On Minimum Deviation Product Aspect Ranking Using Goal Programming

Abstract

Product aspects are differently handled and not consistent among online reviews. Variable characteristics and importance of each aspect through reviews requires ranking process that enable customers, organizations and marketers to identify and use optimal set of aspects that best support product selection, development, and marketing. Identifying the most representative product aspects, and determine their degree of importance in such a way that best support product selection, development, and marketing has been addressed in this paper. The proposed solution in this paper is to determine the importance degree of each aspect from online reviews to perform aspect ranking. Aspect importance determination is formulated as a multi-criteria decision making (MCDM) problem, several criteria for importance determination have been adopted, and a goal programming (GP) model is constructed to identify and select the best product aspects that can support product purchasing decisions by selecting weight values that best maintain their importance. Several experimental tests are performed and the results showed that using GP can perform aspect ranking and maintain aspect importance at minimum deviation compared to the other related methods.