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How do ego-networks evolve? How does such evolution affect firms’ innovation output? This chapter uses a longitudinal sample of firms in the biotechnology industry to address these questions. We use social network theory to develop a model of the structure and dynamics of firms’ interorganizational research collaboration ego-networks. Using novel longitudinal methods, this chapter demonstrates how research collaboration ego-networks in the biotechnology industry change over time and how this evolution affects focal firms’ subsequent innovative output. The model is tested on a sample of 482 biotechnology firms over a span of 17 years (1990–2006). The results indicate the significant impacts of ego-network size, ego-network growth, and the inclusion of new members in the ego-network on the innovation output of biotechnology firms. Our results also suggest that enlarging ego-networks by adding new and diverse members presents significant management challenges.

I assess the extent that the egonet method of collecting data permits accurate inferences to the true structural features of the network. This inference problem has three critical components: local-global inference error, ego distortion, and feature inference error. Analysis of four data sets indicates that structural features can be predicted by estimates generated from egonets in some instances, but more often than not they are not good predictors.

Social networks are not just patterns of interaction and sentiment in the real world; they are also cognitive (re)constructions of social relations, some real, some imagined. Focusing on networks as mental entities, our essay describes a new method that relies on stylized network images to gather quantitative data on how people “see” specific aspects of their social worlds. We discuss the logic of our approach, present several examples of “visual network scales,” discuss some preliminary findings, and identify some of the problems and prospects in this nascent line of work on the phenomenology of social networks.

We propose a framework based on social network analysis for crowdfunding projects.

Our approach is based on the strength of both weak and strong ties of the social network established by the project proponents. Our approach also considers not only the characteristics of the target population and the close social circle of the proponent but also mainly the community of potential backers strongly and weakly attached to his or her network of friends.

Supported by a literature review on social networks, crowdsourcing and crowdfunding, we have established a framework with five constructs (Extension, Cohesion, Centralization, Clustering, and Power) that can help entrepreneurs to raise funds through crowdfunding platforms.

Structural properties of these social networks such as size, cohesion and centralization may prove useful for applicants and platforms interested in succeeding in their projects and for stimulating the interest of scholars in the growing crowdfunding phenomenon.

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.

I evaluate the accuracy with which respondents report egocentered network data. I find that 72% of the time ego’s assessment of the tie between a pair of alters corresponded with both alters’ report of the tie between themselves, and 87% of the time, ego’s report of the tie between a pair of alters is in agreement with at least one of the alters. I discuss the implications of the findings for the debate over the merits of egocentered network data.

This article explores the contingent role that social ties play in the emergence of status hierarchies. We argue that, while status is formed based on actors’ perception and understanding of social cues, network structure, and position influence this process by influencing the attention and legitimacy given to the focal actor in accordance with social cues that signal an actor’s identity. Using a large data set from an open-source software development community, we find that a broker linking diverse network members is less likely to receive status ratings from others and that the rating is more likely to be low when a broker receives a rating. Furthermore, we find evidence that the effects of brokerage are contingent upon certain factors that may affect the attention and legitimacy given to actors in the process of status evaluation, such as the actor’s prior status. An actor’s prior status was found to weaken the negative effect of brokerage. The importance of this study for theories of status, social networks, and attention is discussed.

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.

We construct a theory of team collaboration to explain how social actors activate their network ties to gain access to and acquire the use of social capital held by other network actors. Drawing from weak-strong tie theory and closure-brokerage models of network structures, our theory specifies dynamic processes in which relations vary in their potential for activation, and thus, project teams have differential probabilities of mobilizing and gaining collective use of the varied resources held by their network alters inside and outside the team. The theoretical scope is interorganizational team whose members are employed by two partnering organizations and are assigned to a joint project with a single task or goal to be accomplished within a limited period. We present and discuss a set of propositions about factors that affect the ability of a team to access its members’ social capital for use in a project task.