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TECHNOLOGICAL CAPABILITIES AND INNOVATION IN SOUTHEAST ASIA - EMPIRICAL EVIDENCE FROM SINGAPORE, PENANG (MALAYSIA) AND THAILAND Martin Berger Javier Revilla Diez Chair of Economic Geography, Institute of Geography, Christian-Albrechts Universität Kiel Ludewig-Meyn-Straße 14, 24098 Kiel, Germany Tel.: ++49 (0)431 880-2951, Fax.: ++49 (0)431 880-4658 email: [email protected]; [email protected] Abstract This paper compares groups of firms with different technological capabilities in Bangkok (Thailand), Penang (Malaysia) and Singapore in respect to their innovation activity, cooperation behaviour and assessment of the business environment. While conspicuous differences between the regions are found, the comparison of the different technological capability- groups is less conclusive. However, some empirical evidence suggests that technological capabilities indeed influence innovation activity.

1 Introduction Today’s world economy has been characterised as a ‘knowledge-based economy’ (OECD, 1996) with knowledge being the most important resource and learning being the most important process (Lundvall, 1996). According to this assumption it is essential not only for developed but also for developing countries to foster the innovativeness of their companies. This paper scrutinises empirical data about firms’ innovative activities and co-operation from Singapore, Penang (Malaysia) and the Greater Bangkok Region (Thailand) in order to establish similarities and differences between these regions and between companies at different stages in respect to their technological capabilities (TCs). Key questions are: Why is it important for companies in developing countries to develop TCs and how do TCs relate to innovation? Do companies with different TCs also differ in respect to their innovation activity, if yes, how do they vary? In what way does a company’s location influence its TC-level, its innovation and cooperation behaviour? The paper is structured in the following way: First, a brief theoretical overview is given, stressing the importance of knowledge, learning and innovation for economic development, summarising the concepts of spatial systems of innovation and presenting the concept of technological capabilities. The latter is used in our research to distinguish companies at 1

different stages of their catching-up process. Second, we present the methodology of the surveys conducted in Singapore, Penang and Thailand and its predecessor-surveys in Europe. Finally, the dataset and its key characteristics is introduced. Moreover, in this final chapter two hypothesis are tested: First, companies with advanced TCs are more innovative, cooperative and assess the business environment conditions in a different way than companies with less advanced TCs. Second, distinctive differences can be observed between companies’ innovation and co-operation behaviour as well as their assessment of the business environment conditions in first tier Newly Industrialised Countries (NICs) like Singapore, fast-followers like Penang and ‘laggards’ like Thailand respectively Bangkok (Intarakumnerd et al., 2002).

2 Theoretical Background 2.1 Knowledge, Learning, Innovation and Economic Development Technological change used to fall like manna from heaven, at least as long as it comes to economic theory, until the early 1990s, when Romer (1990) introduced technological change into the neo-classical model of economic growth. In his model innovation is explained endogenously and is seen as the driving force of economic growth. Key determinants of technological change are human capital and knowledge. While human capital encompasses all the knowledge and skills that are bound to a person, the term knowledge describes information in the form of publications or blueprints. Additionally, the understanding of the innovation process has changed fundamentally. Instead of being a linear process (research and development (R&D) – production – marketing) it is now seen as a chain-linked process, which is achieved in an interactive way between partners internal and external to the firm (Kline and Rosenberg, 1986). This change is at least partly caused by increased uncertainty, complexity and costs of the innovation process. Since this process is interactive and therefore based on a division of labour, the transfer of knowledge between the partners is all important. In the field of innovation research it is generally accepted that knowledge can be classified as being tacit or codified. While codified knowledge is written down in articles and manuals or is embedded in technology, tacit knowledge is bounded to specific persons or organisations. Tacit knowledge is reflected by a person’s skills or a firm’s routines. Since it is difficult to articulate tacit knowledge, its transfer is restricted to face-to-face contacts. This does not hold true for codified knowledge, which is globally available by means of modern communication technologies or trade. But even codified knowledge has to be internalised, which means that it has to be converted into tacit knowledge, in order to use it in a different context (Nonaka and Takeuchi, 1995: pp. 65). Learning can thus be defined as a process in which an individual or organisation acquires tacit or codified knowledge. The ability to learn depends on the stock of previously accumulated 2

