Local government policies and pharmaceutical

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Local government policies and pharmaceutical clusters in China

Local government policies

Yuanyuan Yu, Zhiqiao Ma, Hao Hu and Yitao Wang State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China

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Received 20 February 2013 Revised 7 November 2013 19 December 2013 Purpose – The purpose of this paper is to study how local government policy influences the structure Accepted 29 December 2013

Abstract

of Chinese pharmaceutical clusters during their industrial catch-up. Design/methodology/approach – This paper applies a case study method by targeting pharmaceutical clusters in Tonghua, Taizhou, and Tianjin. Findings – The varied structures of pharmaceutical clusters in China demonstrate local governments’ efforts to utilize local resources accordingly. While the local governments in China introduce different policies to firms with different ownership in the process of constructing different cluster composition, all the local governments emphasize motivating the development of small- and middle-sized enterprises for cluster dynamics. Practical implications – The local governments should try to reach a balance between short-term foundation and long-term competitiveness for industrial cluster development. Originality/value – This paper provides the detailed analysis of local governments’ influences on the formation of pharmaceutical clusters in China and helps to enrich the knowledge about how local government promotes industrial clusters to realize industrial catch-up through sectoral innovation system. Keywords Industrial cluster, Cluster structure, Pharmaceutical industry, Local policy, China Paper type Research paper

Introduction The compound annual growth rate of the Chinese pharmaceutical market reached 16.46 percent between 2001 and 2011, the fastest rate globally. In 2011, the output value of the Chinese pharmaceutical industry realized 15,025.09 billion RMB. With such rapid growth, China’s ranking in the global pharmaceutical market jumped from tenth in 2003 to fifth in 2008. In 2006, IMS Health coined the word “pharmerging” to define some rapidly-growing pharmaceutical markets that would influence the future of the global pharmaceutical industry, and China was considered to be one of these markets. In March 2010, IMS redefined 17 countries as “pharmerging” and classified them into three classes according to current and potential market size, among which China is exclusively the largest. IMS Health predicted that in 2013 China would become the world’s third-largest pharmaceutical market. With a gross domestic product (GDP) of more than 8 trillion USD, it is predicted that drug sales in China during 2008-2013 would increase by more than 400 billion USD, equivalent to the predictive value of sales growth in the US pharmaceutical market within the same period (Gertler and Levitte, 2005). Therefore, the pharmaceutical industry in China in the twenty-first century is widely regarded to be a sunrise industry. The development of the pharmaceutical This study is supported by the research funding of University of Macau (MYRG160 (Y1-L2)-ICMS11-HH).

Journal of Science & Technology Policy Management Vol. 5 No. 1, 2014 pp. 41-58 q Emerald Group Publishing Limited 2053-4620 DOI 10.1108/JSTPM-02-2013-0004

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industry in China has begun to emerge with the characteristics of regionalization, large-scale and centralization. After joining the WTO, China’s pharmaceutical industry was forced to accelerate its development in order to deal with the fierce competition of the market, especially facing the entry of multinational pharmas. As industrial cluster is especially important for the development of high-tech industries with systematic complexity, it is natural that the development of pharmaceutical industrial clusters is highly encouraged by the policy makers in China. The pharmaceutical industry is complex, involving varied strands of science and technology, and thus it is difficult to break through the creation bottleneck by only developing isolated technologies (Chan and Daim, 2011). It is a typical knowledge-intensive industry, with the characteristics of high risk and high investment through the process of innovation, producing, and commercialization (Prevezer, 2008). In order to improve the efficiency of innovation and break through the growth limit, the industrial cluster model – with the feature of division and cooperation between near geo-space enterprises – is regarded as an efficient means to enhance the drug innovation capability and promote the development of the regional economy (Gertler and Levitte, 2005). For example, the pharmaceutical industry clusters in Boston, San Francisco Bay, Washington and San Diego, have become not only the backbone of local economy, but also the driver of innovation and industrialization of bioscience in the USA (Walcott, 2002). Leading enterprises in these clusters established cooperative relationships with new companies; thus, new small technology companies could develop rapidly and become large- and medium-sized enterprises or be merged with large enterprises. This virtuous cycle promoted the development of industrial clusters, and the effects of investment and the efficiency of research were greatly enhanced. Another good example is BioRiver – a pharmaceutical cluster in Nordrhein-Westfalen. It provided a valuable platform for enterprises in the region, furnished great circumstances for new enterprises, optimized the structure of pharmaceutical industry, and promoted development (Krauss and Stahlecker, 2001). Since 1996, the pharmaceutical industry in China has been developing rapidly in terms of production scope and scale. Nevertheless, it was just one type of progression to commercialization of imitation drugs, and basic research was seriously lacking. There were few new drugs and investment in innovative R&D was rare. The competitiveness of the Chinese pharmaceutical industry is extremely underdeveloped in comparison with the USA and Japan (Wang et al., 2009). The Chinese Government hopes to convert the industry from simple pharmaceutical production to pharmaceutical innovation (Prevezer, 2008), and therefore wants to improve the competitiveness of the pharmaceutical industry in order to realize industrial catch-up through establishing industrial clusters. While the central government of China has carried out a series of policies to promote the development of a pharmaceutical cluster, local governments also have their own policies for consideration of their own interests as well as the local resources and the environment, to further promote the development of local pharmaceutical industry clusters (Conle´ and Taube, 2010). Some academics even consider local government as one of the most important influencing factors for emergence and development of industrial clusters in China (Qiu and Xu, 2004; Zhu, 2004). While the significant impact of local government is generally recognized, research on how local government influenced the pharmaceutical clusters in China remains less addressed. Therefore, this paper aims to:

.

