  Intangible capital as the result of digitalization and globalization has not
been fully measured yet in the economy because of several challenges. The
limitation of data sources and the methodological issue related to how to
measure and capitalize intangible assets are some fundamental issues. This
paper aims at studying the contribution of intangible capital to business
performance. The specific intangible capital, such as innovation, intellectual
property, and branding are explored using parametric and machine learning
methods. There are two data sources utilized in this study: survey data and
Google Reviews data. Some variables are utilized as predictors based on the
data sources. The variable selection techniques are implemented, followed by
applying parametric regression and machine learning methods to predict business
performance based on intangible capital variables. The results show that the
proxy of intangible capital used in this paper has a significant contribution
to business performance. In addition, variables that are obtained from google
reviews can be used to predict the use of branding with high accuracy.
