Improving strategic decision making with big data-based media analysis - the case of coal power

Abstract

Big data-based methods are currently being developed to aid corporate decision making. This study utilises a big data-based global media analysis to clarify the role of a coal power-related media image in company decision making. Opinion mining is carried out by utilising a specific software tool designed for media analysis and monitoring. The analysis is based on the notion that the media image of company productsor of a specific technologymay have an impact on corporate investment and divestment decisions in the energy production sector. The assumption is that a coal power-related media image may cause corporate brand image-related pressures. The findings indicate that the general media sentiment towards coal power clearly appears to be negative, possibly influencing decisions at the corporate level. It appears that the large negative media sentiment towards coal power in general may override the potential benefits of developing more unknown, cleaner types of coal power and related technologies such as carbon capture and storage (CCS) and carbon capture and utilisation (CCU). Hence, the negative media sentiment towards coal power may mitigate the potentially more positive image of related less well-known technologies. Evidence is provided on the media impact of coal power-related divestment decisions and potential impacts on decision making.