An uncertain Kansei Engineering methodology for behavioral service design

Abstract

To perfect a service, service providers must understand the fundamental emotional effects that a service may invoke. Kansei Engineering (KE) has been recently adapted to service industries to realize the relationships between service design elements and customers’ emotional perceptions. However, effective service design based on KE is still seriously challenged by the uncertainty and behavioral biases of customers’ emotions. This article tries to propose an uncertain KE methodology for behavioral service design. To do so, an integrative framework is first proposed by linking design attributes, emotional needs, and overall satisfaction, so as to design services best satisfying customers’ emotional needs. Second, multinomial logistic regression is used to build the uncertain relationships between design attributes and emotional attributes. Third, a quantitative Kano model is proposed to model the asymmetric and nonlinear satisfaction functions reflecting the “gains and losses” effect of positive emotions and negative emotions. Next, the Prospect Theory is used to derive customer overall satisfaction by distinguishing the “gains and losses”. Finally, the proposed methodology is applied to a case study of the campus express delivery service in China. An independent tracking study shows that the results are consistent with service acceptance and provide valuable insights.