A textual data-driven method to identify and prioritise user preferences based on regret/rejoicing perception for smart and connected products

The rapid development of information technologies yields a promising market for information densely products, i.e. smart, connected products (SCPs) and also alters the way of user-designer interaction in the product design and development. Online review has become a convenient and efficient way to express customers' opinions and preferences on products they have bought. In order to identify and prioritise customer needs in the smartness connected era, this study proposes a novel textual data-driven and regret/rejoicing perception-based user preferences identification and priority framework for SCPs. We first dig customer needs and evaluations from online customer reviews, then design a new directional distance index-based approach to acquire user weights. Combining absolute and relative weights, we introduce an integrated approach to prioritise all customer preferences. Specially, absolute weights are obtained by an improved Borda method based on frequency and position information, while relative weights are determined through probabilistic linguistic-based regret/rejoicing decision-making method. Finally, an application of 12 kinds of smart speakers is constructed and discussed to illustrate the feasibility and usefulness of the proposed approach, and these corresponding results are helpful for smart design, development and improvement of SCPs.