School of Business and Economics


Götz Heinrich Giering

Photo of  Götz Heinrich Giering

Doctoral Researcher in Management Science and Operations

Multi-attribute Decision Making, Behavioural OR, Decision Theory

Götz joined Loughborough University as a doctoral researcher in Management Science in January 2017. Prior to his PhD studies, he undertook a Masters in Business Analytics Consulting at Loughborough University in 2016. His undergraduate degree in International Business Studies was granted from Friedrich-Alexander Universität in Erlangen-Nürnberg and involved courses in Germany, China and South Korea. Over the course of his education he was able to secure multiple scholarships to support his development.

His extra-curriculum activities involved being a programme representative for his master course, as well as being a member of entrepreneurial student societies in Germany and Switzerland.

He gained professional experience during his studies as a student worker at Fraunhofer Institute, and several entrepreneurial projects. Götz holds numerous certificates, e.g. for his involvement for The Institute for Peace Affairs in Seoul, and for his achievements as a programme rep and his work with SAS software during the completion of his master degree.

His personal interests besides research include travelling, investment, chess, and football.

Working Title: Process Tracing the Choice Quality in Riskless Multi-attribute Decisions

Abstract: Empirical findings from behavioural research suggest that individuals employ a range of strategies to construct their preferences when faced with multi-attribute (MA) choice problems. However, it is not well understood what information decision makers use when making a MA choice, and if training decision makers can improve MA choice quality. My project is an ongoing behavioural study that adopts a process-tracing approach to evaluate preference construction processes in terms of quality. The study involves a set of hypothetical choice problems, and utilises normative standards as benchmark to compare against observed decision processes. By doing so, this study goes beyond consistency checks and thus has the potential to identify underlying causes for deviations from the value model. The study findings will enable the development of recommendations to improve decision making processes in MA choice problems.  

Supervisors: Prof. Gilberto Montibeller & Prof. L. Alberto Franco