DECAS: a modern data-driven decision theory for big data and analytics

Decisions continue to be important researchers, organizations and societies. However, decision research requires re-orientation attain the future of data-driven making, accommodating such emerging topics information technologies as big data, analytics, machine learning, automated decisions. Accordingly, there is a dire need for re-forming theories encompass new phenomena. This paper proposes modern theory, DECAS, which extends upon classical theory by proposing three main claims: (1) (big) data analytics (machine) should considered separate elements; (2) collaboration between (human) maker can result in collaborative rationality, extending beyond classically defined bounded rationality; (3) meaningful integration making elements with lead more informed, possibly better, elaborates DECAS clarifies idea relation examples