knowledge, it becomes easier with an increased knowledge stock. Therefore, a company’s learning capabilities depend on its ability to assess, embrace and utilize new knowledge, which has been termed ‘absorptive capacity’ by Cohen and Levinthal (1990). In general four means of learning can be differentiated: 1. Learning by searching: Companies learn while conducting R&D activities in order to explore new knowledge and technology. 2. Learning by doing/ using: Companies learn while producing goods (learning by doing; Arrow, 1962) as well as by using products, e.g. capital goods (learning by using; Rosenberg, 1976). 3. Learning by training/ hiring: Companies learn by acquiring human capital, either through personnel-training (learning by training) or through recruitment of professionals (learning by hiring). 4. Learning by interacting: Companies learn while interacting with other companies, especially customers and suppliers (Lundvall, 1988). Due to its interactive and therefore social character, learning by interacting is strongly influenced by the institutional and organisational framework. While learning by interacting seems possible between remote partners under the condition of stable and standardised technology (Lundvall, 1988: 355), it is fostered by spatial and cultural proximity in an uncertain business environment with complex technologies and rapid technological change. Since learning by interacting is supposed to be of particular importance for innovations (Lundvall, 1988; Gertler, 1995), the factors influencing this kind of learning have received much attention by recent research work, which finally resulted into the elaboration of the concepts of national and regional systems of innovation.

2.2 National and Regional Systems of Innovation Using the paradigm shift from the linear to the chain linked model of innovation as a starting point and taking into account the importance of intra- and inter-firm co-operations for the successful development of innovations, a group of researchers has developed concepts of national systems of innovation (NSI) since the mid 80s (Lundvall, 1985; Freeman, 1987; Dosi et al., 1988; Nelson, 1993). The NSI-approach is at the same time a theoretical and analytical concept. Theoretically it is rooted in institutional and evolutionary economics. While some authors (e.g. Lundvall) support an institutional economics approach, which objective is to examine the relevance of an economy’s institutional and organisational structure for the efficient allocation of production factors, others (e.g. Freeman) belong to the school of evolutionary economics, which contemplates the behaviour of economic agents and their path-depended decisionmaking-processes as well as the grown structures of the economy and its information channels (Grupp, 1997; Revilla Diez, 2002a). The analytical part of the NSI-approach was first elaborated by Nelson (1993) in order to compare the NSI of 15 countries. 3

The main components of a NSI are organisations, institutions and the relations/ interactions among them. Organisations are defined as formal structures with an explicit purpose, which are consciously created (Edquist and Johnson, 1997: 47). Important organisations are companies, knowledgeproducing and diffusing organisations like universities, political organisations such as parliaments or ministries, bridging organisations, that facilitate technology transfer between science and business and finally social organisations like trade unions. Institutions are “sets of common habits, routines, established practices, rules, or laws that regulate the relations and interactions between individuals, groups and organisations” (Edquist and Johnson, 1997: 46). They can be either formal (laws) or informal (traditional way of doing business).While organisations are regarded as players of the game, institutions are seen as the rules of the game. Lundvall et al. (2002: 220) view the following three institutional dimensions as having a major impact on learning and innovation behaviour: First, the time horizon of the agents (short-term in Anglo-Saxon countries vs. long-term in Japan), second, trust between agents and third, the pre-dominating rationality (communicative rationality rather than instrumental rationality seems to support innovative behaviour). Interaction between organisations are either market or non-market relationships. Especially the latter is supposed to be highly relevant for learning (Lundvall and Maskell, 2000; Edquist, 2001). Interaction can take the form of flows of knowledge and information as well as flows of investment and funding, but also informal arrangements like networks (Cooke et al., 1997: 478). The NSI-concept is based on empirical work in developed countries. A simple transfer and implementation of the very same concept in developing countries does not seem to be appropriate. Rather an analysis of the NSI in NICs and developing countries has to take into account the following four aspects: 1. The focus of the NSI-concept lies on the development of new technology through formal R&D. However, in developing countries it is crucial to acquire, utilise, adopt and improve technologies, already established in advanced countries (Wong, 1995; Lall, 2000). This is the reason why in the context of developing countries a broad definition of innovation is applied, which includes new products, processes and organisational arrangements that are new to the firm rather than new to the world (Ernst et al., 1998b: 13). Furthermore, industrial innovation in developing countries is mainly conducted in-house and in an informal manner, where “R&D activities are not clearly and formally articulated with the enterprise strategy” (Arocena and Sutz, 1999: 13)1. 1

