Research and Development Centre), ATIT (Animal Technology Institute Taiwan), PIDC (Plastics Industry Development Centre), FRT (Footwear and Recreation Technology Research Institute), USDDC (United Ship Design and Development Centre), PITDC (Medical and Pharmaceutical Industry Technology and Development Centre), CHC (Cycling and Health Tech. Industry R&D Centre), SRDC (Stone and Resource Industry R&D Centre), PTRI (Printing Technology Research Institute), and INER (The Institute of Nuclear Energy Research). The INER was founded in 1968 and is currently under the administration of the Atomic Energy Council (AEC), Executive Yuan. As a national laboratory, INER possesses a research team composed of 500 talented researchers with graduate degrees. In general, the RISTs have comparatively fewer innovative capacities and limited financial resources. Significantly different from RICTs, the GSRIs with specific industrial technology (hereafter the RIST) mainly target a specific field of industry technologies. Furthermore, their scales are considerably smaller in that their numbers of employees ranged from 1500 for MIRDC to 30 for PTRI in the year 2009. With respect of these RISTs’ industrial technologies, the FIRDI (Food Industry Research and Development Institute) focuses on various food processing technologies and bio-resource collection and research. The ARTC (Automotive Research and Testing Centre) targets vehicle performance testing, emission and fuel economy testing, automotive light testing, and electromagnetic compatibility. It is generally expected that different types of GSRIs are employed to implement policy programs, such as stimulating R&D cooperation and network formation that may differentiate the policy effects. However, there is little literature that explores the issues. By drawing on Flemish experience, Janssens and Suetens (2001) highlight the role of government-sponsored institutes in stimulating cooperation and network formation. Some of the interviewed R&D managers admitted that, although the total amount of R&D expenditures is not necessarily raised by R&D subsidies, R&D efficiency has increased as a consequence of a multiplier caused by networking. In econometric analyses, these effects are seldom shown.

2.2 Local industry innovation engine program (LIIEP) and R&D Networking The mechanism of LIIEP can be broken down into three steps, as shown in Figure 1. First of all, a group of 18 GSRIs ‘adopt’ industry clusters by providing technology consulting services in 25 counties and cities. Second, these GSRIs are also required to organise R&D alliances with local firms to improve their technologies and further look

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at the potential technology issues for grant application. Third, based on the outcomes of the R&D alliances, firms apply for various R&D grants with the GSRIs’ assistance. Figure 1

Mechanism of local industry innovation engine program

The DOIT under Taiwan’s MOEA has since 2008 launched a scheme, entitled the “Local Industry Innovation Engine Program” to increase industrial value-added and achieve regional prosperity by reinforcing industrial clusters. Differing from the “Plan for the Provision of Assistance to SME Technology Development”, LIIEP aims to leverage the capacities of research institutes to assist partner firms by means of various R&D grants by organising local R&D alliances in assigned regions. In order to enforce industrial R&D capacities, the government provides various grant programs, including ASSTD, CITD, ITAS, ITDP, SBIR, and Leading Product Development. The whole program leverages the innovation capabilities of 18 research institutes, consisting of 15 RISTs and 3 RICTs, which are ITRI, III, and the Chung-Shan Institute of Science and Technology (CSIST). CSIST’s technological advantage mainly comes from its defense technologies. Since 2008, the DOIT has begun to leverage research institutes’ capacities to help local firms through the Plan. As of the end of December 2010, these research institutes had organised 324 local R&D alliance cases and helped consortia-firms to propose 328 R&D subsidy applications, of which 239 applications were successfully granted. These R&D alliances included a total of over 870 firms, and led to NT$9.04 billion in total R&D expenditures, of which NT$3.53 billion of the subsidies were granted, and all firm partners contributed NT$5.51 billion of the other R&D expenditures. In Taiwan, LIIEP, with its focus on collaborative R&D, not only integrates the innovation inputs of firms across the industrial upstream, midstream and downstream, but also leverages the innovation capacities of higher education and R&D institutes. With its perspective of innovation and industry policies, collaborative R&D which refers to knowledge linkages plays an important role in assisting industries, especially high-technology industries. LIIEP may cover technology analysis, the analysis of the linkages between key technologies, the analysis of key patents, and the analysis of relevant R&D results. The program is undertaken with respect to technology collaboration models and IP protection models so as to stimulate the formation of industry clusters based on supply chain linkages, while also ensuring the effective utilisation in industry of R&D results produced by universities and research institutes. In addition, LIIEP takes the following issues into consideration. First of all, policies geared toward collaborative R&D aim to enhance innovation networks. The notions of innovation networks are related to the concepts of industrial clusters and the regional innovation system (RIS). The RIS is an adaptation of a national innovation system to a regional setting, in which all the innovation actors are integrated in socio-cultural environments. Within an RIS, actors are systematically engaged in interactive learning (Asheim and Coenen, 2005; Autio, 1998; Tödtling and Trippl, 2005).


