Entrepreneurial Network Analysis of OEMs and ODMs in Taiwan's Information&Electronics Industry
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(2) On the one hand, besides manufacturing responsibility, the pressures of stock and risk were taken on by the brand manufacturers in the past but now are totally undertaken by OEM manufacturers. Therefore, the OEM manufacturers must make use of more module design, which makes the assembling procedure easier: component design can save on material costs for the OEM manufacturers. The most important aspect is to maintain close cooperation relations with the upstream components suppliers, and by doing this, enable the production to achieve just-in-time supply levels and so reduce the risk of carrying stocks. On the other hand, in order to reply rapidly to market demands and to reduce stocks, Taiwan’s information electronics industry proprietors actively set up assembly strongholds and shipping warehouses at places that are close to customers in order to globalize the scope of their business. They offer the customers not only the products, design and maintenance but also the logistic services; all these come in time to form the global production and marketing logistics. These affiliated upstream and downstream cooperating firms serve as the members of the virtual business of big information factories; they cooperate closely with each other to face the keen competition by thus integrating the whole supply chain. The trend to vertical disintegration in production and business resource integration has led the flourishing development of Taiwan’s IE industry in the last twenty years, and encouraged the integration of supply chain, distribution and manufacturing systems; this approach in turn set up the modes of build-to-order (BTO) and configure-to-order (CTO) of customization, which give rise to exceptional performances by Taiwan’s international subcontracting manufacturers. According to Ernst’s research in 2000, Taiwan’s international subcontracting manufacturers (such as OEMs and ODMs) have established a stable global competitive position mainly by means of multi-linkage organizational learning and the acquisition of knowledge. Ernst also emphasizes that, some famous international subcontracting manufacturers in present-day Taiwan, such as Acer and Taiwan Semiconductor Manufacturing Company (TSMC), took advantage of subcontract opportunities to participate in worldwide production networks and gradually accumulate the knowledge and ability of their organizations with the co-evolution of network ties in order to reverse the inferior position of SMEs; Taiwan’s subcontract manufacturers have shifted from OEM to ODM and even to OBM (original brand manufacturer, which means creating its own brand). According to research from Taiwan Institute of Economic Research, the main characteristics of the development of Taiwan’s scientific and technological industry are listed as follows: (1) The industry mainly manufactures information-hardware products; (2) The marketing method is to serve as the OEMs or ODMs of the large U.S. and European factories; (3) The source of production technology comes from abroad (especially the U.S.A. and Japan); (4) The industries have a geographically centralized position and precise division of labor. Therefore, if Taiwan’s international subcontracting firms or small and medium enterprises (SMEs), etc., can have an interactive relationship with domestic and foreign 2.
(3) cooperative manufacturers; the network position in terms of the degree of connection and density of interaction with other companies will influence external inter-firm learning or alliance learning, and the Taiwanese manufacturers can then make great progress in competitive competence in the construction of capabilities and accumulation of knowledge.. 1.3 The activities and networking within OEMs and ODMs The research objective mainly focuses on Taiwan’s international subcontracting manufacturers (especially OEMs and ODMs) of the IE Industry. According to the viewpoint of Chen Zhen-Hsiang and Li Chi-Jen, international subcontracting manufacture can be discriminated in its scope to include four stages of the industry value chain, which are the R&D-based design of products, the production and assembly of products, the establishment and popularization of brands and the marketing services. The essence of international subcontracting manufacture is the inter-firm strategic alliance (Chen Zhen-Hsiang, Li Chi-Jen, 1997; Huang Ming-Zhang, 2002; Huang Yen-Tsung, 2002). This constitutes the exchange activities and production activities within inter-firm alliances (the production activity refers to engaging in various kinds of value activities among the organizations) and the types of different interactive relations among exchange and production activities (Grandori, 1997b, p.903). The “interaction” refers to the information and the resources exchange among firms, which includes the physical assets such as raw materials, (half-) end products and machinery equipment, intangible assets such as relationships and goodwill and capabilities such as procedure and knowledge (Barney, 1991), and in other words refers to information inflow and resource flow (Lame, Speakman & Hunt, 2000; Tsai, 2000). As for the “relationship” type, it shapes the interaction modes during the process of exchange and production activities and will influence the flow, rate, and the quality of information inflow and resource flow to some degree (Ring & Van de Ven, 1992; Heide, 1994; Sobreo & Schrader, 1998; Buvik & Reve, 2002). In addition, seeing that Taiwan’s international subcontracting manufacturers receive the ODM task from foreign customers, they acquire knowledge through the interaction within the networking organizations and start inter-organizational learning, exchange/transference and integration of knowledge. After they finish the task, the new knowledge, technology and experience will become the competitive competence for international subcontracting manufacturers. Specifically speaking, it will improve the organizational performance once the they build up the appropriate “relational capital” (Kale et al., 2000), “relational capability” (Zaheer & Venkatraman, 1995; Lorenzoni & Lipparini, 1999), “alliance capacity” (Kale, Dyer & Singh, 2002), or even “network learning” (Powell, Kogut & Smith-Doerr, 1996; Gulati, 1999) and the “social capital” (Nahapiet & Ghoshal,. 3.