These conclusions are the result of empirical work in Latin America but are supposed to hold true for other developing countries, too. 4

2. Despite being of major importance for the development of absorptive, learning and technological capabilities, human resource development has so far been largely neglected. Therefore, future research has to consider the science and education infrastructure (Lundvall et al., 2002; Wong, 2001). 3. International links offer learning opportunities for developing countries, but they are not well accounted for in the NSI-concept. Due to a dualistic and inhomogeneous economic structure and a weak domestic knowledge base, interactions between national agents are supposed to be less important in developing than in advanced countries (Wong, 2001; Ernst, 2002). Since the NSI is hardly developed, “international linkages need to prepare the way for the development of national innovation systems” (Ernst, 2002: 500). 4. For developed countries the NSI approach is an ex-post concept, which is based on empirical observations. It was utilised to describe, analyse and compare well developed NSI with a strong institutional base and advanced infrastructure. For developing countries on the other hand it is an ex-ante concept, with the NSI being rather an aim, that has to be build up along economic development, than a given asset (Arocena and Sutz, 1999, 2002). For this reason the focus of analysis in developing countries should be on ‘system construction’ and ‘system promotion’ (Lundvall et al., 2002: 226). Regarding these criticism, Wong (2001) has elaborated a modified NSI-concept especially for NICs. The main organisations in his NSI are a) companies, b) public R&D and Science and Technology (S&T) support institutions and c) manpower development institutions. By contemplating science and education separately, Wong shifts human resource development into the centre of his research. The key objectives of his NSI model are “to build up the stock of scientific and technological resources and to allocate and deploy these resources to the respective innovation actors” (Wong, 2001: 544). Hereby he takes into account the diffusion of technology which is crucial for developing countries. Moreover he includes ‘international technology linkages’ to overcome the limited focus on domestic interactions. As a result of these changes and the widening of the concept, it is necessary to consider all direct and indirect policies effecting either the agents of the system or their interactions. In the course of the debate about globalisation, different scholars claimed the end of the nation state and the rise of the regions as “natural economic zones” (Ohmae, 1993: 78). Even though these claims seemed exaggerated, they resulted into stronger research interest in regions. In the field of innovation research this led to the formulation of the concept of regional systems of innovation (RSI) (Braczyk et al., 1998; Cooke, 1992). Taking on the basic ideas of the NSI concept, the key notion of the RSI is that regions offer particular environment conditions and opportunities for interactions that can either foster or hinder the co-operation between innovative actors in a region. Additionally, the amount and quality of regional innovation actors, manufacturing companies, business-service companies, research 5

institutes and universities, influences the opportunities for learning by interacting (Cooke and Morgan, 1998). In conclusion, the endowment of a region with innovative actors and environment conditions that favour co-operation and innovation activities constitute the extend and utilisation of the regional innovation potential. Bearing in mind the positive effects of spatial proximity for innovation-related social capital building (trust) and knowledge spill-over, the regional scale provides an important research level. A special case in point are metropolitan systems of innovation, that are restricted to major metropolitan areas and their hinterland (Fischer et al., 2001; Revilla Diez, 2002b). Since these regions often encompass the major ‘growth engines’ of the national or global economy, their system of innovation, their endowment with innovative actors and the environment conditions they offer are of special interest.

