Ganna Pogrebna

Academic, Educator, Consultant, Blogger


Publish or Perish Citations


Total Grants 2011-2018


Grant Application Success Ratio 2011-2017

Citations per Year


Accepted papers in 2014-2018

Areas of Focus

Economics & Business

Risk and Decision Making
Decision and Game Theory
Behavioural Science

Science & Engineering

Digital Economy
Vulnerability to Cybersecurity Risks
Personal Data
Data Analytics
Smart Cities

I am a Professor of Behavioural Economics and Data Science at the University of Birmingham, Fellow at the Alan Turing Institute, and Fellow at the Warwick Manufacturing Group (WMG). I studied Economics at the University of Missouri Kansas City (US) and the University of Innsbruck (Austria). I hold a Ph.D. in Economics and Social Sciences. Before coming to Birmingham, I worked as a postdoctoral research fellow Columbia University in New York (USA), the University of Bonn (Germany), Humboldt-Universität zu Berlin (Germany), the University of Innsbruck (Austria), and the Department of Economics at the University of Warwick (UK). I also held positions of the Leverhulme Research Fellow, Research Assistant Professor, and Research Senior Lecturer in the Department of Economics at the University of Sheffield and worked as an Associate Professor of Decision Science and Service Systems at WMG (University of Warwick). In November 2017 I was awarded ESRC-Turing Fellowship by the Economic and Social Research Council (ESRC) and the Alan Turing Institute (Turing). Together with Professor Karen Yeung and Professor Andrew Howes I lead Responsible AI Network at the University of Birmingham.


I am interested in analysing individual and group decision-making under risk and uncertainty (ambiguity) using laboratory experiments, field experiments and non-experimental data. I study how decision-makers reveal their preferences, learn, co-ordinate and make trade-offs in static and dynamic risk and uncertain (ambiguous) environments  My work aims to develop quantitative models capable of describing and predicting individual and group behaviour in static and dynamic situations in the face of risk and uncertainty (ambiguity). I contribute my expertise as a behavioural scientist/decision theorist to the projects and activities of Birmingham Business School (University of Birmingham), Warwick Manufacturing Group (University of Warwick) as well as collaborating with the Alan Turing Institute on a number of projects. Blending behavioral science, computer science, data analytics, engineering, and business model innovation, I help cities, businesses, charities, and individuals to better understand why they make decisions they make and how they can optimize their behavior to achieve higher profit, better social outcomes, as well as flourish and bolster their well-being. My recent projects focus on smart technological and social systems, cybersecurity, human-computer and human-data interactions and business models.


In the past, I have taught courses in Microeconomic Theory and Econometrics in various universities. In the University of Warwick, I co-teach a course in Experimental Economics at the MSc level and teach a wide variety of master classes in Decision Theory, Behavioural Science, Microeconomics and Decision Theory in the Digital Domain to PhD and EngD students at the Warwick Manufacturing Group. I also supervise MSc and PhD students. In the Fall of 2017 I am teaching an undergraduate module in Game Theory to 3rd year students at the University of Birmingham.


Before joining academia, I worked in private sector in retail (Agrotechkomplex, Ukraine), marketing and distribution (Steelex S.A., Ukraine), and personal finance (American Express Financial Advisors, currently, Ameriprise Financial, US). I also have experience in working in public sector (Council of Europe, France). In my work as a consultant, I offer advice to businesses and policymakers helping them to understand and predict customer choices and to develop strategies for managing risks related to consumer behaviour. Remember, that you can have the best product in the world but one negative review on Facebook or Twitter can completely destroy all your hard work! In recent years, I have established fruitful collaborations with private sector partners as well as municipalities and cities in the UK, EU, and USA. I am fortunate to have expertise in both economics and decision science which allows me to provide valuable help to companies and cities in many real-life projects requiring market assessment and/or in engineering behavioural change.


I am a frequent contributor to Harriet-small

I also wrote ad hoc contributions forhealthandwellbeing

Occasionally, I contribute to thecrunch_data



Economics and Business

Perroni, C., Pogrebna, G., Sandford, S. and K. Scharf (2018) Are Donors Afraid of Core Costs? Economies of Scale and Contestability in Charity Markets, Economic Journal, forthcoming Open Access Coming Soon

Butler, D. and G. Pogrebna (2018) Predictably Intransitive Preferences, Judgement and Decision Making, 13(3), pp. 217-236. Open Access [Link]

Pogrebna, G., Oswald, A., and D. Haig (2018) Female Babies and Risk-aversion: Causal Evidence from Hospital Wards, Journal of Health Economics, 58, pp.10-17. Open Access [Link]