(4) 1998; Yli-Renko, Autio & Sapienza, 2001; Adler & Kwon, 2002 ) among the networking manufacturers. The actors who own more connections have nearer social distances with all other actors and predominate in resource acquisition and information transmission; these actors may easily become the “prominent actors” because they have low costs and find it easier to acquire the resources they need. On the contrary, for the actors who connect less with other actions in the network, the communication costs will become higher, and it will become difficult for them to influence others or get influenced by others. We define this situation as “peripheral”. The power of roles and the patterns of interaction can be understood more through this relational analytic approach. Therefore, the arrangement of this research first discusses the interdependent relation between Taiwan’s subcontracting manufacturers and domestic and foreign customers in specific businesses, the product sales and production, and then discusses through these interdependent network relations, the different position and role that the actors occupy on the basis of the number of connections with other actors in the network.. 1.4 The objectives of this study In order to understand relationships among OEMs and ODMs in Taiwan’s IE industry, the approach of Social Network Analysis (SNA) will be adopted in the research. This study seeks to describe the network relations of OEMs and ODMs in Taiwan’s IE industry as fully as possible, tease out the prominent patterns in such networks, trace the flow of information (and other resources) through them, and discover what effects these relations and networks have on people, organizations and their performance. The results of this study will reveal the process of production and business activities of OEMs and ODMs in Taiwan. In addition, what kinds of inter-dynamic relationships exist among OEMs and ODMs in Taiwan and how the relationships affect business performance will be explored in this study. Furthermore, how to recognize and confirm the core position of firms through the analysis of social networks, and how the government takes advantage of these core firms to assist policy support and implementation will be answered from this study.. 2. Literature Review on Social Network analysis 2.1 Origin of social network analysis. 4.
(5) A number of disciplines have shaped the development of social network analysis.. German. psychiatrist Jacob L. Moreno (1934), who developed an approach known as sociometry, 1 used network diagrams to represent interpersonal relations in small groups.. British anthropologists. John A. Barnes (1954), Elizabeth Bott (1957), and J. Clyde Mitchell (1969) investigated the structure of community relations in tribal and village societies. Some sociologists at Harvard University explored the patterns of international relations and established the mathematical basis for the analysis of social structure (White, 1963; 1970; White, Boorman and Breiger, 1976). Their extensive research, specifically focusing on ego-centric networks, soon firmly established social network analysis as a method of structural analysis in the 1960s and early 1970s (Scott, 2000). Influenced by mathematically-orientated structural analysts, some scholars started using algebraic concepts to model structural relations and developed advanced techniques for network analysis in other disciplines. The work of Linton C. Freeman (1979) to develop a measure of the centralization of a network for example represents one of the most important measurements in social network analysis. Generally speaking, there have been three distinct research traditions (Wellman, 1983): the concept of the social network, social structure as a social network, and structural explanations of social/political processes. Due to limitations in the scale of social systems and the complexity of these sociological analyses, network analysts use matrices in which each cell represents a potential tie from one network member to another. In addition, they use standard statistical methods, supplementing them with such measures of network properties as the density of ties and the centrality of members. Blockmodeling, for example, has helped researchers to discover basic social structures and to compare actual networks with hypothesized structures. Social network analysis focuses on patterns of relations among people, organizations, states, etc. (Wasserman & Faust, 1994). This research approach has rapidly developed in the past twenty years, principally in sociology and communication science. The International Network for Social Network Analysis (INSNA) is a multidisciplinary scholarly organization, which publishes a refereed journal.. 2.2 Brief Description of Social Network Analysis Social network analysis (SNA) encompasses theories, models and applications that are expressed in terms of relational concepts or processes. Some theoretical concepts have been the inspiration for the development of specific network analysis methods. Pioneers from different disciplines have taken particular aspects of the theoretical idea of social groups to develop more precise social. 1. Moreno used sociometry, which was also the title of a journal found by Moreno in 1937, as a method to investigate how psychological well-being is related to the structural features of what he termed ‘social configurations’. 5.
