A Generic Framework Based on Machine Learning Techniques for Virtual Organization Management

Abstract

The management of Virtual Organization (VO) brings some challenges. One of them is the appropriate and effective coordination and monitoring of distributed businesses processes. It is not easy or trivial to handle the enormous amount of information about and from VOs members. As a direct consequence, decisions are crucial and should be taken not only with agility, but also with intelligence. This paper introduces a framework to support an integrated decision-making environment through which managers will be able to take assisted and smarter decisions. The key element of this framework is the