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ABSTRACT Institutional arrangements that guide collective action between entities create benefits and burdens for collaborating entities and can encourage cooperation or create coordination dilemmas. There is an abundance of research in public policy, public administration, and nonprofit management on cross‐sector alliances, co‐production, and collaborative networks. We contribute to advancing this research by introducing a methodological approach that combines two text‐based methods: institutional network analysis and cost–benefit analysis. We utilize the Institutional Grammar to code policy documents that govern relationships between actors. The coded text is then used to identify Networks of Prescribed Interactions to analyze institutional relationships between policy actors. We then utilize the coded text in a cost–benefit analysis to assess benefit and burden distributive effects. This integrated methodological framework provides researchers with a tool to elucidate both the institutional patterns of interaction and distributive implications embedded in policy documents, revealing insights that single‐method approaches cannot capture. We then utilize the coded text in a cost–benefit analysis to assess benefit and burden distributive effects. This integrated methodological framework provides researchers with a tool to elucidate both the institutional patterns of interaction and distributive implications embedded in policy documents, revealing insights that single‐method approaches cannot capture. To demonstrate the utility of this integrated approach, we examine the policy design of two nonprofit open‐source software (OSS) incubation programs with contrasting characteristics: the Apache Software Foundation (ASF) and the Open Source Geospatial Foundation (OSGeo). We select these cases because: (1) they are co‐production alliances and have policy documents that articulate support for collective action; (2) their policy documents and group discussions are open access, creating an opportunity to advance text‐based policy analysis methods; and (3) they represent juxtaposed examples of high and low risk for collaboration settings, thereby providing two illustrative cases of the combined network and cost–benefit text‐based methodological approach. The network analysis finds that ASF policies, as a high‐risk setting, emphasize bonding structures, particularly higher reciprocity, which creates a context for cooperation. OSGeo, a low‐risk setting, has policies creating a context for bridging structures, evident in high brokerage efficiency, to facilitate coordination. The cost–benefit analysis finds that ASF policies balance the distribution of costs and benefits between ASF and projects, while in OSGeo, projects bear both costs and benefits. These findings demonstrate that the combination of network and cost–benefit analysis is an effective tool for utilizing text to compare policy designs.