Catch-up Industrialization and Growth Trajectory of Science and  Technology: A Comparative Study on Asian Economies
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Catch-up Industrialization and Growth Trajectory of Science and  Technology: A Comparative Study on Asian Economies Catch-up Industrialization and Growth Trajectory of Science and Technology: A Comparative Study on Asian Economies Document Transcript

  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov Catch-up Industrialization and Growth Trajectory of Science and Technology: A Comparative Study on Asian Economies Chan-Yuan Wong (Corresponding author) Department of Science and Technology Studies, Faculty of Science, University of Malaya, 50603 Kuala Lumpur, Malaysia Email: wongcy111@gmail.com Kim-Leng Goh Department of Applied Statistics, Faculty of Economics and Administration, University of Malaya, 50603 Kuala Lumpur, MalaysiaAbstractAs typical emerging economies in the race for acquiring innovation rents, many emergingeconomies have the urgency to transform their economy in which dependent on export-orientedmanufacturing to knowledge-based economy. Many studies highlighted the pathways taken bythese economies to achieve development and how distinctive national innovation systemcontributed to growth and productivity in science and technology. Through theoretical analysisand empirical demonstration, this paper attempts to capture in a stylized the national innovationsystem strategies in shaping science and technology trajectories for South Korea, Taiwan,Singapore, Malaysia and China. The science and technology (proxied by papers and patents)trajectories were examined using bi-logistic growth function. The findings suggests that catch-upgoverning strategic model of South Korea and Taiwan had led to much longer and higherdevelopment trajectories during the transition towards knowledge-based economy than countriesthat are dependent on FDI for learning and acquiring technology such as Singapore and Malaysia.Keywords: Catch-up Industrialization Models, Growth Trajectories, Science and Technology,Papers and Patents, Asian Economies1. IntroductionThe newly industrialized economies (NIEs) and the emerging economies of Asia have beengrowing fast and strong, even after experiencing several economic crises over the decades(Keller and Samuels, 2003). South Korea, Singapore, and Taiwan, as the newly industrializedeconomies, are notable for maintaining high growth and rapid industrialization. They haveachieved remarkable rapid industrial and science and technological catch-up (Wong, 1999).Their science and technology policies have successfully advanced the basic and applied research-based activities that led to a development pattern that is consistent with self-propagating growthin science and technology (Wong and Goh, 2009). Developing countries of Asia, such as Chinaand Malaysia emerged as fast-growing economies given their strong export performance and theavailability of cheap and semi-skilled labour. In the transition to a developed and knowledge-based economy, these countries placed emphasis on upstream activities, attempted to raise 1
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novnational investments in R&D and researchers since the 1990s to develop its science andtechnological capabilities. As typical emerging industrializing economies in the race for acquiring innovation rents1,South Korea, Taiwan, Singapore, China and Malaysia have the urgency to transform theireconomy in which dependent on export-oriented manufacturing to knowledge-based economy.Many studies highlighted the pathways taken by these economies to achieve development andhow distinctive national innovation system contributed to growth and productivity in science andtechnology (Lall and Teubal, 1998, Fagerberg and Godinho, 2004, Hu and Mathews, 2008, andTseng, 2009). These late industrializing economies have been engaging in standard-relatedactivities, building manufacturing capabilities and focusing on import substitution of parts andcomponents (Amsden and Tschang, 2003). As their production moves up the value chain (frombeing merely standard followers to standard leaders), these economies stepped up investment inapplied research to improve their technological capability (Ratanawaraha, 2005). A fewcountries of Asia begun to catch-up with the advances economies, largely attributed to their wellfunctioning national innovation system (Mazzoleni and Nelson, 2003, Wong and Goh, 2009 and2010a). The strategic model of national innovation system of these economies led to promisingdevelopment in the potential and vitality of science and technology, provided policy lessons forthe other developing economies. The evolving models of science and technology policies led to divergent trajectories ofscience and technology growth and diffusion. Wong (1999), Wong and Ho (2007) and Wong andGoh (2010b) suggest the generic technological capability development routes in two distinctivemodels: • New Start-ups for Product Technology Pioneering Model: The model generally involves government incentives and supports to fuel entrepreneurial activities, reduce risks by firms that involved in costly investment for innovation, and stimulate R&D investment for science and technology. Advanced entrepreneurial infrastructure is central for development. Technology policy is basically designed to avoid over-reliant on MNCs’ technologies during early industrialization. State intervention practice is essential to build technology capabilities and competencies, particularly during the infant stage of industrial development (Nelson, 1993, Alavi, 1999 and Reinert, 2008). • FDI Leveraging Model- Technology policy is developed to favor the MNCs (Multinational Corporations) that wish to upgrade their manufacturing process capabilities to manufacture new and advanced products. The spillover of know-how from the multinationals would spawn many local supporting industries and lead to constantly increase of technology among local linkages firms. This could be done so by focusing on the provision of basic infrastructure, political stability and security to support export- intensive manufacturing activities.1 The race is largely attributed to the compliance of many Asian economies to the establishment of WTO standardrules since the mid of 1990s. Many Asian economies amended their IPR (intellectual property rights) to comply withTRIPS agreement and other WTO standards. 2