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In addition, the common regional culture – itself the product of commonly experienced institutional forces – is able to shape the way in which firms interact with one another in the regional economy. Since different RISs vary quite considerably from each other, firms need to identify the innovation region that best fits their R&D needs. More importantly, the local R&D linkages are related to the compatibility between the RIS and the firm’s innovation network. To some extent, the policies for driving the RIS partly focus on firms’ external networks. The external networks embodied in the RIS provide regional firms with a close supplier-chain relationship, common technologies and customers, as well as labour-market pooling. Second, the policies focusing on collaborative R&D can further industrial clustering, which may effectively reduce the barriers to market entry. As argued by Hoang and Antoncic’s (2003) review of (social) network-based research, the existence of asymmetric information and lack of knowledge lead to hidden profit opportunities in an economy. The exchange of information in cooperative firms is useful for identifying these opportunities and engaging in proper activities to realise gains. An industrial cluster is connected with suppliers of intermediate inputs, and is capable of creating knowledge-spillover effects. In some respects, industrial clusters are able to effectively incubate and promote entrepreneurship. That is, industrial clusters benefit the exchange of information. This helps entrepreneurs to perceive of and to exploit business opportunities by redeploying resources that are independent of the origin or ownership of such resources (Johannisson, 1998). Third, LIIEP has as the core value of its policy the upgrading and transformation of local firms and SMEs within the industrial clusters. The majority of Taiwan’s industries are Small and Medium-sized Enterprises (SMEs) that suffer from the weakness of having limited resources for R&D. Under the ongoing trend towards economic globalisation, external competition has become increasingly fierce. SMEs that might otherwise stick to outdated business models and fail to quickly commercialise their innovations need to transform and upgrade themselves, and raise their competitiveness, if they are to survive in the rapidly changing business environment of the future. In order to strengthen their competitiveness, the government encourages SMEs to develop innovative technologies and products by formulating the Small Business Innovation Research (SBIR) program. The SBIR program aims to foster and encourage participation by minorities and disadvantaged firms in technological innovation, and to increase private-sector commercialisation innovations derived from the government-sponsored R&D. The SBIR Program ensures that the nation’s small, high-tech, innovative businesses constitute a significant part of the national research and development efforts. Under the SBIR program, the different types of research projects include: •

developing a brand new idea, concept or new technology

•

applying an existing technology to a new application

•

applying a new technology or business model to an existing application

•

finally, improving an existing technology or product in various respects.

In order to help SMEs to change and innovate, and to adopt the new ways of thinking that will be needed to cope with the constantly changing global environment, in 2008 the government began to implement the Plan for the Provision of Assistance to SME Technology Development by the university sector, and to upgrade Taiwanese industry by

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effectively mobilising the extensive R&D capabilities of the universities. Through expert diagnostic services, the government helps enterprises’ R&D capacities and effectively provides access to the R&D subsidies available from the government. The program aims to make the universities the long-term partners of firms, thereby strengthening the SMEs’ core technology capabilities and enhancing the competitiveness of Taiwanese industry. In parallel to LIIEP, government-sponsored research institutes, such as the Metal Industries Research and Development Centre (MIRDC), have been assigned to implement the “Plan for the Provision of Assistance to SME Technology Development”. In order to incubate the SMEs with the contents of technologies, such a program aims to leverage the capacities of higher education, by bringing together nearly a dozen foundations and institutes, and jointly using the industry-university research value platform, created by the Alliance of Innovation in Traditional Industry (AITI), along with 3000 experts from almost 140 universities and colleges throughout Taiwan. AITI focuses on the traditional industries mainly surrounding the information, electronics, machinery, chemical, food products and biotechnology industries. By integrating innovative design, materials and manufacturing design with household consumer goods, the program aims to create value through innovation, improving the value-added effect derived from industry-university collaboration. As of June 2010, nearly 1800 SMEs had benefited from AITI. University and college experts had contributed to provide timely solutions to over 3700 cases. The assistance had been provided to help secure SME participation in 78 government research projects with a total of over NT$280 million in R&D funding.

