Network Strategy: Volume 25

Two core assumptions set network theory apart from other perspectives and direct research into specific strategic and organizational topics.

Syndicated investments in startups within a particular industry follow an evolutionary path consistent with models of industry growth and evolution. Some industries spend a long time gestating, while others grow and mature quickly. Entry into ecommerce industry segments has both characteristics. What spurred the sector's slow emergence and subsequent quick rise? One obvious answer is the development of the Internet in the mid-1990s. However, a competing possibility is that the diffusion pattern resembles an epidemic among venture capital firms. This chapter examines how the existing structure of the VC syndication network in the US enabled such an epidemic. Consistent with existing theory on the spread of a disease in a small world, this study argues that the incidence of investments in ecommerce startups was a function of prior investments located on shortcuts in the network. The time frame is 1980 to just before the NASDAQ boom in 1999.

In this chapter we investigate the ownership and control of UK firms using contemporary methods from computational graph theory. Specifically, we analyze a ‘small-world’ model of ownership and control. A small-world is a network whose actors are linked by a short chain of acquaintances (short path lengths), but at the same time have a strongly overlapping circle of friends (high clustering). We simulate a set of corporate worlds using an ensemble of random graphs introduced by Chung and Lu (2002a, 2002b). We find that the corporate governance network structures analyzed here are more clustered (‘clubby’) than would be predicted by the random-graph model. Path lengths, though, are generally not shorter than expected. In addition, we investigate the role of financial institutions: potentially important conduits creating connectivity in corporate networks. We find such institutions give rise to systematically different network topologies.

This chapter aims to identify the main determinants that define the architectural properties of network emergence and significantly influence the dynamics underlying network evolution in time. The identification and analysis of these determinants, as well as the dynamic processes tied to them, allows to appreciate the competitive bases and consequences of network morphology. To this purpose, using a complex systems perspective as an integrative conceptual approach, we represent networks as complex dynamic systems of knowledge and capabilities. We perform a comparative in-depth analysis of the processes underlying the emergence and evolution of STMicroelectronic's global network and of Toyota's supplier network in the US so as to allow an elucidatory empirical assessment of the theoretical representation elaborated in the article.

Dyadic multi-dimensionality informs the variation that exists within and between network ties and suggests that ties are not all the same and not all equally strategic. This chapter presents a model of dyadic evolution grounded in dyadic multi-dimensionality and framed within actor-level, dyadic-level, endogenous, and exogenous contexts. These contexts generate both strategic catalysts that motivate network action and bounded agency that may constrain such network action. Assuming the need to navigate within bounded agency, the model highlights three strategic processes that demonstrate how dyadic multi-dimensionality underlies the evolution of strategic network ties.

Inter-organizational alliances and the networks they generate have been a central topic in organization theory over the last decade. However, network analyses per se have been static. Even when information over time has been available, the temporal component has been set aside or aggregated to the end point of the study. Substantially more research has been conducted on organizations initiating inter-organizational relationships. The organization-level research has been decidedly dynamic in nature. However, organization-level research has largely examined the structural characteristics of the networks generated by organizational actions. Work combining network-level and organization-level phenomena has been rare and, to our knowledge, no research including the effects of organization-level actions on the evolution of network-level phenomena has occurred.

In this chapter we use more than 6000 R&D alliances and more than 6500 M&D alliances initiated by more than 1000 biotech firms in the U.S. over a 30 year period to construct quarterly networks. We test 13 hypotheses linking the actions of the firms to changes in network structure. Utilizing hazard-rate models we test the effects of institutional status, positional status (centrality), and structural status (coreness) of firms on their propensity to form ties with different structural consequences. Our research indicates that both R&D and M&D networks in U.S. biotechnology are developing a distinct core/periphery structure over time. Furthermore, we find support for a process of preferential attachment wherein organizations are more likely to form ties with organizations of similar institutional and structural status. Furthermore, we find evidence for cross effects, for example attachment processes that enfold across the two networks.