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov Industrial policy2 of late industrializing economies like South Korea and Taiwan havetraditionally placed emphasis on entrepreneurial infrastructure and development of local-ownedmanufacturing industries, while FDI leveraging countries like Singapore and Malaysia havetraditionally emphasized on institutions that facilitates the operation of MNCs and spillover oftechnology between the MNCs and its local subsidiaries firms. In search for workable policiesfor science and technology, China has been maintaining two competing models operated at thelocal (or regional) level3 toward science and technology development. The success of one regionin science and technology provides some guides and policy implications to other regions to adoptsimilar policies and model for development. The policies run in regions may eventually beelevated to central policies for development of national science and technology (Naughton andSegal, 2003). In the transition to knowledge-based economy, science and technological stock emergedto be significant. Both models generally witnessed positive effects on science and technologicalknowledge stock and development in many Asian emerging countries since the 1990s (Wongand Goh, 2010b). Commitments and initiatives to improve competitiveness appear to be in placein these emerging countries, it remains to be observed to what degree of successful developmentof their technological innovation. To date, although many studies have been conducted to examine the extent of science andtechnological growth and development in many Asian emerging countries, a systematic approachto examine the diverging growth trajectories of science and technology is still severely lacking inthe literature. The focus of the preceding diffusion and development studies (Bhattacharya, 2004,Hu and Mathews, 2005, Leydesdorff and Zhou, 2005, Zhou and Leydesdorff, 2006, and Wongand Goh, 2010a,c) without considering the models of science and technology policies andstructural change of economic activities limits a comprehensive understanding of Asian scienceand technology growth in knowledge-based economic development. By the mean of theoreticalanalysis 4 and empirical demonstration, this study aims to trace the science and technology(proxied by papers and patents respectively) growth trajectories based on bi-logistic growthfunction considering the structural change in economics activities from industrial-based to aknowledge-led development. The study provides a comparative analysis on selected NIEs andfast-growing economies in Asia. South Korea, Taiwan, Singapore, Malaysia and China areincluded in this study for their different level of achievement in development and adoption ofdifferent models for science and technology development. There are significant commonalities between the selected economies to warrant somearguments and discussion of Asian innovation system. These economies are compared in this2 We follow the definition of Chang (2003, pg. 113) where industrial policy is defined as “a policy that intended toaffect particular industries to achieve outcomes that are perceived by the state to be efficient for the economy as awhole”. “The policy attempts to change the economic structure over and beyond what the market is able to do byinducing the private sector agents into new activities that they do not have interest in entering under free marketsituation” (Chang, 2003, pg. 313). State-own enterprises or government linked companies in these economies wereestablished to facilitate their economic development in specific sectors (sectors in which required huge capitalinvestment and protection such as transportations, utilities and automobile industries).3 The improvised strategy is viable due to the size and diversity of the country (see Naughton and Segal, 2003).4 This study seeks to integrate insights from institutional theory and innovation studies to provide a coherent view onthe national institutional dynamics that drive the development of science and technology. 3
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novstudy for several reasons. The science and technology development path of these economies hadmany similarities in their evolution trajectories, technological option and avenue of innovation5(Hobday et al., 2001, Archibugi and Pietrobelli, 2003, Fagerberg et al., 2007, Tseng, 2009 andWong and Goh, 2010b). Their science and technology policy evolved from solely supportingtechnological development in manufacturing industries to strengthening the role of nationalscience and technology institutions to support transformation towards a knowledge-basedeconomy. It would therefore be interesting to compare the extent of divergence in science andtechnological growth trajectories of these economies.2. Concept and MethodologyThe aim of this section is to lay out a conceptual model describing the contexts for catching-upstrategies and a taxonomy of bi-logistic growth function explaining growth trajectories of scienceand technology.2.1 Elucidation of Catching-up Industrialization StrategiesThe order of discussion proceeds from the case of new start-ups for product technologypioneering model to FDI leveraging model.Basically, there are two dominant catch-up governing strategies for new start-ups for producttechnology pioneering model adopted by many developing economies to learn and acquiretechnologies through mechanisms other than FDI. • Chaebol conglomerate approach • SMI-state network approachFor the case of South Korea and Taiwan, the strategies were effective in acquiring manytechnology capabilities (particularly in ICs and semiconductor), and their economies succeededin catching-up and moving towards the world production frontier. This virtuous cycle is builtbased on synergies and systemic effects6. The South Korean strategy for technological development is to build up the processcapability in the initial stage, then followed by the mastering of sophisticated products throughimitative R&D. Foreign knowledge and technology was the main source for technological catch-up of the local firms during the 1960s. The firms of South Korea adopted the reverse product lifecycle strategy to develop their technology capability. The strategy involved is to first develop theprocess capability, then followed by developing sophisticated products through imitative R&D.Finally, firms invest in R&D for own product and process technologies (Wong, 1999). To move up the value-chain of technology, South Korea practice a state protectionstrategy, and mobilized resources targeted at chaebol firms to build technology capabilities andcompetencies, particularly during the infant stage of industrial development. The direct support5 The use of information and communication technologies (ICT) is particularly essential for economic growth inthese economies.6 The magnitude of knowledge spillover to the local economies was impressive due to the adoption of the mentionedstrategies to develop high technological sectors. 4