3

Types of R&D alliances by government-sponsored research institutes

In this section, we quantitatively explore the differences in R&D alliances initiated by two types of research institutes. As mentioned in the above section, these government-sponsored research institutes differ from each other in their innovation capacities, size, technology specialisation fields, and in other respects. By drawing on the dataset of the “Traditional Industry Technology Integration Program Office” regarding the “Local Industry Innovation Engine Program”, we aim to quantitatively examine the differences in the R&D alliances organised by these two types of research institute, namely, RICT and RIST, in terms of the industrial deployment, membership, size, and other dimensions. According to the project office’s dataset, there are 145 R&D alliances organised by RISTs, and 179 alliances by RICTs. Based on the industrial fields of leading firms, the R&D alliances organised by RISTs are mainly in the traditional manufacturing industries (77.24%), while R&D alliances organised by RICTs mainly target the high-tech manufacturing (52.51%) and service (16.2%) sectors. In this study, we define the traditional manufacturing industries including the metal machinery industries, chemical manufacturing industries, and household consumer manufacturing industries. As shown in Table 2, industrial classifications of the R&D alliances by both types of research institutes are quantitatively different at the 5% significance level. As shown in Table 2, the R&D alliances organised by RISTs agglomerate more than those of their RICT counterparts in the traditional industry sector. We further examine whether most of the RIST members in the R&D alliances are traditional firms. Similarly, as shown in Table 3, the ratio of traditional manufacturing firm members in the R&D


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alliances organised by RISTs is higher than that organised by their RICT counterparts at the 5% significance level. Table 2

Industrial classification of leading firms

Types of research institutes

Total no. of R&D alliances

Primary industry (%)

Traditional High-tech manufacturing manufacturing Service sector (%) (%) (%)

Specific industrial technology

145

3.45

77.24

17.93

1.38

Comprehensive technology

179

3.35

27.93

52.51

16.20

Total

324

3.40

50.00

37.04

9.57

Pearson χ2(3) = 83.22* *refers to statistical significance of 10% and below. Table 3

Ratio of traditional manufacturing firm members (%)


Total no of R&D alliances

0

≤40

≤60

≤80

≤100

RIST

131

9.92

0.76

3.82

6.87

78.63

RICT

173

21.97

6.36

0.58

4.05

67.05

Total

304

16.78

3.95

1.97

5.26

72.04

Pearson χ2 (4) = 18.83* *refers to statistical significance of 10% and below.

Moreover, the number of partners may refer to the sizes of R&D alliances. As shown in Table 4, the average size of the R&D alliances organised by RISTs is 2.86 firms, while that of those organised by RICTs is 3.13. The average size of the R&D alliances initiated by the two types of research institutes is marginally different at levels of statistical significance of 10%, indicating that RICTs are more capable than their RIST counterparts in organising R&D alliances on a larger scale. Table 4

Size of R&D alliances

Types of research institutes RIST

Total no of R&D alliances (1)

Total no of firm members (2)

Average size per alliance (2)/(1)

131

375

2.86

RICT

173

542

3.13

Total

304

917

3.02

t value = –1.86* *refers to statistical significance of 10% and below.

Furthermore, the ratios of SME members of R&D alliances organised by the RISTs are higher than those organised by the RICTs at the 5% statistical significance level. As shown in Table 5, the ratio of SME members in the R&D alliances organised by RISTs for 80–100% is 70.99%, while that for RICTs is just 36.99%. There is thus reason to conclude that RISTs may take the SMEs’ demands more into consideration compared

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with their RICT counterparts. To some extent, the results may depict the positive correlation between the GSRIs and their R&D alliance members’ firm sizes. Table 5

Ratio of SME members (%)


No. of R&D alliances

RIST RICT Total

131 173 304

0 7.63 23.70 16.78

≤20

≤40

≤60

≤80

≤100

0.00 1.16 0.66

3.05 9.83 6.91

4.58 6.36 5.59

13.74 21.97 18.42

70.99 36.99 51.64

Pearson χ2 (5) = 37.78* *refers to statistical significance of 10% and below.

