DECAS : A Modern Data-Driven Decision Theory for Big Data and Analytics

• Decisions continue to be an essential topic of utmost importance in every research field and era. However, while decision research has extensively offered a wide range of theories, it remains delved in the past, and needs robustness to sustain the future of data-driven decision-making, encompassing topics and technologies such as big data, analytics, machine learning, and automated decisions. Nowadays, decision processes have evolved, the role of humans as decision makers has changed and become inevitably intertwined with the support of machines, rationalities are no longer limited in the same way, data has become an abundant commodity, and the optimizing of decisions is not so far-fetched a tale as it once was in classical times. Accordingly, there is a dire need for new theories to support new phenomena. This paper aims to propose a modern data-driven decision theory, DECAS, to support the new elements of today’s decisions. Our theory extends upon classical decision theory by proposing three main claims: the (big) data and analytics should be considered as separate elements along with the decision-making process, the decision maker, and the decision; the appropriate collaboration between the decision maker and the analytics (machine) can result in a “collaborative rationality,” extending beyond the bounded rationality which decision makers were classically characterized by; and finally, the proper integration of the five elements, and the correct selection of data and analytics, can lead to more informed, and possibly better, decisions.  Hence, the theory is elaborated in the paper, and introduced to some data-driven decision examples.

Subject headings

SAMHÄLLSVETENSKAP  -- Medie- och kommunikationsvetenskap -- Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning (hsv//swe)

SOCIAL SCIENCES  -- Media and Communications -- Information Systems, Social aspects (hsv//eng)

Keyword

Data-driven decision making

Big data

Analytics

Automated decisions

Decision theory

Algorithmic decisions

Information systems

Informationssystem

Publication and Content Type

ref (subject category)

art (subject category)