کارگزاری در شبکه های شرکت های کوچک و متوسط

This study focuses on SME networks of design and high-tech companies in Southeast Netherlands. By highlighting the personal networks of members across design and high-tech industries, the study attempts to identify the main brokers in this dynamic environment. In addition, we investigate whether specific characteristics are associated with these brokers. The main contribution of the paper lies in the fact that, in contrast to most other work, it is of a quantitative nature and focuses on brokers identified in an actual network. Studying the phenomenon of brokerage provides us with clear insights into the concept of brokerage regarding SME networks in different fields. In particular we highlight how third parties contribute to the transfer and development of knowledge. Empirical results show, among others, that the most influential brokers are found in the non-profit and science sector and have a long track record in their branch.

Firms are increasingly facing their own limitations in today's complex and demanding environment (Das and Teng, 2002, Duysters and de Man, 2003 and Eisenhardt and Bird-Schoonhoven, 1996). The need for cooperation is evident in an environment characterized by uncertainty, complexity and rapid technological progress (Acs et al., 1996). Small and medium-sized enterprises in particular are faced by a dilemma. On the one hand SMEs feel the urge to cooperate with others in order to acquire knowledge and other competencies; on the other hand they often face difficulties in finding partners and often they lack the knowledge base to be able to absorb the required knowledge. This dilemma clearly points to a need for intermediaries in order to deal effectively with the complex environment. Bridging organizations are needed to compensate for weaknesses in the local innovation system (Sapsed et al., 2007). Since intermediaries are becoming more and more important the need arises to provide SMEs with insight into what makes them so valuable. This information enables them to decide with what kind of intermediary they should cooperate. Bridging organizations are gradually gaining attention in SME literature, but there is a clear lack of understanding regarding intermediaries operating within SME networking structures (Klerkx and Leeuwis, 2008). The subject of most network literature is related to the discussion on social capital versus structural holes. New in network literature is the idea of intermediaries whose commercial goal is to bring heterogeneous parties together and co-develop innovations, and not just exploit the knowledge (Obstfeld, 2005). The few existing studies in this area are based on research focusing on large enterprises (Hanna and Walsh, 2002, Pittaway et al., 2004 and Shaw, 2006) or qualitative research in industrial districts (Kunmar et al., 1998 and Morrison, 2008). Although SMEs are believed to provide vital energy and stimulate growth (Heilbroner, 1984 and Schumpeter, 1934) and recently regained popularity as an important topic in the academic literature and policy-making programs (Audretsch and Thurik, 2001, Corbetta et al., 2004, OECD, 2000 and Shane and Venkataraman, 2000), quantitative research on networks in entrepreneurship has been limited to the most rudimentary of network data, especially in the field of regional clustering (Burt, 2000 and Ter Wal and Boschma, 2009). In addition the support instruments in programs unfortunately do not increase the interaction between SMEs and knowledge providers from outside the business sector (Kaufmann and Tödtling, 2002). It is still unclear how intermediaries can successfully bridge gaps or how specific characteristics influence the capacity of brokers. The main focus of this study is on the SME network of design and high-tech companies in Southeast Netherlands. Although we consider SMEs, the far majority of firms in these industries are small firms. Design is seen as increasingly important in product development and there is an increase in efforts to establish co-operations between design and high-tech organizations. The design sector is a dynamic but highly fragmented industry. By highlighting the personal networks of members across design and high-tech industries, the study attempts to identify the main brokers in this dynamic environment. In addition, we investigate whether specific characteristics are associated with these brokers. The main contribution of the paper lies in the fact that, in contrast to most other work, it is quantitative and that it focuses on brokers identified in an actual network (based on both suppliers and users of the knowledge infrastructure). Studying the phenomenon of brokerage will provide more insights into the concept of brokerage regarding SME networks in different fields. In particular it will highlight how third parties contribute to the transfer and development of knowledge. The remainder of this paper is structured as follows. In the literature review section we provide a brief overview of the theory and the empirical field in which the research takes place. Then the methodology used to explore the SME network is described. We will end this paper with the main conclusions and a discussion of the findings.