2.3 Technological Capabilities Like the NICs of East Asia (South Korea, Taiwan) the NICs of Southeast Asia (Singapore, Malaysia and Thailand) have experienced a period of remarkably growth during the final decades of the 20th century. Being all rather late-industrialising countries they managed a pretty successful catch-up process despite at least two severe competitive disadvantages: first, they are remote from the lead user markets in North America, Europe and Japan and therefore disconnected from essential user-producer links; and second, they are distant from the leading sources of technological innovation (Hobday, 2000; Wong, 1999a). These disadvantages result into relatively little innovative activities, and little output in terms of ‘new to the world’-innovations. Instead, „the process of technological change in developing countries is one of acquiring and improving on technological capabilities rather than of innovating at frontiers of knowledge. This process essentially consists of learning to use and improve on technologies that already exist in advanced industrial economies” (Lall, 2000: 13). Because of this, innovations in developing countries are often defined as products, processes or types of organisation new to the firm (Hobday, 2000; Ernst et al., 1998b). There are various ways to categorize firm-level TCs (see Bell and Pavitt, 1995, Lall, 1992, Marcelle, 2002; Wong, 1999b). A very comprehensive framework was elaborated by Ernst et al. (1998b), who distinguish the following capabilities: Production capabilities: which define the knowledge and skills necessary to operate a plant. Basically, these capabilities encompass production management, production engineering, repair and maintenance. Investment capabilities: are the knowledge and skills that are used to conduct a new industrial project, from pre-investment activities such as feasibility studies to project execution. Moreover, the ability for efficient external sourcing is part of investment capabilities. 6

Minor change capabilities: refer to a company’s ability for continuously improvement, adaptation and incremental innovation of products, processes and organisational arrangements. Strategic marketing capabilities: include collecting market intelligence, the development of new markets, the establishment of distribution channels and the provision of customer services. Linkage capabilities: The competence to organise knowledge- and technology transfer networks within the firm, with other companies and with the domestic science and technology infrastructure are summarised in the term linkage capabilities. Major change capabilities: refer to the ability to conduct R&D, develop and introduce new products, processes and organisational arrangements either in-house or in cooperation with customers, suppliers, public research institutes etc. „This classification suggests a sequential ordering of priorities for late industrialization strategies based on imported technology” (Ernst et al., 1998b: 17). Technological capabilities are the result of technological learning. In this process a company acquires codified knowledge (e.g. knowledge embedded in technology or written down in manuals), combines it with existing tacit knowledge and thereby builds up a stock of firm specific, tacit knowledge. This is a conscious and purposive as well as a costly and timeconsuming process, which is non-linear but path-dependent and cumulative. Because of its interactive and technology-specific nature, there is no single trajectory but a range of possible development-paths (Lall, 2000: pp. 16; Ernst et al., 1998a: 333). Whether companies develop technological capabilities and how they do it depends on the structure and efficiency of the NSI: „successful technological learning ... requires an effective national innovation system“ (Kim, 1997: 219; cf. Wong, 1999a). Still, the mechanisms for successful technological learning have to be enquired for. The vast literature on international technology transfer has identified many different transfer channels, ranging from licensing, foreign direct investment, joint ventures and subcontracting to overseas training and education (Hobday, 2000: 133; cf. Kim, 1991; Wong, 1999b; Mowery and Oxley, 1995; Pack and Saggi, 1997). Gertler (2001: 9) has introduced eight channels of convergence, which identify channels of best practice-learning but also offer a convenient framework for the mechanisms of technological learning.