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investigate the structural design of the main pharmaceutical clusters in China; and study the effect of local government policies on pharmaceutical cluster design.

This paper provides a detailed analysis of local governments’ influence on the formation of pharmaceutical clusters in China and helps to enrich the knowledge about how local government promotes industrial clusters to realize industrial catch-up within a national and international context. This study applies the framework of sectoral innovation system to analyze the cluster structure and policy design of the pharmaceutical clusters. The research focuses on three clusters located in three different regions in China. We concentrate on the relationships among different types of firms, and the affection of institution to the firms, especially the local government policy. We discuss the ways that different polices affect the innovation capability of clusters through different types of firms, and the complementarity role of government in enhancing the relations of firms inside and outside industrial clusters. In order to observe the relations and interactions more clearly, we divide the innovation actors into four types according to their properties and analyze the influence of policy. The data in this study consists of materials from multiple sources. It includes policy documents regarding the pharmaceutical industry by Chinese Central Government from 1949 until now, policy documents of the pharmaceutical clusters studied, official websites of the studied development zones and industrial parks, and academic papers relating to Chinese pharmaceutical clusters. In addition, it also includes materials from interviews with firm leaders and university researchers in the studied clusters, and government officials in charge of the clusters. All the materials were combined and analyzed through single clarification and cross comparison. Theoretical framework Sectoral innovation system and cluster As research of industry was concerned more and more about the improvement of innovation capability, and the simple analytical framework did not to fully explain the innovation process of industry (Carlsson and Stankiewicz, 1991; Oltra and Saint, 2009), Franco Malerba proposed the conception of a sectoral innovation system. This is a framework used to study the interaction mechanism of the technology, organization and institution which occurred in the process of innovation from the perspective of the sectoral system (Malerba, 2002), which consists of three parts: knowledge base, actor and networks, and institutions. Different sectors have different knowledge bases. The field of knowledge refers to the specific science and technology of a sectoral innovation activity. The actors contain enterprises and non-business organizations. Enterprises are the principal instigators of innovation, involved in the whole process such as production, sale, and application of new technology. The non-business organizations, such as universities and research institutions, support the innovation and technology diffusion in different ways, and promote the integration and complementarity of knowledge, skill, and specialization (Schmitz, 2006). These actors interact through various methods of cooperation, competition, exchange, and communication (Malerba, 2002), which form the network of the sectoral innovation system. The institutions, which include laws, rules, standards,

Local government policies 43

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customs, and routines, constrain actors’ behavior and affect the relations and interactions between actors (Edquist, 2005). Porter (1990) proposes that the cluster is a group mainly formed by the enterprises of a particular area, which are interactively correlated, compete and cooperate with each other, and are concentrated geographically. The core meaning of cluster in this sense is the high concentration of industry in a certain range of space, which is helpful to reduce the cost, and improve the economic efficiency and competitiveness of enterprises. The cluster is usually associated with a certain industry. It consists of some associated organizations such as enterprises, financial institutions, and chambers of commerce. In fact, the cluster can be seen as the main body of the sectoral innovation system, and the model of sectoral innovation system can be an analysis framework for cluster. It can help to analyze the relationship among actors, find out the innovation mechanism in a sector, and the way of policy tool to promote the development of industry. The enterprises of a cluster are usually interconnected with each other by the significant industrial characteristics. The organizations in clusters can be seen as the actors in the sectoral innovation system. And the networks of the sectoral innovation system can be reflected by the structure of cluster. In the sectoral innovation system, government policy is an important institution that can influence the innovation process and the networks of actors (Patana et al., 2013). Cluster structure as policy design The formation, development and renewal of industrial clusters have received considerable attention during the past decades. In most of the relevant literature, clusters are hailed as a universal panacea for local and regional development (Yeung et al., 2006). With rising attention on industrial clusters, scholars have noticed the structural differences. Using measures of types and scale of enterprises, structure of industry chain, actors network, interdistrict mobility of labor, state role, and capital sources in district formation and character, Markusen (1996) proposed four types of industrial districts: Marshallian and Italianate industrial districts, hub-and-spoke districts, satellite industrial platforms, and state-centered districts (Markusen, 1996). Marshallian and Italianate industrial districts is the widely acknowledged cluster mode that has been discussed in literature (Brusco, 1982). The characteristics of Marshallian structure are defined as intensive networks of trade and cooperation among many small, locally owned firms that make key investment decisions locally, scale economies are relatively low and strong innovative tendencies depending on the trade networks and local government investment (Coe, 2001; Markusen, 1996). In addition, Gordon and McCann (2000) also suggested a classification model of industrial clusters: a classic model of pure agglomeration; an industrial complex model; and a social network model. All of these imply the realities of structural variation among industrial clusters. Furthermore, the spatial, institutional, and network of cluster development have been deeply differentiated by globalization today (Phelps, 2004), which results in a more complex structure of industrial clusters. Additionally, different types of structures of industrial clusters may co-exist and overlap in the same agglomeration as “sticky mixes”, and the structure of a cluster can also transform over time (Coe, 2001). For example, a new hybrid of cluster is found in Vancouver’s film industry, which is named as a “satellite-Marshallian type”, sharing features between the satellite platform type and the Marshallian type (Coe, 2001). The nature of Suzhou Industrial Park

