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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 research community currently employs four very different versions of the social network concept: A social network is seen as a set of socially constructed role relations (e.g., friends, business partners), a set of interpersonal sentiments (e.g., liking, trust), a pattern of behavioral social interaction (e.g., conversations, citations), or an opportunity structure for exchange. Researchers conventionally assume these conceptualizations are interchangeable as social ties, and some employ composite measures that aim to capture more than one dimension. Even so, important discrepancies often appear for non-ties (as dyads where a specific role relation or sentiment is not reported, a specific form of interaction is not observed, or exchange is not possible).

Investigating the interplay across the four definitions is a step toward developing scope conditions for generalization and application of theory across these domains.

This step is timely because emerging tools of computational social science – wearable sensors, logs of telecommunication, online exchange, or other interaction – now allow us to observe the fine-grained dynamics of interaction over time. Combined with cutting-edge methods for analysis, these lenses allow us to move beyond reified notions of social ties (and non-ties) and instead directly observe and analyze the dynamic and structural interdependencies of social interaction behavior.

This unprecedented opportunity invites us to refashion dynamic structural theories of exchange that advance “beyond networks” to unify previously disjoint research streams on relationships, interaction, and opportunity structures.

Network analysis is a well consolidated research area in several disciplines. Within management and organizational studies, network scholars consolidated a set of research practices that allowed ease of data collection, high inter case comparability, establishment of nomological laws and commitment to social capital motivation. This paper aims to elicit the criticism it has received and highlight the unsettled lacunae.

This paper sheds light on Network Analysis’s breakthroughs, while showing how its scholars innovated by responding to critics, and identifying outstanding debates.

The paper identifies and discusses three streams of criticism that are still outstanding: the role of human agency, the meaning of social ties and the treatment of temporality.

This paper brings to fore current debates within the Network Analysis community, highlighting areas where future studies might contribute.

Purpose: This chapter aims: (a) to extend biased net models of homophily to complete networks; (b) to extend the scope of application of these models to processes of social exchange in a small-group laboratory setting; and (c) to link the theoretical model of attraction and repulsion with a standard statistical model of logistic regression as a way of estimating and evaluating the model.

Methods: We discuss the logic of biased net theory and show how it leads to formal mathematical models of tie formation and tie renewal under mechanisms of attraction and repulsion. We then estimate key theoretical parameters in the models by means of logistic regression.

Findings: The estimated effects of homophily in our models are moderate in strength, weaker than corresponding reciprocity effect, and processes of tie formation and tie renewal are driven more by considerations of direct reciprocity than group membership. Under attraction, homophily effects are stronger for tie renewal than tie formation. Under repulsion, the opposite holds.

Limitations: Participants in our study are divided into two groups based on a criterion that is likely to have been too weak to induce strong group identity. Measures that enhance the sense of group identity need to be introduced in future studies.

Research on organizational teamwork is increasingly highlighting the patterned nature of the relational processes (e.g., communication, backup behavior) and psychological states (e.g., trust, shared cognition) that underlie team effectiveness. However, studies of teams often rely on methodologies that do not explicitly assess the underlying patterns of relational processes and states. Social network approaches offer an appealing alternative to the typical methodologies used in team research given that network approaches provide both the theory and methodology necessary to conceptualize and investigate patterns of interactions among group members. Despite the advantages of social network approaches, many team researchers are unfamiliar with the network paradigm and its associated methodologies. The purpose of this chapter is to clarify how networks can be leveraged to answer key research questions related to the study of team functioning and effectiveness. We begin by discussing the evolution and eventual convergence of team research and network approaches. Then, we examine the current state of the literature at the intersection of teams and networks in order to identify key takeaways and remaining questions. We conclude by highlighting opportunities for the future of team network science.

Team cohesion and other team processes are inherently dynamic mechanisms that contribute to team effectiveness. Unfortunately, extant research has typically treated team cohesion and other processes as static, and failed to capture how these processes change over time and the implications of these changes. In this chapter, we discuss the characteristics of team process dynamics and highlight the importance of temporal considerations when measuring team cohesion. We introduce innovative research methods that can be applied to assess and monitor team cohesion and other process dynamics. Finally, we discuss future directions for the research and practical applications of these new methods to enhance our understanding of the dynamics of team cohesion and other processes.

Relationship development is required for any group working together. As members coordinate to accomplish tasks, some level of relationship is created through interaction between group members. However, most group development models focus on task accomplishment and may briefly address relational concerns. Communication research has furthered our understanding of group relationship development based on communicative changes that demonstrate emerging relationships among members. This chapter summarizes research on relationship development in groups. First, the chapter reviews research on group relational messages and relational outcomes. Second, the chapter outlines a framework for explaining group relationship development based on group interaction and development research. Four progressive stages (investigating, initiating, integrating, and interconnecting) are presented that show the communicative changes in group relationship development. Investigating focuses on testing boundaries and getting to know members, while initiating highlights how members become more direct about individual goals and handle conflict. During integrating, members shift to a group mind and tentatively form relationships with members, whereas interconnecting is a sense of we-ness among members and the use of shared group symbols. Future research directions for relational development and the four stages are presented at the end.

