In recent years, a large number of online ratings information about products has emerged on many ecommerce business websites, these online ratings information have significant impact on consumers' understanding products and making purchase decisions. In reality, to make purchase decisions, consumer usually pour their attention to online ratings information of each attribute for products, and give their aspiration of online ratings information of each attribute for alternative products according to their demands. Accordingly, how to select desirable product(s) based on online ratings information and customer's aspirations, it is a noteworthy research issue. On the basis, a method is proposed in this paper for the desirable product(s) selection considering online ratings information and customer's aspiration based on the prospect stochastic dominance. In the method, first, the online ratings information of each attribute for alternative products is crawled by web crawler software, and the gain and loss for the alternative products can be calculated using the attribute rating value and the attribute aspiration, and then the probability distributions about the gain and loss results of each attribute for products are determined according to the obtained gain and loss values. On the basis, the cumulative distribution functions of gain and loss results and their expectations are obtained. Then, based on the obtained cumulative distribution functions of gain and loss values and their expectations, the prospect stochastic dominance relation matrices on pairwise comparisons of products with respect to each attribute are established according to the prospect stochastic dominance rule. Next, the degree of dominance on pairwise comparisons of each attribute of alternative products are calculated using PROMETHEE-Ⅱ method, and the overall dominance degrees matrix for pairwise comparison of products is built using the simple additive weighting method, according to the obtained overall dominance degrees matrix, the "outflow", "inflow" and the ranking values of each alternative products are calculated, respectively. Furthermore, a ranking of the alternative products is determined based on the obtained ranking values Finally, in order to illustrate the feasibility and validity of the proposed method, a case study about car selection is provided based on the online ratings information from the auto-home website.
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