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Tab. 1.1: Channels of convergence Passive/ shallow

Active/deep

Media/ education Travel Management consultants Trade (‘simple market’) Trade (‘organised market’: that is, intense interaction between buyer and seller) Alliances (strategic alliances, joint ventures, cooperation agreements) Mergers/ acquisitions Foreign direct investment

Gertler, 2001: 9; changed A prerequisite for this kind of organisational learning is individual learning of the workforce. This implies that individual learning capabilities are essential for the development of TCs. Therefore, formal learning (e.g. learning by training in university), non-formal learning (e.g. training on the job) and informal training, “which is defined as a lifelong process by which persons who work in foreign affiliates or in domestic companies which closely interact with foreign TNCs [Transnational Companies] may acquire values, attitudes and beliefs embedded in the organizational culture of TNCs through daily experience, observation and exposure to indoctrination” (Ernst et al., 1998b: 16), have to be taken into account. Based on the experience of the Asian NICs Wong characterised five generic routes for rapid technological catch up, which can be seen as successful development paths for technological learning (1999a: pp.8). One route is the ‘Reverse Value Chain’ Strategy that builds upon Hobday’s work on a OEM-ODM-OBM migration strategy (Hobday, 1995, 2000). The notion of the concept is, that latecomers pursue a certain strategy to develop technological capabilities: first they start developing process- capabilities, followed by product designcapabilities and finally new product creation-/ branding- capabilities. “This is a reversal of the normal sequence of value chain activities pursued by large established high-tech firms in advanced countries” (Wong, 1999a: 8). According to this concept a company starts as an Original Equipment Manufacturer (OEM), performing simple component subcontracting or assembly operations for a TNC. The buyer (TNC) provides detailed product specifications and sells the product under its own brand and through its own distribution channels (Hobday, 2000; Wong, 1999a). So the OEM phase marks companies that solely rely on their production capabilities. At the next stage the latecomer firm becomes an Original Design Manufacturer (ODM). The buyer still supplies the general product requirements, but the ODM-firm is responsible for the detailed design and production process. Consequently, the shift from OEM to ODM is based on the gaining of product design, product-process interfacing, manufacturing and sometimes component design capabilities (ibid.). The final step is the move towards Own Brand Manufacturing (OBM)2. 2

Furthermore Wong (1999a) distinguishes between OBM and own idea manufacturing (OIM). The latter company is developing own product ideas, but does not market its products under its own brand. 8

The company develops its own products and sells them under its own brand. Often it even develops specific distribution channels. To become an OBM-firm a company needs at least basic capabilities in the field of marketing, product development and R&D. Table 1.2 summarises the transition from OEM to OBM. As Hobday (2000) points out the OEM to OBM system enables firms to reach into international markets, export large volumes of goods, realise economies of scale and invest in automation. Furthermore, by supplying demanding customers in the leading markets latecomer firms learn by doing, using, and interacting (with the foreign partner), and become acquainted with product and process technology as well as end-user market requirements (Wong, 1999a). Therefore, the OEM-OBM system can be seen “as a training school for technological learning” (Hobday, 2000: 134). Tab. 1.2: Transition of NIE latecomer firms: From OEM to ODM to OBM Technological transition

Market transition

OEM

Learns assembly process for standard, simple goods

Foreign TNC/ buyer designs, brands, and distributes

ODM

Local firm designs (or contributes to the design, alone or in partnership with the foreign company) and learns product innovation

TNC buys, brands, and distributes TNC gains post production valu-added (PPVA)

OBM

Local firm designs and conducts R&D for new products

Local firm organizes distribution, uses own brand name, and captures PPVA

Hobday, 2000:135; changed Since every OEM to OBM phase indicates a particular level of technological capabilities, respective successful technological learning, we have grouped the companies in our dataset about Singapore, Penang (Malaysia) and the Greater Bangkok Region (Thailand) accordingly (see chapter 4). The aim of the following empirical study is to identify differences between these groups in respect to their innovation and cooperation behaviour. If we manage to establish major differences, this could advance our understanding of the mechanisms and importance of knowledge transfer and learning between firms for the development of technological capabilities and therefore of economic competitiveness.