There are 322 R&D alliances, organised by RISTs and RICTs and deployed in various regions with their household disposable incomes. As shown in Table 6, RICTs organise 65.36% of R&D alliances mainly in high-income regions, while RISTs tend to organise 44.76% of their R&D alliances in medium-income regions. The difference in R&D alliances deployed in regions with different income levels reaches the 5% level of statistical significance. That indicates that RICTs with their abundant innovative capacities are able to match the locational advantage of high-income regions, while RISTs are able to match that of the medium-income regions. However, the low-income regions attract fewer R&D alliances. Table 6

Regional deployment of R&D alliances (%)

Types of research institutes RIST RICT Total

No. of R&D alliances

High-income region (%)

Medium-income region (%)

Low-income region (%)

143 179 322

39.86 65.36 54.04

44.76 27.37 35.09

15.38 7.26 10.87

Pearson χ2(2) = 21.24* The disposable incomes of low-income regions for 2009 ranges below NT$727,434, those of medium-income regions range from NT$746,261–845,481, and those of high-income regions range beyond NT$863,161. *refers to statistical significance of 10% and below.

To sum up, the R&D alliances organised by the RISTs stand out based on their characteristics of high ratios of SME members, and fewer numbers of larger firm members, and are oriented toward traditional industries. To some extent, the evidence shows that RISTs may be better than their RICT counterparts in meeting the purposes of LIIEP of caring for traditional and local industries and SMEs because of their weaker competitiveness. This is more or less because the properties of R&D alliances should be highly related to their initiator research institute capacities and organisational characteristics. In comparison with RICTs, RISTs are smaller in their scale and have narrower technology fields. This may constrain these RISTs in organising larger scale R&D alliances with large firms and targeting technologies across industrial sectors. On the other hand, we may propose that the difference between R&D alliances organised by RISTs and RICTs may be attributed to the matching process in persuasive


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communications. The GSRIs can be regarded as message deliverers and firms as message recipients. When both message deliverers and recipients share the same properties, the recipients can more easily catch the messages. In this way, RISTs are more similar to SMEs and the firms in the traditional sectors as opposed to their RICT counterparts in terms of their various characteristics (Cesario et al., 2004).

4

Empirical examination of R&D subsidies granted by R&D alliances

In Taiwan’s NIS, the government intends to leverage the capacities of governmentsponsored research institutes to improve the innovation performance of industrial clusters. In this section, we intend to construct an empirical model to point out the role played by the government-sponsored institutes in determining R&D Subsidies granted to R&D Alliances.

4.1 Statistical description of the data In 2007, the government set up a project office to implement the LIIEP more effectively. So far, the LIIEP has achieved a primary performance in terms of the research alliances organised by the government-sponsored research institutes. According to the LIIEP project office, there have been 294 research alliances achieved in the three years up to the end of 2010. Based these R&D alliances, the government-sponsored research institutes have assisted partner firms to apply for 294 grants, which can be broken down into 155 alliance-type grants and 139 independent-firm grants. All these granted projects will induce NT$7.33 billion of total R&D expenditure, of which government subsidies will account for NT$2.96 billion. In Taiwan, there are various types of R&D grants offered to firms. The SBIR mainly aims at subsidising and small and medium-sized firms’ R&D investments, but ASSTD, CITD, ITAS, ITDP, and Leading Product Development do not specifically focus on SMEs. These R&D grant programs can be classified into two categories, namely, singlefirm types and alliance firm-types. The types of these R&D projects granted to these partner firms may depend on the properties of the firms and the types of R&D alliances. In this section, we quantitatively explore these factors in order to highlight the features and weaknesses of Taiwan’s NIS. In addition, we explore the important factors determining the magnitude of R&D grants subsidised by drawing on the dataset of the LIIEP project office. As per the above studies, the R&D alliances organised by each type of GSRI have their own specific industrial technology fields and properties. Nowadays, there is a problem of ‘Matthew effect’ of R&D resources across industries and regions. That is, the industries with less-competitiveness in terms of innovation usually receive fewer R&D subsidies. As a result the innovation resources may be disproportionately allocated across firms and industrial sectors. Generally speaking, RISTs organise their R&D alliances surrounding traditional industries and are located in lower income regions, and most of the partner firms are SMEs. In comparison, the R&D alliances organised by RICTs mainly target emerging industrial and service sectors, and are deployed in more highly developed regions, and their partner firms are larger in terms of their scale of operations. In comparison with their RICT counterparts, RISTs may more suitable to relieve the problems of ‘Matthew effect’ of R&D resources.

