Digital decision support

Decision makers need to make informed decisions to effectively reach their goals. This theme therefore aims to develop and improve methodology for obtaining data-driven insights in contexts of the digital society.  How can digital technology be used to improve decision making? What methods are necessary to enable this? How can we ensure that methods are statistically sound and robust? How do we ensure that technologies such as AI remain fair, explainable, and aligned with the goals in organisations and society? How does increased digital decision support affect human decision making? Does digital decision support always improve decision quality for everyone?

Digitalisation has contributed to a dramatic rise in the amount of data available in professional contexts. This has had a large impact on how decisions are made in individuals, companies, other organisations, and in society in general. In principle, the availability of detailed data allows people and organisations to better understand their environment. Digital media also offer increasing possibilities to support behavioral change based on such data, which can improve wellbeing and increase productivity.  

However, actually obtaining knowledge from the abundantly available data is not straightforward. The intrinsic value of the data increases with more detail and so does the complexity of the analysis task. Although there are rapid developments in artificial intelligence and machine learning, these methods are not always directly applicable to business or societal questions due to low predictability in those domains. Further work is needed to tailor methods for applications in these fields in general and related to work, prosperity, and entrepreneurship in particular. In addition, the impact of applications of digital decision support tools in, for instance, human resource management, related health psychology, logistics, marketing, finance, and accounting will be studied, both at the level of individuals and of organisations as a whole.