Decision making by extracting soft information from CSR news report

Abstract

This study examines the impact of corporate social responsibility (CSR) news reports on corporate operating performance forecasting using a large database of publicly-listed electronics firms in Taiwan. Applying text mining techniques and latent topic modelling, we construct and measure the intensity of the CSR-corpus index (ICSRI), which can compress tremendous amounts of CSR textual information content into synthesized meaningful dimensions. By doing so, we are able to break down CSR news reports into multiple dimensions and then examine which dimension(s) affects operating performance. To offer decision-makers with a comprehensive, overarching view of the corporate’s operations, this study incorporates balanced scorecards (BSC) and multiple criteria decision analysis (MCDA) to form a final performance rank. The proposed approach, supported by real samples, can assist both internal and external stakeholders in allocating scarce resources to specific CSR dimensions to enhance a corporate’s growth potential as well as to achieve a win-win situation.

Keywords

• corporate social responsibility
• multiple criteria decision analysis
• text mining
• topic modelling
• decision making