in China is largely that of a satellite platform type and is forecast to be likely a satellite neo-Marshallian type in the future (Wei et al., 2009). As more and more industrial clusters are established and developed around the world, the competition among them is becoming increasingly fierce, which leads to rising attention on the structure of the industrial cluster. This is regarded as an important factor to improve the particular cluster’s innovation capacity and distinguish its competitiveness from others (Cao et al., 2008; Dayasindhu, 2002). Under different resource endowments, a suitable structure can make resource allocation more reasonable and efficient among all actors of a cluster. Raw materials, information, and infrastructures can be commonly shared with high efficiency, which then improves productivity and innovation efficiency of these actors (Niu et al., 2008). At the same time, the embeddedness of the cluster structure, which focuses on the role of social relations and the structures of these relations, is another key factor for innovation performance and can lead to the creation of cluster knowledge by forming a dense innovation network beyond only economic relations (Casper, 2007; Dayasindhu, 2002). Because of the significant importance of the cluster structure, how to design appropriate government policy to construct a specific cluster structure becomes a crucial concern (Prevezer, 2008). Research has indicated that cluster structure is not only influenced greatly by location, resource, industrial base, and specialization but also by public policy (Rosenfeld, 2005). Lundequist and Power (2002) discuss the usefulness of policy tools in the cluster building process and summarize some common elements shared by successful clusters. Gordon and McCann (2000) studied clusters in London and found that policy action affected the distinction between clusters and the contrasts in policy implications were important features of different clusters. Local government policy and industrial cluster While realizing the importance of policy in cluster formulation and development, researchers also draw attention to the impact of different national and local government policies. Because of their different powers, local governments and central government have a clear division of policy function. Policy implemented by central government is carried out throughout the country. Because of the different regional economies, cultures, and resource endowments, the effects of central government policies are different. Local government policy is formulated based on the specific circumstances of the region. It is more targeted and is the individual development and complementarities of central government policy. While national policy usual can determine the distribution and competitiveness of the whole industry, local government policy plays a more important role in an individual cluster’s structure formation and development (Goodwin and Painter, 1996). For many local governments, various policies are carried out for different kinds of companies in the cluster, which can influence the formation of a cluster structure by supporting or neglecting some types of companies (Su and Hung, 2009). The literature also looks at how local government should contribute to industrial clusters. Whether local government should get itself actively involved in cluster development, is controversial. Cooke (2001) believed that local government was helpful in developing clusters. In particular, policies should be introduced that stimulate the growth of private investment to motivate investment institutions to step into the development of industrial clusters. Su and Hung (2009) compared two clusters and


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found social capital and accompanying networks were the main factors that shaped a cluster’s configuration, which depended heavily on policy promotion. On the contrary, some scholars do not think that it is wise for local government to involve itself in cluster development. Comparing China and the USA had identified deficiencies of policy, such as difficulty in shifting away from government-led responsiveness to funding programs, problems in promoting cooperation between domestic science and firms, and defect of policies aiming at returnees or financing support to small and medium-sized enterprises (SMEs) (Prevezer, 2008). According to the role of institutions in the formation of clusters, the model of influence of government to the cluster can be divided into two types: bottom-up and top-down (Wang and Dong, 2005). The bottom-up model is demand-induced. It means the cluster has already enjoyed certain advantages, such as favorable natural conditions, and sorts of enterprises. The government must only provide policies to help or guide the formation of the cluster. The top-down model means the cluster is created by the government, who plans and decides its development strategy. As mentioned before, clusters with different structures have different innovation drivers (Fujita, 2012). Therefore, one core question involves designing local policy specific to firms with different ownership in clusters. There are many different firms in a cluster, such as multinational companies (MNCs), SMEs, large private enterprises, and state-owned enterprises (SOEs). In a cluster, MNCs often showed significant effect of agglomeration, including intra-company and inter-company concentration, accumulation of countries of origin, as well as cross-functional copolymer (Defever, 2006). Through geographic concentration and radiation function, the branches of MNCs could strengthen the leadership and industrial clustering ability of a region; the separated value chain could generate the vertical contact, which would promote the collaboration among cities (Ma and Delios, 2009). SMEs also play an important part in clusters. SMEs could transform R&D achievements of universities and research institutions into products more efficiently, and at the same time transfer market demand information to research institutions. In China, private enterprises have become an important part in the development of industry. Large private enterprises have flexible, strong profitability, and high degree of internationalization (Zhao and Xiang, 2010). In a cluster, they can easily play the leading role because of their emphasis on the integration with SMEs, and their professional development strategy. But they can be severely influenced by the external environment, such as the economic restructuring, financial crisis, national or local policies. SOEs is are also important for clusters. If the formation of industrial clusters came from the original structure of the planning economy, then SOEs would be the basic part of the cluster (Wang and Yang, 2010). The obvious advantages of SOEs are occupations of valuable resources, such as human resources, capital, government support, information resources, and so on. But their utilization of resources is relatively inefficient and their reaction to information is also slower than SMEs. Sometimes SOEs play a leading role in clusters through sharing resources with SMEs, in order to implement a diversification strategy (Li, 2009). For clusters, the role of government is to guide the rational and orderly development of industrial clusters, to create a good external environment conducive to innovation, and to prevent the degradation of industrial clusters towards recession. In China, local government plays significant roles in deciding local policy for MNCs, SOEs, large private enterprises, and SMEs. As indicated by Luo (2001), the relationship between MNCs