(6) network definitions. There are three major mathematical foundations of network methods: graph theory, statistical and probability theory, and algebraic models. First, graph theory, which generates the mathematical analysis of nodes and links (Burt, 1980), provides an approximate representation of a social network and a set of concepts that can be used to study formal properties of social networks. It gives us mathematical operations and ideas in which many of these properties can be quantified and measured. Its terminology can be used to label and denote many social structural properties (Scott, 2000). For example, we use graph theory as a model of a social system consisting of a set of actors and the ties between them. Actors in a network are represented as nodes of a graph, while ties between actors are represented as lines between the nodes of the graph. In addition, graph theory also gives us the ability to prove theorems about graphs and representations of social structure (Barnes and Harary, 1983). Second, statistical theory is important as people begin to study reciprocity, mutuality, balance, and transitivity (Wasserman and Faust, 1994). Research on statistical models for social networks increased in the 1980s and development of more advanced statistical models continues today. Simple loglinear models of dyadic interactions are now commonly used in practice using either a nominal or an ordinal scale (Scott, 2000). Statistical models become necessary when researchers test hypotheses about various structural tendencies from multivariate relational network data. For example, special statistical procedures designed to formalize social network analysis notions about the density of ties, the centrality of actors and structural equivalence may contribute to a unique analytical toolbox that further distinguishes social network analysis from conventional social analysis (Wasserman and Faust, 1994; Erickson, 1997; Scott, 2000). Third, algebraic models are widely used to study multirelational networks such as kinship systems (White, 1963), friendship networks (Brass, 1984), and network role structures (Mandel, 1983; Boyd, 1990; Pattison, 1993). A network structured by algebraic models may refer either to relations among individuals or to relations among other social units such as blocks in a blockmodel (Pattison, 1993). In particular, algebraic methods allow for a general means of analyzing network representations into simple components, a property that may greatly enhance the descriptive power of the representation. Discussed in the above theoretical developments, three different notational schemes are used to represent a wide range of network data (Wasserman and Faust, 1994). First, graph-theoretic notations become most useful for centrality and prestige methods, cohesive subgroup ideas, as well as dyadic and triadic methods. They provide a straightforward way to refer to actors and relations. The data for each relation are presented in a two-way matrix, termed a sociomatrix, where the rows and columns refer to the actors making up the pairs. Sociomatrices are adjacency matrices for 6.
(7) graphs. Second, sociometric notation is often used for the study of structural equivalence and blockmodels (White, Boorman and Breiger, 1976). The third notation is algebraic, which is most appropriate for role and positional analysis and relational algebra. Such analyses use algebraic techniques to compare and contrast measured relations, and derive compound relations. There are a variety of techniques in which network data can be collected such as questionnaires, interviews, observations, archival records, experiments, and other qualitative techniques (Wasserman and Faust, 1994). Questionnaires and interviews, for example, are very useful when the study objects are human beings. They can be implemented under several formats, e.g. roster or free recall, free or fixed choice, ratings or complete rankings. Network data also can be obtained from archival records such as journal articles, newspapers, and minutes of meetings (Burt and Lin, 1977). Throughout the network data collection procedure, a specific group of members will be identified from the actor population. Knoke (1994: 280) provided four techniques to locate the key actors: 1. Positional methods: Persons or organizations in the key roles such as the elected or executive positions in the units; 2. Decisional methods: Actors influencing or participating in the decision-making process; 3. Reputational methods: Actors who are believed by knowledgeable observers to possess or exercise actual or potential power in the system; and 4. Relational methods: Actors who maintain important relationships with other members who are not found through reputational queries in the system. Network data gathered from the above methods attempt to measure the ties among all the actors in the set, in addition to collecting actor attribute information. The items regarded as the attributes of particular individuals such as gender and education can be analyzed through analysis of variables in the statistical procedure where attributes are measured as values of particular variables. Relational data, on the other hand, are the ties and connections that relate one to another. By undertaking quantitative and statistical counts of relations, network analysis, which is employed to be the measure of network structure, should illustrate attribute and relational data. Additionally, the drawing software will be helpful to illustrate network data and analyses. The primary tenet of network analysis is that the structure of social relations determines the content and outcomes of those relations. Garton et al. (1997) synthesize literatures in past years and list four units of analysis: (1) Relations: relations are characterized by content, direction and strength. The content refers to the resource that is exchanged. In social networks, pairs may exchange different kinds of information, such as social matters or work-related. The relations between people may have 7.