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4.2 Empirical examination of types of granted R&D projects For firms, industries, and economies, the development of science and technology requires a steady influx of R&D resources. In the case of Taiwan, the government integrates various resources and budgets for supporting the development of science and technology through policy setting and the effective use of resources. As important R&D subsidy programs of the MOEA in Taiwan, the Industrial TDP, the SBIR Promoting Program, and the IT Applications Promotion Project were initiated in 1997 (Mathews and Hu, 2007). The S&T policies leading to the current standard of public-private R&D collaboration in Taiwan were initiated in 1977 when S&T programs were designed to develop pre-competitive basic research and ‘infra-technology’ to disseminate results to the private sector. In 2001, the Industrial Technology Development Alliance Program and the Academic TDP were initiated to foster greater public-private links, with the latter program specifically addressing university-based R&D collaboration. Table 7 summarises the applicants’ eligibilities, the amounts of the government’s subsidies, and their implementation period for various types of Taiwan’s R&D Grant Projects in terms of SBIR/Non-SBIR and Independence/Alliance-type. The reasons for considering these two types of Taiwan’s R&D Grant projects are as follows: Table 7

Summary of R&D grant projects: SBIR/Non-SBIR and independence/alliance-type Applicants’ eligibilities

SBIR

Government subsidies

Implementation period

•

A Small and Medium-sized • Enterprise (SME) with less than NT$80 million in capital, or with not more than 2000 employees

Not more than Independent application: to provide two years each with up to NT$10 million in R&D funding

•

R&D alliance applications: • the applicant must be an SME. The application may be submitted jointly with a university or college, foundation, or other domestic or foreign organisation. At least half of • the alliance members must be SMEs

R&D alliance program: each member is subsidised with NT$10 million in R&D funding. Total subsidies do not exceed NT$50 million

Enterprises are established • under the ROC company law

Total R&D subsidies for each applicant do not exceed NT$30 million within three years.

Non-SBIR •

•

R&D alliance application is available •

Portion of governmental subsidies not more than 50%

Portion of governmental subsidies not more than 30–50%

Not more than three years


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The SBIR program aims to foster and encourage participation by minorities and disadvantaged firms in technological innovation, and to increase private-sector commercialisation innovations derived from the GSRIs. The SBIR Program ensures that the nation’s small, high-tech, innovative businesses are a significant part of national research and development efforts. Under Taiwan’s SBIR program, SMEs can apply for subsidies covering up to 50% of the total cost of R&D. To apply for funding support under the SBIR program, a firm must adhere to the following criteria: •

It must be an SME in accordance with Taiwan’s standard definition of SMEs.

•

It must not owe any back taxes to the government, and must have no record of contract cancellation when participating in government-related technology development plans over the past five years.

•

‘Innovative service’ project applicants may be business offices or medical juridical persons that are engaged in R&D activity and registered for tax purposes.

Finally, in the case of R&D alliance applications related to the SBIR program, the main applicant must be an SME. At least half of the partner firms of the R&D alliance must be SMEs, and the application can be submitted jointly with a university or college, and/or research institutes. Under the SBIR program, each member can be subsidised with NT$10 million in R&D funding. The total subsidies of the R&D alliances cannot exceed NT$50 million. By contrast, under non-SBIR programs, the total R&D subsidies received by each applicant cannot exceed NT$30 million within three years. However, there is no constraint on the total R&D subsidies of the R&D alliance. This appears to suggest that members of the R&D alliance may prefer the non-SBIR programs to the SBIR program because firms enjoy the higher amounts of R&D subsidies and the longer implementation periods.

5

Statistical description

In this subsection, we aim to explore the important factors determining what types of R&D projects are granted by these R&D alliances in terms of SBIR/non-SBIR and independent-firm/alliance types. We draw on the dataset of the project office of the “Local Industry Innovation Engine Program”, in which the valid sample size is 236. In exploring the relevant issues, we summarise the definitions and statistical descriptions of the variables in Table 8. Here two dummy variables, namely, SBIR and ALLIANCE, are used to explore the types of R&D subsidies granted. The independent variables of the empirical model are considered here as follows: type of research institute (RIST), year of R&D granted projects (YEAR), scale of R&D alliance (SIZE) measured by the number of partner firms, ratio of SME partners of the R&D alliances (SME), whether the R&D alliance is related to manifold industries (INDC) or not, the degree of local economic development of the R&D alliance, measured by local disposable household income per capita (LINC), and the types of research institute in terms of their technology fields.