and local government is established on the foundation of “resource complementarity, organizational credibility, political accommodation, and personal relations”. MNCs tend to invest in the region with good infrastructure facilities, strong scientific research strength, and great technical market potential. As the R&D centers of MNCs are engaged in continuous technological innovation activities, their requirements for intellectual property protection are especially strong (Jiang and Lu, 2006). These quests are difficult to complete via the market alone, and support from local government is necessary. Therefore, the formulation of local policies could largely affect the location choice of MNCs (He and Xiao, 2011). The development of SMEs – as one type of vulnerable group in the market competition – usually requires government intervention. For example, China’s local governments often support SMEs through preferential treatment in tax relief and bank loans, and drive the innovation of SMEs by formulating science and technology plans. The influence of government on large private enterprises is mainly reflected by the specific long-term planning for the area, effective supervision of financial systems, and the monitoring mechanism of government officials. While SOEs enjoy rich resources, they mostly lack innovative capabilities and their resource utilization is low. In order to avoid resource waste, local government has to display its capabilities of resource scheduling and consolidation (Dong, 2007). And through industrial planning, government procurement, major projects construction, it also helps SOEs to clarify their innovation directions and to transform their innovation results quickly into new products and service. Pharmaceutical clusters in China The pharmaceutical industry can be seen as a sectoral innovation system because its innovation involves many actors, such as firms, research organizations, financial institutions, government authorities, and consumers. And its innovation network consists of relations among actors, and other features that can influence the actors’ behavior or the development of technology. In the past few decades, with the transition of the economy and medical systems in China, the pharmaceutical industry experienced a high-speed growth and development (Wang et al., 2009). However, due to various development routes, resource dependences, and historical reasons, the distributions of the pharmaceutical industry in China shows obvious regional characteristics. The distribution of resource endowment mostly laid an influential foundation for Chinese pharmaceutical clusters’ formation and development (Conle´ and Taube, 2010). At present, there are around 20 relatively mature pharmaceutical clusters in China. Because the development of the traditional Chinese medicine (TCM) industry is much more mature than the other pharmaceutical industries in China, the clusters that are comprised of many TCM enterprises were formed first. They are mainly located at the regions where there are abundant Chinese herb resources, such as the Changbai Mountain region and Sichuan Province. The clusters with manufacturing enterprises of chemical drugs are mostly formed in Jiangsu and Zhejiang Province, which are famous for abundant chemical raw materials and manufacturing capacities. During the formation of clusters, the changes of organizations and networks are also obvious through merger and acquisition processes and collaboration. In addition to the resource endowment, the government of China played a very important role in the formation, development and distribution of pharmaceutical clusters. And the policies are important institutions that influence the action of


