Mehri Chehrehpak - Faculty of Management and Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran
Alireza Alizadeh - Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran

It is of great importance to identify critical success factors (CSFs) of projects. Many of researchers have attempted to identify, categorize and prioritize these factors. It is notable that CSFs of different organizations under various conditions are different from other organizations. This paper identifies success factors of Iranian construction projects using artificial intelligence and rough sets theory. The major advantages of artificial intelligence can be extraction of success factors using data from projects carried out by these techniques. This leads to active identification of project CSFs over time under changing conditions. In this paper, we survey among 07 parameters related to construction projects and three functional measures including time, cost and project quality, to identify this factors. Using Rough set theory and expert judgment, success factors of Iranian construction project were identified and classified by test series based on t-test. According to results, the CSFs related to Iranian construction projects included are "on-time financing by employee", "an updated schedule", "commitment of employees to the schedule" and "preliminary studies and detailed designs by the employer and consultant team". The present study used elite knowledge of project experts

Critical success factors, construction projects, business intelligence, rough sets theory, t-test