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3 Methodological Approach Carried out in two phases between 1995 and 1999, the European Regional Innovation Survey (ERIS) attempted to empirically asses regional innovation potentials as well as intraregional and interregional co-operation relationships between innovation actors, and at providing a comparative evaluation. For this purpose usable data were obtained from roughly 8,600 innovation actors in eleven European regions, including 4,200 manufacturing firms, 2,500 Knowledge intensive business services (KIBS) and 1,900 research institutions. An overview of the first phase of this project is provided by Fritsch, Koschatzky, Schätzl et al. (1998), while Sternberg (2000) reports on the situation after completion of the second phase. When designing the questionnaires for the postal surveys in Singapore, Penang and Thailand, it was necessary to ensure maximum comparability with the ERIS survey and other empirical studies, such as the Community Innovation Survey of the European Commission (European Commission, 2001) or the Mannheim Innovation Panel of the Centre for European Economic Research (among others, Janz and Licht, 1999; Janz et al., 2001). On the other hand, certain specific features of the survey region and the interests of the co-operation partners had to be taken into account as well. The resulting questionnaires thus represent a compromise in which the core elements of the ERIS questionnaires could, however, be retained: - General information: As an introduction, questions were asked about various firm characteristics such as age, size (in terms of turnover, capital stock, and employees), branch, ownership and functional status, share of exports, educational profile of staff etc. In the analysis these variables can be called upon to explain differences in the innovation and cooperation behaviour. - Innovation activities: Innovating firms which have introduced a new or substantially improved product or manufacturing process in the past three years were asked about details concerning their innovation behaviour. Here, input indicators (personnel and expenditure on R&D and/or innovations) as well as throughput indicators (e. g. patents) and output indicators were registered. A firm is considered to be innovative when new or substantially improved products contribute to at least 25 % of its turnover, or when 25 % of its output is produced with new or improved processes. - Innovation co-operation: In this central part of the survey firms were asked which external sources of technical knowledge they use for their innovation processes, with which external partners they co-operate and where those partners are located3. Here, the most important questions concern the connection between co-operation and innovation success as well as the relevance of spatial proximity to co-operation. The postal survey of manufacturing firms in Singapore was carried out between September 1999 and January 2000 in close co-operation with the Centre for Management of Innovation and 3

The surveyed firms in Thailand were not asked about the location of their co-operation partners. 10

Technopreneurship (CMIT) at the National University of Singapore and with Singapore' s highly influential economic promotion agency, the Economic Development Board (EDB, cf. Schein, 1996). Of the 1,869 questionnaires sent out it was possible to receive 374 usable returns, resulting in a response rate of 20 %. The initial results were presented to the EDB in a report (Wong et al., 2000), and a more detailed analysis of the data set as well as the more extended case study material obtained in interviews is presented in Kiese (2002). The Penang State Innovation Survey carried out in the summer of 2000 in co-operation with the Socio-Economic and Environmental Research Institute (SERI) was based on a database comprising 951 manufacturing firms. Of the 921 questionnaires sent out, 192 were returned in a quality that was usable, which corresponds to a response rate of 20.8 %. The initial results of this survey were presented to the government of the Federal State of Penang in an unpublished report as well as at a workshop (SERI and University of Hanover, 2001; Ong, 2001), and a more comprehensive evaluation of the data as well as additional interviews will follow in Stracke (2003). On the basis of the questionnaires used in Singapore and Penang, Thailand' s National Science and Technology Development Agency (NSTDA) commissioned the Bangkok-based consulting firm The Brooker Group Public Company Limited to carry out the first countrywide R&D and innovation survey between January and April 2001. This was accompanied scientifically by the authors. Of the 13,415 largest Thai firms by turnover, a sample of 2,166 companies was drawn using stratified random sampling based on firm size and industry. 1,019 of these firms returned usable replies, which corresponds to an outstanding return rate of 47 % (cf. Virasa and Brimble, 2001). Tab. 3.1 compares the surveys of manufacturing firms carried out in Singapore, Penang and Thailand with the results of the European Regional Innovation Survey (ERIS). It becomes clear that the samples gained in Southeast Asia are within the range of the ERIS project, both absolutely (sample size) and relatively (response rates).