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innovation actors and the interaction among them. In particular, the Chinese state wants to implement a rapid catch-up for the pharmaceutical industry. Biopharmaceuticals has been confirmed as the top priority in China’s medium-to-long-term plan, including the 11th five-year plan for high-tech industry development and the 12th five-year plan for biotechnology industry development (Conle´ and Taube, 2010; Wang et al., 2009). Under the guidance of the “National Torch Program” and other state policies, China has experienced an interesting phenomenon known as “development zone fever”, and many pharmaceutical industry parks and bases in the Economy and Technology Development Zones are built around the country, most of which claim to focus on modern medicine such as biopharmaceutical industry (Yeung et al., 2006). At present, there are 23 national biotech industry bases, and more than 50 biopharmaceutical industry parks have been established. Based on these industry parks and bases, many pharmaceutical clusters focusing on modern biotechnology have emerged. These clusters are mostly concentrated in coastal areas and some large cities. However, the policies of local government are different among regions, which may affect actors differently. To investigate the impact of local government’s policy on pharmaceutical clusters, a detailed case study focusing on representative clusters is more appropriate than whole coverage of all the pharmaceutical clusters in China. In order to get a comprehensive understanding of the Chinese pharmaceutical clusters, a series of dimensions according to the theory of sectoral innovation system are applied to identity the target clusters for this study, including types and scale of enterprises, structure of industry chain, actors network, role of the state and capital sources. With these dimensions, the influential pharmaceutical clusters in China were studied and compared, first according to second-hand material and data; second, suggestions from key government officials and industrial opinion leaders were consulted to confirm the selection of pharmaceutical clusters further. Lastly, the pharmaceutical clusters in Tonghua, Taizhou and Tianjin cities were selected in order to analyze their cluster structures and local government policies for their formation and development. Structural analysis of three clusters These three clusters represent the general structure features of three types of pharmaceutical clusters in China. The economic and structural information of three clusters are summarized in Table I. The structure of the pharmaceutical cluster in Tonghua The Tonghua cluster is located at the Changbai Mountain region in the south-eastern Jilin Province. It has been selected as the Chinese Herbal Medicine Demonstration Base under the “National Torch Program”, the National Biological Industry Base, and one of the first batch National Biopharmaceutical Industry Bases for export innovation. Until 2011, there were about 95 pharmaceutical enterprises in the cluster, but most of them are private SMEs and no leading firm has emerged. Most of these enterprises concentrate on TCM, including the plant of Chinese herbals, R&D, manufacturing, and sales. The Tonghua cluster has a large amount of plant bases for Chinese herbals, all of which have the good agriculture practices (GAP) certification, such as Xingkaihe ginseng and fritillary bulb planting bases. In addition, the cluster also has 26 R&D institutions and 34 medical wholesale enterprises. The pharmaceutical enterprises in the cluster cover almost the whole industrial chain of TCM. The enterprises can meet

Tonghua

Taizhou

Tianjin

Number of firms Main firm type

95 SOEs, SMEs

87 Four leading large private enterprises SMEs

Industry chain

Herb planting Manufacturing R&D Sales Strong

R&D Manufacturing Sales

284 75 foreign invested enterprises SOEs SMEs R&D Manufacturing

Strong

Weak

Low Marshallian model

High Hub-and-spoke model

High Satellite platform model

Internal networking Scale economic Cluster structure

most of their supply demands by exchange with other enterprises within the cluster, particularly for the supply demand of Chinese herbals. Only some chemical raw materials are needed from outside of the cluster. There is a strong networking among enterprises within the cluster, from herb planting, processing, to manufacture. Now even more and more manufacturing enterprises have started to plant Chinese herbals by themselves. Because the production technology of TCM is relatively simple, the product portfolios of many manufacturing enterprises within the cluster are quite similar. Among these enterprises, there are fierce competitors and low cooperation. The products of these pharmaceutical enterprises are mostly sold to pharmaceutical companies outside. Then the pharmaceutical enterprises in the Tonghua cluster invested greatly to build networks with many sales companies outside. The structure of the pharmaceutical cluster in Taizhou The Taizhou cluster is located in the middle of Jiangsu Province. As one of the center cities of Yangtze River Delta Economy Zone, the Taizhou city has set up the first national medicine high-tech zone in China. It has the biggest anesthetics and vitamin manufacture bases. At present there are 87 pharmaceutical enterprises, including drugs manufacturing, drugs wholesales, and chemical raw materials manufacturing. Among these enterprises, the sales of the Yangtze River Pharmaceutical Group, the Jichuan Pharmaceutical Company, the Jiangshan Pharmaceutical Company, and the Suzhong Pharmaceutical Company account for 85 percent of the sales of the whole Taizhou cluster. The Yangtze River Pharmaceutical Group is one of the biggest pharmaceutical enterprises in China, which functions as leading company in the cluster. In addition to these big domestic pharmaceutical enterprises, the cluster also has many private SMEs that carry out specialized production and provide a series related services. These SMEs have formed strong networks with core firms such as the Yantze River Pharmaceutical Group. Because of the existence of these SMEs, local suppliers can meet most of core pharmaceutical enterprises’ demands. The core companies do not have any motivation to connect with suppliers outside. But these core firms build mature networks with many sales companies around the country to sell their products. Some of their products are even sold to the international market.


