Collective action networks are complex systems of interrelated individuals or groups that come together for a common social change purpose (Ernstson, 2011). Researchers have used social network analysis (SNA) to examine the relationship structures and characteristics of collective action networks. However, determining whether collective action networking produces outcomes has been challenging because networks are complex, affected by context, and produce interdependent data. I addressed these challenges by pairing SNA with qualitative comparative analysis (QCA), a configurational comparative method. Using QCA, researchers can tease out which conditions are necessary or sufficient to produce an outcome. I analyzed a collective action network of community-based resource management groups in Hawaii using SNA. Then, I analyzed the same network using an explanatory mixed methods case study. Finally, I used QCA to integrate the quantitative SNA data with qualitative case study data to determine what conditions were necessary and sufficient to achieve the network’s desired outcomes. Finally, I reviewed the results from using these different methods to explore how QCA can be a useful tool for evaluators to add to their network evaluation toolkit.
","abstract_html":"<p>Collective action networks are complex systems of interrelated individuals or groups that come together for a common social change purpose (Ernstson, 2011). Researchers have used social network analysis (SNA) to examine the relationship structures and characteristics of collective action networks. However, determining whether collective action networking produces outcomes has been challenging because networks are complex, affected by context, and produce interdependent data. I addressed these challenges by pairing SNA with qualitative comparative analysis (QCA), a configurational comparative method. Using QCA, researchers can tease out which conditions are necessary or sufficient to produce an outcome. I analyzed a collective action network of community-based resource management groups in Hawaii using SNA. Then, I analyzed the same network using an explanatory mixed methods case study. Finally, I used QCA to integrate the quantitative SNA data with qualitative case study data to determine what conditions were necessary and sufficient to achieve the network’s desired outcomes. Finally, I reviewed the results from using these different methods to explore how QCA can be a useful tool for evaluators to add to their network evaluation toolkit.</p>","abstract_has_math":false,"creators":["Gowensmith, Debbie"],"institution":null,"degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":null,"degree_department":null,"school":null,"contributors":["Robyn Thomas Pitts","Nicholas Cutforth","Antonio Olmos"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-01T08:00:00Z","date_published":"2022-01-01T08:00:00Z","updated_at":"2026-07-24T02:02:38Z","subjects":["Collective action network","Community-based resource management","Evaluation","Network evaluation","Qualitative comparative analysis","Social network analysis","Community-Based Research","Other Statistics and Probability","Statistics and Probability"],"languages":["en"],"rights":["Copyright is held by the author. User is responsible for all copyright compliance.
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"],"dc:subject":["Collective action network","Community-based resource management","Evaluation","Network evaluation","Qualitative comparative analysis","Social network analysis","Community-Based Research","Other Statistics and Probability","Statistics and Probability"],"dc:title":["Expanding the Network Evaluation Toolkit: Combining Social Network Analysis & Qualitative Comparative Analysis"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."]},"updated_at":"2026-07-24T02:02:38Z"}