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Group interaction networks are networks whose relations are defined by who engages with whom in communication, coordination, or other forms of joint activity. These interaction networks represent the patterns of action that unfold between members of a group and have the potential to inform research on how groups communicate, how psychological states inform, and how communication patterns can impact team performance. Interaction networks are unique in that they can be defined in terms of both structure and temporality; each interaction can be coded as an event that occurs at a specific point in time. Accordingly, interaction networks are well suited for process theories and methods. Further, the growing availability of fine-grained digital trace data makes it easier for researchers to study these networks in depth. In this chapter, theories of structure and time are reviewed in relation to group networks and interactions. A process-oriented relational event-based paradigm for studying group interaction networks is introduced as a possible alternative to prior methods. The chapter concludes with a comparison of relevant social network approaches, as well as a discussion of potential future research.

The purpose of this paper is to establish whether different gender groups develop in similar or dissimilar ways to conventional group formation patterns. Focussing primarily on Tuckman's model of group development, male, female and mixed gender learning networks (groups) of entrepreneurs were observed over a six month period, with the observations recorded and analysed, to establish whether different gender networks of business people adhere to Tuckman's model of group development in terms of early development and cohesion through the forming, storming and norming stages.

A total of 100 entrepreneurs were recruited in Autumn 2009/Spring 2010 and allocated to three different gender networks, male, female and mixed, in Ireland and Wales (six networks in total), as part of the Sustainable Learning Networks Ireland Wales (SLNIW, for detailed information about SLNIW see www.slniw.com) INTERREG 4A funded project. The groups began networking in January 2010, observed by impartial observers who noted group behaviour and dynamics and recorded observations quantitatively (based on adapted Bales criteria) and qualitatively. It is the results of these observations that form the basis of this paper.

This paper analyses the results of the group dynamic witnessed over subsequent network meetings for different gender mixes in Ireland. Whilst the observations are still ongoing, early results indicate that early engagement with group members, team bonding and group dynamics are formed sooner in the single gender groups. The paper explores why this could be the case and considers factors that could then address problems with early group development in mixed gender networks, so that the ultimate “performing” stage of group development and optimal business performance is achieved as early as possible.

This paper will be of considerable value to academics, theorists and practitioners. It will specifically add to the body of knowledge on single gender networks to see if they provide a more effective learning environment.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

This paper explores the emergence and coordination of synchrony in networked groups like those that develop integrated product platforms in collaborative ecosystems. While synchronized actions are an important objective for many groups, interorganizational network theory has yet to explore synchrony in depth perhaps because it does not fit the typical diffusion models this research relies upon. By adding organizationally realistic features – sparse network structure and intentional coordination – to the firefly model from theoretical biology, I take some first steps in understanding synchrony in organizational groups. Like diffusion, synchrony is more effective in denser networks, but unlike diffusion clustering decelerates synchrony’s emergence. Coordination by a few group members accelerates group-wide synchrony, and benefits the coordinating organizations with a higher likelihood that it converges to the coordinating organization’s preferred rhythm. This likelihood of convergence to an organization’s preferred rhythm – what I term synchrony performance – increases in denser networks, but is not dependent on tie strength and clustering.

Purpose – Criminal groups have long been central to explanations of crime and deviance. Yet, challenges in measuring their dynamic and transient nature meant that group-level explanations were often displaced in favor of individual-level ones. This chapter outlines how network methods provide a powerful tool for modeling the dynamic nature of criminal groups.

Approach – The chapter starts by providing a brief introduction to social network analysis, including key concepts and terminology. The chapter then focuses on the types of relational data available to study criminal groups, and how network methods can be used to delineate group boundaries. The chapter concludes by presenting a framework for understanding group dynamics from a network perspective, describing the contributions of network analysis to theories of group processes.