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novfor large chaebol firms not only facilitated them to develop their own products and selling undertheir own brands in the local market, but also enabled them to establish R&D capability tocompete successfully in a few global industries such as automobile, semiconductors, consumerelectronics and telecommunication equipment. The government incentives and supports fueledentrepreneurial activities in the 1970s and 1980s, reduced risks by firms involved in costlyinvestment for innovation, and stimulated R&D investments for science and technology (Wong,1999, Lee, 2006 and Rasiah, 2007). Their dynamic technology policy led to systemic learningand catching-up with the advanced technology of developed countries in most chaebol firms,which subsequently led to growing technological capabilities (Lee and Lim, 2001, Yun, 2007,and Joo and Lee, 2009). The Taiwanese firms adopted the Original Equipment Manufacturing (OEM)-OriginalDesign Manufacturing (ODM)-Original Brand Manufacturing (OBM) strategy to develop theirtechnology capability (Hou and Gee, 1993 and Wong, 1999). The strategy involved is to firstdevelop the process capability through the mastering of contract assembly operations (OriginalEquipment Manufacturing, OEM), then followed by developing sophisticated products throughimitative R&D. Finally firms invest in R&D for own product and process technologies (OriginalDesign Manufacturing, ODM). According to Jan and Chen (2006), the R&D system of Taiwanconsist of industrial firms, government supported institutions and universities. Most of theTaiwanese firms are small. Therefore the R&D resources for developing new technology arelimited. In addition, large firms in Taiwan spent little on R&D activities and the firms weredependent on their foreign partners (the MNCs) to develop new technology. The governmentsupported institutions, including the Industrial Technology Research Institute (ITRI) establishedin 1973, are to support the technology development of small and medium industries (SMIs) ofTaiwan. ITRI plays an important role in initiating, developing and supporting industrial R&Dactivities. ITRI have set up laboratories with firms with the purpose of improving quality andmanufacturing processes of products. Many firms (such as UMC and TSMC) have successfullyspun-off from technology acquired from the ITRI laboratories (Hu and Mathews, 2005). ManyTaiwanese firms now attempt to develop their own products that are sold under their own brands(Original Brand Manufacturing, OBM). All these activities are strongly supported by the ITRIlaboratories and development schemes. Taiwanese firms gradually move to higher value-addedproducts and involved in themselves science-based technological R&D activities7. Accordingly,many academic researchers increased their involvement in R&D activities for industrial firms8.Interaction between firms, government support research institutions and universities is central fordevelopment in which activities between science, technology and market initiate, import, use,modify and diffuse science and technology. The role of the Taiwan government changed from investment and facilitation to the roleof triggering R&D activities during 1970s to stimulate learning and innovations in SMIs. TheTaiwanese SMIs transformed their simple manufacturing operations to higher value-added ODMactivities and OBM. According to Rasiah and Lin (2005), the integrated operations of market,government and social trust had reduced government failure in R&D investment to help raise theflow of reliable information and performance-oriented commitment.7 The activities include telecommunication engineering, biomedical, IC design, optoelectronics and material science.8 During the 1970s and 1980s, the interaction between universities and industrial firms is limited. 5
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov Singapore, Malaysia and China (the province of Guangdong in particular) adopted astrategy that emphasized government facilitation of multinational corporations (MNCs)-inducedtechnological learning (Koh and Wong, 2005). Their science and technology policy supportedthe MNCs that aimed to upgrade their manufacturing process capabilities to manufacture newand advanced science and technological products in Singapore. Thus, the local assembly firmsthat were awarded contracts by the MNCs might also benefit in the process. The industrialtechnology grew from simple manufacturing operations in the 1970s to high value-addedproducts and manufacturing activities, and science-based technological R&D activitiesaccelerated since the early 1990s. In the early 1990s, the government of Singapore and Malaysiastarted to increase their investment in basic research activities to pursue application pioneeringstrategy. This strategy accelerated the development of technological capabilities among theMNCs and local firms through the adoption of new and advanced technologies in theirmanufacturing processes. There are many studies suggest that Singapore and Malaysia has thepotential for attracting applied research activities from MNCs (see Amsden and Tschang, 2003and Chandran and Wong, 2010). The MNCs have taken the advantage of the local resources (interm of local talents and infrastructures) to build their capacity and appropriate the collectiveknowledge embodied in organizational