SUCCESS IN DECISION MAKING: DIFFERENT ORGANIZATIONS, DIFFERING REASONS FOR SUCCESS

In an attempt to elucidate some possible conditions for success in managerial decision making, data were analysed from 53 cases of decisions in eight British organizations, five business firms and three non-business organizations (two universities and a District of the National Health Service). No clear relationships between features of the processes of making the decisions, and their successfulness were found until the business firms and the non-business organizations were separated. Clear differences then showed up, relatively speaking, in the conditions conductive to success. In the business firms, a successful decision was more likely to result from a decision-making process in which resources were available. In other words, in business a successful decision is most likely when sufficient information and sufficient means of implementation are to hand. By contrast, in the universities and the Health District, a successful decision was associated more with the social qualities of the decision-making process itself. In other words, in non-business organizations a successful decision is most likely when the right people participate and the people at the very top do not interfere too much.     

Structural Changes in the Duration of Bull Markets and Business Cycle Dynamics

Asia-Pacific Financial Markets - This paper tests for structural changes in the duration of bull regimes in 18 developed and emerging economies’ adjusted market capitalization stock indexes,...     

On utility maximization under model uncertainty in discrete‐time markets

We study the problem of maximizing terminal utility for an agent facing model uncertainty, in a frictionless discrete‐time market with one safe asset and finitely many risky assets. We show that an optimal investment strategy exists if the utility function, defined either on the positive real line or on the whole real line, is bounded from above. We further find that the boundedness assumption can be dropped, provided that we impose suitable integrability conditions, related to some strengthened form of no‐arbitrage. These results are obtained in an alternative framework for model uncertainty, where all possible dynamics of the stock prices are represented by a collection of stochastic processes on the same filtered probability space, rather than by a family of probability measures.