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Open source software (OSS), a form of Digital or Knowledge Commons, underlies much of the technology that we use in our daily lives. The existence and continuation of OSS relies on the contribution of private resources – personal time, volunteer energy, and effort of numerous actors (e.g., software developers’ time as a common-pool resource) – to public goods, the benefits of which are enjoyed by everyone. Nonprofit organizations such as the Apache Software Foundation (ASF) attempt to aid this process by providing various collective services to OSS projects, acting as a second-order actor in the production of the public good. To this end, the ASF Incubator has created policies – essentially rules or norms – that serve to protect its interests and, as they say, increase the sustainability of the projects. Each policy requires investment by ASF (in terms of money or the use of volunteer time) or an incubating project (in terms of taking project personnel time), the benefits of which can accrue to either party. Such policies may impose additional costs on incubating projects, leading to a decreased production of the OSS public good. Using the ASF Incubator policy documents, we construct a dataset that records who – ASF or an incubating project – bears the cost and who enjoys the benefit of each policy and procedure. We can code most policy statements as costing one party and benefiting one party. The distribution of costs and benefits according to party indicates whether the second-order actor is contributing to an increase in the public good and if they are doing so sustainably. Through a two-way ANOVA, we characterize the impact of ASF policies on the production of public goods (OSS). Being a part of ASF imposes some costs on projects, but these costs may make projects more sustainable. Our analysis shows that the distribution of costs and benefits is fairly symmetric between the ASF and incubating projects. Thus, the configuration of policies or the “institutional design” of the ASF could aid in producing the OSS public good by providing services that projects require. 

Institutions—defined as strategies, norms and rules (Ostrom Understanding institutional diversity, Princeton University Press, Princeton, 2005)—are omnipresent in third sector contexts. In this paper, we present the Institutional Grammar (IG) as a theoretically informed approach to support institutional analysis in third sector research. More specifically, the IG coding syntax allows the researcher to systematically wade through rich text and (transcribed) spoken language to identify and dissect institutional statements into finer syntactical segments of interest to the researcher. It is a versatile method that can generate data for small- or large-N research projects and can be integrated with mixed-method research designs. After first introducing and describing the IG, we present a case study to illustrate how a IG-based syntactic analysis can be leveraged to inform third sector research. In the case, we ask: Do the rules embedded in regulatory text addressing the involuntary dissolution of charity organizations differ between bifurcated and unitary jurisdictions in the United States? Using IG’s ABDICO 2.0 syntax, we identify eleven “Activation Condition” (AC) categories that trigger action and assess variation among the 46 jurisdictions. We ultimately conclude that the rules do not differ between bifurcated and unitary jurisdictions, but that finding is not the primary concern. The case demonstrates IG as an important methodological advance that yields granular, structured analyses of rules, norms and strategies in third sector settings that may be difficult to identify with other methods. We then emphasize four areas of third sector research that could benefit from the addition of IG-based methods: analysis of (1) rule compliance, (2) inter-organizational collaboration, (3) comparative study of institutional design, and (4) the study of institutional change. We close the paper with some reflections on where IG-based analysis is headed.