(8) direction; in other words, a relation is directed or undirected. When one of dyad gives information and the other only receives it, the relation is directed. Besides content and direction, relations also differ in strength. We can decide the degree of strength according to the frequency of communication, the amount of information exchanged and the importance of the information. The strength of relations that the dyad communicates once a day is greater than communication weekly or yearly. (2) Ties: A tie connects a pair of actors by one or more relations. Pairs may maintain a tie based on one relation only or a multiplex tie based on many relations. Thus, ties also have characteristics like content, direction and strength, but they are often referred to as weak or strong. Actors that are connected at short lengths or distances may have stronger connections; actors that are connected many times may have stronger ties. Ties that are weak are generally non-intimate connections that are infrequently maintained. Strong ties include combinations of intimacy, self-disclosure, provision of reciprocal services, frequent contact, and kinship (Garton et al., 1997). (3) Multiplexity: the more relations in a tie, the more multiplex the tie. Social network analysts have found that multiplex ties are more intimate, voluntary, supportive and durable (Wellman and Wortley, 1990). (4) Composition: the composition of a relation or a tie is derived from the social attributes of both participants. For example, a tie lies between different or same-sex dyads, between a supervisor and an underling or between two peers. The centrality of actors and the density of ties are perhaps the two most important and fundamental measures of structural relations. An actor is prominent if the ties of the actor make the actor particularly visible to the other actors in the network. Freeman (1979) as noted above measures the centralization of a network, based on the difference between the centrality of the most central unit and the other units. According to Freeman, centrality can be determined by three types of relation measurement: 1) degree, which refers to the number of direct ties between an actor and other actors in a network; 2) closeness, which refers to the extent to which an actor can reach a large number of other actors in a small number of steps; and 3) betweenness, which refers to the extent to which an actor has a unique path between other actors, so that the latter must deal with the former if they are to communicate. The centrality measurement is critical in most network studies. For example, Brass and Burkhardt (1992; 1993) found that assertiveness and coalition building were related to degree and closeness 8.
(9) measures of centrality. Typically, the general procedure involved in any measure of graph centralization is to look at the differences between the centrality scores of the most central points and those of all other points. In other words, centralization is the ratio of the actual sum of differences to the maximum possible sum of differences. It describes the extent to which the cohesion is organized around particular focal points. In sum, the primary purpose of a graph centralization measure is to express how tightly the graph is organized around its most central points. Another important measurement of structural relations is density, which describes the general level of cohesion in a graph. The density of a graph is defined as the number of lines in a graph, expressed as a proportion of the maximum possible number of lines (Scott, 2000). Although different measures of density can be used to evaluate the cohesiveness of a graph, a subgroup, a blockmodel, or an affiliation network (Wasserman and Faust, 1994), this study will focus on the measure of ties in the graph generated from network data. The most direct way to study a social structure is to analyze the patterns and strength of ties linking its members. These ties linking nodes in a social system are used to explore how structural properties affect behavior beyond the effects of normative prescriptions, personal attributes, and dyadic relationships. They also provide opportunities and constraints because they affect the access of people and institutions to such resources as information and power. The debate on effects of strong ties and weak ties has been addressed by scholars (Granovetter, 1973; 1982; Nelson, 1989). Weak ties provide people with access to information and resources beyond those available in their own social circle, but strong ties provide close support systems in some circumstances and are more readily available. McPherson, Popielarz and Drobnic (1992) found that weak ties and network connections that span greater distance in sociodemographic space are positively correlated with people leaving current groups and joining new ones. Nelson (1989) investigated the relationship between social networks and conflict in 20 organizations and showed that low-conflict organizations are characterized by higher numbers of inter-group strong ties, measured as frequent contacts, than are high-conflict organizations. The comparison between strong and weak ties is ambiguous, and this provides an entry point for one of the major analytical contributions of this project proposal. More particularly, it is the intention of the project to investigate the probably non-linear nature of the relationship between strength of ties and measures of performance. This is spelled out below in section 3.5.. 3 Methodologies 3.1 Research questions. 9.
