شبکه و اکتشاف فن آوری های رمان : فاصله فنی، بین مرکزیت و چگالی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|20097||2008||15 صفحه PDF||سفارش دهید||11845 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Research Policy, Volume 37, Issue 10, December 2008, Pages 1717–1731
This paper aims to understand better the innovation potential of a firm’s alliance network. Here we analyze the role of an alliance network in terms of the technological distance between partners, a firm’s network position (centrality) and total network density. We study how these three elements of an alliance network, separately and in combination, affect the ‘twin tasks’ in exploration, namely novelty creation on the one hand and its efficient absorption on the other hand. For an empirical test, we study technology-based alliance networks in the pharmaceutical, chemical and automotive industries. Our findings indicate that successful exploration indeed seems to require a delicate balance between these two exploration tasks. A second conclusion is that different network positions yield different pay-offs in terms of the number of explorative patents. In other words, success rates for exploration are not spread equally across firms. However, position alone does not tell the full story. Our empirical findings clearly indicate that exploration success also depends on the other two dimensions of embeddedness, namely technological distance and network density. The three elements of network embeddedness need to be considered jointly in order to understand their complementary effects on both novelty creation and absorptive capacity.
There is now increasing consensus in the academic literature that a firm’s embeddedness in a network of interfirm relations matters for its economic and innovative performance (Nooteboom, 1992, Hagedoorn, 1993, Powell et al., 1996, Rowley et al., 2000, Ahuja, 2000a and Owen-Smith and Powell, 2004). The empirical evidence has indicated that this relationship between embeddedness and innovation can be found in industries as diverse as chemicals (Ahuja, 2000a), biotechnology (Baum et al., 2000 and Powell et al., 1996), semiconductors (Stuart, 1998), textiles (Uzzi, 1997), personal computers (Hagedoorn and Duysters, 2002) and banking (Zaheer and Bell, 2005). More recently, some studies have started to unravel this notion of embeddedness in order to understand in what specific ways it contributes to a firm’s innovation performance. Here, characteristics of partners have been studied such as their degree of innovativeness (Stuart, 1998) as well as the properties of alliances such as the role of formal governance mechanisms (Mowery et al., 1996), equity vs. non-equity alliances (Rowley et al., 2000) or the role of repeated contacts (Wuyts et al., 2005). Beyond the dyad level, studies at the network level have shown that the properties of an alliance network also affect innovation. Here it has been shown that apart from the number of direct ties (Ahuja, 2000a and Shan et al., 1994) also a firm’s indirect ties (Ahuja, 2000b) and the redundancy among these ties (Ahuja, 2000b, Baum et al., 2000 and McEvily and Zaheer, 1999) affect its innovation performance. In most of these studies an important function of alliances is that they function as ‘pipelines’ through which information and knowledge flows between firms (Owen-Smith and Powell, 2004). This focus on the diffusion potential of alliances may not be surprising as most studies on the role of embeddedness have been assuming conditions of relative environmental stability. Here, embeddedness refers to routinisation and stabilization of linkages among members as a result of a history of exchanges and relations within a group or community (Gulati, 1998). Under such structure-reinforcing conditions, the role of embeddedness is increasingly well understood (Gulati, 1998, Madhavan et al., 1998 and Koka et al., 2006). These conditions connect with March’s category of exploitation (1991) in which environmental uncertainty is rather limited and the focus is on the refinement and extension of existing competences and technologies. The rationale for teaming up with partners then is formed by possibilities to obtain complementary know-how (Teece, 1986) and/or to speed up the R&D process in industries where time-to-market is crucial. Here, cooperation is attractive as partners have a good understanding of the relevant issues at hand and alliances enable a rapid diffusion of knowledge among partners, enhancing the efficiency and speed of cooperation (Gilsing, 2005). In this strand of literature, an implicit underlying assumption is that similarity of partners is beneficial for learning and innovation. This follows from Cohen and Levinthal’s (1990) influential notion of absorptive capacity, where the idea that the extent to which firms can learn from external knowledge may be largely dependent upon the similarity of the partners’ knowledge bases. In a similar vein, different studies have demonstrated that learning potential declines with an increase in dissimilarity of knowledge stocks (Hamel, 1991, Lane and Lubatkin, 1998, Mowery et al., 1996 and Fleming and Sorenson, 2001). So, for inter-organisational learning in exploitation, similarity is attractive and distances in knowledge and cognition (cognitive distance) constitute a liability. This raises the question of how to understand the role of network embeddedness in view of exploration that can be characterized by breaking away from the established way of doing things, with a focus on the discovery and experimentation of new technologies (March, 1991 and Nooteboom, 2000). By its very nature, exploration is not about efficiency of current activities, but rather forms an uncertain process that deals with the search for new, technology-based business opportunities (Rowley et al., 2000 and Nooteboom, 2000), requiring the production of new insights and knowledge. This points to a different role of a firm’s alliance network, namely its recombination potential for new knowledge creation rather than its function as a channel for diffusion of existing information and knowledge for exploitation. Existing literature has largely ignored this role of alliances for novelty creation and is therefore unable to explain the development of new knowledge and competencies ( Hagedoorn et al., 2000 and Phelps, 2005). In contrast to exploitation, in this process of exploration partner similarity is unattractive whereas cognitive distance between partners forms an important asset. The main