routines and institutional memory for their economic andtechnological gain.2.2 Taxonomy of Bi-logistic Growth FunctionIn an innovation system, universities and research institutions (the national science system) arethe core producers of science output (knowledge production and transfer) while industries (thenational technological system) are the core producers of technology output (Lundvall, 1992). Webelieve the extents of functions of an innovation system are managed and policies andinstitutions are adopted through conscious and collective with bounded rationality choices.Therefore, due to the unique national innovation system, and co-ordinated strategies and effortsfor science and technology, a nation would have distinctive characteristics in the developmentprocess. It is important to study the production of science and technology as output of thenational innovation system. Research on science and technology production in the literature explains how science andtechnological innovation spreads among adopters through the form or pattern of the S-curve(Daim et al., 2006). Following Kondratieff-Schumpeterian business life cycle theory, there aremany functions used as analytical approach to capture the life cycle of science and technologyand explain the phenomena or test specific growth hypothesis (Baudish and Grupp, 2006). Thesimple logistic function stated below is of the most common form: K (1)pt = 1 + ae −btwhere:pt: value of the unit of science/technology at time t,K: potential limit of growth or carrying capacitya: initial stage of growthb: velocity 6
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th NovTo plot the S-curve on log-linear function,L = p t (1 + ae − bt ) L − 1 = ae −bt pt L (2)log( − 1) = log a + bt pt The logistic growth function has a carrying capacity K that is constant, with the basegiven by coefficient a. The carrying capacity provides an indication to the underlying potentialof the process. A constant carrying capacity of the logistic growth function implies that the limitto potential of science or technological production is fixed at some given level. The simple logistic function that has its origin in the biological realm9 is often used tomodel the production of science and technology due to its rich empirical description and itseffectiveness in capturing the changing nature of science and technology (Devezas et al., 2005).The epidemiological concept is used to describe the spread or production of science andtechnology. The production of science and technology is basically influenced by internal sources,a process through contacts among agents of the social and innovation system. Many studies(Gupta et al., 1997, Anderson, 1999, Teng el at., 2002, Watanabe et al., 2003, Bengisu andNekhili, 2005, Devezas et al., 2005, and Nagamatsu et al., 2006) demonstrated that the externalinfluence is relatively weak (revealed through extremely low coefficients and poor fit of theinternal influence model) compared to internal influence. Many studies which focused oninternal influences found this function useful to fit and describe the growth pattern of science andtechnology (Anderson, 1999, Foster and Wild, 1999, Teng el at., 2002, Bengisu and Nekhili,2005, Devezas et al., 2005, and Kucharavy and Guio, 2008). The selected Asian economies are currently evolving from an economy dependent onlabours and capitals to economies that dependent on knowledge-based development. The shift islikely to witness an increasing return to production of science and technology. This is attributedto the properties of knowledge that have characteristics akin to increasing returns (Foray, 2006). Considering the perspective of paradigm shift from industrial to post-industrialknowledge-based economic development, it is crucial to separate the production into two stagesof development (before and after knowledge-based economic development) to capture the twoimpulses of growth. Given two serial paradigm processes, each paradigm is modeled with asimple logistic function 10 . By this, the persistence and ability to improve the production ofscience and technology (the growth characteristics) in the process of paradigm shift can be9 The function is also commonly used to study population growth, a metaphor of biological realm such as evolution,selection, life cycle and survival of the fittest.10 The bi-logistic growth function is useful to depict system with two serial logistic growth processes. Each set ofgrowth is depicted with a simple logistic function. The extended function makes is useful only when dramatic shiftsaway from the first simple logistic behaviour can be observed (Yang and Williams, 2008). 7
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novobserved from the acceleration of the emergence of the second waves. The following equationdepicts two combined simple logistic growth functions. K1 K2 p (t ) = −b1t + (3) 1 + a1e 1 + a 2 e −b2twhere:K1 and K2 are the carrying capacity for the first and second waves respectively.a1 and b1 are coefficients for the first logistic functiona2 and b2 are coefficients for the second logistic function A spectrum of curves can be generated from Equation 3. We follow the Meyer’staxonomy of curves (see Meyer, 1994) as a reference to analyze the systems of production ofscience and technology. Figure 1 shows the four basic patterns of growth curves in bi-logisticfunction. L Llog( − 1) log( − 1) pt pt 99% 99% 1% 1% (a) Sequential (b) Superposed L Llog( − 1) log( − 1) pt pt 99% 99% 1% 1% (c) Converging (d) Diverging Figure 1: Taxonomy of the Bi-logistic Growth Function Source: Meyer (1994). 8
