Behavioural Decision Sciences Research Interest Group (BDS-RIG)
Co-Leader: Nikolaos Argyris, Lecturer in Operational Research
Co-Leader: Ilkka Leppänen, Lecturer in Operations Management
Our latest workshop: How can AI help us make decisions?
The advent of algorithms and data ubiquity has changed the decision landscape. AI is not only used to support decisions, but decisions are outsourced to it as well. Is that a good thing? Join leading researchers exploring the implications for areas such as public policy, law, insurance and health at our upcoming workshop on 31 March.
Behavioural Decision Sciences (BDS) is a Research Interest Group with the goal of bringing together the rigorous research methods used in decision sciences and the empirical methods that stem from behavioural economics, psychology and sociology. The members of the group are multidisciplinary and use modelling and behavioural methods to understand decision making and generate better models and practices for decision makers and analytics professionals. We use a wide range of research methods, from quantitative modelling and simulation to empirical methods such as dataset analysis, laboratory experiments and field studies.
In alignment with the School’s decision sciences agenda, we aim to generate impactful research to inform and support decision makers across society. Our vision is to be the UK’s leading behavioural decision science group with strong international relations.
- Anna Bennato, Lecturer in Economics
- Enrique Fatas, Professor of Economics
- Alberto Franco, Professor of Management Sciences
- Gilberto Montibeller, Professor of Management Sciences
- Simona Rasciute, Senior Lecturer in Economics
- Anna Raffoni, Lecturer in Accounting
- Duncan Robertson, Lecturer in Management Sciences
- Stewart Robinson, Professor of Management Sciences
- Martin Sykora, Lecturer in Information Management
- Antuela Tako, Reader in Operational Research
- Zoe Anastasiou, PhD student
- Tony Dawson, PhD student
- Tatiana Gherman, PhD student
- Goetz Giering, PhD student
- Naoum Tsioptsias, PhD student
- Professor Martin Eppler (University of St Gallen, Switzerland) http://www.knowledge-communication.org/team.html
- Professor Raimo P. Hamalainen (Aalto University, Finland) http://sal.aalto.fi/raimo
- Professor Etienne Rouwette (Radboud University Nijmegen) https://www.ru.nl/english/people/rouwette-e/
- Professor Detlof von Winterfeldt (Honorary Professor, Loughborough University; University of Southern California, US) http://create.usc.edu/about-create/people/detlof-von-winterfeldt
- Argyris, N, & French, S (2017). Nuclear emergency decision support: A behavioural OR perspective. European Journal of Operational Research, 262(1), 180-193.
- Franco, LA, & Greiffenhagen, C (2018). Making OR practice visible: Using ethnomethodology to analyse facilitated modelling workshops. European Journal of Operational Research, 265(2): 673-684.
- Franco, LA, & Hämäläinen, RP (2016). Engaging with behavioural OR: On methods, actors, and praxis. In M. Kunc, J. Malpass, & L. White (Eds.), Behavioural operational research: Theory, methodology and practice, pp. 3-26: Palgrave Macmillan, London.
- Franco, LA, Hamalainen RP (eds.), (2016), Special Issue on Behavioural OR, European Journal of Operational Research, Vol. 249(3)
- Gogi, A, Tako, AA, & Robinson, S (2016). An experimental investigation into the role of simulation models in generating insights. European Journal of Operational Research, 249(3), 931-944.
- Leppänen, I, Hämäläinen, RP, Saarinen, E, Viinikainen, M (2018). Intrapersonal emotional responses to the inquiry and advocacy modes of interaction: a psychophysiological study. Group Decision and Negotiation (to appear).
- Montibeller, G, & Winterfeldt, D (2015). Cognitive and motivational biases in decision and risk analysis. Risk Analysis, 35(7), 1230-1251.
- Robertson, D. A. (2016). Agent-Based Models and Behavioural Operational Research. In Behavioural Operational Research: Theory, methodology and practice, pp. 137-159: Palgrave Macmillan, London.
- Gruebner O., Sykora M., Lowe S. R., Shankardass K., Galea S. and Subramanian S. V., 2017. Big Data Opportunities for Social Behavioral and Mental Health Research. Social Science & Medicine, In Press, ISSN: 0277-9536, DOI:10.1016/j.socscimed.2017.07.018
- Sykora M., 2016. Engineering Social Media Driven Intelligent Systems through Crowdsourcing: Insights from a Financial News Summarisation System, Journal of Systems and Information Technology, ISSN: 1328-7265, Vol. 18, No. 3, DOI:10.1108/JSIT-03-2016-0019
- Downward, P. & Rasciute, S. (2016). No man is an island entire of itself.’ The hidden effect of peers on physical activity: John Donne, Meditation XVII. Social Science and Medicine, 169: 149-156.
- Downward, P and Rasciute, S. (2015) Assessing the impact of the National Cycle Network and physical activity lifestyle on cycling behaviour in England. Transportation Research Part A: Policy and Practice, 78: 425-437.
Doctoral students join a lively and supportive community of research students, becoming an integral part of the School’s research culture. We welcome approaches from suitably qualified graduates, particularly those with a relevant Master's degree and sufficient funding, who may wish to undertake research projects in the specialist areas of the group, leading to a PhD. As a research student, you will be encouraged to attend conferences to present your work and develop joint publications with your supervisors.
The group has great supervisory experience and is keen to supervise high quality research students in members’ specialist research fields. Recognition of the quality of supervision offered by the group members has resulted in funding for doctoral students from Research Councils. For students interested in further information on potential PhD projects and supervisors, please stay tuned to our webpages.
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