During the last decade, neural networks have established themselves as a theoretically sound alternative to traditional statistical models, and a large body of research on their application to business has been produced. The comprehensive range of business and financial applications is such that a focus is required for an in-depth analysis, therefore this review addresses applications related to management, marketing and decision making. Also, given that previous reviews have dealt with earlier publications, the time span of the review is limited to the period 1992-1998. The presentation is centred on summary tables with links between them. These tables classify the studies according to their application areas, the main contributions rendered by the use of neural networks, and the alleged advantages and disadvantages of this, as well as the journal of publication. Further information on the neural network models, other statistical methods against which they have been compared, and features of the analysed data are also provided. The more controversial issues concerning real-world applications of neural networks are discussed as a part of a critical analysis. Many of the studies are shown to be first attempts to apply these new techniques to established areas of research, whereas only a few tackle real-world cases. Although still regarded as a novel methodology, neural networks are shown to have matured to the point of offering real practical benefits in many of their applications.