This study examines the factors that can increase consumer participation rates in green pricing programs by conducting a choice experiment in South Korea. Estimation results were obtained from a conditional logit, conditional logit with interaction terms, random parameter logit, random parameter logit with correlation, and individual-level coefficient models. A novelty of our analysis was the consideration of monetary and non-monetary incentives as factors influencing consumer uptake in green pricing programs. The estimation results show that increased consumer participation in green pricing programs is positively linked with green energy sources that produce fewer externalities, more jobs, and monetary incentives such as tax credits or green mileage. However, there is an inverted U-shaped relationship between participation rates and the share of green electricity in total electricity supply. Mean willingness to pay for fuel cells is highest, followed by solar and wind energy. Estimation from the random parameter logit with allowing for correlations among random coefficients of attributes reveals that consumers are divided into ‘green (pro-environment) consumers’ and ‘blue (growth-oriented) consumers’. Green consumers prefer a higher green electricity share, solar or fuel cell to wind, a greater proximity of green power plants to their homes, and green mileage or green parks to tax credits. In comparison, ‘blue consumers’ favor a lower green electricity share, green power plants that are far from their homes, and monetary incentives rather than non-monetary incentives. The results of this study suggest guidelines for the design of successful green pricing programs. Green pricing programs that are designed with information on types of green energy sources, consider the distance of power plants to consumers' residences, focus on the share of green electricity, and incorporate monetary incentives are likely to have increased consumer participation rates.