The article compares different methods for creating efficient designs in choice experiments for climate change adaptation measures in Kenya. The researchers found that Gaussian quadrature outperformed quasi-Monte Carlo simulations and pseudo-random Monte Carlo in generating these designs. They also noted that the performance of these methods may vary depending on the type of choice model used, such as multinomial logit or mixed logit models.