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Tab. 3.1 Project history and response rates (manufacturing only) Region Baden Hanover-Brunswick-Göttingen Saxony Alsace Barcelona Gironde Slovenia South Holland South Wales Stockholm Vienna ERIS-11 Singapore Penang Thailand 1 launch

1

Year Responses Response rate 1995 430 15.8% 1995 372 20.6% 1995 1,004 16.7% 1997 263 15.0% 1997 395 15.3% 1997 101 12.7% 1997 416 31.2% 1997 261 13.7% 1997 280 17.6% 1997 451 24.0% 1997 204 19.9% 4,177 19.7% Singapore 1999 374 20.0% Malaysia 2000 192 20.8% Thailand 2000 1,019 47.0% Data: European Regional Innovation Survey EDB/NUS-CMIT National Innovation Survey Singapore Penang State Innovation Survey Thailand R&D/Innovation Survey 2000 Country Germany Germany Germany France Spain France Slovenia Netherlands UK Sweden Austria

4 Empirical Evidence 4.1 Key Characteristics of the Dataset The data analysis has been restricted to the machinery and electronics industry, which encompasses fabricated metal products, electrical machinery and equipment as well as electronic products4. This sector has been chosen, because it offers an appropriate basis for interregional comparison: It is one of the most important sectors within manufacturing in all three regions, it is fairly technology-intensive and innovative. The restriction to one sector seemed necessary, because first analyses found, that the sector-affiliation poses a strong influence on the innovation behaviour. In a next step the companies were grouped according to their technological capabilities, e.g. a company was labelled OEM if it made more than 50% of its turnover/ sales with OEM products (see 2.3). Following TC-groups are distinguished in the dataset: manufacturing arm of parent company or MA: Products manufactured by the company according to design specifications provided by parent company or associate in the corporate group

4

Unfortunately the Thailand Statistical Classification (TSIC) 2-digit code combines the important machinery- and electronic sector, which therefore can not be analysed separately. 12

original equipment manufacturing or OEM :Products manufactured by the company according to design specifications provided by external buyers original design manufacturing or ODM: Products developed and designed by the company according to performance requirements of buyers original brand manufacturing or OBM: Products developed and designed by the company and sold under its own brand To allow cross comparison, the dataset was restricted to the following three metropolitan regions: Greater Bangkok Region (GBR): which includes the Bangkok Metropolitan Region and the Eastern Seaboard Penang (PNG): the island of Penang is a high-tech enclave in Malaysia. Singapore (SGP) Tab. 4.1 depicts the size of the sample in the three regions and the distribution over the four technological capabilities groups. It strikes that the percentage of OBM firms is highest in the GBR, which contradicts the assumption that advanced countries host more companies with higher TCs. Instead of indicating a higher than expected innovativeness and competitiveness of the companies in Bangkok, this result rather gives evidence that the TC level in itself is not sufficient to evaluate a company’s innovative capability. Tab. 4.1 Frequency of companies according to technological capability GBR PNG SGP MA 84 15 57 34,6% 20,0% 29,8% OEM 78 37 76 32,1% 49,3% 39,8% ODM 28 16 33 21,3% 17,3% 11,5% OBM 53 7 25 21,8% 9,3% 13,1% Total 243 75 191 100,0% 100,0% 100,0%

To get the broad picture straight, it seems necessary to present figures reflecting the differences in economic development between the regions. Tab. 4.2 shows the means of sales per employee for 1999 in US$. Despite the disadvantage of displaying turnover rather than value added figures, Singapore’s outstanding position is documented clearly. Surprisingly, the total figures for Penang do not confirm higher sales per employee than in the GBR. Nevertheless, the MAs and OBMs in Penang do have an obviously higher mean than those in Bangkok, which supports the assumption of Penangbased companies having a higher position in the value-chain.