(10) The focus of this study is on the modeling of entrepreneurial social networks arising from questionnaire and expert surveys taken from the fieldwork. Three issues stand out as problematic. First, what kinds of relationships of networking and cooperation exist among OEMs and ODMs in Taiwan? In general, by examining the pattern of relationships among firms, groups emerge as highly interconnected sets of actors known as cliques and clusters. In other words, a group is an empirically discovered structure. From this study, we can also know who belongs to a group, as well as the types and patterns of relations that define and sustain such a group. The second issue is which firm(s) might occupy the core positions of the network of OEMs and ODMs in Taiwan. The central positions who share empirically-identified positions are likely to share similar access to informational resources and have greater access to diverse sources of information, while other positions may have a limited pool of new ideas or information on which to draw. Besides, by means of blockmodeling, the study can partition social network actors while simultaneously taking into account role relationships such as giving or receiving orders, socializing, collaborating, and giving or receiving information. The third issue is whether these networks and cooperation relationships have impacts on the innovative performance of the organization. The indicators of organizational innovative performance chose here include two categories: one is the learning performance which contains three. capabilities:. value-conception. competencies,. value-realization. competencies,. and. value-delivery competencies. The other category concerns financial performance: ROI, sales growth rate, and ROA etc.. 3.2 Research Scope and Unit of Analysis This research centers on developing a model of entrepreneurial network analysis, particularly with regard to the OEMs and ODMs in the IE industry. The main operating categories focus on OEMs (Original Equipment Manufactures) and ODMs (Original Design Manufactures) of the IE products for foreign customers. Among them, the IE products include systems products (such as desktop computers, notebook computers and servers), peripheral products (such as monitors, CD-ROM drives and scanners), and module components (such motherboards, chassis and network cards). The research also conducts an assessment to measure how the interaction and interdependence among them affect the industrial performance. In order to analyze these, the interactions (or relationships) that take place among firms are tested. Therefore, the main point of this research is the inter-dynamic relation between Taiwan’s OEMs and ODMs and their domestic and foreign customers in order to understand how Taiwan’s subcontracting manufacturers perform in terms of. 10.
(11) organizational innovation achievements. The analysis proceeds through separate and comparative analysis of OEM and ODM structures and then their interrelations.. 3.3 Methodology The first question is explored using a combination of approaches, in order to build an entrepreneurial social network model of the OEMs and ODMs in Taiwan’s IE industry. One input is derived from the primary data from the annual reports of firms. Another input involves an inductive research strategy, based on questionnaire and experts survey of managers. The second research question, based on the collected data from the first question, will employ SNA and its package software, Pajek, to carry out the analyses and explanations. In other words, after data coding and editing, a matrix table with relational data is merged into the network software, Pajek. In addition, to analyze the relationships among firms, network data are run by a drawing software in order to illustrate the networks. Regarding the last question, the appropriate statistical methods will be used as necessary in this study. A social network is a set of people (or organizations or other social entities) connected by a set of social relations, such as friendship, co-working or information exchange (Garton, Haythornthwaite & Wellman, 1997). Therefore, SNA is the mapping and measure of relationships and flows between people, groups, organizations, or other information/knowledge-processing entities. In other words, SNA provides both a visual and a mathematical analysis of human relationships.. 3.4 Procedures and Research Structure This research will be divided into five steps as follows (see Figure 1). Step 1: Define the question domain. Step 2: Literature review of the IE industry, especially in OEM and ODM firms, Social Network Analysis and industrial network theory, and research design (including questionnaire design and implementation). Step 3: Build the model of the entrepreneurial social network, including four main networks of relationships: attribute, business, financial, and external interaction with information on actors, resources, activities and interactions. Step 4: Measure organizational performance by the outcomes of networks and cooperation relationships. Step 5: Provide strategic managerial suggestions for OEM and ODM firms in Taiwan’s IE industry.. 11.
