Enterprises are now facing growing global competition and the continual success in the marketplace depends very much on how efficient and effective the companies are able to respond to customer demands. The Internet has provided a powerful tool to link up manufacturers, suppliers and consumers to facilitate the bi-directional interchange of useful information. The formation of virtual enterprise network is gathering momentum to meet this challenge. The idea of virtual enterprise network is meant to establish a dynamic organization by the synergetic combination of dissimilar companies with different core competencies, thereby forming a `best of everything' consortium to perform a given business project to achieve maximum degree of customer satisfaction. In this emerging business model of virtual enterprise network, the decision support functionality, which addresses the issues such as selection of business partners, coordination in the distribution of production processes and the prediction of production problems, is an important domain to be studied. This paper attempts to introduce a Neural On-Line Analytical Processing System (NOLAPS), which is able to contribute to the creation of decision support functionality in a virtual enterprise network. NOLAPS is equipped with two main technologies for achieving various objectives, including neural network for extrapolating probable outcomes based on available pattern of events and data mining for converting complex data into useful corporate information. A case example is also covered to validate the feasibility of the adoption of NOLAPS in real industrial situations.