Supporting consumer’s purchase decision: a method for ranking products based on online multi-attribute product ratings

Abstract

Online product ratings, as a type of electronic word-of-mouth, play an important role for helping consumers select desirable products, but it is difficult for consumers to read a large number of online ratings on e-commerce Web site. To support consumer’s purchase decision, how to rank the candidate products based on online product ratings and consumer’s preferences is a noteworthy research topic, while the existing studies concerning this issue are still relatively scarce. This paper proposes a method for ranking products based on online multi-attribute product ratings. In the method, a discrete percentage distribution of the evaluation of each candidate product with respect to each attribute based on online ratings is first constructed, and the $$3\sigma $$ criterion is used to eliminate the anomalous ratings. Then, by defining of the stochastic dominance rules and the stochastic dominance degrees on comparing two discrete percentage distributions, the stochastic dominance relation between each pair of products is determined, and the corresponding stochastic dominance degree is calculated. Further, according to the obtained stochastic dominance degrees, the ranking of candidate products can be determined using the PROMETHEE-II method. A case study on selecting the automobile is given to illustrate the use of the proposed method.