Table I. Structure of three pharmaceutical clusters

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The structure of the pharmaceutical cluster in Tianjin The Tianjin cluster is located in the Tianjin Economic-Technological Development Area (TEDA). As one of the first batch National High Economic-Technological Development Areas which were approved by the State Council, TEDA is located at Bohai Coastal region, which has a perfect development environment for foreign and export-oriented industries and commerce. The pharmaceutical industry is one of the nine important industries in TEDA. Until 2009 there were 284 pharmaceutical-related enterprises. Most of these concentrate on manufacturing, and only 19 enterprises focus on related services. Among these enterprises, there are 75 big foreign invested enterprises, which are the core of innovation and play the leading role for the pharmaceutical cluster in TEDA. At the same time, there are many private SMEs around these foreign enterprises to provide specific services. A few big domestic pharmaceutical enterprises also existed in this cluster, but compared with the foreign invested enterprises as branches of MNCs, their contribution is still small. Except for keeping a few connections with some SMEs that provide services, the foreign invested enterprises mainly connect with their parent companies overseas to get innovation information and manufacturing resource. But their target market is also located in China. Analysis of local government policies During the formation and development of the pharmaceutical industry clusters, the roles of local governments are different among clusters. In order to support the development of local pharmaceutical clusters, local government introduced a series of policies specific to its own resource endowments and cluster objectives. The analysis of three clusters from the perspective of sectoral innovation system is summarized in Figure 1. Local policy for the pharmaceutical cluster in Tonghua The formation of the Tonghua cluster was spontaneous. Because of the abundant Chinese medicinal materials in the Changbai Mountains, many state-owned TCM firms grew in the late 1980s, which attracted more private enterprises to move into this region. With the continuous concentration of enterprises, the demand for industrial resources is increased and market capacity becomes insufficient. The cluster has further requests for infrastructure construction, investment, and financing environment, which is difficult for private SMEs to obtain by themselves. In this case, the Tonghua government plays the role of “night watchman”. It provides the bottom-up model support to the cluster. But the policies are different according to different enterprises. The government involves in the system reform of SOEs directly activating the capital through enterprise reorganization. This measure is helpful to the market allocation of resource. To SMEs, the government provides policy support instead of direct management. First, it helps to adjust the allocation of resources, especially financial flows. It helped SMEs to get bank loans by functioning as a loan guarantor, which makes up the shortage of R&D and manufacturing funding for most SMEs in the cluster. Second, the local government provides proactive fiscal policy. It formulated several policies such as tax preference, land-use preferences, and administrative fee abatement for the SMEs moving into the cluster. Third, it takes efforts to create a favorable market environment. It established pharmaceutical industry association to coordinate and strengthen market supervision. In general, the Tonghua Government plays an indirect role in the formation process of the pharmaceutical cluster. Its main policy target is SMEs emerging from

Networks

Innovation actors

Local government policies

Institutions (Policy)

Policy design

Formation

Development

51

Shareholding reform

State-owned enterprises

Market allocation of resource Loan guarantee

Marshallian model (Tonghua) Small and middle-sized enterprises

Bottom-up

Bottom-up

Top-down

Bottom-up

Top-down

Top-down

Reduce administrative expense Reduce tax Allow the local stock issue Innovation subsidies

Hub-and-spoke model (Taizhou)

Large private enterprises

Increase credit support Encourage integration Attract state research projects Set up exchange service center

Satellite platform model (Tianjin)

Multinational companies

Purchase large scientific research equipment Foreign investment drawback

the cluster internally. The establishment of the cluster depends mainly on enterprises themselves. The policy efforts of local government is mainly about mobilizing the vitality of the cluster, increasing internal dynamics of cluster, and creating a healthy and positive market environment, all of which promote the interactions of innovation actors in Tonghua cluster. Local policy for pharmaceutical cluster in Taizhou While the pharmaceutical industry cluster in Taizhou started from four large private enterprises, its formation also depends heavily on the promotion of local government.

Figure 1. Analysis of three clusters

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In order to make full use of the industrial base, the local government of Taizhou integrated these core companies and local SMEs initiatively to apply for establishing the international pharmaceutical high-tech zone. It also drove the cooperation and connection between SMEs and four core companies to improve the structural dynamics of the cluster. Moreover, the local government led the core enterprises to cooperate actively with advanced research institutions and even invested directly into some research program to improve pharmaceutical innovation. The formation of the pharmaceutical industry cluster in Taizhou is a result of local government promotion. The government played an important role in enhancing the networks between different types of actors. It supplemented the cap between SMEs and large private enterprises and made the cooperation easier. However, after the preliminary founding of the cluster, the local government did not intervene in designing the development strategy of the cluster and returned instead to the role of “night watchman”. It carried out a series of proactive fiscal policies and established the financial platform to assist the future cooperation in the cluster. Consequently, the structure of the Taizhou cluster can be regarded as a result of both government promotion and market driven. Local policy for pharmaceutical cluster in Tianjin Different from the other two clusters, the pharmaceutical cluster in Tianjin mainly depends on local government planning. According to its own resource characteristics and macro policy demand, the Tianjin Government guided the generation of this particular cluster through a top-down model. With superior policy environment, rich clinical research status, and sufficient human resources, the Tianjin Government led the whole construction and development of the pharmaceutical cluster. It formulated a series of preferential policies to attract investment of MNCs. It provided many benefits to attract MNCs, such as tax relief, land-use concession, investment tax rebate, etc. It also helps local enterprises to get financial investment from overseas biopharmaceutical companies. Moreover, it provides direct help to SMEs, such as setting up special financial support and subsidizing SMEs to buy large scientific equipment to pave the way for early drug discovery and development. In a word, the formation and development of pharmaceutical cluster in Tianjin is mostly a result of local government efforts. The government plans and guides the cluster development strategy and provides direct support from capital to technology. The structure of the cluster in Tianjin also depends on the policy preference, particularly its preference to attracting MNCs. Discussion and conclusion By comparing the three pharmaceutical clusters, significant structural variations can be identified. Many structural characteristics of the Tonghua cluster are very similar to the Marshallian structure defined by Markusen (1996). The innovation actors in Tonghua cluster are many private SMEs that focus on TCM. The exchange among cluster enterprises is frequent and close. As most raw materials, business services and technology support are available within the cluster, these enterprises make most investment decisions locally, and there is low degree of cooperation with other enterprises outside the cluster. The scale economy of Tonghua cluster is relatively low but its internal dynamics provide much motivation and benefits to every enterprises within the cluster as described in the literature (Knorringa and Meyer-Stamer, 1998; Markusen, 1996).

