However, house sale prices tend to be spatially autocorrelated due to shared neighborhood environments and similar physical characteristics, which have been rarely considered and accounted for in the random forest model. The random forest model has been frequently used for house sale price prediction because researchers have shown that it can create better results with smaller prediction errors than conventional statistical models. Soy milk, rice milk and almond milk entertained complementary relationships between each other and four types of conventional milk were strong substitutes within the group. Soy milk exerted substituting effects on all types of conventional milk products and vice versa. Three plant milk types had inelastic demand. Estimation results showed that the highest own-price elasticity pertained to soy milk which was в€’0.25. Estimations began with creating a multidimensional hedonic attribute space based on the qualitative information of different types of plant milk and conventional milk available to consumers and then calculating the hedonic distances by Euclidean distance measurement to reparametrize BartenвЂ™s synthetic demand system. A research dataset was uniquely created by associating the productsвЂ™ purchase data from Nielsen Homescan dataset with exclusive first-hand nutritional data. The method of estimation is enlightened from the common practice of companies differentiating their products in multidimensions in terms of attributes. This study is motivated by the need to take into consideration varied nutritional and qualitative attributes in plant milk to examine consumersвЂ™ purchasing behavior and estimate demand elasticities which are achieved by a new approach combing hedonic pricing model with BartenвЂ™s synthetic demand system. increasingly prefer plant-based milk alternative beverages (abbreviated вЂњplant milkвЂќ) to conventional milk.

Hedonic price model