| Title |
A Study on the Prediction Model of Small and Medium Enterprise Growth using Big Data Analysis Techniques |
| Authors |
모혜란(Hye-Ran Mo) ; 김현경(Hyun-Kyung Kim) ; 김현(Hyun Kim) |
| DOI |
https://doi.org/10.5573/ieie.2023.60.3.115 |
| Keywords |
PCA; Feature importance; Forecast model; Big Data |
| Abstract |
Through this paper, we would like to introduce a predictive model for the future growth potential of SMEs based on corporate big data analysis. In particular, financial data is the most important variable related to corporate growth. In previous studies, financial status is frequently used to predict corporate growth potential. However, in this paper, the company's financial data and the company's stock price are used as major variables to predict the company's growth potential. Based on Feature Importance, major variables related to corporate growth were selected. It was confirmed that the company's financial position and stock price are related to each other using the K-Means algorithm. This is because various indicators such as the possibility of a company's entry/expansion into the market, technological advantage/discrimination and expertise, management ability, growth, profitability, and stability are reflected in the company's stock price. In this paper, we were able to propose a model that can predict a company's growth potential using PCA and Feature Importance. |