Online product purchasing decision through IoT platform: based on normal stochastic multi-criteria decision method and vertical projection distance

Online product reviews in the internet of things platform have important implications for consumers’ buying decisions. Considering the large volume and discrete stochastic characteristics of online review information, an online product purchasing decision method based on normal stochastic multi-criteria decision and vertical distance method is proposed. Firstly, we present and prove the weighted arithmetic average operator under normal stochastic information environment. Then, the idea of vertical projection distance is introduced, according to the binary structure of expectation and variance in the stochastic attribute information, a nonlinear programming model for calculating the product attribute weights is designed. Based on this, the weighted arithmetic average operator is used to aggregate the decision information from the attribute dimension, and the priority order of the candidate products is obtained according to the order relation of the binary structure of normal stochastic attributes. Finally, a case study of mobile phone purchase decision-making is carried out to verify the rationality and practicability of this method.