Decision supporting functionality in a virtual enterprise network

Enterprises are now facing growing global competition and the continual suc cess in the marketplace depends very much on how efficient and effective th e companies are able to respond to customer demands. The Internet has provi ded a powerful tool to link up manufacturers, suppliers and consumers to fa cilitate the bi-directional interchange of useful information. The formatio n of virtual enterprise network is gathering momentum to meet this challeng e. The idea of virtual enterprise network is meant to establish a dynamic o rganization by the synergetic combination of dissimilar companies with diff erent core competencies, thereby forming a "best of everything" consortium to perform a given business project to achieve maximum degree of customer s atisfaction. In this emerging business model of virtual enterprise network, the decision support functionality, which addresses the issues such as sel ection of business partners, coordination in the distribution of production processes and the prediction of production problems, is an important domai n to be studied. This paper attempts to introduce a Neural On-Line Analytic al Processing System (NOLAPS), which is able to contribute to the creation of decision support functionality in a virtual enterprise network. NOLAPS i s equipped with two main technologies for achieving various objectives, inc luding neural network for extrapolating probable outcomes based on availabl e pattern of events and data mining for converting complex data into useful corporate information. A case example is also covered to validate the feas ibility of the adoption of NOLAPS in real industrial situations. (C) 2000 E lsevier Science Ltd. All rights reserved.