aim of this paper is to develop an understanding of the role of a firm’s alliance network in view of exploration. To do so, we will first consider this role of cognitive distance between firms in order to understand how far dissimilarity between partners is attractive in view of exploration. Second, we combine such a cognitive view with a social structural one. In this way we complement the literature that has predominantly focused on the role of economic and social factors regarding alliance formation and the role of network embeddedness (Gulati, 1998). A cognition-based understanding of these processes, however, is still in its infancy (Moran, 2005). Combining the role of cognitive and social structural factors may provide us with new insights into what constitutes an optimal network structure for exploration. As we will argue, for exploration firms are faced with a dual task. On the one hand, they need to develop access to heterogeneous sources of knowledge and in this way create a potential for novel combinations. This requires an emphasis on diversity and disintegrated network structures, which is related to Burt’s argument (1992) stressing the benefits of access to non-redundant contacts to obtain novel information (novelty value). On the other hand, firms need to make sure that such novel knowledge, once accessed, is evaluated, and when proven to be valuable is adequately absorbed. This process favours more homogeneous network structures in view of integrating the diverse inputs obtained from distant partners (Hansen, 1999). This is more in line with Coleman’s view (1988) stressing the benefits of redundant network structures. Given these differences between the two tasks, we claim that a firm’s network will impact differently on each task. So, an important contribution of this paper is that it investigates how far optimal embeddedness for novelty creation may form a burden for absorptive capacity and vice versa. In this way, we may shed new light on the ongoing debate on the validity of the arguments by Burt, favouring structural holes, versus those of Coleman, favouring closure. This paper is structured as follows. In Section 2 we elaborate our theoretical argument and formulate a number of hypotheses. Then, in Section 3, we present details about the data, the specification of variables, and the estimation method. In Section 4 we present our main findings. Finally, in Section 5, we provide a discussion of the results, the main conclusions and some indications for further research.
نتیجه گیری انگلیسی
The joint impact of the three explanatory variables is best understood and consistent with the theoretical analysis (as specified in formulae 6–8), if we take all variables in model 6 – linear, quadratic and interaction terms – simultaneously into consideration. To keep the analysis tractable, we start from the observation that firms can control or influence relations only with their direct partners and have virtually no possibilities to do so beyond their ego-network (Bae and Gargiulo, 2003). Therefore, it seems reasonable to consider global density as an exogenous variable for the innovating firms. That leaves them with two variables for dealing with their alliance network when engaging in exploration endeavours, namely their network position and the technological distance with their partners. Consider Fig. 2 that represents the joint effect of technological distance and network centrality, keeping network density constant at the mean level. Full-size image (36 K) Fig. 2. Explorative innovation performance at mean level of network density. Figure options As the figure shows, a (highly) central position in the network yields ample potential for a high exploration performance, if one works with partners at a very limited technological distance, and when supported by ‘sufficient’ density (mean level). However, if working from such a central position with partners that operate at a large(r) technological distance, performance drops rapidly. The interpretation of this finding may be as follows. Being highly central implies a higher chance of being faced with different kinds of knowledge and information (Burt, 1992). This is beneficial for novelty value but also creates a need to understand and integrate potentially unrelated information. Therefore, being a highly central player requires exploration at small technological distances in order to be able to absorb knowledge from all parts of the network. The price for not doing so is a sharp decrease in one’s innovation performance. Also note that the highest impact on explorative innovation performance is found for firms with a central position especially at a very small technological distance. In contrast, a highly peripheral position (at very low or minimal BC) is a liability as it shows a much lower performance compared to more central positions, although such positions initially show an increase in innovation performance when technological distance increases. Moreover, being at the periphery can be advantageous at very high levels of technological distance, where more central firms perform comparatively less well. Being at the periphery generally implies that one is outside the immediate sight of dominant and more central players. Because of this, selection forces to comply with dominant designs and existing systems of production, organization, technical standards and so on, may be somewhat less stringent. Hence, deviating from such prevailing ‘industry recipes’ (Spender, 1989) becomes easier (Gilsing and Nooteboom, 2005). As a consequence, firms at the periphery may enjoy more freedom to experiment with partners at a high technological distance. It might be that this strategy yields more radical innovations with potentially more technological and economic value. However, the way we measure our dependent variable (based on patent counts) does not take this into account, an issue we come back to when discussing limitations and possibilities for future research. Still, firms also need to consider the degree of overall density and how it conditions their choices regarding position and technological distance respectively. Consider therefore Fig. 3, showing the relation between density and betweenness centrality while keeping technological distance at its mean value. Full-size image (47 K) Fig. 3. Explorative innovation performance at mean level of technological distance. Figure options Here we see that the effect of density on innovation performance has a similar, curvilinear effect for both central