New Economic Models in the Digital Economy – Big Data, Innovations and New Business Models
Decision-making is the essence of management. Mammoth amounts of data are being generated through society's interactions with technology, documenting stages of collective human decision making on a scale previously impossible to achieve. Such digital traces of individuals create new scientific and commercial opportunities in the digital economy. The goal of this £697K grant is to explore the opportunities that massive online information streams may offer to gain insight into early stages of collective decision-making. Members of the Behavioural Science GRP funded by this grant include Tobias Preis, Suzy Moat and Nick Chater.
Funded by EPSRC
Risk, Time and Society: The Behavioural Economics of Value
The Leverhulme Trust Award has been granted to a team of economists and psychologists in the Behavioural Science group of WBS and in the Department of Psychology to undertake a programme of work to understand how humans arrive at valuations of goods and services in the present and in the future. There are three principal areas of research:
- How people evaluate alternatives involving risk and uncertainty.
- How people make trade-offs between present and future.
- How individuals' attitudes to time and risk and other social objectives feed into social policy.
Leverhulme Trust Research Programme Award
Cognitive and Social Foundations of Rationality
Rationality focuses on perhaps the key fault-line in the social and cognitive sciences. Many theorists, in philosophy, economics, artificial intelligence and cognitive science explain mind, behaviour, and their consequences for social phenomena, by rational explanation. Others, in judgment and decision making, social psychology, behavioural economics and the neurosciences, argue that people systematically violate rational principles, typically focusing on the influence of mechanistic, not rational, constraints on thought. This project aims to establish how, and to what extent, these viewpoints interact and how far they can be reconciled, by mathematical, computational, and experimental methods. This research programme will have fundamental implications both for scientific and normative questions. It will clarify the interplay of rational and mechanistic explanation of inference, learning, decision making, communication, and social phenomena; and will explore the cognitive underpinnings of our conflicting normative intuitions, helping to inform normative questions in ethics and political philosophy.
Funded by an ERC Advanced Investigator Grant
Bad luck or bad management: how system effects moderate inferences about executive ability
Failure and disaster are often blamed on the people in charge. Organizational researchers have argued that such practice of blaming individuals is often misplaced because the fundamental causes of failures are often tightly coupled systems which make organizations sensitive to rare external shocks. In this project we use a formal model to evaluate this claim and examine how inferences about skill depend on system design. We show that very poor performance in tightly coupled systems is relatively uninformative about individual skill and that moderately low performance can be a more reliable indicator of low skill. Data from Formula One Racing supports this prediction: cars with extremely poor performance do not have the lowest expected quality. Experiments show that participants can learn the non-monotonic association between performance and skill in our model, but they do not act upon this knowledge when making hiring or firing decisions, implying that learning is perhaps not enough to help resist the temptation of firing unlucky executives.