Li, Zh., Loomes, G. & G. Pogrebna (2017) Attitudes to Uncertainty in a Strategic Setting. Economic Journal, 127(601), pp. 809-826 Open Access [Link]

Loomes, G. & Pogrebna, G. (2017). Do Preference Reversals Disappear When We Allow for Probabilistic Choice? Management Science, 63(1), pp. 166-184, Open Access [Link]

Goodall, A. & Pogrebna, G. (2015). Expert Leaders in a Fast-Moving Environment. Leadership Quarterly, 26 (2), pp. 123-142. [Link] will be available here as a part of Green Open Access from December 2016

Ng, I., Scharf, K., Pogrebna, G. & Maull, R. (2015). Contextual Variety, Internet-of-Things and the choice of Tailoring over Platform: Mass Customisation Strategy in Supply Chain Management. International Journal of Production Economics, 159, pp. 76-87. Open Access [Link]

Loomes, G. & Pogrebna, G. (2014). Testing for Independence while Allowing for Probabilistic Choice. Journal of Risk and Uncertainty, 49(3), pp. 189-211. Open Access [Link]

Loomes, G. & Pogrebna, G. (2014). Measuring Individual Risk Attitudes when Preferences Are Imprecise. Economic Journal, 124(576), 569–593. [Link] will be available here as a part of Green Open Access from June 2016. Meanwhile, Working Paper version can be downloaded from here.

Kocher, M., Pogrebna, G. & Sutter, M. (2013). Other-regarding Preferences and Management Styles. Journal of Economic Behavior and Organization, 88, 109-132. [Link]

Pogrebna, G., Krantz, D., Schade, C. & Keser, C. (2011). Words versus Actions as a Means to Influence Cooperation in Social Dilemma Situations. Theory and Decision, 71(4), 473-502. [Link]

Blavatskyy, P. & Pogrebna, G. (2010). Reevaluating Evidence on Myopic Loss Aversion: Aggregate Patterns versus Individual Choices. Theory and Decision, 68(1-2), 159-171. [Link]

Blavatskyy, P. & Pogrebna, G. (2010). Endowment Effects? “Even” with Half-a-Million on the Table! Theory and Decision, 68(1-2), 173-192. [Link]

Blavatskyy, P. & Pogrebna, G. (2010). Models of Stochastic Choice and Decision Theories: Why Both Are Important for Analyzing Decisions. Journal of Applied Econometrics, 25(6), 963-986. [Link]

Pogrebna, G. & Blavatskyy, P. (2009). Coordination, Focal Points and Voting in Strategic Situations: A Natural Experiment. Public Choice, 140(1-2), 125-143. [Link]

Blavatskyy, P. & Pogrebna, G. (2009). Myopic Loss Aversion Revisited. Economics Letters, 104(1), 43-45. [Link]

Blavatskyy, P. & Pogrebna, G. (2008). Risk Aversion When Gains Are Likely and Unlikely: Evidence from a Natural Experiment with Large Stakes. Theory and Decision, 64(2), 395-420. [Link]

Pogrebna, G. (2008). Naive Advice When Half a Million is at Stake. Economics Letters, 98(2), 148-154. [Link]

Science and Engineering


Guo, W., Del Vecchio, M., and G. Pogrebna (2017) Global Network Centrality of University Rankings, Royal Society Open Science, published on October 4, 2017 [Link].

Guo, W., Gupta, N., Pogrebna, G., and Jarvis, S. A. (2016) Understanding Happiness in Cities using Twitter: Jobs, Children, and Transport, Proceedings of the IEEE International Smart Cities Conference, London, UK, 29-30 November, 2016 [Link]

Al Shami, A., Guo, W., & Pogrebna, G. (2016) Fuzzy Partition Technique for Clustering Big Urban Dataset, Proceedings of the IEEE Technically Sponsored SAI Computing Conference, London, UK, 13-15 July, 2016 [Link]

Al Shami, A., Guo, W., & Pogrebna, G. (2015) Clustering Big Urban Data Sets, Proceedings of the IEEE International Smart Cities Conference, Guadalajara, Mexico, Mexico, 25-28 Oct 2015 [Link]

Pogrebna, G. (2015) Servitization through Human-data Interaction: a Behavioural Approach, Proceedings of the Spring Servitization Conference, Birmingham, UK, 18-19 May 2015 [Link]



Parry, G., Pogrebna, G. and Vendrell-Herrero, F. (2017) Windowing television content: Lessons for digital business models. Strategic Change: Briefings in Entrepreneurial Finance, 27(2), pp.151-160.



