Combining Importance-Performance Analysis with Analytic Hierarchy Process for Enhancing Satisfaction

Abstract

This paper aims to explain how to combine the importance-performance analysis (IPA) and the analytic hierarchy process (AHP) to make a better decision. We investigate the relevant relationships among the attributes for enhancing satisfactions on online education services by combining the methodologies of both IPA and AHP. In the course of estimating pair-wise comparisons among attributes, the back-propagation neural network is employed. As an empirical study, we consider how to manage the important attributes (or factors) for enhancing satisfactions on online education services. A questionnaire survey on satisfactions of online courses for Korean Scholastic Aptitude Test was conducted. IPA is a simple but useful technique to determine the status of attributes, but it does not indicate how each attribute should be treated to enhance a managerial goal. However, combination of IPA & AHP can answer the question of what to do with attributes to achieve a goal, which is satisfying customers in this paper. IPA and AHP are very powerful methods, respectively, but when combined, the effect is more than doubled. It is attempted to combine the two very useful methods, IPA & AHP, and the results indicate not only the current status of the attributes, but also the direction of them to achieve a goal. 