New applications for importance-performance analysis (IPA) in higher education : Understanding student satisfaction

Purpose The constantly evolving higher education (HE) sector is creating a need for new business models and tools for evaluating performance. In this paper, an overview of the importance-performance analysis (IPA) model and its applicability as a management tool for assessing student satisfaction in the HE sector is provided. The purpose of this paper is to apply IPA in a new and novel manner, undertaking analysis at three levels; the individual student, for individual attributes and at a construct or factor level which combines individual attributes that are correlated. A practical application is illustrated, assessing the gap between the importance placed on specific student satisfaction attributes and corresponding levels of student-perceived performance realised. Design/methodology/approach The “service product bundle” (Douglas et al. , 2006) is refined based on focus group evaluation. Survey responses from 823 students studying across four Malaysian private universities are analysed using factor analysis and the IPA model utilised to identify importance-performance gaps and explore the implication of the iso-rating line as well as alternative cut-off zones. Findings Factor reduction of 33 original measurement items results in eight definable areas of service provision, which provides a refined and extended management tool of statistically reliable and valid constructs. Research limitations/implications The research is undertaken in a private business school context in Malaysia. Further research could focus on other universities or countries, as well as faculties such as computing and engineering or explore other elements of education-based performance. Practical implications The research method and study outcomes can support HE managers to allocate resources more effectively and develop strategies to improve quality and increase student satisfaction. Originality/value Distinct from other IPA-based studies, analysis is undertaken at three levels; the individual participant, for individual items and at the factor level.