The structural characteristics of the Taizhou cluster are more like the “hub-and-spoke district” which is mentioned in the literature (Markusen, 1996). The four large private enterprises are the main actors of drugs and new manufacturing technologies innovation in the cluster. They act as the hubs or anchors to the cluster’s economy. Many SMEs around these core enterprises are responsible for related activities and supplies for chemical raw materials and services. These SMEs depend upon the core enterprises’ activities and play a role of spokes of a wheel. The dynamism of Taizhou cluster mainly depends on the domestic and international market performance of these four large private enterprises. The network between SMEs and core enterprises in the cluster is strong. Besides many SMEs in the cluster, these core enterprises also keep substantial links with some suppliers and competitors outside of the cluster. Thus, they have close cooperation and connections with other enterprises both locally and externally. Under the strong network, the Taizhou cluster has relatively high level of scale economy. The pharmaceutical cluster in Tianjin has a lot of large foreign invested enterprises that are owned and headquartered externally, which dominate the innovation capacity and business structure of the Tianjin cluster. These foreign invested enterprises have no long-term connections and commitments with enterprises locally. On the contrary, they maintain a connection with their parent companies outside of the cluster. Their parent companies are the biggest suppliers and provide innovation, human resources, and information networks to their branch companies. They also help the branch companies make many key investment decisions externally. The structural characteristics of the Tianjin cluster has many similarities with the “satellite platform” structure defined by Markusen (1996), while there are still some differences. In addition to many foreign invested enterprises, local SMEs are also important parts of the Tianjin cluster. The development of these SMEs mostly depends on the innovation resources spilling from the foreign investment enterprises or other research institutions in the Tianjin cluster. But the cooperation network between these two kinds of enterprises is still weak. The pharmaceutical industry system is so complex that a single cluster structure design cannot meet the development demands completely. The clusters with different resources and developed routes should have corresponding characteristics of cluster structure. As mentioned before, the interaction among actors in clusters is an important factor for improving clusters’ competitiveness. The similar “Marshallian” structure, in which the innovation actors have strong interactions, contributes to the competitiveness of the pharmaceutical industry in Tonghua by making efficient use of the abundant local Chinese herb resources. The Taizhou cluster utilizes its pharmaceutical industrial base and gives full space to its core pharmaceutical enterprises’ advantages by “hub-and-spoke” cluster structure design. The Tianjin cluster has a good satellite platform structure for many foreign enterprises to attract capital and increase innovation capacity and competitiveness of its pharmaceutical industry. The interaction in different structural clusters is varied. And the difference depends on the nature of firms in the cluster and the cluster structure. In the cluster that consists of similar firms, such as in Tonghua, the network of actors is strong and the interaction is active. But its network with the outside is weak, because most of these firms are SMEs. In the cluster, which consists of different types of firms, the network among actors is weak but the relations with outside are stronger. The intensity of


