Abstract
Artificial societies are computer models in which the collective behavior of a population of simulated human decision makers is observed over time. Here we describe an artificial society of “soft computing agents” (model consumers) making probabilistic purchasing decisions about new technological products that are introduced by competing firms. The model is studied under varying conditions to determine the relative success of these firms as they pursue different pricing strategies designed to increase their market share. We find that a critical factor in determining the success of different pricing strategies is the utility that an individual consumer gains from other consumers adopting the same technology. Further, financial success is uncoupled from market share under some conditions, so (for example) while an inferior technology may gain substantial market share by aggressive price-cutting, it is unlikely to gain financial rewards. These results add to growing evidence that artificial society models may prove useful in improving our understanding of collective decision making in complex sociological, economic and business management situations.
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Frels, J.K., Heisler, D., Reggia, J.A. (2008). Predicting the Effects of Alternative Pricing Strategies in an Artificial Society Undergoing Technology Adoption. In: Prasad, B. (eds) Soft Computing Applications in Business. Studies in Fuzziness and Soft Computing, vol 230. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79005-1_3
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DOI: https://doi.org/10.1007/978-3-540-79005-1_3
Publisher Name: Springer, Berlin, Heidelberg
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