Limits to Profit Maximization as a Guide to Behavior Change

Abstract Economists have long been interested in why farmers decide to adopt new technologies. Modeling decision making requires modeling behavior; the key behavioral assumption is profit maximization. In addition, most empirical studies assume a binary decision—adopt or not. This paper argues that adoption should be understood as a process with multiple stages in which the final decision to use the new technology only occurs if the previous stages are completed. While profit considerations are clearly important, particularly in the later stages of the process, they need to be supplemented with other social and cognitive considerations, particularly in the early stages. Understood this way, profit maximization assumptions can provide predictions for the upper or lower bounds of adoption. The adoption rate suggested by profit maximization will be an upper bound if noneconomic factors are expected to either slow down or deter adoption, while that rate will be a lower bound if noneconomic factors are expected to encourage adoption. To capture these elements, econometric models need to pay attention to the timing of decisions and use techniques that condition later‐stage decisions on previous stage outcomes. In addition, the paper suggests the use of expert systems that have economic, learning and social aspects explicitly built into them would be valuable.