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network depends on the nature of firms in cluster, such as the difference between the Taizhou and Tianjin clusters. For industrial clusters, the main role of government is to maintain market order and to create good external environments (Cooke, 2001). As different types of firms have different features and demands, government needs to provide different policies to meet these demands. Even more importantly, changes in the relations among actors, and new relations and new networks from new actors lead to higher demands on the role of government. The local government in China makes different policies to promote the development of clusters and to enhance the long-term competitiveness. The effect of local government in the formation and development of clusters is positive as long as the local government makes proper policies and pays more attention to the real demands of clusters (Prevezer, 2008; Rosenfeld, 2005). The local government policies for pharmaceutical clusters in China give meaningful implications: . The influence model of local government to the formation of clusters depends on the resource endowments, industrial bases, locations, and government requests. And the model can convert after the formation process. The formation of a biopharmaceutical industry cluster in Taizhou is a top-down model. However, after the cluster’s preliminarily foundation, the local government did not intervene in designing the development strategy of the cluster and convert to the model of bottom-up in the cluster development process. . The three local governments in the different clusters have the same policy of strong support for SMEs. On the one hand, because of its private ownership structure, the interactions among enterprises is weak, which needs government to be an initiator to help them to cooperate. They also need many supports from the local government, especially finance support. On the other hand, as the advantage of SMEs is flexible, SMEs always play important roles in industry innovation. Most of innovations are originated or initiated from SMEs, which are the main driving force for clusters. The cluster in Tonghua is made up of SMEs and the Tonghua Government plays an indirect part in the development of the cluster, which is helpful to keep the vitality of this kind of cluster. . SOEs need the guidance from local government because of their ownership structure and their slow reaction to the change of market (Cao et al., 2008; Luo, 2001). So the government can play a very important and direct part in the primary stage of development or transition of SOEs in the cluster, such as the Tonghua cluster. When SOEs find out their own development direction, too much administrative intervention will restrict the development of SOEs. . The impact of government to the large private enterprises is not as direct as for SOEs, but the influence degree is similar because the private enterprises are very sensitive to the policy. The cluster in Taizhou is formed from four large private enterprises. The local government promoted the formation of cluster but did not interrupt the detail development strategy of the cluster, which provide the strong support and try hard to keep the activity of private enterprises. . As the location choice of MNCs depends mainly on investment circumstance and development potential, which lie on the local government policy and administration (He and Xiao, 2011). The local government can plays a direct role in attracting investments from overseas; the connections among MNCs, SOEs

.

and SMEs also need initiation from local government. The cluster in Tianjin is made up of three types of firms and one-third of firms in the cluster are branches of big MNCs. So the Tianjin Government promotes the formation of the by giving directly administrative support to the cluster. The government can play a complementary role in enhancing the relations of firms in and out of cluster. As mentioned before, the interactions among firms are important for the innovative activity. However, the intensity of the relationship and network among actors depends on the nature of enterprise in the cluster. In addition to directly influencing the behavior of firms, government can also affect the innovation capacity of clusters through enhancing the relations between actors, such as establish the cooperation platform, the international pharmaceutical high-tech zone, or promote the cooperation of research between enterprise and university.

As shown in this study the local policy for pharmaceutical clusters in China has two purposes. The first purpose is to make full use of local resource, including natural resource, infrastructure facilities, industrial base, and so on, to facilitate the establishment of industrial cluster efficiently to help to realize industrial emergence and benefit industrial competitiveness. While the specific local policy depends on the nature of cluster resources, promoting internal dynamics within clusters for enhancing long-term competitiveness is generally emphasized. The second purpose is a complementarity to the relations and interactions among innovation actors. The similarities of local governments’ policy for promoting the cooperation between innovation actors demonstrate that the local government in China has put much effort to not only establish industrial cluster but strengthen industrial competitiveness through enhancing the interactions among firms in the industrial clusters and the networks between cluster and outside world, which is particularly meaningful for other economies that are thinking about policy design for industrial clusters. While this paper focuses on the influence of local policy on pharmaceutical clusters in China, it is necessary to indicate that the pharmaceutical clusters in China are relatively new, such as the Tianjin cluster. The long-term effect of local policies needs to be studied in the future. In particular the following need longitudinal observation: how local government implements their policies on SMEs and how local government deals with future entries of firms with different ownership into its cluster. In addition, this paper focuses on the pharmaceutical cluster. Comparison studies in other clusters with high industrial complexity should provide further knowledge about industrial cluster as effective tool for industrial catch-up and how local government can contribute. References Brusco, S. (1982), “The Emilian model: productive decentralisation and social integration”, Cambridge Journal of Economics, Vol. 6 No. 2, pp. 167-184. Cao, X., Xi, Y. and Zeng, X. (2008), “Upgrading resource-based regional industrial clusters to innovative clusters: the case of Shanxi Province in China”, Asian Business & Management, Vol. 7 No. 3, pp. 277-295. Carlsson, B. and Stankiewicz, R. (1991), “On the nature, function and composition of technological systems”, Journal of Evolutionary Economics, Vol. 1 No. 2, pp. 93-118.


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About the authors Yuanyuan Yu is a PhD candidate of medicinal administration at ICMS, University of Macau. Her major research area is about pharmaceutical clusters and national medicine industry in China. Zhiqiao Ma is a Master graduate of medicinal administration at ICMS, University of Macau. He has a Bachelor’s degree of science in Peking University that is one of the top universities in China. His major research area is about pharmaceutical clusters and pharmaceutical industry in China. Hao Hu is an Assistant Professor at ICMS, University of Macau. He holds a BA of industry economics, an MA of management science, a doctorate in management from Sichuan University, and a post-doctorate from HEC Montre´al. His research focuses on sectoral innovation of pharmaceutical, policy management of Chinese medicine, and industrial standardization of Chinese medicine. Hao Hu is the corresponding author and can be contacted at: [email protected] Yitao Wang is a Full Professor at ICMS, University of Macau. He is a famous expert in the Chinese pharmaceutical industry. His research focuses on industrial upgrading and standardization of Chinese medicine.

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