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Tab. 4.2 Mean of sales per employee 1999 in US$ (based on exchange rates 31.12.1999) GBR PNG* SGP* MA 107.435 127.602 248.128 OEM 54.600 45.098 159.161 ODM 45.971 43.771 159.179 OBM 40.275 79.602 207.795 TOTAL 68.951 65.183 192.080

*Note: While Penang and Singapore count employees as full time equivalents; in Bangkok the employees were counted as headcount

Another way of setting the TC-structure into context, is to use the notion of the industry life cycle. Like products industries are supposed to experience a life cycle (Klepper, 1996; Revilla Diez, 2002a: pp. 76), which consists of four phases: 1. Introduction: Mainly small companies with a high innovation output dominate the industry. 2. Growth: Successful small companies witness growing turnover and profits as well as an increase in employees. They therefore become medium to large size companies, that are still characterised by an above average innovation output. 3. Maturity: In this phase the products of the industry are standardised. The market is very competitive with many producers trying to realise economies of scale. The innovation activity decreases and companies are more likely to conduct process than product innovations. 4. Decline: Companies are not competitive any more and therefore experience a steady decline in profits and employees. As a result companies in this phase are small and do rarely innovate. To assign a company to one of the four life-cycle stages two indicators are used: first, the size of the company, measured in the total number of employees; second, the innovation output, measured in the share of new/ improved products of the total turnover. In a first step, we calculated the industry-specific median for the share of new/improved products of total annual sales for both, small (less than 100 employees) and medium/ large companies (100 employees and more) (Tab 4.3). Tab. 4.3 Median of approximate % of total annual sales of new/ improved products Small Companies Medium & Large Companies (= 100 employees) Machinery 2 2 (Label: 1: less than 10%; 2: 10-24%; 3: 25-49%; 4: 50-74%; 5: 75% and above)

Then we arranged: the small companies with an average or above share of new/improved products at the total annual turnover in the introduction phase, the medium/ large companies with an average or above share of new/improved products at the total annual turnover in the growth phase,

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the medium/ large companies with a below average share of new/improved products at the total annual turnover in the maturity phase, and the small companies with a below average share of new/improved products at the total annual turnover in the decline phase. As can be seen from Tab. 4.4, Penang as well as Singapore have explicitly more companies in the first two industry life cycle phases than Bangkok (although this is not statistically significant). This indicates that companies in Singapore and Penang are more often in an early phase of their development, offering good prospects for future growth and employment. In comparison, firms in Bangkok are more often positioned in the growth to maturity phases. This result puts into perspective the TC-frequencies in the three regions and shows that other factors also have a strong influence on economic performance. At the same time it underpins the theoretical argument of the ‘reverse value chain strategy’ (see 2.3), which states that companies in Asian NIEs start in more mature, standardised productions processes and develop towards more sophisticated design, development and branding activities. Tab. 4.4 Number of companies in according to industry-life-cycle GBR PNG n % cum.% n % cum.% Introduction 8 21,6 21,6 6 16,2 16,2 Growth 15 40,5 62,1 24 64,9 81,1 Maturity 9 24,3 86,4 4 10,8 91,9 Decline 5 13,5 100,0 3 8,1 100,0 Total 37 100,0 37 100,0 Chi-Sq. 0,293

n

21 35 10 10 76

SGP % 27,6 46,1 13,2 13,2 100,0

cum.% 27,6 73,7 86,9 100,0

Tab. 4.5 Ownership Structure Region Owner MA OEM ODM OBM Total Chi-Sq. GBR LC 13,4% 43,8% 60,7% 82,7% 43,8% 0,000 JV 47,6% 35,6% 28,6% 15,4% 34,5% MNC 39,0% 20,5% 10,7% 1,9% 21,7% PNG LC 6,7% 51,4% 43,8% 57,1% 41,3% 0,039* JV 13,3% 16,2% 25,0% 14,3% 17,3% MNC 80,0% 32,4% 31,3% 28,6% 41,3% SGP LC 17,5% 60,5% 63,6% 56,0% 47,6% 0,000* JV 8,8% 15,8% 15,2% 8,0% 12,6% MNC 73,7% 23,7% 21,2% 36,0% 39,8% LC = local company; JV= Joint Venture; MNC= Multinational Company * at least one cell with expected frequency