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th NovFollowing explains some characteristics of the linearized logistic growth curve shown in Figure1: • Sequential logistic occurs when the second logistic curve starts once the first logistic curve reaches almost the saturation. This bi-logistic pattern takes place when a declining rate of a routinized R&D of an economy is replaced or reorganized by another form of R&D structure/activities for continuous development (see Teubal 1996 and 1997). • Superposed logistic occurs when the second logistic curve starts to emerge when the first reaches about 20-50 percent of saturation. The witnessing of a continuous successive phenomenon, for example, scientific knowledge to science-based technologies (or when science co-evolves with technology) marks the dynamic of superposed pattern of bi- logistic growth curve (see Schmoch, 2007). • Converging logistic occurs when both logistic curves emerge at different period of time and culminate at about the same saturation. This pattern shows that the second logistic pulse has a higher but much faster growth time than the first pulse. The witnessing of extension of life-cycles in a development process marks the pattern of converging bi- logistic growth curve (see Watanabe et al., 2001). • Diverging logistic occurs when both logistic curves emerge at about the same time but grow at different rates with different level of carrying capacity. This pattern exhibits a strong evidence of self-propagating growth in the development of science and technology. The higher and longer pulse in the second logistic curve shows a successful development of an economy in developing new growth avenues for science and technology (Watanabe et al., 2006 and Wong and Goh, 2010c).2.3 Data SourceScientific resources and production play an important role in technological and knowledge-basedeconomic development (Schmoch, 1997). The term science is often defined as “the creation,discovery, verification, collation, reorganization and diffusion of knowledge about physical,biological/natural and social nature” (Kline and Rosenberg 1986, pp. 287). The term technologyis defined as an instrument of adaptation that includes the manufactured hardware or artifacts,skill and knowledge required to design, manufacture and use technology hardware and differentforms of organization. Forms of organization include institutional settings and rules for thegeneration of knowledge and for the use of technologies (Grupp, 1994, and Dosi et al., 2006).Technology can also refer to a collection of techniques. The term science and technology used in this paper denotes the basic and appliedresearch respectively. Publications are considered specifically as one of the main activities thatrepresents the scientific innovation11 for the analytical purpose. Publications (papers) that reporttheoretical works and research findings are the main channel for documentation anddissemination of scientific findings to further the development of science. Patents represent thecodified part of technological innovation12 that reflects the interest in commercial exploitation ofa new technology (Kondo, 1990, Grupp, 1994 and Kumaresan and Miyazaki, 1999). Accordingto Schmoch (1997) and Grupp (1998), patents as the most frequently adopted indicator for11 Scientific innovation denotes the increases in value of scientific knowledge.12 Technological innovation denotes the increases in value of technological knowledge. 9
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novtechnology provide measure to inventive and innovative activities that lead to new products orprocesses in the market. This paper attempts to elucidate the innovation system of selected Asian economies inshaping the growth trajectories of science and technology using bi-logistic growth function. Thedata used in this paper are the historical series of ISI publications from 1981 to 2005 (ISI, 2005)and utility patents granted from the US Patent Office and Trademarks (USPTO) from 1984 to2004 (USPTO, 2005) for selected Asian economies including China13, Taiwan, South Korea,Singapore and Malaysia. The ISI database covers world leading journals of science and the US’spatents cover useful information of technological activity14. This study assumes that the NIEsand the selected emerging countries in Asia have high tendency to patent theirinvention/innovation in the USPTO15, as US is the major export market for the selected countries(Bhattacharya, 2004 and Schmoch, 2009). In addition, using US patents data helps to preventhome bias16 effect that could be observed in many national patent office (Dachs et al., 2007). The years covered in this study is useful to reveal the context of two broad trends ofdevelopment which shape the evolution of innovation system for NIEs and the selecteddeveloping countries. The trends are the establishment of science and technology policy fordevelopment during 1980s and the continual growth of science and technological productionsince the 1990s. The ISI publications here refer to all fields of sciences, including natural,physical, health and social sciences. Patents are recorded by grant year that indicates whenmarket access of technologies was secured. The reasons for using these data are their availability,completeness for analysis, and comparability across different countries. The data provideuniform and time robust measures of science and technological innovation, which reflectimmediate market and knowledge-based economic development (Hu and Mathews, 2005).3. Analysis and ResultsThis section focuses on modeling the growth trajectories of science and technology, using thenumber of papers and patents as proxy. The bi-logistic growth function (Equation 3) is fitted.The results of the estimated growth trajectories for South Korea and Taiwan are firstly discussed.The subsequent sub-section discusses the results for the FDI leveraging countries, includingSingapore, Malaysia and China..3.1 South Korea and TaiwanFigure 2 and Figure 3 illustrate the number of papers and patents for South Korea and Taiwanrespectively. The figures provide the estimated total production of papers and patents (labeled asestimation), the estimated second logistic curve and the data (labeled as observation). Given theco-existing waves of evolution of papers and patents, the time when each wave emerges can be13 Data for Hong Kong is merged with the data for China.14 The document provides details of inventive and innovative activities (Bhattacharya, 2004).15 Utility patents data from USPTO can be an appropriate indicator for technological innovation (Hu and Mathews,2005).16 Many inventors apply for their patents at their home patent office. The national internal influence is highlyattributed to the competitive environment in the US market. Many Asian firms (local or MNCs) always seekprotection for their innovation to compete in the US market. 10