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Table 8

Definitions of variables and statistical description

Dependent variables SBIR

Definitions = 0: non-SBIR granted project

Data Means STD sources 0.63

0.48 LIIEP

0.74

0.44 LIIEP

0.45

0.50 LIIEP

0.42

0.49 –

3.23

1.24 LIIEP

67.63

37.77 LIIEP

= 1: SBIR granted project ALLIANCE

= 0: single-firm granted project = 1: alliance-type granted project

Independent variables RIST

= 1: Research institute with specific industrial technology = 0: Research institute with comprehensive technology

YR09

= 1: granted project for 2009

SIZE

Number of partner firms

SME

Portion of SMEs (%)

INDC

1: cross industrial sectors

= 0: other years

0.54

0.50 Measured by the study

Disposable household income per capita 6.78 (NT$ thousands, taken in natural logarithms)

0.19 Measured by the study

0: partner firms from single industrial sector LINC

Sample size = 236.

5.1 Empirical evidence We further explore the important factors affecting the R&D alliances’ access to the various types of R&D grants and the scale of the secured governmental subsidies by employing empirical approaches. The first two columns of Table 9 for SBIR and ALLIANCE reveal the empirical results of a Probit model with respect to the SBIR/ non-SBIR types and a single-firm/alliance-type for the granted R&D projects. In consideration of the possible correlation between SBIR and ALLIANCE, we adopt a Bivariate Probit model for empirical examination. The coefficient of ρ is statistically insignificant (Table 9), indicating that both SBIR and ALLIANCE equations can be examined independently. Table 9 further reveals the coefficient of YR09 on SBIR to be positive and also to reach the 5% level of statistical significance. These results are in line with the outcome of the adopted temporary policy for 2009 in order to relieve local industries’ difficulties resulting from the global crisis. Under such a policy, the government increased the probabilities of R&D grants secured for the applicants in order to aid local firms within industrial clusters. The coefficient of SIZE on SBIR is negative in sign and reaches statistical significance at the 5% level. By contrast, the coefficient of SIZE on ALLIANCE is positive in sign and also reaches statistical significance at the 5% level. The empirical results may indicate that the sizes of the R&D alliances are significantly relevant to the types of R&D grants in SBIR/non-SBIR, and also to the single-firm/alliance-type.


257

Usually, an R&D alliance consists of critical partner-firms with upstream and downstream relationships. The larger size of the R&D alliance does not necessarily lead to R&D projects being granted to SMEs, but this should be preferred to R&D projects being granted with the alliance-type. In other words, the partner firms are able to secure the government’s financial support. In line with the argument, the R&D alliances with larger scales of operations in general receive more governmental R&D subsidies. In Table 9, the coefficient of SME on SBIR is positive and statistically significant, but is negative and statistically insignificant on ALLIANCE. That is, the R&D alliance with more portions of SMEs does not tend to provide access to granted projects of the alliance-type but to SBIR. This is because the SBIR is more intended for applicants from SMEs. Table 9

Types of R&D grants and scale of governmental subsidies Probit model

Variables

SBIR

ALLIANCE

RIST

0.29 (1.38)

–0.42 (–1.96)**

YR09

0.69(3.20)***

0.36 (1.91)*

SIZE

–0.19 (–2.18)**

SME

0.02 (7.12)***

0.50 (3.78)***

Bivariate probit model SBIR

ALLIANCE

0.30 (1.42)

–0.41 (–1.93)*

0.68 (3.19)***

0.35 (1.83)*

–0.18 (–2.12)**

–0.004 (–1.37)

0.02 (7.15)***

INDC

0.33 (1.62)

LINC

–1.00 (–1.59)

–0.97 (–1.76)*

–1.01 (–1.62)

–1.02 (–1.86)*

6.07 (1.38)

5.39 (1.40)

6.13 (1.41)

5.76 (1.52)

Intercept

0.55 (2.75)***

0.48 (3.77)*** –0.004 (–1.38)

0.32 (1.60)

0.22 (1.60)

ρ Ln-likelihood No. of Obs.