This paper aims to extend the argument of DeNisi & Smith Sockbeson, who called to bridge the gap between feedback-seeking and feedback-giving research. The paper pushes their argument further by suggesting that future feedback research should systematically adopt a dyadic and dynamic approach to enhance the understanding of feedback episodes.

This paper reviews previous empirical work in the feedback domain and develops conceptual arguments for linking feedback-seeking and feedback intervention research.

Drawing upon previous work, the authors conclude that the current depiction of feedback processes in the literature might have been overly static and one-sided. Furthermore, it is argued that feedback research might have not kept up to date with recent conceptual and methodological developments in dyadic organizational behavior research.

This paper builds on the argument of DeNisi & Smith Sockbeson, in turn contributing to a more complete picture of how feedback processes unfold in organizations. While this paper profiles a few studies that have begun to bridge the disconnect between feedback-seeking and feedback-giving research, one of its limitations is that it does not adopt a systematic approach in reviewing all potential methodologies.

This paper provides a first step toward studying feedback episodes as dyadic and dynamic processes. In doing so it helps solving one of the long-standing puzzles in management research namely why feedback interventions are sometimes detrimental to performance.

El objetivo de este artículo es extender los argumentos de DeNisi & Smith Sockbeson, que hacen un llamamiento para conectar la investigación sobre buscar y ofrecer feedback (retroalimentación). Desarrollamos aún más su propuesta sugiriendo que la investigación futura sobre feedback debe adoptar sistemáticamente una aproximación diádica y dinámica para mejorar nuestra comprensión de los episodios de feedback.

El artículo revisa la literatura empírica en el campo del feedback y desarrolla argumentos conceptuales para vincular la investigación en busqueda de feedback e intervenciones de feedback.

Sobre los resultados de trabajos previos los autores concluyen que la imagen actual de los procesos de feedback en la literatura es excesivamente estática y desde un solo punto de vista. Es más, se argumenta que la investigación en feedback puede no haber seguido algunos desarrollos conceptuales y metodológicos recientes en la investigación sobre comportamiento organizativo diádico.

El presente trabajo toma los argumentos de DeNisi & Smith Sockbeson como punto de partida, y con ello contribuye a desarrollar una imagen más completa sobre como los procesos de feedback se despliegan en las organizaciones. Si bien el trabajo comenta algunos trabajos que han comenzado a conectar las hasta la fecha desconectadas literaturas en buscar y ofrecer feedback, su limitación principal reside en que no adopta una revisión sistemática de todas las metodologías potenciales.

El trabajo ofrece un primer paso hace el estudio de los episodios de feedback como procesos diádicos y dinámicos. De este modo contribuye a solventar uno de los retos clásicos en la investigación en gestión: porqué las intervenciones de feedback son en ocasiones negativas para el rendimiento.

Este artigo visa estender o argumento de DeNisi & Smith Sockbeson, que preenche a lacuna entre a pesquisa sobre buscar feedback e dar feedback. Nós impulsionamos ainda mais o seu argumento, sugerindo que a futura pesquisa sobre o feedback deve adotar sistematicamente uma abordagem diádica e dinâmica para melhorar nossa compreensão dos episódios de feedback.

Este artigo revisa o trabalho empírico anterior no domínio do feedback e desenvolve argumentos conceituais para vincular pesquisas de busca de feedback e de intervenção de feedback.

Com base em trabalhos anteriores, os autores concluem que a representação atual dos processos de feedback na literatura pode ter sido excessivamente estática e unilateral. Além disso, argumenta-se que a pesquisa de feedback pode não ter se atualizado com desenvolvimentos conceituais e metodológicos recentes na pesquisa do comportamento organizacional diádico.

Este artigo baseia-se no argumento de DeNisi & Smith Sockbeson, contribuindo, por sua vez, para um quadro mais completo de como os processos de feedback se desdobram nas organizações. Enquanto o artigo mapeia alguns estudos que começaram a reduzir a desconexão entre a pequisa sobre buscar e dar feedback, uma de suas limitações é que ela não adota uma abordagem sistemática ao revisar todas as metodologias potenciais.

Este artigo fornece um primeiro passo para o estudo de episódios de feedback como processos diádicos e dinâmicos. Ao fazê-lo, ajuda a resolver um dos quebra-cabeças de longa data na pesquisa em administração, principalmente porque as intervenções de feedback às vezes são prejudiciais ao performance.

Group communication as an area of intellectual interest had its beginnings in communication pedagogy with the goal of helping students to become more effective decision makers. A by-product is that group decision making became and remained a central research focus for many years. In the last 20 years, group communication research has facilitated the development of theory, research methods, and technology. Since 2000, group communication scholars have developed research lines on (1) virtual/digital team communication; (2) information sharing, hidden profile, and transactive memory systems; and (3) group participation. This chapter also explores the way in which group communication scholars have become connected with other disciplines that study groups and teams. The chapter concludes with current research methods trends, including interaction analysis, multilevel modeling, and qualitative methods.