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Intangible capital as the result of digitalization and globalization has notbeen fully measured yet in the economy because of several challenges. Thelimitation of data sources and the methodological issue related to how tomeasure and capitalize intangible assets are some fundamental issues. Thispaper aims at studying the contribution of intangible capital to businessperformance. The specific intangible capital, such as innovation, intellectualproperty, and branding are explored using parametric and machine learningmethods. There are two data sources utilized in this study: survey data andGoogle Reviews data. Some variables are utilized as predictors based on thedata sources. The variable selection techniques are implemented, followed byapplying parametric regression and machine learning methods to predict businessperformance based on intangible capital variables. The results show that theproxy of intangible capital used in this paper has a significant contributionto business performance. In addition, variables that are obtained from googlereviews can be used to predict the use of branding with high accuracy.

Measuring Intangible Assets Using Parametric and Machine Learning Approaches