An evaluation index system for intellectual capital evaluation based on machine learning

Currently, there is not yet a mature evaluation index system of intellectual capital among enterprises. The lack of such a system hinders the smooth transform of capital to enterprise value. Therefore, this paper attempts to set up an effective and objective evaluation index system for intellectual capital. First, the data on intellectual capital were collected from some enterprises from the Growth Enterprise Market (GEM). Next, the original data were preprocessed into 1770 effective pieces of data. On this basis, 13 indices were selected from three dimensions (e.g. human capital, structural capital, and relationship capital) of intellectual capital, forming an evaluation index system. After that, the evaluation index system was verified with two machine learning (ML) algorithms, namely, random forest (RF), and support vector machine (SVM). The results show that our evaluation index system can optimize the intellectual capital classification of enterprises, avoiding the subjective defects in qualitative evaluation. The research results shed important new light on the decision-making and scientific management of enterprises.