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novidentified. Each set of growth function models an evolution of a paradigm. South Korea andTaiwan have succeeded in developing new growth avenues over the period examined. In the midof 1990s witnessed the first logistic wave being over taken by the second logistic wave. Thesesignals hinted a transition from the emergence of science and technology to knowledge-drivenactivities. The science and technology experienced the paradigm shift from industrial toknowledge-based economy in the early 1990s, which subsequently witnessed the emergence ofthe second waves of papers and patents production toward the end of 1990s. The persistency ofsearch for new science and technological growth trajectory development would lead tosustainable growth in science and technology. The papers and patents of South Korea and Taiwan exhibit a diverging bi-logistic growthpattern. The second wave that dwells with significant efforts of knowledge-based economicdevelopment shows a longer and higher pulse than the first wave. South Korea and Taiwanregard papers and patents as a unique “capital” to generate value from the intangible assets (theknowledge). Many universities, research institutions and industrial firms (the science andtechnological systems) of these economies exploited these assets through aggressive application-oriented R&D activities. The trend corresponds to the argument of Foray (2006) that codificationof knowledge for the production and reproduction of science and technology is essential fortransformation towards a knowledge-based economy. The self-propagating behaviour of scienceand technology resulted from the significant efforts of the respective government to ensure thesuccessful development of the core sectors (such as biotechnology and information andcommunication technology) in a knowledge-based economy. The R&D activities and the successful development of these emerging sectors requirelearning by searching capabilities and necessary assimilation capacity in their science andtechnology system in order to benefit from the spillover effects of science and technology.Chaebol firms of South Korea were established to provide avenue for development of indigenousscience and technology capabilities. The role of universities public research institutions evolvedfrom training and preparing high of high-quality graduates and conducting basic and appliedresearch for the growth of national productive high-technology enterprises to commercializingtheir research outputs for the market (Sohn and Kelly, 2007). IPR system of South Korea wasestablished to facilitate administrative procedure and improve the quality and efficiency of patentexamination in the USPTO (Lee and Kim, 2010). Such conducive environment and efforts forknowledge-based economic development brought about a rapid increase in the number of papersand patents during the 1990s. The emerged of second wave can be attributed to the agile andcooperative structure of the national innovation system that successfully overcomes the inertia ofthe old paradigm (undertaking absorptive and adaptive technology development).For the case of Taiwan, the Industrial Technology Research Institute (ITRI) was established bythe government to support the technology development of electrical, electronics andsemiconductor SMIs. Taiwanese firms gradually moved to higher value-added products and wereinvolved in science-based technological R&D activities. The complementing environment andleveraging consortia structure of institutions for research resources, in which ITRI engaged inindustrial development and applied research, universities conduct basic research and industries 11
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov 50,000 45,000 1000 99% 100 (1) 40,000 10 (2) 1 35,000 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 0.1 30,000 0.01 0.001 1% 25,000 20,000 15,000 10,000 5,000 0 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17 19 21 23 25 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20 20 Year estimation second logistic curve observation (a) Papers 10,000 9,000 100000 10000 99% 1000 8,000 100 (1) 10 (2) 7,000 1 0.1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 0.01 6,000 0.001 1% 5,000 4,000 3,000 2,000 1,000 0 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20 22 24 26 28 30 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 estimation second logistic curve observation Year (b) Patents Figure 2: Papers and Patents of South Korea. The inset shows the linearlized both of logistic growth curves. 12
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov 50,000 45,000 1000 99% 40,000 100 35,000 10 (1) (2) 1 30,000 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 0.1 25,000 0.01 1% 20,000 15,000 10,000 5,000 0 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17 19 21 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 estimation second logistic curve observation Year (a) Papers 12,000 100000 99% 10,000 10000 1000 100 (1) 8,000 10 (2) 1 0.1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 6,000 0.01 1% 4,000 2,000 0 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 Year estimation second logistic curve observation (b) Patents Figure 3: Papers and Patents of Taiwan. The inset shows the linearlized both of logistic growth curves. 13
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novcommercialize R&D results, led to significant development in knowledge-based economy(Chang and Shih, 2004 and Phillips and Su, 2009). Since the success of ITRI17, many Taiwanesefrom abroad, particularly from the Silicon Valley, started their business and R&D activities inTaiwan (Lin, 2009 and Wu et al. 2010). In addition, the reduction of government interventionand involvement to allow the private sector to lead science and technology and market of ICs,electronics and semiconductor in 1993 brought about a subsequent boom in 2000. The self-propagating process dwells in the second wave of Taiwan is driven by a range of collectiveinstitutions that encourage investment and risk-taking in high-technology, conduciveenvironment (such as Hsinchu science park) in for science and technology activities and hugesupply of engineers and R&D scientists that would creates the demand-pull cycle.3.2 Singapore, Malaysia and ChinaFigure 4, 5 and 6 illustrate the case of Singapore, Malaysia