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ERP implementation projects have received enormous attention in the last years, due to their importance for organisations, as well as the costs and risks involved. The estimation of effort and costs associated with new projects therefore is an important topic. Unfortunately, there is still a lack of models that can cope with the special characteristics of these projects. As the main focus lies in adapting and customising a complex system, and even changing the organisation, traditional models like COCOMO can not easily be applied. In this article, we will apply effort estimation based on social choice in this context. Social choice deals with aggregating the preferences of a number of voters into a collective preference, and we will apply this idea by substituting the voters by project attributes. Therefore, instead of supplying numeric values for various project attributes, a new project only needs to be placed into rankings per attribute, necessitating only ordinal values, and the resulting aggregate ranking can be used to derive an estimation. We will describe the estimation process using a data set of 39 projects, and compare the results to other approaches proposed in the literature.

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Human economic decisions are characterized by a number of factors which make them difficult to model with standard mathematical tools. Decisions can be more easily described by a set of rules, and some of them may be "rules of thumb". Economic behavior is adaptive, in that people are able to adjust to a changing environment. It is argued in this paper that the classifier system framework is a suitable means of modeling human economic decisions. A case of a simple economic decision of finding an optimal price is discussed, which is later made more complex by introducing an input variable that effects the optimal price. It is shown that classifier systems can be used in both tasks, and their performance is compared to human decisions in the same set of circumstances.

APL has a long tradition as a language for the notation of computer architectures that dates back to its use as notation of the IBM 360 system. Its powerful primitives and compactness make it an ideal tool for simulating hardware functions in order to gain insights into the functionality, the performance and the programming issues of an algorithm without the need to undergo the painstaking process of actually building the target machine and implementing the program on it. We have developed an APL2 software simulator for Non-Von Neumann computers. The basic data structure of the system is an array whose elements model a number of RAl\is containing control registers, data and program code. The user can "define" his/her machine by specifying the communication network and communication primitives, the instruction set and its semantics, and the complexity measure. We demonstrate the use of the program system for studying various schemes for adaptive load sharing on multicomputers.

Traditional economic theory sees human economic decisions as rational choices of action to achieve maximum utility. However, economic reality shows that people often behave in ways different from that ideal: actions are not always determined rationally; often they are influenced by other factors, such as chance and tradition. In order to describe the behaviour of economic agents in the real world, we take irrationality and adaptation into account: we present work in progress on a market simulation that shows the effects of partly irrational and adaptive consumer buying decisions on the course of action of entrepreneurs.