(12) Step 1 Define the question domain. Step 2 of Literature review and research design. The entrepreneurial social network analysis for OEM & ODM firms in Taiwan＇s Information & Electronic industry. Information & Electronic Industry. Social Network Analysis. Design of Questionnaire. Step 3 of Data collecting. Industrial Network Theory. Questionnaire and experts interview. model of Entrepreneurship network for OEM & ODM firms Domestic network for OEM & ODM firms. Financial network. External interaction network. Business newowrk. Attribute network. Foreign network for OEM & ODM firms. 1. Centrality Step 4 of analysis outcome. * Degrees * Betweenesss * Closeness. 2. Density. Organizational performance Step 5 of providing strategies. 1. Learning Capability * Value-conception competencies * Value-realization competencies * Value-delivery competencies 2. Financial indicators * Sales growth grate * ROA * ROI Figure 1: Research Framework and flowchart Note: The first year works show in the pink area The second year works show in the yellow area The Third year works show in the blue area. 12.
(13) 3.4.1 Framework of Entrepreneurial Networks The definition of industrial network by Hakansson (1982, 1987): “…consists of three variables: actors (individuals, groups or companies), activities performed by actors (transformations and transactions), and resources (physical assets, financial assets and human assets). Each of three classes of variables forms a network structure, and at the same time they are interwoven in a total network.” In our study, a variable of interpersonal relationships, adding a social point of view, is contained in this model. This model will cover four main networks of relationship: attribute, business, financial, and external interaction (Figure 2). For the purposes of operationalization, the. Actors. activ ities. common elements of each network are explained as follows.. 1. Attribute network This subsection discusses the attribute network, composed of firm scale, capital investment, R&D expenditure, employee profit sharing & stock ownership, initial public offerings, age, the number of the firm’s staff, etc. 2. Business network The content of the business network contains the main business of firms (such as manufacture, design, or others), sales revenues, market shares in domestic or international market, material supplier, equipment vendor, or any cooperation type (includes business contract, buyer-seller relationship)etc. 3. Financial network 13.
(14) The financial network includes gross profit, cross holding/cross ownership, correspondent bank (such as foreign bank; homeland/native bank; financial institute for local region: credit cooperative, farmer’s cooperative, or others), finance raising (such as debenture stock issuing; loan, leveraged buyout and loan), TSE (Taiwan Stock Exchange), OTC (Over-the-Counter) Listed Company, etc. 4. External interaction network The external interaction network consists of interpersonal relationships; exhibition activity; face-to-face meeting, telephone, fax, email, paper letters or memos; audio conference; videoconferencing; trade union/chamber of commerce; venture capital, etc.. 3.4.2 Learning Performance Jao (1996) sees core capability enhancement through cross-border contract manufacturing alliances as having three aspects: Value-conception competencies, Value-realization competencies, and Value-delivery competencies. Through such interactions, the OEMs and ODMs learn techniques and important experience. 1. Value-conception competencies: this includes technical capacities of product development and functional design; shortening the process of new product commercialization; grasping customer needs and knowing market trends well 2. Value-realization competencies: this includes lowering product defect rates and improving product quality; providing the flexible manufacturing for varieties of small-batch products; the number of patents, etc. 3. Value-delivery competencies: this includes the experience in international marketing, repairing or service; experience in building and improving international brands; experience in exploring and managing international distribution and logistics.. 3.4.3 Research hypotheses According to the proposed model (analytical framework), we advance six basic research hypotheses: Hypothesis 1: The better the attribute network between OEMs & ODMs and its contractors, the better the organizational performance will be. Hypothesis 2: The closer the business network between OEMs & ODMs and its contractors, the better the organizational performance will be. Hypothesis3: The closer the external interaction network between OEMs & ODMs and its contractors, the better the organizational performance will be. Hypothesis 4: The closer the financial network between OEMs & ODMs and its contractors, the better the organizational performance will be. 14.