Pogrebna, G. (2018) Introduction: The FUR 2016 Conference. Theory and Decision, 84(3), pp. 305-309.

Research Highlight of the Month

In this section I post an abstract from a recent project which I am particularly excited about. This month it is:


The Data Science of Hollywood: Using Emotional Arcs of Movies to Drive Business Model Innovation in Entertainment Industries


Much of business literature addresses the issues of consumer-centric design: how can businesses design customized services and products which accurately reflect consumer preferences? This paper uses data science natural language processing methodology to explore whether and to what extent emotions shape consumer preferences for media and entertainment content. Using a unique filtered dataset of 6,174 movie scripts, we generate a mapping of screen content to capture the emotional trajectory of each motion picture. We then combine the obtained mappings into clusters which represent groupings of consumer emotional journeys. These clusters are used to predict overall success parameters of the movies including box office revenues, viewer satisfaction levels (captured by IMDb ratings), awards, as well as the number of viewers’ and critics’ reviews. We find that like books all movie stories are dominated by 6 basic shapes. The highest box offices are associated with the Man in a Hole shape which is characterized by an emotional fall followed by an emotional rise. This shape results in financially successful movies irrespective of genre and production budget. Yet, Man in a Hole succeeds not because it produces most “liked” movies but because it generates most “talked about” movies. Interestingly, a carefully chosen combination of production budget and genre may produce a financially successful movie with any emotional shape. Implications of this analysis for generating on-demand content and for driving business model innovation in entertainment industries are discussed.

Keywords: sentiment analysis, consumer-centric design, entertainment, emotions, data science of movies, data science of Hollywood


My Teaching Philosophy


A few years ago I was at a conference at one of the Spanish universities in Barcelona. At that time, Spain had its own system of teaching in higher education and has just announced plans to reform this system to mimic the European teaching system universally applied in other countries of the Schengen zone. Spanish students protested against the change and I will never forget the drawing I saw created by the protesters. It depicted a “de-personalisation” machine which showed different, vibrant and imaginative people going in and grey, gloomy and uncharacteristic people coming out. This was the moment when I realised that preserving individual way of thinking is very important in any learning experience. Therefore, I believe that teaching should take into account individual differences of students and try to structure my lectures and seminars keeping in mind that students will have different levels of experience with my subject as well as different levels of interest in the subject.

Learning new things should be fun. It should not only be valuable but also engaging. I have taught at both undergraduate and postgraduate levels in small and large groups and think that learning process is a process of exchange where students receive information about the subject and communicate with the lecturer to create new knowledge. For example, a lot of great research questions asked in science came out of lectures from the intellectual exchange between professor and students. A successful learning situation is therefore a process in which learning happens on both ends. Surely, the lecturer should bring more information to the classroom but unless both sides are engaged and trying to educate each other the learning process will fail.

What would I like to achieve as a result of the learning process is that my students should have a good conceptual understanding of the classroom material. My father used to explain to me why education is important. He told me that an educated person is a person who can take any book (a book on any subject) off the bookshelf and make sense of it. This is what I expect from my students. Being able to think logically and critically evaluate the concepts which we discuss in class are key skills which I would like them to gain. That way, even if they do not know the answer to a particular question, they can derive the answer logically because they have confidence in their ability, conceptual knowledge and they are not afraid to try.

I would like to encourage the students to think about theoretical concepts and to be able to evaluate them critically. I would also like them to take their knowledge from my course and transfer this knowledge into their daily lives as well as to other subjects. To promote critical thinking, my seminars are structured as open discussions which are particularly beneficial especially in small groups. The questions I ask often do not have unique correct answers but students are encouraged to show their knowledge of concepts and literature as well as develop argumentation skills to be able to prove their point.

Selected Teaching Materials


Experimental Economics EC984-2013

Click here to access EC984-2013 materials (password-protected).

Experimental Economics EC984-2014

Click here to access EC984-2014 materials (password-protected).

Experimental Economics EC984-2015

Click here to access EC984-2015 materials (password-protected).

Experimental Economics EC984-2016

Click here to access EC984-2016 materials (password-protected).

Experimental Economics EC984-2018

Click here to access EC984-2018 materials (password-protected).

Game Theory ECON321A - Year 2017-2018: Winner of the Digital Innovation Prize 2018

Click here to watch student Game Theory videos produced this year for Assessment 2.

Game Theory ECON321A - Year 2018-2019

Click here to access materials.