Revolutionizing Stated Preference Design for Maximum Efficiency in Experiments
Stated Preference experiments are popular but designing them well can be tricky. Researchers have found a way to automatically generate good designs using algorithms. They analyzed different choices in the design to improve efficiency and suggested replacing the least efficient choice with a better one. Through simulation, they were able to create a satisfactory design by iterating this process.