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We select a menu of seven popular decision theories and embed each theory in five models of stochastic choice, including tremble, Fechner and random utility model. We find that the estimated parameters of decision theories differ significantly when theories are combined with different models. Depending on the selected model of stochastic choice we obtain different rankings of decision theories with regard to their goodness of fit to the data. The fit of all analyzed decision theories improves significantly when they are embedded in a Fechner model of heteroscedastic truncated errors or a random utility model. Copyright © 2009 John Wiley & Sons, Ltd.

The Service Systems research group at WMG works in collaboration with large organisations such as GlaxoSmithKline, Rolls-Royce, BAE Systems, IBM, Ministry of Defence as well as with SMEs researching into value constellations, new business models and value-creating service systems of people, product, service and technology.The group conducts research that is capable of solving real problems in practice (ie. how and what do do), while also understanding theoretical abstractions from research (ie. why) so that the knowledge results in high-level publications necessary for its transfer across sector and industry. This approach ensures that the knowledge we create is relevant, impactful and grounded in research.In particular, we pursue the knowledge of service systems for value co-creation that is replicable, scalable and transferable so that we can address some of the most difficult challenges faced by businesses, markets and society. Research StreamsThe WMG Service Systems research group conducts research that is capable of solving real problems in practice, and also to create theoretical abstractions from or research that is relevant and applicable across sector and industry, so that the impact of our research is substantial.The group currently conducts research under six broad themes: AbstractThis study explores the effects of leaders in an iconic, high-technology, turbulent industry. We analyse 62 years of objective performance data from one of the world's most competitive sectors (Formula One competition). The study's findings provide strong support for an 'expert leader hypothesis'. The most successful leaders are disproportionately those who started as drivers or mechanics (not as general managers or university graduates in engineering). Moreover, within the sub-sample of former drivers, it is those who had the longest driving careers who went on to become the most effective leaders. Remarkably, the leader's former experience as a competitive driver is a better predictor of current organizational performance than the driving experience of the person who is actually driving for the team. The study's expert-leader findings are consistent with the hypothesis that longitudinal performance improves when a leader's knowledge and expertise correlate with an organization's core business activity.