and peripheral positions. In other words, irrespective of one’s position, high density inhibits the existence and utilization of diversity, and hence of novelty value, while at low levels it does not support absorption sufficiently. We also find the highest impact on explorative innovation performance at intermediate levels of betweenness centrality (at least when technological distance is kept at the mean level). However, a closer look at Fig. 3 reveals that high levels of network density in combination with high levels of centrality also offer a fairly high impact on exploration. In short, we can say that at average technological distances, central companies in (fairly) dense networks have an advantaged position to develop explorative innovations. Following our findings, we can conclude that our key argument is confirmed, claiming that successful exploration requires a delicate balance between the ‘twin tasks’ of novelty creation on the one hand and its efficient absorption on the other hand. We found that highly central firms enjoy the strongest improvements of their explorative innovation performance and this effect declines steadily when centrality decreases, or alternatively when technological distance increases. Peripheral positions show the least performance, although such positions can be attractive when cooperating with partners at a very large technological distance. In other words, success rates for exploration are not spread equally across network positions. However, position alone does not tell the full story. Our empirical findings clearly indicate that exploration success also depends on the two other dimensions of embeddedness, namely technological distance and network density. Therefore, an important conclusion is that the three elements of network embeddedness need to be considered jointly in order to understand their complementary effects on both novelty creation and absorptive capacity. This is an important finding and contributes to the literature in several ways. One is that it contrasts with the tradition in the literature on alliances and interfirm networks with its bias towards to the role of position (Powell et al., 2005). The message as conveyed from this study is that for exploration the value of a position depends on the technological distance from others and on the degree of network density. A second contribution is that the social network literature specifically considers ‘social distance’ between any two nodes (here firms) in the network, in terms of the number of links on the shortest path between them. Here we have added technological distance between any two firms. This has enabled us to go beyond the dominant focus on partners’ similarity and to understand the positive role of technological distance in exploration. Such a cognition-based view has been largely ignored by the literature with its main focus on the role of economic and social factors regarding alliance formation and the role of network embeddedness (Gulati, 1998 and Phelps, 2005). It also contributes to the literature on learning and innovation that stresses the recombination potential arising from distances in cognition (Nelson and Winter, 1982, Nooteboom, 2000 and Malerba, 2004), but leaves unexplained what are the associated social structural implications. Moreover, considering the role of global density enables one to go beyond the dyadic level, as has been mostly studied in the literature (Salancik, 1995, Gulati, 1998 and Powell et al., 2005). The focus on dyads reflects an undersocialized view of alliances and ignores how far positive effects of a central or peripheral position can be mitigated or amplified by the entire structure. We found that this structure, in terms of its density, indeed plays an important role and conditions the potential benefits of different degrees of centrality for exploration. Both for central and peripheral positions an intermediate degree of density seems to be most effective. In contrast, high levels of density may inhibit the existence and utilization of diversity, and hence of novelty value, while at low levels it does not support absorption sufficiently. This points to an interesting new insight that sheds a different light on the validity of the arguments of Burt versus Coleman. Success in exploration requires a dual emphasis on the benefits of non-redundant contacts for potential novel combinations as well as on network density for integrating the diverse inputs obtained from such contacts. In other words, it seems that both views convey some truth and may be seen as complements instead of opposites as stressed in the literature (Hansen, 1999, McEvily and Zaheer, 1999, Rowley et al., 2000 and Ahuja, 2000b). Limitations of this study, which may provide directions for future research, are as follows. One is that we have studied exploration that is new to the firm. In other words, we cannot substantiate our claims and findings beyond this relatively moderate degree of exploration. It therefore seems useful in future studies to consider more radical degrees of exploration such as the discovery of ‘newly emerging’ technologies (new to the industry) or ‘pioneering’ technologies (new to the world), respectively (Ahuja and Lampert, 2001). For these kinds of exploration one needs partners at presumably (much) larger technological distances than considered here and we anticipate that this will have major implications for the role of both betweenness centrality and density. A second limitation relates to our dependent variable. We have counted the number of explorative patents for each firm and in this way have treated all patents equally. Of course, patents differ in technological and economic value, and taking this into account would definitely enrich future work in this field. Weighing patents based on the number of citations that they receive seems a straightforward way to do this (Ahuja and Lampert, 2001). Such an approach would also enable studying the validity of our conjecture that peripheral firms have better possibilities for more radical exploration when compared with central firms. A final limitation is that we did not consider the effect of ‘tie strength’ on exploration. Different types of alliances can be weighted according to the ‘strength’ of the relationship as some authors have done (see Contractor and Lorange, 1988, Gulati, 1995b and Nohria and Garcia-Pont, 1991). This would require additional research regarding which alliance type is more instrumental for the exploration of new technologies.