This chapter analyzes the relations among bank mergers, changes in boards and their networks, and changes in the global footprint of merging banks. We examine all mergers involving U.S. banks with foreign branches between 1986 and 2004. We find that while the largest banks have become even larger through mergers, their boards have stayed roughly the same size with the same pattern of connections, leaving banks relatively less central in the intercorporate network. And while global banks previously had more globally oriented boards, this is no longer the case, as the link between board networks and strategy has become more tenuous. Because global banks were particularly prone to merging, the average commercial bank in the U.S. is now far more domestically oriented than firms in most other industries. American banks have thus become more domestic at the same time that the rest of American industry has grown much more global.

The arguments in this chapter address all three of the questions motivating this volume on network strategy. First, they focus on the issue of network evolution and show how networks can emerge and change over time. Second, the chapter tackles the issue of endogeneity and shows that, under certain conditions, some structural advantages do precede rather than follow network positions. Networks evolve over trajectories and the trajectories matter. Third, the arguments respond to the core question of network entrepreneurship: does the awareness of structural advantages available to network positions inspire managers, acting on behalf of organizations, to seek these advantages? In responding, this chapter challenges the idea that filling structural holes necessarily confers advantages on the actors filling them. It follows that the advantages of bridging are dependent not only on the network structure, when decisions regarding tie formation or deletion are made, but also on the costs of forming and maintaining ties relative to the benefits obtained from doing so.

Knowledge sharing is a fundamental source of competitive advantage. Social networks are thought to play an important role in knowledge sharing, but are presumed to create a trade-off such that a network can be optimized to promote either knowledge seeking or knowledge transfer, but not both. The trade-off, however, is premised on, and representative of a broader tendency to treat, brokerage and closure as contradictory network forms. We challenge this assertion and propose a theory of knowledge sharing with brokerage and closure as compatible and complementary. Evidence from a contract research and development firm broadly supports our theory. We also report the results of a simulation analysis, which illustrate that only in the extremely rare case when a network is characterized by nearly complete balance do brokerage and closure begin to create a trade-off.

What is the scope of brokerage network to be considered in thinking strategically? Given the value of bridging structural holes, is there value to being affiliated with people or organizations that bridge structural holes? The answer is “no” according to performance associations with manager networks, which raises a question about the consistency of network theory across micro to macro levels of analysis. The purpose here is to align manager evidence with corresponding macro evidence on the supplier and customer networks around four-digit manufacturing industries in the 1987 and 1992 benchmark input–output tables. In contrast to the manager evidence, about 24% of the industry-structure effect on industry performance can be attributed to structure beyond the industry's own buying and selling, to networks around the industry's suppliers and customers. However, the industry evidence is not qualitatively distinct from the manager evidence so much as it describes a more extreme business environment.

We examine how the ability of one actor to gain access to resources controlled by another depends on two factors: (i) the number of mutual acquaintances connecting the prospective lender and borrower and (ii) the scarcity of the resources in question. We argue that the incentives to renege on an agreement grow as the resources being traded become increasingly scarce. Mutual acquaintances, however, dampen these incentives, and therefore become more important to facilitating exchange as demand for the good of interest rises. Our analysis of qualitative and quantitative evidence from a study of senior partners at an international consultancy supports these propositions.

We develop and test a model of how a software firm's business strategy (product scope and market scope) interacts with the firm's network position (alliance degree and structural holes) to impact performance. We test the joint-effects hypotheses on a sample 359 packaged software firms that have entered into 5,489 alliances involving 2,849 distinct firms during the time period, 1990–2002. While prior studies have demonstrated the importance of network positions as a determinant of firm strategy and performance, this chapter begins to examine the performance effects of how a firm's business strategy and network positions interact. We find support for three of the four hypotheses lending empirical support for our theoretical model. We develop implications for network-based perspectives of strategy and outline areas for further research.

Network formation is often said to be driven by social capital considerations. A typical pattern observed in the empirical data on strategic alliances is that of small-world networks: dense subgroups of firms interconnected by (few) clique-spanning ties. The typical argument is that there is social capital value both to being embedded in a dense cluster, and to bridging disconnected clusters. In this chapter we develop and analyze a simple model of joint innovation where we are able to reproduce these features, based solely on the assumption that successful partnering demands some intermediate amount of technological similarity between the partners.

