The aim of this paper is to introduce a regression-based analytical framework for developing service improvement strategies which account for asymmetric effects in customer satisfaction and loyalty. A hierarchical research design is applied to minimize the risk of multicollinearity. The high managerial value of the framework is demonstrated in a case study on airline passenger satisfaction. A four-dimensional importance-performance analysis is used to derive improvement-priorities of the main components of airline passenger services, whereas several determinance-asymmetry analyses are used to derive priorities of the service attribute forming the service components. |