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Understanding the determinants of creativity at the individual and organizational level has been the focus of a long history of research in various disciplines from the social sciences, but little attention has been devoted to studying creativity at the dyadic level. Why are some dyadic interactions more likely than others to trigger the generation of novel and useful ideas in organizations? As dyads conduit both knowledge and social forces, they offer an ideal setting to disentangle the effects of knowledge diversity, tie strength, and network structure on the generation of creative thoughts. This paper not only challenges the current belief that sporadic and distant dyadic relationships (weak ties) foster individual creativity but also argues that diverse and strong ties facilitate the generation of creative ideas. From a knowledge viewpoint, our results suggest that ties that transmit a wide (rather than narrow) set of knowledge domains (within the same tie) favor creative idea generation if exchanges occur with sufficient frequency. From a social perspective, we find that strong ties serve as effective catalysts for the generation of creative ideas when they link actors who are intrinsically motivated to work closely together. Finally, this paper also shows that dyadic network cohesion (i.e., the connections from the focal dyad to common contacts) does not always hinder the generation of creative ideas. Our empirical evidence suggests that when cohesion exceeds its average levels, it becomes detrimental to creative idea generation. Hypotheses are tested in a sociometric study conducted within the development department of a software firm.

Homophily in social relations results from both individual preferences and selective opportunities for interaction, but how these two mechanisms interact in large, contemporary organizations is not well understood. We argue that organizational structures and geography delimit opportunities for interaction such that actors have a greater level of discretion to choose their interaction partners within business units, job functions, offices, and quasi-formal structures. This leads us to expect to find a higher proportion of homophilous interactions within these organizational structures than across their boundaries. We test our theory in an analysis of the rate of dyadic communication in an email data set comprising thousands of employees in a large information technology firm. These findings have implications for research on homophily, gender relations in organizations, and formal and informal organizational structure.

Theories of conflict emphasize dyadic interaction, yet existing empirical studies of civil war focus largely on state attributes and pay little attention to nonstate antagonists. We recast civil war in a dyadic perspective, and consider how nonstate actor attributes and their relationship to the state influence conflict dynamics. We argue that strong rebels, who pose a military challenge to the government, are likely to lead to short wars and concessions. Conflicts where rebels seem weak can become prolonged if rebels can operate in the periphery so as to defy a government victory yet are not strong enough to extract concessions. Conflicts should be shorter when potential insurgents can rely on alternative political means to violence. We examine these hypotheses in a dyadic analysis of civil war duration and outcomes, using new data on nonstate actors and conflict attributes, finding support for many of our conjectures.

Sharing a public language facilitates particularly efficient forms of joint perception and action by giving interlocutors refined tools for directing attention and aligning conceptual models and action. We hypothesized that interlocutors who flexibly align their linguistic practices and converge on a shared language will improve their cooperative performance on joint tasks. To test this prediction, we employed a novel experimental design, in which pairs of participants cooperated linguistically to solve a perceptual task. We found that dyad members generally showed a high propensity to adapt to each other's linguistic practices. However, although general linguistic alignment did not have a positive effect on performance, the alignment of particular task-relevant vocabularies strongly correlated with collective performance. In other words, the more dyad members selectively aligned linguistic tools fit for the task, the better they performed. Our work thus uncovers the interplay between social dynamics and sensitivity to task affordances in successful cooperation.

This paper examines how organizations collaborate with multiple partners, such as when they develop innovative and complex product platforms like smartphones, servers, and MRI machines that rely on technologies developed by organizations in three or more sectors. Research on multipartner alliances often treats them as a collection of independent dyads, neglecting the possibility of third-party influence and interference in dyads that can inhibit innovation. Using a multiple-case, inductive study of six groups, each composed of three organizations engaged in technology and product development in the computer industry, I examine the collaborative forms and processes that organizations use to innovate with multiple partners in groups. Groups that used the collaborative forms of independent parallel dyads or single unified triads generated mistrust and conflict that stemmed from expectations about third-party participation and overlapping roles and thus had low innovation performance and weaker ties. Other groups avoided these problems by using a dynamic collaboration process that I call \"group cycling,\" in which managers viewed their triad as a small group, decomposed innovative activities into a series of interlinked dyads between different pairs of partners, and managed third-party interests across time. By temporarily restricting participation to pairs, managers chose which ideas, technologies, and resources to incorporate from third parties into single dyads and ensured that the outputs of multiple dyads were combined into a broader innovative whole.

Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.

Methods for descriptive network analysis have reached statistical maturity and general acceptance across the social sciences in recent years. However, methods for statistical inference with network data remain fledgling by comparison. We introduce and evaluate a general model for inference with network data, the Exponential Random Graph Model (ERGM) and several of its recent extensions. The ERGM simultaneously allows both inference on covariates and for arbitrarily complex network structures to be modeled. Our contributions are three-fold: beyond introducing the ERGM and discussing its limitations, we discuss extensions to the model that allow for the analysis of non-binary and longitudinally observed networks and show through applications that network-based inference can improve our understanding of political phenomena.

We use data from a 12-month ethnographic study of two medical-surgical units in a U.S. hospital to examine how members from different occupations can collaborate with one another in their daily work despite differences in status, shared meanings, and expertise across occupational groups, which previous work has shown to create difficulties. In our study, nurses and patient care technicians (PCTs) on both hospital units faced these same occupational differences, served the same patient population, worked under the same management and organizational structure, and had the same pressures, goals, and organizational collaboration tools available to them. But nurses and PCTs on one unit successfully collaborated while those on the other did not. We demonstrate that a social structure characterized by cross-cutting demographics between occupational groups—in which occupational membership is uncorrelated with demographic group membership—can loosen attachment to the occupational identity and status order. This allows members of cross-occupational dyads, in our case nurses and PCTs, to draw on other shared social identities, such as shared race, age, or immigration status, in their interactions. Drawing on a shared social identity at the dyad level provided members with a \"dyadic toolkit\" of alternative, non-occupational expertise, shared meanings, status rules, and emotional scripts that facilitated collaboration across occupational differences and improved patient care.

Using a longitudinal dataset of research collaborations over 15 years at Stanford University, we build a theory of intraorganizational task relationships that distinguishes the different factors associated with the formation and persistence of network ties. We highlight six factors: shared organizational foci, shared traits and interests, tie advantages from popularity, tie reinforcement from third parties, tie strength and multiplexity, and the instrumental returns from the products of ties. Findings suggest that ties form when unfamiliar people identify desirable and matching traits in potential partners. By contrast, ties persist when familiar people reflect on the quality of their relationship and shared experiences. The former calls for shallow, short-term strategies for assessing a broad array of potential ties; the latter calls for long-term strategies and substantive assessments of a relationship's worth so as to draw extended rewards from the association. This suggests that organizational activities geared toward sustaining persistent intraorganizational task relationships need to be different from activities aimed at forging new ones.

Embeddedness in social networks is increasingly seen as a root cause of human achievement, social stratification, and actor behavior. In this article, we review sociological research that examines the processes through which dyadic ties form, persist, and dissolve. Three sociological mechanisms are overviewed: assortative mechanisms that draw attention to the role of actors' attributes, relational mechanisms that emphasize the influence of existing relationships and network positions, and proximity mechanisms that focus on the social organization of interaction.