In the network strategy view, relative competitive advantage stems not merely from opportunity structures embedded in networks but also from the distribution of ability and motivation among firms. Thus, there is a need to “bring the firm back in” to the network strategy narrative. We demonstrate that a mixed-methods design, blending large-sample data with micro-data on specific firms and their networks, can increase our understanding of the interplay of network structure and actor mechanisms, thus bridging the chasm between theory and practice in network strategy. We believe this is a critical step toward the “strategic design of networks.”

We discuss the ‘gloomy’ side of firms’ embeddedness in networks of inter-firm partnerships. We propose a nested understanding of the effects of three levels of overembeddedness – environmental, inter-organizational and dyadic overembeddedness – on subsequent inter-firm partnership formation and argue for a joint examination of these three levels and their interactions over time. As a whole, increases in firms’ embeddedness will generate decreasing returns to the firms involved, prompting (i) the search for and attachment to novel partners and (ii) the dissolution of extant partnerships. On the flipside, overembeddedness thus sparks network evolution – by cueing firms to look beyond their embedded partnerships.

Organizational networks are generally considered major antecedents of mutual influence in adopting similar practices, typically via a structure of dense ties, or closure. We propose that under conditions of competitive interdependence, closure may be associated with links established to access resources and knowledge and become a possible source of differentiation rather than imitation. We test these and other antecedents of imitative behavior and performance in the Italian TV industry with 12 years of data on 501 productions. We find that network closure is associated with lower imitation, centrality, but not status, leads to imitation, and that imitation lowers performance.

In this chapter we examine the process by which new firms become central actors within their industry networks. We focus, in particular, on how relatively new venture capital (VC) firms become more central within investment syndication networks. We present a model that captures the relationships among (1) the social capital and status of the new VC firm's founders, (2) the VC firm's resource endowments, (3) the VC firm's ability to forge relationships with other prestigious and central venture capital firms, (4) the visibility-enhancing performance of portfolio firms, and (5) the urgency and effort exhibited by the new VC as it pursues these opportunities. These factors combine to shape a new VC's journey from the periphery to the center of its industry network. To illustrate these processes, we develop in-depth case studies of Benchmark Capital and August Capital, two VC firms founded in 1995. We then elaborate upon the enacted nature of resource and opportunity constraints and conclude with a discussion of how new firms create their own self-fulfilling prophecies.

We propose an information-based view of the dynamics of network positions and use it to explain why bridging positions become stronger. We depart from previous network dynamics studies that implicitly assume that firms have homogenous information about the network structure. Using network experiments with both students and managers, we vary a firm's network horizon (i.e., how much information a firm has about the network structure) and the network horizon heterogeneity (i.e., how this information is distributed among the firms within the network). Our results indicate that firms with a higher network horizon occupy a stronger bridging position, especially under conditions of high network horizon heterogeneity. At a more general level, these results provide an indirect validation of what so far has been an untested assumption in interfirm network research, namely that firms are aware of their position in the overall network and consciously attempt to improve their position.

In this study, we seek to broaden the research focus in the strategic alliance literature from a firm's “partner strategy” to its “network strategy” by linking a firm's partnering choices to changes in its network position over time. Using data on all underwriting syndicates in Canada over nearly 40 years, we conceptualize and model the interplay between an investment bank's own and its partners’ syndicate participation. Our findings indicate that the lead banks, which have greater discretion in choosing syndicate partners than co-lead banks, are more likely to make partner selections that create bridging positions that provide access to timely and non-redundant information as well as opportunities to play a broker role across unconnected others. We also find, however, that lead banks’ bridging positions deteriorate when they form ties with other lead banks. Network-based competitive advantages are thus influenced by network opportunities and constraints as well as partner-specific concerns, suggesting that new insights into the dynamics of interfirm networks and competitive advantage of firms are possible within this broader view.