(15) Hypothesis 5: These network structures in each respect do not differ significantly as between OEMs and ODMs (null hypothesis). Hypothesis 6: Integration between OEMs and ODMs does not significantly improve the overall business performance (null hypothesis). Apart from Hypothesis 5, all focus on the interaction between OEMs and ODMs. Hypothesis 5 allows an assessment of the benefits (if any) to be gained by upgrading from OEM to ODM status, while Hypothesis 6 assesses the overall gains (if any) from systemic integration. 3.5 New analytical contributions from the Research The assessment of these hypotheses will go beyond the procedures normally established in SNA to extend the power of the technique as applied to the practical case study. In the first place, the intention is to go beyond simple categories of yes/no links in the networks in order to quantify the impact of strong versus weak ties. As already noted, strong ties confirm centrality and consolidate patterns of strength, whereas weak ties allow extension into new areas of future strength. Both however have disadvantages that are reverse-images of these sources of gain. Strong ties can lead to “lock-in” to old methods and exclusion from emerging areas of dynamism. There have been many examples in recent history, such as the early attempt by U.S. industry to respond to the challenge from the rise of Japan by trying to consolidate the power of its giant companies in the 1980s. Equally weak ties can lead to “lock-out” from the current sources of better performance through peripheralizing the organization’s links. Would a midway position be better or worse than either extreme? This question was studied in a recent paper by Männik & von Tunzelmann (2006), which found on the basis of data for 5 Eastern European countries that a midway position was ‘best’ for some of the functions covered in Hypotheses 1 to 4 above, while an extreme position was ‘best’ in some of the others. In technology transfer, the midway position was the ‘best’ – avoiding the dual problems of lock-in and lock-out. Thus in this study we will consider whether the relations are non-linear, especially when amalgamating the individual hypotheses into the overall system assessment of Hypothesis 6. Secondly, through Hypothesis 5 we can begin to make a judgment about the dynamic gains from moving from OEM status towards ODM and later OBM. As seen above, OEM status is already becoming more demanding, so the jump to ODM is also becoming more difficult to achieve. But most scholars and many policy-makers believe that such a jump could be very beneficial for IE enterprises in Taiwan. Since we will have only cross-sectional data from the study we can make only limited inferences about dynamic processes, but we can see what the network structures look like separately for OEM and ODM status, and the gains in performance (if any) obtainable from changing the status in this way. 15.
(16) 3.6 Limitations of the Research In general, the data on social networks are collected by questionnaires, interviews, observations. People are often asked to identify the frequency of communication with others as well as the medium of interaction. Questions may refer to a specific relational content such as “socialize with” or “give advice to” within a given time frame. Besides, respondents are asked to think about each member of their company, to identify the means of communication for each type of relation, and to recall behavior that took place over a broad time frame in order to capture as much information as possible. There is a drawback in using SNA method as to which data are based on recall and may be less reliable. It is also quite difficult to include everything in one model. Moreover, not all interaction relationships are included in this model. Strictly speaking, the whole actors, resources, activities, and personnel relationships for the full chain of Information & Electronics industry in Taiwan could not be contained in this model for my research. Nevertheless some key elements and strategic issues are studied in both breadth and depth using this approach.. 4. Expected results and contributions The overview of the Information & Electronics industry in Taiwan has not been able to establish much consideration to date of the effects of network relations on organizational performance in Taiwan, even though the concept of Social Network Analysis has adopted in many fields and received much attention from scholars worldwide. In this study, we are adapting the SNA approach to analyzing the measurement of organizational performance. This study seeks to describe network relations of the IE industry in Taiwan as fully as possible, tease out the prominent patterns in such networks, trace the flows of information (and other resources) through them, and discover what effects these relations and networks have on people, organizations and their performance. From the government and policy perspective, this study also casts light on how to attract foreign firms to invest continually in this area and form industry cluster effects via the “position analysis”. Through such analysis the government in Taiwan may be able to deliver related information and integrated resources, and assist or inversely control the whole industry’s development policy. The results of this study can be expected to reveal the process of production/business activities of the IE industry in Taiwan, and to explore what kind of inter-dynamic relationships exist among IE firms and how the relationships affect business performance. Furthermore, the questions of how to recognize and confirm the core position of firms through the analysis of social networks, and how the government can take advantage of these core firms to assist policy support and implementation, and similar issues, will be answered from this study.. 16.
(17) References（略）. 17.
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