Quantitative Models of Learning Organizations

In a rapidly changing economical environment, quick adaptation is one of the crucial tasks for modern management and permanent learning is a key-factor in the struggle for successfully coping with this challenge. The learning process itself is based not only upon the information gathered on the market, but also upon the totality of knowledge within the company. This book develops a theory of a firm that is based on these principles rather than on optimization and classical equilibrium. It uses quantitative models to describe adaptive firm behavior, the various types of learning as well as various domains of application (organization of new production development, adoption of business models, market entry etc.). It gives an introduction to the various mathematical models of learning and to the applications to problems in microeconomics as well as in business administration. The reader can expect a comprehensive introduction to the subject, its significance for economic theory and managerial practice.

Organizational Learning - Foundations and Significance (A. Taudes): Microeconomics and Business Strategy; The Learning Firm.- Genetics-based machine learning applications to product placement (T. Fent): Genetic-based machine learning; Product Placement.- Ant based computation in the Management Sciences (H. Dawid/K. Doerner/ R. Hartl/M. Reimann): Ant Systems to solve operational problems; Ant based approaches to strategy.- Neural Network and Game Theory Applications to New Product Development (G. Dorffner/M. Feurstein/A. Mild/M. Natter/A. Taudes): Neural Networks in Agent-Based Economic Modeling; Organizing Learning and Product / Process Development

* a comprehensive introduction to both theory and application of mathematical models on organizational learning, strategy and innovation * international wellknown researchers