Predicting Firm Performance Using ESG Scores, Annual Reports, and Patents

Authors

Chiayu Lai, National Pingtung University of Science and TechnologyFollow
Deng-Neng Chen, National Pingtung University of Science and TechnologyFollow
Yu Tsuo, National Pingtung University of Science and TechnologyFollow
Jun-Hong Liu, National Pingtung University of Science and TechnologyFollow

Paper Number

1676

Abstract

Data analytics has become a recent trend. Prior studies on predicting the future financial direction and enterprises change mainly focus on using a single variable-oriented analysis to examine the impact of corporate finance. In addition to the quantitative data on financial statements, many studies also attempt to adopt publicly disclosed documents to forecast company performance. This paper aims to propose a predictive model for firm financial performance by extracting economic indicators and multi-faceted features based on patents, annual reports, and environmental, social, and corporate governance (ESG) scores by applying machine learning classifiers. Experimental results show that patent and ESG scores significantly impact earnings per share (EPS) and Tobin’s Q. The results of our analysis also should be of interest to firms in improving their patenting strategies and ESG scores and to investors in assisting their investment decisions.

Comments

Paper Number 1676

Recommended Citation

Lai, Chiayu; Chen, Deng-Neng; Tsuo, Yu; and Liu, Jun-Hong, "Predicting Firm Performance Using ESG Scores, Annual Reports, and Patents" (2022). PACIS 2022 Proceedings. 129.
https://aisel.aisnet.org/pacis2022/129