Assessing the potential demand for electric cars

Abstract An ordered logit specification for use on ranked individual data is used to analyze survey data on potential consumer demand for electric cars. In many situations in economics and marketing we would like to be able to forecast consumer demands for goods which have not yet appeared in actual markets. By defining goods as a bundle of underlying attributes, we can use discrete choice models to estimate consumer evaluations. Then new good demand is forecast by use of the estimated coefficients to compare consumer evaluation of the new good to existing choices. When ranked individual data are available, we can estimate separate coefficients for each individual rather than assuming identical coefficients as is usual with logit models. Our results indicate considerable dispersion in individual coefficients. This finding can have important implications for new product analysis.