and China. The transition from theindustrial-based to knowledge-driven activities witnessed the emergence of second waves in theproduction of papers and patents during the 1990s.The papers of Singapore exhibit a superposedbi-logistic growth pattern. Both curves culminate at about the same saturation. In the early 1990s,the Singapore government started to increase their investment in basic research activities topursue application pioneering strategy. This strategy accelerated the development oftechnological capabilities among the MNCs and local firms through the adoption of new andadvanced technologies in their manufacturing processes. However, such pursue has not led tomuch higher pulse in the second logistic curve. The increased of basic research activities onmanufacturing processes (to solve immediate manufacturing problems) of MNCs could tended tostray away from triggering self-propagating behaviour between science and technology. Thepatents of Singapore exhibit a converging cum diverging pattern of bi-logistic growth. Bothlogistic curves emerge at different rates with different level of carrying capacity. The second,larger logistic pulse has a higher and much faster growth time than the first pulse. Theexperience of Singapore provides an interesting contrast to the cases of South Korea and Taiwan.The Singapore science and technology policy had favoured the MNCs that seek to upgrade theirmanufacturing process capabilities to manufacture new and advanced products in Singapore(Amsden and Tschang, 2003). However, many MNCs (as the national productive high-technology enterprises) of Singapore may not have the interests of advancing applied researchactivities. Thus, since the 1990s, universities, research institutions and many selected state-owned enterprises were heavily funded by the state to strengthening the learning capabilities intechnology (applied research) and commercialize research outputs with high-technology spin-off.The efforts of advancing applied research activities witnessed significant growth in patents sincethe 1990s, it remains to be observed to what degree of successful development of theirtechnological innovation for knowledge-based economy. The papers of Malaysia exhibit a converging bi-logistic growth pattern. Both curvesculminate at about the same saturation. Both logistic curves emerge at different period of timeand culminate at about the same saturation. The efforts to develop basic research during thetransition to knowledge-based economy witnessed a significant increase in papers production.17 The establishment of Taiwan Semiconductor Manufacturing Company (TSMC) had induced many returnees fromabroad to start up their own Integrated Circuit (IC) design house and other high technology companies in HsinchuScience Park of Taiwan (Lin, 2009). 14
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov 21,000 100 99% 18,000 10 (1) (2) 1 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 15,000 0.1 0.01 1% 12,000 9,000 6,000 3,000 0 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017 2019 2021 2023 2025 2027 2029 2031 2033 2035 2037 2039 estimation second logistic curve observation Year (a) Papers 700 1.00E+07 99% 600 1.00E+06 (2) 1.00E+05 1.00E+04 (1) 500 1.00E+03 1.00E+02 1.00E+01 400 1.00E+00 1.00E-01 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 1% 300 1.00E-02 200 100 0 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 Year estimation second logistic curve observation (b) Patents Figure 4: Papers and Patents of Singapore. The inset shows the linearlized both of logistic growth curves. 15
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov 3000 1000 99% 2500 100 (1) 2000 10 (2) 1 1 5 9 13 17 21 25 29 33 37 41 45 49 1500 1% 0.1 1000 500 0 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 estimation second logistic curve observation (a) Papers 200 180 1000 99% 100 160 10 (2) (1) 140 1 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 120 0.1 100 0.01 1% 80 60 40 20 0 84 86 88 90 92 94 96 98 00 02 04 06 08 10 12 14 16 18 20 22 24 26 28 30 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 estimation second logistic curve observation (b) Patents Figure 5: Papers and Patents of Malaysia. The inset shows the linearlized both of logistic growth curves. 16
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov 600000 100000 99% 10000 500000 1000 (1) 100 (2) 10 400000 1 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 0.1 0.01 1% 300000 200000 100000 0 81 83 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17 19 21 23 25 27 29 19 19 19 19 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 estimation second logistic curve observation (a) Papers 6,000 10 99% 5,000 (2) 1 4,000 1 5 9 13 17 21 25 29 33 37 41 45 49 (1) 0.1 3,000 1% 0.01 2,000 1,000 0 84 87 90 93 96 99 02 05 08 11 14 17 20 23 26 29 32 19 19 19 19 19 19 20 20 20 20 20 20 20 20 20 20 20 estimation second logistic curve observation (b) Patents Figure 6: Papers and Patents of China. The inset shows the linearlized both of logistic growth curves. 17
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Nov Unlike the case of South Korea and Taiwan, the patents of Malaysia exhibit a divergingpattern of bi-logistic growth. The second logistic pulse has a higher pulse and much fastergrowth time than the first pulse. The efforts of advancing applied research activities have led toonly gradual increase of patents in the second wave of patents. We observe that the basicresearch activities were lacking in sense of purpose and highly fragmented from the productionstructure of technology (see Wong et al. 2010). This could be attributed to the rising“bureaucratic barriers” and lacking of “political will” the gradually developed within thetechnological and institutional foundation of society (see Felker, 2003, Ritchie, 2005 and Gomez,2009). The papers of China exhibit a diverging pattern of bi-logistic growth. Systematic reformof Chinese innovation system began since the mid of 1980s. Since then, China undertookreforms in their institutional structure to advance the horizontal linkages among national researchinstitutions18, universities and industries (Xue, 1997, Naughton and Seagal, 2003, Motohashi andYun, 2007, Hu and Mathews, 2008, and Zhao et al., 2009). The current economic growth