Prioritising engineering characteristics based on customer online reviews for quality function deployment

In market-driven product design, customer requirements (CRs) are usually obtained from consumer surveys. However, valuable CRs can also be found in a large number of online reviews. Largely due to their free text nature and the quantity, these reviews are often neglected and are seldom utilised directly by designers. In this work, one important question in quality function deployment on how to prioritise engineering characteristics (ECs) is investigated. Customer opinions concerning ECs are extracted from online reviews. By taking advantage of such opinion information, an ordinal classification approach is proposed to prioritise ECs. In a pairwise manner, in which customer opinions are deemed as features and the overall customer satisfactions are regarded as the target values, the weights of ECs are derived. Furthermore, an integer linear programming model is implemented to convert the pairwise results into the original customer satisfaction ratings. Finally, an exploratory case study is presented using reviews of four branded printers collected from Amazon and their analysis was conducted by two experienced design engineers. The experimental study reveals the merits of the proposed approach.