Purpose: This study aims to explain the use of Importance and Importance Analysis (IPA) with a diagonal regression approach and standard error of estimation (SEE) in the case of lecturers in intellectual capital universities in Indonesia.
Theoretical framework: The Lecturer Study of Intellectual Capital University is closely related to the excellence of Human Resources, individually and collectively as a key factor for higher education excellence. Science analysis can produce strategic considerations to improve the overall performance of higher education institutions.
Method/design/approach: The research design uses a quantitative approach; the population is all university lecturers in Indonesia. Scale data is in the form of semantic differential, questionnaires are made in Google forms which are shared using social media: email, WhatsApp’s and telegrams. There were 225 answers worthy of analysis, coming from 65 universities spread across 14 provinces in Indonesia. Furthermore, the data were analyzed using Importance and Importance Analysis with a diagonal regression approach and standard error of estimation.
Results and conclusion: The study results show that a high difference in the mean importance and importance does not necessarily indicate irrelevant performance, because the spread of the data must be checked from the estimated standard error according to the considered level of accuracy. It is concluded that lecturers at intellectual capital universities in Indonesia currently need improvement in the fields of academic position, learning skills, and relationships between lecturers. Besides that, the indicators that need improvement are innovation, relativity, and lecturer involvement in method-making.
Research implications: University lecturers are one of the key factors in the development of universities today. With the presence of lecturers, the university can carry out its business processes as a higher education institution. It seems that this research has not been responded well by all lecturers in Indonesia, it is evident that only 225 respondents want to be involved in this research, even though the benefits are considered very strategic for fostering the role of lecturers in improving the quality of universities as a whole, then the use of semantic differential scales is very suitable for analysis IPA because the data can be implemented directly in the analysis, there is no need for data transformation.
Originality/value: Science studies in the field of Intellectual Capital are still new, as well as the use of semantic differential scales and diagonal regression approaches with standard error estimation that have not been found in previous literature.