Utopia and its Discontents: Dreams of Catastrophe and the End of 'the End of History'

The institutionalization of Utopia Studies in the last decade is premised upon a specifically aesthetic reception of Ernst Bloch’s theory of the “utopian impulse” during the 1980s and 1990s. A postmodern uneasiness to both left and right formulations of the "End of History" during this period imposes a resistance to concepts of historical and political closure or totality, resulting in a "Utopianism without Utopia". For all the attractiveness of this pan-utopianism, its failure to consider the relation between historical representation and fulfillment renders it consummate with liberalism as a merely inverted conservatism. In contrast to this specific recuperation of a Bloch, the continuing importance of Walter Benjamin’s theory of the dialectical image and the speculative concept of historical experience which underlies it becomes apparent. The intrusion of the historical Absolute is coded throughout Benjamin’s thought as the eruptive and mortuary figure of catastrophe, which stands as the dialectical counterpart to the utopian wish images of the collective dream. Indeed, the motto under which the Arcades Project was to be constructed derives from Adorno: “Each epoch dreams of itself as annihilated by catastrophe”.

Understanding what drives the purchase decision in pension and investment products

The aims of this paper are to first seek an understanding of consumer decision-making when purchasing pension and investment products, and second to ascertain how this decision-making affects the consumer's choice of distribution route. The study employed both focus groups and postal questionnaire survey methods based on the framework of a classical decision-making model that investigated problem recognition, information search, evaluation tools used and post-purchase. The findings show that the decision-making process experience differed to a lesser or greater degree depending on the distribution route. The majority of respondents had recognised the need to make a purchase decision long before seeking information. Younger respondents on all incomes believed that they must make some pension provision for themselves as opposed to relying on the government's retirement provision. Many changed channels for information searches, but tended to settle with the Independent Financial Adviser (IFA). The two main evaluation tools for pension and investment were found to be the ‘charges’ and ‘historic fund performance’. The vast majority of respondents reiterated their worry that the outcomes would not be known until retirement. In terms of analysis by the level of ‘financial literacy’, respondents who scored in the upper quartile were more inclined to be on a higher income, less inclined to evaluate on charges and more proactive in discussing the investment strategy of their pension fund. Respondents who scored in the lower quartile had opposite results. One of the implications of these findings is that the younger respondents’ recognition of pension savings favours the government's intention to reverse the existing balance of pension distribution. The other main implication is that the findings will be of help to managers in appreciating the dominance of the IFA channel by providing an explanation of why consumers choose this route, and, additionally, can assist direct marketing managers in identifying customers who will be more likely to use multichannel or single-channel shoppers. It can also help the marketing manager increase the usage of different channels by addressing the factors driving the purchase decision and distribution choice.

A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Coping with an ageing population is a major concern for healthcare organisations around the world. The average cost of hospital care is higher than social care for older and terminally ill patients. Moreover, the average cost of social care increases with the age of the patient. Therefore, it is important to make efficient and fair capacity planning which also incorporates patient centred outcomes. Predictive models can provide predictions which their accuracy can be understood and quantified. Predictive modelling can help patients and carers to get the appropriate support services, and allow clinical decision-makers to improve care quality and reduce the cost of inappropriate hospital and Accident and Emergency admissions. The aim of this study is to provide a review of modelling techniques and frameworks for predictive risk modelling of patients in hospital, based on routinely collected data such as the Hospital Episode Statistics database. A number of sub-problems can be considered such as Length-of-Stay and End-of-Life predictive modelling. The methodologies in the literature are mainly focused on addressing the problems using regression methods and Markov models, and the majority lack generalisability. In some cases, the robustness, accuracy and re-usability of predictive risk models have been shown to be improved using Machine Learning methods. Dynamic Bayesian Network techniques can represent complex correlations models and include small probabilities into the solution. The main focus of this study is to provide a review of major time-varying Dynamic Bayesian Network techniques with applications in healthcare predictive risk modelling.