The concept of stochastic dominance is described and its use is illustrated in relation to the evaluation of the output of a systems simulation model of lucerne haymaking in south-west Spain. Two alternative machinery systems are ranked for various lucerne areas using the criteria of stochastic...

Evaluating the risk of a particular decision depends on the risk aversion of the decision maker related to the underlying utility function. The objective of this paper is to use stochastic efficiency with respect to a function (SERF) to compare the ranking of risky alternatives using alternative...

Often analysts must conduct risk analysis based on a small number of observations. This paper describes and illustrates the use of a kernel density estimation procedure to smooth out irregularities in such a sparse data set for simulating univariate and multivariate probability distributions.

To concentrate on treating the most serious risks, methods of business risk management usually seek to identify the main risks and to assess their relative importance. Risks are typically assessed in terms of their chances of occurrence and the severity of their consequences. The assessments may...

Decision analysis, the practice of Bernoullian decision theory and Bayesian statistics, is reviewed in relation to its application in management. Aspects of the scaling of beliefs (probabilities) and preferences (utilities) are discussed, focussing on practical problems. It is concluded that the...

A version of multiattribute utility theory is evaluated as an aid to social decision making using an Australian case study. A multiattribute utility function is assessed over the descriptive, discrete decision alternatives of the decision problem rather than over the risky consequences of the...

Bugs are an unavoidable aspect of mathematical programming (MP) modelling. In this paper we discuss the prevention and diagnosis of bugs in MP models. The topic is rarely addressed in the literature but is crucial to the success of modelling projects, especially for large models. We argue that...

Simulation models are valuable tools in the analysis of complex, highly constrained economic systems unsuitable for solution by mathematical programming. However, model size may hamper the efforts of practitioners to efficiently identify the most valuable configurations. This paper investigates...