论文标题
使用参数和机器学习方法测量无形资产
Measuring Intangible Assets Using Parametric and Machine Learning Approaches
论文作者
论文摘要
由于有几个挑战，在经济中尚未完全衡量数字化和全球化的无形资本。数据源的局限性以及与如何衡量和资本化无形资产有关的方法论问题是一些基本问题。本文旨在研究无形资金对业务绩效的贡献。使用参数和机器学习方法探索了特定的无形资本，例如创新，知识产权和品牌。这项研究中有两个数据源：调查数据和Google审查数据。一些变量根据数据源被用作预测因素。实施了变量选择技术，然后应用参数回归和机器学习方法来预测基于无形资本变量的业务绩效。结果表明，本文使用的无形资本的代理对业务绩效有重要贡献。此外，可以使用从Google评论获得的变量可用于预测品牌的使用高度准确性。
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.
