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The Network Perspective: Overview and Implications for Teams

Lauren E. Benishek University of Central Florida. The Network Perspective: Overview and Implications for Teams. What you know doesn’t matter. “It’s not what you know; it’s who you know.” - American Proverb. Why networks?.

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The Network Perspective: Overview and Implications for Teams

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  1. Lauren E. Benishek University of Central Florida The Network Perspective:Overview and Implications for Teams

  2. What you know doesn’t matter “It’s not what you know; it’s who you know.” -American Proverb

  3. Why networks? • Traditional methodology and research focuses on individual characteristics, relies on aggregation for multilevel study, make assumptions about nesting, and focuses on formal relationships (Slaughter, Yu, & Koehly, 2009) • The network perspective focuses on the relationships between individuals • Provides a way to measure social context

  4. Premises and principles • Central premise: individuals’ behaviors and outcomes are significantly affected by how the individual is tied into the social network (Slaughter et al., 2009) • Four core principles (Wasserman & Faust, 1994) • Actors and their actions are interdependent • Relational linkages serve as channels for resource transfer • Social environment structure constrains and provides opportunities to individuals • Structure is conceptualized as enduring patterns of relationships among actors

  5. Talking about networks • Nodes and actors are the individuals, work groups, organizations, and communities in the network of interest • Ego: a specific individual of interest • Altar: other actors in the ego’s network • Ties and connections refer to the relationships between actors

  6. Social network analysis: Mapping populations • Social Network Analysis has roots in social psychology dating back to the 1930’s (Cross, Parker, & Sasson, 2003) • Dr. J. L. Moreno (1934) envisioned mapping the entire population of New York City, and is often credited with the idea of graphing connections

  7. SNA: Not one thing • Social network analysis is a set of analytic tools that can be used to map networks of relationships (Cross, Parker, & Sasson, 2003) • Provides a means for assessing and promoting collaboration • Enables diagnosis of inefficient social functioning • Targets areas for improvements • Can suggest solutions

  8. Definition and network types • A social network is the set of actors (i.e. nodes) and the relationships (i.e. ties) between these actors (Wasserman & Faust, 1994) • Ego-centered network • Egos report on their relationships with alters • Provides a sample of network climate and structure

  9. Network types continued • Complete network • Most common type of network • Measures relational ties of all members in a bounded group • Provides copious information about the group’s social structure • Sociocognitive network or cognitive social structures (CSSs; Krackhardt, 1987) • Extends measurement of complete network to include egos’ perceptions of relationships between alters

  10. Social structure: Centrality • Centrality is the extent to which an actor is embedded in the network • Degree centrality measures the number of direct partners of each actor • Common measure of structural importance • Closeness centrality quantifies the distance between actors • Representative of important interaction features • High centrality characterized by few hops to all alters • Betweenness centrality index of the extent to which an ego falls along the shortest path (termed geodesics) between alters

  11. Social structure: Prestige • Prestigeindexes the number of incoming ties • Often considered to be and used as a measure of an actor’s popularity • Proximity prestige is the closeness of alters to an ego • Status or rank prestige considers the position of alters to whom an ego is tied • Direct ties to prestigious actors may increase the ego’s own prestige

  12. Networks are multilevel • The social network has been partitioned into five levels (Monge & Contractor, 2003) • Individual • Dyad • Triad • Subgroup • Global • Networks are embedded in larger contexts; to understand network changes attention must be given to these larger contexts (Granovetter, 1985)

  13. Networks in team research • SNA can supplement extant research by providing tools that examine the nuances of connection webs • Processes within teams can be assess with more preciseness • Connections can be analyzed across interrelated teams (multiteam systems, MTSs; Mathieu, Marks, & Zaccaro, 2001)

  14. Measuring team networks • Methods for studying team member cognitions are still underdeveloped but more refined methods will be developed with future research in this arena • Network analysis has the potential to provide team and MTS researchers with more insight to and understanding of such processes and emergent states as transactive memory (see Austin, 2003; Lewis, 2003), boundardy spanning (see Marrone, 2010), and information sharing (see Mesmer-Magnus & DeChurch, 2009)

  15. Conclusion • Network analysis can promote the development of new constructs, refinement of old constructs, and methods for analyzing their relationship that are capable of handling highly complex data (Slaughter et al., 2009)

  16. Questions?

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