Association for Public Policy Analysis & Management

Policy-makers at the federal, state, and local levels devote billions of dollars to subsidize residential solar photovoltaic (PV) diffusion. Because these subsidy policies rely on individual adoption decisions to generate the beneficial outcomes they promote, the design of effective programs to implement subsidy policies requires an understanding of the individual adoption decision-making process. However, there are often multiple theoretical lenses through which a single phenomenon – such as the diffusion of solar PV – can be explained. Choosing a powerful theoretical lens yields diagnostic insight to the structure and evolution of the diffusion process that can inform policy design and program implementation. In this research, we develop a framework for making an informed choice of theoretical lens.

Rather than choose a single theoretical lens, we build three agent-based models (ABMs) of solar PV diffusion that explain adoption decision-making with rules derived from two different theoretical foundations; (1) a purely social influence-oriented approach based on complex contagions, (2) a cognitive agent approach based on the Theory of Planned Behavior and opinion dynamics, and (3) a hybrid of the first two. We then compare across models on two features: the relationship between modeling error and parameterization of each theoretically-derived mechanism and the policy recommendations that stem from the choice of theoretical lens. Precise parameterization-error relationships in a model reflect the explanatory power of a particular choice of theoretical lens, while the stability of policy recommendations across models demonstrates insensitivity to theoretical lens choices. With this framework for directly comparing theories of individual decision-making we address a perennial question for policy scholars – from whom should I borrow?