This paper investigated the existence of main brokers in the network across design and high-tech industries and modeled the relationship between a person‘s brokerage capacity and characteristics. Since the world surrounding organizations is becoming more and more complex, organizations will have to rely more on brokers to access external knowledge. Many companies find that they do not possess the necessary (scientific) resources to cope with additional burdens and seek external support to overcome their own cognitive and technical limitations. It is argued that the most successful brokers must have specific characteristics that enable them to transfer and develop knowledge optimally. The paper highlights individual's affiliation, kind of partner and kind of partner information as sources of brokerage capacity influence. Empirical results show that there are actors with powerful brokerage capacity in the actual network. Instead of identifying brokers in the actual network, we could have started our research with a preselected group of brokers and constructed the network from there. However we would have missed information on less obvious brokers in the field. Furthermore we are not limited to a certain kind of broker or a certain sector. Our research enabled us to generate knowledge regarding brokerage in general. Consequently results can be relevant to other industries in dynamic environments in the Netherlands. Empirical results also show that the most influential brokers are found in the non-profit and science sector and have a long track record in their branch. It seems that discussing finance is not sufficient. Actors in the field foremost like to discuss practical support in the form of valuable contacts and innovation-related information with intermediaries. However, finance, marketing and operational information is also discussed with them. The results show what specific characteristics influence the capacity of brokers. They also provide insight into how brokers bridge the cognitive and technical distance between parties. In other words, the research indicates how companies can reach a better balance between the two forms of social capital. The research findings imply that SMEs should get involved in projects in the non-profit or science sector. Furthermore SMEs or even non-profit organizations whose brokerage capacity is not in line with their ambitions should invest in connections with branch experienced people with a broad knowledge base. From a non-profit consultant point of view this research is also interesting. They often have difficulties in proving their successes. Sometimes merely mentioning contact information leads to a successful match. Sometimes brokerage takes much time and effort and still the involved parties are dissatisfied. Moreover the effectiveness of non-profit organizations is subject to discussion in the Netherlands. Branch associations for example are already dozens of years old. Their contribution to the individual company is difficult to perceive. This research shows that the intervention of their consultants (eventually) is of value to companies. Still, in the high-tech and design sector new product-service combinations have been established which have not been created through traditional interventions. Traditional supply-side innovation policies seem to be insufficient to meet the challenges posed in promoting competitiveness. At the European Union level interest is focused on public procurement as a means to spur innovation (Edler and Georghiou, 2007). Regarding the effectiveness of government expenditures it is relevant to know how new networks come to exist and what roles intermediate organizations play. Measurement at individual level gives a profound picture of actual contributions. It is now possible to review policy from the bottom up. Regarding the limitations of this study, we have little information on the representativeness of our sample for the total group of people involved in design and high-tech industries. A possible source of bias may be that the persons in the initial sample and first two waves have the advantage of being among the first mentioned. They have had more chance of being mentioned more often. Another possible source of bias is that the invitation to participate in the survey was signed by ourselves. Respondents might consider ourselves to be associated with a particular group, non-profit, and hence this may influence their willingness to participate in the survey. Furthermore we have asked respondents to mention important Dutch partners in Southeast Netherlands thereby excluding foreign subsidiaries in the network. The exclusion is a limitation of our study. Foreign subsidiaries are more innovative compared to domestic firms. Their innovativeness is heavily based on knowledge transfers from associated companies in addition to local knowledge. Therefore a foreign subsidiary can be regarded as an important partner. On the other hand they are inclined to cooperate less with domestic public knowledge institutions, especially when proprietary knowledge is concerned (Van Beers et al., 2008 and Sadowski and Sadowski-Rasters, 2006). It seems that foreign individuals act as gatekeepers. Although some respondents have mentioned foreign partners who are working in the Netherlands our research did not take this perspective into account. However relations in the field are dynamic patterns of growth and development and (brokerage) positions in a network partly reflect the past. The network represents a network across design and high-tech industries in the Southeast Netherlands, with all its specific structures. In other countries, other relationships are present. For example, in China the absence of institutional trust based on unpredictable government action and control, mistrust of strangers and shortage of reliable market information, leads to an absolute reliance on trust-based personal connections as a means for almost any transaction. The so-called Guanxi is the Chinese version of social networks ( Zhou et al., 2007). The interaction between non-profit, science and profit sector are different in this country; therefore characteristics of brokers will be different. Related to this point, relations of people will vary per lifecycle stage of the industries. We noticed that collaborations between design and high-tech industries have only recently been stimulated. This particular network may be in an early life cycle stage. We look at brokerage capacity from a network perspective. Network analysis is limited to tertius gaudens measurements. It is not yet possible to measure closed triple relations. Progress in those areas would be interesting. We do not measure the amount of brokerage an actor actually performs, although opportunity and actual behavior will probably correlate highly. What level of brokerage, what exactly is being brokered is also not measured (Burt, 2005). Future, qualitative, research can complement this investigation by taking an in-depth look at what brokers actually do. In spite of these limitations, this paper represents one of the first empirical contributions discussing the issue of brokerage in SME networks. A better understanding of brokers in SME networks can be a starting point for more work on the managerial and policy implications of brokerage.