Findings – Network methods have provided meaningful advances to the study of group dynamics, leading scholars to revisit assumptions about the impact of group’ structure on delinquent behavior. Network studies of group dynamics have primarily focused on the cohesion–delinquency link (within-group structure) and the social contagion of conflict (between-group structure), highlighting important opportunities for the intersection of these two inquiries.

Value – Network methods provide a means to revisit and extend theories of crime and delinquency with a focus on social structure. The unique affinity between group dynamics and network methods highlights immense opportunities for expanding the knowledge of collective trajectories.

The field of Human Resource Management (HRM) has long recognized the importance of interpersonal influence for employee and organizational effectiveness. HRM research and practice have focused primarily on individuals’ characteristics and behaviors as a means to understand “who” is influential in organizations, with substantially less attention paid to social networks. To reinvigorate a focus on network structures to explain interpersonal influence, the authors present a comprehensive account of how network structures enable and constrain influence within organizations. The authors begin by describing how power and status, two key determinants of individual influence in organizations, operate through different mechanisms, and delineate a range of network positions that yield power, reflect status, and/or capture realized influence. Then, the authors extend initial structural views of influence beyond the positions of individuals to consider how network structures within and between groups – capturing group social capital and/or shared leadership – enable and constrain groups’ ability to influence group members, other groups, and the broader organizational system. The authors also discuss how HRM may leverage these insights to facilitate interpersonal influence in ways that support individual, group, and organizational effectiveness.

The purpose of this paper is to theoretically clarify the relationship between public service motivation and performance by suggesting a framework in which social networks among members provide an explicit mechanism linking employees’ PSM with their performance and by proposing several empirically testable propositions.

The author suggests a theoretical framework based on a literature review and combining insights from several major strands of theory including social capital and social network theories.

Conceptually, the paper shows that, first, the extent of the social relationships among group members and their positions within a network vary depending on the level of PSM; second, individuals with high PSM are more likely to complete their tasks when they are in central positions in a network of advice relations and less likely to complete their tasks when they are in peripheral positions in central positions and a network of advice relations in a network of adversarial relations; third, group members with high PSM are more likely to complete group tasks when the group has higher density in a network of advice relations and less likely to complete tasks in a dense network of adversarial relations.

The author demonstrates the possibility of reciprocal relationships between PSM and social networks, in which PSM builds social capital that reinforces each member’s PSM by enhancing relationship quality, which will positively affect performance.

This paper provides opportunities for future empirical research by developing the discussion about a new conceptual mechanism in the relationship between PSM and performance, proposing an initial conceptual framework that clarifies the PSM and performance linkage, and suggesting several testable propositions.

The purpose of this paper is to explore the effect of “multiplex” (multiple overlapping) networks and leadership on group performance in a higher education setting.

Using a combination of social network analysis and interviews, the authors employ a case study approach to map the connections between academic group members. This paper analyses the relationship between this mapping and academic performance.

The authors identified two dimensions which influence group effectiveness: multiplex networks and distributed–coordinated leadership. Where networks are built across tasks, inter-relationships develop that lead to greater group performance.

Where group members create a dense hive of interconnectivity and are active across all group tasks, and also informally, this increases the opportunity for knowledge sharing. When this is similarly experienced by a majority of group members, there is positive reinforcement, resulting in greater group effectiveness.

This paper highlights the importance of the richness of formal ties in knowledge-intensive settings. This paper is the first to differentiate between formal connections between colleagues related to different tasks within their role. This suggests that dense configurations of informal ties are insufficient; they must be coupled with strong ties around formal activity and demonstrative leadership.

The objective of this paper is to review the literature on how networks can be used in developing countries to encounter export‐marketing problems. Several case studies of export‐grouping and subcontracting networks, involving small‐ and medium‐sized enterprises in developed and underdeveloped countries, are reviewed. The paper presents a qualitative model that identifies the determining factors for successful export network organisations: a clearly defined market problem or market opportunity; a willingness to respond together; development of solidarity, coherence and commitment; initiating foreign market activities. This model is useful to study similar initiatives in developing countries.