0.56 (2.80)***

–101.74 236

–109.09 236

–209.56 236

Figures in parentheses are t-values. *, ** and *** refer to statistical significance of 10, 5, and 1%.

As shown in Table 9, the coefficients of INDC on SBIR are positive but insignificant, while they are also positive and statistically significant on ALLIANCE. The empirical results appear to indicate that the R&D alliances with cross-industry partners tend to provide access to R&D grants of the alliance-type. That is, the R&D alliances consisting of partners from different sectors in general prefer to apply for research grant projects across industrial sectors. As a result, the types of their granted research projects should tend to be of the alliance-type. Finally, we can see from Table 9 that the coefficient of LINC is negative and reaches the 10% level of marginal significance. The empirical evidence may indicate that R&D alliances in lower-income regions tend to apply for R&D grants of the alliance-type. To some extent, LIIEP successfully helps local firms not only to secure government R&D resources, but also to organise R&D networking and to further solidify local industrial clusters in lower-income regions. Based the above evidence, we may argue that GSRIs successfully play both roles of local buzz and cross-region pipelines in increasing the region-specific knowledge-stock and improving the comparative advantage of lower-income regions. In other words, LIIEP has met the policy purposes for the reallocation of R&D resources to the regions with lower competitiveness.

258

6


Concluding remarks

In Taiwan’s national innovation system, the government-sponsored research institutes have a role in helping the government in its implementation of industrial technology policies. However, few studies intend to highlight the properties and limits of the GSRIs in acting as the government’s policy tools or agencies. For enriching the issues surrounding the Triple-Helix innovations, this study investigates the differences in performance of two kinds of assigned GSRIs under the context of the LIIEP. GSRIs help those firms with the potential to secure for themselves government R&D grants. To some extents, R&D resources can be reallocated to the industrial clusters located in the difficult regions. In addition, GSRIs perform external knowledge sourcing and diffusion within the local system. That is, the mechanism of the LIIEP more or less is line with Graf’s (2011) gatekeeper framework. By quantitatively comparing the two types of GSRIs in terms of their capacities and behaviour, the study aims to emphasise the comparative advantages of research institutes with specific technologies in terms of caring for the industrial clusters that are losing their competitiveness. The important findings are depicted in Figure 2 and are also summarised as follows: Figure 2

GSRIs, types of research alliance and granted R&D projects

First of all, based on the empirical evidence from Section 3, the types of research alliances organised by the RISTs are marked by their smaller scale in terms of the number of firm members, higher proportions of SME members, and their deployment mainly in lower-income regions. To some extent, the evidence reflects the matching effect between types of GSRIs and sizes of firms. Second, as shown in Sections 3 and 4, in comparison with RISTs, RICTs prefer that their firm-members apply for alliance-type R&D grants. This is partly because alliancetype R&D grant projects help RICTs to diffuse their own technologies by technology sharing with their team-members. Third, RISTs have lower capacities in organising larger-scale R&D alliances. Accordingly, RISTs prefer that their team member firms secure both independent firm-type and SBIR R&D grant projects. Part of the reasons may be attributed to the fact


259

that the SBIR program sets up a limited amount of alliance-type R&D subsidies. In addition, RISTs’ R&D alliances are characterised by more portions with SME members, and also support to secure SBIR grants. Fourth, from Sections 3 and 4, RISTs’ research alliances are mainly deployed in lower-income regions in which most of the granted R&D projects are of the alliance-type. The above evidence may imply that RISTs are superior to their RICT counterparts in terms of increasing the internal density of local networks in lower-income regions. Finally, based on the above discussions, the following point deserves explicit emphasis. Acting as a part of the Triple Helix and also as a policy assistant, different GSRIs can have their specific policy contributions based on their internal endowments and external networking relationship. The government should not simply treat all research institutes in the same way. By contrast, the government may adopt a sophistic and differential approach in leveraging GSRIs’ specific capacities. In particular for relieving the distributive inequality of innovation resources across industrial sectors and regions, RISTs enjoy a comparative advantage in achieving the policy objects.

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Note 1

Academia Sinica, established in 1928, has been the most well-known research institution in Taiwan. From its beginning, Academia Sinica has the pursuit of academic excellence. Nowadays, Academia Sinica has expanded to 24 research institutes and preparatory offices and 7 research centres. Academia Sinica has the mission to conduct cutting-edge research in the humanities and sciences, nurture academic talents, and issue policy advisories.