ofChina has recorded positive effects on scientific activities. The combination of huge supply ofengineers and R&D scientists and technicians, strong basic R&D investment and the return ofqualified Chinese scientists from overseas contributed to the development of a knowledge-basedeconomy, and China had caught up with Singapore and South Korea in the production of science(Leydesdorff and Zhou, 2005 and Zhou and Leydesdorff , 2006). China has become one of theleading nations in terms of research output. The scientific system of China had progressed in anexponential rate (Leydesdorff and Zhou, 2005, and Kostoff et al. 2007). The patents of Chinaexhibit a diverging pattern of bi-logistic growth. The second wave could be dwells withsignificant supply-push efforts to develop science and technology capabilities shows a muchfaster pulse than the first wave. To move to high value-added technological production, thescience and technology policy was developed to encourage upgrading of manufacturing processcapabilities for the manufacturing of new and advanced products by the MNCs and localconglomerate firms. Many industrial-cluster science parks, high-technology infrastructures andresearch institutions were established to provide industries with the necessary support and suchefforts successfully induced industrial technological innovation and patenting activities. Closerexamination of the patenting data shows that most patents belong to multinationals of Taiwaneseand American origin. These foreign assigned multinationals’ patents comprise the major share oftotal Chinese patents in the US patent system. Many MNCs have taken the advantage of the localresources (in term of local talents and infrastructures) to build capabilities and appropriate thesepatents for their economic and technological gain. According to Naughton and Seagal (2003),there are many local-owned firms benefited from the spillover effects in these cluster and movedaway from cheap-labour manufacturing activities since the mid of 1990s. China has thenprogressively streamlining its institutions to subsidize learning to advance its locally ownproductive organizations (as national champions). There is a tendency for Chinese innovationsystem to be converging towards of its Korean or Taiwanese counterparts. Closer observation ofthe patenting data shows that that ratio of locally-owned organization is increasing with time.However, it can be observed that the production of patents for China is relatively lowercompared to South Korea and Taiwan, suggesting a gap to be caught-up. It appears that there areuntapped potentials of scientific resources (the increase of papers) for technology development18 Chinese government has gradually reduced their funding to research institutions’ operational costs, pushing themto acquire resources from industries (Xue, 1997). 18
  • Paper prepared for the 9th Globelics International Conference 2011 (Buenos Aires), 15th -17th Novdue to the nature of manufacturing activities and technological competencies of the MNCs19 andlocal firms in China.4. ConclusionThe findings of this paper have expanded the research on innovation system in characterizingscience and technological trajectories in emerging Asian economies. In order to achieve theobjectives of research, this study first constructed a conceptual framework to analyze thetrajectories of science and technology. The framework of analysis in this study is adoptedextensively from the Wong’s theoretical perspective (see Wong, 1999) on national innovationsystem and Meyer’s taxonomy (see Meyer, 1994) of bi-logistic growth function. Bi-logisticgrowth function is found useful and effective in highlighting the path of science andtechnological evolution underlying its catch-up industrialization model. The use of bi-logisticgrowth function to explain the national innovation system in particular and the changing level ofscience and technology is a relatively new effort in the literature. For the case of South Korea and Taiwan, the economies that learn and acquiretechnologies through mechanisms other than FDI, the evidence suggests a sign of transition fromindustrial-based to knowledge-driven activities and the formation of evolving dynamicpropagating behaviour in science and technology. Their second wave of bi-logistic curve thatdwells with significant efforts of knowledge-based economic development shows a longer andhigher pulse than the first wave. On contrary, the pursued to develop science and technology by the FDI-leveragingcountries such as Singapore and Malaysia has not led to much longer and higher pulse in thesecond logistic curve. Based on these two distictive governing approaches, this study highlightsthe generic evolutionary paths that may be useful as policy lessons, particularly for thedeveloping economies. The findings indicate that institutional dynamics of chaebol conglomerateapproach of South Korea and SMI-state network approach of Taiwan are important to drive theself-propagating behaviour particularly in the second wave of bi-logistic curve. AlthoughSingapore, Malaysia and some provinces of China deliberately directed FDI towards selectedpriority high-technology sectors to develop some indigenous science and technology capabilities,the production of papers and patents witnessed an interesting contrast to the cases of SouthKorea and Taiwan. This could be largely attributed to the nature of manufacturing-basedactivities and technological competencies of the MNCs in these economies. Recently, there aresignificant efforts by the state of these economies to strengthen the learning capabilities intechnology. Many universities, research institutions, selected state-owned enterprises and (local-owned) private conglomerate firms were heavily supported to advance applied research activities.Given the efforts in establishing their collective institutions for science and technologyproduction, it is expected that the following pulse (the “third wave”) of the logistic curve and thepotential (carrying capacity) for science and technology development will increase.19 The inertia of MNCs-focused export-oriented economy built over the years could be a hindering factor for theeconomy to leap-frog into a knowledge based economy. 19
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